Recent publications
Cocoa agroforestry systems (AFS) provide multiple ecosystem services, which are influenced by features of the shade tree community. By strategically selecting and managing shade trees based on their functional traits, cocoa farmers can affect functional diversity of AFS and potentially enhance the benefits they deliver. In this research, we applied functional trait ecology to better understand the effect of functional diversity of cocoa AFS on three ecosystem services: carbon storage, soil fertility, and provisioning of cocoa and other products. To achieve this, we characterized 30 AFS across a gradient of ecological complexity and established relationships between functional diversityw indices and ecosystem services using ANOVA and multiple regression models. As a result, two contrasting ecological dynamics were observed: low-complexity AFS, dominated by resource-conservative traits (higher leaf dry matter content, higher stem specific density, and low leaf nitrogen concentration), were associated with lower carbon stocks and soil fertility, while high-complexity AFS, characterized by resource-acquisitive traits (low leaf dry matter content, low stem specific density, and high leaf nitrogen concentration), delivered greater ecosystem services. Through the multiple regression analysis, we found that AFS dominated by species with greater maximum potential height, greater leaf nitrogen concentration, lower leaf dry matter content, lower leaf mass per area, and lower leaf nitrogen-phosphorus ratio were associated with higher carbon storage (R² = 0.84), soil fertility (R² = 0.7 for soil nitrogen), and multiple ecosystem services (R² = 0.78). Additionally, cocoa yields were negatively correlated with shade cover and the dominance of large-leaf shade trees, revealing a potential trade-off between maximizing yields and enhancing ecosystem services. Nevertheless, the models indicated that a win-win scenario can be achieved when shade trees are productive, generating additional benefits. Finally, our study highlights critical relationships between shade tree traits and delivery of key ecosystem services for farm sustainability and farmer livelihoods.
Introducing artificial intelligence techniques in agriculture offers new opportunities for improving crop management, such as in coffee plantations, which constitute a complex agroforestry environment. This paper presents a comparative study of three deep learning frameworks: Deep Forest, RT-DETR, and Yolov9, customized for coffee plant detection and trained from images with a high spatial resolution (cm/pix). Each frame had dimensions of 640 × 640 pixels acquired from passive RGB sensors onboard a UAS (Unmanned Aerial Systems) system. The image set was structured and consolidated from UAS-RGB imagery acquisition in six locations along the Central Valley, Costa Rica, through automated photogrammetric missions. It was evidenced that the RT-DETR and Yolov9 frameworks allowed adequate generalization and detection with mAP50 values higher than 90% and mAP5095 higher than 54%, in scenarios of application with data augmentation techniques. Deep Forest also achieved good metrics, but noticeably lower when compared to the other frameworks. RT-DETR and Yolov9 were able to generalize and detect coffee plants in unseen scenarios that include complex forest structures within tropical agroforestry Systems (AFS).
The concept of well-being of rural families is part of a theory under construction in which new theoretical elements are constantly being incorporated. This research aims to determine the influence of farmers’ knowledge on the well‑being of cocoa growing families in the departments of Santander, Huila, Meta and Caquetá, Colombia. Four categories of farmers were identified with different levels of knowledge in the management of cocoa cultivation obtained through a cluster analysis. The well-being of cocoa farmers, understood as the balance in the capital endowment of rural households, was obtained through the application of a semi-structured interview with 49 variables of human, cultural, social, political, natural, built, and financial capitals. The results show that cocoa knowledge is heterogeneous in the study area, with a slight improvement towards harvesting, post-harvest and transformation links. There is a positive relationship between cocoa knowledge and the well-being of cocoa farming families. Thus, producers with greater integral knowledge, with emphasis on post-harvest and bean transformation links, showed greater well-being. The Random Forest analysis identified that human capital (political, social, human, and cultural) made the greatest contribution to well-being. The findings show that cocoa knowledge contributes to the well-being of rural households to the extent that it favors vertical relationships (linkages with local governments) and horizontal relationships of producers (participation of association managers, sharing knowledge with friends, neighbors and partners, and cocoa training).
