Assessing Agrobiodiversity: A Compendium of Methods has been prepared by Dunja Mijatović and Toby Hodgkin with contributions from Lukáš Pawera, Stella Beghini, Gennifer Meldrum, Mattia Manica, Barbara Smith, Devra Jarvis, Sajal Sthapit, Roba Bulga Jilo, Stanley Zira, Yasuyuki Morimoto, Patrick Maundu and assistance from (in alphabetical or- der): Alberto Tarraza Rodríguez, Alejandro González Álvarez, Annelie Bernhart, Epsha Palikhey, Ghanimat Azhdari, Helga Gruberg Cazón, Lal Kumara Wakkumbure, Maede Salimi, Mehdi Esmaeili, Natalia Estrada-Carmona, Reuben Mendakor Shabong and Sonthana Maneerattanachaiyong. Citation PAR (2018) Assessing Agrobiodiversity: A Compendium of Methods (Platform for Agrobiodiversity Research, Rome). Cover photo Jhum rice fields in Arunachal Pradesh, India. Photo courtesy of Somnath Roy. Platform for Agrobiodiversity Research 2018 PARPlatform for agrobıodıversıty research The Platform for Agrobiodiversity Research (PAR) is an independent nongovernmental orga- nization that seeks to contribute to the conservation and sustainable use of agrobiodiversity by supporting the development and dissemination of relevant knowledge. www.agrobiodiversityplatform.org ACKNOWLEDGEMENTS The authors are grateful to the many local communities around the world who have had the patience and interest to participate in the research processes described here and share their wisdom, and to our colleagues and friends who have developed, tested, improved and shared the methods with us. Thanks also to those who provided the examples used in the text including: Stefano Padulosi, Bioversity International, Italy; Oliver King, M.S. Swaminathan Research Foundation, India; Jean Teo Gien Kheng, Department of Agriculture Sarawak, Malaysia; Amadou Sidibe, Institut d’Economie Rurale, Mali; Wilfredo Rojas, PROINPA, Bolivia; Suman Sahai, Gene Campaign, India; Sumilia, Swisscontact/Andalas University, Indonesia; and Soumik Chatterjee, Centre for Pollination Studies, Calcutta University, India. Special thanks to Ilse Köhler-Rollefson from the League for Pastoral Peoples, India. We thank The Christensen Fund and Bioversity International for financial support and help with the resources needed, Loredana Maria for continuing administrative support and Paul Neate for editorial work. We also thank Jean-Louis Pham, Eliot Gee, Devon Sampson, Eylem Ertürk and Erkut Ertürk for valuable suggestions on the text. We thank Güneş Akçay for graphic design and Francesco Pasta for illustrations. Special thanks to Paola Viesi for photos in Section 10 and Somnath Roy for the cover photo. We al- so wish to acknowledge our colleagues and friends who contributed photographs includ- ing Barbara Vinceti, Gaia Gullotta, Devon Sampson, Janaka Prasad, Pushan Chakraborty and DEDICATION Paul Bordoni. The Compendium is dedicated to the memory of our dear friend, colleague and mentor, Assessing Agrobiodiversity: A Compendium of Methods has been developed with Dr Bhuwon Sthapit, who passed away in August 2017 and whose ideas, like seeds, are the support of The Christensen Fund, and in partnership with Bioversity International, planted in our work. Rome; Centre for Sustainable Development (CENESTA), Iran; Instituto de Investigaciones en Agricultura Tropical (INIFAT), Cuba; Local Initiatives for Biodiversity, Research and Development (LI-BIRD), Nepal; North East Slow Food & Agrobiodiversity Society (NESFAS), India; Pgakenyaw Association for Sustainable Development (PASD), Thailand; Southern Alliance for Indigenous Resources (SAFIRE), Zimbabwe; Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Czech Republic; Centre for Agroecology, Water and Resilience, Coventry University, UK; and Centre for Pollination Studies, Calcutta University, India. TABLE OF CONTENTS Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 9 . Uses of Wild Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 9 .1 Collection of Data on the Use of Wild Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 1 . About Agrobiodiversity Research . . . . . . . . . . . . . . . . . . . . 3 9 .2 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 1 .1 What is Agrobiodiversity? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1 .2 The Contribution of Agrobiodiversity Research . . . . . . . . . . . . . . . . . . . . . . . . 5 10 . Diversity of Domestic Animals and Breeds . . . . . . . . . 54 1 .3 The Research Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 10 .1 Questionnaire for Key Informant Interviews or Focus Groups Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 2 . Overview of Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . 8 10 .2 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 2 .1 Diversity of What? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 .2 Local Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 11 . Pollinator Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 2 .3 Data Gathering Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 11 .1 Field Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 2 .4 Agrobiodiversity Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 11 .2 Community Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 2 .5 Sampling Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 12 . Landscape Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3 . Transect Walks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 12 .1 Conducting Participatory Landscape Mapping . . . . . . . . . . . . . . . . . . . . . . . 68 12 .2 Converting Drawn Maps into Digital Format . . . . . . . . . . . . . . . . . . . . . . . . . 70 4 . Seasonal Calendars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 13 . Resilience Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5 . Household Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 5 .1 Conducting the Household Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 14 . Richness, Evenness and Divergence for Crop Species and Varieties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 5 .2 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 6 . Four Cell Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 15 . Data Organization and Analysis . . . . . . . . . . . . . . . . . . . . . 81 15 .1 Organizing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6 .1 Conducting a Four Cell Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 15 .2 Good Practice for Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6 .2 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 15 .3 Exploratory Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 7 . Characterizing Crops and Crop Varieties . . . . . . . . . . . . 37 15 .4 Checking Assumptions for Statistical Testing . . . . . . . . . . . . . . . . . . . . . . . . 83 15 .5 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 8 . Seed Sources and Seed Networks . . . . . . . . . . . . . . . . . . . 41 8 .1 Conducting a Survey of Seed Supply Practices . . . . . . . . . . . . . . . . . . . . . . . . 42 8 .2 Describing Local Seed Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 8 .3 Focus Group Discussion on Seed Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 INTRODUCTION Sorghum varieties, Kenya. Photo: Bioversity International/Y. Morimoto 2 INTRODUCTION THE COMPENDIUM Agrobiodiversity is the diversity of crop Drawing on experiences from projects The first steps in agrobiodiversity research variety diversity in a farming community. This species and varieties, livestock species and around the world, this Compendium has been include assessing the diversity present in an is followed by sections 7 and 8 on obtaining in- breeds, wild plants, pollinators, soil biota and prepared by the Platform for Agrobiodiversity area and understanding its management and formation on crop and variety traits, uses and other aquatic and terrestrial organisms that Research (PAR) to support the documentation, use. The Compendium provides guidelines values, and seed systems. make agricultural and food production possi- co-creation and sharing of knowledge about for the collection and analysis of information Section 9 explains methods for collect- ble. Meeting the challenges of climate change, agrobiodiversity and its management. The about the diversity of crops, livestock, pollina- ing information about the use of wild plants. improving nutrition and health, and achiev- Compendium seeks to encourage and support tors and harvested wild plants. The methods Section 10 describes the process of obtaining ing a transformation towards more sustain- collaborative research that aims to help local described have all been used and documented information on animal and breed diversity and able and equitable production systems will all communities to: with communities around the world in land- on the socioeconomic factors that are import- require the restoration of agrobiodiversity and • Maintain and recover local crops, varieties scapes with diverse environmental and cul- ant to their maintenance and use. Section 11 its improved conservation. and breeds tural features. These methods can be adapt- presents two methods for assessing pollinator ed to specific research contexts and com- The growing interest in supporting agro- • Revive practices and knowledge associated diversity. bined with many methods not covered in the ecological ways of farming has created new op- with agrobiodiversity Compendium. Section 12 describes ways of finding out portunities to explore diversity-rich approach- • Diversify fields, farms and landscapes about the distribution of diversity and areas es with small-scale farmers, pastoralists, for- Section 1 describes some general principles of importance for ecosystem services through est dwellers, urban gardeners and other com- • Protect and restore ecosystems. of agrobiodiversity research, including the ap- participatory mapping and Section 13 covers munities. There is a great need to support proaches to be adopted and the ways in which community-based assessment of social-eco- these communities in their efforts to revive or the results can be used. Section 2 provides an logical resilience. Section 14 explains how to maintain diversity and associated knowledge overview of methods used in agrobiodiversity calculate richness, evenness and divergence and practices. assessments together with some suggestions for crops or crop varieties. Section 15 deals on how to obtain the data needed. In areas rich in agrobiodiversity, knowledge with some general aspects of data analysis. sharing and innovations arise through daily Sections 3 and 4 describe two of the key ini- This is the first version of the Compendium observation, experimentation and exchange. tial tools, transect walks and seasonal calen- and PAR plans to add further sections to fu- Both diversity and management practices are dars, respectively, as these are usually some ture versions, e.g. on assessing soil biodiver- continuously changing and result in adaptive of the first activities carried out with the sity. Your comments and suggestions for ways biocultural systems that emerge through an community. of improving the Compendium would be most interplay between people and their environ- Section 5 presents methods for carrying welcome and should be sent to ments. Such areas, where diversity and asso- out household surveys. Section 6 describes the platformcoordinator@agrobiodiversityplatform.org ciated knowledge exist in dynamic forms, can ‘four cell analysis’ approach for assessing the benefit from scientific recognition and sup- abundance and distribution of local crop and port. In the same way, science has much to learn from the communities who maintain diversity. Woman holding gourd bowls with white and purple hibiscus flowers, Boumboro village, Mali. Photo: D. Mijatović 1. ABOUT AGROBIODIVERSITY RESEARCH Offerings to the spirits at the beginning of rice harvest in San Din Daeng Karen community, Thailand. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 4 1. ABOUT AGROBIODIVERSITY RESEARCH 1.1 WHAT IS AGROBIODIVERSITY? Since the beginning of agriculture more than 10,000 years ago, hundreds of thousands of crop Crops and animals depend on countless or- varieties and thousands of livestock breeds have been created through human and ecosystem ganisms above and below ground that inter- interaction. These varieties and breeds are adapted to specific ecologies, climates and human act with each other in a complex web of eco- ot needs, and they continue to evolve in unique environments and management systems. logical activities. Ecological processes that re- Ph sult from the interactions among species and between species and the environment provide AGROBIODIVERSITY includes all the variety and variability of animals, plants and microorgan- a continuous flow of essential ecosystem ser- isms that are used directly or indirectly for food and agriculture, including crops, livestock, trees and vices, including soil fertility maintenance, soil fish. Created and managed by farmers, pastoralists, fishers and forest dwellers, it comprises the di- erosion control, pest and disease regulation versity of genetic resources (varieties, breeds) and species used for food, fodder, fibre, fuel and med- and pollination. icine. Agrobiodiversity also includes the diversity of non-harvested species that support production (soil microorganisms, predators, pollinators) and those in the wider environment that support agro- • Thousands of species of plants and ecosystems (agricultural, pastoral, forest and aquatic) as well as the diversity of the agroecosystems mushrooms have been cultivated or (FAO and PAR 2011). harvested. to: F Pho • Countless varieties of cultivated species have been developed through adaptation to diverse natural and cultural environments. • Thirty-eight species of animals and around 8,000 distinct breeds of livestock have been domesticated and bred by pastoralists and other livestock keepers. ho • More than 20,000 species of wild bees and P many species of butterflies, flies, moths, wasps, beetles, birds, bats and other animals contribute to the pollination of plants, many of which are food to people and animals. • Millions of organisms, including verte- brate animals, earthworms, nematodes, insects, fungi and bacteria, are found in healthy soil. Pho Common bean (Phaseolus vulgaris), Cuba. Photo: G. Gullotta to t: o A o G : G O/ : D . G . G D. M . u M llotta ullotta arti i ns jatović Assessing Agrobiodiversity: A Compendium of Methods Section 1 - About Agrobiodiversity Research 5 1.2 THE CONTRIBUTION OF AGROBIODIVERSITY RESEARCH In recent decades, great advances have DESCRIBING DIVERSITY CO-CREATING KNOWLEDGE SHARING DIVERSITY been made in describing agrobiodiversity and understanding the cultural and biologi- Assessment of the diversity of local variet- Agrobiodiversity management involves a Conservation and innovation in agrobio- cal forces that sustain and create that diver- ies, breeds and wild plants and of their man- dynamic interplay between conservation and diversity depend on continued exchange of sity. Substantial evidence has been generat- agement and uses is a key first step in their im- innovation. Integration of traditional and sci- knowledge and experiences, seeds and culti- ed on the important contribution of agrobio- proved conservation and use. Converting local entific knowledge helps create strategies that vation techniques between generations, and diversity to resilience, livelihoods, health, nu- knowledge into written documents, drawings, harness agrobiodiversity to improve sustain- between individuals and communities. In ad- trition and ecosystem services. Inspiring col- maps or audio and video recordings can help ability, resilience, nutrition, health and live- dition to traditional forms of knowledge shar- laborative initiatives have emerged that have prevent loss of diversity. Documenting the use lihoods. Collaborative research can support ing and transmission, different forms of ex- shown how research can assist or even insti- of wild plants, the diversity and abundance of local processes of innovation without under- change networks, institutions and activities gate actions to maintain and increase agrobio- insect pollinators and the number, distribu- mining the biological and cultural underpin- are important for the conservation of and ac- diversity through co-creation and sharing of tion and characteristics of local crops, variet- nings of diversity-rich agricultural and pas- cess to materials and knowledge that other- knowledge. ies and animal breeds can help local commu- toral systems. Participatory disease manage- wise may be lost. Social networks and associ- nities to assert, conserve and protect their tra- ment strategies (Mulumba et al. 2012), partic- ations can help enable local communities to ditional knowledge. Documentation of local ipatory plant breeding (Ceccarelli and Grando engage in collective management practices knowledge about diversity can also facilitate 2009) and sustainable grazing plans (LPP and and strengthen the property rights of individ- the processes of knowledge sharing and trans- LIFE Network 2010) are examples of strategies uals or groups, as shown by community seed mission from elders to younger generations. combining local and scientific knowledge. banks (Vernooy et al. 2017) and diversity fairs (Sthapit et al. 2006). Different forms of exchange networks, institutions and activities, such as community seed banks and diversity fairs, have emerged as important for the conservation and access to diversity and knowledge that otherwise may be lost. Community seedbank, India. Photo: Bioversity International/P. Bordoni Assessing Agrobiodiversity: A Compendium of Methods Section 1 - About Agrobiodiversity Research 6 1.3 THE RESEARCH PROCESS The diversity present in any landscape is to emphasize mutual learning. Participatory Figure 1.1 Participatory research process the result of interactions between biological, agrobiodiversity research requires a collabo- ecological, environmental, social and cultur- rative relationship between community mem- Select sites based on the interest of the local communities, evidence al processes. Because of this, assessing agro- bers, local organizations and researchers. of unique agrobiodiversity or biodiversity and its management requires ap- expression of concern over loss of Every aspect of the research process should agrobiodiversity. proaches that transcend single disciplinary be discussed and agreed with the community perspectives. This is best done using a ‘trans- in order to develop a common understanding disciplinary’ approach, which implies using of the methods, the analysis and the purpos- Discuss a Free Prior Informed a common language that all participants can es of the data collection. This will help avoid Consent (FPIC) agreement with understand, building joint visions and discuss- the community and have it signed unreasonable expectations or extracting infor- by their representatives. The FPIC ing choices and challenges. Transdisciplinary protocol should summarize the agreed mation that could go against potential bene- approaches include innovative participato- conditions of the research process, fits for the community. state how it benefits the communities ry ways of working with local communities involved and under what conditions and engaging research practitioners from dif- The members of local communities where data are shared and used. Collect data. ferent disciplines, policymakers and other research is taking place play an important role stakeholders. in data collection, analysis, validation and sharing. It is essential that they are given an Studies of agrobiodiversity are best opportunity to use the research process and achieved through the process of participa- results to address their own questions, needs tory research (Figure 1.1). Participatory ap- Analyse the data obtained. and challenges. proaches focus on local perspectives, seeking Share and validate the data and the results of any analysis with the local communities by visualisation, public presentations and discussions. Develop action plans to enhance the management and maintenance of agrobiodiversity through community- based approaches using the results obtained. Doña Viviana preparing a presentation on community biodiversity registers, Cachilaya, Bolivia. Photo: H. Gruberg Cazón Mlawula community garden, Swaziland. Photo: S. Beghini FURTHER INFORMATION / FAO and PAR (2011) Biodiversity for Food and Lang DJ, Wiek A, Bergmann M et al. (2012) PAR Climate Change Project (2010) FPIC – Agro- Agriculture: Contributing to food security and sus- Transdisciplinary research in sustainability sci- biodiversity and Climate Change project. http:// REFERENCES tainability in a changing world. (FAO, Rome). ence: practice, principles, and challenges. Sustain- agrobiodiversityplatform.org/climatechange/ Bharucha Z, Pretty J (2010) The roles and values ability Science 7(1):25-43. the-project/abd_and_cc_project_fpic/ Gómez César M, Sthapit B, Vernooy R (2016) of wild foods in agricultural systems. Philosophical Safeguarding local crop knowledge: the use of Lassen B (2012) Biocultural Community Pro- Sthapit BR, Shrestha P, Upadhyay MP eds Transactions of the Royal Society B: Biological community biodiversity registers (Bioversity Inter- tocols (Deutsche Gesellschaft für Internationale (2006) On-farm Management of Agricultural Biodi- Sciences 365(1554):2913–2926. national, Rome). Zusammenarbeit [GIZ], Bonn, Germany). versity in Nepal: Good Practices (NARC/LI- BIRD/ Ceccarelli S, Grando S (2009) Participatory Bioversity International, Nepal). International Society of Ethnobiolo- LPP and LIFE Network (2010) Biocultural plant breeding. Cereals, ed. Carena MJ (Springer, gy (2006) The ISE Code of Ethics. http://www. Community Protocols for Livestock Keepers (Lokhit Vernooy R, Sthapit BR, Bessette G (2017) Commu- New York, USA), pp. 395–414. ethnobiology.net/what-we-do/core-programs/ Pashu-Palak Sansthan, Sadri, Rajasthan, India). nity Seed Banks: Concept and Practice. Facilitator CENESTA (2013) Evolutionary Plant Breed- ise-ethics-program/code-of-ethics/ Handbook (Bioversity International, Rome). Mulumba, JW, Nankya R, Adokorach J et al. ing. A method to adopt crops to climate changes, Klein AM, Vaissiere BE, Cane JH et al. (2007) (2012) A risk-minimizing argument for traditional increase on-farm biodiversity and support sustain- Importance of pollinators in changing landscapes crop varietal diversity use to reduce pest and dis- able livelihoods. (Tehran, Centre for Sustainable for world crops. Proceedings of the Royal Society B: ease damage in agricultural ecosystems of Uganda. Development). Biological Sciences 274(1608):303–313. Agriculture, Ecosystems & Environment 157:70–86. 2. OVERVIEW OF DATA COLLECTION Data gathering with a Lyngngam community, Meghalaya, India. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 9 2. OVERVIEW OF DATA COLLECTION Agrobiodiversity research uses methods The methods described in this Compendium Crop species – plant species cultivated in Domesticated animal species – cattle, drawn from a range of disciplines (e.g. anthro- provide information on: agriculture or aquaculture. Crops and crop sheep, goat, pig, horse, donkey, buffalo, chick- pology, ethnobotany, genetics, botany, bioge- • species are often but not always the same. en and duck and some less-common species The amount and distribution of crop ography, ecology). It requires approaches that and livestock diversity at household and For example, ‘wheat’ encompasses a number such as geese, llama, yak, camel and guinea integrate traditional and scientific knowledge community level and the diversity of useful of species, including Triticum aestivum (bread pig. and that can take account of different world- wild plants and pollinators wheat), T. durum (durum or pasta wheat) Local breeds – groups within a domesticat- views of diversity and the environment. Data and T. spelta (spelt). In contrast, the species • Important characteristics (traits), ed animal species having common ancestors collection procedures include commonly used Brassica oleracea contains several crops, in- methods such as household surveys and focus management and uses of crops, crop and identifiable external characteristics and cluding kale, cabbage, cauliflower, broccoli varieties, livestock species and breeds and appearance, homogeneous behaviour and/or group discussions as well as specifically de- and Brussels sprouts. signed participatory methods such as the ‘four wild plants other characteristics. Like local varieties, such Local or traditional varieties (landrac- breeds have evolved to suit local conditions. cell analysis’. The methods presented here • The ways in which seeds and planting es) – dynamic populations of crops with cer- have been widely used to investigate the rich- materials are exchanged and affect Wild plants – wild species gathered for tain characteristics selected by farmers. They ness and distribution of species, varieties or diversity food, medicine, rituals, dyes, building materi- have a distinct identity (phenotype) and are breeds and their characteristics (traits), values al, etc. • Changes in diversity over time often genetically diverse and locally adapted. and uses. Methods to study seed flows, land- Modern varieties developed by plant breeding Pollinators – animals, including insects, use systems and the perceptions of the sourc- • Community perceptions of the landscape, organizations are usually more uniform than vertebrates and mammals, that pollinate plant es of resilience and ecosystem services are al- and the importance of different land uses traditional varieties. species. so described. for the provision of ecosystem services and The choice of methods for data collec- resilience tion and analysis will depend on the specific • Needs and opportunities for agrobiodiversity questions that are being asked. For example, conservation and use. does the research focus on describing diver- sity (amount and distribution) or is it related 2.1 DIVERSITY OF WHAT? to particular aspects of diversity management such as the revival of local seeds? Research Agrobiodiversity encompasses both the dif- questions can reflect the perspectives of spe- ferences among individual plants or animals, cific disciplines (e.g. ethnobotany), or may differences among crop varieties, between an- be concerned with exploring various practi- imal breeds or among wild plant populations, cal questions, such as how to conserve and in- and the assortment of species, ecosystems crease diversity to improve productivity, resil- and land uses. Most of the methods in this ience, livelihoods, nutrition and health. Compendium focus on assessing and describ- ing variety, crop, breed or species diversity. Demonstration of four cell analysis. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 10 LANDSCAPE PERSPECTIVE A landscape (or seascape) perspective al- separately, different components of agrobio- lows a better understanding of the composi- diversity depend on each other and should be tion and patterns of agrobiodiversity, its man- seen as a part of a wider agroecological sys- agement and uses at the community level. tem managed by local communities. In such a system, practices for managing diversity, land Different crop varieties are cultivated on and water are closely interrelated. different types of soil, along elevation gradi- ents and across different cultural groups. In A landscape perspective allows a more com- addition to domestic crops and animals, local plete understanding of the interactions be- communities rely on wild species harvested tween different components of diversity, e.g. along the continuum of land-use intensity in the role of forests and sacred groves in provid- pastoral, rotational and other types of system. ing food and medicine, maintaining pollinator populations and mitigating the effects of ex- Although information about the crop, ani- treme weather events. mal and wild plant diversity is often collected Figure 2.1 Community landscape map, Tshongogwe community, Zimbabwe. Source: Agrobiodiversity, Land and People Project, PAR and SAFIRE. Sacred grove, Mali. