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Managing agricultural landscapes to support biodiversity conservation requires profound structural changes worldwide. Often, discussions are centered on management at the field level. However, a wide and growing body of evidence calls for zooming out and targeting agricultural policies, research, and interventions at the landscape level to halt and reverse the decline in biodiversity, increase biodiversity-mediated ecosystem services in agricultural landscapes, and improve the resilience and adaptability of these ecosystems. We conducted the most comprehensive assessment to date on landscape complexity effects on nondomesticated terrestrial biodiversity through a meta-analysis of 1,134 effect sizes from 157 peer-reviewed articles. Increasing landscape complexity through changes in composition, configuration, or heterogeneity significatively and positively affects biodiversity. More complex landscapes host more biodiversity (richness, abundance, and evenness) with potential benefits to sustainable agricultural production and conservation, and effects are likely underestimated. The few articles that assessed the combined contribution of linear (e.g., hedgerows) and areal (e.g., woodlots) elements resulted in a near-doubling of the effect sizes (i.e., biodiversity level) compared to the dominant number of studies measuring these elements separately. Similarly, positive effects on biodiversity are stronger in articles monitoring biodiversity for at least 2 y compared to the dominant 1-y monitoring efforts. Besides, positive and stronger effects exist when monitoring occurs in nonoverlapping landscapes, highlighting the need for long-term and robustly designed monitoring efforts. Living in harmony with nature will require shifting paradigms toward valuing and promoting multifunctional agriculture at the farm and landscape levels with a research agenda that untangles complex agricultural landscapes’ contributions to people and nature under current and future conditions.

With the Convention on Biological Diversity conference (COP15), United Nations Climate Change Conference (COP26), and United Nations Food Systems Summit, 2021 is a pivotal year for transitioning towards sustainable food systems. Diversified farming systems are key to more sustainable food production. Here we present a global dataset documenting outcomes of diversified farming practices for biodiversity and yields compiled following best standards for systematic review of primary studies and specifically designed for use in meta-analysis. The dataset includes 4076 comparisons of biodiversity outcomes and 1214 of yield in diversified farming systems compared to one of two reference systems. It contains evidence from 48 countries of effects on species from 33 taxonomic orders (spanning insects, plants, birds, mammals, eukaryotes, annelids, fungi, and bacteria) of diversified farming systems producing annual or perennial crops across 12 commodity groups. The dataset presented provides a resource for researchers and practitioners to easily access information on where diversified farming systems effectively contribute to biodiversity and food production outcomes. Measurement(s) yield trait • biodiversity outcomes Technology Type(s) Meta-Analysis Factor Type(s) Crop type • non-domesticated taxa Sample Characteristic - Organism Mammalia • Arthropoda • Aves • Amphibian • Annelida • Eukaryota • Nematoda • Plant • Reptile Sample Characteristic - Environment agricultural field • natural environment Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14723913

Dietary transition towards higher consumption of animal source foods (ASF) associated with higher incomes across low and middle-income countries could have negative impacts on environmental systems and their potential in the long run to provide services necessary for achieving multiple Sustainable Development Goals (SDGs). In this article, we integrate economic, land use allocation, and biophysical models to investigate trade-offs between the five ecosystem services and their contributions to various SDGs associated with agricultural expansion to meet future demand for ASF, using Tanzania as a case study. Our results show that under the scenario of sustainable socio-economic development, between 2010 and 2030 in Tanzania, per capita income grows by 169% and the share of population at risk of hunger declines from 34.8% to 23%. These changes can be associated on a macro-level with positive contributions to achievement of SDG 1 (No Poverty) and SDG 2 (Zero Hunger). To satisfy feed demand for increased livestock production domestically, an increase by 21.4% of biomass production as compared to 2010 is needed. Analysis of alternative scenarios for meeting this new demand shows potential threats on a landscape level to achieving numerous SDGs and more generally to attaining sustainable food systems. Ecosystem-based contributions primarily decline to SDGs: SDG 3 (Health), SDG 6 (Clean Water), SDG 11 (Sustainable Cities), SDG 13 (Climate) and SDG 15 (Terrestrial Life). We find that higher crop productivity and redesign of agro-ecosystems to increase on-farm tree cover could significantly limit these losses. Alternatively, the growing demand for ASF could be satisfied with imports, which would allow for reducing the trade-offs locally. However, this would result in at least partially only displacing ecosystem service losses to the exporting countries.

