Local to regional-scale mechanisms behind successful climate services for agriculture in Latin America Diana Giraldo a,b, David Ríos b, Carlos Navarro-Racines c, Kemly Camacho d, Armando Martínez-Valle e, Steven D. Prager b,f, Diego Obando g, Carlos Zelaya e, Deissy Martínez-Baron b, Ángel G. Muñoz h, Julian Ramirez-Villegas i,j,k,* a School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom b International Center for Tropical Agriculture (CIAT), Cali, Colombia c International Center for Tropical Agriculture (CIAT), c/o IICA, Guatemala City, Guatemala d Independent Consultant, Sulá Batsú Cooperative, San José, Costa Rica e International Center for Tropical Agriculture (CIAT), Managua, Nicaragua f Bill and Melinda Gates Foundation, Seattle, United States g International Center for Tropical Agriculture (CIAT), Tegucigalpa, Honduras h Department of Earth Sciences. Barcelona Supercomputing Center (BSC). Barcelona, Spain i International Center for Tropical Agriculture (CIAT), c/o Bioversity International, Rome, Italy j Bioversity International, Rome, Italy k Plant Production Systems Group, Wageningen University & Research, Wageningen, the Netherlands A R T I C L E I N F O Keywords: Climate services Decision-making Sustainability Multi-stakeholder network Outcome Harvesting A B S T R A C T The provision of climate services (CS) has grown at an unprecedented rate over the last decade in response to climate-related risks in several sectors of the global economy; this is especially true in agriculture. Several studies document lessons learnt from (un)successful climate services, and attempt to distil these into key principles, recommendations, or requirements. However, limited systematic analysis and data on the characteristics of the CS that are conducive to success exist to date, including for agriculture. Here, we analyse the Local Technical Agroclimatic Committees (referred to here by its Spanish acronym MTAs) as a CS approach that effectively delivers in formation to farmers sustainably and at local scale. We propose a framework comprising sixteen metrics that help measure the effectiveness, sustainability, and scalability as key dimensions of CS success. We apply this framework to 26 MTAs across four Latin American countries, namely, Guatemala, Honduras, Nicaragua, and Colombia. The analyses revealed that the MTAs played a significant role in CS transformation pathways, producing a total of 158 outcomes (changes in behaviour of people or institutions), and involving at least 279 institutions at various levels and with diverse roles. Analyses of the sixteen metrics revealed a wide range of performance across the 26 MTAs, with nearly half of the MTAs considered to have or nearly-achieved effectiveness, sustainability, and scalability. MTAs success stems not only from an increase in numbers of farmers and locations reached but also from the evolving roles and responsibilities of a diverse ecosystem of actors that accompany enhanced capacities and tangible benefits on the ground. Based on these results, we propose key CS elements, namely, collaboration; participation; adaptability and flexibility; financial (crowd) resourcing; robust governance and strong * Corresponding author at: International Center for Tropical Agriculture (CIAT), c/o Bioversity International, Via di San Domenico, 1, 00153 Rome, Italy. E-mail address: j.r.villegas@cgiar.org (J. Ramirez-Villegas). Contents lists available at ScienceDirect Climate Risk Management journal homepage: www.elsevier.com/locate/crm https://doi.org/10.1016/j.crm.2025.100721 Received 24 January 2024; Received in revised form 6 June 2025; Accepted 11 June 2025 Climate Risk Management 49 (2025) 100721 Available online 16 June 2025 2212-0963/© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). mailto:j.r.villegas@cgiar.org www.sciencedirect.com/science/journal/22120963 https://www.elsevier.com/locate/crm https://doi.org/10.1016/j.crm.2025.100721 https://doi.org/10.1016/j.crm.2025.100721 http://creativecommons.org/licenses/by/4.0/ leadership; awareness of and improvements in data availability, quality, and assurance; capacity development; user-centred communication; adequate incentives; and enabling policy environment. 1. Introduction The provision of Climate Services (CS) has grown in an unprecedented manner over the last decade in response to climate-related risks in several sectors of the global economy (Lourenço et al., 2015; Vaughan et al., 2016), and most notably in agriculture (Chiputwa et al., 2022; Vaughan et al., 2019a; Hansen et al., 2022a). CS are defined as the generation, translation and dissemination of climate information to support decision-making (Vaughan & Dessai, 2014). The Global Framework for Climate Services (GFCS) emphasizes tailoring climate information to user needs, while other definitions highlight co-production, accessibility, and actionable relevance from regional to local scales (Born et al., 2021; Vaughan et al., 2016). A variety of CS are currently operational in many countries across the globe (Ferdinand et al., 2021; Hansen et al., 2019; Vaughan et al., 2019b). These services have been designed and implemented through either bottom-up processes that foster the active involvement and participation of multiple stakeholders (e.g., farmers, field officers, government, business, civil society, and academia) or top-down processes in which there is limited or no consideration of end users and their needs (Fraser et al., 2006; Kolstad et al., 2019). A growing body of literature suggests that bottom-up approaches that systematically and widely consider users and their needs are more likely to succeed (Brasseur and Gallardo, 2016; Clarkson et al., 2022; Hansen et al., 2022a; Lourenco et al., 2015; Tall et al., 2014). We define success in CS as encompassing effectiveness, scalability, and sustainability (Ferdinand et al., 2021; Hansen et al., 2022a, see Sect. 3.2.2). Early work by the US National Academy of Sciences (Council, 2001) identified five conditions for successful CS, namely that they are user-centric, are research-based, use advanced climate information at different time and spatial scales, promote stewardship toward the knowledge base, and leverage participation of different stakeholders. These conditions, however, are only loosely consistent with the five CS design recommendations of Tall et al. (2014), and the six core principles proposed by Ferdinand et al. (2021). Tall et al. (2014) highlight co-production; partnerships between organizations of different nature; use of varied communication channels to reach the last mile; continuous learning and improvement; and engagement and targeting of the most vulnerable. Ferdinand et al. (2021) identified data quality, equity, co-creation, accountability, sustainability, and scalability as key principles to drive investment and service provision. Most recently, Hansen et al. (2022) identified four drivers of national climate services—demand heterogeneity, policy, last-mile capacity, and support from the external CS community. Though these knowledge and practice syntheses are broad reviews of current practice and can help guide climate service imple mentation, existing literature tends to focus either on top-down institutional arrangements (e.g., policy frameworks and governance structures) and detailed local case studies of CS design and use (Hansen et al., 2022a; Ferdinand et al., 2021; Tall et al., 2014). These studies have generated valuable insights, particularly regarding user needs, institutional barriers, and design principles. However, many rely heavily on first-hand practitioner accounts or expert consultation, often without methods for comparison across contexts (Vaughan & Dessai, 2014). Addressing this gap is essential for generating transferable lessons and informing scalable implementation models for participatory climate services. The goal of this study is to help address remaining gaps in understanding by providing a systematic analysis of the characteristics of climate services, with a focus on the Local Technical Agroclimatic Committees (MTAs, for their acronym in Spanish). MTAs are participatory spaces that bring together stakeholders to co-produce, translate, and disseminate agroclimatic information. Specifically, we aim to evaluate and distill the key institutional and participatory elements that contribute to their success—or limitations—in order to generate clear, evidence-based recommendations for CS implementation across the region. We address the following research question: How can the interaction of institutions within MTA networks foster the reconfiguration of climate services to enhance their effectiveness, sustainability, and scalability? We systematically documented development outcomes (i.e., systems changes and transformations) arising from the MTAs in four countries in Latin America (Guatemala, Honduras, Nicaragua, Colombia) using an outcome harvesting approach that involved a literature review and key informant interviews. Using the information gathered, we then synthesized the outcomes achieved and assessed the effectiveness, sustainability, and scalability of the MTAs, providing insights into regional elements and mechanisms relevant for climate service implementation in Latin America. 