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 11 2.2 LOCAL KNOWLEDGE Agrobiodiversity and its management are intrinsically linked to local knowledge and cultur- GENDER AND AGROBIODIVERSITY al practices. Aspects of local or traditional knowledge that are important for agrobiodiversity re- search include the following: Agrobiodiversity knowledge and its acquisition are gender-differentiated. Knowledge arises out of experiences and daily acts and hence from gendered roles and responsibilities. Women and Local classification systems (ethnotaxonomies) – Local names and classification sys- men have different roles in agricultural and pastoral production systems and consequently have tems for crops, animals, forest or pasture flora, soil types and ecosystems reveal important in- different specialized knowledge about crops, animals, wild plants and the preparation of food, formation about diversity and reflect the interactions between people, plants, animals and the medicine and various crafts (e.g. weaving, natural dyes). Women have long been known for their environment. specialized knowledge about seeds. The gender differences need to be taken into consideration Management practices and systems – Agrobiodiversity is a result of distinct management to avoid gender-related bias in all stages of research. systems in diverse environments. Practices including seed selection and exchange and the man- agement of animals, soil, water sources, forest and other ecosystems all influence the evolution, richness and conservation of agrobiodiversity. Exploring local knowledge and preferences for shea (Vitellaria paradoxa) varieties, Burkina Faso. Uses, values and beliefs – Wild species, crops, varieties, domestic animals and breeds are as- Photo: B. Vinceti sociated with a diversity of cultural uses, values and practices. Specific varieties, breeds or spe- cies may have a special place within traditional worldviews (or cosmovisions) or in local cul- ture for their nutritional, culinary, medicinal or adaptive traits (e.g. adaptation to specific soil). Sacred groves and sacred woods have cultural and ecological importance. Indigenous fishing practices, Qeshm Island, Iran. Photo: M. Salimi Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 12 LOCAL NAMES AND CLASSIFICATION to capture specific parts or characteristics of LOCAL VARIETY AND BREED NAMES SYSTEMS importance for species or varietal identifica- AS MEASURES OF DIVERSITY tion. For example, for the identification of the Agrobiodiversity research requires a good species (and variety) of cereals such as wheat, In many parts of the world, local variet- increase when working with different commu- understanding of local names and classifica- rice and millets, the photos need to show the ies and breeds are recognized through local nities where other factors such as differences tion systems for crops, animals, wild plants, structure of the spike or panicle and the shape names. They may be named after places of or- in pronunciation may complicate identifica- soil, seasons, pests and diseases and other fea- and colour of the seed. igin, morphological characteristics, phenology tion further. Focus group discussions and four tures of diversity and the environment. Local or other specific traits. Names of varieties and cell analysis are ways of coping with this prob- names and classification systems are specific In many cases, the correspondence between breeds may change over time or vary from com- lem. Further studies using field trials or even to cultures. local name and scientific name is one to one: munity to community or even from household molecular genetic methods can shed addition- one local name corresponds with one scientif- to household. Individual farmers in a commu- al light on the similarities and differences be- One of the simplest and most-effective ic name. nity may call the same variety or breed by dif- tween varieties that farmers recognize. ways to understand local categorization is to ferent names or different breeds or varieties use a ‘freelisting’ method. For example, ask- However, for certain plants the correspon- ing interviewees or focus group participants dence may not be one to one, and this results by the same name. This identity problem may to list all vegetables, fruits or wild food plants in: can help to understand categorization from a • Overdifferentiation (several local names cultural-domain perspective. refer to only one Latin name) or Once local and common names have been • Underdifferentiation (one local name Local black awned wheat variety, Turkey. Wild edible fruits, West Sumatra, Indonesia. identified, the next step is to link them with refers to several Latin names) (Table 2.1). Photo: D. Mijatović Photo: L. Pawera scientific or Latin names, which consists of ge- One solution is to work with specimens or nus and species (e.g. Malus domestica for ap- examples of crops, varieties or wild plants, and ple). The identification of species of crops, to ask the respondents or focus group partici- pollinators and wild plants often requires col- pants to show or to bring the examples of spe- laboration with botanists, entomologist and cies and varieties discussed. Photographs tak- other experts. Specimens or photos can be en in advance can be helpful too. used to consult the botanists. The photos need Table 2.1 Correspondence of local names for wild food plants with scientific names (example from the White Carpathians, Czech Republic). Correspondence Type Folk Name Scientific Name One-to-one Kokoška Capsella bursa-pastoris Overdifferentiation Kašičky, Kozičky, Černý bez, Hural Sambucus nigra Rumex acetosa Underdifferentiation Šťovík Rumex acetosella Rumex crispus Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 13 2.3 DATA-GATHERING METHODS Agrobiodiversity information is collected using a combination of quantitative (e.g. surveys) Focus group discussions (FGDs) are used to explore topics in more depth and from different and qualitative (e.g. focus group discussions) methods. Field and participant observations, spe- perspectives within a community. FGDs are particularly useful to find out about diversity distri- cies inventories, field trials, nutritional composition analyses, pest and disease determination, bution, important characteristics, management practices, constraints and opportunities, and any remote sensing and molecular genetic studies are just some of the ways that can be used to obtain other topic. FGDs are used to validate data from other sources and to reach a consensus at the additional data. The Compendium describes some common data-gathering methods: community level, e.g. on variety identity and properties. Many methods in the Compendium draw on focus group methodology further described on page 15. Household survey questionnaire is used to collect information from a sample of households in a community using a structured interview. Information collected includes land uses, man- Key informant interviews are in-depth interviews with community members that have spe- agement practices, characteristics of crops, varieties and breeds, seed sources and uses of wild cialized knowledge about agrobiodiversity, e.g. medicinal plants, food or seed processing and plants. The household survey also provides information on demographics, socioeconomic status beekeeping. These are conducted using semi-structured or structured interviews that consist of of households and other aspects to enable differentiation of the sample and analyses of changes questions presented to all key informants in the same way. The Compendium gives examples of over time. Further information is given in Section 5: Household surveys. key informant interviews to collect information on animal diversity, wild plants and other as- pects of diversity. Information obtained from key informants is complementary to information Mandailing respondent showing a wild vegetable fern (Cyathea junghuhniana), West Sumatra, Indonesia. from household surveys and FGDs. Photo: L. Pawera Identifying edible plant species and assessing their conservation status, Benin. Photo: B. Vinceti Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 14 PARTICIPATORY TECHNIQUES Household survey questionnaire, FGDs and key informant interviews are the main methods to collect information about agrobiodiversity. There are a number of techniques for systematic collection of agrobiodiversity data that can be applied, modified and combined in surveys, FGDs and key informant interviews. Some of these techniques and methods described in the compen- dium can be deployed to facilitate empowerment and decision-making in relation to agrobiodi- versity and other resources. Participatory data collection techniques can contribute to processes of shared learning, enabling ownership and mobilization of knowledge to address issues faced by local communities (e.g. loss of diversity, climate change and malnutrition). • Listing or freelisting involves creating Two examples of ranking are given in Table institutions. An example is given in Figure • Calendars and timelines show changes lists of items with individuals or groups 2.3 and Table 2.4. Another example is given 2.2, see Section 3: Transect walk for in uses, management and availability of about species or other items (e.g. fruits, in Figure 7.1, which shows the results of a examples of transect diagrams. diversity over time. While calendars show animals, wild plants, varieties of a crop). scoring of rice varieties for different traits. • seasonal changes; timelines illustrate Mapping describes the location and See Section 9: Uses of wild plants for Ranking, scoring, pile sorting and similar changes over a longer period of time, distribution of resources, land uses and further information on the freelisting techniques can be applied and adapted in e.g. occurrence of droughts and floods, landscape features, their importance and process. many different research contexts. pest and disease outbreaks, introduction changes over time. Landscape mapping • Ranking, scoring or rating, pile sorting • of commercial crop varieties or animal Diagrams drawn by survey respondents, is explained in Section 12, and mapping and similar techniques elicit attributes, breeds. Examples of calendars are given FGDs participants or key informants can be used to explore many other aspects similarities and relations among items in Section 4: Seasonal calendars; and an illustrate and explain processes, of diversity and its management such as within a domain (which have been identified example of timeline is given in Section 13: relationships and structures related to species distribution or migratory routes through freelisting or some other method). Resilience assessment. diversity, management practices or social between dry- and wet-season pastures. A farmer listing foods that have become less Researchers map a home garden with a farmer, FGDs about the role played by formal and informal institutions. Men and women conducted the exercise common in his community as part of a focus group, Yucatan, Mexico. separately and presented their results to the rest of the group and other community members, Burkina Faso. Yucatan, Mexico. Photo: D. Sampson Photo: D. Sampson Photos: B. Vinceti Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 15 FOCUS GROUP DISCUSSIONS Designing FGDs Conducting FGDs Facilitation Many methods described in this • Identify the main aim and the key research Preparation – Make sure the research A successful FGD depends on a skilled facil- Compendium make use of FGD techniques to objectives team gets familiar with the script, committing itator to guide the group's discussion. The fa- explore a specific topic with a group of par- • Make a list of questions (schedule or script) the questions to memory as much as possible. cilitator needs to encourage discussion by cre- ticipants. The information collected in FGDs as guidance for the FGD session ating a warm and comfortable environment. Pre-session – Use the time before the FGD draws from local knowledge and from experi- It is essential that the facilitator respects par- starts to become familiar with the group dy- ences, beliefs, perceptions and attitudes of the • Decide on the number of respondents ticipants’ knowledge, experiences, opinions, (usually 4–15) namics and make all participants comfortable. participants. An FGD is a moderated discus- perceptions and customs. Important facilita- sion between participants, and not between • Select the participants through purposive Session- Introduction – before proceeding tor skills include: the researcher and the participants. FGDs are or convenience sampling with the questions and discussion: • Good speaking and listening skills not only for the researcher or facilitator to get • Recruit the participants in advance • The facilitator introduces the team and the information, but also provide a chance for the • Good observation of participants’ body topic and purpose of the FGD, and thanks participants to exchange information among • Identify a venue for the discussion language and group dynamics the participants and organisers themselves. • Prepare and organize material • • Some knowledge of the topic of discussion The participants introduce themselves (one FGDs can be organized around a set of • Organize refreshments for the participants option is randomized self-introduction • Flexibility to adapt to the flow of the open-ended questions on a specific topic, but instead sequential introductions) discussion other techniques such as scoring, ranking and • Decide if to conduct a mixed or separate diagramming can be used to obtain informa- gender group according to the local socio- • The facilitator initiates the discussion and • Ability to remain impartial and maintain tion. During the FGD, the information is re- cultural context. proceeds with the script. verbal and non-verbal objectivity corded on, for example, a large sheet of white • A sense of humour to keep the discussion paper or on cards. The recorded information relaxed and encourage sharing of is not just for the researcher, but also for the information (Nyumba et al. 2018). participants. FGDs require good planning and organiza- tion during research design, preparation and data collection. An FGD is conducted by a team consisting of a facilitator and one or more as- sistants, note-takers or rapporteurs. The facil- itator manages the discussion, and needs to create a comfortable environment for all par- ticipants. The assistants’ role is to document the content of the discussion. Making a seasonal calendar, Mali. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 16 2.4 AGROBIODIVERSITY DATA During or after interviews and FGDs, the information collected is organized and processed to While some of the information collect- Qualitative data can be gathered using create data tables that can later be analyzed. For example, Figure 2.1 shows a diagram of seed ed will be quantitative (How many varieties? techniques that allow easy transformation in- sources drawn by a farmer during a household survey. Such a diagram can be processed to create What is the size of the field?), much will be to quantitative data (freelisting, ranking, rat- a table (Table 2.2). To encode data on seed sources identified by farmers, the code ‘1’ is assigned semi-quantitative or qualitative (Which vari- ing, pile sorting). Examples of such transfor- to those sources from which there is an arrow pointing to the farmer, and the code ‘2’ to those for ety is better? Why?). mations and their uses include the following: which the farmer is the source. Quantitative data (numbers, also called nu- Characterization: merical) are observations that can be counted • Binary – the informant in a survey or (discrete data, e.g. trees in a field) or measured Figure 2.1 Diagram of a farmer’s response to questions about seed sources. Source: Jarvis and Campilan (2006) focus group is asked to say ‘yes’ or ‘no’ (e.g. (continuous data, e.g. area of land). As such, Is this variety resistant to a disease?), or to Map drawn by respondent A Map drawn by respondent B this type of data should always be associated choose between two possible values (e.g. with a unit of measurement (e.g. number of parents extensionist Is this variety resistant or susceptible to a parents extensionist trees, hectare). particular disease?) Qualitative data (text) describe characteris- • Categories – the informant is asked FARMER A FARMER B tics or properties of a subject. Qualitative da- to choose or give a description, e.g. white, ta are also called categorical as they express red or black for the colour of grains in rice. market neighbour market neighbour a categorical measurement not in terms of numbers, but in terms of words. Qualitative Comparative: relative data can be extracted from questionnaires, in- relative NGO • Rating – the informant is asked to NGO terview transcripts, FGDs, diagrams and any rate an item on a numerical scale between other participatory data-gathering technique. two or more alternatives, e.g. yield: low, Table 2.2 Tabulated data from the farmer’s response to questions about seed sources from Figure 2.1. For many analyses, qualitative data need to be medium, high quantified, which involves turning the words Respondent Parents Neighbour Market Relative Extensionist NGO into numbers (coding) (e.g. fruit colour: or- • Ranking – the informant is asked to ange = 1, red = 2, purple = 3). Coding requires rank a list of items in order, for example, A 1 2 1 0 0 1 construction of a category system that allows according to preference or importance. all of the data to be categorized systematical- Tables 2.3 and 2.4 provide examples of the ly. After coding, the data can be organized, in- results of ranking for traits and functions B 1 1 0 2 0 0 terpreted and analyzed for frequencies and of fruits. relationships between variables, means and C Belief statements: variance. • The informant is asked to assess the D truth of a statement against a predeter- mined scale, e.g. this variety is good for feeding to nursing mothers: true, interme- diate, false. Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 17 2.5 SAMPLING STRATEGIES Table 2.3 Results of one-dimensional ranking of local fruits for taste. Four informants ranked each fruit on a Choosing the participants and sample size that have been selected based on particular scale of 1 to 5, in which higher values indicated better taste. After summing the values for the four informants for the different fruits, it appears that banana is considered the tastiest fruit among the informants. are two important first steps in any study. The criteria, such as established trust and willing- choice of sampling approach is directly linked ness to engage with the researchers. For im- Fruit Informant 1 Informant 2 Informant 3 Informant 4 Total Rank to the study objectives. The sample should be pact assessments, the sample should include able to represent the population that is of in- villages and households that are not partici- Apple 3 4 5 4 15 4 terest to the study and be large enough to have pating in any specific interventions to serve as sufficient statistical power to answer the re- a ‘control’. Orange 3 4 4 3 14 5 search questions. The selection of participants should con- The sampling strategy should consider both sider the variation of knowledge distribution Mandarin 4 4 4 4 16 3 the selection of communities and the selec- among different age groups or social groups: tion of participants within communities and certain knowledge can be held only by elders Banana 4 5 5 5 19 1 households for data collection. In some cases, or specialist ‘custodians of knowledge’. For it is desirable to target specific people (‘knowl- example, knowledge about medicinal plants edge holders’). If the focus of the study is a is commonly maintained by herbalists, tradi- Grape 5 4 4 4 17 2 specific region or district, then communities tional healers or shamans. It is important to should be selected to ensure a balanced reflec- keep in mind that knowledge is often gen- Table 2.4 Results of multidimensional ranking of local fruits for different domains (taste, food security, income, tion of the different social and environmen- der-differentiated: women and men have dif- tradition). One informant scored each fruit for different characteristics on a scale of 1 to 5 and the scores were summed across the domains. Durian had the highest final rank for the domains of interest. tal conditions in the region. Often, the focus ferent knowledge, preferences and concerns of study is a specific village or set of villages in relation to diversity. For example, in terms Fruit Taste Food Income Tradition Total Rank of preference for crop traits, traits important security to women include qualities related to prepa- Durian 4 4 4 4 16 1 ration and nutrition, while for men, import- ant qualities are more likely to be related to productivity. Mango 4 3 4 4 15 2 There are two main approaches to sam- Mangosteen 4 2 3 4 13 4 pling: probability sampling and non-proba- bility sampling. Probability sampling gives Banana 4 4 2 4 14 3 the best chance of obtaining a sample that is truly representative of a population. Non- probability sampling is used in specific cases, Guava 3 2 2 2 9 5 such as if the objective of the study is to docu- ment as much knowledge as possible in a short time or to document rapidly disappearing tra- ditional knowledge. A summary of sampling strategies is provided below (based on Newing Young researcher in Lyngngam community, 2011). Meghalaya, India. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 2 - Overview of Data Collection 18 Sample size is a key consideration in In bigger research projects, sample size PROBABILITY SAMPLING NON-PROBABILITY SAMPLING planning your research and different meth- should take into consideration the total pop- ods may require different sample sizes to ulation size, the magnitude of difference in Simple random sampling – Pick out individ- Convenience sampling – Interview anyone ual cases (participants) from a sampling frame, that you can find who fits your broad criteria. give the amount of information needed. specific indicators that will be assessed statis- using a random numbers table. For example, The sample size depends on the study de- tically and the resources available (time, peo- households can be randomly selected for inclu- Targeted sampling – Seek out individuals sign, and the methods for data collection ple and funds). A good practice is to conduct a sion in a survey by first preparing a list of house- who are most relevant to study. Targeted sampling is used in studies that focus on a particular group and statistical analysis you are planning power analysis (McDonald 2014) to determine holds in the community, in consultation with lo- cal leaders, and then randomly selecting house- (e.g. particular ethnic group, pregnant mothers be- to use. In general, a sample size of at least the necessary sample size to detect a signifi- tween the ages of 25-30) or people with specialized 30 individuals is desirable for crop and va- cant difference in an indicator of interest. holds from the list. In Microsoft Excel, the function =RANDBETWEEN(1,100) can be used to generate a knowledge (e.g. traditional healers). riety diversity information from a house- random number for each household in the list, and Purposive sampling – (also known as judg- hold survey. Economists, social scientists then the households assigned the highest numbers mental, selective, or subjective sampling) – Select and others who want to have a more robust can be selected for surveying. a sample based on personal judgment of their suit- dataset tend to use larger sample sizes (50– Systematic sampling – Use a random num- ability for the study. 100 households). bers table to pick the first participant or household, Quota sampling – Define two or more sub- and then select additional participants following groups (e.g. men and women) and set the pro- a constant interval (n = total population (P) / de- portion you want in each category (e.g. 50:50). sired sample size (N)). E.g. for a total population of Interview anyone you can find in each subgroup 100 individuals or households, if the desired sample until you have reached the target sample size. FURTHER INFORMATION / REFERENCES size is 20, the interval (n=P/N) will be calculated as n = 100/20 = 5. If the random number (first partic- Snowball sampling – (also known as chain sampling, chain-referral sampling or referral sam- Bernard HR (2002) Research Methods in Anthro- McDonald JH (2014) Power analysis. Handbook ipant) is 7, then the second participant is 12 (7+5), pling) and respondent-driven sampling – Seek out pology: Qualitative and Quantitative Approaches of Biological Statistics, 3rd ed. (Sparky House Pub- the third participant is 17 (12+5)... until 20 partici- individuals who are most relevant to the study, in- (Altamira Press, Walnut Creek, Oxford, UK). lishing, Baltimore, Maryland). Available at: http:// pants or households are selected. terview them and ask if they know of others you www.biostathandbook.com/power.html Gonsalves J, Becker T, Braun A et al. (2005) Par- Cluster sampling – Divide the population in- could interview or who are linked to them in a spe- ticipatory Research and Development for Sustainable Newing H (2011) Conducting Research in Con- to ‘clusters’ (often, geographical areas), take a sam- cific way (e.g. in studying seed systems). Then in- Agriculture and Natural Resource Management - A servation: Social Science Methods and Practice ple of clusters, and then take a sample of cases from terview those individuals suggested by already in- Sourcebook. Volume 1: Understanding Participatory (Routledge, Abingdon, UK). each selected cluster. This approach is particularly terviewed respondents. Research and Development (CIP-UPWARDS, Lagu- useful for a large, dispersed population. To achieve Nyumba TO, Wilson K, Derrick CJ et al. (2018) na, Philippines and IDRC, Ottawa, Canada). probability sampling, a sampling frame is needed The use of focus group discussion methodology: for each cluster that is sampled. Jarvis DI, Campilan DM (2006) Crop genet- Insights from two decades of application in conser- ic diversity to reduce pests and diseases on-farm: vation. Methods in Ecology and Evolution 9(1):20–32. Stratified random sampling – Stratifying Participatory diagnosis guidelines. Version I. Bio- the population before applying random sampling Newing H (2011) Conducting Research in Con- versity Technical Bulletin No. 12 (Bioversity Inter- methods involves developing criteria for stratifi- servation: Social Science Methods and Practice national, Rome). cation (e.g. socioeconomic subgroups). Divide the (Routledge, Abingdon, UK). population into ‘strata’ (groups of cases with cer- Jarvis DI, Hodgkin T, Brown AHD et al. (2016) PAR Climate Change Project (2010) FPIC – tain characteristics, such as men and women, rich Crop Genetic Diversity in the Field and on the Farm: Agrobiodiversity and Climate Change project.. and poor, large and small landowners), and then Principles and Applications in Research Practices (YALE University Press. New Haven, NY, USA). http://agrobiodiversityplatform.org/climatechange/ take a random sample of cases from each stratum. the-project/abd_and_cc_project_fpic/ Martin GJ (2004) Ethnobotany: A Methods Man- ual (Chapman and Hall, London, UK). 