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The overriding difference between what faunal managers are doing now and what a manager using a systems approach does is feedback. Now there is little feedback within the arena once known as "wildlife management." Feedback occurs in biological systems (e.g., Atkinson 1965, Bayliss 1966, Smith 1968, Jones 1973), and appears to occur in populations, in ecosystems, and abundantly in social systems. This chapter emphasizes the dominant role of feedback in systems thought and application, and presents several principles of using feedback.
Feedback discriminates the systems approach from a systematic approach, management by objectives, adaptive management, or a dozen other fads in managerial expression. The modern faunal system manager will be a master of feedback, one of the control theorist for the complex human ecosystem. As cybernaut, the new steering person, he or she can guide people and nature to lasting preferred states of the forest and its resources.
Feedback sounds like a special process. It is much more; indeed it is an entire subsystem with all system components shown as follows.
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| The general system of modern general systems theory. |
For feedback to operate, there must be objectives, typically Types 3, 4, and 5. There needs to be a set of primary objectives unified into a system performance measure of some type along with a set of constraints. Without these, there can be little or no feedback (which largely explains its absence!) If we use the well-worn analogy for feedback of a thermostat on the wall, the objective is "to achieve a room temperature of approximately 68 degrees F." Inputs are needed to determine what the system is doing. (The thermometer collects data on room temperature.) Several processes are involved, namely comparing the inputs about the current status with the objective and, based on findings, changing the operation. (The furnace or air conditioner is turned on or off depending on the difference detected.) Feedforward does not exist in natural systems to my knowledge, but in human systems. Feedback monitors this subsystem, correcting and improving it, and adjusting current responses to assure smooth or efficient transitions to the new conditions.
In all cases, feedback is a changing and correcting subsystem. Yes, it monitors, it receives and stores information, and it processes it, but most importantly, based on the system objectives, it takes corrective action.
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Feedback can be conceived in a simple diagram (Fig. 5.1), a part of a system. The manager exists at A and has made many past decisions and taken various actions or made plans. The next step is some action to be taken symbolized as box B. This could be a simple act such as fertilizing a wildlife food plot or a complex one such as establishing hunting season limits. Box C is the managerial feedback subsystem action. The manager may plan to spread 1000 kg of fertilizer, go to the field, observe the color and density of the present plants, and adjust the amount to 850 because of the condition resulting from previous applications. The consistent picture is one of any act potentially affecting itself because of a prior condition. The affects can be increasing (multiplicative or additive), decreasing (multiplicative or subtractive), or stabilizing (both of the above). Catalytic action may be generalized as one of the above three.
If there is a delay in the feedback, then corrections are not likely to be as desired and systems can be expected to fluctuate as in Fig. 4.5 or 4.6. Delays in analyzing data from game harvests and adjusting the next season result in typical failures and suboptimization. Biological systems tend to have almost instantaneous feedback, keeping the surviving animal sensitively attuned to and adjusted to the environment.
Systems with feedback must have objectives. When feedback is missing, there is evidence that there are no objectives. Try to imagine a new house with a thermostat without any means for the owner to set a desired temperature. Without a thermostat there is no temperature control. Feedback systems in faunal systems are needed; they need to be created, "installed", and set in operation.
A set of objectives can be translated as being a description of a preferred state. Of course this preferred state may be dynamically changing but at some time when a decision must be made, a state does exist. Novick and Alesch (1970:6) said:
"A system of indicators [success criteria, Type 3] is critical for helping to determine changes in the state of a system. Whether ecosystems are purposive and have innate objectives is worth further study and debate. For government to exercise a cybernetic function, it is necessary also to have descriptions of preferred states for the various systems with which government is concerned."
Indicators are not sufficient to make a good system. The system itself must be "wired up", the power turned on, and feedback continually making adjustments.
Norbert Weiner and associates decided on the name "cybernetics" for the "science of communication and control" (1954). It was derived from a Greek word for "steersman." The manager with hand on the ship's rudder or other figure easily comes to mind. There is the general notion that biological and ecological systems tend to be and often are homeostatic. They develop an equilibrium about a condition. The manager may be part of that system. Often others perturb that system; the manager may be able to bring it back more quickly than if it is left alone, to homeostasis.
Another part of cybernetics and the calling is that it accepts complexity in systems (Beer 1959:98). It also accepts variation, of probabilities in systems.
