Joint environmental and social benefits from diversified agriculture.

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.

Changes in crop trait plasticity with domestication history: Management practices matter.

Crop domestication has led to the development of distinct trait syndromes, a series of constrained plant trait trade-offs to maximize yield in high-input agricultural environments, and potentially constrained trait plasticity. Yet, with the ongoing transition to organic and diversified agroecosystems, which create more heterogeneous nutrient availability, this constrained plasticity, especially in root functional traits, may be undesirable for nutrient acquisition. Such agricultural systems require a nuanced understanding of the soil-crop continuum under organic amendments and with intercropping, and the role crop genetic resources play in governing nutrient management and design. In this study, we use a functional traits lens to determine if crops with a range of domestication histories express different functional trait plasticity and how this expression changes with soil amendments and intercropping. We utilize a common garden experiment including five wheat (Triticum aestivum) varietals with a range of domestication histories planted in a factorial combination with amendment type (organic and inorganic) and cropping design (monoculture or intercropped with soybean). We use bivariate, multivariate and trait space analyses to quantify trait variation and plasticity in five leaf and five root functional traits. Almost all leaf and root traits varied among varieties. Yet, amendment type was nearly inconsequential for explaining trait expression across varieties. However, intercropping was linked to significant differences in root acquisitive strategies, regardless of the varietals' distinct history. Our findings show substantial leaf and root trait plasticity, with roots expressing greater trait space occupation with domestication, but also the strong role of management in crop trait expression. We underscore the utility of a functional trait-based approach to understand plant-soil dynamics with organic amendments, as well as the role of crop genetic histories in the successful transition to low-input and diversified agroecosystems.

Plant trait relationships are maintained within a major crop species: lack of artificial selection signal and potential for improved agronomic performance.

The exploration of phenotypic spaces of large sets of plant species has considerably increased our understanding of diversification processes in the plant kingdom. Nevertheless, such advances have predominantly relied on interspecific comparisons that hold several limitations. Here, we grew in the field a unique set of 179 inbred lines of durum wheat, Triticum turgidum spp. durum, characterized by variable degrees of artificial selection. We measured aboveground and belowground traits as well as agronomic traits to explore the functional and agronomic trait spaces and to investigate trait-to-agronomic performance relationships. We showed that the wheat functional trait space shared commonalities with global cross-species spaces previously described, with two main axes of variation: a root foraging axis and a slow-fast trade-off axis. Moreover, we detected a clear signature of artificial selection on the variation of agronomic traits, unlike functional traits. Interestingly, we identified alternative phenotypic combinations that can optimize crop performance. Our work brings insightful knowledge about the structure of phenotypic spaces of domesticated plants and the maintenance of phenotypic trade-offs in response to artificial selection, with implications for trade-off-free and multi-criteria selection in plant breeding.

Leaf functional traits and pathogens: Linking coffee leaf rust with intraspecific trait variation in diversified agroecosystems.

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.

Tree Effects on Coffee Leaf Rust at Field and Landscape Scales.

Although integrating trees into agricultural systems (i.e., agroforestry systems) provides many valuable ecosystem services, the trees 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 affecting 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.

A trait-environment relationship approach to participatory plant breeding for organic agriculture.

The extent of intraspecific variation in trait-environment relationships is an open question with limited empirical support in crops. In organic agriculture, with high environmental heterogeneity, this knowledge could guide breeding programs to optimize crop attributes. We propose a three-dimensional framework involving crop performance, crop traits, and environmental axes to uncover the multidimensionality of trait-environment relationships within a crop. We modeled instantaneous photosynthesis (Asat ) and water-use efficiency (WUE) as functions of four phenotypic traits, three soil variables, five carrot (Daucus carota) varieties, and their interactions in a national participatory plant breeding program involving a suite of farms across Canada. We used these interactions to describe the resulting 12 trait-environment relationships across varieties. We found one significant trait-environment relationship for Asat (taproot tissue density-soil phosphorus), which was consistent across varieties. For WUE, we found that three relationships (petiole diameter-soil nitrogen, petiole diameter-soil phosphorus, and leaf area-soil phosphorus) varied significantly across varieties. As a result, WUE was maximized by different combinations of trait values and soil conditions depending on the variety. Our three-dimensional framework supports the identification of functional traits behind the differential responses of crop varieties to environmental variation and thus guides breeding programs to optimize crop attributes from an eco-evolutionary perspective.