Humanity is challenged with making progress toward global biodiversity, freshwater, and climate goals, while providing food and nutritional security for everyone. Our current food and land-use systems are incompatible with this ambition making them unsustainable. Papers in this special feature introduce a participatory, integrated modeling approach applied to provide insights on how to transform food and land-use systems to sustainable trajectories in 12 countries: Argentina, Australia, Canada, China, Germany, Finland, India, Mexico, Rwanda, Sweden, the UK, and USA. Papers are based on work completed by members of the Food, Agriculture, Biodiversity, Land-use, and Energy (FABLE) initiative, a network of in-country research teams engaging policymakers and other local stakeholders to co-develop future food and land-use scenarios and modeling their national and global sustainability impacts. Here, we discuss the key leverage points, methodological advances, and multi-sector engagement strategies presented and applied in this collection of work to set countries and our planet on course for achieving food security, biodiversity, freshwater, and climate targets by 2050.

Governments are updating national strategies to meet global goals on biodiversity, climate change and food systems proposed in the Convention on Biological Diversity post-2020 framework and agreed at the United Nation’s Climate Change Conference (COP26) and Food Systems Summit (UNFSS). This represents a unique and crucial opportunity to integrate and accelerate food system actions to tackle interconnected global challenges. In this context, agroecology is a game-changing approach that can provide the world’s growing population with nutritious, healthy affordable food, ensure fair incomes to farmers and halt and reverse the degradation of the natural environment. Here, we explore agroecological transition pathways in four case studies from low- and middle- income countries and identify catalysts for change. We find that enabling policy and market environments, participatory action research and local socio-technical support each plays a critical role in stimulating transitions towards agroecology. We propose strategies and priorities for research to better support agroecological transitions using these catalysts of change as entry points. Engagement of governments, private sector, civil society, farmers and farm workers in this research agenda is essential.

Whether or not reservoirs contain water throughout the dry season is critical to avoiding late season crop failure in seasonally-arid agricultural landscapes. Locations, volumes, and temporal dynamics, particularly of small (<1 Mm3) reservoirs are poorly documented globally, thus making it difficult to identify geographic and intra-annual gaps in reservoir water availability. Yet, small reservoirs are the most vulnerable to drying out and often service the poorest of farmers. Using the transboundary Volta River Basin (~413,000 sq km) in West Africa as a case study, we present a novel method to map reservoirs and quantify the uncertainty of Landsat derived reservoir area estimates, which can be readily applied anywhere in the globe. We applied our method to compare the accuracy of reservoir areas that are derived from the Global Surface Water Monthly Water History (GSW) dataset to those that are derived when surface water is classified on Landsat 8 OLI imagery using the Normalised Difference Water Index (NDWI), Modified NDWI with band 6 (MNDWI1), and Modified NDWI with band 7 (MNDWI2). We quantified how the areal accuracies of reservoir size estimates vary with the water classification method, reservoir properties, and environmental context, and assessed the options and limitations of using uncertain reservoir area estimates to monitor reservoir dynamics in an agricultural context. Results show that reservoir area estimates that are derived from the GSW data are 19% less accurate for our study site than MNDWI1 derived estimates, for a sample of 272 reservoir extents of 0.09 to 72 ha. The accuracy of Landsat-derived estimates improves with reservoir size and perimeter-area ratio, while accuracy may decline as surface vegetation increases. We show that GSW derived reservoir area estimates can provide an upper limit for current reservoir capacity and seasonal dynamics of larger reservoirs. Data gaps and uncertainties make GSW derived reservoir extents unsuitable for monitoring reservoirs that are smaller than 5.1 ha (holding ~49,759 m3), which constitute 674 (56%) reservoirs in the Volta basin, or monitoring seasonal fluctuations of most small reservoirs, limiting its utility for agricultural planning. This study is one of the first to test the utility and limitations of the newly available GSW dataset and provides guidance on the conditions under which this, and other Landsat-based surface water maps, can be reliably used to monitor reservoir resources.

