Forest Insect Population Dynamics, Outbreaks, and Global Warming Effects



A. S. Isaev

V. G. Soukhovolsky

O. V. Tarasova

E. N. Palnikova

A. V. Kovalev




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Alexander S. Isaev, D.Sc. (Biology), Full Member of the Russian Academy of Sciences (RAS), Head of Research at the Centre for Problems of Ecology and Productivity of Forests RAS (CEPF RAS). Graduated from the Leningrad Forestry Engineering Academy. An expert in forest entomology and ecology. Director of the V. N. Sukachev Institute of Forest and Wood SB USSR AS (1976–1985), Head of the USSR Forest State Committee (1985–1991), Director of CEPF RAS. The author of more than 300 published studies, including over 20 monographs on forest ecology and forest entomology. Awards: Gold Medal of the International Union of Forest Research Organizations (IUFRO), V. N. Sukachev Medal of RAS, and IUFRO George Varley Award for Excellence in Forest Insect Research.

Vladislav G. Soukhovolsky, D.Sc. (Biology), Professor, Leading Researcher at the V. N. Sukachev Institute of Forest SB RAS. Graduated from the Faculty of Physics at the Krasnoyarsk State University. An expert in mathematical modeling of complex biological, ecological, social, and political systems. The author of over 500 published studies, including 16 monographs.

Olga V. Tarasova, D.Sc. (Agriculture), Professor of the Department of Ecology at the Siberian Federal University. Graduated from the Faculty of Biology at the Krasnoyarsk State University. Between 1978 and 1981, a graduate student at the Department of Ecology at the Krasnoyarsk State University (Academic Adviser – A. S. Isaev). An expert in forest entomology. The author of over 150 published studies, including four monographs. Award: V. I. Vernadsky Award for Excellence in Ecological Education.

Elena N. Palnikova, D.Sc. (Agriculture), Professor of the Department of Ecology and Forest Protection at the Siberian State Technological University. Graduated from the Faculty of Biology at the Krasnoyarsk State University. Between 1978 and 1982, a graduate student at the V. N. Sukachev Institute of Forest and Wood SB USSR AS (Academic Adviser – A. S. Isaev). An expert in forest entomology. The author of over 100 published studies, including one monograph.

Anton V. Kovalev, Ph.D. (System Analysis). Senior Researcher of International Scientific Center for Organism Extreme States Research (Krasnoyarsk Scientific Center). Graduated from the Faculty of Automatization and Robototechnic at the Siberian Technological State University. Between 1999 and 2002, a graduate student at the V. N. Sukachev Institute of Forest SB RAS (Academic Adviser – V. G. Soukhovolsky). An expert in system analysis of ecological processes. The author of over 100 published studies, including one monograph.


An insect outbreak is one of the first critical events in ecological systems described in world literature (Exodus 10:12). Until now, however, prediction and control of insect populations damaging forest stands and agricultural crops has remained an unresolved issue. The current insect outbreak situation can still be described with the biblical quote: “… When it was morning, the east wind had brought the locusts …”.

Research in insect population dynamics is important for more reasons than just protecting forest communities. Insect populations are among the main ecological units included in the analysis of stability of ecological systems. Moreover, it is convenient to test new methods of analyzing population and community stability on the insect-related data, as by now ecologists and entomologists have accumulated large amounts of such data.

In this book, the authors analyze population dynamics of quite a narrow group of insects – forest defoliators. We hope, though, that the methods we propose for the analysis of population dynamics of these species may be useful and effective for analyzing population dynamics of other animal species.

Below is a brief description of each chapter in the book.

Chapter 1 is, rather predictably, a review of the literature on modeling forest insect population dynamics. Section 1.3 provides a brief description of the phenomenological theory of population dynamics (Isaev et al., 1984; Isaev et al., 2001).

Chapter 2 discusses the issue that is seldom addressed in the literature – the choice of the way of describing insect population dynamics. In our opinion, for each definite task in the analysis of insect population dynamics, there is a specific way of data presentation: as a time series, a phase portrait, the “Lamerey stairs”, or potential function. Therefore, we discuss different ways of presenting survey data, as related to the purposes of the analysis.