The role of plant functional traits and diversity in soil carbon dynamics within riparian agroforests.

Restoration of agricultural riparian buffers with trees (agroforestry) provides an elegant solution to enhance carbon storage while also augmenting local biodiversity. Yet the scope and role of riparian plant community diversity in key soil dynamics remain unresolved. Operationalizing riparian age (young [<10 yr] and mature [>30 yr] since establishment] and forest stand type (coniferous and deciduous dominant) to capture the potential extent of plant diversity, we measured plant functional trait diversity and community weighted mean trait values, microbial composition, abiotic soil conditions, and rates of soil CO2 efflux (mg CO2 -C m-2 h-1 ). We used piecewise structural equation modeling (SEM) to further refine the role of biotic indices (leaf, root, and microbial characteristics), and abiotic factors (soil physio-chemical metrics) on soil C cycling processes in riparian systems. We found significantly lower rates of CO2 efflux (F = 8.47; p < .01) over one growing season and higher total soil C (F = 3.46; p = .03) in mature buffers compared with young buffers. Using SEM, we describe influences on soil C content (marginal r2  = 61) and soil CO2 efflux (marginal r2  = 53). Within young buffers, soil C content was significantly predicted by fungal/bacterial ratio and root length density, whereas in mature buffers, tree leaf characteristics were associated with soil C content. Soil CO2 efflux was predicted by soil moisture, soil carbon content, and herbaceous root characteristics. Evidently, leaf and root functional traits in combination with broad soil parameters significantly describe soil C dynamics in the field; however, significant pathways are not the same throughout the life cycle of a riparian agroforest.

National-scale changes in crop diversity through the Anthropocene.

Expansion of crops beyond their centres of domestication is a defining feature of the Anthropocene Epoch. This process has fundamentally altered the diversity of croplands, with likely consequences for the ecological functioning and socio-economic stability of agriculture under environmental change. While changes in crop diversity through the Anthropocene have been quantified at large spatial scales, the patterns, drivers, and consequences of change in crop diversity and biogeography at national-scales remains less explored. We use production data on 339 crops, grown in over 150 countries from 1961 to 2017, to quantify changes in country-level crop richness and evenness. Virtually all countries globally have experienced significant increases in crop richness since 1961, with the early 1980s marking a clear onset of a ~ 9-year period of increase in crop richness in countries worldwide. While these changes have increased the similarity of diversity of croplands among countries, only half of countries experienced increases in crop evenness through time. Ubiquitous increases in crop richness within nearly all countries between 1980 and 2000 are a unique biogeographical feature of the Anthropocene. At the same time, we detected opposing changes in crop evenness, and only modest signatures of increased homogenization of croplands among countries. Therefore context-dependent and, at least, national-scale assessments are needed to understand and predict how changes in crop diversity influence agricultural resistance and resilience to environmental change.

Farmer social networks: The role of advice ties and organizational leadership in agroforestry adoption.

With the decline in public budgets for agricultural extension support, ties between members of farmer groups are becoming more important to facilitate information transfer about agroforestry. This paper examines the role of social network ties in predicting organizational leadership in an agroforestry-based farmer group. Using social network data derived from interviews with members of farming groups based in the Ayeyarwady Delta of Myanmar, we established a positive relationship between advice-seeking ties and organizational leadership. In other words, farmers who were highly sought for agroforestry advice were more likely to be elected as leaders of the farmer group. Results show the frequency of interactions through advice-seeking ties also had a positive influence on the probability of farmers holding leadership positions. We found a core-periphery structure for the advice networks, whereby farmer leaders were overrepresented at the network core. Interestingly, general members of the farmer group were also in the core of the core-periphery structure, suggesting that engaging with farmers without leadership roles can also effectively disseminate agroforestry information to peripheral farmers. We conclude that farmer groups are valuable in agroforestry adoption and persistence and further analyses of formal leadership structures are needed to support more transparent and accountable governance.

