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Environmental systems science

Environmental systems science grew out of the exigencies of the DDT litigation which began in 1966. It made its first formal appearance in the concluding days of the DDT hearings at Madison Wisconsin in the spring of 1969 when it was necessary to summarize the thousands of pages of scientific testimony about the effects of DDT and its principal environmental metabolite, DDE, upon the Lake Michigan regional ecological system and the manner in which DDT and DDE were transported in and out of that complex system which included the states of Michigan and Wisconsin as well as one of the largest bodies of freshwater in the world.

It was formally presented to the academic science community in a paper published in Science, “Systems Studies Of DDT Transport” and later at the annual meeting of the American Association for the Advancement of Science (AAAS) in Boston.

Ecology

Ecology is often characterized as the scientific study of the “web of life. Human beings can be found somewhere in that web, either as spinner or unwilling captive, and there has been much written about man’s “place in nature.” As a modern science, Ecology deals with organisms in their environment and with the processes that link organisms and their habitats.

Ecology, however, is more than the study of any organism in its environment, it is the integrated study of organisms and their environment. Ecology involves consideration of the prerequisites for human existence on earth: the essential physical and chemical factors, food, and energy. Ecology as an integrative discipline provides a framework within which seemingly disparate human activities can be seen in relationship to each other; although the vision is less than clear at times in relation to the whole of life.

The study of the relationships among different organisms and between organisms and their environment has resulted in the description of various biogeochemical cycles which provide a convenient way of modeling very complex systems. The most nearly perfect cyclical processes are those involving water and nitrogen, while the least cyclical processes are those in which material is removed from the continents and deposited in the permanent basins of the ocean. ·

In 1969, Paul Shepard observed that

“Ecology . . . as such cannot be studied, only organisms, earth, air, and sea can be studied. [Ecology] is not a discipline: there is no body of thought and technique which frames an ecology of man. It must be therefore a scope or a way of seeing. Such a perspective on the human situation is very old and has been part of philosophy and art for thousands of years. It badly needs attention and revival.” The Subversive Science: Essays Toward An Ecology of Man (1969).

The fundamental and basic concepts of animal ecology are also the fundamental and basic concepts of human ecology. The laws of Nature apply to the human species as they do to animals. Human beings cannot ignore the dynamic forces of the environment with impunity.

Ecosystems

A natural community is an assemblage of populations of plants, animals, bacteria, fungi and other microorganisms that live together in some place at some time and interact with one another and their environment to such an extent that they may be considered together as a system of some definite composition and structure, relating to its external environment, and capable of development and function.

A community, therefore, is just a system of organisms, including man, living together and considered as a set (in the mathematical sense of a group or collection of objects, relations or events) by reason of their effects upon one another and their interactions with the environment they share. A community and its associated environment when considered as a functional system of complementary relationships, together with the transfer and circulation of matter and energy throughout the system is called an ecosystem.

Ecosystems are real like a pond, or a lake or a stream or a forest or an ocean; but they are also abstractions in the sense of being conceptual schemes developed from a study of real systems which, although characterized by great diversity and unique combinations of abiotic and biotic components, still may be characterized by certain general structural and functional attributes that are common to ecosystems as ecosystems. In particular, the two primary ecological processes of energy flow and material cycling establish the basis for consideration of ecosystem dynamics or ecological energetics.

Ecological systems

Ecological systems are composed of many components which interact in a variety of ways. Each biological component of the system is affected by the physical abiotic elements of the system, and all the variables change not only with respect to time but from place to place since the environment is heterogeneous. Discrete system elements interact and each component of the system affects all the others in one way or another. The complexity of the system of interlocking cause-effect pathways confronts us with a superficially baffling problem, and systems analysis was developed to handle such situations.

In the case of a real ecological system, no attempt at simulation can be truly complete. Indeed, the art of systems ecology is to determine the crucial elements and processes that govern the general behavior of the ecological system as a system. Systems analysis is particularly useful to citizens and legislators who have to make decisions from less than a total data base.

