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The objective of the research was to provide an overview of soil N2O emissions in coffee cropping systems; summarizing available field data on soil emissions and identifying controlling factors (fertilizer type, precipitation, temperature, altitude). A systematic search of Scopus, Science Direct, Springer, and Scielo for experimental-type studies was conducted from January 2000 to October 2021. Of the seventy manuscripts determined through the search strategy, eight studies met the inclusion criteria. Analysis of the included studies revealed that they were conducted in Ecuador, Costa Rica, and Nicaragua; the rainfall of the fields ranged from 910 mm to 2740 mm per year and the average temperature was 20.3°C. Coffee is planted under agroforestry systems and monocultures; in addition, the most abundant forest species in coffee agroforestry systems are leguminous plants of the Inga and Erytrina genus and 60% of the studies have been developed with the Catuai coffee variety. The pH and humidity of the soil where coffee plantations are developed range from 4.67 to 6.34 and 53.3 to 67.05% respectively. Finally, the fertilizers used are of chemical, organic, and chemical + polymer origin, at fertilization rates ranging from 66 to 400 kg.N.ha-1yr-1 and N2O emissions ranging from 0.2 to 12.8 kg.N.ha-1yr-1. Overall, the present systematic review provides a scientific basis for evaluating N2O emissions generated in coffee crops. [ABSTRACT FROM AUTHOR]

The goal of sustainable coffee production requires multiple functions from agroforestry systems. Many are difficult to quantify and data are lacking, hampering the choice of shade tree species and agronomic management. Process-based modelling may help quantify ecosystem services and disservices. We introduce and apply coffee agroforestry model CAF2021 (https://doi.org/10.5281/zenodo.5862195). The model allows for complex systems with up to three shade tree species. It simulates coffee yield, timber and fruit production by shade trees, soil loss in erosion, C-sequestration, N-fixation, -emission and -leaching. To calibrate the model, we used multivariate data from 32 different treatments applied in two long-term coffee agroforestry experiments in Costa Rica and Nicaragua. Without any further calibration, the model was then applied to agroforestry systems on 89 farms in Costa Rica and 79 in Guatemala where yields had been reported previously in farmer interviews. Despite wide variation in environmental and agronomic conditions, the model explained 36% of yield variation in Costa Rica but only 15% in Guatemala. Model analysis quantified trade-offs between yield and other ecosystem services as a function of fertilisation and shading. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is predicted to cause shifts in temperature and precipitation patterns that will be detrimental for global agriculture. Developing comprehensive strategies for building climate resilient agroecosystems is critical for maintaining future crop production. Arabica coffee (Coffea arabica) is highly sensitive to the quantity and timing of precipitation, so alterations in precipitation patterns that are predicted under climate change are likely to be a major challenge for maintaining coffee agroecosystems. We assessed cultivar selection as a potential component of more resilient coffee agroecosystems by evaluating water stress responses among five Arabica coffee cultivars (clonal hybrids H10 and H1 and seedling lines Catuai 44, Catuai, and Villa Sarchi) using a precipitation reduction experiment in the highlands of Tarrazú, Costa Rica. During the first harvest (eighteen months after planting), plants under the rainout treatment had 211 % greater total fruit weight and over 50 % greater biomass than under the control treatment, potentially due to protection from unusually high rainfall during this period of our experiment. At the second harvest (30 months after planting), after a year of more typical rainfall, plants under rainout still produced 66 % more fruit by weight than under control. The magnitude of the responses varied among cultivars where, at the first harvest, H10 and H1 had approximately 92 % and 81 % greater fruit production and 18 % and 22 % greater biomass, respectively, and at the second harvest H10 had 60 % more fruit production than the overall average. Thus, our findings suggest that the hybrid lines H10 and H1 are more resilient than the other cultivars to the stress of high soil moisture. Overall, our results indicate that stress due to higher than average rainfall could impair coffee plant growth and production, and that cultivar selection is likely to be an important tool for maintaining the viability of coffee production, and the resilience of global agroecosystems more generally, under climate change. [ABSTRACT FROM AUTHOR]