Root Functional Trait and Soil Microbial Coordination: Implications for Soil Respiration in Riparian Agroecosystems.

Predicting respiration from roots and soil microbes is important in agricultural landscapes where net flux of carbon from the soil to the atmosphere is of large concern. Yet, in riparian agroecosystems that buffer aquatic environments from agricultural fields, little is known on the differential contribution of CO2 sources nor the systematic patterns in root and microbial communities that relate to these emissions. We deployed a field-based root exclusion experiment to measure heterotrophic and autotrophic-rhizospheric respiration across riparian buffer types in an agricultural landscape in southern Ontario, Canada. We paired bi-weekly measurements of in-field CO2 flux with analysis of soil properties and fine root functional traits. We quantified soil microbial community structure using qPCR to estimate bacterial and fungal abundance and characterized microbial diversity using high-throughput sequencing. Mean daytime total soil respiration rates in the growing season were 186.1 ± 26.7, 188.7 ± 23.0, 278.6 ± 30.0, and 503.4 ± 31.3 mg CO2-C m-2 h-1 in remnant coniferous and mixed forest, and rehabilitated forest and grass buffers, respectively. Contributions of autotrophic-rhizospheric respiration to total soil CO2 fluxes ranged widely between 14 and 63% across the buffers. Covariation in root traits aligned roots of higher specific root length and nitrogen content with higher specific root respiration rates, while microbial abundance in rhizosphere soil coorindated with roots that were thicker in diameter and higher in carbon to nitrogen ratio. Variation in autotrophic-rhizospheric respiration on a soil area basis was explained by soil temperature, fine root length density, and covariation in root traits. Heterotrophic respiration was strongly explained by soil moisture, temperature, and soil carbon, while multiple factor analysis revealed a positive correlation with soil microbial diversity. This is a first in-field study to quantify root and soil respiration in relation to trade-offs in root trait expression and to determine interactions between root traits and soil microbial community structure to predict soil respiration.

The leaf economics spectrum's morning coffee: plant size-dependent changes in leaf traits and reproductive onset in a perennial tree crop.

BACKGROUND AND AIMS: Size-dependent changes in plant traits are an important source of intraspecific trait variation. However, there are few studies that have tested if leaf trait co-variation and/or trade-offs follow a within-genotype leaf economics spectrum (LES) related to plant size and reproductive onset. To our knowledge, there are no studies on any plant species that have tested whether or not the shape of a within-genotype LES that describes how traits covary across whole plant sizes, is the same as the shape of a within-genotype LES that represents environmentally driven trait plasticity. METHODS: We quantified size-dependent variation in eight leaf traits in a single coffee genotype (Coffea arabica var. Caturra) in managed agroecosystems with different environmental conditions (light and fertilization treatments), and evaluated these patterns with respect to reproductive onset. We also evaluated if trait covariation along a within-genotype plant-size LES differed from a within-genotype environmental LES defined with trait data from coffee growing in different environmental conditions. KEY RESULTS: Leaf economics traits related to resource acquisition - maximum photosynthetic rates (A) and mass-based leaf nitrogen (N) concentrations - declined linearly with plant size. Structural traits - leaf mass, leaf thickness, and leaf mass per unit area (LMA) - and leaf area increased with plant size beyond reproductive onset, then declined in larger plants. Three primary LES traits (mass-based A, leaf N and LMA) covaried across a within-genotype plant-size LES, with plants moving towards the 'resource-conserving' end of the LES as they grow larger; in coffee these patterns were nearly identical to a within-genotype environmental LES. CONCLUSIONS: Our results demonstrate that a plant-size LES exists within a single genotype. Our findings indicate that in managed agroecosystems where resource availability is high the role of reproductive onset in driving within-genotype trait variability, and the strength of covariation and trade-offs among LES traits, are less pronounced compared with plants in natural systems. The consistency in trait covariation in coffee along both plant-size and environmental LES axes indicates strong constraints on leaf form and function that exist within plant genotypes.

Accumulating crop functional trait data with citizen science.

