The shelter capability of artificial windbreaks is also influenced by their permeability

An accumulation of insect pest near windbreaks is more evident in windy weather as compared to calm weather conditions . Higher permeability of artificial windbreaks leads to higher wind speed in the leeward side, lower sheltering effects for insect pests, and lower insect pest density near the artificial windbreaks . Furthermore, higher windbreak permeability also shifts the positions of the highest insect pest density further away from the windbreak. Instead of maximal insect pest density at one wind break height for 0% permeable windbreak, the highest density was observed at distance equivalent to 2 to 3 windbreak height for thrips , aphids , fungus gnats , and gall midges . Besides artificial windbreaks, natural hedgerows also exert similar effects on insect pest distribution . In another experiment, using trace of rubidium element to mark egg parasitoids in the genus Aragus overwintering in French prune trees, Corbett and Rosenheim showed that the peak in Aragus density did not coincide with the original points of dispersal but some distance downwind, displaying certain degree of windbreak effect. Therefore, it can be inferred from these studies that the wake zone, which, in this case, can be considered as edge environment, traps insects along edges, resulting in their higher density along edges as compared to field interior.Several studies have examined effects of the combination of natural landscape fragmentation and microclimatic conditions and how such variables affect insect communities in non-agricultural habitats . The spatial distribution of a butterfly, Lopinga achine Scopoli ,hydroponic nft system showed distinct edge-biased distribution, which was explained by specific micro-climatic conditions leading to the ground cover of Carex montana L. having the highest abundance near forest edges .

In a study of bark beetle [Ips typographus L. ] infestations, Kautz et al. investigated the risk of infestation in three types of forest edges and compared the results of trees from the interior of the same forests. They concluded that the risk of bark beetle infestation was highest in forest patches cleared by sanitary logging measures, in particular along south-facing edges. Thus, the combination of a particular edge management practice and ambient temperature was highlighted as a key driver of bark beetle infestations. Although exclusively based on analyses of data derived from natural habitats, such studies strongly suggest that edge-biased distributions are often explained by micro-climatic differences between edge and interior locations. Using different types environmental sensors, it has been demonstrated how abiotic variables, including ground surface temperature and soil temperature, show considerable with-field variation and in particularly vary between edges and inwards into fields . Such micro-climatic variation can lead to spatial variation in crop growth and relative suitability of host plants and therefore lead to edge-biased distribution of herbivorous insects in agricultural systems.Although windbreaks and hedgerows are common features in many agricultural systems, sole reliance on the shelter effect and microclimate promoted by these features does not provide encompassing account for the occurrence of edge-biased distributions, especially for agricultural systems in which they are not present. Other factors that are more intrinsic to the agricultural environment, such as the nature of landscape matrix, have been shown to affect insect rate of dispersal and emigration and result in their aggregation along edges. In a marked release and re-captured experiment on movement of delphacid plant hopper, Prokelisia crocea Van Duzee , in patches of prairie cord grass, the rate of emigration from cord grass patches bordered with brome grass matrix was higher than that from cord grass patches bordered with mudflat .

The same study also noted the accumulation of plant hoppers along cord grass-mudflat edges, but no such aggregation of plant hoppers was observed along cord grass-brome edges. It was later confirmed that the lower permeability of cord grass-mudflat edges makes this type of edges a barrier to emigration since plant hoppers behaviorally avoid crossing highly contrast border between vegetated cord grass matrix to sparsely vegetated mudflat matrix . Moreover, the cord grass-mudflat border was clearly not a reflective edge, as plant hoppers did not show edge-avoidance behavior. Meanwhile, the distribution of plant hoppers within a homogenous patch of cord grass was found to be random . Therefore, although landscape matrix permeability may explain why insects can be contained in their original patches, it does not directly explain the aggregation of insects along edges, especially for the case of delphacid plant hoppers.In cases where agricultural systems are adjacent to natural forests, the edges can be described as an “ecotone” that marks the ecological change between two environments . The adjacency of vegetation of two different habitats results in an increase in floral diversity and vegetation heterogeneity . The increase in heterogeneity of vegetation along field edges has been shown to increase carabid species richness along field edges . For example, boreal forests with sparse ground vegetation were found to have lower numbers of herbivorous invertebrate prey for carabids . The interspersion between grasses, shrubs, and boreal trees as seen in the edges between farming lands and boreal forests can effectively increase the density of ground vegetation, resulting in greater abundance of herbivorous invertebrates which, in turn, leads to higher carabid abundance along edges . Similarly, the interspersion of vegetation types between the forest edges and urban habitat in north Ohio has been attributed to the increase in ant species richness .