Objective: To identify the current coffee knowledge as agroforestry systems, with emphasis on Mexico. Design/Methodology/Scope: A search for documentary information was performed on the Internet based on Google®, with the keywords "agroforestry and coffee plantations" and "coffee systems in Mexico". Results: 88 documents were found; 91% of publications were in Spanish, 40% were from Colombia, 24% from Mexico, 7% from Costa Rica and the remaining 29% of other countries. Study Limitations/Implications: This topic is studied in several institutions, although it does not constitute a systematized study line. Findings/Conclusions: Most research works are centered on the importance of the coffee agroforestry system as provider of environmental services, among which the carbon and water intake, biodiversity reserve and erosion buffering stand out. [ABSTRACT FROM AUTHOR]

Coffee is often grown in production systems associated with shade trees that provide different ecosystem services. Management, weather and soil conditions are spatially variable production factors. CAF2007 is a dynamic model for coffee agroforestry systems that takes these factors as inputs and simulates the processes underlying berry production at the field scale. There remain, however, uncertainties about process rates that need to be reduced through calibration. Bayesian statistics using Markov chain Monte Carlo algorithms is increasingly used for calibration of parameter-rich models. However, very few studies have employed multi-site calibration, which aims to reduce parameter uncertainties using data from multiple sites simultaneously. The main objectives of this study were to calibrate the coffee agroforestry model using data gathered in long-term experiments in Costa Rica and Nicaragua, and to test the calibrated model against independent data from commercial coffee-growing farms. Two sub-models were improved: calculation of flowering date and the modelling of biennial production patterns. The modified model, referred to as CAF2014, can be downloaded at 10.5281/zenodo.3608877. Calibration improved model performance (higher R2, lower RMSE) for Turrialba (Costa Rica) and Masatepe (Nicaragua), including when all experiments were pooled together. Multi-site and single-site Bayesian calibration led to similar RMSE. Validation on new data from coffee-growing farms revealed that both calibration methods improved simulation of yield and its bienniality. The thus improved model was used to test the effect of N fertilizer and shade in different locations on coffee yield. [ABSTRACT FROM AUTHOR]

Like many perennial crops, coffee exhibits alternate bearing, a pattern of reproduction in which high-yielding years are followed by low-yielding ones. Alternate bearing threatens farmer livelihoods, yet little is known about the underlying mechanisms in coffee or the potential for farm management to mitigate it. The resource budget model, an ecological theory positing endogenous resource tradeoffs as the driver of reproductive variability, could help fill this gap. On three coffee farms in Santa María de Dota, Costa Rica, we manipulated relative fruit load, fertilizer levels, and shade cover to test whether the model's core assumptions (i.e., that fruiting depletes resources and limits investment in subsequent reproduction) can elucidate patterns of alternate bearing in coffee, and to assess whether these patterns are impacted by farm management practices. Coffee plants exhibited within-year and between-year tradeoffs of a high fruit load that scaled from decreased bean size during the same season to fewer fruited nodes and fruits per node in both old and new cohorts of branches during the subsequent season. Stem nitrogen concentration was also depleted in response to high fruit loads and recovered during the subsequent season of low fruiting. The findings provide novel evidence that tradeoffs of a high fruit load are manifested in several reproductive traits at both the branch- and plant-level and offer initial support for the resource budget model in the system. While both moderate shade and increased fertilizer levels tended to improve reproductive traits, a lack of interactive effects between either management treatment and the relative fruit load treatment suggests that they do little to mitigate the reproductive tradeoffs underlying alternate bearing. • Coffee exhibits alternate bearing: high-fruiting years are followed by low years. • We explored the role of resource tradeoffs and management in alternate bearing. • High fruit loads depleted nitrogen and limited bean quality and subsequent fruiting. • Fertilizer and shade management had no clear effect on between-year tradeoffs. • Results offer support for the resource budget model in coffee. [ABSTRACT FROM AUTHOR]

Understanding how species functional traits relate to the delivery of ecosystem services is essential to support on-going biodiversity conservation efforts. While much recent work has been conducted, relatively few studies relating functional ecology to ecosystem services has utilized field experiments, particularly for animal species. We used a functional diversity (FD) approach to study the effect of bird traits on the control of the coffee berry borer ( Hypothenemus hampei ) and the effect of canopy cover management on bird FD. We conducted an exclosure experiment to test the effect of bird FD on the difference of H. hampei infestation rates between coffee shrubs both exposed to, and excluded from bird foraging activity. We addressed the following questions: (1) is avian FD, at the plot level, a good predictor of H. hampei infestation? (2) do gleaner bird species contribute to the control of the pest? and (3) how does shade management affect avian FD? We found that (1) all four FD indices calculated using bird traits were significant predictors of H. hampei differences in infestation rates, (2) richness of gleaning bird species was also a significant predictor of differences in H. hampei infestation rates, and (3) the interaction between month and canopy cover management affects bird FD, however whether this affects delivery of the pest control service remains unclear due to the particular biology of H. hampei . In revealing the connection between avian traits and the removal and potential control of H. hampei , our study highlights the importance of bird diversity persisting in agricultural landscapes, and the necessity of integrating bird conservation to foster healthy production systems. [ABSTRACT FROM AUTHOR]

