Borror and DeLong’s Introduction to the Study of Insects

Borror and DeLong's Introduction to the Study of Insects pdf

Understand the insect world with BORROR AND DELONG’S INTRODUCTION TO THE STUDY OF INSECTS! Combining current insect identification, insect biology, and insect evolution, this biology text provides you with a comprehensive introduction to the study of insects. Numerous figures, bullets, easily understood diagrams, and numbered lists throughout the text help you grasp the material.

Book Review by Dr. Lee D. Carlson

Important for both biologists and non-biologists

Everything about insects is fascinating, and this book gives a comprehensive overview of their behavior, anatomy, and classification. For non-experts in entomology, such as this reviewer, the book provides the necessary background for further study. Topics such as the molecular genetics of insects and the genetic engineering of insects are not covered, but there are plenty of other books that treat these topics in detail. Only the first four chapters were read by this reviewer, but only chapter four will be discussed here.

Early on in chapter four, the authors dispel the prejudice that since insects have small nervous systems and have short life spans, they are not automatons and can exhibit a remarkable degree of spontaneity. Insects can adjust to the circumstances of their environment and the organization of their activities can be extremely complex. What is most interesting about their discussion of insect behavior is the emphasis on how it depends on the internal state of the insect, and not only its nervous system but also its internal organs.

The authors view the basic unit of behavior in an insect as being a `reflex’. A receptor that is stimulated will cause a particular group of insects to contract, which is observed as a body movement of the insect. A `releaser’ is the stimulus that actually triggers a specific collection of movements. This results in what is called a `fixed-action pattern’, which, as the name implies, occurs the same way every time it occurs. To be contrasted with these are the `modal-action patterns’ that adapt to changes in the body position of the insect relative to external objects. A `central pattern generator’ the authors write, is responsible for the leg and wing movements of insects, and allows them to navigate in noisy environments. All of these considerations of insect behavior are interesting in themselves, but even more so considering that they are being applied to unexpected fields such as artificial intelligence. Indeed, the learning abilities of insects are being emulated in various machines in the last few years, with good success. And even, a new area of artificial intelligence called `swarm intelligence’ has arisen that is based on the behavior of ants.

Along these same lines, the authors discuss four categories that he believes are useful in characterizing insect behavior. These categories clarify to a large extent the difference between `preprogrammed’ and modified behaviors. The first of these are called `closed instincts’, which are fixed programs. The second is more flexible and are called `open instincts’, where experience feeds back and changes the program. The third consists of `restricted learning’ and is the analog of classical conditioning.

The last one is `flexible learning’, wherein experience can result in significant changes in the behavior pattern. All of these categories have found expression in machines, as well as the types of learning that the authors believe exists in insects: habituation, and associative, latent, and insight learning. The authors admit though that insight learning, where familiarity with relationships among (neutral) stimuli is obtained, has not been established without controversy in insects. Honey bees though they quote as examples of insects that can engage in insight learning.

Very interesting also in this discussion of the behavior of insects is the use of mathematical models. As expected intuitively, these models involve control theory, but even more “exotic” approaches such as optimality theory and dynamic stochastic modeling. Optimality theory is used with the assumption that insects evaluate their state variables and engage in decision-making that optimizes their gain according to some criterion.

Needless to say the learning abilities and behavior of insects is fascinating, and no doubt there are many surprises waiting for future entomologists. Their research efforts will not only assist in the better understanding of the most important representatives of the animal kingdom but they will be immediately used by those who are attempting to emulate this “primitive” intelligence of insects in machines.

About the Author

Norman F. Johnson is a professor of biology at Ohio State University and curator of the Ohio State University insect collection. His research interests include the systematics of parasitic Hymenoptera and in particular the Proctotrupoidea. His focus to date has been on the Scelionidae, a speciose group important as biological control agents of their hosts. In 1992 he assumed the position of director of the OSU Insect Collection.

Charles A. Triplehorn is emeritus faculty at Ohio State University and his broad interests include systematics and biogeography of Coleoptera. His research is primarily on the large family Tenebrionidae, especially those of the Western Hemisphere. Since his retirement from Ohio State in 1992, he has concentrated on two major projects: a revision of the genus Eleodes and of the Neotropical Diaperini. Triplehorn is the former president of the American Entomological Society.