Trait-based ecology is greatly informed by large datasets for the analyses of inter- and intraspecific trait variation (ITV) in plants. This is especially true in trait-based agricultural research where crop ITV is high, yet crop trait data remains limited. Based on farmer-led collections, we developed and evaluated the first citizen science plant trait initiative. Here we generated a dataset of eight leaf traits for a commercially important crop species (Daucus carota), sampled from two distinct regions in Canada, which is 25-fold larger than datasets available in existing trait databases. Citizen-collected trait data supported analyses addressing theoretical and applied questions related to (i) intraspecific trait dimensionality, (ii) the extent and drivers of ITV, and (iii) the sampling intensity needed to derive accurate trait values. Citizen science is a viable means to enhance functional trait data coverage across terrestrial ecosystems, and in doing so, can directly support theoretical and applied trait-based analyses of plants.

Regional and global shifts in crop diversity through the Anthropocene.

The Anthropocene epoch is partly defined by anthropogenic spread of crops beyond their centres of origin. At global scales, evidence indicates that species-level taxonomic diversity of crops being cultivated on large-scale agricultural lands has increased linearly over the past 50 years. Yet environmental and socio-economic differences support expectations that temporal changes in crop diversity vary across regions. Ecological theory also suggests that changes in crop taxonomic diversity may not necessarily reflect changes in the evolutionary diversity of crops. We used data from the Food and Agricultural Organization (FAO) of the United Nations to assess changes in crop taxonomic- and phylogenetic diversity across 22 subcontinental-scale regions from 1961-2014. We document certain broad consistencies across nearly all regions: i) little change in crop diversity from 1961 through to the late 1970s; followed by ii) a 10-year period of sharp diversification through the early 1980s; followed by iii) a "levelling-off" of crop diversification beginning in the early 1990s. However, the specific onset and duration of these distinct periods differs significantly across regions and are unrelated to agricultural expansion, indicating that unique policy or environmental conditions influence the crops being grown within a given region. Additionally, while the 1970s and 1980s are defined by region-scale increases in crop diversity this period marks the increasing dominance of a small number of crop species and lineages; a trend resulting in detectable increases in the similarity of crops being grown across regions. Broad similarities in the species-level taxonomic and phylogenetic diversity of crops being grown across regions, primarily at large industrial scales captured by FAO data, represent a unique feature of the Anthropocene epoch. Yet nuanced asymmetries in regional-scale trends suggest that environmental and socio-economic factors play a key role in shaping observed macro-ecological changes in the plant diversity on agricultural lands.

Intraspecific Trait Variation and Coordination: Root and Leaf Economics Spectra in Coffee across Environmental Gradients.

Hypotheses on the existence of a universal "Root Economics Spectrum" (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world's most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another.

Resistance and resilience of root fungal communities to water limitation in a temperate agroecosystem.

Understanding crop resilience to environmental stress is critical in predicting the consequences of global climate change for agricultural systems worldwide, but to date studies addressing crop resiliency have focused primarily on plant physiological and molecular responses. Arbuscular mycorrhizal fungi (AMF) form mutualisms with many crop species, and these relationships are key in mitigating the effects of abiotic stress in many agricultural systems. However, to date there is little research examining whether (1) fungal community structure in agroecosystems is resistant to changing environmental conditions, specifically water limitation and (2) resilience of fungal community structure is moderated by agricultural management systems, namely the integration of trees into cropping systems. Here, we address these uncertainties through a rainfall reduction field experiment that manipulated short-term water availability in a soybean-based (Glycine max L. Merr.) agroforest in Southern Ontario, Canada. We employed terminal restriction fragment length polymorphism analysis to determine the molecular diversity of both general fungal and AMF communities in soybean roots under no stress, stress (rainfall shelters added), and poststress (rainfall shelters removed). We found that general fungal and AMF communities sampled from soybean roots were resistant to rainfall reduction in a monoculture, but not in an agroforest. While AMF communities were unchanged after stress removal, general fungal communities were significantly different poststress in the agroforest, indicating a capacity for resiliency. Our study indicates that generalist fungi and AMF are responsive to changes in environmental conditions and that agroecosystem management plays a key role in the resistance and resilience of fungal communities to water limitation.

The importance of plant genotype and contemporary evolution for terrestrial ecosystem processes.

