Ecological Model Types

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• Publisher: Elsevier
• Year: 2016
• eBook ISBN: 9780444636263
• Topic: Biological Sciences
• Subtopic: Ecology
• Index: Biological Sciences

Ecological Model Types brings an understanding on how to quantitatively analyze complex and dynamic ecosystems with the tools available today. Ecosystem studies widely use the notions of order, complexity, randomness, and organization, and are used interchangeably in literature, which causes much confusion.Better models synthesize our knowledge on ecosystems and their environmental problems, in contrast to statistical analysis, which only reveal the relationships between the data. This book brings together experts on ecological models to create a definitive work on how to understand our complex Earth.- Bridges the gap between statistical analysis and synthesis of data, enhancing our understanding about ecosystems and their environmental problems- Helps readers understand complex ecosystems by walking through the best modeling options to analyze and predict environmental effects- Provides a detailed review of 14 model types, covering the breadth of options available for analysis at this time

Chapter 1

Introduction

An Overview

S.E. Jørgensen Emeritus Professor, Copenhagen University, Denmark
E-mail address: [email protected]

Abstract

The discipline of ecological modeling has been developed since the 1970s, a process that has been evolving quickly due to development of proper techniques, computer power, and adequate software, together with the recognition of existence of environmental problems, as well as the establishment of sufficient knowledge on ecological processes, how they are regulated, and hence how to retain ecosystem properties. At the beginning, our understanding was based on rudimentary solutions like introduction of various environmental technologies but later management was expanded by extensive use of models assisted by use of more advanced technologies, regulatory and legislative initiatives. This was necessary as the environmental problems we had to address soon turned out to exhibit an almost ever-increasing complexity. Ecological models can be used for survey, to reveal system properties, establish research priorities, and to test scientific hypotheses. Hence, we consider them useful as experimental tools. A basic grouping shows that ecological models in general belong to three areas: biodemographic, bioenergetic, and biogeochemical. Technically, the models have been developed within a set of 14 different approaches which results in almost 300 papers published per year about ecological modeling in the journal of Ecological Modelling alone. This represents a 16-fold increase in pages published as compared to the late 1970s. In the recent decades, ecological modeling has also developed in a direction to include theoretical studies of ecosystems, such as the possibility of goal oriented behavior, understanding of complexity, and organizational issues.

Keywords

Development; Ecological modelling; Ecosystem modelling; Environmental modelling; Model classification; Model publications; Model tools; Model types

1.1. Application of Ecological Modeling

The field of ecological modeling has developed rapidly during the last four decades due to essentially three factors:

1. The development of computer technology, which has enabled us to handle very complex mathematical systems.

2. A general increased knowledge about environmental problems, including that a complete elimination of pollution is not feasible (denoted zero discharge), but that a proper pollution control with limited economical resources available requires serious considerations of the influence of pollution impacts on ecosystems. Models are indispensable tools in this context.

3. Our knowledge about environmental and ecological problems has increased significantly. We have particularly gained more knowledge of the quantitative relations in the ecosystems and between the ecological properties and the environmental factors.

Good models are syntheses of our knowledge about ecosystems and their environmental problems, in contrast to a statistical analysis, which only will reveal the relationships between the data. A model is able to include our entire knowledge about the system, if required for a proper solution of the environmental problem:

• which components interact with which other components, for instance that zooplankton grazes on phytoplankton,

• our knowledge about the processes often formulated as mathematical equations which have been proved valid generally,

• the importance of the processes with reference to the problem;

These are a few examples of knowledge which may often be incorporated in an ecological model. This implies that a model can offer a deeper understanding of the system than a statistical analysis. It is therefore a stronger tool in research and can result in better management plans, on how to solve environmental problems. This does of course not mean that statistical analytical results are not applied in the development of models. On the contrary, models are build on all available knowledge, including knowledge gained by statistical analyses of data, physical-chemical-ecological knowledge, the laws of nature, common sense, and so on. That is in short the advantage of modeling.

The idea behind the use of ecological management models is demonstrated in Fig. 1.1. Urbanization and technological development has had an increasing impact on the environment. Energy and pollutants are released into ecosystems, where they may cause more rapid growth of algae or bacteria, damage species, or alter the entire ecological structure. An ecosystem is extremely complex, and it is therefore an overwhelming task to predict the environmental effects that such emissions may have. It is here that the model comes into the picture. With sound ecological knowledge, it is possible to extract the components and processes of the ecosystem that are particularly involved in a specific pollution problem to form the basis of the ecological model (see also the discussion in Chapter 2). As indicated in Fig. 1.1, the resulting model can be used to select the environmental technology eliminating the emission most effectively.

Figure 1.1 The environmental problems are rooted in the emissions resulting from industrialization and urbanization. Sound ecological knowledge is used to extract the components and processes of the ecosystem that are particularly involved in a specific pollution problem to form the ecological model applied in environmental management to select good solutions to the focal problem.

Fig. 1.1 represents the idea behind the introduction of ecological modeling as a management tool around years 1970–1975. The environmental management of today is more complex and applies therefore a wider spectrum of tools.

Today, we have as alternative and supplement to environmental technology, cleaner technology, ecotechnology, environmental legislation, international agreements, and sustainable management plans. Ecotechnology is mainly applied to solve the problems of nonpoint or diffuse pollution, often originating from agriculture. The significance of nonpoint pollution was hardly acknowledged before around 1980. The global environmental problems play furthermore a more important role today than 20 or 30 years ago, for instance the reduction of the ozone layer and the climatic changes due to the greenhouse effect. The global problems can hardly be solved without international agreements and plans. Fig. 1.2 attempts to illustrate the more complex picture of environmental management today.

Mathematical models are not only applied in environmental management but are widely applied in science, too. Newton's laws are for instance relatively simple mathematical models of the influence of gravity on bodies, but they do not account for frictional forces, influence of wind, etc. Ecological models do not differ essentially from other scientific models not even by their complexity, as many models used in nuclear physics today may be even more complex than ecological models. The application of models in ecology is almost compulsory, if we want to understand the function of such a complex system as an ecosystem. It is simply not possible to survey the many components and their reactions in an ecosystem without the use of a model as a holistic tool. The reactions of the system might not necessarily be the sum of all the individual reactions, which implies that the properties of the ecosystem as a system cannot be revealed without the use of a model of the entire system.

Figure 1.2 The idea b...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of Contributors
• Acknowledgements
• Chapter 1. Introduction: An Overview
• Chapter 2. Biogeochemical Models
• Chapter 3. Dynamic Population Models
• Chapter 4. Steady State Models
• Chapter 5. Earth's Surface Modeling
• Chapter 6. Application of Structurally Dynamic Models (SDMs)
• Chapter 7. Artificial Neural Networks: Multilayer Perceptron for Ecological Modeling
• Chapter 8. Ecotoxicological Models
• Chapter 9. Fugacity Models
• Chapter 10. Fuzzy Adaptive Management of Coupled Natural and Human Systems
• Chapter 11. Coastal Ecosystem Modeling in the Context of Climate Change: An Overview With Case Studies
• Index