Thermal Tolerance of the Coffee Berry Borer Hypothenemus hampei: Predictions of Climate Change Impact on a Tropical Insect Pest

Coffee is predicted to be severely affected by climate change. We determined the thermal tolerance of the coffee berry borer , Hypothenemus hampei, the most devastating pest of coffee worldwide, and make inferences on the possible effects of climate change using climatic data from Colombia, Kenya, Tanzania, and Ethiopia. For this, the effect of eight temperature regimes (15, 20, 23, 25, 27, 30, 33 and 35°C) on the bionomics of H. hampei was studied. Successful egg to adult development occurred between 20–30°C. Using linear regression and a modified Logan model, the lower and upper thresholds for development were estimated at 14.9 and 32°C, respectively. In Kenya and Colombia, the number of pest generations per year was considerably and positively correlated with the warming tolerance. Analysing 32 years of climatic data from Jimma (Ethiopia) revealed that before 1984 it was too cold for H. hampei to complete even one generation per year, but thereafter, because of rising temperatures in the area, 1–2 generations per year/coffee season could be completed. Calculated data on warming tolerance and thermal safety margins of H. hampei for the three East African locations showed considerably high variability compared to the Colombian site. The model indicates that for every 1°C rise in thermal optimum (Topt.), the maximum intrinsic rate of increase (rmax) will increase by an average of 8.5%. The effects of climate change on the further range of H. hampei distribution and possible adaption strategies are discussed. Abstracts in Spanish and French are provided as supplementary material Abstract S1 and Abstract S2

Carbon allocation in fruit trees: from theory to modelling

International audienceCarbon allocation within a plant depends on complex rules linking source organs (mainly shoots) and sink organs (mainly roots and fruits). The complexity of these rules comes from both regulations and interactions between various plant processes involving carbon. This paper presents these regulations and interactions, and analyses how agricultural management can influence them. Ecophysiological models of carbon production and allocation are good tools for such analyses. The fundamental bases of these models are first presented, focusing on their underlying processes and concepts. Different approaches are used for modelling carbon economy. They are classified as empirical, teleonomic, driven by source–sink relationships, or based on transport and chemical/biochemical conversion concepts. These four approaches are presented with a particular emphasis on the regulations and interactions between organs and between processes. The role of plant architecture in carbon partitioning is also discussed and the interest of coupling plant architecture models with carbon allocatio

Coffee agroforestry systems in Central America: I. A review of quantitative information on physiological and ecological processes

Coffee is widely grown across Central America at altitudes between 600 and 2500 m, mostly in association with trees that provide shade and other services. Research on coffee agroforestry systems has identified many environmental factors, management strategies and plant characteristics that affect growth, yield and environmental impact of the system. Much of this literature only presents qualitative estimates of the importance of the different growth determining factors, or highly site-specific estimates. Quantitative information is required to allow statistical analysis or the construction of process-based models of the system. Here, we review the available quantitative information for the latter purpose, with emphasis on the data needs for modelling agroforestry systems common in Central America. Process-based models require environmental data—weather, soil—and data on the physiological characteristics of the coffee plants and trees. Our review showed that the current literature is insufficient to allow full parameterisation of a process-based model for any coffee-tree combination. Information on weather, coffee and trees is highly limited, but soil information seems more adequate. A regional network of replicated multi-factorial experiments, focusing on the interactive effects of different environmental factors, may help address the main knowledge gaps