Most landscapes, including agricultural ones, are composed of a mosaic of favorable, sub-optimal and lethal thermal habitats which directly influences the performance of ectotherms such as insect pest. To better manage crop pest populations in the context of climate change, it is necessary to measure thermal heterogeneity at a fine, ecologically relevant, scale.
If the future demand of 9 billions people is to be met, food production must virtually double by the year 2050. One potential approach of meeting this demand is the control of crop pests, which globally consume the amount of food sufficient to feed more than 1 billion people. In the context of improving pest management methods, the objective of our project is to better understand and model the thermal environment of crop pest, a key factor explaining their performance and damages to crops.
The thermal mapping of agricultural landscapes is a key step to understand crop pest response to temperature conditions in the micro-environments they live in. Temperature measurements are performed along elevational gradients (2500-4500 m) by combining automatic temperature loggers and a high resolution thermal camera mounted on a drone. Crop pest abundance is quantified using pheromone traps, in collaboration with local farmers.
Based on hundreds of temperature measurements made in Ecuadorian agricultural landscapes and analyzed through Fourier transforms and geostatistics, our first results show very strong discrepancies between temperature interpolations of global climatic models and field measurement, in micro-environment where insects live.
Our first results highlight the need to integrate the thermal heterogeneity of agricultural landscapes into models of crop pest population dynamic and management.
Faye E, Herrera M, Bellomo L, Silvain JF, Dangles O (in prep) Strong discrepancies between operative temperature mapping and interpolated climatic units in agricultural landscapes.
This study shows that caution is needed when using global climatic s
As climate changes rapidly at both regional and global scales, agro-ecosystem users are faced with the challenge of developing new strategies to manage pests in an uncertain and changing world. Conventional pest management often seeks to maintain agro-ecosystems in a steady state by perpetuating current desired crop management conditions to face pest problems. This approach is quite efficient in addressing short-term variability or when conditions are either relatively constant or change in a predictable fashion. However, under conditions of rapid directional social-ecological changes, new conditions emerge for which steady-state pest management is no longer adequate. Under these conditions, adaptive management (AM), "a systematic process for continually improving management policies and practices by learning from the outcomes of previously employed policies and practices", provides mechanisms to adjust to change and uncertainty.
Worldwide, uncertainty related to temperature heterogeneity, variability, and extremes (which are all predicted to increase in the context of climate change), is a key obstacle to the development of efficient ectotherm pest control strategies. Our project proposes to address this issue by developing a multi-model based framework of adaptive management in pest control in the context of climate change and variability. This framework will integrate three main types of thermal uncertainties: 1) uncertainty about the environment, 2) uncertainty about the underlying behavior of the system, and 3) uncertainty about the observation and decision made on the managed system. To face these challenges, our project proposes 1) to improve our knowledge of thermal heterogeneity in agricultural landscapes, 2) to develop more accurate temperature-related insect population dynamics modeling, and 3) to integrate the concept of AM in pest control. We will apply our general framework to the case of the potato moth (Phthorimaea operculella) in the Bolivian highlands. Potato moth is one of the major pest problems worldwide and the Bolivian highlands one of the regions where the effect of global warming are expected to be the greatest due to high altitude and proximity to equator. This region is also characterized by high poverty, high climatic variability and thermal uncertainty, rapid changes in land use, and a mosaic of agro-ecosystems at the landscape level. While developed under specific conditions, the outputs of our project are expected to have a broader relevance into the fields of global change ecology, population dynamic modeling, pest control, and adaptive resource management.
Our project will combine several fields of research that have emerged independently during the last decade to face the challenge of predicting responses and adaptation of social and ecological systems to global changes: the ecology of thermal landscapes, the development of variable temperature-dependent population dynamics, and the concept of adaptive management in pest control. All these fields are in their early-development phase, boosted by recent technological advances in terms of broad-scale temperature metrology (thermo-radiography) and computational power (individual-based models, cellular automata, agent-based models) which will all be used in our project. Moreover, the project will gather into the same research framework scientists, resource managers, and farmers, so that a truly integrated approach of pest management in an uncertain world could emerge.
Monsieur Olivier DANGLES (UR 072 - Diversité, Ecologie et Évolution des Insectes Tropicaux) – firstname.lastname@example.org
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IRD UR 072 - Diversité, Ecologie et Évolution des Insectes Tropicaux
Help of the ANR 220,000 euros
Beginning and duration of the scientific project: December 2012 - 48 Months