3. TRANSECT WALKS Farmer harvesting semi-wild tuber-bearing plant 'Talas hitam' (Xanthosoma sagittifolium), West Sumatra, Indonesia. Photo: L. Pawera Assessing Agrobiodiversity: A Compendium of Methods 20 3. TRANSECT WALKS A transect walk is a walk along a defined The data collected provide an overview of path (transect) across the study area, together the main crops and animals in the landscape with key informants, to create a diagram that and of the availability of key resources. They shows a cross-sectional view of the landscape. provide an idea of the number of households Transect walks are usually a starting point and their location that can be helpful for con- for other investigations and provide a useful ducting the household survey. The data col- preliminary to most of the other activities in lected will help in the formulation of hypoth- this Compendium. They can also be used af- eses to be tested through the other methods ter the first exercises of participatory mapping described in the Compendium and provide in order to validate the information collected some idea of the major problems faced by the during the mapping exercises and can be used community. with seasonal calendars, timelines and other methods. During the walk, the following infor- CONDUCTING A TRANSECT mation can be collected: WALK • Topography and altitude (preferably using A transect walk is conducted by a facilitator a global positioning system [GPS]) or interviewer, note-taker and key informants. • Soil characteristics Participants • Cropping systems and major crops or crop The key informants should be knowledge- types (e.g. orchards, arable fields) able about the environment, land uses and dif- Figure 3.1 Example of a diagram produced from a transect walk in Sierra del Rosario, Cuba. Source: INIFAT, ferent activities in the landscape. Where pos- Agrobiodiversity, Land and People Project, PAR. • Livestock species and occurrence sible, participants should include women and • Type of wild vegetation (woods, marshes, men and older and younger community mem- Process shrubs) bers to provide different perspectives on the suitable interval) and take note of whether the Before starting the walk, the facilitator asks questions and issues raised. land-use pattern has changed. • Population (houses, schools, community the informants to name and list all the land us- areas) Choosing a path es (‘zones’) in the area, making clear that the The facilitator asks participants to describe The facilitator should ask the local infor- exercise aims to collect information not only features encountered along the path and to ex- • Activities (grazing, foraging for wild mants to suggest the most suitable path for on farming systems but also on grazing areas, plain the key characteristics of the areas that edibles). the transect walk. The path chosen should wild zones and other land uses. they see. The discussion can be facilitated by The discussions during the walk can cov- cover the greatest diversity of the area, and asking questions about the details and by mak- As the walk progresses, the team should er any relevant topic, such as crop or livestock can be drawn on a rough map. If the path is ing observations. The note-taker makes notes stop at every key feature and at the beginning diversity, land management, land ownership, very long, more than one walk will be needed. of all information gathered and takes photo- of a new zone (such as residential, topograph- pollution problems, resource limitations and graphs or draws sketches. ic, land use, cropping system) and record the illegal cultivation or logging activities. distance from the last feature or zone. As an al- ternative, stop every 50 or 100 paces (or other Assessing Agrobiodiversity: A Compendium of Methods Section 3 - Transect Walks 21 The key questions that have to be asked Table 3.1 Example of a table used to capture information gathered during a transect walk when stopping in each zone are: Zones Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 ϐ What is this zone called? ϐ What are the main characteristics of Soil type this zone? ϐ What crops or animals are here? Water availability ϐ What activities are carried out in this zone? By whom? Trees ϐ What is the land ownership – private, collective or state-owned? Crops After the transect walk has been complet- ed, discuss and check the information and data Vegetation collected. Where more than one transect walk has been completed, results can be combined and compared. The final results are a diagram Animals (see example in Figure 3.1 and Figure 3.2) and table (see example in Table 3.1). Management In the table, the column heads list the dif- ferent zones encountered, with information Problems on altitude if available. In the left-hand col- umn, list the topics of interest (plants, land Opportunities use, problems, drainage system and so on) and then fill in the details of what was observed in Transect walk in Huay Hin Lad Nai, Thailand. each zone. Photo: D. Mijatović FURTHER INFORMATION Figure 3.2 Diagram produced from a transect walk in Cachilaya, Bolivia. Source: Agrobiodiversity, Land and People Project, PAR. Illustration: F. Pasta Rufina P (2013) Participatory Rural Apprais- al (PRA) Manual (FAO, Saint Lucia). Available at: http://himachal.nic.in/WriteReadData/l892s/15_ l892s/1499233403.pdf 4. SEASONAL CALENDARS FGD facilitator recording participatory ranking and monthly availability of food plants in Minangkabau community, Simpang village, West Sumatra, Indonesia. Photo: L. Pawera Assessing Agrobiodiversity: A Compendium of Methods 23 4. SEASONAL CALENDARS Seasonal changes have a big influence on The calendar can be drawn on big sheets of areas, mating seasons and the main times The facilitator can also ask about off- the management and use of agrobiodiversi- paper either as a grid or as a circle. The facil- for offspring production. farm activities: ty. Any study exploring agrobiodiversity and itator and participants draw a grid on a large Seasonal calendars can also provide im- different aspects of local livelihoods has to sheet of paper (Table 4.1). Information can be ϐ What other activities do you have portant information about food availability, take into account how seasonal variations af- written directly in the grid or on sticky notes to carry out (e.g. working in a local using questions such as: fect agricultural activities, livestock manage- and then attached to the paper. processing factory)? ment or the availability and collection of wild ϐ In which month do you have the Creating a calendar may begin with add- Festivals and other cultural events can plants. This can be done using a seasonal cal- most food available from your own ing the main characteristics of the seasons also be added to the calendar. endar to collect information on: production? by asking participants a series of questions, ϐ What festivals do you celebrate during • Seasons (most often related to rainfall and starting with: ϐ In which months do you have to buy the year? When? temperature) food from the market? ϐ What are the different seasons? When • Activities related to crop production does it rain? (Continue with other The facilitator can also ask about the (preparing land, sowing, harvesting, etc.), questions about temperature regime use of wild plants for food and medicine, animal husbandry or collection of wild etc., as necessary) e.g.: plants Then the facilitator asks questions about ϐ When do you gather wild food plants? • Food availability the main crops and the different agricultur- • Season-specific local knowledge about al activities people perform during the year the environment and agrobiodiversity and adds them to the calendar. Examples of Dec Jan management, such as environmental and such questions include the following: F biological indicators v ϐ What is the first activity you perform o • Other activities and practices, such as in the farming year (e.g. preparing the collecting honey, seasonal work outside soil; in rotational agriculture, this may the farm, holidays, festivals and other be through burning crop residues on cultural events. the land)? When do you carry out this activity? Seasonal calendars can be created in focus group discussions or workshops with mixed or ϐ When do you sow seeds of the different separate groups for women and men. It is de- crops? sirable to have a facilitator and a note-taker at ϐ When do you harvest each crop? these events. Ask the group to name the different activ- The information collected depends on the ities that are important and add when they aims of the exercise. are carried out. In the case of animals, this is likely to include moving to new grazing Figure 4.1 Circular seasonal calendar Sep Oct ug N June July ay A Mar Apr eb M Assessing Agrobiodiversity: A Compendium of Methods Section 4 - Seasonal Calendars 24 Table 4.1 A table for seasonal calendar FURTHER INFORMATION Months Jan Feb March April May June July Aug Sep Oct Nov Dec Jarvis DI, Hodgkin T, Brown AHD et al. (2016) Chapter 6. Abiotic and Biotic Components of Agricultural Ecosystems. Crop Genetic Diversity in Seasons the Field and on the Farm: Principles and Applications of Research Practices (Yale University Press, New Farming activities* Haven, USA, and London), pp. 126–153. Food availability Wild plant harvesting Off farm activities Cultural events * Activities related to soil, crop or animal management or other activities of importance to the participants. Add rows to capture different timing of activities with major crops and varieties or animal species and their breeds. Figure 4.2 Seasonal availability calendar of wild and cultivated leafy vegetables in local language Bamanakan, Ségou region, Mali. Source: Bioversity International and Institut d'Economie Rurale, IFAD-EU NUS Project. 5. HOUSEHOLD SURVEYS Young men next to purple yam (Dioscorea alata) locally known as "hingurala", Milleniya, Sri Lanka. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 26 5. HOUSEHOLD SURVEYS 5.1 CONDUCTING THE HOUSEHOLD SURVEY Household surveys are used to collect infor- allow sound analysis and interpretation of the Inform the community well ahead of time At the end of each day, check the complet- mation on agrobiodiversity from a sample of data. It should be translated into the local lan- about the planned survey and discuss the best ed questionnaires to make sure they have been households in a community or larger area us- guage with precise, brief, simple and culturally timing with them in detail (e.g. month, week, filled in correctly, that there are no major gaps ing a questionnaire. The households sampled appropriate wording. Unless otherwise stated, day, time of day). The research team should and that different interviewers have used the are usually from diverse socioeconomic back- all questions concern the current production test the questionnaire by completing it ahead same approach. grounds and are selected using stratified ran- season or year, not previous years. of time to make sure there are no problems The example questionnaire in Annex 5.1 dom sampling (see ‘Probability sampling’ un- with any of the questions. Make plenty of cop- Note: In many parts of the world there are consists of the following parts: der Section 2.5: Sampling strategies and sam- ies of the questionnaire available in the local two cropping seasons per year. During the survey ple size). language and share them with those who are A – Identification and validation information you should ask only about the current cropping interested. Jarvis and Campilan (2006) pro- Annex 5.1 provides an example of an agro- season; a second survey may be needed to cap- B – General information vide general advice on individual interviews biodiversity survey questionnaire that can ture all the information about what is grown in for crop diversity. It is best to have two people C – Land-use diversity and practices be adapted to meet different research ob- the other cropping season. carry out the survey so that one can contin- jectives. This questionnaire was designed to D – Crop diversity (species and varietal) ue a conversation with the respondent while collect basic information about households, the other records the answers. Farmers will be E – Livestock diversity farming systems, the amount of crop and an- giving up quite a lot of time to help with com- imal diversity, and use of wild plants. Surveys F – Use of wild plants pleting the questionnaire and their concerns can also provide more detailed information and the other demands on their time should Parts A and B should be included in all such about livelihoods, diets and consumption, cli- be respected. questionnaires, while the precise content and mate-change adaptation or any other topic of inclusion of other sections will depend on the interest. The objective is to generate data and Owita garden, Milleniya, Sri Lanka. Photo: J. Prasad research questions. statistics about diversity and production prac- tices and to identify some of the constraints to, and opportunities for, increasing diversity. The survey takes the form of a structured interview that involves asking a set of sim- ple short-answer questions. Each question is asked in the same way to each informant and may be open-ended or fixed choice or may ask for some kind of scoring or ranking. While most of the questions will involve a verbal re- sponse, diagrams can also be used to obtain in- formation where this is easier for the respon- dent (e.g. on seed supply in part D). The house- hold questionnaire should be designed to en- able the answers to be easily recorded and to Assessing Agrobiodiversity: A Compendium of Methods Section 5 - Household Surveys 27 A – IDENTIFICATION AND C – LAND-USE DIVERSITY AND D – CROP DIVERSITY (SPECIES AND Start by asking what crops are cultivated by VALIDATION INFORMATION PRACTICES VARIETAL) the informant, making sure that all the differ- ent crop types are covered (cereals, tuber and Record the number of the questionnaire in This part of the questionnaire gathers infor- This part of the questionnaire gathers the root crops, vegetables, fruit, oilseeds, legumes the field ‘Questionnaire ID’ to keep track of mation on the household’s land use and prac- information needed to determine the amount and pulses). the number of interviews conducted at each tices. These might include home gardens, irri- and distribution of crop and varietal diversity site. Fill in the site name, surveyor identi- gated and non-irrigated fields, pasture, agro- used by households and communities. It is es- The questions might be as follows: ty and survey date. Record the identity of the forestry areas, orchards and fishponds. Other sential to record the identity of each crop and ϐ What crops do you grow? person who checked the survey and date when production systems identified during the tran- (where known) variety grown and the areas For each crop: the questionnaire was checked. sect walk (e.g. rotational fields) should also be planted with each crop and each variety. In the included. For each land-use type, record ‘yes’ case of tree crops, it is often better to ask ques- ϐ Do you grow different varieties of the B – GENERAL INFORMATION or ‘no’ and whether it is privately owned, rent- tions about the number of trees being grown crop? Use this part of the questionnaire to col- ed or community owned. rather than the area they occupy. Questions For each named variety, ask: lect the information about the household. about the area under production are often The results can be used to determine the to- ϐ Is the variety local or commercial? This should include the name, gender and age quite difficult for informants to answer and it tal number of production types available to the of the informant and some basic information is often necessary to ask follow-up questions ϐ What is the source of the seed? (see community, the most commonly available and that provide good estimates (e.g. Do you grow Section 8 for categories of seed sources on the household (e.g. number of household used production types and the extent to which members, gender, children and involvement more than this area here or less? How much and further questions) different households use the same production in farm work). This can be expanded to collect more?). In some cases, it may be easier for the ϐ What is the area planted of the variety? types or different ones. additional socioeconomic data where needed. farmer to draw an outline map of the land they ϐ What is the total production? cultivate and fill in the different fields with their crops and varieties on the map. Answers ϐ What are the most important reasons to the questions in this section can be used to for choosing this species or variety calculate richness, evenness and divergence (e.g. high yield, adapted to local soil, (see Section 14: Richness, evenness and diver- medicinal properties)? gence for crop species and varieties). Farmers show sweet potato (Ipomoea batatas) tubers grown in their home garden, Yucatan, Mexico. Photo: D. Sampson Assessing Agrobiodiversity: A Compendium of Methods Section 5 - Household Surveys 28 Not all crops will have named varieties and E – LIVESTOCK DIVERSITY F – USE OF WILD PLANTS it is often possible to obtain variety-level in- This part of the questionnaire gathers in- formation for only a few of the major crops. This part of the questionnaire gathers in- formation on the number of households that Note also that individual farmers often have formation on the use of non-cultivated plants, keep animals, what these are and how many their own names for varieties and the four cell asking informants which wild plants they use breeds of each there are in the community and analysis process (Section 6: Four cell analysis) and for what purpose. Ask the informant: households. Section 10: Diversity of domesti- will help in developing an agreed list of vari- cated animals and breeds provides ways of ob- ϐ Which wild plants do you use? eties. Where there is more than one cropping taining more information on the importance season per year, ask about the current one and After they have listed the plants they use, of animal diversity in a community. remember that different varieties might be ask each of the following questions about each grown in the other cropping seasons. Ask the following questions: plant: Note on crop classification: Farmers may ϐ What animal species do you keep? ϐ Where do you gather it (e.g. near the have their own classification of crops that differs river, in the forest, in fallow land, For each species, ask: from the scientific one. For example, in north- other)? ϐ How many different breeds do you have? east India, people group potatoes, sweet pota- ϐ What do you use them for (food, toes and taro under one large group. The inter- For each breed, ask: medicine, fodder, firewood, building viewer should use these local terms during the ϐ What do you use this breed for (e.g. material, other)? interview and, wherever possible, take photos or eggs, milk, meat, leather, manure, etc.)? ϐ What part(s) of the plant do you use make notes on the different types discussed. ϐ How many females and males are of (leaves, roots, shoots, bark, flowers, Note on units of area and production: Use reproductive age? fruits, seeds)? the same measures for the area under cultivation ϐ Is the number of female animals stable, Note: List options for responses in the ques- and for production for all informants. Use local increasing or decreasing? tionnaire to facilitate consistent recording. measures of areas and production during the in- ϐ Is the number of male animals stable, terviews and then convert these to international Where possible, take photographs of wild increasing or decreasing? units when transferring the data. plants that respondents identify as useful, Determining the identity of breeds is of- these can help confirm the identity of the dif- Additional questions: Past status of crop ten quite difficult. Informants may not make ferent plant species and check that the same and varietal diversity much distinction between different breeds and local names are used by all informants. To understand changes in cultivation and just regard their animals as local or exotic. The data provide information on the gener- production, ask about the crops and varieties Knowing the numbers of female and male al use of wild plants by a community. Combine grown in previous years. Ask the same ques- Man holding African black plum (Vitex doniana), animals in a population allows one to calculate these data with the information on wild plants Boumboro village, Mali. tions as for crop and varietal diversity but in the effective population size at household and Photo: D. Mijatović obtained through the key informant inter- past tense. community levels. views to complete the identification and anal- ϐ What crops and varieties did you grow ysis of information on the use of wild plants last year? (see Section 9: Uses of wild plants). ϐ What was the area under cultivation? ϐ What was the total production? Assessing Agrobiodiversity: A Compendium of Methods Section 5 - Household Surveys 29 5.2 DATA ANALYSIS FURTHER INFORMATION / REFERENCES Transfer the information on the individual record sheets to an electronic version, prefer- MARKET SURVEYS Broman KW, Woo KH (2017) Data organiza- Another way of collecting information about tion in spreadsheets. The American Statistician ably an Excel spreadsheet, as soon as possible. diversity from households is through the Surveys can also be conducted in local 72(1):2–10. documentation of local ‘foodways’ (Maundu The way in which the data are organized is im- food markets. Such surveys can help explore et al. 2013).  In this method, local community portant and will affect how they can be ana- Ellis SE, Leek JT (2017) How to share data for local food diversity as well as market systems members are invited to document their collaboration. PeerJ Preprints 5:e3139v5 lyzed (see Section 15: Data organization and including supply and value-chains. Every in- foodways in order to capture  food  diversity within local food systems over the seasons, analysis). Some helpful guidance can be found dividual household is likely to consume a mix Jarvis DI, Campilan DM (2006) Crop genet- and also the cultural aspects of food: its uses in Jarvis and Campilan (2006), Broman and of foods grown by themselves, gathered from ic diversity to reduce pests and diseases on-farm: and symbolic meanings and its relationship to the wild and procured from markets. Visiting Participatory diagnosis guidelines. Version I. Bio- Woo (2017) and Ellis and Leek (2017). health and nutrition.  a few local markets (main as well as small versity Technical Bulletin No. 12. Bioversity Inter- farmers’ markets) can help understand plant national, Rome, Italy. Foodways include the knowledge, practices, Where diagrams have been used to answer beliefs and other cultural aspects related to how questions, you will need to have developed and animal resources such as foods consumed Maundu P, Bosibori E, Kibet S, Morimoto Y et a community acquires, stores, prepares and uses in an area and import/export movements of agreed ways of converting the information to al. (2013) Safeguarding Intangible Cultural Heritage: its food. They also include describing gender the key food items and groups. data sheets (see Section 2.4: Agrobiodiversity a practical guide to documenting traditional food- aspects and seasonal dynamics. Documenting During market visits one can record what ways. Using lessons from the Isukha and Pokot com- foodways provides an understanding of how data). people acquire food (e.g. market, cultivation, is sold, sources of food items, price per unit, munities of Kenya (UNESCO). hunting, gathering), how it is prepared and The data provide an overview of agrobiodi- etc. These are not only observations, but da- Newing H (2011) Conducting Research in Con- processed, who prepares it, what tools are used, versity in a community. The data can be used ta are collected through interviews and con- when it is prepared, and who eats it. servation: Social Science Methods and Practice versations. An informal market visit is recom- to explore the extent and distribution of agro- (Routledge, Abingdon, UK). Foodway documentation in Gumuz region, Ethiopia. mended before carrying out a formal survey. Photo: Bioversity International / Y. Morimoto biodiversity as follows: C – number of land uses and access to pro- Market visits and surveys provide a quick overview of foods in each season and give an duction options understanding of how important each food is. D – richness and evenness of crop and vari- Information to record includes: ety diversity (Section 14) E – richness and effective population size of • Names of food items sold animal species and breeds (Section 10) • Food groups F – richness of wild species and their uses • Price per unit (Section 9). • Sources The data can also be combined for further • Type of sellers (see Annex 5.2). analysis of relationships between different Recording each food item by taking photos components of diversity and between diversi- is an effective way of clarifying the informa- ty and household or land-use features using, tion with key local informants after the mar- for example, multiple regression and multiple ket visit. Regular observations and measures factorial analysis. An example of this would be will capture the patterns in seasonal availabil- the relation between animal diversity (rich- ity of food diversity. ness and effective population size) and house- hold numbers or respondents sex. See Section 15 for further suggestions. Assessing Agrobiodiversity: A Compendium of Methods Section 5 - Household Surveys 30 ANNEX 5.1 A SAMPLE HOUSEHOLD SURVEY QUESTIONNAIRE SECTION D: CROP DIVERSITY INFORMATION (SPECIES AND VARIETAL) SECTION A: IDENTIFICATION AND VALIDATION INFORMATION 8. What cereal crops do you grow? (add extra rows as necessary) Questionnaire ID: _______________________________________________________________________ Site name: _______________________________________________________________________________ Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for Survey conducted by: ___________________________________________________________________ Species variety?**List all that name commercial seed* planted area production production Survey date: _____________________________________________________________________________ apply Survey checker: _________________________________________________________________________ Data of check: ___________________________________________________________________________ SECTION B: GENERAL INFORMATION 1. Village name: 2. Respondent’s name(s): 3. Respondent’s sex: Male/Female 4. Age (in years): 9. What root/tuber crops do you grow? (add extra rows as necessary) 5. Number of family members: Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for Male_____ Female_____ Children, under 15 years_____ Species variety?**List all that name commercial seed* planted area production production apply 6. Number of family members involved in farm work: Male_____ Female_____ Children, under 15 years_____ SECTION C: LAND-USE DIVERSITY AND PRACTICES 7. Land use type (add extra rows as necessary) Which wild areas are used (forest, Non- Are the fields in 10. What vegetables do you grow? (add extra rows as necessary) Homegarden Fruit Irrigated wetland, meadows, Pasture Agro-forestry Fishpond irrigated different parts of (Yes / No) orchard fields fishing grounds) fields the landscape? and for which Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for purposes? Species variety?**List all that name commercial seed* planted area production production apply Assessing Agrobiodiversity: A Compendium of Methods Section 5 - Household Surveys 31 11. What fruit do you grow? (add extra rows as necessary) E – LIVESTOCK DIVERSITY Reasons for choosing this 15. What type of livestock do you keep? (add extra rows as necessary) Variety Local or Source of Area Unit for Total Unit for Species variety?**List all that name commercial seed* planted area production production Uses: milk Number of Number of Is the number of Is the number apply Breed (1), meat (2), females of males of female animals of male animals Species name manure (3), and reproductive reproductive stable, increasing or stable, increasing other specify age age decreasing? or decreasing? 12. What oilseed crops do you grow? (add extra rows as necessary) Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for Species variety?**List all that name commercial seed* planted area production production apply F – USE OF WILD PLANTS 16. What wild plants do you use? (add extra rows as necessary) Habitat (forest, Main uses (food, medicine, fodder, Part(s) used (leaves, roots, shoots, Species (local name) meadow, near water) firewood, building materials) bark, flowers, fruits, seeds) 13. What legumes and pulses do you grow? (add extra rows as necessary) Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for Species variety?**List all that name commercial seed* planted area production production apply 14. What other crops do you grow? (add extra rows as necessary) ANNEX 5.2 A SAMPLE MARKET SURVEY QUESTIONNAIRE Reasons for choosing this Variety Local or Source of Area Unit for Total Unit for Species variety?**List all that name commercial seed* planted area production production Food groups(grains, Type of vendor apply Source Name of food vegetables, fruits, (whole sale, Gender of within or Photo item (species meat/poultry/seafood, Cost/Unit small retailer, the vendor outside of the number variety/breed) dairy, beans, eggs, permanent (M or F) community nuts, processed foods) vendor) *Source of seed: Maintained by yourself; obtained from a relative or neighbour in same community; obtained from a relative or contact from another community; obtained from market / commercial seed seller; obtained from extension service or government agency; obtained from NGO or from a seed fair **Reasons: High yield (Y), adapted to local soil (S), medicinal properties (M), cooking properties (C), drought- tolerance (D), etc. 6. FOUR CELL ANALYSIS Four cell analysis of mango diversity Photo: Tropical Fruit Tree Diversity Project. Assessing Agrobiodiversity: A Compendium of Methods 33 6. FOUR CELL ANALYSIS Four cell analysis (FCA) is a method for as- During the focus group discussion, the par- Note: Experience shows that when conduct- problems of the household survey – the sessing the abundance and distribution of crop ticipants develop a description of the impor- ing an FCA it is best to first draw one axis (many relationship between variety names used and varietal diversity in a community or land- tance or frequency of the crop or variety by households/few households) and obtain the re- by informants and their actual identity. scape. It is used to gather information about initially by stating how many farmers grow it. sults for this before proceeding to the second axis • The FCA allows for a discussion of the species and varietal diversity of crops or trees They then state whether a crop or variety is (large area/small area). reasons why a particular crop or variety has on farms and in home gardens or orchards. grown on large areas (or, in the case of trees, The cut-off point between many and few the distribution that it does. FCA is based on focus group discussions with in large numbers, if this is more appropriate) households or between large and small areas is community members. The groups can be or whether it is grown on small areas. This cre- • The results of an FCA may be influenced based upon the judgement of the participants mixed or separated by gender or age or accord- ates the four cells of the analysis (Figure 6.1). by a few dominant participants in the in the focus group discussion. As each crop or ing to other criteria of interest. When repeated focus group discussion. In contrast, the variety is discussed and placed in a particular over time, the analysis can give an insight into household survey allows individuals to Many Households Few Households cell, there should be some additional discus- changes in diversity in a specific area and can provide information uninfluenced by the Large Areas Large Areas sion as to why it is put there. This discussion be used to explore the reasons for any change views of others, or to share information will identify the particular traits that it has from the perspective of the farmer. With suit- that they might not share in a public and consider any other reasons that may affect able modifications, the FCA could probably be discussion. how widely it is grown (e.g. seed availability, used also for animals or other components of marketability, labour requirements). agrobiodiversity. 