Viewing an ecological system as an interlocking complex of processes characterized by many reciprocal cause-effect pathways, it can be seen that one of the principal attributes of a system is that it can only be understood by considering it as a whole.

The processes of energy flow and material cycling are fundamental to the study of environmental systems, whether those systems are “ecosystems” in the classic sense of that word as used by plant and animal ecologists, or the myriad of systems in which human beings interact with other human beings or their environment, and the systems are characterized by the jargon of economics or the social sciences.

These fundamental processes, however, are manifested through the agency of living organisms: plants, animals, including human beings, and microorganisms.

By reason of the unique morphological, physiological and behavioral attributes of each species of living organism, each of those species has unique ecological attributes as well. For just as no organism is sufficient unto itself, neither are ecosystems, or in the larger sense, environmental systems, discrete entities delimited sharply from other ecosystems or environmental systems. The mere existence of contiguity and/or continuity complicates the study of environmental systems.

Perhaps the most fundamental dimension of an ecosystem is its productivity, whether that productivity is measured in terms of the creation of organic material per unit of area over time, or in the terms of industrial engineering or management science. All biologic activity including human life depends ultimately on the energetics of gross primary productivity, the energy bound in photosynthesis by green plants.

Although the over-all productivity of the world may seem very large, effective limitations on what human beings harvest as food result from characteristics of environment that affect production, the function of plant ecosystems and the efficiencies and technology of plant harvest as well as economic, social, political and cultural factors.

Three of the major modes of nutrition (the means of utilizing plant productivity) are represented in the three functional units of most natural communities. The producers, or green plants create their own food and metabolize a portion of it for their own needs. The consumers, or animals, feed by ingestion and internal digestion of organic material. The reducers, bacteria, fungi and other microorganisms live by absorption and employ external digestion; decomposing organic matter to its inorganic elements.

The Regional Environmental System

Before the Regional Environmental System can be defined, the word “environment” which has become so common must be precisely defined since it has come to mean different things to different people.

“Environment” should be defined in the broad sense now accepted by environmental systems scientists after a series of courtroom tests which began in 1966 with the first challenge to DDT as an environmental toxicant, (Carol A. Yannacone v. Dennison, et. al), and tested during hearings before the Wisconsin Department of Natural Resources, and in the federal courts during the Project Rulison litigation,.

Environment is the word used to represent the complex System established (in the mathematical sense) by the union of the sets of natural, social, economic and societal resources existing in a region; and the set of all interactions among those resources; and the sets of natural, social, societal and economic processes operating within or upon the region.

The constant feedback between human beings and their environment implies a continuous alteration of both. However, the various aspects of biological and social nature constitute such a highly integrated system that they can be altered only within a certain range.

The human community and its social and economic systems constitute integral elements of any region just as surely as do the aquifers, aquifer recharge areas, precipitation, climate, topography, watersheds and drainage units, groundwater, soils, vegetation, wildlife, scenic vistas, historic sites, and all the other readily determinable elements that environmental scientists and planners are so fond of inventorying. The interactions between and among those natural, social, societal and economic systems establish the Regional Environmental System at the moment of concern and define the region, in space and time, throughout which the effects of actions upon any element of the system may be perceived.

The elements of Regional Environmental Systems

Ecosystems when considered as a community and its associated environment operating as a functional system of complementary relationships, together with the transfer and circulation of matter and energy thrughout the system are generally the largest units of a Regional Environmental System. A Regional Environmental System may contain one or more associations of identifiable ecosystems which act as Regional ecological systems

A systems approach is required in order to determine the boundary values and elemental optimizations of the complex, nonlinear, dynamic relations that describe the region as it actually exists in real time, rather than as some stylized formalization which is often little more than a figment of the imagination of some self-proclaimed expert.

Environmental Systems Analysis

Environmental systems analysis demonstrates the extent of the overall impact on the environment of a region —The Regional Environmental System —which can be expected from any alteration, modification or disturbance of any particular system or system element.

