Modern Wild Faunal Resource System Management
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| by R.H. Giles, a lecture presented 5 June, 1979, at the American Association for the Advancement of Science Divisional Symposium on Science and Land Use Decisions, 16th Annual Meeting, Pacific Division, AAAS, Moscow, Idaho. |
Time, space, energy, and variety and their interactions are the major topics of the paper. Hope is suggested in computer models, in new concepts of matrix manipulation of data, in improved research planning, and in valued energetics.
This paper is about heuristics and hope. Heuristics is not a widely used word but an exciting one, full of subtlety and potentially quite rich. It is not a scientific word for it is much too imprecise, but it carries information and has its own ambience. Roughly, it means the way one finds out or discovers. Strangely (at least to me) hope is no longer widely used, perhaps because it has excessive metaphysical connotations. Nevertheless hope remains a good and useful word that includes concepts of both goals and expectations of their achievement. "I hope that X occurs" is a statement about the perceived desirability of X and a level of intensity of that desire. Hope is a statement about the pathways to that future instant when X begins.
Heuristics and hope must be etched in your mind, for those may be the only things you will ever remember about this paper. The rest will be cosmic otherness, losses that might be tracked by learning-forgetfulness curves and probability functions for ideas accepted. The desire I have is that, in remembering these words, the reader may later reconstruct a personal rationale, as partially suggested in the following paper, for it is on that whole personal reconstruction which must be built a viable science for people. That it might be done is the ground for hope.
The reader is encouraged along a tortuous, conceptual path. The goal is to achieve a concept of science intimately relevant to the future.
The Basic-Applied Dichotomy
It is easy to understand and appreciate administrative, budgetary, and legalistic reasons why there needs to be a taxonomy classifying basic and applied research. Only recently has it become evident how harmful that taxonomy has been to science. A premise of this paper is that science is. It exists, multidimensional but continuous. The fundamental difference between basic and applied, though there are a few others, is that of when the conclusions reached are applied. Basic research seems to take longer for its findings to be applied, a trivial distinction on a temporal continuum. Taxonomic and administrative problems arise when basic research is quickly applied and so-called applied research findings languish in the shade. There is no longer any meaningful difference between these taxa; they are artificial and invalid under the rules of nomenclature and should be abolished as intellectually, personally, and organizationally divisive. They are the root of great ineffectiveness in the scientific community -- especially those dealing with land use questions. By focusing in the future on wholeness, similarity, and generality, then predictions will be more correctly made.
As an example of ways science may be handled in the future, and there are dozens, let scientists not engage in the debate over whether studies of the endocrinology of mid-line color changes in certain stream fish are basic. Such studies are the substance for interpreting the effects on fish of non-point water pollution from farming and forestry practices. When pollution disrupts the endocrine system and prevents color change there is impact. When color change is a basic sequel in a courtship ritual, then its failure to change causes reproductive failure. The real land use and impact question is not whether pollution killed fish, but whether it resulted in a generation not being born. From research such a question can be answered, understood, and corrective changes made. There is only one science.
Sequences
It seems conspicuous when looked at directly that a major aspect of the research application-rate problem above is the problem of the sequence of discovery. Perhaps it is obvious, but emphasis is needed to prevent losing sight of the sequence phenomenon in research and to avoid attributing more to the basic-applied dichotomy than it deserves. The apparent scientific successes are those that by chance or planning fall in a fortuitous sequence. The fate of absolutely equal quality research (by any criterion) is a function of the environment in which the results are placed.
The analogy of a three-number lock combination is somewhat instructive. Three correct numbers will not allow entrance; only numbers and the proper sequence. The odds of the proper sequence are quite low. This realization can put into perspective efforts at technology transfer and can explain to those with over-expectations for science, why progress may not be as swift as desired.