Pests and diseases are the main yield-reducing factors in simplified agricultural systems. Their role in complex, diverse, agricultural systems may, however, be less apparent because of the many interactions in which they are involved. However, it is essential to understand the relationships between pests and diseases, on the one hand, and ecosystem services (including crop production), on the other, to develop sustainable agroecosystems. Our study aims to illustrate these complex relationships based on the example of coffee agroecosystems in Costa Rica. We analysed a dataset consisting of 107 coffee plots characterized for their topoclimates, soils, coffee plant production characteristics, cropping practices, and pest and disease injuries. Meta-variables were created through cluster analyses to account for these different broad attributes of coffee-based agroecosystems. In particular, coffee injury profiles were determined on the basis of injury levels incurred by pathogens, nematodes, and insects over the course of one growing season. We used correspondence analysis to assess the levels of linkage between injury profiles and other agroecosystem meta-variables. Indicators of biodiversity based on shade diversity and of attainable yield were incorporated in the analysis as additional variables. Four groups of coffee-based agrosystems were identified, ranging from extensive (low-input, perennial polyculture) to intensive (unshaded high-input monoculture). Each group of coffee-based agroecosystem corresponds to varying levels of pest and disease injuries, crop yield, and ecosystem service provision, excluding coffee production. In each group of coffee-based agrosystem, we discussed the drivers of coffee production and explored potential avenues to improve sustainability based on ecosystem services provision. We highlighted that the physical characteristics of the environment, topoclimate and soil characteristics, are the main drivers of injury profiles and of resulting yield losses. Cropping practices and pest and disease management first need to be adapted to these physical characteristics. Where topoclimate and soils favour pest and disease development, potentially leading to heavy yield losses, system diversification can enhance ecosystem service provision, including production of other crops, thus helping to offset low coffee production. Where physical environmental characteristics hamper pests and diseases, increasing ecosystem service provision by incorporating shade trees may be considered, provided that coffee production is not significantly reduced. We conclude that there is an acute need to quantify losses caused by pests and diseases in agroforestry systems, in order to provide a rational basis for growers’ decisions and to better determine the value of economic incentives needed for ecosystem service provision. [ABSTRACT FROM AUTHOR]

The article presents a study on the landscape content of three coffee pathogens and pests such as coffee berry borer (Hypothenemus hampei), root-knot nematode (Meloidogyne), and fungus (Hemileia vastatrix) in 29 areas in Turrialba, Costa Rica. The study applied correlation analysis to examine abundance of coffee borer and coffee proportion in land. Results showed that coffee plots improved the survival of coffee borer and its movements.

The density of colonies of leaf-cutting ants, Atta cephalotes L. (Hymenoptera: Formicidae), was measured and compared among coffee (Coffea arabica L.) plantations in five management categories: monoculture conventional, diversified conventional, diversified organic, highly diversified conventional, and highly diversified organic. Twenty-four small farms (<4 ha) in Turrialba, Costa Rica, were included in this study. Within-farm and off-farm (landscape) variables were measured and tested for their relationship with A. cephalotes colony density. Total ant colony density (colonies per ha) and density of new colonies shortly after a nuptial flight were significantly greater in the coffee monoculture conventional system, compared with all other systems. Total ant colony density and density of new colonies were inversely related to percentage of shade within the farms. Within farms, colony density was greater near edges adjacent to riparian forest than those adjacent to nonforested land. Regardless of edge type, plots closer to the edge (0-30 m) had greater colony density than those furthest from the edge. At the landscape scale, density of new colonies was positively related to fallow land use coverage within a 2,000-m buffer radius and to forest coverage within a 500-m radius. Results indicate that coffee farm management practices and landscape level factors can affect A. cephalotes colony densities. Understanding such practices and factors could assist in the development of better management methods of these injurious insects in coffee farms. Increased diversification in coffee farms, possibly due to the greater shade associated with it, may reduce colonization by the ants, which are considered forest gap specialists. [ABSTRACT FROM AUTHOR]