Systems analysis is a method for studying, or in the first instance determining, relationships among elements of interdependent systems which can be considered as sets (in the mathematical sense of a collection or aggregation of objects or events) because they behave as a unit, are involved in a single process, or contribute to a single effect.

The principal reason for using systems analysis in ecology, economics and more recently, the social sciences, is the complexity of environmental systems originating from a variety of causes: the large number of variables; the large number of different types of variables; different levels of systems organization (populations, communities, trophic levels, cycles) and the non-homogenous and nonuniform distribution of system elements throughout time and space.

Although systems analysis has its roots in military and industrial operations research, applied mathematics, probability, statistics, computer science, engineering, econometrics and biometrics, there are common and now somewhat standard approaches for dealing with the great complexities inherent in the considerations of real systems.

One is the operating maxim that complex processes can be most easily dissected into a large number of relatively simple unit components, and that complex historical processes in which all variables change with time (evolve) can be dealt with most easily in terms of recurrence functions which express the state of a system at time t+1 as a function of the state of the system at time t. Thus the system is considered not in terms of its entire history but rather in terms of the cause-effect relationships that operate through a typical time interval.

Systems analysis combines the basic ideas of recurrence relations and optimization in order to determine the optimal choice from among an array of alternative strategies at each of a sequence of times: the multistage decision process.

Recurrence relationships

This idea of the recurrence relationship is common throughout mathematics. Matrices of transition probabilities in Markov processes are merely stochastic versions of a recurrence relation. Difference equations, differential difference equations, dynamic programming, and the “loops” of computer programs are all based on recurrence relations in which the output from each stage in the computation is the input for the following stage. No breakdown in this approach occurs if the state of the system at time t is a function of the state of the system not only at time t-1, but also at time t+1, t+ 2 . . . t+n. Only the number of variables in the recurrence relationship and the dimensionality of the problem are increased.

Optimization

Another of the basic principals of systems analysis is optimization which brings to many practical problems the whole body of pure and applied mathematical theory related to the maximization and minimization of functions: the mathematics of extrema.

Tools for environmental systems analysis

Multistage decision processes share two important basic similarities from a computational standpoint: high dimensionality and the need to be solved by some iterative process; requirements common to other types of problems often encountered in pure and applied mathematics and which have led to development of such now commonplace techniques as multiple linear regression analysis, iterative non-linear regression analysis, and gradient methods for finding maxima and minima among others.

Feedback and feedback control are other concepts of systems analysis that are important ·in the consideration of ecological, economic and social systems, so that a realistic mathematical description of a process includes terms such that deflection toward the equilibrium or steady state follows departure from equilibrium within the recovery limits of the particular system.

Interaction among system elements is easier to describe in terms of changes and the rates of change at some specific instant in time rather than in terms of the history of the process over time, so that models of interactions are typically conceived of in terms of differential rather than algebraic equations. ·

Inequality constraints are encountered commonly in ecological systems analysis problems, as are thresholds and limits. Similarly, the common technique of computer programming in terms of a cyclically repeated routine or “loop” is suitable for consideration of ecological problems where historical processes unfold through the repetition of variants of the same basic cycle of events and dispersal occurs through a parallel process, but in space as well as time.

Information in environmental systems science

Another important concept from systems analysis useful in environmental systems studies in that of information. The amount of information is related to the degree of order or negentropy in a system and this concept plays a role in studies of community organization.

Models

Models are attempts to describe a system as the set of its interrelated and interacting elements so that mathematical techniques may be applied in an attempt to predict the behavior of the system as a whole over some future period of time. Traditionally, researchers used physical models in laboratory experiments to study the behavior of real systems, however, it has become increasingly difficult to construct physical models of complex environmental and social systems so the emphasis today is on the mathematical representation of such systems.

Ecological systems are composed of many elements which interact in a variety of ways. Each biological component of the system is affected by the physical abiotic elements of the system, and all the variables change not only with respect to time but also from place to place since the environment is heterogeneous. Discrete system elements interact and each component of the system affects all the others in one way or another. The complexity of the system of interlocking cause-effect pathways confronts us with a superficially baffling problem, and systems analysis was developed to handle such situations.

