Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

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.

Fowles and Nansen’s chapter discusses insect-based bioconversion. When insects are mass produced under controlled conditions, they can break down significant quantities of food waste. Further, as the insects consume this waste, they produce multiple valuable commodities, such as insect biomass (proteins, lipids), pharmaceuticals, biofuels, lubricants, and fertilizer from their excrement. This process is called bioconversion and will be a serious contender among food waste treatment options in the coming decades. Insect bioconversion is gaining traction both as a research topic and as a business opportunity. Fowles and Nansen discuss both the need to increase capacity and to maximize the potential benefits of using insects as bioconverters of food waste. They provide both theoretical and practical solutions for expanding insect-based bioconversion to food waste streams.

Agricultural organisms, such as insect herbivores, provide unique opportunities for studies of adaptive evolutionary processes, including effects of insecticides on movement and oviposition behavior. In this study, Brassica leaves were treated with one of two non-systemic insecticides and exposed to two individual strains (referred to as single or double resistance) of diamondback moth (Plutella xylostella) (DBM) exhibiting physiological resistance. Behavioral responses by these two strains were compared as part of characterizing the relative effect of levels of physiological resistance on the likelihood of insects showing signs of behavioral avoidance. For each DBM strain, we used choice bioassays to quantify two possible types of behavioral avoidance: 1) females ovipositing predominantly on leaf surfaces without insecticides, and 2) larvae avoiding insecticide-treated leaf surfaces. In three-choice bioassays (leaves with no pesticide, 50% coverage with pesticide, or 100% coverage with pesticide), females from the single resistance DBM strain laid significantly more eggs on water treated leaves compared to leaves with 100% insecticide coverage (both gamma-cyhalothrin and spinetoram). Females from the double resistance DBM strain also laid significantly more eggs on water treated leaves compared to leaves with 100% gamma-cyhalothrin, while moths did not adjust their oviposition behavior in response to spinetoram. Larvae from the single resistance DBM strain showed a significant increase in mobility in response to both insecticides and avoided insecticide-treated portions of leaves when given a choice. On the other hand, DBM larvae from the double resistance strain showed a significant decrease in mobility in response to insecticides, and they did not avoid insecticide-treated portions of leaves when given a choice. Our results suggest that pest populations with physiological resistance may show behavioral avoidance, as resistant females avoided oviposition on leaves without gamma-cyhalothrin. Thus, physiological resistance and behavioral avoidance do not appear to be controlled by the same selection pressures, and the mechanisms responsible for behavioral avoidance may vary among life stages. Our analysis also suggested that a population with lesser physiological resistance to insecticides may be under a stronger selection pressure and therefore be more likely to develop avoidance behaviors than a population with higher levels of physiological resistance.