Determining the number of repetitions in agricultural experiments: Importance of effect size and variability. Introduction. The effect size and variability are relevant factors in estimating the number of repetitions in an experiment, where their impact is often unknown to the researcher. Objetive. To analyze the effect of the variability and effect size on the number of repetitions required in agricultural research. Materials and methods. The spatial correlation parameters estimated from the uniformity trial in the rice crop were used to perform 10,000 simulations of random fields. In each simulation, 16 experimental units of 24 m2 were formed, and an analysis of variance was adjusted to estimate the average residual variance, called scenario A.Additionally, a scenario B was proposed, where the 95th percentile of the estimated variances was used. The effect size was defined based on the results of a meta-analysis on the effect of agricultural practices on rice yield, and resulted in a 15% of the overall mean of the uniformity trial data. Additional effect sizes of 10% and 5% of the overall mean were also proposed. Results. In scenario A, four repetitions were needed to achieve a power of 0.91 and detect a 15% effect, while six repetitions were necessary to detect a 10% effect with a power of 0.81. In scenario B, five repetitions achieved a power of 0.86 to detect a 15% effect, while nine repetitions were required to detect a 10% effect with a power of 0.82. Neither of the scenarios achieved a power 0.80 to detect a 5% effect. Conclusion. The smaller the effect size to be detected and the greater the residual variance, the more repetitions were required to achieve a test power of 0.80. These two factors should be considered when planning experiments in agriculture.
The Vilcanota is the second-largest snow-capped mountain range in Peru, featuring 380 individual glaciers, each with its own unique characteristics that must be studied independently. However, few studies have been conducted in the Vilcanota range to monitor and track the area and volume changes of the Suyuparina and Quisoquipina glaciers. Notably, there are only a few studies that have approached this issue using LIDAR technology. Our methodology is based on a combination of optical, radar and LIDAR data sources, which allowed for constructing coherent temporal series for the both the perimeter and volume changes of the Suyuparina and Quisoquipina glaciers while accounting for the uncertainty in the perimeter detection procedure. Our results indicated that, from 1990 to 2013, there was a reduction in snow cover of 12,694.35 m² per year for Quisoquipina and 16,599.2 m² per year for Suyuparina. This represents a loss of 12.18% for Quisoquipina and 22.45% for Suyuparina. From 2006 to 2013, the volume of the Quisoquipina glacier decreased from 11.73 km³ in 2006 to 11.04 km³ in 2010, while the Suyuparina glacier decreased from 6.26 km³ to 5.93 km³. Likewise, when analyzing the correlation between glacier area and precipitation, a moderate inverse correlation (R = −0.52, p < 0.05) was found for Quisoquipina. In contrast, the correlation for Suyuparina was low and nonsignificant, showing inconsistency in the effect of precipitation. Additionally, the correlation between the snow cover area and the annual mean air temperature (R = −0.34, p > 0.05) and annual minimum air temperature (R = −0.36, p > 0.05) was low, inverse, and not significant for Quisoquipina. Meanwhile, snow cover on Suyuparina had a low nonsignificant correlation (R = −0.31, p > 0.05) with the annual maximum air temperature, indicating a minimal influence of the measured climatic variables near this glacier on its retreat. In general, it was possible to establish a reduction in both the area and volume of the Suyuparina and Quisoquipina glaciers based on freely accessible remote sensing data.
We examined how different patterns of crystal methamphetamine (CM) use are associated with different psychosocial and sexual health outcomes among gay, bisexual, and other men who have sex with men (GBM). We used latent class analysis to identify different patterns of CM use with the ASSIST scale for GBM who report using CM (n = 228), and examined how these classes differed from each other and from GBM who do not use CM (n = 2221). Results: We found four CM-use classes based on ASSIST responses. Classes defined by occasional use but few problems were more likely to test positive for STIs, while classes defined by more frequent use and problems were less likely to have STIs, but reported greater psychosocial problems. Interventions should focus on tailored substance use counselling and health promotion strategies to address the diversity of problems faced by GBM who use CM.
