Executive Summary

Sustainably managing limited resources, such as productive land areas and available freshwater, will be one of the world's most pressing challenges in the coming years. Population increases and economic growth will significantly influence humanity's future demand for land and water for different uses. In particular, changes in food and energy use will have substantial environmental impacts. They will also influence each other in many ways. At the same time, the production of food and energy, and the water resources they require, will be affected by global climate change. Sustainability issues arising from competition and synergies between future production of bioenergy and food, and related water use, are highly important in this context.

Population growth is one of the factors contributing to increased demand for land and water. While the world's population has approximately doubled since the 1960s, global economic activity has increased approximately 40 fold. Since growth in incomes is strongly correlated with increased consumption of animal-derived food (meat, milk, eggs), the combination of population increases and economic growth will likely result in increased feed and food production. This will drive up pressures on land and water resources if not counteracted by innovations that reduce land and water use. Social inequities are increasing as well, with both very rich and very poor populations often practicing ‘inefficient’ methods of using land and water.

Introduction

The extent of the circumpolar boreal forest strongly corresponds to macroclimate. Within its climatic limits, the system functions as a complex interrelation between solar radiation, soil moisture, the forest floor organic layer, nutrient availability, forest fires, insect outbreaks and vegetation patterns (Bonan & Shugart 1989). Bonan (1989a and Chapter 15 of this volume) has specified a model for the environmental regimes, which sets the limits driving boreal forest dynamics. He has linked this model with a forest succession model, a gap model, which simulates the demographic processes of tree populations through time within the environmental constraints, and a model of moss dynamics. The combined model mimics the large-scale dynamics of boreal forest (Bonan 1989a; Bonan & Korzukhin 1989).

Bonan's model simulated different stands well with respect to species composition, biomass and density. The ability to simulate such trends in quantitative characteristics of tree species is a robust feature of gap models in general (Shugart 1984; Leemans & Prentice 1987). This robustness is largely a result of the coupling of growth responses of individual trees to environmental factors. If the annual growth of a tree declines as a result of environmental conditions, its chances of dying increase. Thus, the individual tree is removed from the plot, leaving room for better-adapted individuals. This aspect of the traditional gap models appears to provide a robust ability to reproduce composition, biomass and density. If more precisely defined forest structures are used to test such models, the models are often less successful.

Introduction

Models for simulating different aspects of vegetation dynamics have become increasingly popular during recent decades. Initially, mathematical modeling was only accessible to well-trained biomathematicians, but with the increasing availability of small and faster computers and with the development of modern software, it has been applied by more traditionally trained ecologists and foresters. Recently, many papers that present different models and applications within ecology have been published (e.g. Emanuel et al. 1984; van Tongeren & Prentice 1986; Running & Coughlan 1988; Tilman 1988; Costanza, Sklar & White 1990; Keane, Arno & Brown 1990).

Simulation models can help in the understanding and management of ecosystems. Such models are usually the only tool available for translating a collection of hypotheses for ecological processes into a testable representation of how the whole ecosystem functions. Simulation models can be used not only to evaluate hypotheses generated by field studies and ecological experiments, but also for situations where the more traditional ecological approach is less applicable, for example for studies that span several research generations, such as the study of processes involved in forest succession and gap-phase replacement of individual trees within a stand (Watt 1947). Ecological hypothesistesting by experiment and field studies for such long-term and largescale processes is almost inevitably incomplete and must be supplemented by simulation experiments.

Simulation models consist of a collection of hypotheses, most often in equation form. These hypotheses define how the major parts of the model change over time (Swartzman & Kaluzny 1987).

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.