Introduction

The perception that there is a relationship between the patterns observed on a landscape and the set of physical and biological processes that generate those patterns is central to modern ecology. The concept was perhaps best elucidated in the classic 1947 presentation of A. S. Watt but was also an important construct in earlier papers by Watt (e.g. 1925) and others. The basic premise is to view an ecosystem as a working mechanism (Tansley 1935; Watt 1947). Such a mechanism, as a consequence of its internal interactions and interactions with the environment, produces the patterns that we see in nature. When one inspects Tansley's (1935) original definition of the ecosystem, one finds the same concepts that one sees in hierarchy theory today (Allen & Starr 1982; Allen & Hoekstra 1984; O'Neill et al. 1986; Urban, O'Neill & Shugart 1987).

Of course, the Watt–Tansley ecosystem paradigm has been reintroduced as a major ecosystem construct in ecological studies. One conspicuous reintroduction of these concepts was Whittaker's (1953) review, which used the Watt pattern-and-process paradigm to redefine the ‘climax concept’. These same ideas are also found in ecosystem concepts developed by Bormann & Likens (1979a,b) in their ‘shifting-mosaic steady-state concept of the ecosystem’, as well as in what Shugart (1984) called a ‘quasi-equilibrium landscape’. Given the richness of concepts developed by ecologists in the first half of this century, it is foolish to propose that any idea is new, but we are now in a position to extend the pattern-and-process paradigm in what may be fundamentally important ways.

This is an era of increased interest in the function and interaction of the major geophysical, geochemical and ecological systems of the earth. The interest in these large spatial scale studies has had diverse origins: the success of the ‘International Geophysical Year’ of global observations (1957–8) and a shared comprehension of just how much time has passed since this effort; the characterization of the surface of the earth from an ever increasing availability of images from space; the realization that humans are altering the composition of the atmosphere; a relative warming in international political tensions and the increased likelihood of sustained international scientific exchanges; an improved understanding of the past dynamics of the earth's surface resulting from radioisotope dating and analysis of paleoecological data; and the ramifications of computers with the power to solve complex equations of the fluid motion of the atmosphere and oceans. The conjunction of these and many other developments have turned the interests of many scientists in different disciplines to the issue of increasing the level of understanding of the earth as an interacting, dynamical system.

However, for all of these exciting developments, scientists in one of the important disciplines contributing to the study of the working of the planet, ecological sciences, are focused largely on the understanding of biota – environment interactions at very short time and space scales. Kareiva & Andersen (1988) found that about 80% of the studies in a sample of the journal Ecology were developed on areas less than 100 m2 Weatherhead (1986) sampled studies in the three areas of ecology, evolutionary biology and behavior and found the average duration of study to equal 2.5 years.

In the Introduction, we expressed a hope that this book would represent a point of departure for subsequent studies of the world's boreal forest ecosystems. We have presented the physical (Chapter 15) and biological (Chapter 16) elements of a computer model designed to simulate the local changes in any forest in the boreal zone. For purposes of future identification, we will refer to the merged version of this model as the BOFORS model and we expect these versions of the model to be updated as further work and information are incorporated into the model structure. Detailed information on the model is available in Bonan (1989a) for the biophysical features of the model and in Leemans & Prentice (1989) for the biological and silvicultural features of the model. Listings of the computer program for the BOFORS model are available on request from the University of Virginia's Science and Technology Library (Charlottesville, Virginia, USA) on interlibrary loan. The model is available in two implementations: Bonan (1990c) is a version of the model with all of the physical subroutines included (see discussions in Chapter 15); Leemans (1990) is a version of the model that has been used to simulate several locations in the USSR and Fennoscandinavia (see Chapter 16). The FORSKA model (Leemans & Prentice 1989) is available (in English) upon request from: Meddelanden från Växtbiologiska Institutionen, Uppsala University, Uppsala, Sweden, and on interlibrary loan from the University of Virginia library mentioned above.

Introduction

The problem of predicting ecological responses to global environmental change has generated a rich array of scientific challenges for ecosystem ecologists. The International Geosphere–Biosphere Program (IGBP), chartered by the International Council of Scientific Unions in 1986, has as its objective:

IGBP is one of the most exciting scientific opportunities of our time. The intellectual challenge is ultimately to unify ecological and geophysical sciences at the global scale: a large undertaking in which ecosystem ecology must play a central part.

One of the major tools for this multidisciplinary undertaking will be ecosystem simulation models implemented on high-speed computers. Global dynamics models exist for the atmosphere and oceans as physical systems, but not yet for ecosystems and their interactions with the atmosphere and oceans. This book represents the first attempt to develop a unified model of a major biome (the boreal forest) at the global scale. The model described in the chapters by Bonan (Chapter 15) and Leemans (Chapter 16) belongs to a well-established class of models that simulate the dynamics of forests by projecting the change in size of individual trees over time, through explicit representations of the interactions between arrays of individuals and their local resource environment.