Abstract: The shade impact by Inga densiflora on water use and drainage in a coffee agroforestry system (AFS) was compared to coffee monoculture (MC) in Costa Rica. Rainfall interception, transpiration, runoff and soil water content were monitored during 3 years. Runoff was lower in AFS than MC (5.4 and 8.4% of total rainfall, respectively) and a higher water infiltration was observed under AFS. Still, the higher combined rainfall interception+transpiration of coffee and shade trees in AFS resulted in a lower drainage than in MC. No coffee water stress was recorded either in AFS or MC as relative extractable soil water remained above 20% during the dry seasons. Time course of soil water content showed enhanced access to soil water between 100 and 200cm depth in AFS. This suggests complementarity for soil water between coffee and shade trees. The model HYDRUS 1D predicted that drainage at 200cm depth accounted for a large fraction of annual rainfall (68% for MC and 62% for AFS). Climatic scenario simulations showed (1) a potential competition for water between coffee and shade trees when the dry season was extended by 4–6 weeks compared to actual, and (2) a severe reduction in annual drainage, but without competition for water when rainfall was reduced down to 40% of the actual. [Copyright &y& Elsevier]

Abstract: Controlling coffee nematodes using fewer pesticides is a priority for most producing countries. The aim of this study was to identify ecological and agricultural factors associated with Meloidogyne exigua and Pratylenchus coffeae sensu lato population densities in coffee roots. The influence of these factors was studied in a two-year survey by characterizing 57 coffee plots in five major producing regions in Costa Rica, where coffee is generally cultivated in intensified systems. Correspondence analyses and Chi-squared automatic interaction detector (CHAID) classification trees were used to identify and classify the ecological and agricultural factors associated with nematode population densities. M. exigua and P. coffeae population densities were opposites with respect to soil characteristics. Low M. exigua population densities were especially found in soils with low sand and high Zn and K contents. The opposite was seen for P. coffeae. In addition, M. exigua and P. coffeae seemed to have different climatic requirements: M. exigua was mainly found at lower altitudes than P. coffeae. Consequently and through possible competition phenomena between P. coffeae and M. exigua, a negative correlation was found between the two nematode population densities on a plot scale. We found only one cropping practice that seemed to affect both nematodes similarly: a within-row distance between coffee trees of less than 0.9m was associated with large M. exigua and P. coffeae population densities. The results of this study provide further evidence of the greater intensity of pest and disease attacks in intensified coffee systems. [Copyright &y& Elsevier]

The impact of Erythrina poeppigiana on soil characteristics, at three different positions relative to the shade tree and from three different soil depths, was evaluated in pairs of comparable Costa Rican coffee farms (organic and conventional) in 2000 and 2004. In the conventional system at 0–5 cm, higher C and N concentrations were found close to the shade tree versus the positions 2 m from the trunk (5.04 vs. 4.18%). This positive effect could influence only 20% of the farm area when high population of E. poeppigiana were used. This finding highlighted the importance of E. poeppigiana in maintaining SOM levels. In contrast, the organic system showed similar C and N concentrations for all positions probably due to an even distribution of pruning residues and to the use of organic amendments. A trend to higher total C and N concentrations for organic farms in comparison to conventional farms was found. No significant temporal changes in soil C or N concentrations were found between 2000 and 2004. [ABSTRACT FROM AUTHOR]

We monitored the development of American leaf spot of coffee, a disease caused by the gemmiferous fungus Mycena citricolor, in 57 plots in Costa Rica for 1 or 2 years in order to gain a clearer understanding of conditions conducive to the disease and improve its control. During the investigation, characteristics of the coffee trees, crop management, and the environment were recorded. For the analyses, we used partial least-squares regression via the spline functions (PLSS), which is a nonlinear extension to partial least-squares regression (PLS). The fungus developed well in areas located between ≈1100 and 1,550 m above sea level. Slopes were conducive to its development, but eastern-facing slopes were less affected than the others, probably because they were more exposed to sunlight, especially in the rainy season. The distance between planting rows, the shade percentage, coffee tree height, the type of shade, and the pruning system explained disease intensity due to their effects on coffee tree shading and, possibly, on the humidity conditions in the plot. Forest trees and fruit trees intercropped with coffee provided particularly propitious conditions. Apparently, fertilization was unfavorable for the disease, probably due to dilution phenomena associated with faster coffee tree growth. Finally, series of wet spells interspersed with dry spells, which were frequent in the middle of the rainy season, were critical for the disease, probably because they affected the production and release of gemmae and their viability. These results could be used to draw up a map of epidemic risks taking topographical factors into account. To reduce those risks and improve chemical control, our results suggested that farmers should space planting rows further apart, maintain light shading in the plantation, and prune their coffee trees. [ABSTRACT FROM AUTHOR]

