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In 2000, CATIE began a long-term coffee agroforestry trial aimmg to research complex interactions among climate, soil, shade trees, managements, and coffee varieties, useful for the development of systems that enhance soil ecological restoration, biodiversity, and ecosystem services. The trial consists of combinations of shade and managements: six types of shade from associations of legume and timber trees, and full-sun systems, combined with four managements (high conventional (AC), moderate conventional (MC), intensive organic (MO) and low organic (BO)), resulting in >20 types of systems, in which traditional and improved coffee varieties are also being tested. More than 30 research centers and universities have been involved to produce >30 scientific papers, >40 theses, and >20 technical documents. The revision of the main fmdings indicates that full sun systems (AC, MC) produce high yields but with a trade-off on ecosystem services provision; while agroforestry systems with legume trees, especially MO and MC, reached both good productivity and provisioning ecosystem services (improving soil quality, carbon sequestration, regulation of pests ). Systems with only timber trees and BO collapsed. The economic analysis shows that most agroforestry systems are profitable, including those with MO or BO, with important lessons to reduce production costs. The most successful innovations related to soil improvements, shade and pest regulation, silvicultural mechanization, and carbon storage derived from the trial, were used as inputs to environment-focus policies, design of researchdevelopment projects and programs such as NAMA coffee. The results have been disseminated to more than 40,000 producers and hundreds of students through projects and relevant platforms such as PCP-AGROFORESTA, PROMECAFE, RECIPROCAFE, the Alianza de Mujeres en Café, PROCAGICA-IICA-UE, and coffee courses/diplomas. Thus, it is being demonstrated that diversification and good practices can contribut

Shade trees in agroforestry systems confer ecosystem services, such as enhanced soil fertility from diverse litter inputs, microclimate regulation via shade, and disease mitigation through trophic and abiotic interactions. With this thriving role of agroforestry in sustainable agriculture, particularly for tree crops, systematic and reliable methods to select shade trees for specific agroecosystem outcomes are crucial. Plant functional traits offer a framework to describe, select and manage shade trees. Over the last decade, shade tree leaf functional traits and whole plant traits have been assessed in agroforestry systems. Yet, we lack amalgamated information on (i) what we know about shade tree trait relationships with functions to achieve desired agroecosystem outcomes, (ii) how decades of shade tree selection by farmers impacts agroforests inter- and intraspecific trait diversity, and (iii) which shade tree traits should be considered for achieving farmer priorities. We consolidate literature on Coffea arabica (coffee) and Theobroma cacao (cocoa) agroforestry systems to summarize the role of shade tree functional traits in three key ecosystem functions: soil fertility, microclimate modification and crop productivity. We compile global and regional datasets on tree functional trait diversity to show the functional space of agroforestry tree species compared with the overall functional space observed in plants. Despite, or maybe because of, high shade tree diversity, shade tree trait characterization remains coarse and commonly measured at the community scale in the literature. Based on published trait data, we show that farmers adjust the functional composition of shade trees to increase the recycling of soil nutrients (high leaf nitrogen), the production of wood (skewing towards lower wood densities) and the production of fruits (tendency towards high seed size). Common shade trees in coffee and cocoa systems fall in the mid-range of leaf acquisitive to conserva

Agricultural simplification continues to expand at the expense of more diverse forms of agriculture. This simplification, for example, in the form of intensively managed monocultures, poses a risk to keeping the world within safe and just Earth system boundaries. Here, we estimated how agricultural diversification simultaneously affects social and environmental outcomes. Drawing from 24 studies in 11 countries across 2655 farms, we show how five diversification strategies focusing on livestock, crops, soils, noncrop plantings, and water conservation benefit social (e.g., human well-being, yields, and food security) and environmental (e.g., biodiversity, ecosystem services, and reduced environmental externalities) outcomes. We found that applying multiple diversification strategies creates more positive outcomes than individual management strategies alone. To realize these benefits, well-designed policies are needed to incentivize the adoption of multiple diversification strategies in unison.

Farming systems that support locally diverse agricultural production and high levels of biodiversity are in rapid decline, despite evidence of their benefits for climate, environmental health, and food security. Yet, agricultural policies, financial incentives, and market concentration increasingly constrain the viability of diversified farming systems. Here, we present a conceptual framework to identify novel processes that promote the emergence and sustainability of diversified farming systems, using three real-world examples where farming communities have found pathways to diversification despite major structural constraints. By applying our framework to analyze these bright spots in the United States, Brazil, and Malawi, we identify two distinct pathways—network and institutional—to diversification. These pathways emerge through alignment of factors related to social and ecological structure (policies, institutions, and environmental conditions) and agency (values, collective action, and management decisions). We find that, when network and institutional pathways operate in tandem, the potential to scale up diversification across farms and landscapes increases substantially.