A network of agronomists, researchers, and practitioners associated with cacao farming provided open access to their independent field trials across Latin America and the Caribbean (LAC). A centralized dataset was assembled using qualitative and quantitative data from 25 experimental field trials (hereafter referred to as “CacaoFIT”) spanning several LAC agroecosystems. This dataset was used to document the main traits and agroclimatic attributes of the cacao cultivation model being tested within the CacaoFIT network. By synthesizing data from an entire network of cacao trials, this study aimed to highlight specific design features and management practices that may contribute to better cacao farming sustainability. The CacaoFIT network comprises 200 ha of field trials testing over 150 cacao genotypes and set up under different shade canopy design, management, and research goals. Small-sized trials were common across Mesoamerica, whereas medium to large-size trials were distinct to South America. Cacao trials were 15 years old (on average) and ranged from 3 to 25 years of establishment. Most cacao trials were managed conventionally (i.e., 55%), while 20% were under organic practices, and the remaining 25% presented both conventional and organic management approaches. Most field trials (ca. 60%) planted an average of 10 international clones or national cultivars at high (1,230–1,500 plants ha⁻¹) and medium density (833–1,111 plants ha⁻¹). Mixed shade canopies were the dominant agroforestry model, while timber vs. leguminous shade canopies were also common. The diversity and depth of research domains examined across the CacaoFIT network varied widely. Agronomy and agroforestry topics dominated the research agenda across all trials, followed by environmental services domains. Cacao physiology and financial performance were researched to a lesser extent within the network. Five featured field trials from CacaoFIT offered technical guidelines to inform cacao farming within similar contexts. This collaborative work is a scaffold to encourage public–private partnerships, capacity building, and data sharing amongst cacao researchers across the tropics.
Increasing costs of coffee production relative to coffee prices has led to concern across the industry of lack of profitability of coffee production especially for smallholders who comprise a large majority of producers. This study compares coffee production costs and income over a decadal interval of 2008 versus 2019 for coffee farmers in some of the main coffee growing regions of Costa Rica and Guatemala. Costs and income were collected by farmer recall using a standard questionnaire with trained research surveyors. Net income as assessed by EBITDA (earnings before interest, taxes, depreciation and amortization) increased by about 30% in Costa Rica, but declined to a third of its 2008 level in Guatemala. Agronomic costs of production per hectare increased by 31% in Costa Rica and 62% in Guatemala, mostly due to increased labor costs (higher daily wage rates), while fertilizer usage increased but unit costs remained stable. Gross income was stable in Guatemala but increased in Costa Rica due to receiving significantly higher prices for their coffee in 2019 compared to 2008, while in Guatemala prices declined. Nevertheless, the response was not uniform between farms in Costa Rica while high and medium productivity groupings of farms had higher EBITDA, low and very low productivity farms experienced a decline similar to Guatemala. The difference in performance of farm groups in Costa Rica was due to a decline in production per hectare of the lower productivity group; while the difference between Guatemala and Costa Rica was firstly due to price differences, and secondarily due to lower productivity of some farm groups. The investment of Costa Rican farmers was undoubtedly supported by the substantially increased price received by farmers (as compared to Guatemala), reflected in the increase in export price of coffee from Costa Rica relative to Guatemala. This shows the importance of farmers receiving higher prices for their produce in enabling them to cover increasing production costs, invest in increasing productivity and maintain profitability.
Trees on Farms (TonF) are ubiquitous. Farmers obtain numerous goods and services from their trees, which help them to cope with their livelihood needs and contingencies, climate change, and other stresses. Some benefits from trees on farms are extensive to the global society. Decision- and policymakers as well as development leaders are not consciously aware of the extent (in terms of area covered, human population involved, contribution to national and local economics, etc.) and importance (for rural livelihoods and provision of ecosystem services) of trees on farms. As a consequence, they do not include this important natural resource in their territorial development and nature conservation planning. Trees on farms are “invisible” in most forest legislation in the world. This has to be changed. Unfortunately, the inaccuracy and lack of enough detail of current TonF assessments impede the estimation of the actual benefits derived from them, which in turn inhibits evidence-based planning and policy development. In this chapter, we document the role of TonF in providing livelihoods, conservation of tree diversity, and storage of carbon in aboveground biomass in 90 smallholder farms in Northeastern Nicaragua. This knowledge can help in the design of restoration efforts and can also contribute to support policy and institutional enabling environments to motivate farmers to retain, manage, and use TonF.