6.1 CONDUCTING A FOUR CELL FCAs may appear to provide similar infor- ANALYSIS FCA provides a way of assessing: mation to the crop and variety section of the • The FCA is conducted by a facilitator and The amount and distribution of diversity of household survey (Section 5: Household sur- a note-taker together with a mixed group of local crop or of varieties within a crop Many Households Few Households veys) but there are important differences. Small Areas Small Areas farmers. • Which crops or varieties are common, These include the following: • Participants: Invite 10–15 participants of unique, rare or endangered Lost varieties The FCA is a participatory exercise different genders, ages and diverse socioeco- • The characteristics (traits) of crops or that develops a consensus on how the nomic strata. Alternatively, conduct the exer- varieties that provide reasons for the group sees a crop or variety. It does not cise with separate female and male groups. observed distribution provide an accurate measure of richness Figure 6.1 The four cell analysis approach to assessing crop or varietal diversity or evenness as done by the household Materials: Drawing the four cell chart re- • Other factors encouraging or discouraging survey, but only a general idea. However, quires large sheets of paper, marker pens of dif- farmers to grow a certain crop or variety. During the focus group discussion, a fifth an FCA with knowledgeable participants ferent colours, stick-on papers (sticky notes) cell is often added that lists lost crops or lost While FCA can be used for both crops and can unearth information about rare and or cards of different colours. Alternatively, varieties of a specific crop. This allows the for varieties of specific crops, these should be lost varieties that may not be discovered the analysis can be carried out by marking out group to identify crops or varieties that used to done in separate exercises. Where varieties are through household surveys. the axes of the cells on the ground and plac- be grown in the area but that for some reason the focus of interest, only one crop should be ing the crops, varieties or symbols represent- are no longer grown. The group can discuss • The FCA allows the group to reach a discussed at one time. ing them in the different cells as the discus- whether these could or should be reintroduced. consensus on the identity of particular sion continues. varieties. This helps solve one of the Assessing Agrobiodiversity: A Compendium of Methods Section 6 - Four Cell Analysis 34 Ask participants to bring specimens of the Note: Before starting this exercise, the par- Step 1: Make a list of crops or varieties Step 4: Ask about lost varieties different crops or varieties to the venue where ticipants in the focus group must decide what the exercise is to be conducted, or organize a is meant by the categories ‘many households’, Ask participants about all the different After all the crops or varieties have been walk through the field sites where target crops ‘few households’, ‘large area’ and ‘small area.’ crops or varieties and write each name on a placed into one of the cells, ask participants or varieties are found before the focus group Generally, the category ‘few households’ is like- different card or sticky note. to name those varieties that are no lon- meeting. During the walk, specimens can ly to mean fewer than 10% of the households in Step 2: Draw the first axis (many ger cultivated in the community, and place be collected and placed in the different cells an area. households/few households) these varieties into a separate cell (See during the exercise. Figure 6.1). First, draw the vertical axis separating ‘ma- ny households’ from ‘few households’. Do Step 5: Collect descriptors of each not draw both axes in the beginning – this crop or variety is important because drawing both axes at For each crop or variety, ask the partici- the beginning leads to confusion and poor pants what its main distinguishing traits information gathering. are and what they like and dislike about it. Many Few Ask: Households Households ϐ Why is this crop/variety in this cell and For each card or specimen represent- not another one? ing a crop or variety, ask the participants ϐ What are the characteristics of this on which side of the axis the crop or vari- crop/variety? ety should be placed, i.e. grown by many ϐ What do you like about this crop/ households or grown by few households. variety? What is special about it? Step 3: Draw the second axis (small ϐ What do you dislike about this crop/ area/large area) variety? Some of this discussion will probably be Draw the horizontal axis separating ‘small part of Steps 1 and 2 when the crops or vari- area’ from ‘large area’ and ask the partic- eties are first listed and their distinguishing ipants into which cell each crop or variety characteristic described. falls. For each crop or variety, give the par- ticipants plenty of time to discuss before Step 6: Discussion they make a final decision. Discuss with participants how they feel Large Areas about crops being placed in their respec- tive cells and if they would like to undertake measures to increase the cultivation of rare varieties or crops. This can give important Many Few information about existing conservation ef- Households Households forts and the reasons for changes in diversi- ty patterns within a community. Four cell analysis of potato varieties grown in Coromata Media, the Lake Titicaca region, Bolivia. Small Areas Photo: PROINPA and Bioversity International, IFAD-NUS Project Assessing Agrobiodiversity: A Compendium of Methods Section 6 - Four Cell Analysis 35 6.2 DATA ANALYSIS Figure 6.2 Results of four cell analysis conducted in Coromata Media community, Bolivia. Source: PROINPA and Once transcribed, the data can be tabulat- Information from a group of villages can be Bioversity International, IFAD-NUS Project. ed to provide an estimate of the numbers of combined to explore particular questions such varieties in each category, as, for example, in as the local availability of alternative sources Figure 6.2. This shows the distribution of po- of seed of varieties that have been lost in some 2 varieties: 4 varieties: tato varieties grown by the Coromata Media villages, as in the example for different mil- Huayacha, Wila Imilla Chiji Pala, Janqu Pala, community in Bolivian Altiplano. The rela- let crops in the Kolli Hills of India (Table 6.2). Pala Morado, Wila Pala tively large number of varieties grown by a few Here, the little millet variety ‘Malliyasamai’ families in small areas is a common finding, has been lost in all villages except Puliyampatti, Many Households - Large Areas Few Households - Large Areas especially where the overall number of variet- which still grows a large area, while the foxtail ies of a crop is high. millet ‘Koranthinai’ is threatened throughout Many Households - Small Areas Few Households - Small Areas the area. A number of varieties are found only 9 varieties: 62 varieties: in small areas grown by a few households and Ayawiri, Chiyara Amajayu, Camara, Chiji Pala/Chixi, might therefore be considered threatened. Surimana, Chiyara Chiji Pitikilla/Chixi, Chiji Yurima, Chinito, Imilla, Chiri Luki, Janqu Chiyara Isla, Chiyara Surimana Largo, Chuquipitu, Cuchi Chiyara Taraco, Choclito, Chuquipitu Na- Callu, Muruku, Pitikilla iran Morado, Condor Piqui, Cuchi Jipilla, Rojo, Piñu Blanco Garri Blanco, Garri Rojo, Holandes, Sa- pallu, Holandesa, Huancu Callu, Janqu, Janqu Ajahuiri, Janqu Imilla, Janqu Pala, Janqu Piticalla, Janqu Polo, Janqu Sicha, Janqu Yurima, Kaisalla, Kaka Surimana, Kalla Pitikilla, Kealla, Koyu/Q óyu, Leke Cayu, Loka, Luki Taraco, Manzana Imilla, Morado Chuqipitu, Morado Kaisalla, Pala Morado, Pepino, Peruanito, Pureja Blanco, Queta, Sacampaya/Zaqam- paya, Sacampaya Negro, Saitu Luki, Sani Imilla, Sapallu, Tonko Puya, Tonko Puya Blanco, Wila Koyu, Wila Nairan Peruano, Wila pala, Wila Piñu/Phinu, Wila Surima- na, Wila Taraco, Wila Wislla, Wislla Paqui, Wislla Wislla, Yurima Lost varieties Papa Milagro Papa Criolla Morado Kullo Mandailing women assessing diversity and extent of collecting wild vegetables in four cell analysis, Sontang village, West Sumatra, Indonesia. Photo: L. Pawera Assessing Agrobiodiversity: A Compendium of Methods Section 6 - Four Cell Analysis 36 Table 6.2 Distributions of local varieties of minor millets in villages surveyed in Kolli Hills, India. Source: M.S. VARIETY VILLAGE Swaminathan Research Foundation and Bioversity International, IFAD-NUS Project. Padasolai Sempoothu Thirupuli valavu Oorpuram Puliyampatti Thuvarapallam Valukulipatti MH=Many households LA=Large area Kodo Millet (Paspalum scrobiculatum) FH=Few households Illangkelvaragu MH/LA MH/LA FH/SA - MH/LA - SA=Small area Panivaragu - - - - - FH/SA Perunkelvaragu FH/SA MH/LA MH/LA FH/LA Lost - Sattaikelvaragu - - Lost FH/LA - FH/SA Thirivaragu - - - - - Lost Little Millet (Panicum sumatrense) Karumsamai - - - - - Lost Kattavettisamai - - Lost Lost - FH/LA Malliyasamai Lost Lost Lost MH/LA Lost FH/SA Foxtail millet, Nepal. Photo: LI-BIRD/E. Palikhey Perumsamai FH/SA MH/LA Lost - - FH/SA Sadanjsamai MH/LA FH/SA - - - Lost Foxtail Millet (Setaria italica) Koranthinai - - - FH/SA FH/SA - Mookanthinai - - - - - Lost Palanthinai FH/SA FH / LA FH/SA - - Lost Senthinai - - - - MH/LA Lost 7. CHARACTERIZING CROPS AND CROP VARIETIES Rice varieties in a Karen community, San Din Daeng, Thailand. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 38 7. CHARACTERIZING CROPS AND CROP VARIETIES CONDUCTING A FOCUS GROUP DISCUSSION ON Crops and their varieties differ in appear- Common categories for uses of crops and CHARACTERISTICS OF CROP VARIETIES ance, taste and fragrance, tolerance to pests or their varieties are food, fodder, material for resistance to diseases, adaptation to soil type, building or other specific uses such as dyes, The aims of a focus group discussion (FGD) Participants: Invite 10–15 people of dif- time of seeding, date of maturity, height and cultural use in specific ceremonies or festivals, on characterizing crops and their varieties are ferent genders, ages and socioeconomic strata other properties – these make up their char- and medicinal. There are also important agro- to: to participate. Alternatively, conduct the ex- acteristics or traits. Each crop species and va- ecological uses such as green manure, erosion • Create an overview of the level of diversity ercise with separate female and male groups. riety has some unique traits, uses and values control, windbreak, firebreak and shade. of crops or varieties of major crops Women and men are known to have different for farmers, and these are sometimes reflect- preferences for crop traits. For example, wom- Characteristics or traits of crops and variet- ed in their local names. One of the best ways • Describe the characteristics of local en are often more interested in the cooking ies vary depending on the crop – traits of im- of describing and exploring these traits and varieties, including size, colours and yield and processing properties of crops and variet- portance for a rice variety are not the same as uses is through a focus group discussion. This ies than men. those that are important for a fruit or vegeta- • Characterize local varieties in terms of can be carried out as part of a four cell analy- ble variety. Examples of crop and variety traits: uses, values and traits Materials: Recording the information sis (Section 6: Four cell analysis) or may be do- ne separately. • Morphological: colour, size, height • Identify the positive and negative traits of gathered requires a large sheet of paper (chart particular crops or varieties. paper or brown paper), marker pens of differ- Collecting information about local names, • Agronomic: maturation time/earliness, ent colours, and stick-on papers (sticky notes) uses and traits of crops and crop varieties is competitiveness with weeds, yield In addition to these aims, other questions or cards of different colours. important to gaining an understanding of their can be discussed and more data can be collect- • Quality: storability, processability, market ed, depending on research questions. Ask participants to bring specimens of the agroecological, cultural, nutritional, economic value different crops or varieties to the venue where and other values and functions. Assessments The FGD is conducted with a facilitator, a the exercise is to be conducted or organize a of traits in a crop or varietal portfolio can also • Resistance to or tolerance of biotic note-taker and a mixed group of farmers (see help identify which important traits are miss- and abiotic stress: pest tolerance, walk through the field sites where target crops ‘Focus group discussions’ under Section 2.3: or varieties are found and collect specimens ing and could be (re)introduced. For exam- disease resistance, tolerance of drought or Data-gathering methods). for later discussion. ple, if all varieties of a crop are vulnerable to waterlogging, adaptation to poor soil drought, there may be a need to (re)introduce • Use related traits: flavour, nutritional or improve access to varieties that are drought qualities, smell tolerant. This list is not exhaustive; rather it is a guide of the kind of traits that are likely to be important to farmers that can be raised in a fo- cus group discussion. Farmer holding a variety of common bean (Phaseolus vulgaris), Sierra del Rosario, Cuba. Photo: G. Gullotta Assessing Agrobiodiversity: A Compendium of Methods Section 7 - Characterizing Crops and Crop Varieties 39 Step 1: Draw a table on a big sheet of paper (see the example in Table 7.1). Start with crops Step 2: Draw another table on a large sheet of paper with one column for each trait iden- that have the largest number of varieties. For example, rice. Then ask the participants to list tified in the previous step, and any other traits that the participants find important or that all rice varieties and add them to the table. Then, ask the participants to describe each vari- should be assessed for the research (see Table 7.2). ety. Add the information provided by the participants to the table. See Table 7.3 for an exam- Table 7.2 An example of table for scoring traits of varieties ple of a completed table. Traits Table 7.1 An example of data collection sheet Crop Variety Earliness Drought Flood Resistance Resistance Good Yield Other Crop Variety Local / Meaning of Positive Negative Other tolerance tolerance to disease to insects storage traits Commercial local name Description Uses traits traits notes Crop 1 Variety 1 Crop 1 Variety 1         Variety 2 Variety 2         Variety 3 Variety 3 Variety 4 Variety 4 Crop 2 Variety 1 Crop 2 Variety 1 Variety 2 Variety 2 Variety 3 Variety 3 Variety 4 Crop 3 Variety 1 Crop 3 Variety 1 Variety 2         Leave blank columns for traits that might be added during the discussion. Then ask the partic- Sorghum varieties, Kenya. Photo: Bioversity International/Y. Morimoto ipants to rate each variety for each trait. The easiest procedure is to use a scoring scale of poor, moderate or good (1-3 scale), but more-complex approaches may be useful for important traits or when the focus group wants to make clearer distinctions. For each variety, the facilitator asks ϐ Is this an early maturing variety? On a scale 1 to 3, how would you describe the earliness of this variety? ϐ Is this variety tolerant of drought? On a scale 1 to 3, how would you score the tolerance of drought of this variety? Step 3: Discuss further the importance of different traits. ϐ Which traits are the most important for the crop, variety or community? See Figure 7.1 for an example of the results of a scoring of rice varieties for different traits. The figure shows that the varieties have different traits. For example, some varieties are more drought tolerant than others. Overall, many varieties have low pest tolerance and disease resistance. Assessing Agrobiodiversity: A Compendium of Methods Section 7 - Characterizing Crops and Crop Varieties 40 DATA ANALYSIS Figure 7.1 Example of scoring for different traits of rice varieties in Sarawak, Malaysia.Source: Climate Change and Transfer the data collected from the discus- • Identify crops, varieties and traits of Indigenous Communities Project, PAR. sions to an Excel sheet. Information can be or- importance for specific problems (e.g. for 0 – very poor; 1 – poor; 2 – moderate; 3 – good. ganized and analyzed to: climate-change adaptation). • Describe uses and trait composition in See Section 15: Data organization and anal- farming systems ysis for more information on the analysis of • Understand which traits are important, traits and uses. and which traits encourage or discourage farmers to grow a variety Table 7.3 List of rice varieties, their uses and characteristics in San Din Daeng, Thailand. Type: paddy (P), hill rice cultivated in rotational fields (R) Meaning Variety Name Type Of Local Characteristics Uses Positive Negative Traits Traits Name Bu taj baux R   Grown in fallow Food, income, Hmong Soft peel, Cannot be land 3-5 years people like to buy good taste, stored longer than 1 year Bu htau laj R   Long leaf, long Strong stem, Hard seed, stem, long spike Family consumption no insects, need more easy to thresh time to cook Used to heal diarrhoea Black sticky in animals, special sweet Resistant to Each family Piv iv soo R Black seed made for children, given pests and grows not more rice to pregnant women and diseases than 1 bag of thin people, natural dye black rice Tasty, easy to Hard seed, Bu nemoo R Good smell Good smell Family consumption thresh, good need more smell time to cook Bu pox lox P Circle rice Seed is round Family consumption Easy to thresh Risks of insects Soft, large Risk of disease, Bu kweiv R Zebra Spike is black and white colour Family consumption seeds heavy spike that breaks easily Dirty rice, spike Bu ha P   darkish outside Family eating, feed to No diseases, white inside pigs and chickens tasty, strong stem 8. SEED SOURCES AND SEED NETWORKS Seed granaries, Mali. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 42 8. SEED SOURCES AND SEED NETWORKS 8.1 CONDUCTING A SURVEY OF SEED SUPPLY PRACTICES This section describes how to collect and • Explore whether the exchange of seed Describing seed supply and seed networks ϐ If maintained by yourself, what was analyse information on seed sources, access between individuals within a community is time consuming. Thus, it is best carried out the original source of the seed you are and exchange.1 The aim is to understand the constitutes a network on only one or two major staple crops. The using? local seed system – how farmers obtain and • Identify varieties that are private survey may be carried out as part of the larg- maintain the seeds and other planting materi- (maintained by individual farmers and er household survey (see Section 5: Household ☐ Always yourself als of the crop varieties that they use. never exchanged) and why this is (practical, surveys). ☐ Relative or neighbour in the same The information obtained answers ques- cultural or other reason) For the selected crop, ask about the seed community (gift, exchange, purchase) tions about: • Investigate whether there are differences source of each variety named by the farm- • The overall availability of seed and the in the ways that men and women or er during the household survey and about the ☐ Relative or contact from another different sources of supply that farmers use wealthy and poor farmers access seed for original source of seed. community (gift, exchange, purchase) • different crops The relative importance of different ϐ What is the source of the seed you have ☐ Market/commercial seed seller sources of supply for different crops and • Find out who is important in maintaining planted? varieties seed flows or in supplying a range of ☐ ☐ Extension service or government Maintained by yourself from a crop • varieties agency (gift, purchase) The extent and importance of local seed you have grown in the past (self) exchange networks • Assess rates of turnover of seed stocks and ☐ NGO (gift, purchase) • thus how much the system is changing ☐ Relative or neighbour in the same The identity of key individuals – sometimes over time community (gift, exchange, purchase) called nodal farmers or custodian farmers – ☐ Seed fair in maintaining crop and varietal diversity. • Identify the main constraints to seed ☐ Relative or contact from another ϐ When did you obtain the seed? availability and ways of strengthening Information on seed sources, maintenance, community (gift, exchange, purchase) access to diverse varieties or new materials. access and exchange can be used to: ☐ You always had it • The information collected should take ac- ☐ Market/commercial seed seller Describe the types of exchange mechanisms count of age, gender and other relevant factors ☐ This year that occur – who is involved and whether that may affect access to or provision of seeds. ☐ Extension service or government these are gifts, sales or exchanges agency (gift, purchase) ☐ Last year • Note: Questions about seed management may Identify crops and varieties for which be sensitive. Individual farmers may not want to ☐ NGO (gift, purchase) ☐ In the last two to five years exchange between different actors is an be completely open about seed sources for cultur- important part of their evolution and al or other reasons. ☐ Seed fair ☐ More than five years ago management 1 The term ‘seed’ is used throughout to refer both to true seed and to other types of planting materials such as tubers, offsets or cuttings. Assessing Agrobiodiversity: A Compendium of Methods Section 8 - Seed Sources and Seed Networks 43 DATA ANALYSIS After transferring the answers from the them, others were always obtained from mar- Figure 8.1 Seed sources for different Bambara groundnut (Vigna subterranea) varieties reported by farmers household survey to an Excel spreadsheet the kets, while still others were obtained from a surveyed in Sikasso and Segou regions of Mali. Source: Institut d'Economie Rurale and Bioversity International, IFAD-EU NUS Project. data can be analysed in various ways. For ex- number of different sources. The proportion ample, the results can be compiled to deter- of farmers using the different seed sources can mine the ways in which seed of each variety also be calculated as in Table 8.1. Other anal- is accessed by the community as in Figure 8.1 yses can be carried out to explore differenc- for Bambara groundnut (note: in this example, es between gender or age with respect to seed the investigators added a category for seeds sources, or turnover (e.g. how often has a vari- obtained from relatives). Some varieties were ety been exchanged or obtained from a market maintained entirely by the farmers that grew over the last five years). Table 8.1 Seed sources for fonio (Digitaria exilis) reported by farmers surveyed in Sikasso and Segou regions of Mali. Source: Institut d'Economie Rurale and Bioversity International, IFAD-EU NUS Project. Seed source Number of farmers with seed source Own production 85 Relative 28 Other villages 24 Market 34 Relative Farmer in the village Market Diversity Field Own Production Farmer from another NGO village Fonio (Digitaria exilis) seeds. Photo: Bioversity International NUS Community Assessing Agrobiodiversity: A Compendium of Methods Section 8 - Seed Sources and Seed Networks 44 8.2 DESCRIBING LOCAL SEED NETWORKS Seed network studies provide information on the flow of seeds within a community and on the DATA ANALYSIS Comparing seed networks importance of specific individuals in the community as sources of seeds. The information can be These maps can be used to compare seed obtained through a three-stage interview process illustrated in Figure 8.2 and explained below. Data about seed sources and modes of ex- networks between communities, for different change can be used to draw maps that show crop species or varieties and between past and the seed flows (Figure 8.3). Combine all the in- Figure 8.2 Respondents for a three-stage interview process to identify seed flows present seasons for a particular crop/variety. formation on the different varieties and map For example, Figure 8.3 shows seed networks the connections. Before starting to draw the for rice in two different communities in Nepal, 1st stage respondents map, identify the nodal farmers. These are 10-20 individuals from Kaski and Begnas. In Kaski, an upland commu- different households, 2nd stage respondents 3rd stage respondents the individuals who were named most fre- individuals identified nity with large numbers of traditional rice va- obtained from individuals identified as seed source by the quently as seed sources. Decide on a minimum stratified random as seed source by the rieties, exchanges are frequent and there is a 1st stage respondents 2nd stage respondents number of times a farmer must be mentioned sampling rich and highly developed network creating in order to qualify as a nodal farmer. constant flows of seed of important varieties This visual seed network representation within the community. In Begnas, a commu- shows how many seed sources and different nity with fewer traditional varieties, there are modes of exchange are present for each vari- fewer exchanges and the networks are poorly Step 1: First-stage interview ety, who are the nodal farmers, whether there developed. This may be the result of a great- are many exchange points and how diverse the Identify 10–20 first-stage respondents through stratified random sampling (see ‘Probability er use of modern varieties obtained from com- modes of exchange are (e.g. a variety may on- sampling’ under Section 2.5: Sampling strategies and sample size). mercial sources. For more information on how ly be sold, or may be both sold and exchanged to analyze the results of seed network studies, Ask each first-stage respondent the following questions for each variety they have sown this for other goods). see Ricciardi (2015), Subedi et al. (2003) and season: Thomas et al. (2015). ϐ From whom did you receive the seeds of this variety for this season? ϐ Was it as a gift, exchange or purchase? ϐ Now ask the same questions for the seed of each variety sown in the previous season. Table 8.2 Sources of seed for each variety sown by each first-stage respondent in the current season and previous season List seed sources for each respondent and each variety in a table like Table 8.2. This Season Previous Season Step 2: Second-stage interview Farmer Variety Traditional or modern Source (farmer Made of Source (farmer Made of Interview farmers who were named as a seed source by the first-stage informants. Ask each of name or other exchange name or other source) source) exchange them from whom (s)he took seeds of the variety identified in the first-stage interview. Repeat the questions for the previous season and enter the information separately (see table 8.2). Step 3: Third-stage interview Ask the same questions of farmers who were named as seed source by the second-stage informants. Assessing Agrobiodiversity: A Compendium of Methods Section 8 - Seed Sources and Seed Networks 45 