Following the coffee price crisis in the early 1990s until today and its impacts on the economy of coffee-exporting countries, specialty and niche marketing possibilities were explored. Moreover, many producers in Latin America have attempted to diversify their farms and products to decrease economic dependence on one cash crop, as shade trees are now propagated in coffee plantations to increase sustainability of coffee production and quality. Therefore, trees are being widely established, thus creating agroforestiy systems, The canopy layer usually includes timber, service or fruit trees, or a combination of these. In January and February 2005, interviews with 30 organic coffee producers in Turrialba (Costa Rica) were carried out. Objectives of the survey were to characterize species, volume and production of fruit trees present in coffee fields, to assess the farmers' incentive for establishing fruit trees within their coffee-production system, and to determine the perceived impact of those fruit trees on coffee. The farmers who participated in the survey had a highly diverse production of fruits in their coffee agroforestry systems. Higher quantities of fruits are being produced for a few products with secure markets (e.g., banana, citrus, plantain, and guava), regardless of their impact on coffee production. The other fruits were used mainly in household consumption. Diversification of the farm was generally seen as an economic benefit (higher income and better security), although environmental effects were also perceived. Following this reasoning, finding accessible markets for less common products may be crucial for sustaining and promoting higher diverse production systems. [ABSTRACT FROM AUTHOR]

1 In Mesoamerica, shade trees are often included within coffee ( Coffea arabica) agroforestry systems. Shade trees potentially protect the main crop by increasing vegetational diversity and reducing insect herbivory through one or more mechanisms. 2 The effect of on-farm vegetational diversity on harvesting of coffee leaves by the leaf-cutting ant, Atta cephalotes L., was examined on 15 coffee farms varying in vegetational diversity near Turrialba, Costa Rica. The farms ranged from coffee monocultures to complex-shade coffee systems with three or more tree species present. The vegetational diversity of each farm was quantified using a leaf area index. 3 The species composition and biomass of the plant material being carried into colonies by ants was collected, identified to species, and its biomass was quantified four times during one year for at least two colonies in each of the 15 farms. 4 The proportion of plant biomass that was coffee being retrieved by A. cephalotes differed significantly among farm management types, and was highest (40%) in monocultures and lowest (< 1%) in farms with complex shade. Coffee was always harvested in a lower proportion than predicted based upon its relative abundance on the farms. 5 In dual-choice bioassays with laboratory colonies, A. cephalotes significantly preferred the leaves of the predominant shade tree species on the farms, poró ( Erythrina poeppigiana) over coffee. 6 The results indicate risk of injury by A. cephalotes can be reduced in vegetationally diverse coffee agroecosystems due at least in part to a foraging preference by the ants for plants other than coffee. [ABSTRACT FROM AUTHOR]

The distribution of the plant-parasitic nematodes Pratylenchus coffeae sensu lato and Meloidogyne spp. were studied in two plots, one in Guatemala ( P. coffeae and M. paranaensis) and the other in Costa Rica ( P. coffeae and M. exigua). The quantity of nematodes per g fresh weight root were counted for each coffee tree sampled. The distributions were aggregated, and generally fitted well to negative binomial distributions. Population aggregation was greater when a smaller number of nematodes were involved, suggesting that initial colonization develops in foci. Analyses of the relationships between population levels of the species suggested that there was competition between Pratylenchus coffeae and Meloidogyne spp. This competition was expressed differently depending on the relative population density of the different species. [ABSTRACT FROM AUTHOR]

The coffee disease complex known as corky-root, composed of the root-knot nematode Meloidogyne arabicida and Fusarium oxysporum, causes serious damage to Coffea arabica in Costa Rica. Resistance to Meloidogyne arabicida alone and to the field population (M. arabicida, M. exigua, F. oxysporum) was evaluated under controlled and field conditions. The studied material consisted of subspontaneous-derived C. arabica accessions, C. canephora accessions, introgression lines derived from the interspecific Timor Hybrid (C. arabica×C. canephora) and F1 hybrids from crosses between subspontaneous-derived accessions and cultivars. Accessions resistant to M. arabicida and to the field population were identified at varying frequencies in the different groups of study materials. The results showed that resistance to corky-root is heritable and that genetic resistance to M. arabicida is an effective strategy against corky-root disease. By using C. canephora rootstocks, it was possible to substantially reduce mortality in the field and reduce by half the number of plants with corky-root symptoms. The results were used to define appropriate strategies for the sustainable management of coffee corky-root disease resistance. [Copyright &y& Elsevier]