2. The local technical agroclimatic Committees (MTAs) approach The MTAs approach was developed in Latin America (LAM) as a blueprint vehicle for supporting the provision of timely, accessible, and useful climate information to farmers (Loboguerrero et al., 2018). Through the MTAs farmers and other stakeholders (i.e., field technicians, scientists, and representatives from the public and private sector) access climate information across multiple timescales, including historical records, short-term forecasts, and seasonal outlooks. This information is provided in various formats, such as maps, time series, and summaries tailored to local agricultural calendars (CIAT, 2023; Zapata-Caldas et al., 2024). MTA participants then assess how climate variability may affect agri-food systems, co-develop recommendations to respond to anticipated conditions, and generate actionable products for broader dissemination—bulletins, radio programs, WhatsApp messages—. The role of the National Meteorological and Hydrological Services (NMHSs) is central to this process, particularly in generating weather and climate data, co- producing agroclimatic bulletins, and offering technical support to ensure that information is locally relevant, timely, and decision- oriented. A total of 102 MTAs have been created in 11 Latin American countries; to date, 88 remain active (Fig. 1; Giraldo Mendez D. Giraldo et al. Climate Risk Management 49 (2025) 100721 2 et al., 2023a; Giraldo-Mendez et al., 2021). See Supplementary Table S1. The MTAs form a wide network that addresses climate risk management from the local to the national and regional levels. Today, they contribute to the regional strategy for disaster risk management in the agricultural sector and food and nutrition security in LAM (FAO, 2018), national climate change adaptation plans (Howland and Francois Le Coq, 2022); climate change national communi cations (Martínez et al., 2021); and the Nationally Determined Contributions of countries such as Colombia, Honduras, Guatemala, and Panamá (IDEAM and MADS, 2017; NDC Partnership, 2018). For a more detailed description of the MTAs approach the reader is referred to Loboguerrero et al. (2018). 3. Materials and methods This paper makes a methodological contribution by providing empirical evidence-based on the evaluation of the MTAs through an iterative process (Fig. 2) comprising three components: (i) an analysis of innovation areas and their pathways using the Outcome Harvesting tool; (ii) an evaluation of institutional collaboration and influence through Social Network Analysis (SNA) and (iii) a robust framework to assess the sustainability, effectiveness, and scalability of the MTAs using a Success Achievement Score. Fig. 1. Local Technical Agro-climatic Committees (MTA) established in Latin America. The MTA names focus of this study are shown in bold. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 3 3.1. Inventory of institutional participation We focus on four Latin American countries where MTAs have been in operation for the longest time up to the time the present study was initiated (2019). We analysed a total of 26 MTAs (Table 1; indicated in bold text in Fig. 1) in Colombia (9), Honduras (7), Guatemala (7), and Nicaragua (3). For each MTA we identified as wide as possible a list of participating institutions via consultation with the MTAs leader organizations and CGIAR research staff in the countries of interest. 3.2. Outcome harvesting Outcome Harvesting (OH) is a semi-structured method to identify system changes and transformations in a development context (Blundo-Canto et al., 2021). We are interested in the outcomes that the MTAs have generated within their national context. Outcomes are defined as “observable changes in the behavior, relationships, activities and actions of boundary partners” (Rassmann et al., 2013, p. 4). Harvesting refers to the use of a range of methods (e.g., literature reviews, interviews, focus group discussions) to gather evidence about the outcomes (Wilson-Grau, 2018). Applying the OH required defining, the change agent (i.e., the MTAs), the social actor (i.e., the participating institutions), and the harvester (i.e., an independent evaluator). We conducted the OH study at the end of 2019, focusing on outcomes generated from 2016 to 2019. The approach involved four steps: Fig. 2. Flowchart providing an overview of the analysis steps and results. Table 1 List of the 26 MTAs analysed in the four countries. Country ID MTA Name Year Established Colombia MTA_BOY MTA Boyacá 2018 Colombia MTA_CAL MTA Caldas 2017 Colombia MTA_CAU MTA Cauca 2012 Colombia MTA_COR MTA Cordoba 2015 Colombia MTA_MAG MTA Magdalena 2016 Colombia MTA_NAR MTA Nariño 2016 Colombia MTA_SAN MTA Santander 2016 Colombia MTA_SUC MTA Sucre 2016 Colombia MTA_TOL MTA Tolima 2017 Honduras MTA_COM MTA Comayagua 2016 Honduras MTA_PAR MTA El Paraiso 2016 Honduras MTA_CHO MTA Choluteca 2016 Honduras MTA_INT MTA Intibucá 2016 Honduras MTA_SRC MTA Santa Rosa de Copan 2016 Honduras MTA_OLA MTA Olancho 2016 Honduras MTA_STB MTA Santa Barbara 2016 Guatemala MTA_CS MTA Centro-Sur 2018 Guatemala MTA_CHI MTA Chiquimula 2017 Guatemala MTA_PRO MTA El Progreso 2019 Guatemala MTA_QUE MTA Quetzaltenango 2019 Guatemala MTA_QUI MTA Quiché 2019 Guatemala MTA_TOT MTA Totonicapán 2019 Guatemala MTA_ZAC MTA Zacapa 2019 Nicaragua MTA_EST MTA Estelí 2018 Nicaragua MTA_MAD MTA Madriz 2018 Nicaragua MTA_SOM MTA Somotillo 2017 D. Giraldo et al. Climate Risk Management 49 (2025) 100721 4 i) Identify guiding research questions: our objective was to understand transformations and systems changes and their relationship with MTAs elements and dynamics. Hence, our guiding question is What types of innovations have occurred regarding the decision- making of agricultural stakeholders as a result of the MTAs? This question allows us to focus on the results (i.e., the outcomes) as well as on the processes (i.e., the conditions and actions) that have led to these results. ii) Review existing documentation: the aim of this step was to gather information about internal MTAs organisation, dynamics, type of institutions involved and their roles, and potential outcomes achieved. Documents—including peer-reviewed literature, web pages, blogs, press releases, reports, and other forms of grey literature—were selected based on predefined criteria: (a) they described activities directly related to the MTAs, (b) reported observable changes in stakeholder behavior, institutional prac tices, or policies, (c) identified participating institutions, and (d) provided verifiable contextual information (e.g., time, loca tion). Documents were collected through MTA leaders, partner institutions, and targeted online searches. iii) Stakeholder interviews: we performed 62 semi-structured interviews with key stakeholders of the MTAs in Spanish (18 farmers organizations, 19 local government institutions, 11 NGOs, 9 central government institutions, 3 academic institutions and 2 private sector organisations). These 62 actors were selected from a larger list of participants based on how recurrently they participated in the MTAs. The interview used nine guiding questions (Table 2) aimed at gathering information along five key areas, namely, (1) role, functions, challenges, and limitations to participate in the MTAs; (2) perception of the value added of the MTAs to the stakeholders and farming households; (3) perception of the outcomes driven by the MTAs (i.e., what, when, where) and the underpinning evidence; (4) how the agroclimatic information is generated and disseminated in the MTAs; (5) esti mations of users reached and changes in practices or behaviour observed in them. These five areas help us in identifying and mapping the outcomes, but also in measuring the scale and understanding the sustainability of the MTAs (also see Sect. 3.3). The interviews were conducted—using a combination of in-person visits, videoconferences, and phone calls—by an independent evaluator experienced in OH methodology. A standardized semi-structured interview protocol (Table 2) was used to ensure consistency across interviews. All interviews were audio-recorded with participants’ consent, transcribed verbatim, and translated into English. Coding consistency was ensured through a shared coding framework developed collaboratively with the independent evaluator, calibration exercises to align interpretation, and regular cross-checking throughout the analysis. Triangulation with document analysis further strengthened the reliability and validation of the identified outcomes. iv) Identify and validate outcomes: in this step, the potential outcomes are first reviewed, and verified according to the SMART— Specific, Measurable, Achievable, Relevant, Timely—indicators often used in outcome harvesting approaches (Wilson-Grau, 2018). In the validation process, the harvester compares results across institutions interviewed and between interview data and literature but also obtains the views of one or more individuals who are independent of the MTAs (third parties) but knowl edgeable about one or more of the outcomes and the contribution of the MTAs. The validated outcome database is then analysed to clearly outline innovations and their pathways (e.g., institutions, practices, policies, knowledge, and relationships) and map them in a timeline. The analysis of the documentation review and the interviews (translated into English) was carried out using the Nvivo software (Jackson et al., 2019) through a structured deductive–inductive coding process. Initial coding categories followed the OH interview (Table 2), focusing on institutional roles, participation, communication methods, and observed impacts, while additional themes were identified inductively. All coded information was tagged with metadata (e.g., country, year, MTA). Coding explicitly captured who changed, what changed, when and where changes occurred, and how the MTAs contributed to these transformations. Table 2 Semi-structured interview questions used in the Outcome Harvesting. 