Kaski Begnas i lips ul C l s hin a 4 i a n 4, Ph N. M Man 4 i a . Ch ina s h ula K C S. China 4 Chin a 4 M ro N. Masula Sabitri N Sa . . M a N asula nsu J l a i 4 Chandina 8 ya haite K C . Ma asula C nsuli N. a l Ma asu h nsuli Mansuli, M M an S. d Masula ina Jaya B S G 14 Masula . Ma 4 n 2 ya su a li J Masula ula S. Mansuli S. Mansuli Mas uli hina 4 s Masula Man C S. i Masino tmur ina Pokhrel Mu Masula Chand Ch 4 in na a 4 Chi ram a Fa Masul K R. Mansuli . M C R. Mansuli a h n in 1 S a . s M Sab u it li a 4 4 Faram 7 ansuli i S ri hin Masula C jh a C h La b i i n tr a i Sa ansuli 4 Sabitr China 4 bitri S. M Jiri S. bi Man suli Ma i ja s n s Pan u u li a la N. M S. M n asula uli China 4 isio S. M ns lev ansuli K. Ma Te a R. Mansuli N. Mansuli Ba Chandin uli sma ns ti Ma . N S . Ma C n han asula li su d u li in M s ya a n Ja S. Ma ya S a okan Jaya a Television J S din . Mansuli Ja a han ansuli y ro a Jay a Sabitri C . M Pu SS s . a N Jaya Ja Ch ya in B a 4 a S. Mansuli smat Jaya i B 4 a 4 P 4 h n i ı llip h s M Masula C as S. Mansuli 2 ula Mansuli Chaite S China 4 . Man ar s s u i li sul Sab Lal an it S. M ri Chaite 2 Masula Figure 8.3 Maps of seed networks for rice in two communities in Nepal: Kaski and Begnas. Arrows show direction of seed flows and exchange mode (exchange, purchase, borrow, trial, gift). The variety name is given above the Exchange Purchase Borrow Trial Gift arrow. Source: Subedi et al. (2003) China 4 China 4 S. Mansul abit ri i S Ch S ina Ra a 4 n bitr C i h i i P n J a a 4 n a k y a a j hina 4 C China 4 Mansuli Phillips Masula BG 1 M 4 a4 s 2 ula Radha 32 la Masu Masula i C S. Mans ul S h. M ina a n 4 suli China 4 China 4 S. Mansuli K. M Masulaansuli K. Mansuli Sabitri Sabitri Masula Jaya N. Mansuli Sabitri Jaya Dipahiya Jaya Chandina Mansuli China 4 N. Mansuli China 4 China 4 S. Mansuli i K. Ma nsul sulin R. M a sula Ma la Masu li nsu . M a S uli ina 4h S. s C Ma n ns a uli S. M 44 S. Ma nsuli B ati asm B nsu li Ma Jaya asul a M China 4 abit ri S a 4N. Masu hin la C Sabitri asul a M a 4 Chin K. Mansuli itri 4 Sa b hin a C ani aj R k Pan Assessing Agrobiodiversity: A Compendium of Methods Section 8 - Seed Sources and Seed Networks 46 8.3 FOCUS GROUP DISCUSSION ON SEED SUPPLY A focus group discussion (FGD) provides ☐ Extension service or government An FGD can also create a diagram of seed FURTHER INFORMATION/ an opportunity to obtain general information agency (gift, purchase) supply practices using the following approach. REFERENCES on seed availability and seed quality of differ- ☐ NGO (gift, purchase) The facilitator draws squares representing On seed systems in general: ent crops and varieties in the community and ☐ Seed fair the individuals participating in the FGD on a can be used when time is limited or a full-scale Almekinders C, de Boef W (2000) Encourag- large sheet of paper and writes their names in household survey is not undertaken. ing Diversity. The Conservation and Development of ϐ Which farmers can supply seeds of this each square. These squares are arranged in a Plant Genetic Resources (Practical Action Publish- The FGD on seed supply can be combined variety? big circle around the sheet of paper. ing, Rugby, UK). with the four cell analysis (Section 6). Once the ϐ Is it readily available, usually available Each farmer then tells the group the to- Hodgkin T, Rana R, Tuxill J et al. (2007) Seed varieties have all been identified and placed in or difficult to obtain? tal amount of seed (s)he used this season and systems and crop genetic diversity in agroecosys- the different cells, start with the common vari- tems. Managing Biodiversity in Agricultural Ecosys- ϐ What are the limitations on availability writes that in their square. eties grown in large areas and for each variety tems, ed. Jarvis DI, Padoch C, Cooper HD (Bioversi- ask the following questions: (e.g. lack of seed, high cost)? The facilitator then asks each farmer to ty International, Rome/Columbia University Press, New York, USA). draw a set of circles around their square for ϐ Where can you get seed of this variety? ϐ Are there problems with seed of this variety (e.g. poor quality of seed, each way in which they obtained the seed and Jarvis DI, Sevilla-Panizo R, Chávez-Servia JL et ☐ Maintained by yourself from a crop identity not reliable, not available when indicate the amount they obtained from each al. eds (2005) Seed Systems and Crop Genetic Diver- sity On-farm, Proceedings of a Workshop, 16–20 Sep- you have grown in the past (self) needed)? source and varieties involved. tember 2003, Pucallpa, Peru (IPGRI, Rome). ☐ Relative or neighbour in the same Try to be as specific as possible and ask The facilitator can then ask for additional Pautasso M, Aistara G, Barnaud A et al. (2013) community (gift, exchange, purchase) for individual farmers’ opinions and then see information to add to the picture, such as the Seed exchange networks for agrobiodiversity con- ☐ Relative or contact from another if there is a consensus. Prepare a data sheet identity of a known seed supplier in the com- servation. A review. Agronomy for Sustainable De- munity who is not at the FGD meeting. velopment 33:151–175. community (gift, exchange, purchase) summarizing the information on each variety ☐ (Table 8.3). Market/commercial seed seller Once these steps have been completed, the On collection and analysis of seed system facilitator can annotate the diagram with lines information: and arrows connecting suppliers of seed to Ricciardi V (2015) Social seed networks: iden- recipients. tifying central farmers for equitable seed access. Agricultural Systems 139:110–121. Table 8.3 Table for recording farmers’ opinions on aspects of seed supply in their community Subedi A, Chaudhary P, Baniya BK et al. (2003) Variety Source Farmer Sources Availability Problems With Who maintains crop genetic diversity and how? Seeds Implications for on-farm conservation and utiliza- tion. Culture and Agriculture 25(2):41–50. Variety 1     Thomas M, Verzelen N, Barbillon P et al. (2015) Variety 2     A network-based method to detect patterns of lo- cal crop biodiversity: Validation at the species and Variety 3 infra-species levels. Advances in Ecological Research 53:259–320. Variety 4     Local herbalists looking for medicinal plants in the Turkestan Range, Kyrgyzstan. Photo: L. Pawera 9. USES OF WILD PLANTS Assessing Agrobiodiversity: A Compendium of Methods 48 9. USES OF WILD PLANTS 9.1 COLLECTION OF DATA ON THE USE OF WILD PLANTS Wild plants continue to be an important of local wild plant resources and their uses. FOLK CATEGORIZATION AND FOLK FREELISTING part of the human diet, and have cultural, me- Interviewing key informants is the best ap- TAXONOMY dicinal and economic values for local commu- proach when the objective of the study is to In freelisting, informants are asked to list, nities. Many wild species are actively man- document as much knowledge as possible in a Communities often have specific terminol- for example, all wild food plants that people aged to a greater or lesser extent. The use of short time or to document rapidly disappear- ogies and ‘folk categories’ for wild food plants, in their community use and their answers are wild plants is studied using ethnobotanical ing traditional knowledge. wild vegetables, forest medicines, etc. (see al- noted in the order in which they are given. It approaches – a combination of anthropolog- so Local names and classification systems in is a simple and effective method for capturing Often, certain knowledge is held by special- ical, ethnographic, botanical and ecological Section 2). One of the important decisions for a large amount of traditional knowledge, and ist ‘custodians of knowledge’. For example, approaches (Martin 2004, Albuquerque and the study will be whether to categorize plant for quantifying plants’ cultural importance this is the case with medicinal plant knowl- Alves 2016). Such studies can help to: uses according to folk categories (this would (Quinlan 2005). The ease of freelist interview- edge, which is commonly maintained by herb- be a more emic and culturally-sensitive point • ing makes it ideal for collecting ethnobotani- Describe culturally important species and alists, traditional healers or shamans. In this of view) or to follow scientific categorization cal data from a large sample. their uses case, the method employed for selection of of plant uses, such as the Economic Botany • The assumptions of the freelisting method: Assess the sustainability of harvesting informants will be purposive (targeted) sam- Data Collection Standard (Cook 1995). The lat- pling or snowball (chain-referral) sampling • ter would be a more etic or scientific approach, • More commonly used items are cited by Identify species that could be domesticated (Tongco 2007; see also ‘Non-probability sam- and is more widely used in the international more people (frequency of citation) or included in breeding programmes pling’ in Section 2.5: Sampling strategies and context and for comparative purposes. Emic • Identify underutilized species, or those sample size). • Informants tend to cite more important perception is that of the community, while et- items earlier in the list (position in the list) with the potential to contribute to When study participants are chosen us- ic perception is an external (scientific) point nutrition, climate-change resilience and ing purposive or snowball sampling, the re- of view. • A more knowledgeable person will give other aspects of community well-being sults cannot be extrapolated as a finding for a longer list than a less knowledgeable • Determine changes and dynamics of the whole community. If the study aims to as- person (number of listed plants) traditional knowledge over time sess knowledge and plant use across the whole Thus, freelisting will indicate: community, use a household survey (Section • Enable intracultural and cross-cultural 5: Household surveys) that uses a stratified • What items belong to a particular domain comparison of traditional knowledge. random sample of informants. (folk categorization) Information about the use of wild plants is • What items are the most important in that most commonly collected through interviews domain (cultural importance) with local people, but may also be collect- • Who is most knowledgeable about the topic ed through focus group discussions or house- (number of items an individual informant hold surveys. Because not everyone has the lists). same knowledge of wild plants, their uses, lo- cations and harvesting, it is important to iden- tify key informants – those with knowledge Etlingera elatior (also known as torch ginger), Fiji. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 9 - Uses of Wild Plants 49 Freelisting is conducted with the minimum ETHNOBOTANICAL QUESTIONS Table 9.1 Tabulation of basic ethnobotanical data of 30 informants, but gives better results with 50 or more informants. Individual informants The freelisting method results in lists of Scientific Local Plant Place plant Food part Main local Other uses of Availability are asked to list all plants they know (or use) plants known to or used by the community for names names category used uses collection of plant in a particular category (e.g. wild food plants different purposes. Additional questions are used, fruits consumed, medical plants used for needed to find out about the different aspects Medicine Mature fruit for gastrointestinal disorders). of local knowledge and use. Fruit Fruit eaten raw stomach Forest 4 ache For wild food plants, the interviewer asks: Go back to the list of plants, and ask the fol- lowing questions about each plant: Cocos Mature fruits What wild food plants do you know? 2 nucifera Kelapa Fruit Fruit pressed to obtain ϐ Does the plant have other local names? The freelist for one informant may look like cooking oil If so, note down all plant names. this: Young leaves Material for ϐ What part(s) of the plant do you use Vegetable Leaf eaten raw making a Kangkung air brush (bark, root, flower, leaves…)? Bayam liar Aerial part Daun kelor ϐ What is the mode of preparation or Ipomea Kangkung Vegetable Leaf and boiled or stir- No River 2 Rimbang administration (infusion, decoction, aquatica liar, Lara stem fried Keladi raw, cooked…)? Mangga hutan ϐ Where do you gather it (e.g. near to Kapunduang river, in forest, on fallow land, in home Depending on study objectives, this would garden, in rice field)? Pressing plant specimen of wild vegetable Claoxylon longifolium in Sontang village, West Sumatra, Indonesia. then be followed up with separate questions Photo: L. Pawera ϐ How available is this plant (i.e. use a for other use categories, e.g.: scale from 1 to 5, where 1 is rare and 5 is What medicinal plants do you know? highly abundant)? What wild fodder plants do you know? ϐ Does the plant have some other uses beside the main use (medicine, spiritual What wild plants do you know that can use, technical material, and others)? be used for firewood? Additional questions can provide infor- What wild plants do you know that can mation on a plant’s economic value, season- be used for construction? al availability, time or distance to collection place, source of knowledge, quantity collected or frequency of use. The answers can be tabu- lated as in Table 9.1. 2 The list of plants given will depend on the exact question asked. For example, if informant is asked “Which wild food plants do you use?”, the list of used plants will be shorter than if we ask for known plants. Assessing Agrobiodiversity: A Compendium of Methods Section 9 - Uses of Wild Plants 50 9.2 DATA ANALYSIS DIVERSITY OF USED WILD PLANTS • The total number of species known by the SALIENCE INDEX community. Information about wild plants is usual- The salience index is a value expressing the cultural significance of freelisted items. The sa- ly organized by species, indicating their us- USE REPORT lience index (of one item) is calculated using the following formula: es and the number of informants who men- inverted rank tioned them. Basic analysis includes the or- The most basic step towards quantifica- Salience = Index tion of ethnobotanical information is to con- number of all items in the list ganization of data into the botanical fami- lies, genera, and species they belong to, and vert the collected data on plant uses into use where rank is the position/order of the plant in the freelist. some of the following calculations: reports. Generally, one use report is when one The composite salience for all informants can be calculated by summing the individuals’ sa- • The total number of useful species informant mentions the use of one species in lience scores and dividing the result by the number of informants (Table 9.3). one use category. For example, in a study of • The number of species per botanical wild food plants in the White Carpathians in A free software (Anthropac; Analytic Technologies, Inc. http://www.analytictech.com/an- family the Czech Republic (Pawera et al. 2017), the thropac/anthropac.htm) is available for analysing large freelist datasets. • The number of species per use category first informant stated that they used elderber- • The most commonly used wild species ry (Sambucus nigra) as follows: Table 9.2 Analysis of freelist from one informant based either on the number of times a • Mature fruits for jams, preserves or Fruit Rank Inverted rank/no. of all Salience index (order in the list) items species is cited in freelisting or on the marmalade (category 'Fruits') percentage of informants who cited the • Kangkung air Flower for tea (category 'Recreational 1 5/5 1 species. beverages') Bayam liar 2 4/5 0.8 The data can be further analyzed to cal- • Flowers coated in batter and fried Daun kelor 3 3/5 0.6 culate quantitative ethnobotanical indices, consumed as a snack (category 'Others'). Rimbang 4 2/5 0.4 such as use reports, salience index, use val- This informant thus gave the species three Keladi ue or cultural importance index (see below). 5 1/5 0.2 use reports. In the whole study, which in- These indices show the importance of par- volved 65 informants, Sambucus nigra was re- Table 9.3 Analysis of freelists from two informants ticular species in the community. ferred to as being used in five different food categories and obtained a total of 71 use re- Fruit Informant 1 Informant 2 Total Salience Composite STATUS AND DISTRIBUTION OF Salience ports. The number and percentage of use re- PLANT KNOWLEDGE IN THE ports for particular use categories or for bo- Kangkung air 1 0.2 1.2 0.6 COMMUNITY tanical families indicate the importance of Bayam liar 0.8 0.6 1.2 0.6 To understand the distribution of knowl- that use category or plant family. For instance, Daun kelor 0.6 0.4 1 0.5 edge in the community and traditional in the White Carpathians study, the highest Rimbang 0.4 1 1.4 0.7 knowledge richness, calculate: share of use reports (31%) was recorded for the • The average number of species mentioned category 'Fruits'. Keladi 0.2 0.8 1.0 0.5 per informant • The average number of species mentioned in particular use categories per informant Assessing Agrobiodiversity: A Compendium of Methods Section 9 - Uses of Wild Plants 51 Table 9.4 Example of final Family, Species Local Name Habitata Food Categoryb Parts Used And Mode Of Use Use Use Actual ethnobotanical table with wild Report Value Usec food plants used traditionally in the White Carpathians, Czech Alliaceae Republic. Planá Leaves eaten raw on the bread, added to soups, scrambled Source: Pawera et al. (2017) Allium vineale AN VEG 5 0.08 ++ pažitka eggs Allium scorodoprasum Planý/divoký česnek ME/AN SEA Bulbs as garlic substitution 2 0.03 VEG Leaves eaten raw, added to salads 27 ++++ Medvědí česnek, Allium ursinum FO Hadí česnek, Česnečica SEA Fresh/dried leaves added to sauces and soups 4 0.54 ++++ ALC Fresh leaves with honey and wine for preparation of liqueur 1 + Apiaceae Aegopidum Bršlice AN VEG Leaves stir-fried a few minutes as a spinach 2 0.03 - podagraria Seeds for seasoning dishes, soups and added to homemade Carum carvi (Planý-) Kmín, Kmínek ME SEA 17 0.28 ++ saveloys Asteraceae Flowers and leaves eaten raw, on the bread or added to AN VEG 23 +++ Bellis perennis Sedmikráska, Chudobka soups/salads 0.42 REC Flowers for recreational tea 2 Carlina acaulis Myslivecký chléb, Pupava, Bodláček ME VEG Receptacles eaten raw 11 0.18 + AN REC Dried grounded roots as a coffee substitution 6 - Cichorium intybus Čekanka 0.12 VEG Flower buds loaded in oil 1 - Matricaria discoidea Heřmánek AN REC Flowers for digestive herbal tea 3 0.05 + OTH Flowers boiled with sugar to prepare honey 21 +++ Taraxacum sect. Ruderalia Pampeliška, Půpava, Pléška AN/ME VEG Leaves added to salads/eaten directly 18 0.70 ++++ Kirschner, H.Øllg. & Štěpánek REC Dried grounded roots as a coffee substitution, flowers for tea 3 - ME CHS Stem sucked/eaten for sweet sap 7 - Tragopogon orientalis Kozí brada 0.13 VEG Roots eaten boiled 1 - Tussilago farfara Podběl, Pupava AN/AQ REC Flowers for recreational tea 2 0.03 + Balsaminaceae Impatiens parviflora Oříšky AN/FO FRU Seeds eaten raw 2 0.03 + Boraginaceae FO CHS Flowers sucked 2 - Pulmonaria officinalis Medunica, Bedrnica, Medrnica 0.05 VEG Leaves eaten raw 1 - Kostival, Černý kořen, Černyj kořeň, Symphytum officinale AN/MEA/ CHS Flowers sucked 2 0.03 - Medunica AQ a habitat-gathering environment: AN-Anthropic (villages/homegardens/crofts/orchards/fields/roads); ME - Meadows/pastures; FO - Forests (oak forest/oak-hornbeam/beach forest/spruce forest), AQ-Aquatic (swampy area on the pond/stream bank) b food category: FRU-Fruits (including fruit kernels and seeds); VEG-Vegetables; SEA-Seasoning plants; REC-Recreational beverages; ALC-Alcoholic beverages; CHS–Children’s snacks; OTH-Others c actual use where: - expresses only historical use; + rare use; ++ occasional use; +++ common use; ++++ very frequent use Assessing Agrobiodiversity: A Compendium of Methods Section 9 - Uses of Wild Plants 52 USE VALUE AND CULTURAL interviewed. The plant species with high ver- account only listed plants while the other two al- CROSS-GROUP COMPARISON IMPORTANCE INDEX satility of uses (use in more categories) and so reflect the diversity of plant uses. high frequency of citations will have a high Where research aims to compare the diver- To assess the cultural importance of partic- Table 9.4 gives an example of a table with use value. sity of useful plants or the similarity of plant ular plant species, one can calculate a quanti- ethnobotanical information for food plants, uses across communities or ethnic groups or tative ethnobotanical index such as use value The cultural importance index is calculat- which includes the number of use reports (UR) from different areas or sections of the commu- (Phillips and Gentry 1993) or cultural impor- ed as: and use value (UV). The table shows 15 species u i nity, an index such as the Jaccard index can be NC NC tance index (Tardío and Pardo-de-Santayana UR that belong to five families. UV and UR val- CI = ∑ ∑ ui applied (González-Tejero et al. 2008). s 2008), which take into account frequency and N ues show that some species, such as dandelion u=u1 i=i1 (Taraxacum), are more used than other plants. Jaccard Index = [C/(A + B − C)] × 100 diversity of species uses. Where u is use, i is an informant, NC is the In total, dandelion obtained 42 UR and it can Where A is the number of species in sample The use value (for one species) is calculat- total number of use categories, N is the num- be considered the most culturally important A, B is the number of species in sample B and C ed as: ber of informants and UR is a user report. wild food plant species as demonstrated by the is the number of species common to A and B. A Use value (UV)=U/N Note: The difference between the compos- highest UV (0.70). high Jaccard index value indicates a similarity Where U is the number of use reports cit- ite salience index and the use value index or cul- between the groups compared. Alternatively, ed by all informants for a given plant spe- tural importance index is that the first takes into a visual illustration of similarity can be made cies, and N is the total number of informants by using a Venn diagram that shows overlaps Dried purple and white hibiscus flowers in gourd bowls, Mali. of plant species among the groups compared Photo: D. Mijatović (Figure 9.1). Tien Shan Pamir Alay Achillea Millefolium Bunium Persicum 140 25 90 Cichorium Intybus Hippophae Rhamnoides Hypericum Perforatum 11 Peganum Harmala 17 Plantago Major 17 Punica Granatum Rosa Canina 58 Urtica Dioica Zea Mays Pamir Figure 9.1 A Venn Diagram for medicinal plant species used in major Central Asian mountain systems. Source: Pawera et al. (2016) Assessing Agrobiodiversity: A Compendium of Methods Section 9 - Uses of Wild Plants 53 NUMBER OF PREPARATION METHODS AND PLANT PARTS USED FURTHER INFORMATION / REFERENCES In order to understand in more detail how local people use plants, it is common to assess the Albuquerque UP, Alves RRN eds. (2016) Intro- Phillips O, Gentry AH (1993) The useful plants proportion of used plant parts (e.g. fruits, seeds, leaves, roots) (Figure 9.2), or by mode of prepa- duction to Ethnobiology (Springer, Switzerland). of Tambopata, Peru: I. Statistical hypotheses tests ration (e.g. use raw, dried, decoction, tincture) (Figure 9.2). with a new quantitative technique. Economic Bota- Anderson EN, Pearsall D, Hunn E, Turner N ny 47(1):15–32 eds. (2011) Ethnobiology (John Wiley & Sons Inc, Preserved 1% New Jersey, USA). Quinlan M (2005) Considerations for collecting Infusion 37% Tincture 2% freelists in the field: examples from ethnobotany. Cook FEM (1995) Economic Botany Data Collec- Powder 2% Field Methods 17(3):219–234 tion Standard (Royal Botanic Gardens, Kew, UK). Smoke 3% Reimers EAL, Cusimamani EF, Rodríguez EAL Paste 2% Cunningham AB (2001) Applied Ethnobotany: et al. (2018) Ethnobotanical survey of medicinal People, Wild Plant Use and Conservation (Earthscan, plants used in Zacatecas state, Mexico. Acta Soci- Abingdon, Oxford, UK). etatis Botanicorum Poloniae 87(2):3581 González-Tejero MR, Casares-Porcel M, Sán- Tardío J, Pardo-de-Santayana M (2008) Cul- chez-Rojas CP et al. (2008) Medicinal plants in tural importance indices: A comparative analysis Decoction 11% the Mediterranean area: Synthesis of the results based on the useful wild plants of southern Canta- of the project Rubia. Journal of Ethnopharmacology bria. Economic Botany 62(1):24–39 116(2):341–357 Tongco MDC (2007) Purposive sampling as a Fresh 25% Dried 16% Martin GJ (2004) Ethnobotany: A Methods Man- tool for informant selection. Ethnobotany Research ual (Chapman and Hall, London, UK). and Applications 5:147–158. Figure 9.2 Example of medicinal species proportion according to the mode of preparation in Turkestan Range, Kyrgyzstan. Source: Pawera et al. (2016) Pawera L, Verner V, Termote C et al. (2016) Medical ethnobotany of herbal practitioners in the Bulb and root 9% Turkestan Range, southern Kyrgyzstan. Acta Soci- Whole plant 11% etatis Botanicorum Poloniae 85(1):3483 Tincture 2% Pawera L, Łuczaj Ł, Andrea Pieroni A, Polesny Seed and Z (2017) Traditional plant knowledge in the White Fruit 12% Carpathians: Ethnobotany of wild food plants and crop wild relatives in the Czech Republic. Human Ecology 45(1):1–17 Flower 9% Bark 5% Stem 9% Leaf 43% Figure 9.3 Example of proportion of medicinal plant uses according to the plant parts used in Zacatecas state, Mexico. Source: Reimers et al. (2018) 10. DIVERSITY OF DOMESTICATED ANIMALS AND BREEDS Seasonal water point on Hawas river where salty spring water mixes with fresh water, believed to have medicinal properties, Ethiopia. Photo: P. Viesi Assessing Agrobiodiversity: A Compendium of Methods 55 10. DIVERSITY OF DOMESTICATED ANIMALS AND BREEDS Thousands of breeds of domesticated an- • The population sizes of the different imals exist in diverse pastoral, mixed crop– breeds or species held by individuals and livestock and other production systems around by the community. the world. This high diversity of breeds is a re- The data obtained from this can be ana- sult of interplay between biological, environ- lysed to determine the effective population mental and cultural factors. Local breeds have size of the different breeds and domestic an- unique cultural, social and ecological values. imal species in the community (see 10.2: Data They may have characteristics such as dis- analysis). ease resistance and adaptation to local envi- ronments. The management of local breeds is Additional information on animal diversi- linked to specific land-use or governance sys- ty is best obtained from key informants and tems. Pastoralists have developed unique ad- through focus group discussions using the aptation mechanisms to survive in harsh con- Local Livestock for Empowerment of Rural ditions, one of which is seasonal migration. People (LIFE) protocol approach.3 This pro- They often have an extensive knowledge of lo- tocol was developed to study aspects of local cal plants for such needs as ethnoveterinary breeds beyond their population size and pro- medicine and for meeting the requirements of ductive performance of individual animals. animals at different stages of their life cycles The adapted version presented here is de- as well as knowledge of the environments they signed to gather information on: inhabit. • Characteristics of local breeds Cultural importance and adaptation to the The Karrayyu-Oromo pastoralists reside in the local environment are among the most im- • Social, cultural and ecological aspects of fringes of upper Awash valley, Ethiopia. In Karrayyu-Oromo society, cattle are sacred to portant reasons for the persistence of tradi- breed management women, who care for them, milk the cows and tional breeds. In addition, these local breeds • Local knowledge associated with breed make butter/ghee. The men take care of camels, including milking and herding them. Goats, sheep, generate an array of benefits, including their management donkeys and horses are taken care of by everyone, contribution to social cohesion and identity, including the youth. and their roles in nutrient cycling, nutrition • Constraints and opportunities for and resilience. conservation and sustainable use of local In the photo above, a Karrayyu boy is holding a gorbo breeds. milking container woven by Karrayyu women from the Household surveys (see Section 5: leaves of desert palm, straw and a specific mountain grass locally called migira. In the photo on the left, a Household surveys and Annex 5.1: A sample 3 The approach used for this section is adapt- young girl is holding goat kids. household survey questionnaire) can include ed from Köhler-Rollefson I, Rathore HS (2005). Photo: P. Viesi questions that provide information on: The LIFE-method: A people centred conceptu- al and methodological approach to the documen- • The