In general, a system is analyzed in terms of its components. The processes affecting each component are analyzed and described so that changes with respect to time and distance can be described and ultimately predicted. The interrelationships among the components of the system are also analyzed and a model of the system is usually developed and eventually tested by attempting to simulate, the consequences of alterations in the state variables representing components of the system.

Viewing an ecological system as an interlocking complex of processes characterized by many reciprocal cause-effect pathways, it can be seen that one of ·the principal attributes of a system is that it can only be understood by considering it as a whole.

After it has been determined which variables need to be considered in order to fully describe a system, a model can be structured. A model is simply some method, usually a mathematical equation or set of equations, which can be used to describe the behavior of a system (a watershed, air mass, etc.). The first models are generally conceptual models which simply seek to fully describe the system and its behavior qualitatively without making any attempt to quantitatively predict such behavior.

Models can often be used to predict the consequences of certain events or actions well in advance, thus allowing the public to consider risks and evaluate the costs, benefits of community action before embarking on a costly and perhaps disastrous courses.

Once a model has been developed which accurately describes the behavior of a complex system, it can be used in simulation studies to demonstrate how the system can be managed in real life for optimal benefit.

The process of modeling environmental systems

Model development must include comparison of predictions based upon the model with observed system behavior. A wide variety of models are available to describe the movement of water and substances contained in water, movement of materials in the atmosphere and the accumulation of substances in individual organisms or communities of organisms. If calculated behavior does not correspond closely enough to observed behavior, appropriate changes must be made in the model to make it more realistic.

The ability to explain and simulate events clearly varies with their complexity. An architectural model, although a replica in miniature of a building, generally reflects only the form and visual elements of the building while ignoring its structure. Nonetheless, it is a model of the building.

The elements of environmental systems models

In Design With Nature (1970), regional planner Ian McHarg demonstrated an inexpensive and efficient way to model major regions of the United States to describe their environmental systems and permit predictions to be made about regional consequences of specific actions by human beings and nature in and upon those areas.

In the first instance, the descriptions necessarily reflect the jargon and technical vocabulary of these independent academic disciplines, but models can nevertheless be developed for simulation of the operant natural, social and political processes of a region and these distinct perceptions can be arrayed in a layered multilevel model or plan reflecting reality, chronology and causality.

Geology

The principal long-term natural processes determining the course of future development in all regions will be geological. Bedrock geology provides the basement of a region and becomes the bottom layer in this type of simulation. Generally the geological events leading to the formation of igneous, metamorphic and sedimentary rock are measured in terms of hundreds and thousands of millennia. Bedrock geology serves as the physical foundation for plotting the evolution of a landscape.

Surficial geology or the manifestation of bedrock geology at the surface of the land provides a second layer. The major events determining surficial geological characteristics are those of the Pleistocene which began one million years ago and ended with the last Ice Age a little over 10,000 years ago.

Hydrology

The geologic processes and systems of a region are the principal determinants of ground water hydrology.
Groundwater is likely to be abundant in surficial deposits and sedimentary rocks, but is limited to cracks, fissures, and faults in igneous and metamorphic rocks. The current expression of exposed bedrock and the upper surface of surficial deposits defines the physiography of the region and represents another layer in this model, a layer which includes the most recent geological activity — coastal and fluvial deposits.

Although river courses are dynamic, many large lakes and major rivers may have occupied their corridors for thousands of years.
The hydrology of surface waters follows physiography in time and causality.

Soils can be considered the final step in the evolutionary progress of geological events, and are largely a consequence and expression of surface water processes and climate.

Vegetation and natural animal populations

The natural vegetation of a region depends on the geology, physiography, hydrology, soils, and climate of the region while the indigenous animal populations depend upon the vegetation.

Existing current human land use provides the surface characteristics which are most recent in time.