1. In which MTAs does your institution participate? 2. What has been the role or function of your institution in the MTA? What challenges and/or limitations has your institution experienced in participating in the MTA? 3. What are the key participating institutions in the MTA? Do you consider that the MTA generate transformations for the participant institutions and/or farming households? Explain why? 4. The MTA has produced outcomes in the following areas (answer Yes/No): A. Agroclimatic information B. Public policy C. Institutional programs D. Practices of technical staff E. Adaptation practices implemented F. Another; which? 5. About the outcomes identified A. Describe the outcome you identify B. When (year) did the outcome, you identify take place? C. Where did the outcome happen? (territory, institution, or project) D. How did the MTA contribute to this outcome? E. Why is this outcome important? 6. How is the information generated by the MTA disseminated in your territory? 7. How many farmers do you estimate are receiving the information generated by the MTA? 8. What are your recommendations for the future of the MTA? What is your vision for the future of the MTA? D. Giraldo et al. Climate Risk Management 49 (2025) 100721 5 3.3. Network analysis of the MTAs Because of their composition and nature (see Sect. 2 and Loboguerrero et al., 2018), the MTAs can be described as multi- stakeholder platforms or innovation networks (Adekunle and Fatunbi, 2012; Koerner et al., 2022). Hence, we first applied network analyses (Hermans et al., 2017; Sartas et al., 2018) to investigate the structure of the relationships shared by individual institutions according to their types (institutional network) and roles (influence network) in the MTAs networks at country level. The institutional network analysis systematically assesses the exchange and dissemination of new information across the MTAs partner organizations, contributing to our understanding of both the sustainability of the MTAs and their capacity to reach their various constituencies (Sartas et al., 2018; Seifu et al., 2022). To build the network, we considered the MTAs as the nodes that connect different institutions and allowed connections between any participating institutions (through the MTAs) regardless of their role, participation level, and contribution. The type of institution (e.g., farmer organization, private sector, government), and level (e.g., regional, national, local) were considered as attributes. The influence network helps understand how different types of institutional roles may contribute to key dimensions of MTA performance—particularly in effectively reaching users, and potentially supporting sustainability and scaling (Ofoegbu and New, 2021; Tesfaye et al., 2020). In this network, connections occur only if participating institutions had a clearly defined role. The at tributes analyzed were the roles of the institutions—such as MTA leader, passive participant, coordination support, climate and crop technical support, capacity building, and resource mobilization. 3.4. Analysis of sustainability, scalability, effectiveness of the MTAs In general terms, success is seen as the ability of CS to generate long-term development outcomes at scale (Ferdinand et al., 2021; Hansen et al., 2022b, 2022a). While the impact pathways for CS to generate outcomes and the outcomes themselves are varied (Hansen et al., 2022b), this definition of success implies three elements. A first dimension is scale, which implies that the MTAs reaches many organizations, people, and covers a large and growing geographic area. The second dimension is sustainability, which implies that the MTAs and its outcomes are sustained over the long-term. The final dimension is the effectiveness at reaching users, which relates to the ability of the MTAs to deliver timely and relevant information to farmers—aligned with their decision-making cycles and perceived needs (Giraldo et al., 2023)—thereby enhancing the uptake of the information. Fig. 3 proposes a list of key elements that contribute to effectiveness, sustainability, and scalability based on existing literature (Hansen et al., 2021, 2022a; Sarku et al., 2022) covering a wide range of contextual factors. To assess MTA success, we calculated sixteen metrics derived from three sources: (i) network analysis of institutional collaboration and influence networks (Sect. 3.3), (ii) direct measurements from MTA records (e.g., attendance, bulletins), and (iii) outcome har vesting evaluation. These metrics were selected through a triangulated process grounded in the literature, empirical relevance, and feasibility of consistent application across MTAs. Each metric was mapped to one or more dimensions of success—effectiveness, sustainability, and scalability. Each metric was standardized using binary thresholds (1 = meets defined criteria, 0 = does not), following established approaches for ensuring comparability across heterogeneous cases (Wilson-Grau, 2019; Hermans et al., 2017; Ferdinand et al., 2021). A detailed description of each metric, justification, and supporting references is provided in Supplementary Table S2. We determine which of these sixteen metrics (measurable for the MTA through the sixteen metrics in Table 3) are most likely to have resulted in their success. To this aim, we first map each of the sixteen metrics to the sustainability, effectiveness, and scale of the MTAs (see Fig. 3). Then, we integrate the sixteen metrics into a single score that responds to the three dimensions of success. Finally, we compare the numbers and extent of the outcomes identified integrated score across all MTAs and use these to draw specific rec ommendations for the design of CS. To assess the scaling of each MTA, we analysed nine metrics. Specifically, we examined the degree of centrality within the collaboration network, the percentage of farmers reached through the OH and M&E, and the number of communication channels employed to disseminate the information generated within each MTA further the bulletin (i.e., WhatsApp, radio, podcast, SMS). The policy environment and collaboration were analysed through the proportions of institutions involved in each MTA, understanding different stakeholders’ roles in scaling and the dynamics played out at different levels of decision-making, governance, and leadership. Furthermore, diversification in systems (i.e., metric H: number of agri-food systems) served as an entry point or “spark of interest” that enabled stakeholders to expand their reach and cover a greater number of systems within each MTA. For sustainability, we conducted an analysis of eight metrics. These metrics included the centrality measurements (degree, betweenness, closeness) organization (i.e., frequency and timing of the meetings), stakeholder participation (e.g., number of meetings since creation), proportions of institutions involved, dissemination channels, and governance and leadership (e.g., presence or not of the public institutions). Finally, to assess effectiveness, we analysed nine metrics including the types and diversity of climate and agronomic information, the involvement of field officers, the availability of training and involvement of academia, the types of channels used to disseminate content, types of institutions participating, and the accountability (monitoring and evaluation of outcomes). To assess the performance of each MTA, we developed the Success Achievement Score (SAS), a composite indicator integrating 16 binary metrics (Eq. (1). In equation (1), the numbers 1 to 3 that multiply the metrics correspond to a dimensionality weighting, representing the number of dimensions to which those metrics contribute to. See Supplementary Methodology S1 for detailed scoring procedures and dimensional weighting rationale. SAS = 2(A + B + C)+3(D)+ 1(E)+1(F)+3(G)+2(H)+1(I)+1(J) + 2(K)+ 1(L)+3(M)+2(N)+1(O)+2(P) (1) D. Giraldo et al. Climate Risk Management 49 (2025) 100721 6 Fig. 3. Dimensions of climate services success, along with a list of key elements and their corresponding metrics. *Nodes with higher betweenness tend to have a greater influence on the flow of information or resources within the network. **Nodes with higher closeness centrality are more “central” in the network because they tend to be closer to other nodes, making them more efficient in terms of communication and information spreading. D. G iraldo et al. Climate Risk Management 49 (2025) 100721 7 For example, A, B and C correspond to centrality measures, and if the MTA complies with all the centrality metrics, the sum of A + B + C would equal 3; in the given formula, A, B, and C are multiplied by 2 because they contribute to 2 dimensions (Table 3). Similarly, the metric D (% of types of institutions) contributes to 3 dimensions (sustainability, effectiveness, and scale), and it is therefore multiplied times 3. The weighting strategy was developed in response to both theoretical framing and empirical constraints. Our three dimen sions—effectiveness, sustainability, and scalability are treated as equally important, reflecting the conceptual position that no single Table 3 Metrics of the MTAs assessed and their relationship with the three dimensions of success (sustainability, effectiveness, and scale). Metrics of the MTAs Method Relevance to success dimensions Effectiveness Sustainability Scale A. Degree of centrality (# connections) NA ​ X X B. Betweenness (# steps in shortest path) NA X X ​ C. Closeness (length of shortest path) NA X X ​ D. Different types of institutions NA X X X E. Organization: frequency of meetings DM ​ X ​ F. Participation: # meetings since creation DM ​ X ​ G. Accountability (M&E) # outcomes DM X X X H. Information: agri-food systems of focus DM X ​ X I. Information: types and scales of climate DM X ​ ​ J. Information: agronomic information DM X ​ ​ K. Dissemination: % Field officers NA, DM X ​ X L. Dissemination: % farmers receiving info DM ​ ​ X M. Dissemination: Types of channels DM X X X N. Governance and leadership NA, DM ​ X ​ O. Capacity building: Academia & training NA, DM ​ ​ X P. Public-private and resource mobilisation NA, DM ​ X X * Method: NA: network analysis; DM: direct measurement through the OH or consultation with MTA leaders. Fig. 4. Areas of Transformation with key outcomes (changes) identified during the 2016–2019 period across the network of MTAs in four countries (CO, NI, HN, GT). The scales represent the percentage of outcomes found in each AT. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 8 Fig. 5. Institutional network composition and characteristics for Colombia, Guatemala, Honduras, Nicaragua, and the regional network (left side). MTA nodes (black dots) are coded as shown in Table 1. The right side shows the number of organizations per level within each institutional network. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 9 dimension alone defines CS long-term success. The SAS is converted to percentage using the maximum possible SAS value (i.e., 29). The percentage is used to qualitatively assess the level of success of the MTA. In the present study, a SAS value below or equal to 50 % is assigned to mean no success has been achieved; a SAS value between 51 and 65 % means that the MTA is in only in the process of achieving success and requires substantial work in more than one dimension; a SAS between 66 and 89 % means that the MTA has partially achieved success and with moderate or minor improvements in either sustainability, scale, or effectiveness would likely move toward totally achieving success; and a SAS value equal or above 90 % means that the MTA has totally achieved the three elements of success. The SAS calculation is performed for each MTA individually. The three dimensions addressed by the metrics with the highest weight in the formula are D, G, and M. These metrics represent the proportion of institutions present in the MTA in the network analysis, the number of outcomes identified in the OH, and the dissemination of information generated in the MTA beyond the agroclimatic bulletin, respectively. Fig. 5. (continued). D. Giraldo et al. Climate Risk Management 49 (2025) 100721 10 4. Results 4.1. Outcomes and transformations due to the MTAs A total of 243 outcomes were identified and analysed in the first round of outcome harvesting. After the verification process using SMART indicators, 158 outcomes remained, distributed across Colombia (61 %, n = 96), Honduras (16 %, n = 25), Guatemala (17 %, n = 27), and Nicaragua (6 %, n = 10). The 158 outcomes were grouped into five Areas of Transformation (AT) pointing out the three dimensions emerging from the implementation of the MTAs in the 2016–2019 period (Fig. 4). Most outcomes emerged around policy, governance, and leadership (AT5, 30 % of outcomes reported), followed by participation and collaboration (AT4, 27 %), changes in perceived usefulness (AT3, 22 %), communicating the agroclimatic information (AT2, 16 %), and data quality and assurance (AT1, 5 %). The first transformation area was data quality and assurance (AT1), whereby the main transformation was the integration of climate information into decision-making processes of the participating institutions. The OH process found that the MTAs encouraged a closer approach by National Meteorological and Hydrological Services (NMHS) to meet MTA participants’ needs. This closer approach specifically allowed (i) downscaling the climate predictions, (ii) integrating data from local weather station networks, and (iii) capacity building to understand climate forecasts as probabilities with degrees of uncertainty. More tailored information encouraged the uptake and dissemination of the information generated in the MTAs by the participating organisations in the MTA, therefore giving rise to a second transformation area around communicating the agroclimatic information (AT2, Fig. 3). Various local dissemination and communication mechanisms allow the information about how to cope with climatic variation to reach people beyond MTAs (see Supplementary Box S1). Furthermore, these local stakeholders further disseminate the information through their own collaboration networks, therefore reaching a larger audience. It is noteworthy, however, that small-scale farmers in remote areas are generally not reached by the MTAs. As climate-informed agronomic recommendations are developed and reach end users, a further transformation area is seen (perceived usefulness, AT3), whereby rural families reportedly adapted their farming practices based on MTAs information, often resulting in reduced losses and/or increased profitability. Farmers modify several production practices based on the agroclimatic information they receive at the MTAs (e.g., sowing dates, date to request credits to adjust it to the new sowing date, preparing tanks for rainwater harvesting in case of above-normal rainfall forecasts, pest and disease management). The MTAs have created a space to facilitate traditional and scientific literacy, democratizing agroclimatic knowledge and fostering significant improvements in participation and collaboration (AT4, Fig. 3) among the participants. Field officers gained a deeper un derstanding of the effects of climate variability, which enabled them to provide better guidance to farmers, ultimately leading to greater awareness and use of the agroclimatic information. Moreover, the MTAs incorporates farmers’ traditional knowledge (e.g., bioindicators) through its bulletins. Additionally, the MTAs serves as a local hub to exchange knowledge about several topics (aside from agroclimatic information), and to build capacity. Lastly, many outcomes (30 %) emerged around policy, governance, and leadership (AT5), as the MTAs contributed to the creation of local interinstitutional partnerships and helped attract new and strengthen existing climate adaptation projects and actions at both the national and local levels. At the national level, the MTAs have influenced the National Adaptation Plan and the Nationally Determined Contribution to the United Nations Framework Convention on Climate Change (Colombia), a law to create and sustain the MTA (Honduras, Ministerial Law 392–2017), and the internal strategy of the Guatemala Ministry of Agriculture and Livestock (Guatemala). More locally, the MTAs have leveraged the actions of several projects. The combination of public policy and organizational strategy has been able to attract funding for innovation, scaling, and basic operations but also has enabled a substantial degree of stakeholder coordination around climate services. 4.2. Unpacking the functioning and dynamics of the MTAs network With an understanding of the wide range of transformations occurring from the MTAs, we now set to analyse their dynamics and functioning. This is crucial because only with a deep understanding of the MTAs network, participant roles, key actors within the network, and their influence, we gain sufficient understanding of the institutional landscape, and of the functioning of the MTAs. In Fig. 5, each node (N) in a network represents an institution. The ties (L) between each node are depicted as lines and are connected to the MTA in a bidirectional (i.e., reciprocal) manner. Fig. 5 shows that the institutional network composition is smallest in Nicaragua (N = 18; L = 41) and largest in Colombia (N = 120; L = 371). The MTAs serves as the central node (in black dots in Fig. 5), with a wide variety of institutions connected to it in a fan-like structure. The MTA node assumes a critical role by directly connecting to the peripheral nodes, acting as a key node for agroclimatic information exchange amongst institutions, bridging gaps across scales and integrating different areas of knowledge (e.g., food security, early warning, agriculture, climate, financing). In the network structure identified, two groups of participating institutions generally emerge: (1) a group of organisations that are only connected with themselves through the MTAs; and (2) a group of organisations that are connected between themselves both directly and through the MTAs, and that are typically involved in multiple MTAs. The first group (peripheral) is typically composed by local-level and/or farmer-facing organisations that would typically play an important role in information translation and dissemi nation. The second group (the country core group) shows numerous ties in the network, likely has a greater degree of influence, and is composed by organisations with a diverse set of roles including climate forecast production (e.g., NMHS), coordination and/or funding (e.g., Ministries of Agriculture, international NGOs, national farmer organisations), and training (e.g., universities). To complement the national-level analyses, we conducted a regional-scale examination by aggregating institutional network data across the four countries. At this regional level, the network comprises 279 organizations (nodes) and 1,064 ties, revealing a D. Giraldo et al. Climate Risk Management 49 (2025) 100721 11 moderately dense but diverse structure of stakeholder interaction across the MTAs (Fig. 5e). Analysis of centrality metrics highlights important differences in how various institutional types are positioned within the network. International NGOs exhibit the highest betweenness centrality, suggesting that they act as key brokers or intermediaries, facilitating information flow between otherwise disconnected actors across countries. In contrast, programs and projects have the highest degree centrality, indicating that they maintain the most direct connections to other institutions—often serving as operational connectors across national and subnational levels. Further analysis of the two groups of stakeholders (peripheral and core) reveals a more nuanced picture in terms of stakeholders and their roles in each of the MTA (Fig. 6, also see Supplementary Fig. S3 for the influence network). More specifically, through the influence network analysis, the OH, and our own knowledge of the MTAs network, we identified six different roles in the MTAs network: passive participant (26 % participants across all MTA), MTA leader (10 %), MTA coordination support (15 %), crop technical support (31 %), climate technical support (9 %), and resource mobilisation (14 %). Passive participants primarily receive information, Fig. 6. Institutions (%) categorized based on their roles and contributions to the MTA in four countries. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 12 though they can become more active as time passes. The MTA leaders manage the MTA effort with support from the ‘MTA coordination support’. Both crop and climate technical support act as experts that provide technical information on either climate predictions or on the effect of a particular seasonal climate outlook on crops. The climate technical support is typically provided by meteorologists from the NMHS, except in Nicaragua, where no NMHS participation in the MTAs was documented; instead, climate information was provided by international organizations and regional projects supporting the MTAs. The crop technical support is provided by agronomists, extension officers (public and private), researchers, and farmers. A last role is resource mobilisation, focusing on raising and managing the financial resources to carry out the MTA meetings and further activities (e.g., creation and dissemination of the agroclimatic bulletin). 4.3. Characteristics of the MTAs in relation to their effectiveness, sustainability, and scalability While the SAS offers a synthesized view of MTA performance, it is crucial to unpack how individual MTAs perform across the three core dimensions—effectiveness, sustainability, and scalability—in order to understand the specific drivers and gaps within each. Fig. 7 shows the result of the integrated score, and its individual components (also see Supplementary Table S3). Effectiveness refers to the extent to which MTAs deliver timely, relevant, and actionable information that supports on-farm de cision-making. High effectiveness was observed in MTAs such as Córdoba, Boyacá, in Colombia, as well as El Paraíso in Honduras, Fig. 7. Comparison of ranking and metrics for quantify the success of an MTAs. Each metric in the formula has a value of 1 = YES (Y) if the MTA is above a certain threshold (measuring compliance), or 0 = NO (N) if it does not. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 13 which consistently integrated climate and agronomic information, engaged field-level extension agents, and reached farmers through diverse dissemination strategies. These MTAs also featured strong participation from technical institutions and demonstrated align ment between forecast content and crop-cycle decision windows. In contrast, MTAs with lower effectiveness scores—especially those in Nicaragua, as well as several in the moderate-SAS group—often lacked clear integration of agronomic advisories, had limited farmer representation, or relied solely on bulletin dissemination without active field-based engagement. This weakened the perceived utility and uptake of climate services at the farm level. Sustainability captures institutional continuity, leadership stability, and the operational capacity to persist independently of external facilitation. MTAs such as Sucre, Tolima, Cauca, and Nariño demonstrated strong institutional anchoring, regular meetings, and a stable core of participants, including public-sector representatives. These platforms showed signs of institutional maturity, including routines for self-evaluation, and some were integrated into regional planning or funding processes. By contrast, several MTAs—particularly those with SAS ≤ 65 %—displayed intermittent activity, relied heavily on donor-driven facilitation, or lacked long-term institutional commitments. In Nicaragua, ongoing political uncertainty and weak engagement from national authorities further limited the MTAs’ ability to function autonomously. These conditions disrupted continuity and limited the development of governance structures that support sustainability. Scalability reflects the potential of MTAs to influence broader systems through replication, policy integration, and multi- stakeholder participation. High-scoring MTAs in this dimension included El Paraíso, Córdoba, and Chiquimula, which not only involved a diverse range of actors—including NMHS, producer associations, and academic institutions—but also contributed outcomes that were referenced in national or regional planning discussions. These MTAs showed evidence of horizontal scaling (e.g., expansion to new areas) and vertical scaling (e.g., integration into institutional frameworks). Low-performing MTAs in this domain tended to have narrow institutional bases and lacked documentation of outcomes or engagement with decision-making bodies beyond the local scale. The three Nicaraguan MTAs, again, were especially constrained in this regard due to limited public-sector collaboration and low network density. This multidimensional analysis reveals that while a composite score like the SAS is useful for summarizing performance, it can mask important internal variation. These results suggest that targeted improvements in specific dimensions may yield more effective Climate Services than uniform interventions. 5. Discussion Our analysis shows that despite variation across the network of 26 MTAs analysed, 12 of the 26 MTAs in three out of the four countries have achieved all or nearly all elements of success (scalability, effectiveness in use, and sustainability). Furthermore, the comprehensive analysis of outcomes and MTAs characteristics presented here helped identify (i) areas of success and areas requiring further work in individual MTA; (ii) the diverse roles that the institutions play when collaborating within a network; (iii) lessons learned that could be applicable to other MTA implementations in different locations; and (iv) priorities for future climate services initiatives in Latin America. 5.1. Factors likely conducive to MTAs success This study provides one of the first comparative assessments of the MTAs across multiple countries, combining network analysis, outcome harvesting, and a composite scoring methodology. While Section 4.3 presents descriptive differences across effectiveness, sustainability, and scalability, the discussion here focuses on why MTAs performed differently. Several important lessons emerge from our research. Lesson 1: Lifespan and maturity shape performance trajectories MTAs with longer operational histories tended to perform better across all dimensions. The Cauca MTA (Colombia) served as the pilot for implementing the MTAs approach in 2012 (Loboguerrero et al., 2018). This MTA has been continuously operating until today (for almost ten years), continuously providing information to users and improving its own performance. A second reason relates to the spillover effect associated with the success of the pilot, which led to the near-immediate systematic expansion of the approach to several other departments with significant agricultural production. This early success and rapid growth phases which follow a typical technology adoption curve were also observed in Guatemala, whereby the success of a first MTA (Chiquimula in 2017) led to the rapid and systematic scaling of the approach over the entire country (see Fig. 1). Lesson 2: Central support with local autonomy drives success High-performing MTAs benefited from central-level support structures—whether through government ministries, international cooperation, or national producer organizations—that provided coordination, funding, and technical services. In Colombia, central support is especially crucial for financial resourcing (from the Ministry of Agriculture), climate forecast provision (from the NMHS), and for coordination (from international cooperation organisations). In Guatemala, the Ministry of Agriculture does not directly provide significant financial resourcing, but they leverage contributions of many other actors and projects, and coordinate the scaling (while allowing for local governance to develop) across the country. This central support allows for a highly decentralised governance system that is adaptable and responsive to local needs (in terms of information, capacities, and general technical support), but at the same time maintains a high level of coordination and resource (personnel, financing, capacities) flow between the central and the local organisations. On the contrary, in Honduras, where governance was centralised, the levels of success observed were much lower, and it seems unlikely to that progress will be made swiftly toward a higher performance level unless changes in the governance take place. Nicaragua’s fragmented and externally driven coordination further hampered continuity and local ownership. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 14 Lesson 3: Financial and institutional sustainability requires resilient resource flows Continued resourcing and resource flow (both financial and in-kind) has also been an essential ingredient in the success of the MTA. In Honduras, where significant sustainability challenges are observed, the MTAs management and governance was dependent on resources from international aid managed by the Secretariat of Agriculture and Livestock (SAG). Likewise, the participation of many organisations, and especially international cooperation, was also project dependent. In Nicaragua, where limited involvement and buy-in from the central Government was seen, international cooperation organisations took on the role of operating the MTAs with financial resourcing for the MTAs. Despite participation of local farmer organisations, sustainability challenges are clear in all Nicaragua MTAs. Lesson 4: Actor diversity and flexibility enhance adaptive capacity Two additional reasons that explain the success of the MTAs relate to the interdisciplinary and cross scale integration resulting from a high diversity of actors (see Fig. 6 and Fig. 7), and the flexibility and adaptability of the approach. Diversity fosters resilience and inclusion, brings together complementary perspectives in mediated discussions (Darnhofer et al., 2012; Singh et al., 2016), and enables interdisciplinary collaboration and integrated problem-solving (Clarkson et al., 2022). Collaboration can also facilitate the integration of climate information (from both local and scientific sources) with other data or knowledge (e.g., soil types, socioeconomics, vulnerability, capacity, risk, traditional knowledge) to produce downscaled information that is relevant for local decision-making (Born et al., 2021; Darnhofer et al., 2012; Nkiaka et al., 2019). On the other hand, adaptability and flexibility allowed continuity and even expansion during the recent COVID-19 pandemic lockdowns. Flexibility and adaptability have allowed the approach to be implemented and adjusted in a wide range of geographical, socioeconomic and political contexts, and have allowed the participation of a wide diversity of stakeholders with different (but complementary) roles (Giraldo-Mendez et al., 2021; Millar and Connell, 2010; Wigboldus et al., 2016). This finding aligns with our network analysis results, which showed that MTAs with higher actor centrality and cross-sectoral ties were more likely to report integrated outcomes and adaptive capacity. 5.2. (Re)defining success for climate services in agriculture We draw practical recommendations, which can guide the design and implementation of other climate service programs and projects. These extend beyond traditional recommendations such as improvements in the accuracy of climate predictions, and the timeliness of information dissemination (Guentchev et al., 2023; Millar and Connell, 2010; Woltering et al., 2019). 1. Collaboration among diverse stakeholders, each with access to unique sources of knowledge and power, encourages con nections within and across administrative levels. This interconnectedness is vital for achieving scalability in climate services (Hermans et al., 2017). 2. Participation can vary in intensity, from passive listening to active involvement in decision-making processes, which in fluences the transformative process and its outcomes (Lemos and Morehouse, 2005). Regular meetings proved of paramount importance in sustaining and growing stakeholder engagement. Monthly MTA are resource and time demanding. By contrast, quarterly MTA may fall short in providing relevant information during critical decision-making stages. Supplementary mechanisms such as virtual sessions or social media platforms (e.g., WhatsApp) are useful in addressing participation gaps. 3. Adaptability and flexibility of CS implementations necessitates the support of multiple stakeholders, utilizing their capacities and roles to help the service continuously evolve to meet specific contexts and needs (Hermans et al., 2017; Sartas et al., 2018). 4. Financial resourcing is critical for supporting the development and implementation of climate services. Projects that typically support the initial establishment of MTAs often have fixed timeframes, which do not align with the timelines required for transformational processes to lay the groundwork for sustainability (Dupar et al., 2021). Consequently, it is essential to develop adaptive and flexible frameworks or business models to accommodate the long-term needs of climate services, through a mix of public and private funding (Vogel et al., 2019). 5. Robust governance and strong leadership allow maintaining engagement and participation in climate service development, therefore preventing attendance to quickly diminish (Millar & Connell, 2010) and enhancing effectiveness (Vogel et al., 2019). Crucially, the leadership should be a recognized institution selected by participants, actively operating within the territory, and supporting service delivery beyond a project and/or program’s lifespan. Good leadership also encompasses accountability and transparency and adequate tracking of achievements and failures (e.g., Hernández-Quevedo et al., 2022). 6. Awareness of and improvements in data availability and quality of climate information, as reported by stakeholders involved in the process, helped participants become aware of available weather and climate information and how to access and use it (Bouroncle et al., 2019), fostering meaningful dialogue between climate scientists and users, and promoting effective communication and collaboration. 7. Capacity development was one of the processes gathered in the OH that reportedly led to significant changes in learning, knowledge, attitudes, capacities, and skills, leading to sustained interest in climate services beyond MTAs. This applies to the organisations (e.g., NMHS training for forecast improvement) as well as local agronomists and farmers. Improvement in institutional capacities can lead to the establishment of new institutional arrangements (e.g., new unit of agroclimatology), methods, practices, knowledge, objectives, and ways of thinking (Blundo-Canto et al. 2021). 8. User-centred communication involves users in the co-production process, creates feedback loops for continuous improve ment, fosters social inclusion, and recognises that transfer and diffusion are not linear processes, and that scaling should be viewed as part of a more continuous process (Woltering et al., 2019). For example, the MTAs in Cauca, Santander, and Boyacá in D. Giraldo et al. Climate Risk Management 49 (2025) 100721 15 Colombia were the first pilots to implement a participatory extension and climate services approach called PICSA (Clarkson et al., 2022). 9. Adequate incentives help encourage early participation, uptake, and behavioural changes, and sustain such engagement over the long-term. Millar and Connell (2010) caution that a project may appear successful if incentives encourage early partici pation and changes. However, it is essential to cultivate genuine engagement and understanding among stakeholders to ensure lasting benefits and meaningful progress in addressing climate-related challenges. 10. Lastly, successful climate services depend on fostering an enabling policy environment. Hermans et al. (2017) posited that influential organizations (who have a well-defined role, see Fig. 6) within a network can act as catalysts for change. For example, institutions within MTA networks may take on boundary-like roles by facilitating coordination, elevating climate services in policy agendas, and promoting institutional alignment as essential components of disaster risk management and the development of climate-resilient strategies (Dupar et al., 2021). The MTAs implementation support and align with national climate goals and commitments including NDCs and National Adaptation Plans (Howland & Francois Le Coq, 2022: Martínez et al., 2021). 