Farming approaches for greater biodiversity, livelihoods, and food security
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Scientists and policy-makers globally are calling for alternative approaches to conventional intensification of agriculture that enhance ecosystem services provided by biodiversity. The evidence reviewed here suggests that alternative approaches can achieve high crop yields and profits, but the performance of other socioeconomic indicators (as well as long-term trends) is surprisingly poorly documented. Consequently, the implementation of conventional intensification and the discussion of alternative approaches are not based on quantitative evidence of their simultaneous ecological and socioeconomic impacts across the globe. To close this knowledge gap, we propose a participatory assessment framework. Given the impacts of conventional intensification on biodiversity loss and greenhouse gas emissions, such evidence is urgently needed to direct science-policy initiatives, such as the United Nations (UN) 2030 Agenda for Sustainable Development.
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Too often organic practices or environmental sustainability in agricultural production are prioritized at the cost of human and social aspects of food systems, resulting in barriers for disadvantaged consumers who cannot access, afford, nor identify with food from alternative agri-food systems.
“Too often organic practices or environmental sustainability in an agricultural production system are prioritized at the cost of the human and social aspects of food systems [4], resulting in barriers for disadvantaged consumers who cannot access, afford, nor identify with food from these alternative agri-food systems [4,5].”
From Agroecological Transition: A Territorial Examination of the Simultaneity of Limited Farmer Livelihoods and Food Insecurity (2022) · cites this paper as [4]
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- Authors
- Garibaldi, L. A., Gemmill-Herren, B., D’Annolfo, R., Graeub, B. E., Cunningham, S. A., & Breeze, T. D.
- Affiliations
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Biovision – Foundation for Ecological Development (CH)
- Australian National University (AU)
- University of Reading (GB)
- Corresponding author
- Garibaldi, Lucas A.
- Venue
- Trends in Ecology & Evolution
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 32
- Issue
- 1
- Pages
- 68-80
- ISSN
- 0169-5347 (ISSN-L)
- OpenAlex
- W2533630581
- Cited by
- 380
- References
- 90
- Citations by year
- 2026: 28 · 2025: 36 · 2024: 34 · 2023: 41 · 2022: 55 · 2021: 42 · 2020: 48 · 2019: 48 · 2018: 28 · 2017: 19
- FWCI
- 2.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Trends in Ecology & Evolution (publishedVersion)
- PubMed (publishedVersion)
- ANU Open Research (Australian National University) (submittedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-sa)
- CONICET Digital (CONICET) (submittedVersion, cc-by-nc-sa)
- Funders
- Universidad Nacional de Río Negro (40-B-399, PI 40-B-399)
- Topics
- Physical Sciences › Environmental Science › Environmental Chemistry › Sustainable Agricultural Systems Analysis
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Plant and soil sciences
- Keywords
- agricultural intensification, biodiversity conservation, food security, livelihoods, ecosystem services, socio-economic impacts, greenhouse gas emissions, biodiversity loss, sustainable development, crop yield, science-policy interface
- MeSH terms
- Agriculture, Conservation of Natural Resources, Food Supply, Ecosystem, Biodiversity
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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