number and identities of animal tation of animal genetic resources. Paper present- ed at Tropentag 2005, Conference on International species and breeds held by individuals and Agricultural Research for Development, October 11– by the community 13, 2005, Stuttgart, Hohenheim, Germany. Assessing Agrobiodiversity: A Compendium of Methods Section 10 - Diversity of Domesticated Animals and Breeds 56 10.1 QUESTIONNAIRE FOR KEY INFORMANT INTERVIEWS OR FOCUS GROUP DISCUSSIONS The livestock diversity questionnaire comprises two parts. Part 1 is a listing of local livestock > Size breeds and species and their characteristics. Part 2 gathers information on the socioecological > Colour and cultural context and conservation opportunities for each breed separately. The example de- > Important morphological features scribed here can be modified or expanded to reflect research questions or to suit the local context. > Disease resistance or susceptibility > Product features (includes meat, milk, cheese, eggs, leather, wool) Select participants to ensure that there will be a diversity of experiences and knowledge. > Behaviour. Include both men and women and younger and older members of the community. A focus group ϐ What distinguishes this particular breed from other breeds? (Use the trait list above to help discussion should involve 5–15 participants; if necessary, separate ones can be held for men and answer this) women. The procedures should be similar to those described in ‘Focus group discussions’ under Section 2.3: Data-gathering methods and Section 6.1: Conducting a four cell analysis. Always re- ϐ What is the origin of the breed? cord the main points in ways that all participants can see them and discuss them. Knowledge and management practices In the case of interviews with key informants, each interview should be carried out separately ϐ Who is the main caretaker of this breed (feeding, milking, taking to pasture, taking care of so that the informants do not influence each other. The procedure followed is that for the house- the animal when it is sick)? hold survey (Section 5.1: Conducting the household survey). ϐ Do women have a specific role or traditional knowledge about this breed? PART 1: NUMBER OF ANIMAL SPECIES AND BREEDS ϐ How is the knowledge about that breed shared? Ask the group or informant the following questions: You may want to include questions to elucidate the local terminology (folk taxonomy) for the animals, for example, various age and sex classes as well as colour types. Examples of such ques- ϐ What livestock species do you keep and how many breeds are there for each species? tions include: ϐ What are the local names of each breed? ϐ What do you call young females and males of this breed? For each breed, ask each participant or informant the following question: ϐ What do you call mature females and males of this breed? ϐ How many females and males are of reproductive age? ϐ What do you call this coat colour or pattern? This will provide a freelist of all the livestock species and breeds kept by the group as a whole Ecological and production context (in the case of a focus group discussion) or by each informant (in the case of key informant interviews). ϐ Which parts of the landscape or ecological zones are important to the animals and why? ϐ Do the animals graze in cropped areas? During which season? List periods in which animals PART 2: SOCIOECOLOGICAL AND CULTURAL CONTEXT AND CONSERVATION graze in cropped areas. OPPORTUNITIES ϐ Do animals migrate seasonally? What is the migration route? Describe migration route This part of the interview is conducted separately for each breed. This consists of a series of with information on times of the year or season of migration questions aimed at understanding the characteristics, uses, management and conservation of the ϐ Have seasonal migration routes changed in recent years? If yes, why do you think that individual breeds. happened? Description of the breed ϐ What are the main characteristics (traits) of the breed? Points to record include: Assessing Agrobiodiversity: A Compendium of Methods Section 10 - Diversity of Domesticated Animals and Breeds 57 Social context ☐ Ability to survive in an unfavourable environment including low water availability, poor grazing or feed availability, mountainous terrain (as appropriate) ϐ Is the breed associated with a particular community or cultural or social group? Name the ☐ Good reproductive performance. group and provide information on their role(s). ϐ What is the social network that supports the management of the breed? Chances for sustainable use and conservation Is there a producer organization? ϐ What pressures does the breed face that threaten its survival or sustainable use? ϐ ☐ Loss of grazing Livelihood significance ☐ Changes in agricultural production systems ϐ What products are obtained from the breed? ☐ Loss of traditional institutions ☐ Lack of health care ϐ Do you sell animals or their products? What is sold, when and how? ☐ Lack of market demand ϐ Is the breed used for draught power? Do you use its manure (fertilizer, fuel, etc.)? ☐ Lack of interest by younger generation ☐ Drought/floods or other natural catastrophes Breeding mechanisms and strategies ☐ Conflict/war ϐ Do you give or lend animals to anybody outside the community? ☐ Other. ϐ Are any animals linked to deities? Interest in revival/conservation by the local community ϐ Which of the following strategies are used as part of the breeding strategy for the breed? ϐ Is there interest in the local community in maintaining the breed? If yes, what are the ☐ Selection (of either males or females or both) reasons for maintaining the breed (livelihood, identity, cultural)? ☐ Offspring testing ϐ What are the existing local institutions that could be mobilized to support conservation ☐ Oral or written record keeping of genealogies efforts? ☐ Castration of unwanted male animals ☐ Avoidance of inbreeding. ϐ What constraints need to be addressed? ϐ What are the main breeding objectives for the breed? These might include: ϐ What are the suggestions of the local community for how the breed might be conserved? ☐ Good yields (meat and milk) Further questions about local knowledge, gender roles or migration routes can be developed as ☐ Ability to walk long distances needed. The questions in the household survey (Section 5) or on the use of wild plants (Section 9) ☐ Good mothering instincts can be used to find out about the uses of wild plants as part of breed management. ☐ Need for social currency (acting as dowry or bride price) Cows and piglets in rotational farming, San Din Daeng, Thailand. Photos: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods The Karrayyu-Oromo pastoralists are considered among the last Oromo tribes that still exercise the Gada system – an ancient form of democracy. Power among the communities alternates every eight years. One full Gada cycle lasts 40 years. Gada is a political as well as social institution which governs the life of individuals in Oromo society. Following the Gada system, every eight years another community comes to live in a place shown on the photo. Each family has a house (a) and animal enclosure (b), which make a circular form around the common community space in the middle (c). Men and boys seasonally migrate with camels (d), while women stay home to take care of cattle, sheep and goats. Photo: R. Bulga Jilo. Illustration: F. Pasta (a) (b) (c) (d) Assessing Agrobiodiversity: A Compendium of Methods Section 10 - Diversity of Domesticated Animals and Breeds 59 10.2 DATA ANALYSIS CALCULATING RICHNESS AND population size of the cattle breeds (survey da- Table 10.1 List of animal species and breeds in one community in Zimbabwe in 2015. Source: SAFIRE, ta) and effective population size. Agrobiodiversity, Land and People Project, PAR. EFFECTIVE POPULATION SIZE For example, the effective population size Species Number of Breeds Breed names Trend Data from the household survey and from for the Tuli cattle breed in the community is: key informants can be analyzed to: Cattle 4 Tuli ↑ Ne = (4(48 x 594))/(48 + 594) = 177.6 • Calculate richness or number of livestock     Nkone ↑ species and breeds The results suggest that the effective pop-     Brahman ↑ • ulation size of the Brahman breed is low and Calculate the total population size and this breed might be at risk of disappearing in     Mashona ↓ effective population size for each breed. the community but that other breeds are prob- Chicken 5 Isikhova ↓ In most domesticated animal species, the ably of sufficient size at present. FAO has sug-     Insingizi ↑ numbers of breeding males and females is un- gested that an effective population size of 50 equal, with few breeding males and large num- is the threshold for concern, and the Brahman     Ithendele ↓ bers of females. Just counting the total size of breed is well below this in the community.     Imbila ↓ the population might not tell us much about The same calculations for population size     Indiya ↑ the likely survival of a breed (imagine a popu- and effective population size can be done for lation with only one male but many females). Goats 2 Mashona goat ↑ each year for which data are available to track To deal with this problem we calculate the ef-     Matabele ↑ changes in the conservation status of the fective population size. populations. Donkey 1 African ↑ The effective population size is the num- ber of individuals that a population with equal ANALYSIS OF OTHER DATA Table 10.2 Numbers of breeding males and females in cattle breeds in one community in Zimbabwe and numbers of both sexes would have to have in calculation of effective population size for each breed. Source: SAFIRE, Agrobiodiversity, Land and People Project, PAR. order to produce similar numbers of offspring Data from the household survey can be as the actual population of interest. combined to explore associations between an- Breed names Effective Males(Nm) Effective Females(Nf) Effective Population Size(Ne) imal species and breed diversity (richness and Effective population size (Ne) is calculated effective population size) and household fea- Tuli 48 594 177.6 using the following equation: tures such as gender or age and between live- Nkone 15 156 54.7 N = (4 x N N )/(N + N ) stock diversity and other diversity using mul- e m f m f tiple regression, multiple factorial analysis or Brahman 3 20 10.4 where Nm is the number of breeding males principal component analysis (see Section 15). Mashona cattle 18 53 53.7 and Nf is the number of breeding females in Similarly, information from the focus group the actual population. meeting or key informant survey can be com- For example, a community in Zimbabwe pared with other community or diversity da- kept four breeds of cattle, five breeds of chick- ta. Note that the focus group and key infor- en, two breeds of goats and one breed of don- mant data are not a random sample as partic- key (Table 10.1). Table 10.2 shows the total ipants have been selected for the information they can give. 11. POLLINATOR DIVERSITY Nomia sp. on flowers of eggplant. Photo: FAO/D. Martins Assessing Agrobiodiversity: A Compendium of Methods 61 11. POLLINATOR DIVERSITY 11.1 FIELD SURVEYS There is global concern about declining Many species are pollinators, for example: Passive sampling of insect pollinators is Although not all bees are attracted to pan pollinator abundance and diversity. Insect birds pollinate some flowers such as hibis- used to establish which species of bees are traps, it has been established that approxi- pollinators are important for crop produc- cus, bats play a role in the pollination of some present in the landscape. A common approach mately 90% of common species are likely to be tion and for maintaining wild plant popula- fruits such as mango and guava and flies are is to use water-based pan traps. The advantage detected (Grundel et al. 2011). The frequency tions, are sensitive to changes in the environ- important pollinators of cocoa (from where of pan trapping is that the sampling method of trapping will depend on the aim of the sam- ment (such as changes in landscape composi- we derive chocolate). However, the majori- is simple and can be done by almost anyone; pling. Trapping can be carried out on a week- tion and structure) and are an important indi- ty of animal-mediated pollination is carried it collects a wide-range of bee species and can ly basis if the aim is to intensively sample a cator of wider ecosystem health. This section out by bees. Bees are specialists in pollination, give a good indication of which bees are pres- season of pollinators, or a monthly basis to presents two methods for assessing pollinator they have formed symbiotic relationships with ent. The data collected represents the back- get a less detailed but broader picture of how diversity: plants where they are dependent on the flower ground level of bees; it samples the local area the pollinator community changes across the • products (nectar provides them with sugar and rather than an individual field in an area as the seasons, or on one or two occasions annually Field surveys to establish which species of pollen provides them with protein) for survival bowls will attract bees from some distance. If to get a snap shot of pollinators over several bees are present in the landscape and in the process they provide essential pol- done over several years this sampling will give years. It is important to remember that if years • Community surveys to understand lination services. an indication of whether bee diversity is de- are to be compared, then sampling should take document local knowledge about clining. The disadvantage is that expertise in place on the same date each year. It is up to the pollinators. There are approximately 20,000 known spe- identification is necessary for processing the researcher to tailor the sampling regime to the cies of bees in the world and almost certainly Information about which pollinators are pan trap samples and the volume of traps col- question being asked. many that have yet to be identified. Most peo- present and which plants they pollinate is use- lected means that the data processing can be ple are familiar with honeybees but this group ful in agrobiodiversity assessment, and for lengthy. also includes other social bees such as bum- making decisions about how to manage agro- blebees that live in colonies and solitary bees biodiversity. This information is typically that live alone, such as carpenter bees and lacking. It is also important to know if there blue-banded bees. Bee nests can be found in have been declines in pollinator numbers, in a variety of habitats, from soil, to dead wood, order to target management. Systematic field live trees and old walls. Some bees are general- surveys can be used to assess pollinator pres- ists and feed on a wide-range of species, where ence and diversity and local communities can as some are specialists and are dependent on play an important role in gathering informa- just one species of plant. They are crucial for tion about wild bee pollinators, by drawing on food production, particularly of vegetables their observations over many years. Both field and fruit. So although other species do have a surveys and community surveys help us to un- role in pollination, it is useful to focus on bees derstand the status of pollinators in a given ar- as they are the most important. ea, two methods are outlined here. Pollinator visiting coffee flowers in the Kerio Valley, Kenya. Photo: FAO/D. Martins Assessing Agrobiodiversity: A Compendium of Methods Section 11 - Pollinator Diversity 62 PAN TRAPS with water and a drop of unscented detergent ziplock bag, have a spatula or spoon ready to PINNING AND LABELLING BEES added (washing up liquid for example). If pos- help you gently transfer the bees, being care- Pan traps are small coloured bowls that are sible, sampling should be carried out during ful not to damage them. Add a data label to Bees should be pinned for and stored for filled with water with a small amount of de- dry conditions, however, if this is not possible, the bag. To do this use a small piece of white identification on a styrofoam block using en- tergent to break the surface tension. Bees are or there is a risk of rain, a small overflow hole paper, and write using a pencil (which will tomological pins. More details on pinning attracted to the bowls and are trapped by the should be made at the top of the bowl to allow not smudge as a pen would) recording: loca- bees and labelling them can be found on www. water. Three colours of bowls (ultraviolet blue, excess liquid to drain away. tion, date, time of collection, name of collec- bwars.com. Good labelling is important. Labels ultraviolet yellow and white) are used, which tor. Protect the bag by placing into a box and should be pinned close to the specimen so that Set traps early morning, before 9 am and represent the three colours that attract bees. take it back to your headquarters. Bees should it is clear which bee it refers to. Label each bee collected after 24 hours. Make a clear record of The bowls are painted with ultraviolet paints be taken out of the bag as quickly as possible with the following information on thick archi- the following information: because bees see the ultraviolet spectrum. • as they will quickly degrade in the bag. If you val quality paper (20mm x 8mm is a good size Site location and description It has been established that the minimum are setting more than one transect, do keep to use): • Date and time set number of pan traps for sampling is approx- the bees from the different transects in sepa- • • A unique ID number Date and time collected imately 20. Here we present a sampling lay- rate bags. Providing you are not transporting • Country out used successfully in a participatory tri- • Number of bowls set the bees too far it’s not necessary to put them • Region al with farmers in India (Basu et al. 2016). It • Number retrieved (some bowls may ‘go in alcohol. If you need to keep the bees for any • Specific location comprises a transect of 200m with 27 bowls, 9 missing’ or fall over). length of time before processing you may need • Latitude and Longitude of each colour. Figure 11.1 shows the layout. to decant the bees into individual glass vials • Date The transect is located randomly in the area SAMPLE COLLECTION with 70% alcohol. In this case each bowl is • Name of collector. that you wish to sample. Alternatively you can likely to need its own vial. Label each vial sep- Each bowl should be tipped into a small net place 24 traps, 8 of each colour, at 5 m inter- arately, using card and pencil to write, slipping The unique ID number will enable any re- such as an aquarium net or a large tea strain- the label into the vial. searcher to find details of the bee in project vals along a transect of 100m. Bowls can be er. Bees from all the bowls can be combined. database. fixed to canes, set away from dense vegetation After collection carefully shake the bees into so that they are visible to bees. The photo on SAMPLE PROCESSING Now bees are ready for identification. a plastic bag, such as a strong sandwich bag or the right shows a farmer setting up a sampling Identification of species is a specialist task and The next step is to wash and dry the bees. station and illustrates how the traps can be must be carried out by a taxonomist. However, Helpful instructions and videos for process- set-up. Each bowl should be two thirds filled it is relatively straight forward to identify bees ing and storing bee specimens can be found to family and training of keen individuals in on the Bee Wasp and Ant Recording Scheme parataxonomy (identification of insects by website under the heading ‘Additional help- non-specialists) can be organised through lo- ful resources’ (www.bwars.com) along with ad- cal museums and universities. Guides and ad- vice on identification. See also http://www.fao. vice can also be found on www.bwars.com. org/3/a-i5367e.pdf. 50 meter 200 meter Figure 11.1 Schematic design of trapping station. Each Setting up a pan trap station: the light-weight plastic group of three traps was placed at least 5m apart. The bowls painted with UV paint and are attached to coloured circles represent different coloured traps. the canes with wire. Photo: Centre for Pollination Source: Basu et al. 2016 Studies, University of Calcutta, India. Assessing Agrobiodiversity: A Compendium of Methods Section 11 - Pollinator Diversity 63 SAMPLE STORAGE DATA STORAGE • Date and time when trap set • Name of person who identified the • specimen Date and time when trap collected Over time bee specimens will degrade. This Build a database for the information. Data • • Date the identification took place can be minimized by keeping the bees in in- can be stored in a simple spreadsheet such GPS coordinates sect proof strong boxes with a silica gel pouch as Excel. Any amount of information can be • • Who entered the record Habitat it was collected from to prevent moisture accumulating (bees can stored but the following are useful: • When the data were entered go mouldy quite quickly). Store the boxes in a • Country • Type of trap used dark cool place. Placing the boxes in a freezer • • Notes field for weather, conditions, • Region Collector’s name for three days at -10c periodically will help to problems encountered, flowers blooming, ensure any pests are killed. • Specific location • Genus etc. • Site Number • Species • Unique ID number for the sampling event • Unique ID number for the individual specimen. Human error is inevitable. It is advisable to have more than one person entering and checking the data to ensure that data is en- tered correctly and matches the specimen. DATA ANALYSIS From the database it will be relatively easy to collate summary data for each site, and date, such as which bees are present or calcu- late species richness for the site. Further da- ta analysis will depend on the aim of the sam- pling programme and a statistician should be consulted to ensure the analytical approach is appropriate. Bees pinned and labelled in a pest resistant storage box. Photo: Centre for Pollination Studies, University of Calcutta, India. Assessing Agrobiodiversity: A Compendium of Methods 11.2 COMMUNITY SURVEYS The local community will hold a certain Before the survey is carried out a series of Stage 1 amount of knowledge about local pollinator photographs of bee species known to occur in populations and the purpose of this exercise is Carry out separately for each group of five. the country / region should be printed ready to collate that information in a way that it can for the exercise. This relies on local facilitators Show the photographs to the partici- be used to make decisions about biodiversi- having some basic information about the na- pants and ask them whether they recognize ty. To ensure the dataset is robust, this meth- tionally / regionally present bee community. the bees and if they can name them. Local od uses structured discussions, followed by a names should be recorded along with the process of peer-to-peer validation to enable a At each site identify at least 15 participants number of people who can recognize the consensus to be reached. In this way there is ensuring that there is no bias in terms of gen- bees. agreement among community members and der or age. Randomly allocate participants in- error from unreliable observations is mini- to three groups of five individuals. If it is pos- Ask the participants the questions sible to include more individuals in the survey, shown in Table 11.1. Encourage partici- mized. The method aims to gather informa- tion about: then the same process should be repeated (i.e. pants to expand on the questions and allow • Which bees are present on local farms three groups of five). Experience has shown additional discussion. Make detailed notes that five individuals is the optimum number of the discussions – it is easier if a note-tak- • Whether there has been any change in bee for small group discussion in this case. At the er is present so that the facilitator can focus numbers over time start of the session explain the purpose, pro- on the conversation. • Which plants they visit and potentially cess and expected output of the exercise and pollinate. Invite the participants to disperse for give participants the opportunity to withdraw sometime. During this time take the an- This information can then be used to identify: if they would like to. It is important that par- swers from the participants and turn them • Which bees are present and locally ticipation is voluntary. into a set of statements, keeping the state- important The exercises consist of two stages. The ments from each group separate. Write • Which bees, if any, should be targeted in first stage of the exercise is carried out sep- these in a way that they can be discussed local management plans. arately with each group of five participants. in peer groups. For example: “Blue-banded In the second stage the participants of each bees have declined by 50% in the last 10 group come together to share and review gath- years”; “carpenter bees visit aubergine and Community survey participants looking at photos of ered information. bottle gourd”; “Asian honey bees could be pollinators, Northeast India. Photo: P. Chakraborty encouraged by planting more trees which will grow tall”; “bee numbers could in- crease if less pesticides were sprayed”. Stage 2 Bring the participants back into their groups and ask each group to review the statements from the two other groups. Ask participants to either accept, reject or mod- ify the statement, encouraging discussion. Bee hives on a baobab tree, Mali. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 11 - Pollinator Diversity 65 Table 11.1 Questions about pollinators for the community survey Questions Purpose What do you understand by ‘pollination’? Establishing local knowledge about pollination How do you know this? Establishing the source of local knowledge Please rank the insects in the picture book according Collating local knowledge about the importance of to their value as crop pollinators. Please also indicate particular pollinators those that you do not think play a role. How do you know that the insects you mention have Establishing the source of local knowledge a role? Are there other insect pollinators not shown here? Adding local knowledge to existing knowledge about local pollinators Which crops do you see each of these insects visiting? Establishing local understanding of which insects visit which crops and are therefore likely to be pollinators Have there been any changes in the abundance of Gathering local knowledge on pollinator declines or any of these pollinators in the last 5, 10, 20 years? By increases and the time scale over which these have what percentage do you think they have increased or occurred. declined? How do you know there has been a change? Establishing the source of local knowledge Why do you think this change has occurred? Scoping reasons for pollinator abundance change In your opinion, how could their abundance be Gathering local expertise on managing pollinators increased? Would it be useful to have more pollinators? Establishing how important the community thinks that pollinators are in their local context Stingless bees (Meliponini) constitute a diverse group of highly eusocial insects that occur throughout the tropics. Eusociality is the highest level of organization of animal sociality. Eusocial species, any colonial animal species (e.g. ants, bees, some wasps, termites), live in multigenerational family groups. The majority of individuals cooperate to care for juveniles and relatively few (or even a single) reproductive group members. Keeping of stingless honeybees is known as meliponiculture. Stingless bees store their flavoursome honey in clusters of small resin pots near the edges of the nest. Stingless bees of Melipona genus, Cuba. Photo: G. Gullotta Assessing Agrobiodiversity: A Compendium of Methods Section 11 - Pollinator Diversity 66 ANALYSIS Keep the information from the three groups bees had been seen visiting particular crops researchers assumed that the more farmers The same study showed that the commu- separate. At the end there may be consensus and constructed a visitation network based on cited an interaction, the more confidence they nity perceived that blue-banded bees had de- across groups but if this is not the case then participant observation (Figure 11.2). Network could have that this interaction exists. In this clined by at least 60% in some areas and car- it is useful to know how groups differ. It indi- analysis was performed using “R” statistical way the line width represents a proxy for con- penter bees had declined by 75%. This pro- cates uncertainty within the community. Data software version 3.0.1(R_Core_Team, 2013) (R_ fidence in the information. The network shows vides an early warning sign for scientists. The can then be summarized to establish: Core_Team 2013) with “bipartite” (Dormann, that Apis dorsata (the Asian honey bee) visit- participants recommended reducing chemi- • Which pollinators are well known 2013) and “SNA” (Butts 2006) used to con- ed the most crops and that Lasioglossum spp. cal pesticides, conserving natural habitat and • Which are observed to be present struct the network with “ggplot2” (Kahle and (sweat bees) visited the least. Aubergine was preserving big trees to encourage more bees. • Which are considered to be declining and Wickham 2013) and “igraph” (Csardi and the most visited crop and spiney gourd the This gives the community an excellent start- why Nepusz 2006) packages used to visualise data. least well visited. The network has some lim- ing place for participatory research. • How the local community consider these itations; bigger bees are more likely to be spot- The information from the three study ar- pollinators could be managed. ted so there is some bias in the data. However eas was pooled to form a single network de- REFERENCES this is a good basis for further research and in A study in Northeast India used this ap- scribing crop-bee interactions based on farm- Basu P, Parui AK, Chatterjee S et al. (2016) Scale this case sparked a positive discussion around proach to collate information about pollinator er perceptions. In this network the width of dependent drivers of wild bee diversity in tropical pollinators within the local community. the connecting lines shows the number of heterogeneous agricultural landscapes. Ecology and populations (Smith et al. 2017). In this study Evolution 6:6983-6992. researchers took the data recording which farmer groups that cited an interaction. The Butts C (2006) The sna package: tools for social network analysis, V2. 