Such explanations can easily become excuses for lack of progress. A sequential strategy of research is only appropriate if rigorous planning is done. Ackoff (1962) delineated sequential and simultaneous research strategies and their counter-balancing forces of costs, time, and risks. Sequential research has lower costs, takes longer, but involves less risks than does simultaneous research. Simultaneous research is a broad, multi-worker, multi-lab approach usually taken in a short period. The author is convinced that the scientific community has little time to aid people significantly and to preserve current living standards, at least for U.S. citizens. Only simultaneous assaults on major research issues such as land use seem appropriate. That conviction arises from observations of a host of environmental problems, the increase in counterintuitive consequences of many of the most altruistic actions, and the rate at which thresholds of tolerance and supply are reached. Although the author is an advocate of simultaneous, team assaults on major problems, in such projects there may be inefficiencies and partial failures. Nevertheless, such projects seem advantageous because they buy society time. They put conclusions and discoveries in the hands of decision makers and shapers of society.
There exists today an economic order that appears unwilling to tolerate costly simultaneous research programs. The programs are needed, desperately, but they seem unlikely. Society will trade time for risk and time for cost. Instead of buying time, it will spend it. This is very saddening; it is a decision that can be reversed, but not likely. Sequential research therefore is most likely to be done because of cost constraints and the social ignorance that says: (1) we have unlimited time, and (2) the burgeoning society with its demands is not at great risk.
The only current hope that can counter this failure is in research planning. Since sequential research seems inevitable, then planning can reduce its costs, and importantly, allow all possible haste. Planning can reduce its major disadvantage of time required and improve sequencing. Research planning has been advocated for years. Its need is voiced again, but perhaps in more meaningful terms than the past. The planning needs are for solving problems like:
These are problem statements appropriate for high science. They are timely, researchable, essential, and will require assiduous application of the scientific method -- from the most esoteric and micro- to the most philosophical and macro-approaches. They cannot be achieved in any period of time that has relevance to the human condition without the most profound and scholarly thought, without at least one or more people thinking them all the way through and writing or diagramming this thought. Previously there was not enough known or the technology was unavailable to do so; these conditions have changed. The plan that will result following such thought must exist, it must be charted, it must be a shared view, it must be begun, and it must be altered as need arises. With all this, the goal must remain and pressure and leadership must be exercised to achieve the goal. of course every scientist does not have to "join up;" there can be enough programs to occupy all scientists and require more. There need to be "outliers," challengers, and those with the alternate hypotheses, and they should be supported. There are enough parallels in biology to be convincing that long-term survival is closely tied to energy spent on monitoring, dispersing, and diversifying, and that society needs to fund these mutant efforts. But there must be a plan; the risk of planning must be assumed. The risk of research planning must replace the risk of no-planning.
Research planning advocated herein has no similarity to the typical agency document called a research plan, little more than an open palm to Congress. Neither is it the gyrations of or mere presence of that glib, handsome cadre of employed planners. Neither is it glorified statistical services or platitudinous reports. Planning is seeing where we as a world society, as a nation, must likely be in 50 years, charting a minimum course to that destination, and creating decision aids to allow changes along the way. Planners can say: "At least we must know B or at least we must have greater precision in our estimates of rate Q." This is possible in land use; it is probably possible for most of science. Of course the living, dynamic mind of people will not be satisfied with a 1979-1980 concept, but the course will be set. Minor adjustments along the route to any destination are expected.
Occurrence
Dr. Byron Cooper, the late dean of Appalachian geologists, showed the author a community water tank placed on a rock outcrop and told him with unusual confidence that the particular rock would fail and the tank be destroyed- -but he could not tell when. The people below it lived in ignorance. Thousands of people live on flood plains, fully aware of flooding, willing to do so with certain knowledge of its occurrence. They do not live in ignorance, only with uncertainty about when floods will occur. There are dozens of similar examples of the mixed personal and social calculus, and Starr (1969) suggested that people make conceptual third-power transformations when dealing with risk, i.e., they are prone to equate hazards to the third power of the benefits, real or imagined. Society has not sorted out these complexities. It probably operates intellectually in a linear domain where the worst imaginable risk is loss of a member of the family.