Standard tools that can quantitatively track the impacts of higher global demand for animal-sourced food to their local environmental effects in developing countries are largely missing. This paper presents a novel integrated assessment framework that links a model of the global agricultural and food system, a landscape-level environmental impact assessment model, and an ecosystem services simulation model. For Tanzania, this integrated assessment showed that a projected increase in the demand and production of foods of livestock origin with optimistic economic growth between 2010 and 2030 leads to an improvement in food security. However, resulting transitions in land use impact negatively on the future provisioning of ecosystem services, increasing phosphorus, nitrogen, and sediment in runoff and reducing water quality in areas downstream of the agricultural expansion. Losses in ecosystem services are lowest when diversified farming practices are adopted in areas of agricultural land expansion. The role of land management in the environmental impacts of expanded livestock production is highlighted, as is the need for a new generation of analytical tools to inform policy recommendations.

Diversified farming systems are increasingly recognised for their potential to enhance the sustainability and resilience of food systems. Yet it remains unclear whether empirical research adequately captures the drivers and constraints shaping farmers' decisions regarding diversified farming systems across stages of decision‐making, influencing factors, practices and contexts. We present a systematic evidence map of 354 regression models from 193 peer‐reviewed studies (1982–2023) examining how multiple factors relate to five decision‐making stages (awareness, interest, adoption, intensity of adoption and dis‐adoption) across 10 diversified farming practices in 45 countries. Factors were classified into 14 categories spanning biophysical, socio‐economic, psychological, institutional and contextual dimensions. To identify geographic gaps, we compared the spatial distribution of decision‐making research with country and subregional suitability for profitable diversified farming systems. The literature overwhelmingly focuses on the adoption stage (82% of studies), with limited evidence on factors influencing farmers' awareness of, interest in or dis‐adoption of diversified practices. Coverage is uneven across practices, factors and regions. Agroforestry dominates the literature (39% of studies), while crop–animal integrated practices are rarely assessed. Models most often include human (95%), natural (77%) and financial capital (71%), with limited representation of political and institutional conditions and psychological factors (e.g. perceptions and social norms). Among the 70 countries with very high suitability for profitable diversification, only 17 (24%) are represented, with particularly limited evidence in Europe, Latin America and the Caribbean. While the literature provides robust evidence on factors influencing adoption, gaps across other decision‐making stages, institutional and psychological dimensions, complex practices and high‐suitability regions constrain its relevance for policy and investment. More holistic, theory‐informed research capturing decision‐making across stages and contexts is needed to support the implementation and long‐term viability of diversified farming systems. Read the free Plain Language Summary for this article on the Journal blog. Resumen Los sistemas agrícolas diversificados son cada vez más reconocidos por su potencial para mejorar la sostenibilidad y resiliencia de los sistemas alimentarios. Sin embargo, no está claro si la investigación empírica captura adecuadamente los factores que impulsan o limitan las decisiones de los agricultores a lo largo de las distintas etapas del proceso de toma de decisiones, ni cómo estos varían entre prácticas y contextos. Este estudio ofrece un mapa sistemático de evidencias basado en 354 modelos de regresión procedentes de 193 artículos revisados por pares (1982–2023), que analizaron cómo múltiples factores se relacionan con cinco etapas del proceso de toma de decisiones (conocimiento, interés, adopción, intensidad de adopción y abandono) en diez prácticas agrícolas diversificadas en 45 países. Los factores se clasificaron en 14 categorías que abarcan dimensiones biofísicas, socioeconómicas, psicológicas, institucionales y contextuales. Para identificar regiones relevantes, pero con escasa evidencia, comparamos la distribución geográfica de los artículos con el potencial de los países y subregiones para la implementación de sistemas agrícolas