2. (Department of Sociology, Figure 11.2 Visitation network describing crop-bee interactions based on farmer perceptions. Source: Smith et al. (2017) University of California, Irvine, California, USA). Csardi G, Nepusz T (2006) The igraph software package for complex network research. Interjour- nal, Complex Systems 1695:1-9. Grundel R, Frohnapple KJ, Jean RP, Pavlovic NB (2011) Effectiveness of bowl trapping and netting for inventory of a bee community. Environmental Entomology 40:374-380. Kahle D, Wickham H (2013) ggmap: Spatial Vi- sualization with ggplot2. R Journal 5(1). R_Core_Team (2013) A language and environ- ment for statistical computing. (R Foundation for Statistical Computing, Vienna, Austria). Smith BM, Chakrabarti P, Chatterjee A et al. (2017) Collating and validating indigenous and local knowledge to apply multiple knowledge sys- tems to an environmental challenge: A case-study of pollinators in India. Biological Conservation 211:20-28. Tomato Amegilla.sp Flat bean p. Cer Brinjal atina.sp. Maize Sweet Potato Xylocopa.spp. Ridge gourd Sunflower Ladies finger Mustard Apis.dorsata Pointed gourd Pumpkin Cucumber Ap Spiney gourd is.cerana Bitter gourd Radish Cori Bottle gourd Lasioglossum.spp. 12. LANDSCAPE MAPPING Participatory mapping, Udukumbura, Sri Lanka. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 68 12. LANDSCAPE MAPPING 12.1 CONDUCTING PARTICIPATORY LANDSCAPE MAPPING Participatory landscape mapping is a way of processes on landscape management and on Participatory landscape mapping is best mixed group of men and women, or separate- obtaining and documenting spatial informa- development projects. carried out in a focus group discussion or ly with men and women if that is more cul- tion on land use, agrobiodiversity and land- workshop. Before the workshop, all commu- turally appropriate. Information collected in Common uses of participatory maps scape features. Participatory mapping taps in- nity members should be informed about what separate groups sometimes provides a better include: to local knowledge, and provides a greater un- • the exercise is intended to achieve and how understanding of the differences in land use Gathering information about land derstanding of human–environment interac- the community will benefit, and all commu- and landscape perceptions between women and resource-use patterns, hazards tions, activities and processes in a landscape. nity members should be invited to participate. and men. It is important that both older and and community values in relation to It can be used to gather information on spa- Some of the participants will have extensive younger members of the community partici- agrobiodiversity conservation tial distribution of landscape features such as knowledge about different land uses and ac- pate in order to capture different perceptions forest, cropland, grassland and wetland; hu- • Creating management plans, such as tivities in the landscape (e.g. forestry, use of of landscape features and allow for exchange man activities such as farming, grazing, fish- community-protected areas and buffer wild plants, sources of water, sacred sites) and of information between them. Depending on ing and collecting wild plants; and impor- zones can act as expert informants. the research context and purpose, it may be tance of specific areas for ecosystem services. • Sharing knowledge within and among local desirable to include participants with exper- Mapping is usually best conducted with 10- Participatory maps are also useful in identify- communities tise in different areas (e.g. animal herders, tra- 20 participants. It can be carried out with a ing and locating the main challenges and haz- ditional healers, artisans, farmers, fishers). ards encountered at community level, such as • Promoting community engagement in Participatory mapping, Taveuni Island, Fiji. Photo: D. Mijatović soil erosion, desertification, pollution, defor- decision-making processes concerning estation, fire and hydrogeological risks (e.g. natural resource management flooding, landslides, avalanches). • Monitoring changes in land cover and When information is updated over time, practices over time maps can show changes in land-use patterns • Documenting the impacts of logging, and diversity. These can be analysed using the mining and ‘land grabs'. tools provided by most georeferencing soft- ware. For example, this can show how much forest cover has been lost due to deforestation and logging activities, or a change in land use from grazing to crop production. The participatory process is, in itself, of central importance. Knowledge is shared with- in the community and can be used for develop- ing land-management plans. Access to spatial knowledge can help clarify and support com- munity demands on their landscape and be- come a negotiating tool for decision-making Assessing Agrobiodiversity: A Compendium of Methods Section 12 - Landscape Mapping 69 PREPARATION also on the transparencies to permit Human activities, such as fishing, The importance of different land us- georeferencing and digitizing the maps. cropping, grazing, and collecting wild food, es for ecosystem services, such as wa- 1. Identify participants and venue for the • Prepare blank transparent overlays in medicinal plants, fodder, timber, and build- ter regulation, soil quality, pollination and workshop in discussions with members advance. During mapping, make sure ing. Use different symbols for the different pest control. Ask participants to locate on of the community. Keep in mind that the that every transparent overlay is firmly activities. the map the areas that provide different activity may well take a whole day and attached to the map in order to prevent ecosystem services. people will probably have to come and go Challenges and hazards, such as movement between the two and ensure to deal with other commitments. Make threatened habitats or species, areas of soil One way of doing this is by giving partic- the accuracy. This can be done by lining sure the activities are dynamic and that erosion, soil and water pollution, deforesta- ipants coded cards for different ecosystem up the dots with coordinates on map participants are provided with adequate tion, desertification, drought, plant diseas- services, which they can place on the parts and transparent overlays (see Figure refreshments. es, flood risk or fire risk. These can be iden- of the landscape that are the most import- 12.1a). tified through discussions that start with ant for each ecosystem service. Since eco- 2. Arrange for one or more facilitators (one questions such as: system services are fairly abstract terms, it for each working group). These will need to THE MAPPING PROCESS is best to ask specific questions like those conduct transect walks and interviews with ϐ Are there places where the water is listed in Table 12.1. key informants before the workshop to get Mapping can be conducted in different polluted? to know the local classification of land and ways, here we provide an example of activities ϐ Are floods and mudslides happening land-use patterns. for participatory mapping. in any particular place? 3. Prepare and print maps and collect other After the introduction and preliminary dis- Table 12.1 Questions about ecosystem services (these general questions should be followed up with more materials such as large pieces of transparent cussion, invite the participants to add the fol- specific ones as appropriate). plastic (blank transparent overlays), paper, lowing items to the map: Type of ecosystem coded cards (for the activity on ecosystem Question Land features and land cover service , such as services) and pads of sticky notes. Printed rivers, roads, lakes, forests and villages. Provisioning Where do you go to get water to drink or for use in cooking? maps can be prepared using a satellite base map. Participants can then draw landscape This will help everyone to recognize and lo- From where do you get water for agriculture? features on transparent overlays on the cate themselves on the map. The partici- map. pants can start by marking their own homes Cultural Which areas are important for cultural reasons? and then marking natural and managed • Prepare and print the satellite map in land cover/use types by drawing different Regulating Which areas are important to minimize flooding? advance. The map should be 1m x 1m areas (technically called polygons) for for- or larger. Use Landsat or Google Earth Which areas are important to minimize the impact of droughts? est, crop production, grazing and fishing. images at a scale of 1:15,000–1:30,000, adjusting the scale depending on the While conducting the mapping workshops, Which areas are important to reduce soil erosion? area that the community manages. make a legend on the side of the map with Which areas are important to maintain soil fertility? In the case of nomadic communities, all the components on the map. Use points, the scale may need to be smaller than lines and different shapes to add features Which areas are important for pollination? 1:30,000. When preparing the map on the map. This will help in the process of in Landsat or Google Earth, add dots transferring them to digital maps with geo- Which areas are important for pest control? with coordinates along the edges of referencing software. Supporting Which areas are important for wildlife, for example, for mating season, forage, the map (see Figure 12.1a). Mark these spawning, migration? Assessing Agrobiodiversity: A Compendium of Methods Section 12 - Landscape Mapping 70 Another way to conduct this activity is by us- * Ask each question, one at a time, and let Figure 12.1 Taking photos of the transparencies FURTHER INFORMATION ing signs for land cover/use types and coded the participants place their cards on the a: Transparencies matching the cards for ecosystem services (see photo below land-cover/use sign that best corresponds coordinate marks Basupi LV, Quinn CH, Dougill AJ (2017) Using right). to the question. For example, ask the participatory mapping and a participatory geo- graphic information system in pastoral land use * Make signs for each land cover/use on first question, “Where do you go to get investigation: Impacts of rangeland policy in Bo- sheets of paper. For example, the forest water for human consumption?” After all tswana. Land Use Policy 64:363–373 sign might consist of a sheet of paper with participants have placed their cards on the Chambers R (2006) Participatory mapping and ‘forest’ written in local language. Place the sign, move on to the next question. geographic information systems: Whose map? Who signs on a table or on the ground. The signs is empowered and who disempowered? Who gains represent land uses in the landscape. and who loses? Electronic Journal of Information * Prepare coded cards with a unique b: Taking picture from centre of Systems in Developing Countries 25(2):1–11 the map perpendicularly number and questions in English and local Fagerholm N, Käyhkö N, Ndumbaro F, Khamis language. A unique number is assigned to M (2012) Community stakeholders’ knowledge each participant beforehand. For example, in landscape assessments – Mapping indica- the participant with number 1 will get ten tors for landscape services. Ecological Indicators 18:421–433 cards marked with the number 1, one card with each of the ten questions in Table 12.1). The farmer with number 2 will get ten cards with the number 2 on them, and Assessing the importance of different land uses for ecosystem services, Meghalaya, India. Figure 12.2 Map of the Abolhassani Indigenous Nomadic Tribal Confederacy, Iran. so on. Photo: D. Mijatović Source: G. Azhdari, CENESTA 12.2 CONVERTING DRAWN MAPS INTO DIGITAL FORMAT Geographical data from the maps can be are beyond these guidelines and, wherev- digitized. The first step is to georeference the er possible, geographic information system base map and transparent overlays. For this, (GIS) experts should be asked to support or do the transparent overlays laid over the base georeferencing. map have to be photographed. Make sure the Georeferencing tools are specific software transparent overlays are well labelled, that the that allows the creation and analysis of spa- coordinates on the base map and transparen- tial data, based on information carrying geo- cies match (Figure 12.1a) and that the trans- graphical coordinates. Commercial GIS soft- parent overlays are not wrinkled. Put the base ware includes ArcGIS and ArcMap. QGIS map and the transparent overlays on a flat sur- (Quantum GIS http://www.qgis.org/en/site/) is face. Using a good camera that takes high-res- a user-friendly open-source tool for mapping olution images, take a photograph from above and digitizing geographical information. The the centre of the map and perpendicular to the program allows the user to draw points, lines map (Figure 12.1b). and polygons (also called ‘shapefiles’) over Georeferencing is the process of assign- satellite or topographical bases (also called ing coordinates to the participatory maps. ‘rasters’). The different steps involved in georeferencing 13. RESILIENCE ASSESSMENT Highland pastures, Naxçıvan, Azerbaijan. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 72 13. RESILIENCE ASSESSMENT Resilience in agricultural landscapes refers The questions are divided into five groups: CONDUCTING A RESILIENCE ASSESSMENT to their capacity to recover after stresses such • Landscape/seascape diversity and as drought, flood or hurricane, and to adapt ecosystem protection Participants: The resilience assessment is most important information – reasons, prob- to changing conditions. The social-ecological conducted in a workshop with ten community lems and possible solutions. The note-taker’s resilience assessment aims to develop a bet- • Biodiversity (including agricultural members of mixed age and gender. It also in- job is to capture the discussions and explana- ter understanding of the factors that contrib- biodiversity) volves one or more facilitator(s), a note-taker tions around each question. He or she should ute to resilience to climate change. The results • Knowledge and innovation and, if needed, a translator. take notes during the entire workshop, includ- of the assessment provide a basis for develop- ing the introduction. ing plans to enhance resilience through better • Governance and social equity Facilitator: The facilitator is responsible management of diversity, soil and water. • for describing the purpose of the assessment Preparation: Preparation includes plan- Livelihoods and well-being. to the participants and for making sure that all ning and organizing the assessment work- The assessment involves community mem- During the assessment, the participants are steps are taken in the right order and that all shop, identifying possible participants, fix- bers in a workshop, discussing and assessing asked to discuss each question and give an in- participants are involved. It is important that ing a date that is convenient to everyone and their response to 20 questions (see Table 13.1) dividual and a collective score of their current the facilitator ask the questions in a way that ensuring that there is a suitable venue avail- that provide the indicators of resilience. view and of their perception of the trend. They is easily understandable to all participants. He able and adequate refreshments are provided. are also asked to explain the reasons for the or she should practice asking each question Preparation also includes other practical mat- scores and trends. beforehand and prepare supporting questions ters such as translating the indicators into the and local examples. local language. Translator: If the facilitator and note-tak- Materials: Materials needed for the day of er do not speak the local language, a transla- the workshop include: tor will be needed to translate the written list • A translated list of indicators, large sheets of indicators and questions and an interpreter of paper, coloured pens for mapping, will be needed to ask the questions and trans- stickers, tape and other material you think late the answers and discussion during the will be helpful for the assessment assessment. • Food and refreshments, as the workshop is Note-taker: The trends and scores for the likely to last an entire day. indicators (described later) do not capture the Climate change timeline, Lyngngam community, Meghalaya, India. Source: Agrobiodiversity, Land and People Project, PAR. Assessing Agrobiodiversity: A Compendium of Methods Section 13 - Resilience Assessment 73 Table 13.1 Social-ecological resilience indicators Domain Indicator of social-ecological resilience to Very low Very high (Score=5) Domain Indicator of social-ecological resilience to Very low climate change (Score=1) climate change (Score=1) Very high (Score=5) Landscape Landscape diversity: The landscape is composed of One or very Governance Land/resource rights: Customary or formal rights Rights are not Rights are fully diversity and a diversity/mosaic of natural ecosystems and land few natural High number of ecosystem ecosystems and natural ecosystems and social over land/water and other natural resources are recognized and recognized and not use types. and land uses equity clearly defined and recognized. heavily disputed disputed protection land uses Institutions exist Ecosystem protection: Areas within the landscape There are no Key resources are and are capable are protected for their ecological and/or cultural areas under under some form of Local governance: Accountable and transparent local institutions are in place for the effective There is no of transparent, importance. protection protection governance of resources and local biodiversity. institution participatory and effective decision- Landscape integration: Ecological interactions Ecological Ecological making between different components of landscape interactions are are taken into consideration in natural resource interactions are not considered considered and Social capital: Individuals within and between Little or no Very high level of management. harnessed communities are connected and coordinated cooperation and cooperation and coordination in coordination in Recovery and regeneration of the landscape: through networks that manage resources and The landscape has the ability to recover and Very low ability Very high ability exchange materials, skills and knowledge. natural resource natural resource to recover and to recover and management management regenerate from environmental shocks and stresses. regenerate regenerate Access to Social equity: Rights and access to resources and resources and Biodiversity Local food diversity: The community consumes a Very few or no Very high diversity opportunities for education, information and opportunities Access to resources (wild and diversity of locally-produced food. locally-sourced of local foods widely decision-making are fair and equitable for all is not fair and and opportunities is agricultural) foods consumed community members. equitable fair and equitable Crop/animal diversity: Households and/or Very few or Local crop varieties community groups maintain a diversity of local no local crop and animal Socioeconomic Socioeconomic crop varieties and animal breeds. varieties and breeds are widely Livelihoods animal breeds conserved and used and well- Infrastructure: Socioeconomic infrastructure is infrastructure adequate for community needs. does not meet infrastructure meets Common being community all community Sustainable management of common resources: resources are Common resources needs needs Common resources are managed sustainably in are sustainably order to avoid overexploitation and depletion. overexploited or depleted managed Human and environmental health: The overall state of human health in the community taking Health situation Health situation is Knowledge into consideration the prevailing environmental is bad satisfactory and Innovative practices: New sustainable practices in Community is Community agriculture, fisheries and forestry are developed, not receptive members receptive conditions. innovation adopted and improved, and/or traditional to change, no to change and Households are practices are revitalized. innovation adjust their Income diversity: People in the landscape are Households have involved in a variety practices involved in a variety of sustainable income- no alternative of sustainable generating activities. economic income-generating Traditional knowledge related to biodiversity: Local knowledge activities Local knowledge and cultural traditions related to Local knowledge and cultural activities biodiversity are transmitted to young people in the and cultural traditions are traditions are lost transmitted to Biodiversity-based livelihoods: The community Livelihoods are Livelihoods are community. develops innovative use of the local biodiversity for not related to being improved young people its livelihoods. local biodiversity through sustainable use of biodiversity Documentation of traditional knowledge: Biodiversity in the landscape, including agricultural Little or no biodiversity, and knowledge associated with it documentation Traditional Socioecological mobility: People are able to move knowledge is around to take advantage of shifts in production There are no There are sufficient is documented, stored and made available to in the documented opportunities and avoid land degradation and opportunities for opportunities for community members. community overexploitation. mobility mobility Women’s knowledge: Women’s knowledge, Women’s Women’s The indicators are scored as: 1 = very low, 2 = low, 3 = medium, 4 = high, and 5 = very high; and given a decreasing, experiences and skills are recognized and knowledge, knowledge, increasing or stable trend. respected at household, community and experiences and landscape levels. skills are not experiences and recognized and skills are recognized respected and respected Assessing Agrobiodiversity: A Compendium of Methods Section 13 - Resilience Assessment 74 RESILIENCE ASSESSMENT • Domesticated animal species and SCORING THE INDICATORS (6–8 explain their answers. For example, if a WORKSHOP breeds HOURS) participant gives a score of 3, the facilita- • Useful wild species tor asks, “Why did you give to this question The workshop consists of three parts: Individual scores and trends: Participants a score of 3?” The note-taker captures the 1. Introduction • Fish in streams, rivers and lakes answer 20 questions one by one. The an- explanations given by the participants and • swer to each question consists of a score Insects, etc. the main points of the discussion. 2. Scoring the 20 indicators and a trend: 3. Conclusions Write their answers on a big piece of paper Consensus (group) score and trend: After Score: Participants give a score to each and stick it on the wall. all participants have given their score and question on a 5-point scale. The facilita- trend for each question, ask for a consen- INTRODUCTION (2 HOURS) Explain resilience tor will need to explain what each number sus (group) answer. This creates a space for • Ask participants to draw a timeline means. discussion and reaching a common agree- During the introduction, the facilitator in- troduces and develops a common under- for the last 30 years with major events and Trend: Participants give a trend for each ment. Give the participants time to dis- changes (droughts, floods, etc.) (Figure question by using the following categories: cuss and explain their answers to each oth- standing of key concepts, such as the land- 13.1). er while working towards an agreement on scape, agrobiodiversity and resilience. ↑ Steep upward trend (e.g. getting better) the consensus score and trend as a group. Explain what is a landscape • Describe ‘resilience’ by discussing During the discussion, the participants will examples from the timeline: recovering → No change • Ask workshop participants to draw a share their ideas, views and problems. This after stress (e.g. drought) and the ability to ↓ Steep downward trend (e.g. deteriorating). map of their landscape with forest, rivers, helps reach a common understanding of adapt to change. water sources, lakes, fields, houses, roads, Draw a table on a big sheet of paper and add the landscape, threats and solutions. When etc. • Ask the participants to explain participants’ names (Table 13.2). Record the group has reached a consensus answer, resilience in their own words. the scores and trends in this table. move on to the next question. • Ask the participants for local words for the landscape and write these down on • Describe ‘adaptation’ by discussing, After participants have given their scores a big sheet of paper. For example, in Japan, for example, how they cope with and adapt and trends, the facilitator asks them to traditional landscapes are called satoyama, to drought or floods, and other extreme which means forest-field. The word weather events, irregular rainfall, etc. satoyama expresses the links between the Figure 13.1 An example of climate change timeline in Pgaz K’Nyau, Thailand. Source: Agrobiodiversity, Land and People Project, PAR cultivated (field) and uncultivated (forest) . parts of the landscape. Since 2000 the weather is unpredictable, rainfall is Explain agrobiodiversity erratic and seasonal patterns are changing Ask participants to list the most import- Very dry and Floods and Drought Flood and Drought cold year with hail landslide Rice harvest loss flash flood ant agrobiodiversity elements in their land- scape. These include: 1989 1993 1998 2000 2003 2009 2010 2011 2014 2015 • Landscape parts (fields, forest patches, rivers, pastures, water sources) Many rats eat Rice had no seeds Flies Many worms in the village but they seed in the field Community rice bank die when they touch water • Crops and varieties of the main crops established Assessing Agrobiodiversity: A Compendium of Methods Section 13 - Resilience Assessment 75 CONCLUSIONS The timeline and the answers to the 20 questions will reveal the main challenges faced by the community as well as possible solutions. For example, there may be problems with increas- ing frequency of droughts, the loss of diversity and traditional knowledge, or the lack coordi- nation and social cohesion. The facilitator can summarise the problems and discuss possible solutions that emerged during the discussion of the 20 indicators. If the group identifies solu- tions, more-detailed follow-up steps and actions can be defined. DATA ORGANIZATION AND ANALYSIS Data organization and analysis can involve: • Transcription of the timeline, notes, scores and trends • Plotting of scores and trends, and calculation of the mean and standard deviation for scores • Qualitative analysis to understand social-ecological processes in a community. Table 13.2 A table for recording scores and trends during resilience assessment. RESPONDENTS QUESTIONS A B C D E F G H I J K 1 2 3 4 Resilience assessment, Sierra del Rosario, Cuba. Photo: H. Gruberg Cazón 5 6 7 8 9 10 11 12 FURTHER INFORMATION 13 UNU-IAS, Bioversity International, IGES, UNDP 14 (2014) Toolkit for the Indicators of Resilience in So- 15 cio-Ecological Production Landscapes and Seascapes 16 (International Partnership for the Satoyama Initia- 17 tive, Tokyo). 