This socio-intellectual state neither justifies nor excuses scientists' snipes at those who create models and cannot match temporal events very well. I am of the opinion that while risk taking is investigable, it is ascientific. It is a human trait, a function of a physiological, psychological, sociological, theological, and economic milieu. It cannot be observed directly, only behaviorally. Its expression in behavior can be manipulated. There is no way to avoid a risky world: uncertainty is one of the immutable laws with which people must live. Thus, like assigning weights or expressing preference, assigning acceptable risk levels is a human act and at least for the purpose of this analysis, ascientific.
There are scientific laws, and these form the basis for a belief that occurrence of a class of things can be predicted with near certainty. The time and place predictions are worth working on. I view estimating flood rates as a scientific activity, just as I do predicting weather and the occurrence of solar and planetary events. These are activities dealing with occurrence and at least somewhat with their temporal precision.
Criticism was once leveled at modeling, a deductive aspect of the scientific method, in terms of the example that it could not predict the emergence of a new leader in a Vietnamese village who significantly altered the battlelines of that past war. I contend that viable models can and probably should have predicted the occurrence of such a person. "Leader" is not an unnamed genus. The time and place are certainly problems, but in the future such events will probably be at least as predictable as are flood and earthquake events.
The precise details of the future are not needed even if it is possible to know them. It would be a very boring world. Instead, what is needed are general characteristics of the future, expressions of orders of magnitude, and the near-presence of thresholds of concern. As Starr and Rudman (1973:360) said in a parallel vein for land use:
"While it is obviously not possible to predict the content and time scale of specific technical achievements which may be important in future social change, it may be feasible to see the range of the general characteristics of growth of that societal resource encompassed by the common term 'technology'."
Similar negative comments have been made about biologists' inability to predict micro-events about wildlife models. Could the formation of an anti-hunter group have been predicted when law Q was modified? It could have. At least the option could have been explored, and strategies then developed for dealing with occurrences of high probability. Whether it would occur in a particular area at a particular time or with a particular intensity of feeling implies the existence of more knowledge than is had for even some of the better-known aspects of science. Such knowledge is not achievable at present rates of acquisition of knowledge, with present organizations, or at current funding over any reasonable future period, say the next 500 to 1000 years. It is unreasonable to continue to behave as if it could be achieved. An alternative will be suggested.
Returning to the problem of sequence above, the forester is well attuned to the site that is "perfect" for one species but is stocked with another. A timber stand exists if a seed-source was present, and if a fire occurred after seeding, and if the ground conditions were right for the seed, and if the rain fell before or after the fire. A stand is a function of sequence as much as factor. The forest scientist with complete knowledge (in the theoretical sense) of all forest factors cannot predict a priori a stand because of the innumerable sequences. yet foresters can predict a forest will occur and over time what forest will eventually exist -- and persist indefinitely. This knowledge (or lack of it) is not discouraging. It allows the forester to explain what he sees; it allows him to compute with various degrees of probability the future states of the forest on any land. People desire certainty; it does not exist. Such awareness allows people to operate with less entropy or frustration , more attuned to the probabilistic world.
Duration
The expanding confidence bounds on regressions are familiar. The farther into the future one projects, the less confident one tends to become. But prediction is not projection and the statement about increasing confidence bounds does not necessarily apply, especially if attention is given to the occurrence phenomenon above. An example in resource use may be instructive. Elk forage following fire or clear cutting is known to follow certain rules of succession, being irruptive, then declining to a fairly constant state over time (about 50 years). There are difficulties in predicting the forage in the first 10 years (the confidence bounds are quite wide), but few later. Aggregating these production functions can yield a far truer picture of regional elk forage in the distant future than the near future.
The mental image of sweeping, expanding confidence bounds on linear regressions has confused research planners. The future will not be like the past. Most natural resource experts know far more about the independent variables in the equations than they admit and some things (like elk forage) can be very closely estimated for the practical and long term future. The practical and long term future is for at least 50-years. Society is probably still behaviorally or genetically operating as if people had a life expectancy of 20 to 30 years. Changing concepts of future reality have not matched gains in life expectancy.