This kind of model can be represented by a series of maps at consonant scales. The primary value of such a model is that it is integrative, and demonstrates causal relationships among natural processes.

Causal relationships and environmental systems models

Mountains and hills reflect rock harder than adjacent valleys. Rock type definition explains physiography.

Surficial deposits conceal bedrock and reveal their own morphology.

Terminal moraines, outwash plains, drift, till, kames, kettles, eskers and other topographical features become comprehensible in terms of the geological processes from which they were formed.

The patterns of rivers and streams vary with the permeability of rocks and soils and reveal this in the extent and structure of the drainage systems. ·

The abundance of lakes often reveals obstructions to drainage by glaciation.

The forces of weather and gravity work on rock and produce soils.

Soil textures and patterns are derived from the parent material and the vegetation that has occupied them.

Soils mirror river courses, old and modern.

Coarse material remains at high elevations, while fine sediments occupy valleys.

Plants reveal the most discriminating perceptions of environmental factors. Elevation, slope, aspect, soils and climate are synthesized in the pattern and distribution of native vegetation throughout a region.

Animals, being mobile, are less localized than plants; nevertheless, animal habitats conform to vegetative associations.

Finally, at least until the Second World War, human beings can be seen mining where geology provides mineral resources, farming in conformity to soil productivity, shellfishing in estuaries, building on sure foundations, locating roads and railroads in river corridors and through mountain passes.

The ecological model just described reveals the underlying basis for such superficial perceptions.

Static and dynamic modeling

It can be said that even an ecologically sophisticated model is static and of necessity frozen at some instant of time past. Indeed, this is true, and any such model must become dynamic if it is to describe and predict even the near future. Nevertheless, important elements of such a model can properly remain somewhat static. Few geological events are so dynamic as to be consequential on planning scales measured in decades, with the important exceptions of earthquakes, beach erosion and deposition, fluvial processes such as floods and subsidence.

Surface water systems are likely to remain within existing geological corridors, and soils to retain their lower horizons within the time scale of human planning.

The native vegetation associations will probably persist or follow well-defined successional patters if permitted to do so by man.

Not all of the elements in this type of ecological model are dynamic to the same degree.

Bedrock and surficial geology can be considered together with climate as groundwater process.

Soils and climate can be studied to predict runoff, erosion and sedimentation.

Precipitation, runoff, and percolation can be examined as determinants of vegetation distribution and dynamics, while vegetation and land use can be considered as influences on microclimate.

As these and other relationships are integrated, the value of the basic data can be enhanced. There are innumerable sub-models which can be developed as parts of overall regional models. ·

This layered modeling technique pioneered by Ian McHarg leads to understanding of the causal relationships among the major phenomena and processes constituting the region as a system. It also facilitates identification and description of relationships among the elements of many seemingly unrelated elements and processes.

Mathematical models

Although mathematical models can be developed at various levels of sophistication and complexity, mathematical models must remain generally idealized present representations of reality and at the present state-of-the-art cannot include all the variations of all the elements of even the simplest natural systems.

Mathematical modeling requires knowledge of the physical aspects of the system being modeled as well as the mathematical techniques for operating upon the model.

In many ways, the characteristic of the model are influenced by the specific objectives of the model builder, and the techniques involved in analysis of the real world system will depend on the model formulated for its study.

Testing and validation of environmental systems models

That testing and validation of any model in terms of its consistency and conformity with the experimental and real world experiential data should be obvious. However, human judgment, is required at every stage in the analysis of complex systems in order to avoid building computationally unfeasible models or models which may be mathematically feasible but so oversimplified as to be non-representative of the system modeled. Enthusiasm by a researcher for a particular solution technique occasionally leads to modeling systems in a way that will permit the use of that particular technique, rather than modeling the system as it actually occurs in nature. This is particularly true in consideration of economics where unreasonable commitment to linear regression techniques often leads to misrepresentation of the environmental impact of business and government action on environmental systems and is becoming obvious in recent attempts at numerical modeling of global climate change.

