As evidence of the effectiveness of natural insect pest control strategies mounts, there is global interest in implementing sustainable agriculture methods to complement or replace less sustainable pest control practices like pesticide use. Promoting the adoption of natural pest control strategies depends in part on knowing where they will be most effective, but making these predictions remains a challenge for ecologists. A new study by an international team of scientists in the journal Ecological Applications suggests archetype models—models developed based on ecological theory and recurring patterns in the systems being modeled—could help ecologists in their efforts to predict pest control services across landscapes.
The ability to promote natural pest control through plant diversity and beneficial insects that prey on insect pests (i.e., natural enemies) is influenced not only by local land management practices, but also by broader land-use patterns surrounding a farm. For example, the performance of a natural pest control strategy implemented in farms surrounded by old growth forests could be substantially better or worse when implemented in similar farms surrounded by intensively cultivated agricultural fields. This suggests that landscapes could theoretically be designed to enhance natural pest control services. However, in practice the relationship between pest suppression services and landscapes is hard to pin down. Previous observational studies show that pest suppression and crop yields are strongly context dependent, making it hard for researchers to predict where natural pest control strategies are likely to provide the greatest benefit.
Ecological modelers have sought to address this challenge by evaluating natural pest control systems through mechanistic models that quantify interactions between different players (e.g., insect pests or natural enemies) in the system. While mechanistic models have offered many insights in classical biological control research, ecologists modeling complex natural pest control systems face fundamental trade-offs. A previous review article by first author Nikos Alexandridis of Lund University and colleagues published in the journal Biological Control in 2021 showed that the complexity and context dependency of agroecological systems makes it hard to predict interactions between plants, pests, and natural enemies, and that mechanistic models must often sacrifice generality for realism or vice versa.
As Alexandridis describes, “Faced with the difficult challenge of predicting the behavior of natural systems under strong human influence, ecologists typically have to choose between how many systems they model and how accurately they model them.” This means existing natural pest control models are usually either too specific to be applied across different landscape types or too broad to inform actionable management recommendations.
The new study in Ecological Applications suggests this challenge could be overcome by combining knowledge and data from correlative studies of insect traits with causal relationships derived from ecological theory. To bridge these contrasting approaches, the authors adapt the concept of archetypes, or ‘context-specific generalizations,’ from sustainability science.
“This emerging field faces similar challenges of complexity and context dependency, pushing research towards either grand theories of limited applicability or case-specific explanations. Archetypes lie between these two extremes, relying on recurring patterns to provide explanations of intermediate generality, akin to middle range theories in sociology,” Alexandridis explains.
The objective of this study was to apply an archetype approach to identify recurring patterns in natural pest control that could be applied to major agroecosystem types worldwide. For example, while there may not be a consistent relationship between landscape composition and natural pest control broadly speaking, the authors suggest that grouping insects and their natural enemies according to their life-history traits could elicit a more predictable response to certain landscape characteristics. As they explain, organisms from different systems often respond similarly to changes in land-use when they are grouped by specific characteristics such as their dietary or dispersal traits. Developing archetypes by defining groups of insects that share such traits could allow researchers to represent natural pest control in diverse agroecosystems that share key characteristics.
The authors provide proof of concept for such an approach by developing two crop-pest-enemy archetype models describing two groups of pests and their associated natural enemy complexes with different habitat preferences: one model describes a resident pest that stays in the crop field year-round, and another describes a transient crop pest that moves to non-crop habitats for part of the year. They then test the models’ ability to reproduce observations of natural pest control in response to changes in landscape composition and configuration in Europe.
The study found that differences regarding the pests’ overwintering traits (i.e., resident versus transient pests) yielded strikingly different predicted responses to land-use gradients. Predicted responses were also in line with the patterns observed in crop fields for these species across Europe. These results indicate the potential for archetype models to not only resolve inconsistencies in observed patterns of natural pest control, but also to generate strong predictions about important applied outcomes such as avoided pest damage or increased crop yield, which are often difficult to accurately measure across different agroecosystems.
Overall, the authors demonstrate the potential for archetype models to explain apparently contradictory responses of natural pest control to the same management strategies. These models could serve as the building blocks to upscale natural pest control models across agroecosystems that comprise a mosaic of crops hosting different pests and natural enemies. Co-senior author with Yann Clough of Lund University, Emily Poppenborg Martin of Leibniz University Hannover explains, “Finding simple but accurate ways to model and predict natural pest control services in crops is a major challenge we are just beginning to address, despite its crucial importance for our ability to transition agriculture towards sustainability. Archetype models of pest control are a key step in this direction—and here we demonstrate that they can indeed work to make predictions and simulate impacts of agricultural landscape management worldwide.”