To understand land use change, to predict, one must understand succession (Golley 1977). Further advances in this area are needed, but they are sufficient to allow scientists to estimate now the long term consequences of almost any act resulting from a spill of toxic material, construction of a powerline, or building an airport (Giles and Snyder 1970). The interaction between sequence and duration is fraught with difficulty. Present society is beset by a host of poorly made, denigrating decisions of the past. Large dams, contaminated areas, exterminated species, and desert range overgrazing are examples. These are irrevocable. Their rate of occurrence has probably slowed, but it is still a positive rate.
Students work with the author's computer game called Waterloo, trying to stabilize the shrimp in a coastal estuary. The shrimp are a biological integrator of most of the factors of the watershed. Only late in the game do they usually realize that they cannot replace the silt lost to beach erosion by their watershed decisions. The replacement silt from the watershed is all trapped behind a dam which was built prior to their involvement and a part of the game. They are sadden and frustrated by this discovery. The best of managerial knowledge--perfection if it exists--cannot overcome the constraints placed on their system by past generations.
The above role of past decisions can alter Leopold's useful analogy of land health and the creation of a dynamic environment in which people may discover their humanity. Such change can cause the analogy to be replaced with the concept of the incurably ill in which the land manager is the nurse solely intent on continuing survival and keeping the patients from hurting each other.
Retrospect
Lest there be confusion about prior emphasis on heuristics and hope, a review may be useful at this point. Herein, the pathways have been analyzed to discover the role that science has in predicting futures. To this point a unified humanistic concept of science has been presented. It has within it a concern for the time when discoveries will be used for people, the concept that research can buy society time in this critical period, and that society is likely to opt for more sequential than simultaneous research. To reduce the impact of this decision, it is important that rigorous research planning be given higher importance than ever before. Contrary to some who contend that prediction is out of the ken of science, the author holds that it is presently well within science, has historical roots in astronomy, and needs to be given more emphasis, not because of its shortcomings, but inclusive of them for the utility it has for shaping a reasonable environment for people. The limitations have been discussed under interactive topics of sequence, occurrence, and duration.
The Problems of Space
There are scant research papers that provide the latitude, longitude, and elevation where studies were conducted. So many phenomena operate in this real three-dimensional space (e.g., electromagnetism, insolation, gravity fields) that additional controls may be gained on the variance which typically is observed. Besides this subtle point, it is possible to begin to focus on site-specific prediction. In Virginia the author has a data base of about 50 factors in each of 1.1 million, 27-acre (1/9th kilometer) cells. This allows, for example, computation of the likely impact of a high voltage power line, if it were in place, using 12 dimensions of impact, 42 critical characteristics of the cells, and a 30-year economic expectancy. The author and staff are currently developing a computer system with the Animal and Plant Health Inspection Service, USDA, to achieve nationwide analyses and optimization of farmer or rancher holdings on request. The intent is to bring to bear, on-site, the findings of science to make them relevant to the decision-making tasks of the owner.
Each point or cell on the Earth may be characterized in hundreds of ways. Computers are now capable of storing and retrieving these data and putting them together in the best ways currently known. These are the intricate relations of any site. A new scientific orientation to the three-dimensional spot can produce huge gains in predictive capabilities. There is no way to visit each cell in Virginia for research (to do so even for one hour each would take over 60 working years). Idaho has 2.1 times the area of Virginia; there are a few states in between. Scientists have classified and clumped data in the past to an amazing degree. There are regions and range maps of all types; now thee exists the technology to dis-aggregate and discriminate. It is time to start the reverse journey.
The spatial domain is not unrestricted. Certain life forms have attitudinal limits. These can be used to eliminate the grossness and unpredictability of many animal and plant range maps. predictability can be improved by managerially restricting from use certain areas. Land use zoning by people is somewhat related. A new zoning based on prediction is possible. Because we know that certain plants will undergo moisture stress in their lifetime if planted in cell of coordinate x,y,z, then let managers be sure that they are willing to assume the risk of that loss (or pay the total long term costs). Let society be sure pesticide use will not be required in a cell when that cell is near another one in which occurs a highly threatened life form. By such action and containment it is possible to reduce the mismatches in predictions and reduce the large number of alternatives which must be explored in struggles to see the future.