Plant genetic variation and evolutionary dynamics are predicted to impact ecosystem processes but these effects are poorly understood. Here we test the hypothesis that plant genotype and contemporary evolution influence the flux of energy and nutrients through soil, which then feedback to affect seedling performance in subsequent generations. We conducted a multiyear field evolution experiment using the native biennial plant Oenothera biennis. This experiment was coupled with experimental assays to address our hypothesis and quantify the relative importance of evolutionary and ecological factors on multiple ecosystem processes. Plant genotype, contemporary evolution, spatial variation, and herbivory affected ecosystem processes (e.g., leaf decay, soil respiration, seedling performance, N cycling), but their relative importance varied between specific ecosystem variables. Insect herbivory and evolution also contributed to a feedback that affected seedling biomass of O. biennis in the next generation. Our results show that heritable variation among plant genotypes can be an important factor affecting local ecosystem processes, and while effects of contemporary evolution were detectable and sometimes strong, they were often contingent on other ecological, factors.

An in situ approach to detect tree root ecology: linking ground-penetrating radar imaging to isotope-derived water acquisition zones.

Tree root distribution and activity are determinants of belowground competition. However, studying root response to environmental and management conditions remains logistically challenging. Methodologically, nondestructive in situ tree root ecology analysis has lagged. In this study, we tested a nondestructive approach to determine tree coarse root architecture and function of a perennial tree crop, Theobroma cacao L., at two edaphically contrasting sites (sandstone and phyllite-granite derived soils) in Ghana, West Africa. We detected coarse root vertical distribution using ground-penetrating radar and root activity via soil water acquisition using isotopic matching of δ(18)O plant and soil signatures. Coarse roots were detected to a depth of 50 cm, however, intraspecifc coarse root vertical distribution was modified by edaphic conditions. Soil δ(18)O isotopic signature declined with depth, providing conditions for plant-soil δ(18)O isotopic matching. This pattern held only under sandstone conditions where water acquisition zones were identifiably narrow in the 10-20 cm depth but broader under phyllite-granite conditions, presumably due to resource patchiness. Detected coarse root count by depth and measured fine root density were strongly correlated as were detected coarse root count and identified water acquisition zones, thus validating root detection capability of ground-penetrating radar, but exclusively on sandstone soils. This approach was able to characterize trends between intraspecific root architecture and edaphic-dependent resource availability, however, limited by site conditions. This study successfully demonstrates a new approach for in situ root studies that moves beyond invasive point sampling to nondestructive detection of root architecture and function. We discuss the transfer of such an approach to answer root ecology questions in various tree-based landscapes.

Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp.] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination.

Assessing local knowledge use in agroforestry management with cognitive maps.

Small-holder farmers often develop adaptable agroforestry management techniques to improve and diversify crop production. In the cocoa growing region of Ghana, local knowledge on such farm management holds a noteworthy role in the overall farm development. The documentation and analysis of such knowledge use in cocoa agroforests may afford an applicable framework to determine mechanisms driving farmer preference and indicators in farm management. This study employed 12 in-depth farmer interviews regarding variables in farm management as a unit of analysis and utilized cognitive mapping as a qualitative method of analysis. Our objectives were (1) to illustrate and describe agroforestry management variables and associated farm practices, (2) to determine the scope of decision making of individual farmers, and (3) to investigate the suitability of cognitive mapping as a tool for assessing local knowledge use. Results from the cognitive maps revealed an average of 16 +/- 3 variables and 19 +/- 3 links between management variables in the farmer cognitive maps. Farmer use of advantageous ecological processes was highly central to farm management (48% of all variables), particularly manipulation of organic matter, shade and food crop establishment, and maintenance of a tree stratum as the most common, highly linked variables. Over 85% of variables included bidirectional arrows, interpreted as farm management practices dominated by controllable factors, insofar as farmers indicated an ability to alter most farm characteristics. Local knowledge use on cocoa production revealed detailed indicators for site evaluation, thus affecting farm preparation and management. Our findings suggest that amid multisourced information under conditions of uncertainty, strategies for adaptable agroforestry management should integrate existing and localized management frameworks and that cognitive mapping provides a tool-based approach to advance such a management support system.