Real life, in contrast with theories about it ... is likely to reveal error. Real machinery, in contrast with the blueprints of machinery ... is likely to go wrong. Orthodox scientific research is prone to regard these errors as lapses from its own concept of the ideal ... an atypical response is not so much a lapse ... but a member of a statistical population of approximations to a norm. It is this approach which informs cybernetic thinking on the issues of imperfection, miscalculation, malfunction and breakdown in the multifarious "machines" which it studies.(Beer 1958)
A faunal system could be one such "machine."
Stability is a general quest studied in cybernetics. Companies and economies are very interested in stability. The probabilities of failures or perturbations are of interest. Margalef (1968:3) observed that "in cybernetic systems that occur naturally, whether the meanders of a river or organisms, the only test to pass is the ability to remain." One sequel is the study of how to prevent perturbations. Backup systems seem highly relevant in designing faunal systems. The quest is to have sufficient systems but at low cost. Hardly discussed, backups in designed systems are needed...from budgets, to vehicle failures, to research proposal delivery schemes, to critical staff losses.
In CAP6144, the reader may insert values for variables in the managerial equation:
Qt+1 = Q* - (S-K) (Qt - Q*)
or in
bt+1 = B - (S-C1) (bt-B)
from Chapter 4, then to estimate the amount that each might vary (for whatever reasons) under reasonable conditions. The objectives are never clearcut so Q* may be "soft" (plus or minus an amount) or just changed unexpectedly up or down in a year. Weather and other variables can make annual outcomes (Qt) vary, and control of the system, K, can vary due to causes ranging from a manager's spouses sickness all the way to his or her laziness. S, the natural system's tendency to continue along an established ecological pathway can be punched out by a lightning fire or an insect epidemic. In the second equation, only benefits are manipulated but C1 is viewed as the control that can be exercised by the money spent. Depending on the inputs, symmetry of Fig. 4.5 disappears and something akin to 4.6 appears - a most familiar graph of local conditions! The manager's feedback design responsibilities are depicted in 6.7 - how to create backup, fail-safe, ameliorating, and mitigating subsystems to damp these well-known and fully-expected fluctuations.
A reason for loss of legitimacy of a systems approach is that expectations may exceed the capability of the system to deliver. Similarly, a thermostat set for 1100F may create a fire in the house. Faunal agencies seem to get into situations of promising more than they can deliver (or delivering more than they promise, as when game or songbirds become vertebrate pests). There is another minor problem with precisely stating objectives. The problem is one recognized intuitively (or otherwise) by politicians. Specific objectives tend to increase expectations, for they are looked upon as promises for the future. Recognizing this may happen, the faunal system manager can build a feedback system so that reasonable accomplishment time can be stated in lower-order objectives, and other provisions can be developed to reduce the frustrations and dissonance of the expectation-satisfaction imbalance.
Feedback subsystems must not be seen as change systems. While change is often needed, feedback systems will not be properly designed unless they can also stabilize the state of a system if it presently meets objectives.
Feedback systems take energy; they cost money or time. Long-term costs of the feedback system versus net systems performance must be observed as a kind of feedback to the feedback system itself. Detailed checking of expense account vouchers in public wildlife agencies is an example of how the costs of a feedback system can escalate far beyond any benefits derived from it. Spot checks (sampling), deterrence, and supported morality will keep most such accounts in line. If all personal expense accounts were illegally doubled, would that loss be equal to or greater than the costs of checking and rechecking done by supervisors and clerks throughout an agency? In general it would seem rational for the costs of "checking up" not to exceed the losses from not checking. The feedback system, itself needs a feedback mechanism, a simple computer statement such as:
If median annual errors detected are less than annual staff costs, then subtract from staff time allocated to making the checks next year.
One aspect of control theory is that systems may be designed to "teach themselves" rules for operation (Beer 1959, Simon 1957). Natural systems exhibit it in the short run (predatory behavior relative to traps) and long run (genetic information). Cybernetics seeks to harness the ability of a system to teach itself optimum behavior. Hunter and user systems (Chapter 13) are conspicuously in need. With the right information of the right type to separate publics, it seems likely that people will draw conclusions on their own about optimum behavior.
Consistent with the concepts of learning theory, it is important that feedback be seen as a positive and rewarding influence as well as a negative or "cut-back" influence on operations. Within public faunal agencies there are some rewards for good work, few punishments for inferior performance. C'est la vie can become rampant. If it were not for a personal commitment to the faunal resource and some peer pressure from several wildlifers who trot when they could walk, the typical wildlife agency would appear to have the vitality of a state highway work force.