If site visits to the land are impossible in real time, Landsat imagery of only limited usefulness, and funding unlikely to increase substantially, then what are the alternatives for the nation and its scientists? Certainly better planning is one answer. Research direction and leadership, a past anathema, will be essential in the energy- and money-short future. Far more attention must be paid to sampling in time and space. No scientist will add excess animals to experiments having carefully computed sample sizes. No nation can afford limited or excessive research projects; the value of n, the sample size, must be carefully computed. Attention must be given to holistic computer models, particularly simulations that allow planners and managers to ask "what if .. . ?" questions assuming goal sets as well as certain action proposed on the land. When equations are not known, then subjective probability needs to be used, computing using the best current knowledge in a system with abundant feedback over time. Within these development there is reason to be hopeful about the future.
The Energy-Matter Problems
Not enough effort has been spent on the net energetics of systems. Adopting an energy metric provides an invaluable aid to modeling (Odum and Odum 1976). Integrating various researchers' work and making tradeoffs and comparisons between quite different concepts can be expedited among these who adapt the metric and become attuned more closely to energy transfer and its loss relations in many systems.
The Variety Problem
Variety is a general word for variance, juxtaposition, richness, various aggregation indices, and diversity. It is interactive with the above topics. Knowledge of it adds another dimension and thus, increases the potential to predict and control temporal as well as spatial occurrence. It allows such concepts as likely yield and site quality to be quantified. Modern science tends to be probabilistic and thus, is rooted in population theory. Variety or variance is a population characteristic. Inductive science has a role in predicting the future of populations. There is little it can do for the absolutely unique event. It is far easier to remember that ecosystems are unique than that animals are unique. This premise needs careful handling for it can be misleading. In the same way that every person is said to be unique, every animal is also. Every geographic cell on the Earth's surface is different, by at least one characteristic. Classical experimental procedures generally assume internal similarity and work to achieve control over external variables. Such abundant computer data storage is now available that it suggests that aggregation into statistics may not be necessary. Individual plants, animals, and ecosystems--even humans--may be allowed to retain their identity and uniqueness in a large matrix. They are assigned a place in a sequenced, scaled, n-dimensional topology. The observed individuals occupy space in a hypervolume. Subsequent observations must fall within or near the volume. As conditions change over time due to chemical, physical, and human forces, the position in the matrix may change. The future is limited to nearby empty cells, under the assumptions of uniqueness and a largely continuous real world. The options are narrowed; decisions for the future are made with less uncertainty.
The Resource Tetrahedron
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| Expectations of results drive research systems |
Literature Cited
Ackoff, R. L. 1962. Scientific method: optimizing applied research decisions. John Wiley and Sons, Inc., New York, N.Y. 464 p.
Ackoff, R. L. 1974. Redesigning the future: a systems approach to societal problems. Wiley-Interscience Pub., John Wiley and Sons, N.Y. ix + 260p.
Giles, R. H., Jr. and N. Snyder. 1970. Simulation techniques in wildlife habitat management, p. 637-654 in J. A. Bailey, W. Elder, and T. D. McKinney (eds.) 1974. Readings in wildlife conservation, The Wildlife Society, Washington, D.C. 722 p.
Golley, F. B. 1977. Ecological succession. Benchmark Papers in Ecology, Vol. 5, Dowden, Hutchinson and Ross, Inc., Stroudsburg, Pa. 389 p.
Odum, E. P. and E. C. Odum. 1976. Energy basis for man and nature. McGraw-Hill Book Co., New York. x + 297 p.
Starr, C. 1969. Social benefit versus technological growth. Science 165:1232-1238.
Starr, C. and R. Rudman. 1973. Parameters of technological growth. Science 182:358-364.
Watt, K. E. F. 1973. Principles of environmental science. McGraw-Hill Book Co., New York. xiv + 319 p.
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