We think that a necessary condition for the successful analysis of processes occurring in forest ecosystems is a certain irreverence towards the field data. As field ecologists, we know very well how much effort it takes to carry on insect population surveys on the same plot in the forest for many years. On the other hand, we are aware of the inaccuracy of the field data and the inevitable errors in estimates of the density of population dispersed over a vast area. Survey data should not be regarded as something incontrovertibly true but rather as a basis for research activities. These activities should include repair and transformation of the field data, based on the theoretical concepts developed in this research. Before using the survey data for analysis, they need to be “cleaned” as much as possible, to remove the inevitable errors of surveys, without distorting the time series. Our experience shows that it is important not only to collect the data but also to treat them properly. Therefore, Chapter 2 gives a detailed description of field data repair and transformation. This chapter focuses on the methods used to process survey data and transform an arbitrary time series into the stationary time series, which can then be studied by using standard techniques of correlation and spectral analysis.

Chapter 3 is devoted to the analysis of weather effects on the development of outbreaks of taiga defoliating insects. This subject has been extensively discussed in the literature, especially in the last decades, as related to the possible global climate change. Here we present our understanding of these processes.

Chapter 4 analyzes spatial coherence of population dynamics of the same insect species in different habitats and the temporal coherence of population dynamics of several insect species in the same habitat. Such analysis can be used to reveal interactions between species associated with, for example, competition for food and to estimate possible responses of different species to external impacts such as changes in weather and geophysical parameters.

Chapter 5 describes parasite – host interactions for populations of forest insects and their parasites in different outbreak phases.

In Chapter 6, we present a model of food consumption by insects, which links population dynamics with food properties. We propose a quasi-economic approach to describing food consumption and introduce indicators of food consumption analogous to costs in economics. In this way, we relate the energy and population approaches to the description of the processes in the forest – insect system and approach evaluation of fecundity of individuals – very important parameters for analysis and forecast of insect population dynamics.

Chapter 7 is devoted to modeling time series of forest insect population dynamics by using autoregressive models. The chapter describes models of population dynamics of the larch bud moth and other species of the defoliating insect community in forests of the Alps, the pine looper in Europe, defoliating insects in the Siberian pine forests, the European oak leaf-roller in European Russia, and the gypsy moth in the South Urals. For autoregressive models, we introduce parameters of stability, stability margin, and robust stability, which are used to assess the risks of “removal” of the species from the community. These models serve as a basis for developing adaptive methods for short-term forecasts of forest insect population dynamics.

Chapter 8 deals with a new method of describing and modeling forest insect population dynamics, based on the presentation of critical events in the population as first- and second-order phase transitions. Using the models of phase transitions, we managed to introduce conditions of the occurrence of forest insect outbreaks, describe the patterns of insect migrations in the forest during an outbreak, and characterize the susceptibility of populations to weather effects.

We consider in Chapter 9 methods of short-, medium-, and long-term forecasting of insect population dynamics based on the approaches described in the previous chapters and methods of assessing the risk of the tree stand damage and death caused by insect outbreaks. In addition to that, Chapter 9 contains a brief discussion of the problems associated with controlling the risks of insect attacks and making decisions about extermination measures based on forest entomological monitoring. We may have given too little consideration to these issues, and they will need to be discussed more thoroughly in a future study.

Finally, in Chapter 10, we discuss the effects of possible global climate change on population dynamics of defoliating forest insects. We use ADL-models and phase transition models developed in this book to assess the risks of outbreaks under various scenarios of climate change.

We hope that this book will be useful to specialists in ecology, entomology, ecological modeling, and forest protection as well as to undergraduate and graduate students of ecology and entomology.

We are grateful to our former and current Ph.D. students – S. Astapenko, Y. Bekker, O. Bulanova, P. Tsikalova, T. Iskhakov, I. Kalashnikova, P. Krasnoperova, V. Kuznetsova, M. Meteleva – for their assistance in different stages of the research. We specially appreciate out deceased colleagues – Yuri P. Kondakov and Viktor M. Yanovsky, with whom we had studied forest insect population dynamics for many years.

Our studies were supported by very many grants of Russian Foundation for Basic Research No. 96-04-48340, 99-04-49450, 00-04-48990, 02-04-48769, 02-04-62038, 03-04-49723, 03-04-62037, 04-04-49821, 08-04-00217, 08-04-07052, 09-04-00412, 10-04-08236, 11-04-00173, 11-04-08064, 15-04-01192.