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. (Résumé d'auteur

Shade trees: a determinant to the relative success of organic versus conventional coffee production

Greater understanding of the influences on long-term coffee productivity are needed to develop systems that are profitable, while maximizing ecosystem services and lowering negative environmental impacts. We examine a long-term experiment (15 years) established in Costa Rica in 2000 and compare intensive conventional (IC) coffee production under full sun with 19 agroforestry systems combining timber and service tree species with contrasting characteristics, with conventional and organic managements of different intensities. We assessed productivity through coffee yield and coffee morphological characteristics. IC had the highest productivity but had the highest yield bienniality; in the agroforestry systems productivity was similar for moderate conventional (MC) and intensive organic (IO) treatments (yield 5.3 vs 5.0 t/ha/year). Significantly lower yields were observed under shade than full sun, but coffee morphology was similar. Low input organic production (LO) declined to zero under the shade of the non-legume timber tree Terminalia amazonia but when legume tree species were chosen (Erythrina poepiggiana, Chloroleucon eurycyclum) LO coffee yield was not significantly different than for IO. For the first 6 years, coffee yield was higher under the shade of timber trees (Chloroleucon and Terminalia), while in the subsequent 7 years, Erythrina systems were more productive, presumably this is due to lower shade covers. If IC full sun plantations are not affordable or desired in the future, organic production is an interesting alternative with similar productivity to MC management and in LO systems incorporation of legume tree species is shown to be essential

Impact of agro-forestry systems on the aroma generation of coffee beans

A long experiment has been established since 2000 at CATIE (Tropical Agricultural Research and Higher Education Center), Turrialba, Costa Rica. Twenty agro-forestry systems with different shade types and managements (organic and non-organic) consisting of an incomplete randomized block-design with shade tree as main effect and subplots represented by management were set up. The effects of different managements and shade types on the aroma and color generation of roasted coffee beans were investigated. The total protein content was significantly higher (P < 0.05) under the intensive conventional (IC) (168 g/Kg) and intensive organic (IO) (167 g/Kg) managements than under the moderate conventional (MC) (153 g/Kg in IC vs. MC group, 157 g/Kg in MC vs. IO group). Comparing with the moderate conventional (MC) management, the intensive organic (IO) management had a stronger ability to generate more flavor and color. The total protein content was significantly higher (P < 0.05) under the full sun system (172 g/Kg) than under the shaded (159 g/Kg) and Erythrina system (155 g/Kg), under the service system (165 g/Kg) than under the timber system (146 g/Kg), under the legume timber system (170 g/Kg) than under the non-legume timber system (152 g/Kg). The full sun system had a greater flavor generation and color after roasting. Comparing with the timber system, the service system produced roasted beans with the more flavor and color. Comparing with the non-legume shade tree, the legume shade tree improved the performance of flavor and color in the roasted coffee beans

Assessing the accuracy and robustness of a process-based model for coffee agroforestry systems in Central America

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 https://doi.org/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