Purpose: Longitudinal data on the experience and perpetration of intimate partner violence (IPV) among gay, bisexual, and other men who have sex with men (GBM) are limited. We estimated the prevalence of past 6-month (P6M) physical and/or sexual IPV (hereafter IPV) experience and perpetration, identified their determinants, and assessed temporal trends, including the impact of the coronavirus disease (COVID)-19 pandemic. Methods: We used data from the Engage Cohort Study (2017-2022) of GBM recruited using respondent-driven sampling in Montréal, Toronto, and Vancouver. Adjusted prevalence ratios (aPRs) for determinants and self-reported P6M IPV were estimated using generalized estimating equations, accounting for attrition (inverse probability of censoring weights) and relevant covariates. Longitudinal trends of IPV were also assessed. Results: Between 2017 and 2022, 1455 partnered GBM (median age 32 years, 82% gay, and 71% White) had at least one follow-up visit. At baseline, 31% of participants experienced IPV in their lifetime and 17% reported ever perpetrating IPV. During follow-up, IPV experience was more common (6%, 95% confidence interval [CI]: 5%-7%) than perpetration (4%, 95% CI: 3%-5%). Factors associated with P6M IPV experience included prior IPV experience (aPR: 2.68, 95% CI: 1.76-4.08), lower education (aPR: 2.31, 95% CI: 1.32-4.04), and substance use (injection aPR: 5.05, 95% CI: 2.54-10.05, non-injection aPR: 1.68, 95% CI: 1.00-2.82). Similar factors were associated with IPV perpetration. IPV was stable over time; periods of COVID-19 restrictions were not associated with IPV changes in this cohort. Conclusion: Prevalence of IPV was high among GBM. Determinants related to marginalization were associated with an increased risk of IPV. Interventions should address these determinants to reduce IPV and improve health.
Aim
Successional changes in functional diversity provide insights into community assembly by indicating how species are filtered into local communities based on their traits. Here, we assess successional changes in taxonomic and functional richness, evenness and redundancy along gradients of climate, soil pH and forest cover.
Location
Neotropics.
Time period
Last 0–100 years.
Major taxa studied
Trees.
Methods
We used 22 forest chronosequence studies and 676 plots across the Neotropics to analyse successional changes in Hill's taxonomic and functional diversity of trees, and how these successional changes vary with continental‐scale gradients in precipitation, soil pH and surrounding forest cover.
Results
Taxonomic and functional richness and functional redundancy increased, while taxonomic and functional evenness decreased over time. Functional richness and evenness changed strongly when not accounting for taxonomic richness, but changed more weakly after statistically accounting for taxonomic richness, indicating that changes in functional diversity are largely driven by taxonomic richness. Nevertheless, the successional increases in functional richness when correcting for taxonomic richness may indicate that environmental heterogeneity and limiting similarity increase during succession. The taxonomically‐independent successional decreases in functional evenness may indicate that stronger filtering and competition select for dominant species with similar trait values, while many rare species and traits are added to the community. Such filtering and competition may also lead to increased functional redundancy. The changes in taxonomically‐independent functional diversity varied with resource availability and were stronger in harsh, resource‐poor environments, but weak in benign, productive environments. Hence, in resource‐poor environments, environmental filtering and facilitation are important, whereas in productive environments, weaker abiotic filtering allows for high initial functional diversity and weak successional changes.
Main conclusion
We found that taxonomic and functional richness and functional redundancy increased and taxonomic and functional evenness decreased during succession, mainly caused by the increasing number of rare species and traits due to the arrival of new species and due to changing (a)biotic filters.
Secondary tropical forests play an increasingly important role in carbon budgets and biodiversity conservation. Understanding successional trajectories is therefore imperative for guiding forest restoration and climate change mitigation efforts. Forest succession is driven by the demographic strategies—combinations of growth, mortality and recruitment rates—of the tree species in the community. However, our understanding of demographic diversity in tropical tree species stems almost exclusively from old‐growth forests. Here, we assembled demographic information from repeated forest inventories along chronosequences in two wet (Costa Rica, Panama) and two dry (Mexico) Neotropical forests to assess whether the ranges of demographic strategies present in a community shift across succession. We calculated demographic rates for >500 tree species while controlling for canopy status to compare demographic diversity (i.e., the ranges of demographic strategies) in early successional (0–30 years), late successional (30–120 years) and old‐growth forests using two‐dimensional hypervolumes of pairs of demographic rates. Ranges of demographic strategies largely overlapped across successional stages, and early successional stages already covered the full spectrum of demographic strategies found in old‐growth forests. An exception was a group of species characterized by exceptionally high mortality rates that was confined to early successional stages in the two wet forests. The range of demographic strategies did not expand with succession. Our results suggest that studies of long‐term forest monitoring plots in old‐growth forests, from which most of our current understanding of demographic strategies of tropical tree species is derived, are surprisingly representative of demographic diversity in general, but do not replace the need for further studies in secondary forests.