Therefore, the ecotone environment observed along field edges could serve as a preferential habitat for some insect species.In the discussion of edge-biased distributions in relation to the vegetation heterogeneity, there seems to be an underlying assumption that vegetation homogeneity exists within a given habitat or agricultural system. Therefore, the heterogeneity of vegetation observed in the ecotone along edges is mainly caused by the interspersion between the vegetation types of two environments, while the within-system variation of vegetation is often ignored. However, despite cropping systems predominantly being monocultures and under a quasihomogeneous management regime, there is broad evidence of significant vegetational heterogeneity within agricultural fields. That means individual crop plants within an agricultural field may have differential growth rates, phenotypes, and quality. This issue was highlighted above as microclimatic conditions may vary within fields and show distinct gradients between edges and locations further inwards into fields . Edge-biased crop development has been observed and reported for almost 100 years in winter wheat fields,nft channel where wheat rows along the borders showed higher yields than those in the center . Over the years, rice , maize and climbing beans , wheat , millets, Sudan grass , soybean , cotton , rapeseed , carrots, cabbages, and onions have been shown to display edge-biased distribution of growth. In rice, the increase in yield of border rows compared to central portions of fields or plots ranged from 63 to 68% . The difference can be as large as 394% between edge and center crops . The major factors accounting for such edge-biased growth difference have been attributed to competition for nutrients and light among crop plants . The body of research documenting edge-biased distributions of crop development often regards the phenomenon as undesirable and seeks ways to curb the effect to avoid overestimation in yield calculations . However, from an entomological perspective, the research focus would be to study how within field vegetational heterogeneity contributes to the edge-biased distribution of insects in agricultural systems. We are unaware of any published study addressing this question directly, but the edge resource model by Ries and Sisk could partially explain this, as micro-climatic conditions near edges may affect host plant growth and quality . Nonetheless, given that edge crops can have significantly higher yield than center crops, it is reasonable to hypothesize that there are physiological, and therefore nutritional, differences between edge and center crops. If such physiological differences are linked to differences in suitability as hosts and insects are able to—via volatiles or visual cues—perceive such differences among crop plants, then vegetational heterogeneity may partially explain observed edge-biased distributions of insects. That is, vegetational heterogeneity may drive selection by favoring both behavioral attraction and oviposition behavior by insects to certain plants. In addition, difference in suitability of crop plants will likely lead to differential growth and survival rates of insects.

As an example, longevity and fecundity of Sitobion avenae and Rhopalosiphum padi L. have been shown to increase with the level of nitrogen fertilizer applied to wheat host plants . Meanwhile, poor-quality host plants can cause many female insects to resorb their own eggs to mobilize nutrients for their survival . In broader term, female insects have been shown to vary their oviposition and number of eggs laid in accordance to the suitability of host plants for the performance of future progeny . Therefore, the better-quality edge crops may be preferred by insects or provide better growing conditions for insects and their larval stages, resulting in a skewed distribution towards crop edges. However, using plant vigor to explain edge-biased distribution of insects may also involve important trade-offs. On one hand, more vigorous plants may provide insects and their larvae with more nutrients for their development. On the other hand, healthier plants can also produce more defensive chemicals such as alkaloids, glucosinolates, and phenolics to protect themselves from insect herbivores . Furthermore, the idea of plant quality as potential explanation for insect aggregation along edges is also contested by the data reported by Haynes and Cronin . Their study found that the nitrogen content of plants along mudflat-cord grass edges and bromecord grass edges was both higher than that of plants in the interior. Interestingly, delphacid plant hoppers aggregated along mudflat-cord grass edges but not along bromecord grass edges, implying that host plant quality may not be the main driving factor of edge effect. Thus, we argue that considerable research is needed to investigate the complex of factors affecting plant growth along edges compared to inwards into cropping systems and how differential plant growth may affect their role as suitable hosts for associated insect communities.Originally, skewed distributions of agricultural insects towards field edges were mostly regarded as a source of error when developing insect sampling plans. Therefore, the data collected along field edges were not considered representative of the actual insect population . However, edge-biased distributions of insects in agricultural systems can potentially provide opportunities to optimize sampling efforts. Currently, sampling units employed in sampling plans are often randomized and spread across the field. Such an approach can be highly labor intensive. Given the prevalence of edge effects in many insect species, stratified sampling plans with a greater focus along field edges than field interiors can reduce sampling efforts as well as increase sampling accuracy if a stable spatial pattern of insect distribution within an agricultural system is well studied and established. For example, increased performance of such a spatially targeted sampling approach was demonstrated for the wheat stem sawfly . In addition, Severtson et al. described a spatially optimized sequential sampling plan for cabbage aphids in canola fields. In their study, canola fields were divided into two types of sampling grids: inner grids and edge grids. Edge grids were defined as the areas within 20 m of the field edge, while inner grids were the rest of the sampling grids. Their sampling results showed that 9 out of 20 edge grids displayed infestation level above threshold while only 2 out of 20 inner grids showed infestation level above threshold. Taking the proposed edge effect distribution of aphids into account, Severtson et al. conducted stratified sampling analysis and managed to reduce spatial variability as well as to increase accuracy of infestation level. Nonetheless, we also acknowledge that edge effect distribution of insects in many agricultural systems can be highly seasonal and temporally dependent .Furthermore, applications of insecticides in agricultural fields have been proven to greatly change the edge-biased distribution of insects to random distribution across agricultural fields . Therefore, the mentioned limitations may jeopardize the robustness of edge-stratified sampling methods and highlight the importance of timing in proposed edge-stratified sampling methods. Broadly speaking, increased understanding of the mechanisms responsible for edge-biased distributions can be used to improve the practices of precision agriculture. As compared to conventional agriculture, precision agriculture focuses more on timely and targeted application of treatments to control insect pest infestations rather than field-wide and calendar-based spraying of chemicals . The knowledge of edge-biased distributions can help create targeted sampling plans to generate more reliable mapping of insect distributions and enable more targeted application of pesticides used in IPM programs .