6. Conclusion This paper develops and applies a comprehensive evaluation framework to evaluate the performance of Local Technical Agro climatic Committees (MTAs), combining social network analysis, outcome harvesting, and multi-criteria evaluation to offer a richer empirical lens for understanding how climate information translates into action. The success of MTAs lies in its ability to foster a diverse ecosystem of actors, drive capacity building, and deliver tangible benefits at the grassroots level. By serving as a vital space for interaction among all stakeholders, the MTAs promotes a collaborative approach bridging the gap between local, national, and regional levels, impacting the livelihoods of vulnerable communities across Latin America. The MTAs emphasis on participatory engagement and diverse representation has cultivated a robust governance framework that bolsters rural development and resilience at the community level. Additionally, establishing two-way conversation and trustworthy relationships between climate and crop scientists, agronomists, farmers, and other stakeholders participating in the process has been crucial in translating technical and scientific knowledge into practical decision-making processes in the real world. This study provides one of the first cross-country, evidence-based frameworks to evaluate the effectiveness of participatory climate services. The continued expansion and strategic uptake of MTA principles across Latin America not only validate our findings but demonstrate their lasting utility for scaling resilient, user-driven climate action. CRediT authorship contribution statement Diana Giraldo: Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. David Ríos: Writing – review & editing, Visualization, Investigation, Formal analysis, Data curation. Carlos Navarro-Racines: Writing – review & editing, Resources, Investigation, Data curation. Kemly Camacho: Writing – review & editing, Formal analysis, Data curation. Armando Martínez-Valle: Writing – review & editing, Resources, Data curation. Steven D. Prager: Writing – review & editing, Writing – original draft, Supervision, Resources, Investigation, Funding acquisition, Conceptu alization. Diego Obando: Writing – review & editing, Resources, Investigation, Data curation. Carlos Zelaya: Writing – review & editing, Resources, Investigation, Data curation. Deissy Martínez-Baron: Writing – review & editing, Resources, Funding acquisition, Conceptualization. Ángel G. Muñoz: Writing – review & editing, Resources, Investigation, Conceptualization. Julian Ramirez-Vil legas: Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was carried out with the support of the Climate Services for Resilient Development (CSRD), the AgMetGaps project, and United States Agency for International Development (USAID) Award#: AID-BFS-G-11-00002-10 towards the CGIAR Fund (MTO 069018); the Climate Change, Agriculture and Food Security (CCAFS), under the project Agroclimas (http://bit.ly/2i3V0Nh); and the AgriLAC Resiliente, Climate Resilience (ClimBeR), and Livestock & Climate (L&C) One CGIAR Initiatives. CCAFS is carried out with support from CGIAR Trust Fund Donors and through bilateral funding agreements. For details, please visit https://ccafs.cgiar.org/ donors. We also acknowledge support from the “A Common Journey” Project, funded by the International Fund for Agricultural Development (IFAD), and the Resilient Central America (ResCA) project funded by The United States Department of State, through a grant to The Nature Conservancy. ÁM was partially supported by ACToday, the first Columbia World Project, and by Grant RYC2021- 034691-I, funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. The views expressed in this paper cannot be taken to reflect the official opinions of these organizations. The authors acknowledge the contribution from the 279 partners that participate in the MTA across Latin America, and specifically the 62 organisations that were interviewed as part of D. Giraldo et al. Climate Risk Management 49 (2025) 100721 16 http://bit.ly/2i3V0Nh https://ccafs.cgiar.org/donors https://ccafs.cgiar.org/donors this work. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.crm.2025.100721. Data availability Data will be made available on request. References Adekunle, A., Fatunbi, A., 2012. Approaches for setting-up multi-stakeholder platforms for agricultural research and development. World Appl. Sci. J. 16, 981–988. Blundo-Canto, G., Andrieu, N., Soule Adam, N., Ndiaye, O., Chiputwa, B., 2021. Scaling weather and climate services for agriculture in Senegal: evaluating systemic but overlooked effects. Clim. Serv. 22, 100216. https://doi.org/10.1016/j.cliser.2021.100216. Born, L., Prager, S., Ramirez-Villegas, J., Imbach, P., 2021. A global meta-analysis of climate services and decision-making in agriculture. Clim. Serv. 22, 100231. https://doi.org/10.1016/j.cliser.2021.100231. Bouroncle, C., Müller, A., Giraldo, D., Rios, D., Imbach, P., Girón, E., Portillo, F., Boni, A., van Etten, J., Ramirez-Villegas, J., 2019. A systematic approach to assess climate information products applied to agriculture and food security in Guatemala and Colombia. Clim. Serv. 16, 100137. https://doi.org/10.1016/j. cliser.2019.100137. Brasseur, G.P., Gallardo, L., 2016. Climate services: Lessons learned and future prospects. Earths Future 4, 79–89. https://doi.org/10.1002/2015EF000338. CIAT, International Centre for Tropical Agriculture; Ministerio de Agricultura, Gadaneria y Alimentacion (Guatemala); Instituto Nacional de Sismología, Vulcanologia, Meteorologia e Hidrología, 2023. Recopilación de Boletines Agroclimáticos, Guatemala. Doi: 10.6084/m9.figshare.24796650.v1. Chiputwa, B., Blundo-Canto, G., Steward, P., Andrieu, N., Ndiaye, O., 2022. Co-production, uptake of weather and climate services, and welfare impacts on farmers in Senegal: a panel data approach. Agric. Syst. 195, 103309. https://doi.org/10.1016/j.agsy.2021.103309. Clarkson, G., Dorward, P., Poskitt, S., Stern, R.D., Nyirongo, D., Fara, K., Gathenya, J.M., Staub, C.G., Trotman, A., Nsengiyumva, G., Torgbor, F., Giraldo, D., 2022. Stimulating small-scale farmer innovation and adaptation with Participatory Integrated climate Services for Agriculture (PICSA): Lessons from successful implementation in Africa, Latin America, the Caribbean and South Asia. Clim. Serv. 26, 100298. https://doi.org/10.1016/j.cliser.2022.100298. Council, N.R., 2001. A Climate Services Vision: First Steps toward the Future. https://doi.org/10.17226/10198. Darnhofer, I., Gibbon, D., Dedieu, B. (Eds.), 2012. Farming Systems Research into the 21st Century: The New Dynamic. Springer Netherlands. Doi: 10.1007/978-94- 007-4503-2. Dupar, M., Weingärtner, L., Opitz-Stapleton, S., 2021. Investing for sustainable climate services. Insights from African Experience (research Report). ODI Report. FAO, 2018. Estrategia Regional para la Gestión del Riesgo de Desastres en el Sector Agrícola y la Seguridad Alimentaria y Nutricional en América Latina y el Caribe (2018-2030). Ferdinand, T., Illick-Frank, E., Postema, L., Stephenson, J., Rose, A., Petrovic, D., Migisha, C., Fara, K., Zebiak, S., Siantonas, T., 2021. A Blueprint for Digital Climate- Informed Advisory Services: building the Resilience of 300 Million Small-Scale Producers by 2030. Working Paper. Fraser, E.D.G., Dougill, A.J., Mabee, W.E., Reed, M., McAlpine, P., 2006. Bottom up and top down: Analysis of participatory processes for sustainability indicator identification as a pathway to community empowerment and sustainable environmental management. J. Environ. Manage. 78, 114–127. https://doi.org/ 10.1016/j.jenvman.2005.04.009. Giraldo, D., Clarkson, G., Dorward, P., Obando, D., Ramirez-Villegas, J., 2023. The development of a farmer decision-making mind map to inform climate services in Central America. Frontiers in Climate 5, 1235601. https://doi.org/10.3389/fclim.2023.1235601. Giraldo-Mendez, D., Navarro-Racines, C., Martínez Barón, D., Loboguerrero Rodriguez, A.M., Gumucio, T., Martínez, J.D., Guzmán-Lopez, H., Ramírez-Villegas, J., 2021. Local Technical Agroclimatic Committees (MTA): A detailed guide on its implementation step by step - Second Edition. Giraldo Mendez, D., Martinez Baron, D., Munoz, L.A., Navarro, C.E., 2023a. In: Agroclimatic Technical Committees (MTAs): Information within reach of Latin American farmers for better decision-making in the field, pp. 11–p. http://www.relaser.org/index.php/documentos/repositorio-de-documentos?task=document. viewdoc&id=588. Guentchev, G., Palin, E.J., Lowe, J.A., Harrison, M., 2023. Upscaling of climate services – what is it? A Literature Review. Clim. Serv. 30, 100352. https://doi.org/ 10.1016/j.cliser.2023.100352. Hansen, J., Kagabo, D., Clarkson, G., Furlow, J., Fiondella, F., 2021. Climate Services for Agriculture: Empowering Farmers to Manage Risk and Adapt to a changing climate in Rwanda (Final Project Report) (Report). CGIAR Research Program on Climate Change, Agriculture and Food Security. Hansen, J.W., Born, L., Dossou-Yovo, E.R., Mwongera, C., Dalaa, M.A., Tahidu, O., Whitbread, A.M., Solomon, D., Zougmore, R., Zebiak, S.E., Dinku, T., Grossi, A., 2022a. Country-specific challenges to improving effectiveness, scalability and sustainability of agricultural climate services in Africa. Front. Clim. 4. Hansen, J.W., List, G., Downs, S., Carr, E.R., Diro, R., Baethgen, W., Kruczkiewicz, A., Braun, M., Furlow, J., Walsh, K., Magima, N., 2022b. Impact pathways from climate services to SDG2 (“zero hunger”): a synthesis of evidence. Clim. Risk Manag. 35, 100399. https://doi.org/10.1016/j.crm.2022.100399. Hansen, J.W., Vaughan, C., Kagabo, D.M., Dinku, T., Carr, E.R., Korner, J., Zougmore, R.B., 2019. Climate Services can support African Farmers’ Context-specific Adaptation needs at Scale. Front. Sustain. Food Syst. 3, 21. https://doi.org/10.3389/fsufs.2019.00021. Hermans, F., Sartas, M., van Schagen, B., van Asten, P., Schut, M., 2017. Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling. PLOS ONE 12, e0169634. https://doi.org/10.1371/journal.pone.0169634. Hernández-Quevedo, M., Navarro-Racines, C., Ajquejay, S., Giraldo, D., Ramírez-Villegas, J., 2022. Monitoring and evaluation of the Local Technical Agroclimatic Committees (MTA) in Guatemala - 2022 (Report). Howland, F., Francois Le Coq, J., 2022. Disaster risk management, or adaptation to climate change? the elaboration of climate policies related to agriculture in Colombia. Geoforum 131, 163–172. https://doi.org/10.1016/j.geoforum.2022.02.012. Ideam, P., Mads, D., 2017. Resumen ejecutivo Tercera Comunicación Nacional de Colombia a la Convención Marco de las Naciones Unidas sobre Cambio Climático (CMNUCC). Terc. Comun. Nac, Cambio Climático Bogotá DC Colomb. Jackson, K., Bazeley, Patricia., Jackson, K., Bazeley, P., 2019. Qualitative data analysis with NVivo. Koerner, J., Thornton, P., Klerkx, L., 2022. Outcome-oriented multi-stakeholder network design: four innovation spaces to accelerate food system transformation. Knowl. Manag. Dev. J. Kolstad, E.W., Sofienlund, O.N., Kvamsås, H., Stiller-Reeve, M.A., Neby, S., Paasche, Ø., Pontoppidan, M., Sobolowski, S.P., Haarstad, H., Oseland, S.E., Omdahl, L., Waage, S., 2019. Trials, errors and improvements in co-production of climate services. Bull. Am. Meteorol. Soc. https://doi.org/10.1175/BAMS-D-18-0201.1. Lemos, M.C., Morehouse, B.J., 2005. The co-production of science and policy in integrated climate assessments. Glob. Environ. Change 15, 57–68. https://doi.org/ 10.1016/j.gloenvcha.2004.09.004. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 17 https://doi.org/10.1016/j.crm.2025.100721 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0005 https://doi.org/10.1016/j.cliser.2021.100216 https://doi.org/10.1016/j.cliser.2021.100231 https://doi.org/10.1016/j.cliser.2019.100137 https://doi.org/10.1016/j.cliser.2019.100137 https://doi.org/10.1002/2015EF000338 https://doi.org/10.1016/j.agsy.2021.103309 https://doi.org/10.1016/j.cliser.2022.100298 https://doi.org/10.17226/10198 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0080 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0090 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0090 https://doi.org/10.1016/j.jenvman.2005.04.009 https://doi.org/10.1016/j.jenvman.2005.04.009 https://doi.org/10.3389/fclim.2023.1235601 http://www.relaser.org/index.php/documentos/repositorio-de-documentos?task=document.viewdoc&id=588 http://www.relaser.org/index.php/documentos/repositorio-de-documentos?task=document.viewdoc&id=588 https://doi.org/10.1016/j.cliser.2023.100352 https://doi.org/10.1016/j.cliser.2023.100352 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0125 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0125 https://doi.org/10.1016/j.crm.2022.100399 https://doi.org/10.3389/fsufs.2019.00021 https://doi.org/10.1371/journal.pone.0169634 https://doi.org/10.1016/j.geoforum.2022.02.012 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0160 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0160 https://doi.org/10.1175/BAMS-D-18-0201.1 https://doi.org/10.1016/j.gloenvcha.2004.09.004 https://doi.org/10.1016/j.gloenvcha.2004.09.004 Loboguerrero, A.M., Boshell, F., León, G., Martinez-Baron, D., Giraldo, D., Recaman Mejía, L., Díaz, E., Cock, J., 2018. Bridging the gap between climate science and farmers in Colombia. Clim. Risk Manag. Scaling up Climate Services for Smallholder Farmers: Learning from Practice 22, 67–81. https://doi.org/10.1016/j. crm.2018.08.001. Lourenço, T.C., Swart, R., Goosen, H., Street, R., 2015. The rise of demand-driven climate services. Nat. Clim. Change 6, 13–14. https://doi.org/10.1038/ nclimate2836. Martínez, J.D., Leal, M., Martínez Barón, D., Navarro-Racines, C., Baena, A., Hernández, H., Godínez, H., Astaiza, M.L., Mercado, J., 2021. Memoria de los diálogos sobre sector agropecuario y cambio climático en Guatemala 2020 (Report). Millar, J., Connell, J., 2010. Strategies for scaling out impacts from agricultural systems change: the case of forages and livestock production in Laos. Agric. Hum. Values 27, 213–225. https://doi.org/10.1007/s10460-009-9194-9. NDC Partnership, 2018. Honduras Releases First NDC Partnership Plan for Climate Action | [WWW Document]. URL http://ndcpartnership.org/news/honduras- releases-first-ndc-partnership-plan-climate-action (accessed 1.14.20). Nkiaka, E., Taylor, A., Dougill, A.J., Antwi-Agyei, P., Fournier, N., Bosire, E.N., Konte, O., Lawal, K.A., Mutai, B., Mwangi, E., Ticehurst, H., Toure, A., Warnaars, T., 2019. Identifying user needs for weather and climate services to enhance resilience to climate shocks in sub-Saharan Africa. Environ. Res. Lett. 14, 123003. https://doi.org/10.1088/1748-9326/ab4dfe. Ofoegbu, C., New, M., 2021. The role of farmers and organizational networks in climate information communication: the case of Ghana. Int. J. Clim. Change Strateg. Manag. 13, 19–34. https://doi.org/10.1108/IJCCSM-04-2020-0030. Rassmann, K., Smith, R., Wilson-Grau, R., 2013. Retrospective ‘Outcome Harvesting’:. Sarku, R., Van Slobbe, E., Termeer, K., Kranjac-Berisavljevic, G., Dewulf, A., 2022. Usability of weather information services for decision-making in farming: evidence from the Ada East District. Ghana. Clim. Serv. 25, 100275. https://doi.org/10.1016/j.cliser.2021.100275. Sartas, M., Schut, M., Hermans, F., van Asten, P., Leeuwis, C., 2018. Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale. PLOS ONE 13, e0197993. https://doi.org/10.1371/journal.pone.0197993. Seifu, M., van Paassen, A., Klerkx, L., Leeuwis, C., 2022. A state-initiated multi-stakeholder platform as an instrument to build agricultural innovation system capacity: a case study from Ethiopia. Innov. Dev. 1–22. https://doi.org/10.1080/2157930X.2022.2064959. Singh, C., Dorward, P., Osbahr, H., 2016. Developing a holistic approach to the analysis of farmer decision-making: Implications for adaptation policy and practice in developing countries. Land Use Policy 59, 329–343. https://doi.org/10.1016/j.landusepol.2016.06.041. Tall, A., Hansen, J., Jay, A., Campbell, B.M., Kinyangi, J., Aggarwal, P.K., Zougmoré, R.B., 2014. Scaling up climate services for farmers: Mission possible. Learning from Good Practice in Africa and South Asia (report). Tesfaye, A., Hansen, J., Radeny, M., Belay, S., Solomon, D., 2020. Actor roles and networks in agricultural climate services in Ethiopia: a social network analysis. Clim. Dev. 12, 769–780. https://doi.org/10.1080/17565529.2019.1691485. Vaughan, C., Buja, L., Kruczkiewicz, A., Goddard, L., 2016. Identifying research priorities to advance climate services. Clim. Serv. 4, 65–74. https://doi.org/10.1016/ j.cliser.2016.11.004. Vaughan, C., Hansen, J., Roudier, P., Watkiss, P., Carr, E., 2019a. Evaluating agricultural weather and climate services in Africa: evidence, methods, and a learning agenda. Wires Clim. Change 10, e586. Vaughan, C., Muth, M.F., Brown, D.P., 2019b. Evaluation of regional climate services: Learning from seasonal-scale examples across the Americas. Clim. Serv. 100104. https://doi.org/10.1016/j.cliser.2019.100104. Vaughan, C., Dessai, S., 2014. Climate services for society: origins, institutional arrangements, and design elements for an evaluation framework. Wiley Interdisciplinary Reviews: Climate Change 5 (5), 587–603. https://doi.org/10.1002/wcc.290. Vogel, C., Steynor, A., Manyuchi, A., 2019. Climate services in Africa: Re-imagining an inclusive, robust and sustainable service. Clim. Serv. 15, 100107. https://doi. org/10.1016/j.cliser.2019.100107. Wigboldus, S., Klerkx, L., Leeuwis, C., Schut, M., Muilerman, S., Jochemsen, H., 2016. Systemic perspectives on scaling agricultural innovations. A Review. Agron. Sustain. Dev. 36, 46. https://doi.org/10.1007/s13593-016-0380-z. Wilson-Grau, R., 2018. Outcome Harvesting: Principles, Steps, and Evaluation Applications. IAP. Woltering, L., Fehlenberg, K., Gerard, B., Ubels, J., Cooley, L., 2019. Scaling – from “reaching many” to sustainable systems change at scale: a critical shift in mindset. Agric. Syst. 176, 102652. https://doi.org/10.1016/j.agsy.2019.102652. Zapata-Caldas, E.; Giraldo, D.; Bonilla Barillas, M.; Navarro Racines, C.E.; Orrego, E.; Gardeazabal, A.; Low, J.F.; Müller, A. (2024) Los servicios climáticos como bienes públicos codiseñados por entidades del sector agroalimentario latinoamericano: caso de estudio en Guatemala. In: Martínez-Baron, D. (et al.) Transición digital en agricultura y políticas públicas en América Latina. Rio de Janeiro (Brasil): E-papers Serviços Editoriais Ltda. p. 615-642. ISBN: 9786587065878. D. Giraldo et al. Climate Risk Management 49 (2025) 100721 18 https://doi.org/10.1016/j.crm.2018.08.001 https://doi.org/10.1016/j.crm.2018.08.001 https://doi.org/10.1038/nclimate2836 https://doi.org/10.1038/nclimate2836 https://doi.org/10.1007/s10460-009-9194-9 https://doi.org/10.1088/1748-9326/ab4dfe https://doi.org/10.1108/IJCCSM-04-2020-0030 https://doi.org/10.1016/j.cliser.2021.100275 https://doi.org/10.1371/journal.pone.0197993 https://doi.org/10.1080/2157930X.2022.2064959 https://doi.org/10.1016/j.landusepol.2016.06.041 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0250 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0250 https://doi.org/10.1080/17565529.2019.1691485 https://doi.org/10.1016/j.cliser.2016.11.004 https://doi.org/10.1016/j.cliser.2016.11.004 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0265 http://refhub.elsevier.com/S2212-0963(25)00035-X/h0265 https://doi.org/10.1016/j.cliser.2019.100104 https://doi.org/10.1002/wcc.290 https://doi.org/10.1016/j.cliser.2019.100107 https://doi.org/10.1016/j.cliser.2019.100107 https://doi.org/10.1007/s13593-016-0380-z https://doi.org/10.1016/j.agsy.2019.102652 Local to regional-scale mechanisms behind successful climate services for agriculture in Latin America 1 Introduction 2 The local technical agroclimatic Committees (MTAs) approach 3 Materials and methods 3.1 Inventory of institutional participation 3.2 Outcome harvesting 3.3 Network analysis of the MTAs 3.4 Analysis of sustainability, scalability, effectiveness of the MTAs 4 Results 4.1 Outcomes and transformations due to the MTAs 4.2 Unpacking the functioning and dynamics of the MTAs network 4.3 Characteristics of the MTAs in relation to their effectiveness, sustainability, and scalability 5 Discussion 5.1 Factors likely conducive to MTAs success 5.2 (Re)defining success for climate services in agriculture 6 Conclusion CRediT authorship contribution statement Declaration of competing interest Acknowledgments Appendix A Supplementary data Data availability References