There are many ways that rewards and punishments can be implemented. In some cases, a small act of leadership will suffice. In some cases, an unpleasant decision must be executed and an associated temporary entropy of the system experienced for its net long-term health.
Only as an example, but one given to point out the need for continued search for parallelism and isomorphic solutions to wildlife problems, is the finding by Drenick (1960) that under very weak constraints on the type of life distributions, complex (mechanical) systems that contain many components tend asymptomatically toward a constant number of failures per unit time. This is a situation which can be described by means of a model using the Poisson distribution. These mechanical failures may be "managed" or they can be studied as the natural state. Analysis can then suggest whether action is justified. There appear to be parallels in staff work within the wildlife agency; in watershed failures within a management area; in species failing to achieve their potential on a management area. By not focusing quite so intently upon wildlife, and looking around at other systems, it seems to me that there are solution algorithms and subsystems, already constructed and ready for revision and use by faunal managers.
I know of no one who comprehends feedback more fully, both at the micro and macro levels than R.L. Ackoff. His book, Redesigning the Future (1974) is especially useful for those who will read it from the point of view that it is a blueprint for major feedback systems. There are dimensions of the counterintuitive or perverse consequences of decisions that are implicit in the concept of feedback systems for large systems. The subversive idea (subversive in its being hidden, rather than being evil) is part of a full-blown concept of feedback.
Feedback, while a system component, is also a philosophical stance. When the feedback force is seen as K in the above equation, and K is the managerial action, then the manager "becomes" K. The manager is the control agent, potentially causing the system to fluctuate or bringing it under control. "Take charge!" is the public's command for the faunal system manager; the magnitude of K is the extent to which that is done due to risk-taking behavior, prior experience and knowledge (education), natural ability, or constraints imposed by the budgetary, working, and physical environment.
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The above equation is for objectives, but the form is useful for expressing other feedback relations. I recall understanding it first in Smith (1974). Beer (1959) spoke of one aspect of a feedback subsystem as being "almost sentient: watchful, never missing its job."
Fig. 4.5(previously shown)is a useful diagram of a system with feedback working. Change is shown in Q over time. It is equally useful to concentrate on K, the manager's control effort, by observing a diagram de-emphasizing time as shown here in Fig. 5.2.
The system's performance (any measure -
call it P) at t+1 is observed in relation to performance at other times. The picture is typical of a managed system spiraling toward some state. The objective may be depicted as in the figure. The deviation of the projected end-condition from it, from some condition near the vortex, is the faunal system manager's problem - typically solved by work with the population, the environment, and simultaneously with people.
The simplest feedback-related act of the faunal system manager will be to make proposals in terms of objectives of the form of D in Chapter 4. Few people will make or seem to have the time to make perceptive analyses of proposals for funding. The proposals that go the farthest to meeting objectives are turned down unless they are fairly inexpensive or routine (i.e., having low risk). Pressure for cost effectiveness (i.e., achievement of objectives per unit cost) not efficiency (i.e., lowest per unit cost) will help create an environment that is salutary for feedback.
A tree-planting rule would be an interesting feedback mechanism. "No tree may be cut until its replacement (at least 2 years old) is certified."
There are many examples of existing or potential feedback subsystems. A wildlife law enforcement evaluation system can provide a monthly or periodic agent's report to the agent, furnishing him or her with personal, confidential reports on how well he or she is performing relative to others, relative to a set of stated objectives, or even relative to regional standards. To have meaning, to go beyond being a monitoring report and to become feedback, the report must suggest means by which the agent's performance can be improved. A real need is to move from "monitoring" and "administrative reports" to systems promoting desired change. This can be a computer-generated type feedback.
The MAST system (Lobdell 1972) can be used, not only to allocate, but also to evaluate current performance and practices relative to perceived objectives.
Terrestrial ecosystems can be monitored, as aquatic systems are now monitored, and then devices can be added that provide early-warning of problems and operational changes.
Timber-trend analyses provide a type of regional monitoring, but until these are better integrated as feedback, they are at best merely input to decisions about industrial and public forest policy.
The computer can be used at all levels far more effectively than it has been as a feedback device. Emphasis on input-output relationships in systems will be laughable many years hence in an era of major use of feedback functions.
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Last revision May 22, 2001.