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Despite many years of research, there is still a lack of consensus as to the nature of the relationship between shade trees and agronomic intensification in coffee agroforestry systems. While some studies find unshaded intensively managed coffee is the most productive, other studies find no trade-off between shade characteristics and productivity. Our study of 179 farms from the main coffee growing regions of Costa Rica and Guatemala analyzed how shade affected the productive response of coffee to intensification of agronomic management. Four levels of coffee productivity were differentiated for each country associated with three levels of shade development in Costa Rica and two levels in Guatemala. The highest coffee productivity group was associated with medium shade development in both countries. High shade groups had low productivity, but very low productivity groups were associated with low (Costa Rica) or medium (Guatemala) shade. Medium and high productivity farms were associated with high elevation, lower rainfall and regions with higher coffee prices. Yields with a moderate level of investment (720–1,500 USD−1) and with medium shade (LAI 0.55-1.1) were not significantly different from yields with higher investment or lower shade levels. The increase in yields with increasing N fertilizer application were similar under low, medium and high LAI, but the mean productivity significantly lower with high LAI. Agronomic intensification to increase productivity is equally effective for low and medium shade systems (LAI

Introducción. El manejo de árboles de sombra en un sistema de producción se considera una práctica de adaptación basada en ecosistemas capaz de proveer múltiples servicios ecosistémicos. Objetivo. Contribuir al entendimiento de los efectos de los árboles en cafetales sobre servicios ecosistémicos de aprovisionamiento y regulación, y cómo el análisis de relaciones entre servicios puede contribuir a mejorar el diseño y manejo de estos sistemas. Desarrollo. El estudio se realizó entre julio y octubre de 2017. Los árboles de sombra tienen un efecto sobre el rendimiento de café, atribuido a su influencia en la regulación de la carga fructífera. Este efecto puede tener resultados positivos con un manejo agroforestal adecuado, pues reduciría fluctuaciones bienales extremas de la producción de café. Los árboles también regulan el clima dentro del cafetal (microclima), además, tienen efectos positivos sobre la fertilidad del suelo, la cantidad de materia orgánica, el reciclaje de nutrientes, disminuyen la evaporación del suelo, reducen la erosión y secuestran carbono. Sin embargo, hay algunos aspectos que aún siguen siendo complejos y a veces contradictorios. En general, la documentación de los aspectos positivos de los árboles sobre servicios de aprovisionamiento y regulación son mayores que los negativos. Conclusión. Esta revisión evidencia un efecto de los árboles de sombra sobre los servicios ecosistémicos. El conocimiento de dichos efectos, con base en el interés y expectativas de los sistemas sociales, debe ser complementado con análisis de relaciones entre servicios con miras a identificar mejores prácticas agroforestales o sistemas modelo capaces de proveer varios servicios simultáneamente.

The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013-2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

Abstract Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local‐scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – https://www.nhm.ac.uk/our-science/our-work/biodiversity/predicts.html). We make site‐level summary data available alongside this article. The full database will be publicly available in 2015.