Systems analysis is still to some extent an art wherein success requires a serendipitous blend of real world data, modeling, mathematical and scientific intuition, choice of the “right” optimization techniques, and often represents, in retrospect, the “propitious confluence of fortuitous circumstances.”

The vocabulary of environmental systems science

There are certain terms commonly used in systems analysis with which planners, attorneys and concerned citizens should be familiar.
The controllable and partially controllable constrained inputs to a system are called decision variables.

When each decision variable has been assigned a particular value, the resulting set of decisions is called a policy.

A policy which does not violate any of the constraints imposed by the system is called a feasible policy.

The set of all possible feasible policies is termed a policy space and may vary with time in space of many dimensions. (For example, air, water, soil, vegetation, and animal communities would each be considered “dimensions” in this sense of the word.)

The condition of the system at any time and place is represented by variables known as state variables.

Supplementing the state variables are the system parameters which may be constant or variable and are determined by considerations outside the system under immediate consideration.

State vectors are quantities which in addition to magnitude are characterized by direction in time (past or future), in space (any direction in any dimension), or both, and must include all aspects of the system which are or can be affected by changes in the decision variables.

The concept of a “best decisions” set or policy implies the ·existence of criteria by means of which the effects of any feasible policy on the output of the system can be evaluated. Such criteria are called overall objectives, and in most instances consist of many component objectives some of which are quantitative, while others are measurable at best only in an ordinal or qualitative sense.

If two objectives can be measured or described in the same units or terms and to the same general relative degree of accuracy, they are said to be commensurate.

Non-commensurate objectives are those which cannot be expressed in excesses of that already moribund system.

The objective function in environmental systems science

The objective function is a statement by means of which the consequences or output of the system can be determined, given the policy, the initial values of the state variables, and the system parameters.

Although conventional usage, particularly in economics has limited the term objective function to quantitative objectives that are commensurate, many environmental systems include non-quantitative and non-commensurate objectives, which may account for the reluctance of many economists to consider environmental factors in cost/benefit and benefit-risk analyses. ·

Weighting and scaling factors can be used as means of combining multiple objectives of varying dimensions into a· single objective function, but such factors are usually determined politically and socially rather than mathematically.

Formulation of an objective function is a major concern of systems analysis, and characterization of the appropriate restrictions or constraints on the operation of a model is one of the most critical steps in the process of formulating an objective function. There are natural and physical constraints, economic constraints, societal constraints, and political constraints limiting the operation of any real environmental system.

Environmental systems optimization considerations

There is no single or “best” optimization technique which can be applied to any specific problem in environmental systems analysis. Each of the techniques available has advantages and disadvantages, so that selection of any specific technique involves consideration of many factors including:

the structure of the objective function and constraints inherent in the formulated model
the nature of the data available as inputs to the model
The level of accuracy of the solution sought
the characteristics of the computers available for solution of the problem
the computers and computer processing time available.

Optimization methods are generally considered in two groups characterized by the mathematical techniques associated with their implementation: Control theory with its classical roots in the calculus of variations, and Operations Research.

Operations Research which contributed substantially to the success of the Allies during World War II deals mainly with programming analysis of the mathematical model in order to achieve a specific solution goal. The word “programming” when used in the context of “mathematical programming” is analogous to “planning,” and should not be confused with computer programming, although computers generally perform the iterative mathematical computations required by many mathematical programming techniques.

The future path for environmental systems modeling

Until recently, ecological studies have usually been limited to consideration of small sites by small numbers of scientists. The significant insights that have been derived from such studies can now be used to quantify the great masses of data provided by our national remote sensing efforts.

When relationships among individual elements of major environmental systems have been identified and eventually quantified, predictive models can be developed by means of which the consequences of human activities on natural systems and the modification of natural processes by mankind can be enumerated and quantified.

Environmental systems science meets the need of those responsible for public policy, particularly with respect to land use planning and resource management, to understand the system of interacting elements or component parts of the social, economic and natural environments and how any proposed human activity they are considering may affect the entire system or parts of the system.