From a local descriptive to a generic predictive model of cereal aphid regulation by predators.

The temporal dynamics of insect populations in agroecosystems are influenced by numerous biotic and abiotic interactions, including trophic interactions in complex food webs. Predicting the regulation of herbivorous insect pests by arthropod predators and parasitoids would allow for rendering crop production less dependent on chemical pesticides. Curtsdotter et al. (2019) developed a food-web model simulating the influences of naturally occurring arthropod predators on aphid population dynamics in cereal crop fields. The use of an allometric hypothesis based on the relative body masses of the prey and various predator guilds reduced the number of estimated parameters to just five, albeit field-specific. Here, we extend this model and test its applicability and predictive capacity. We first parameterized the original model with a dataset with the dynamic arthropod community compositions in 54 fields in six regions in France. We then integrated three additional biological functions to the model: parasitism, aphid carrying capacity and suboptimal high temperatures that reduce aphid growth rates. We developed a multi-field calibration approach to estimate a single set of generic allometric parameters for a given group of fields, which would increase model generality needed for predictions. The original and revised models, when using field-specific parameterization, achieved quantitatively good fits to observed aphid population dynamics for 59% and 53% of the fields, respectively, with pseudo-R2 up to 0.99. But the multi-field calibration showed that increased model generality came at the cost of reduced model reliability (goodness-of-fit). Our study highlights the need to further improve our understanding of how body size and other traits affect trophic interactions in food webs. It also points up the need to acquire high-resolution data to use this type of modelling approach. We propose that a hypothesis-driven strategy of model improvement based on the integration of additional biological functions and additional functional traits beyond body size (e.g., predator space search or prey defences) into the food-web matrix can improve model reliability.

Towards Predictions of Interaction Dynamics between Cereal Aphids and Their Natural Enemies: A Review.

(1) Although most past studies are based on static analyses of the pest regulation drivers, evidence shows that a greater focus on the temporal dynamics of these interactions is urgently required to develop more efficient strategies. (2) Focusing on aphids, we systematically reviewed (i) empirical knowledge on the drivers influencing the dynamics of aphid-natural enemy interactions and (ii) models developed to simulate temporal or spatio-temporal aphid dynamics. (3) Reviewed studies mainly focus on the abundance dynamics of aphids and their natural enemies, and on aphid population growth rates. The dynamics of parasitism and predation are rarely measured empirically, although it is often represented in models. Temperature is mostly positively correlated with aphid population growth rates. Plant phenology and landscape effects are poorly represented in models. (4) We propose a research agenda to progress towards models and empirical knowledge usable to design effective CBC strategies. We claim that crossover works between empirical and modeling community will help design new empirical settings based on simulation results and build more accurate and robust models integrating more key drivers of aphid dynamics. Such models, turned into decision support systems, are urgently needed by farmers and advisors in order to design effective integrated pest management.