Nature+ Quantitative Monitoring Household Survey, Colombia

cg.authorship.typesCGIAR single centre
cg.contributor.affiliationInternational Food Policy Research Institute
cg.contributor.donorCGIAR Trust Fund
cg.contributor.initiativeNature-Positive Solutions
cg.coverage.countryColombia
cg.coverage.regionAmericas
cg.coverage.regionSouth America
cg.coverage.regionLatin America and the Caribbean
cg.howPublishedGrey Literature
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/QFQURF
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/PZVGOH
cg.identifier.doihttps://doi.org/10.7910/dvn/xkbydg
cg.identifier.projectIFPRI - Innovation Policy and Scaling Unit
cg.identifier.publicationRankNot ranked
cg.placeWashington, DC
cg.reviewStatusInternal Review
cg.subject.actionAreaSystems Transformation
cg.subject.impactAreaEnvironmental health and biodiversity
cg.subject.impactAreaGender equality, youth and social inclusion
cg.subject.sdgSDG 5 - Gender equality
cg.subject.sdgSDG 13 - Climate action
cg.subject.sdgSDG 12 - Responsible consumption and production
dc.contributor.authorInternational Food Policy Research Institute
dc.date.accessioned2025-06-27T19:21:36Z
dc.date.available2025-06-27T19:21:36Z
dc.identifier.urihttps://hdl.handle.net/10568/175361
dc.titleNature+ Quantitative Monitoring Household Survey, Colombiaen
dcterms.abstractThe NATURE+ survey conducted in Colombia integrated household and community-level questionnaires to develop a comprehensive understanding of the socio-economic, agricultural, and environmental dynamics influencing potential beneficiaries of NATURE+ interventions. The study focused on two key departments: Nariño and Putumayo. At the household level, the survey collected detailed socio-economic and demographic data, including household composition, education levels, land ownership, income sources, self-employment activities, and asset ownership. This information provides crucial insights into the economic conditions of the surveyed population. The survey also documented agricultural practices on farms and in chagras—traditional agroforestry systems maintained by Indigenous communities. Specific attention was given to crop and livestock production, crop biodiversity, and the use of fertilizers and pesticides. The survey further investigated the adoption of nature-positive solutions, including agroforestry practices, environmental management (such as waste handling and renewable energy use), and awareness of biodiversity benefits. Issues related to food security and dietary diversity were also addressed. At the community level, the questionnaire aimed to capture broader socio-economic, environmental, and institutional factors across selected communities in Cumbal (Nariño) and multiple municipalities in Putumayo. It gathered demographic estimates—such as population size, gender and age composition, and number of households—to construct a socio-economic profile of each community. The survey assessed the prevalence and benefits of nature-positive practices, such as biodiversity conservation, agroforestry, and sustainable land management. It also evaluated the role of external actors, including NGOs and extension agencies, in promoting these practices. Additional components covered community infrastructure, natural resource governance, and ongoing sustainability initiatives.en
dcterms.accessRightsOpen Access
dcterms.audienceAcademics
dcterms.audienceGeneral Public
dcterms.audiencePolicy Makers
dcterms.bibliographicCitationInternational Food Policy Research Institute (IFPRI). 2025. Nature+ Quantitative Monitoring Household Survey, Colombia. Washington, DC: IFPRI [dataset]. https://doi.org/10.7910/DVN/XKBYDG. Harvard Dataverse. Version 1.
dcterms.isPartOfHousehold- and Community-level Surveys
dcterms.issued2025-06-18
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherInternational Food Policy Research Institute
dcterms.relationhttps://hdl.handle.net/10568/172753
dcterms.subjectagrifood systems
dcterms.subjectsustainable agriculture
dcterms.subjectnatural resources management
dcterms.subjectland degradation
dcterms.subjectfood security
dcterms.typeDataset

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