This study aimed to evaluate the stability of cacao clone production by analyzing the dynamics of pod production over time. It investigates correlations in multi-year production levels and explores how genetics influence both intra-annual and inter-annual temporal production dynamics of total and healthy pods. To address these questions, data were analysed from a clonal cacao trial conducted over a period of 18 years in Costa Rica. Longitudinal data analysis provided a clearer understanding of the link between yields over successive years. The best-fit model proved to be the ante-dependence model. This model indicated that the correlation between two successive years was relatively stable, and the correlation between years decreased as the interval between years increased. These correlations are also higher as the age of the trees increases. The clones differ more in terms of their production of healthy pods than total pod production. Four dynamic patterns, considering both intra- and inter-annual production, were identified, revealing differences in production timing and distinct peaks for each class. Inter-annual variability analysis revealed differences in healthy pod production among classes, with some displaying more sustainable production dynamics over 18 years. Intra-annual variability analysis showed significant variation in production periods among clones, with different production distributions throughout the year allowing selection of escape and or resistant clones. The study emphasized the importance of genetics in sustainable cacao production, with potential implications for clonal selection. It was suggested to combine clones of different classes to mitigate risks and spread harvests, emphasizing that resilience is a crucial criterion in cacao breeding programs to effectively meet new challenges. Further research is recommended to explore the influence of various environmental factors and facilitate more efficient selection in perennial crops, with the aim of selecting more resilient clones, a particularly important objective in the context of climate change.
The paper focuses on the failure to account for the value of standing tropical forests, and of ecosystem services in general, in economic decision-making. This blindness to the values of nature has led to overexploitation, degradation and destruction of tropical forests, which, in turn, has also significantly contributed to greenhouse gas emissions. Forest conservation and restoration has a critical role to play in the fight against climate change and brings a vast array of additional benefits, from security in water, energy, food, health and livelihoods to maintaining biodiversity itself as a core component of our living planet. As first Minister of Environment and Energy under President Oscar Arias (1986–1990), I brought these views into societal decision-making in Costa Rica and here I briefly describe how.
This article is part of the theme issue ‘Bringing nature into decision-making’.
Though facing significant challenges, coffee (Coffea arabica) grown in Haitian agroforestry systems are important contributors to rural livelihoods and provide several ecosystem services. However, little is known about their genetic diversity and the variety mixtures used. In light of this, there is a need to characterize Haitian coffee diversity to help inform revitalization of this sector. We sampled 28 diverse farms in historically important coffee growing regions of northern and southern Haiti. We performed KASP-genotyping of SNP markers and HiPlex multiplex amplicon sequencing for haplotype calling on our samples, as well as several Ethiopian and commercial accessions from international collections. This allowed us to assign Haitian samples to varietal groups. Our analyses revealed considerable genetic diversity in Haitian farms, higher in fact than many farmers realized. Notably, genetic structure analyses revealed the presence of clusters related to Typica, Bourbon, and Catimor groups, another group that was not represented in our reference accession panel, and several admixed individuals. Across the study areas, we found both mixed-variety farms and monovarietal farms with the historical and traditional Typica variety. This study is, to our knowledge, the first to genetically characterize Haitian C. arabica variety mixtures, and report the limited cultivation of C. canephora (Robusta coffee) in the study area. Our results show that some coffee farms are repositories of historical, widely-abandoned varieties while others are generators of new diversity through genetic mixing.
Coffee cultivation under agroforestry systems is one of the main agricultural activities in Central America, but climate change is putting its sustainability at risk. Rainfall erosivity has worsened, thus driving soil losses. Although the vegetal covers in coffee agroforestry systems play a crucial role in controlling erosion, the specific influence of each cover layer remains unclear. In this study, we assessed the influence of the canopy (tree and banana cover and coffee cover) and ground cover (weed and litter) on water driven soil erosion, to determine which type of cover has the most influence on soil erosion control. The study site is situated in the core and buffer zones of the Macizo de Peñas Blancas National Park (Nicaragua), where seventeen coffee sampling plots with an agroforestry system composed of an Inga spp and Musa spp canopy cover were analysed. The results showed that the 19.2 ± 3.4% of the soil surface was affected by erosion and it was mainly related to the litter ground cover (r = –0.95, P < 0.001). Also, this cover presented the best partial correlation (ryl.tcw = –0.93, P < 0.001) when the effects of the other vegetal covers were eliminated. Specifically, the litter cover accounted for 90% of the erosion variability, while the impact of the other types of cover was negligible, accounting for just 1% of the erosion. We conclude that litter layer is more important than canopy cover for effective erosion control, and the main function of shade trees is as a source of litter biomass.
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.
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