Influence of spatial scale on landscape effects important to arthropod management

The development and expansion of effcient spatial technologies and geostatistical analysis capabilities over the last few decades has enabled a dramatic increase in spatial landscape research. The knowledge gained from this research in large-scale agroecosystems impacts implementation of integrated pest management (IPM) programs across four spatial scales: (i) intrafeld, (ii) local landscape, (iii) regional, and (iv) continental. Understanding the variability and interactions across these agroecological landscape scales can increase management options to encompass wider impacts from mobile pest and benefcial insects. IPM programs implemented by farmers and other managers have largely been applied uniformly at the feld level. However, management of pest insects with clear and predictable intrafeld spatial distributions may become more effcient through site-specifc applications. The makeup of local landscapes surrounding felds directly affects the dynamics of feld populations of pests, natural enemies, and pollinators, and this impact will expand considerations for managing local landscapes. Beyond the local landscape (i.e. regional landscape), longer range movement by pests and natural enemies and their interactions with crop and non-crop habitats can dramatically infuence pest risk potential, natural enemy prevalence, and management itself. Finally, continental-scale migration of pests can contribute signifcantly to risk assessment important for IPM program development and implementation. Case studies are presented illustrating the incorporation of improved spatial understanding into the development and implementation of IPM programs. Increasingly, sustainability of large-scale crop production systems will be enhanced by farm-level IPM decisions that account for local, regional, and continental landscape interactions. The success of future IPM programs will depend on better understanding these broader ecological interactions to enhance the prediction of agroecosystem services across all spatial scales and increase overall effectiveness of landscape services and economic and environmental resilience.