Systems Ethology
2026-04-03
Preface
The work contained in this monograph represents the contributions of Bland Ewing to a field he originally described as `population ethology’ or ‘quantitative population ethology’, which I now call ‘systems ethology’. The original unpublished manuscripts are all over 25 years old. Nevertheless, the ideas fit nicely with current theories about population dynamics, with the present strong interest in Markov chain Monte Carlo methods for simulation, with today’s fast desktop computing environments, and with efforts in many areas of ecology to construct individual-based models of behavior in small populations.
Professor Evert Schlinger played a key role in getting Bland Ewing to UC Berkeley in the late 1960s. Bland worked under Professor David L. Wood, who ultimately introduced us to Ewing’s work in the context of the western pine beetle project.
Most of this work developed during the early 1970s. This was Yandell’s first introduction to bridging ecology, mathematics and computers, and has had an indelible imprint on his career. Finally the material can be published in enhanced form for others to share. The purpose of this document is to honor Bland Ewing, and to make it possible for myself and others to benefit from his ideas and perspective.
This monograph is developing out of a collaboration of four scientists who worked together in the 1970s when these ideas were young. The core material was to be Bland Ewing’s dissertation, but for a variety of reasons that never materialized.
At the time, we felt the ideas were 25 years ahead of their time. Now, hindsight suggests that we might have been correct. While individual-based ecological models are now regularly published in the literature, they are almost exclusively time-driven, greatly limiting their capacity to expand to study large populations.
Bland’s underlying aim was to design a simulation system directly useable by field biologists, relying direcly on field measurements to examine ethological questions about populations of interacting individuals. Such questions do not have answers in dynamical systems models, but rather in emergent properties that may be counter-intuitive.
The authors would like to thank Dr. David L. Wood for his continual and unwavering encouragement over the long haul. We would like to thank David Baasch and Dr. William Waters for the contributions and encouragement they have provided in this effort, and Dr. Peter A. Rauch for his early efforts to organize this material. The authors would like to thank Drs. C. Huffaker, R. Smith, and J. Knox for their support in the development of this modeling technique. We would like to particularly thank Ms. Floy Worden who typed original manuscripts quickly and accurately in the 1970s, and Ms. Karen Denk who retyped these into a modern word-processor in the 1990s.
This work was performed in part under the auspices of the U.S. Department of Energy and supported in part by a National Science Foundation grant (NSF GB-34718) to the University of California; the Environmental Protection Agency through an interagency agreement (EPA-IAG-COV-4) with the Lawrence Livermore National Laboratory; the “Huffacker Project” Grant (DEB 75-04223) which combined funds from the National Science Foundation and the Environmental Protection Administration, NSF Grant BSR 86-1304-01; grants from NSF, USDA, UC-IPM and the Citrus Board; and the University of Wisconsin-Madison College of Agricultural and Life Sciences. The U. S. Forest Service supported Ewing in the initial phase of this effect. The findings, opinions and recommendations expressed herein are those of the authors and not necessarily those of the University of California, the National Science Foundation, the Environmental Protection Agency, the U. S. Forest Service, the Atomic Energy Commission or the Lawrence Livermore Laboratory. This paper contains part of the intended Doctoral Dissertation of Bland Ewing.
Copyright 2001 BS Yandell