Coffee leaf rust is a polycyclic disease that causes severe epidemics impacting yield over several years. For this reason, since the 1960s, more than 20 models have been developed to predict different indicators of the disease's development and help manage it. In existing models, standardized periods of influence of the meteorological predictors of the disease are determined a priori, based on strong assumptions. However, the appearance of a symptom or sign can be influenced by complex combinations of meteorological variables acting at different times and for different durations. In our study, we monitored a total of 5400 coffee leaves during a year and a half, in different agroforestry systems, in order to detect the onset dates of the disease symptoms, such as lesion emergence, and signs, such as sporulation and infectious area increase. In these agroforestry systems, we also recorded microclimate. We statistically identified the complex combinations of microclimatic variables responsible for changes in lesion status to construct three models predicting lesion emergence probability, lesion sporulation probability and growth of its infectious area. Our method allowed the identification of different microclimatic variables that fit well with the knowledge about the coffee leaf rust biology. Minimum air temperature from 20 to 18 days before a lesion emergence explained the status change from healthy to emergence of visible lesion, possibly because the short germination phase is stimulated by low temperatures. We also found a unimodal effect of rainfall over a period of 10 days, 33 days before lesion emergence, with a maximum at 10 mm. Below this threshold, uredospore dispersal is efficient, increasing the lesion appearance probability; above this threshold, wash-off effects on uredospores probably occurs, decreasing the probability of lesion emergence. In addition, we identified microclimatic variables whose influence on coffee leaf rust had not been described before. These variables are likely to be involved in the internal development phases of the disease in the coffee leaves: (1) unimodal effects of maximum air temperature in different periods on sporulation and infectious area growth (2) positive and unimodal effects of rainfall in different periods on sporulation and (3) a negative effect of leaf thermal amplitude in different periods on lesion emergence, sporulation and infectious area growth. Although these models do not provide predictors of the level of disease attack, such as incidence, they provide valuable information for warning systems and for mechanistic model development. These models could also be used to forecast risks of infection, sporulation and infectious area growth and help optimize treatment recommendations. • Microclimate is a main predictor of the development of coffee leaf rust (CLR). • Forecasting risks of CLR lesion emergence, sporulation and infectious area growth enables specific control recommendations. • Asynchronous microclimate windows are responsible for the onset of CLR symptoms and signs. • Pathogen inoculum size and productive coffee plants status are also important CLR development predictors. [ABSTRACT FROM AUTHOR]

The DynACof model was designed to model coffee agroforestry systems and study the trade-offs to e.g. optimize the system facing climate changes. The model simulates net primary productivity (NPP), growth, yield, mortality, energy and water balance of coffee agroforestry systems according to shade tree species and management. Several plot-scale ecosystem services are simulated by the model, such as production, canopy cooling effect, or potential C sequestration. DynACof uses metamodels derived from a detailed 3D process-based model (MAESPA) to account for complex spatial effects, while running fast. It also includes a coffee flower bud and fruit cohort module to better distribute fruit carbon demand over the year, a key feature to obtain a realistic competition between sinks. The model was parameterized and evaluated using a highly comprehensive database on a coffee agroforestry experimental site in Costa Rica. The fluxes simulated by the model were close to the measurements over a 5-year period (nRMSE = 26.27 for gross primary productivity; 28.22 for actual evapo-transpiration, 53.91 for sensible heat flux and 15.26 for net radiation), and DynACof satisfactorily simulated the yield, NPP, mortality and carbon stock for each coffee organ type over a 35-year rotation. Image 1 • DynACof simulates NPP, carbon allocation, growth, yield, energy and water balance. • It accounts for spatial effects using metamodels from the 3D process-based MAESPA. • Leaf and air temperature inside the canopy are computed to control plant growth. • It successfully simulated the fluxes (energy, water, carbon), growth and yield. • DynACof can be used to optimize coffee AFS, e.g. facing climate changes. [ABSTRACT FROM AUTHOR]