diversificados rentables. La evidencia se centra principalmente en la etapa de adopción (82% de los estudios), con información limitada sobre los factores que influyen en el conocimiento, el interés o el abandono de estas prácticas por parte de los agricultores. Asimismo, la evidencia disponible es desigual entre prácticas, tipos de factores y regiones. La agroforestería concentra la mayor parte de la evidencia (39% de los estudios), mientras que las prácticas que integran cultivo–ganadería son escasamente estudiadas. Los modelos incluyen con mayor frecuencia factore relacionados al capital humano (95%), natural (77%) y financiero (71%), con una representación limitada de las condiciones políticas e institucionales y de los factores psicológicos (por ejemplo, percepciones y normas sociales). De los 70 países con muy alto potencial para la diversificación agrícola rentable, solo 17 (24%) están representados, con un numero de estudios particularmente bajo en Europa, América Latina y el Caribe. Aunque la evidencia disponible es sólida en relación con los factores que influyen en la adopción, sigue siendo limitada para otras etapas del proceso de toma de decisiones. También es escasa en relación con factores institucionales y psicológicos, así como en prácticas complejas y en regiones con alto potencial de rentabilidad. Estas limitaciones reducen su relevancia para orientar políticas públicas y decisiones de inversión dirigidas a la transición hacia una agricultura más sostenible. Por ello, se requiere investigación más integral y basada en marcos teóricos que capture la toma de decisiones a lo largo de las distintas etapas y contextos, con el fin de apoyar la implementación y la viabilidad a largo plazo de los sistemas agrícolas diversificados. Résumé Les systèmes agricoles diversifiés sont de plus en plus reconnus pour leur potentiel à renforcer la durabilité et la résilience des systèmes alimentaires. Il n’est toutefois pas certain que la recherche empirique rende suffisamment compte des facteurs déterminants et des contraintes qui façonnent les décisions des agriculteurs concernant ces systèmes, incluant les différentes étapes de la prise de décision, les facteurs d’influence, les pratiques et les contextes. Nous présentons une cartographie systématique des données issues de 354 modèles de régression provenant de 193 études évaluées par des pairs (1982‐2023) qui examinent comment de multiples facteurs sont liés à cinq étapes de la prise de décision (sensibilisation, intérêt, adoption, intensité de l'adoption et désengagement) pour dix pratiques d’agriculture diversifiée dans 45 pays. Les facteurs ont été classés en 14 catégories couvrant les dimensions biophysique, socio‐économique, psychologique, institutionnelle et contextuelle. Afin d’identifier les lacunes géographiques, nous avons comparé la répartition spatiale des recherches sur la prise de décision avec l’aptitude des pays et des sous‐régions vis‐à‐vis de la rentabilité potentielle des systèmes agricoles diversifiés. La littérature se concentre très majoritairement sur la phase d’adoption (82 % des études), les données sur les facteurs influençant la sensibilisation des agriculteurs, leur intérêt ou leur désengagement vis‐à‐vis des pratiques diversifiées étant limitées. La couverture est inégale selon les pratiques, les facteurs et les régions. L’agroforesterie domine la littérature (39 % des études), tandis que les pratiques intégrées cultures‐élevage sont rarement évaluées. Les modèles incluent le plus souvent le capital humain (95 %), naturel (77 %) et financier (71 %), avec une représentation limitée des conditions politiques et institutionnelles et des facteurs psychologiques (par exemple, les perceptions et les normes sociales). Parmi les 70 pays présentant une très forte aptitude à une diversification rentable, seuls 17 (24 %) sont représentés, avec des données particulièrement limitées en Europe, en Amérique latine et dans les Caraïbes. La littérature fournit des données solides sur les facteurs influençant l'adoption ; cependant, des lacunes persistent concernant les autres étapes de la prise de décision, les dimensions institutionnelles et psychologiques, les pratiques complexes et les régions à forte aptitude ; ces lacunes limitent la pertinence de la connaissance pour les politiques et les investissements. Des recherches plus holistiques, fondées sur la théorie et rendant compte de la prise de décision à travers les différentes étapes et contextes, sont nécessaires pour soutenir la mise en œuvre et la viabilité à long terme des systèmes agricoles diversifiés. Read the free Plain Language Summary for this article on the Journal blog.

