Functional redundancy of weed seed predation is reduced by intensified agriculture.

Intensified agriculture, a driver of biodiversity loss, can diminish ecosystem functions and their stability. Biodiversity can increase functional redundancy and is expected to stabilize ecosystem functions. Few studies, however, have explored how agricultural intensity affects functional redundancy and its link with ecosystem function stability. Here, within a continental-wide study, we assess how functional redundancy of seed predation is affected by agricultural intensity and landscape simplification. By combining carabid abundances with molecular gut content data, functional redundancy of seed predation was quantified for 65 weed genera across 60 fields in four European countries. Across weed genera, functional redundancy was reduced with high field management intensity and simplified crop rotations. Moreover, functional redundancy increased the spatial stability of weed seed predation at the field scale. We found that ecosystem functions are vulnerable to disturbances in intensively managed agroecosystems, providing empirical evidence of the importance of biodiversity for stable ecosystem functions across space.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

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.