Research has demonstrated that intraspecific functional trait variation underpins plant responses to environmental variability. However, few studies have evaluated how trait variation shifts in response to plant pathogens, even though pathogens are a major driver of plant demography and diversity, and despite evidence of plants expressing distinct strategies in response to pathogen pressures. Understanding trait-pathogen relationships can provide a more realistic understanding of global patterns of functional trait variation. We examined leaf intraspecific trait variability (ITV) in response to foliar disease severity, using Coffea arabica cv. Caturra as a model species. We quantified coffee leaf rust (CLR) severity—a fungal disease prominent in coffee systems—and measured key coffee leaf functional traits under contrasting, but widespread, management conditions in an agroforestry system. We found that coffee plants express significant ITV, which is largely related to shade tree treatment and leaf position within coffee canopy strata. Yet within a single plant canopy stratum, CLR severity increased with increasing resource conserving trait values. However, coffee leaves with visible signs of disease expressed overall greater resource acquiring trait values, as compared to plants without visible signs of disease. We provide among the first evidence that leaf traits are correlated with foliar disease severity in coffee, and that functional trait relationships and syndromes shift in response to increased disease prevalence in this plant-pathogen system. In doing so, we address a vital gap in our understanding of global patterns of functional trait variation and highlight the need to further explore the potential role of pathogens within established global trait relationships and spectra.

While integrating trees into agricultural systems (i.e., agroforestry systems) provides many valuable ecosystem services, they can also interact with plant diseases. We demonstrate that a detailed understanding of how plant diseases interact with trees in agroforestry systems is necessary to identify key tree canopy characteristics, leaf traits, spatial arrangements, and management options that can help control plant diseases at different spatial scales. We focus our analysis on how trees affect coffee leaf rust, a major disease impacting one of the world's most significant crop commodities. We show that trees can both promote and discourage the development of coffee leaf rust at the plot scale via microclimate modifications in the understory. Based on our understanding of the role of tree characteristics in shaping the microclimate, we identify several canopy characteristics and leaf traits that can help manage coffee leaf rust at the plot scale: namely, thin canopies with high openness, short base height, horizontal branching, and small, dentate leaves. In contrast, at the edge of coffee farms, having large trees with high canopy volume and small, thick, waxy leaves is more useful to reduce throughflow wind speeds and intercept the airborne dispersal of urediniospores, an important consideration to control disease at the landscape scale. Seasonal pruning can help shape trees into the desired form, and trees can be spatially arranged to optimize desired effects. This case study demonstrates the added value of combining process-based epidemiology studies with functional trait ecology to improve disease management in agroforestry systems.

Selecting crops that express certain reproductive, leaf, and root traits has led to diverse crop domestication syndromes. However, scientific and informal on-farm research has primarily focused on understanding and managing linkages between only certain traits and yield. There is strong evidence suggesting that leaf functional traits—i.e., the morphological (e.g., specific leaf area [SLA]), physiological (e.g., photosynthesis), and chemical (e.g., leaf nitrogen (N) concentrations) traits of plants—have also been influenced by domestication, and reflect trade-offs and constraints among aspects of crop biology and agroecosystem environmental conditions. Yet, our understanding of how agroforestry systems influence trait expression and relationships remains limited. We measured nine morphological (thickness, area, SLA), physiological (maximum photosynthetic rates, stomatal conductance, and water-use efficiency [WUE]) and chemical traits (leaf carbon (C) and N concentrations, C:N ratios), on six cultivars grown in two clonal gardens with distinct environmental characteristics (i.e., a “Mild dry season” with near-optimal cacao growing conditions, and a “Harsh dry season” site with sub-optimal conditions). Genotype x Environment interactions were detectable in leaf functional trait expression, though these interactions varied strongly with the group of traits being evaluated; morphological traits varied widely among clones but these differences were robust across sites, while physiological and chemical traits significantly differed between clones, though inter-clonal differences varied depending on sites. Specifically, SLA increased with the clone productivity potential at both sites, while the least productive clones exhibited higher trait variation with a given site. Our results suggest that evaluating functional trait variation informs our understanding of Genotype x Environment interactions in crops widely cultivated in agroforestry systems. These results also suggest

Plant resource acquisition strategies reflect a plant's ability to forage and exploit available resources. Belowground, these strategies are coordinated between plant roots and their actively cultivated microbial communities, which is reflected in root functional trait expression that varies along a conservation gradient (from resource acquisition to conservation), and a collaboration gradient (from outsourcing to do-it-yourself strategies). We know that the heterogeneous soil environment largely shapes the expression of root traits and their paired microbial associations, but we have not yet fully explored how the manipulation of the soil environment via specific management practices, including soil amendment regimes, control this plant functioning belowground in biodiverse agroforestry systems. The main objective of this study is to determine how soil amendments shape belowground resource acquisition and microbial collaboration strategies in coffee agroforestry systems. We measured key coffee root functional traits and characterized root endophytic fungal populations under contrasting but widespread soil amendment regimes (inorganic, organic, and organic with additional local soil microbial inoculant). We found that amendment regimes dictate variability in belowground resource strategies. More specifically, coffee plants under inorganic management expressed greater conserving root traits, contrasting plants under organic management with additional local soil microbial inoculant that expressed greater acquisitive roots traits and enhanced collaboration with symbiotic fungi. Interestingly, the local soil microbial inoculant applied to the soil contained relatively minimal symbiotic fungi, but rather mostly moulds and yeasts. Our results highlight that soil amendments differentially control root trait expression and microbial collaborations, providing further insight into the role of sustainable agroforestry management decisions in shaping plant resource acquisition