Improving livelihoods in Rwanda requires overcoming food insecurity and malnutrition. Vision 2050 is Rwanda’s long-term development strategy, yet little is known about its potential trade-offs for the country’s biodiversity, forest cover, and greenhouse gas (GHG) emissions. Scenario analysis can provide insights into how to achieve such goals more sustainably. Here, we use the Food, Agriculture, Biodiversity, Land-Use, and Energy (FABLE) Calculator, a simple integrated assessment tool, to explore potential sustainability implications by 2050 through two scenarios: (1) Current Trends and (2) Vision 2050. The Vision 2050 pathway incorporates components of the government’s long-term development strategy and associated national agricultural policy targets. It includes greater increases in crop productivity and decreases in post-harvest losses, and shifts to more sustainable diets, compared to the Current Trends pathway. Results show that the Vision 2050 pathway would, relative to Current Trends, lead to a greater decrease in agricultural land area and an increase in non-forested natural land-cover area, with consequent decreases in GHG emissions from agriculture, increases in carbon sequestration, and increases in the share of land that can support biodiversity conservation. Shifts to a healthier diet in the Vision 2050 pathway would only be compatible with national agricultural priorities if these diets favor consumption of foods that underpin sustainable livelihoods in Rwanda, such as beans, cassava, potatoes, sweet potatoes, banana, and corn. We discuss the potential for integrated land-use planning and adoption of agroecological farming practices to help Rwanda achieve food security, livelihood, biodiversity, and climate mitigation goals in tandem.

Sustainable land management is at the heart of some of the most intractable challenges facing humanity in the 21st century. It is critical for tackling biodiversity loss, land degradation, climate change and the decline of ecosystem services. It underpins food production, livelihoods, dietary health, social equity, climate change adaptation, and many other outcomes. However, interdependencies, trade-offs, time lags, and non-linear responses make it difficult to predict the combined effects of land management decisions. Policy decisions also have to be made in the context of conflicting interests, values and power dynamics of those living on the land and those affected by the consequences of land use decisions. This makes designing and coordinating effective land management policies and programmes highly challenging. The difficulty is exacerbated by the scarcity of reliable data on the impacts of land management on the environment and livelihoods. This poses a challenge for policymakers and practitioners in governments, development banks, non-governmental organisations, and other institutions. It also sets demands for researchers, who are under ever increasing pressure from funders to demonstrate uptake and impact of their work. Relatively few research methods exist that can address such questions in a holistic way. Decision makers and researchers need to work together to help untangle, contextualise and interpret fragmented evidence through systems approaches to make decisions in spite of uncertainty. Individuals and institutions acting as knowledge brokers can support these interactions by facilitating the co-creation and use of scientific and other knowledge. Given the patchy nature of data and evidence, particularly in developing countries, it is important to draw on the full range of available models, tools and evidence. In this paper we review the use of evidence to inform multiple-objective integrated landscape management policies and programmes, focusing on how to simultaneously achieve different sustainable development objectives in diverse landscapes. We set out key success factors for evidence-based decision-making, which are summarised into 10 key principles for integrated landscape management knowledge brokering in integrated landscape management and 12 key skills for knowledge brokers. We finally propose a decision-support framework to organise evidence that can be used to tackle different types of land management policy decision.