Reducing ecological complexity using the archetype approach - an application to natural pest control

Complexity and context-dependence in ecological and socioecological phenomena often cause inconsistent or seemingly idiosyncratic responses. This apparent lack of generality presents a challenge to the implementation of ecological principles in environmental management. We mostly rely for prediction on data-hungry correlative models that offer little mechanistic understanding. The alternative of process-based modelling is knowledge-intensive and has limited applicability across systems, due to a trade-off between generality and realism. Here, we present an archetype approach, combining trait-mediated mechanistic understanding into ecological models of intermediate generality, as a way to overcome these limitations. We demonstrate its potential in the case of natural pest control across crop-pest-enemy systems. After reviewing the current modelling approaches and their shortcomings, we show that similar responses of natural pest control in cases that share key characteristics indicate the potential for context-sensitive generalizations. Example archetypes show great promise for improved understanding and prediction. We outline how statistical analysis of available data and rule sets for model development will allow systematic definition of archetypes representing the key processes of all major crop-pest-enemy systems of the world. In this and other applied cases, the use of archetype approaches is a major step forward in facilitating both scientific synthesis and uptake of ecological knowledge in environmental management. Archetype approaches can enhance the application of ecological principles not only to crop pest control, but also to the management of a wide range of natural resources that have been affected by fragmentation of ecological research.