Abstract
Spatial ecology includes research into factors responsible for observed distribution patterns of organisms. Moreover, the spatial distribution of an animal at a given spatial scale and in a given landscape may provide valuable insight into its host preference, fitness, evolutionary adaptation potential, and response to resource limitations. In agro-ecology, in-depth understanding of spatial distributions of insects is of particular importance when the goals are to (1) promote establishment and persistence of certain food webs, (2) maximize performance of pollinators and natural enemies, and (3) develop precision-targeted monitoring and detection of emerging outbreaks of herbivorous pests. In this article, we review and discuss a spatial phenomenon that is widespread among insect species across agricultural systems and across spatial scales—they tend to show “edge-biased distributions” (spatial distribution patterns show distinct “edge effects”). In the conservation and biodiversity literature, this phenomenon has been studied and reviewed intensively in the context of how landscape fragmentation affects species diversity. However, possible explanations of, and also implications of, edge-biased distributions of insects in agricultural systems have not received the same attention. Our review suggests that (1) mathematical modeling approaches can partially explain edge-biased distributions and (2) abiotic factors, crop vegetation traits, and environmental parameters are factors that are likely responsible for this phenomenon. However, we argue that more research, especially experimental research, is needed to increase the current understanding of how and why edge-biased distributions of insects are so widespread. We argue that the fact that many insect pests show edge-biased distribution patterns may be used to optimize both pest monitoring practices and precision targeting of pesticide applications and releases of natural enemies.
Highlights
Altamirano et al (2016) showed that the spatial distribution of galling insects sampled at transects in nine forests in Central Argentina were most predominant along forest edges and that many species benefitted from unspecified forest edge conditions
We discuss the following two questions: (1) What are the potential mechanisms responsible for an edge-biased distribution of insect populations in agricultural systems? (2) How can increased knowledge about edgebiased distributions and their governing mechanisms help to enhance the efficiency of agricultural pest management practices?
Liebhold and Tobin (2008) argue that the relevance of simple diffusion models to predict spatial distributions of insects is limited to small spatial scales and fails to account for greater rate of diffusion at large spatial scales
Summary
2.1 Edge-biased distributions in open field systems 2.2 Edge-biased distributions in orchard systems 2.3 Edge-biased distributions in stored-product systems 2.4 Edge-biased distributions in small-scale laboratory experiments. 3. Theoretical models of edge-biased insect distributions 3.1 Simple diffusion model 3.2 Stratified diffusion model 3.3 Influential edge models. 4. Potential driving factors of edge-biased distributions 4.1 Mobility altering factors 4.1.1 Wind patterns 4.1.2 Microclimate 4.1.3 Terrain property 4.2 Vegetational factors contributing to edge-biased distributions 4.2.1 Vegetation heterogeneity 4.2.2 Plant quality. 5. Potential applications of edge-biased distributions into insect monitoring and pest management
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