18 19 20 14. RICHNESS, EVENNESS AND DIVERGENCE FOR CROP SPECIES AND VARIETIES Rice harvest, Hanku, Nepal. Photo: LI-BIRD/E. Palikhey Assessing Agrobiodiversity: A Compendium of Methods 77 14. RICHNESS, EVENNESS AND DIVERGENCE FOR CROP SPECIES AND VARIETIES richness, evenness and divergence allows us to Figure 14.1 illustrates richness and evenness in two farms. Both Farm A and Farm B have nine Richness is the number of distinct describe: varieties of a crop (illustrated through the vertical lines in different colours; v=variety) and there- species, crops or varieties present on a farm, in a community or in a landscape. • The amount of crop or variety diversity fore have the same richness (9). However, the varieties in Farm A are grown on approximately (which may include all varieties in an area equal areas, whereas those on Farm B are grown on very different areas. Thus, Farm A has much Evenness measures the distribution or only the traditional varieties) greater evenness than Farm B. or relative abundance of crops or variet- ies. It shows whether different types oc- • The way the diversity is distributed across Figure 14.1 Areas of different crop varieties grown on two farms. cur with similar or different frequencies. fields, households, communities or villages In the case of trees, it is usually based on • The extent to which farmers (or Farm A differences in the numbers present while communities within a landscape) differ in the case of field crops it is measured with respect to the distribution of as differences in the areas the different agrobiodiversity. crops or varieties occupy. This information can be used to: Divergence indicates how different • Identify common and rare species, crops or households are within or between com- varieties munities or the extent to which differ- ent communities differ within a land- • Identify any rare crops or varieties in need scape with respect to the crops or variet- of particular conservation action ies they grow. It measures how likely it is • Identify which farmers grow and maintain that two randomly chosen samples taken many crops or varieties from any two farms or communities will be the same. The higher the divergence, • Begin to identify patterns of distribution Farm B the more different one farm is likely to of diversity associated with particular be from another. sections of the community (e.g. men and women, rich and poor), specific environments (e.g. upland areas, valleys) or production areas (e.g. home gardens, Calculating richness, evenness and diver- irrigated or non-irrigated fields). gence allows us to describe the amount of di- versity within a farm, community or landscape and to look at the differences between them. Richness, evenness and divergence can be cal- culated for species, for crops or for the vari- eties present within a crop. The calculation of Area Planted Area Planted V1 V1 V2 V2 V3 V3 V4 V4 V5 V5 V6 V6 V7 V7 V8 V8 V9 V9 Assessing Agrobiodiversity: A Compendium of Methods Section 14 - Richness, Evenness and Divergence for Crop Species and Varieties 78 CALCULATING RICHNESS, EVENNESS AND DIVERGENCE There are several ways to calculate richness, First, create an Excel sheet by transferring RICHNESS grown on a farm that is occupied by a partic- evenness and divergence of crops or varieties the data from the household questionnaire ular variety. (see Magurran 2003). In this Compendium we (household identifier, names of varieties and To determine richness of varieties of one It can be thought of as the probability of use the Simpson Index (see Jarvis et al., 2008). area under each variety in each household). specific crop: any two individuals drawn at random from an It is worth remembering that all measures of In the case of tree crops, enter the number of Count the number of different varieties infinitely large community belonging to the evenness also reflect richness to some extent trees of each type grown by a household in- grown by each household same variety (in the example given) and con- since their calculation involves calculating the stead of the area. Count the total number of different variet- veys information on the variance of the vari- frequencies of all the crops or varieties being Table 14.1 gives an example of calculat- ies in the community etal abundance distribution. investigated. ing evenness and divergence for varieties of In the case of a finite community) a more Bambara groundnut grown by a sample of ten Calculate the average number of varieties households in Tshongwe, Zimbabwe. per household (average richness) and compare appropriate formula would be: this with the total number in the community. h = ∑( (ni[ni−1])/(N[N−1]) ) Figure 14.1 Richness and evenness of taro and rice varieties in a Lyngngam community, Meghalaya, India. Calculate the frequencies of each variety Source: NESFAS, Agrobiodiversity, Land and People Project, PAR. where ni is the number of individuals in the 30 in the community as a whole so as to identify ith species and N is the total number of indi- Taro varieties those that are grown in only very small areas viduals. From a probabilistic viewpoint, this 24 by a few farmers and have a low frequency, as is the probability of any two individuals be- 18 these are at risk of being lost. ing the same species if drawn at random from 12 EVENNESS a population without replacement. 6 The relative abundance of crops or vari- However, the Simpson Index is generally eties (evenness) can be calculated using the expressed as 1−h (or 1/h) because h increases 0 M Rh Ki D Ba N W N Ty Th Ba Sh Py Simpson Index (Jarvis et al. 2008). It is rela- as diversity decreases. The following example atsa a ria ian h ga an io r a n a l w hm ng gp ja p g n a h e g r g n l i a e an m ng tively simple to calculate and depends to a uses the notation 1−h to indicate the Simpson ah on ng gsan substantial extent on the frequencies of the Index. As a consequence, it will be between 0 30 g most common varieties, which means that it and 1 and increase as diversity increases. High Rice varieties is less sensitive to situations where not all the values indicate low evenness while low val- 24 rare varieties have been identified. ues show that the frequencies of the differ- 18 ent types are relatively even. The household The Simpson Index is defined as: Simpson Index tells us about the distribution 12 h = ∑(p 2) of varieties or crops on each farm (do farmers i grow the same amounts of each variety or do where pi is the proportional representation 6 they grow different amounts). The community of each species, crop or variety, i.e. the frac- Simpson Index tells us about the distribution 0 tion of the total area of, for example, wheat B B B B B B B B B B B B B between varieties over the whole community. a m a d a a a i ba sa n a o m r a b a n a a a a a ai h w n it iju i a n n i o ja h m b m n r n a ar ah a i w r it sy g r p gw g b t h o r ap la a t ok ng Number of households Number of households Assessing Agrobiodiversity: A Compendium of Methods Section 14 - Richness, Evenness and Divergence for Crop Species and Varieties 79 1. Calculate the Simpson Index for each 3. Calculate the community Simpson Index In the example used for Table 14.1, the further the unique variety grown by Household household (each row in Table 14.1) using the same formula with the values community as whole grows four varieties of 1 (variety 4). o2+o2+ ... +o2 obtained from step 3 and the total area Bambara groundnut and each household grows 1 2 N The previous analysis can be extended under the crop. between one and three varieties, although 1- to assess any relationship between the se- N most farmers (seven out of ten) grow three va- ( ∑o ) In Table 14.1, the individual-level Simpson lected indices (richness, evenness, diversity) i rieties. The area under each variety on a farm i Index values for the ten households ranges and some explanatory variables. Among ma- ranges from 1000 to 2000m2 and the area giv- Where v is the area under variety 1 grown from 0 to 0.667 and the mean Simpson Index ny other statistical methods, regression mod- 1 en to the crop ranges for 1000m2–5000m2, so by that farmer, v that under variety 2, and is 0.564. The community-level Simpson Index elling could be used to explain the variation 2 the areas under each variety on each farm are where the total area under the crop for the value is 0.694. in univariate indices (defined as the depen- quite similar although there is some range in household is dent variable) as a function of some explan- N Divergence is the difference between the the area allocated by each household to the o = (∑o ). atory variables (defined as the independent i community evenness value and the average crop as a whole. While one household grows i variables). Linear regression or one of its ex- farm evenness value, divided by the communi- only one variety (Simpson Index 0), the others Calculate the mean evenness for the house- tensions should be applied, depending on the ty evenness value, i.e.: have Simpson values of 0.500–0.667. At 0.693, holds, not forgetting to include households characteristic of the response variable, the hy- the community Simpson Index is not too dif- with a Simpson Index of 0. (Community Simpson - HH Simpson) pothesis underlying the sampling design and ferent from the average household Simpson the relationship between dependent and inde- 2. Calculate the area under each variety at Community Simpson Index (0.564) and thus the divergence (0.186) pendent variables. Useful resources to guide the community level by summing the areas is relatively low compared with other exam- the researcher in choosing the appropriate for that variety over all households (each In the example in Table 14.1: ples you may find. This is a community where regression technique include Faraway (2014, column in Table 14.1). the households sampled have rather similar (0.694 − 0.564)/0.694 = 0.187 2016) and Zuur, Ieno and Smith (2007). strategies. It might be interesting to explore Cleaning bambara groundnut (Vigna subterranea), Mali. Photos: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods Section 14 - Richness, Evenness and Divergence for Crop Species and Varieties 80 Table 14.1 Richness and evenness (Simpson Index) for Bambara groundnut (Vigna subterranean) varieties from ten households in Tshongogwe, Lupane, Zimbabwe. FURTHER INFORMATION/ REFERENCES Source: SAFIRE, Agrobiodiversity, Land and People Project, PAR. Faraway JJ (2014) Linear Models with R, Second For a more advanced approach to exploring Household Total Estimated area of each VARIETY (m2) Richness HH Simson Index (HH) Area (or h) Edition (CRC Press, Boca Raton, FL, USA). richness and evenness, the following can be Faraway JJ (2016) Extending the Linear Model consulted: Var 1 Var 2 Var 3 Var 4 with R: Generalized Linear, Mixed Effects and Non- Baselga A (2010) Partitioning the turnover and HH 1 5000 0 2000 2000 1000 3 0.640 parametric Regression Models, Second Edition (CRC nestedness components of beta diversity. Global Press, Boca Raton, FL, USA). Ecology and Biogeography 19:134–143. HH 2 3000 1000 1000 0 1000 3 0.667 Jarvis DI, Brown AHD, Hung Cuong P (2008). Baselga A (2017) Partitioning abundance-based A global perspective of the richness and evenness multiple-site dissimilarity into components: Bal- HH 3 3000 1000 1000 0 1000 3 0.667 of traditional crop-variety diversity maintained by anced variation in abundance and abundance gra- farming communities. Proceedings of the National dients. Methods in Ecology and Evolution 8:799–808. HH 4 3000 1000 1000 0 1000 3 0.667 Academy of Sciences USA 105:5326–5331 Magurran AE (2003) Measuring Biological Di- A statistical package is freely available on R HH 5 2000 0 1000 0 1000 2 0.500 versity (Blackwell Publishing, Oxford, UK). see: Baselga A, Orme CDL (2012) betapart: an R HH 6 2000 0 1000 0 1000 2 0.500 Simpson E H (1949) Measurement of diversity. Nature 163:688. package for the study of beta diversity. Methods in Ecology and Evolution 3:808–812. HH 7 3000 1000 1000 0 1000 3 0.667 Zuur A, Ieno EN, Smith GM (2007) Analyzing Ecological Data (Springer Science & Business Me- HH 8 3000 1000 1000 0 1000 3 0.667 dia, New York, USA). HH 9 3000 1000 1000 0 1000 3 0.667 Mango varieties sold in the market, Mali. Photo: D. Mijatović HH 10 1000 0 0 0 1000 1 0.000 TOTAL 28000 6000 10000 2000 10000 4 0.694 Average richness 2.6 Community Frequency 1000 0.214 0.357 0.071 0.357 Household Simpson Index 0.564 Community Simpson Index 0.694 Divergence 0.187 15. DATA ORGANIZATION AND ANALYSIS Maize varieties, San Din Daeng, Thailand. Photo: D. Mijatović Assessing Agrobiodiversity: A Compendium of Methods 82 15. DATA ORGANIZATION AND ANALYSIS This section describes good practices for working with data collected during different investi- • Avoid leaving cells empty; use a 15.2 GOOD PRACTICE FOR gations and gives an overview of some techniques for the organization and analysis of data. It is unique code to denote missing DATA ANALYSIS intended to be only an introduction to some of the most important issues; information on where values. to find additional and more-detailed instructions are provided for the interested reader. • Always double check. Double check Discuss the research design and analyses • Human and computer readability. Data that dates, labels and numeric values are planned with a statistician ahead of time, if 15.1 ORGANIZING DATA should be formatted to be understandable consistent and stored correctly. possible. The specific question that you wish Any information collected should be or- by human eye but also to be easily processed to answer determines what data you should • Keep track of changes and have backups. ganised and stored in an appropriate way. The by computer software. Later analysis might collect and how they are analysed. Always find Sometime, somewhere, something will choice of where and how to store data should be carried out using statistical software out about and check the assumptions of the go wrong and you could lose your data. be based on the characteristics of data them- and ease of processing data will reduce chosen analysis procedures. The following are Always have backups. selves and the ‘audience’ for whom the da- your workload. some suggestions on data analysis approaches ta are intended. Keep data in formats that are • Always keep original data-record sheets and good practices: accessible to most people (i.e. in open for- • Metadata are important. Always include and note books and store them in a • Know the question. It is fundamental to mats and not in proprietary software formats). basic information about the author, safe place. They are your responsibility have a clear research goal (‘the question’) At present, Excel spreadsheets are one of the purpose and description of data, version and keeping them safe may be a legal number and explanations of any codes or in order to ensure that you collect the most commonly used tools for data entry and requirement as well as showing recognition labels and formatting conventions. This required data, organize it and then analyse storage. Broman and Woo (2017) and Ellis et and respect for the information providers. information can be stored in a separate it appropriately. al. (2017) provide practical guidelines for data organization and sharing. file. • Research design. Planning in advance the Wild fruits, Naxçıvan, Azerbaijan. • Be consistent and tidy.4 When entering data collection process and the variables Simple rules that can improve spreadsheet Photo: D. Mijatović data in spreadsheets one should: to be collected will improve the analysis data entry and subsequent analyses include and help in choosing the most suitable the following: • Label the top row with a header statistical techniques. Test your methods • Plan where and in what format data • Enter a single record in each if possible to identify potential issues and should be stored. This will facilitate the subsequent row (avoid double-row to improve data coding and consistency. identification of potential pitfalls in data headers or empty rows) • Check the quality of data. Identify and collection and data entry. • Store a single variable in each decide how to deal with missing values, • Keep in mind that in the future your column. Do not use a single cell to check data consistency and resolve any data might be shared with collaborators store multiple pieces of information miscoding. After this is done, the different or the public. Always keep track of the • Avoid using colours to convey indices to understand patterns of diversity data-entry process and keep a record of meaning. It is better to add a column and its management within and among all data transformations or computation where the information could be communities can be calculated (see actions. Ensure that shared files do not stored Sections 9.2, 10.2 and 14). include sensitive personal information about respondents. 4 Recommended readings are Broman and Woo (2017) and Wickham, (2014). Assessing Agrobiodiversity: A Compendium of Methods Section 15 - Data Organization and Analysis 83 15.3 EXPLORATORY DATA ANALYSIS The first step in any analysis is to look at • Calculate mean, median, range and you are applying a regression model, this residuals of the model (residuals being the the data patterns. In this phase, no specif- standard deviation. Descriptive statistics check should be applied to the residuals of difference between the observed and the ic hypothesis is tested. Rather, the goal is to such as the mean or the median measure the model (residuals being the difference estimated values). have a preliminary understanding of the in- the overall tendency of the data. The between the observed and the estimated formation collected, by, for example, creating range and standard deviation provide • Independence. Many statistical techniques values). graphs and calculating appropriate descriptive information about its spread (variance). assume independence among observations. statistics that summarize the principal fea- The correlation coefficient can be • Check the normality of the data. A However, it is not always easy to identify tures of the data (such as mean, median and calculated to assess the relationship normal distribution of the data is a deviations from independence and it is variance). Exploratory analysis can include the between two quantitative variables to common assumption for many statistical helpful to take the possibility into account following: explore some preliminary relationships techniques. This can be visually checked in the experimental design phase. For that may be important for subsequent by plotting histograms. If the normality example, soil samples taken at locations • Prepare graphs. Graphs are great tools to analyses. In statistical techniques such as assumption is not met, consider close to each other may have more similar visualize and present patterns or general regression modelling, collinearity (when transforming the data or using statistical characteristics than samples taken far trends in data. Quantitative data might two variables are correlated) can result in techniques that do not require normality. from each other simply because they are be graphed using histograms (to highlight non-significant parameter estimates. Log transformation is a common way of close. This would be a deviation from an data distribution), scatterplots (to highlight transforming positive non-normal data assumption of spatial independence and trends, patterns and relationships with 15. 4 CHECKING ASSUMPTIONS (Figure 15.1). If you are using a regression might affect soil-sampling plans. other quantitative variables) and boxplots FOR STATISTICAL TESTING model, this check should be applied to the (to highlight clusters, groups and outliers), among other techniques. Qualitative data One can also check if assumptions required might be graphed using bar charts (to for applying a chosen analysis hold and, where highlight frequencies) or a Likert-type needed, take corrective action or opt for other Figure 15.1 Example of a log transformation of data to improve the conformity to a normal distribution. The histogram on the left shows the raw data and the histogram on the right shows the log transformed data scale (to highlight ratings). techniques, e.g. if the sample size is too small Source: Meldrum et al. (2018) • Check for outliers in the data. Double or if there are clear outliers. Checking assump- RAW DATA LOG TRANSFORMED DATA check the data for outliers (data values that tions can include: are very different from all the others in a • Check the variance of the data. One of set). Consult the original data forms and the assumptions of analysis of variance attempt to find reasons for inconsistent (ANOVA) and related techniques values. Exclude outliers if there is good (regression modelling, discriminant reason to believe the data are erroneous analysis) is homogeneity of variance. or that the sampled unit does not fit Homogeneity means that the variance of within the sample criteria (e.g. a survey different groups that you want to examine 0 0 of smallholder households that includes a is the same. This can be visually inspected farm with more than 100ha). using a boxplot, where the variation 0 20000 40000 60000 0 2 4 6 8 10 12 in the observations could be explored #Google scholar records #Google scholar records individually or subdivided into groups. If #species 200 600 1000 #species 50 100 200 Assessing Agrobiodiversity: A Compendium of Methods Section 15 - Data Organization and Analysis 84 15.5 STATISTICAL ANALYSIS LINEAR REGRESSION independent variable (in this case, age) on the dependent variable (in this case, knowledge) is There are many resources on the internet Example: Using ANOVA to investigate dif- Linear regression can be applied if the main relevant and not just statistically significant, that can be used for data analysis and appro- ferences in crop richness by household type objective of the research is to understand the because a very small effect can be statistically priate statistical tools relevant for agrobiodi- Figure 15.2 shows the mean and variation relationship between two variables. significant given a large-enough sample size. versity analysis. These include: of crop richness for different types of house- Example: Using linear regression to inves- Whenever possible, provide confidence inter- • The vegan packages for R – https://cran.r- hold that were identified through a cluster tigate differences in knowledge of wild plants vals or standard errors for any estimates. project.org/web/packages/vegan/index.html analysis (see ‘Ordination and clustering’). The ANOVA test shows that the level of crop diver- Calculate and compare how many species MULTIVARIATE METHODS • Past3 – https://folk.uio.no/ohammer/past/ sity is not the same for all types of household. are mentioned on average by different gen- • Anthropac (Analytic Technologies, Inc.) Often, agrobiodiversity data include ma- The probability of the difference in crop rich- ders, occupations, ethnic groups or age groups. free software for analysing freelists – ness occurring by chance alone is less than 1 Figure 15.3 shows an example of the relation- ny variables, including the presence or level http://www.analytictech.com/anthropac/ of production of many species, varieties and in 20 (p<0.05). To determine which household ship between the age of informants and their anthropac.htm breeds and social and environmental data. It type has significantly higher crop richness, a knowledge on wild food plants. To conclude post hoc test is needed. Tukey’s test of honest that this is a statistically significant trend, the is possible to construct more-complex models Relatively simple analyses that are of- regression analysis would need to show that using multiple ANOVA, multiple regression, ten used include test of independence (such significant differences is commonly applied the probability of the slope being different to general linear models, generalized linear mod- as chi square), ANOVA and linear regression. in such cases. From the graph, it can be seen zero is less than 1 in 20 (p<0.05). You should els and a wide number of other possibilities. ANOVA, linear regression and their exten- that cluster 1 has the highest diversity, clus- sions may be used to assess differences be- ter 2 is in the middle and cluster 3 has lowest always check that the estimated effect of the Figure 15.3 Relationship between the age of informant and number of use reports and number of wild food tween groups and relationships between two crop diversity. plant categories in the White Carpathians (Czech Republic). Source: Pawera et al. (2017) or more variables. When there is more than 40 one variable of interest (dependent variable in Figure 15.2 Boxplot of crop richness by household the linear regression framework), multivariate type. Source: Bioversity International and Gene Campaign, IFAD-NUS Project. analysis should be considered rather than just 30 analysing each variable separately. These dif- ferent methods are described in most statistics manuals or text books (see ‘Further reading’ at 20 the end of this section). ANALYSIS OF VARIANCE 10 ANOVA is one of the most commonly used statistical techniques to test whether there are 0 Use reports (r=0.15) significant differences between two or more Food categories (r=0.26) groups. The assumptions of ANOVA are: Regression line 1 2 3 • Independence of observations 20 30 40 50 60 70 80 90 100 Household type (cluster) • Normal distributions of the residuals Age of informants • Homogeneity of variances. Crop richness 4 6 8 10 12 14 Number of reports and food categories Assessing Agrobiodiversity: A Compendium of Methods Section 15 - Data Organization and Analysis 85 ORDINATION AND CLUSTERING • Multiple factor analysis, for combinations FURTHER INFORMATION/ of quantitative and qualitative variables REFERENCES Ordination and clustering are complemen- • Non-metric multidimensional scaling, Agresti A (2002) Categorical Data Analysis, Meldrum G, Padulosi S, Lochetti G, Robitaille tary methods that enable associations and which is well suited for species composition Second Edition (Wiley-Interscience, Hoboken, New R, Diulgheroff S (2018) Issues and prospects for the groupings of variables to be recognized. These data. Jersey, USA). sustainable use and conservation of cultivated veg- approaches can help reduce the complexity of etable diversity for more nutrition-sensitive agri- Broman KW, Woo KH (2017) Data organiza- the dataset and target key variables that can Example: Clustering to define household culture. Agriculture 8(7):112. tion in spreadsheets. The American Statistician be subject to more-specific modelling and hy- typologies 72(1):2–10. Pawera L, Łuczaj Ł, Andrea Pieroni A, Polesny pothesis testing. Common methods for ordi- A clustering of households in Uttaranchal Z (2017) Traditional plant knowledge in the White Ellis SE, Leek JT. (2017) How to share data for nation include: Carpathians: Ethnobotany of wild food plants and India was made based on crop and livestock collaboration. PeerJ Preprints 5:e3139v5. crop wild relatives in the Czech Republic. Human • Principle components analysis, which is species maintained, irrigated area, income Hastie T, Tibshirani R, Friedman J (2009) The Ecology 45(1):1–17. used for quantitative variables sources, farm size and income level. A geo- Elements of Statistical Learning: Data Mining, Wickham H (2014) Tidy Data. Journal of Statisti- graphic pattern in the household typologies Inference, and Prediction (Springer-Verlag, New • Multiple correspondence analysis, for cal Software 59(10). York, USA). qualitative variables was apparent when plotted on a map (Figure Zuur AF, Ieno EN, Smith GM (2007) Analyzing 15.4). Legendre P, Legendre L (1998) Numerical Ecol- Ecological Data (Springer Science + Business Me- ogy, Second English Edition (Elsevier Science, dia, New York, USA). Amsterdam). Figure 15.4 Clustering of households based on crop and livestock species maintained, irrigated area, income sources, farm size and income level using multifactor analysis and hierarchical clustering with the FactomineR package. A geographic pattern in the household typologies was apparent when plotted on a map. Source: Bioversity International and Gene Campaign, IFAD-NUS Project. Factor Map Cluster 1 Cluster 2 Cluster 3 -4 -2 0 2 4 6 Dim 1 (10.26 %) -4 -2 0 2 4 PARPlatform for agrobıodıversıty research http://agrobiodiversityplatform.org