The Nature and Utility of Traditional Ecological Knowledge

by Milton M. R. Freeman

Increasingly, the published scientific literature and the convening of conferences and workshops reflects the growing awareness that there is a legitimate field of environmental expertise known as traditional ecological knowledge. For about a half century anthropologists and some animal and plant taxonomists (e.g., Mayr et al. 1953:5) have recognized the accuracy with which various non-western peoples have identified different species; indeed, such "folk-taxonomies" include more than just those food or medicinal species having obvious practical utility. The comprehensiveness of the taxonomic system suggests that the extent of traditional knowledge may be quite profound, and that, indeed, taxonomy is important (as in the biological sciences) as the basis for building extensive systems of knowing about nature.

More recently, many scientists have begun to understand that such traditional knowledge extends far beyond what in western science would be called descriptive biology, beyond knowing how to identify different species of animals, or describe their feeding, reproduction, or migratory behaviour. The knowledge possessed by such tradition-based, non-industrial societies is essentially of an "ecological" nature, that is to say, it seeks to understand and explain the workings of ecosystems, or at the very least biological communities, containing many interacting species of animals and often plants, and the determinative role played by certain key biological and physical parameters in influencing the behaviour of the total biological community.

In the recent social science literature this aspect of traditional knowledge has to a large extent been documented, more especially, for a large number of so-called foraging (i.e., hunter-fisher-gatherer) peoples, from the tropics to the Arctic (e.g., Williams and Hunn 1982; Freeman and Carbyn 1988; Ruddle and Johannes 1991). It is important to note that such traditional ecological knowledge has been found to have management relevance, especially in regard to sustainable use of renewable resources (McCay and Acheson 1987; Berkes 1989; Freeman et al. 1991). It is also important in such endeavours as Environmental Impact Assessment (e.g., Freeman 1975; Craig 1989; Nakashima 1990).

Expressed another way, traditional ecological knowledge is more than merely esoteric; it is directed toward gaining a useful understanding of how ecological systems generally work, to how many of the key components of the total ecosystem interrelate, and how predictive outcomes in respect to matters of practical concern can best be effected. This is precisely what ecological scientists or wildlife and fisheries biologists attempt to do; however, the question remains: How successful are both groups (the scientists and the traditional resource users) in their efforts to understand these complex realities?

Why question scientists' environmental knowledge?

First, it must be stated that even attempting to define the task at hand in relation to such dynamic complexity (as ecosystems represent) is a daunting task. Not only do such biophysical systems contain innumerable interacting components, or sub-systems, but most basic parts (e.g., the micro-organismic component that accounts for the greatest proportion of the biological activity of the ecosystem) are largely unknown to science and for the most part ignored in the analysis. Most ecologists have little understanding or even interest in microbial taxonomy, physiology, or ecology, yet the classical approach to analysing ecosystem structure and function is largely built upon the presumption that such knowledge is controlled.

Then it must be remembered that ecosystems are subject to purely stochastic (or random) variation from place to place, season to season, and year to year. Of course, variability can be allowed for, but it cannot be predicted. Lastly, we might consider the problem of comprehending the ecosystem-as-a-whole, when the methods of science are essentially reductionist, that is to say, they seek to understand organisms or nature by studying the smallest or simplest manageable part or sub-system in essential isolation.

How good, one may ask, is a methodology that takes the exceedingly complex whole apart, and essentially destroys its components? Is the whole really only the sum of all its disassociated parts? Can we ever come close to understanding so complex and interactive a system by studying each part in isolation, by treating it as if it were a non-living machine?

Perhaps we can gain such an understanding through the above methods of study. However, the task would seem to require that immense quantities of research be conducted so that each part is in fact adequately understood under an almost infinite variety of variable and constantly refigured conditions; and then it would require the very careful reintegration of all these disarticulated pieces of useful knowledge in order to reconstruct the system as a whole.

Can we make ecological complexity more understandable?

Some might suggest that there are more practical and reasonable ways of trying to understand complex systems as wholes than by taking them apart and then laboriously reassembling all the once integrated bits and pieces to reconstruct a semblance of the former system-as-a-whole.

Traditional knowledge seeks to comprehend such complexity by operating from a different epistemological basis. It eschews reductionism, placing little emphasis on studying small parts of the ecological system in isolation from the dependent interacting biophysical milieu. It also recognizes that the reductionist approach is impractical in the extreme: even if one were to know everything there was to know about everything of importance under all possible combinations and permutations of variability, such an immense database would be impossible to work with in practice.

Given such apparent limitations of the scientific method and its inherent appetite, scientists are always calling for more research data, in fact, for more and more knowledge about less and less. Why not, by way of contrast, approach the problem from a purely practical, as opposed to eminently impractical, standpoint? Fishery scientists are among those making such pleas (e.g., Tanaka 1986) for a simplified, intuitively generated analytic approach, remarkably similar to the tradition-based system of knowing.

The traditional ecological knowledge (TEK) approach recognizes that a supercomputer of extraordinary sophistication does exist, and that it can work for all practical purposes with incomplete data sets. Indeed, it is able to creatively fill in many of the knowledge blanks, an absolutely essential characteristic in those cases where knowledge is not just unknown but, in fact, may be unknowable.

This supercomputer, the human brain, is programmed to collect and systematize knowledge, to intuitively filter out background noise and discern chaos, and to draw normative conclusions from various disparate data sets (via group experience extending through preceding generations) pertaining to the same general ecological system in all its varying states. The programs which run the computations in this supercomputer may be old, quite traditional in fact, but the data-base is constantly updated as new data pertaining to changing environmental circumstances alter the behaviour of the biological communities which provide the empirically derived data which the brain receives, stores, and analyses.

Why should one believe that this old-style intuitive approach to knowing is relevant to assessing environmental circumstances? First, it operates on a rational basis that underlies much scientific research carried out today. For example, it employs critical comparative analysis: comparing what is happening now with what is known to have happened in the past. Scientists also do this: they study variability in data sets and attempt to account for it.

However, scientists rarely have comprehensive data sets that take note of a variety of co-varying environmental features over long periods of time. Scientists continually warn of the need to accumulate "base-line" data, data against which future changes can be compared. Traditional knowledge-based systems already possess such data sets, often of sufficient length to cover several population "cycles" where periodicity may be measured in 70- or 80-year spans.
 

The Problem of Acquiring "Base-line Data"

Even if scientists were fortunate enough to have such extensive year-round, somewhat standardized observations, annually repeated for those particular species, it is most unlikely that they would have concomitant data pertaining to such all-season environmental conditions as temperature, precipitation, parasite levels, or any of a very large number of seemingly pertinent ecological changes occurring in the system-as-a-whole at the same time. These are just the data sets that accumulate in TEK systems, or at least tend to be recorded when deviations take place from normative expectations.

The essential difference between the scientist's approach to knowing what is happening and that of the tradition-based resource user is not the difference existing between the attenuated data base available to the scientist compared to the more extensive data set of the local user. Nor is it the reductionism of the scientist versus the holism of the local resource user, important as these particular differences may be.

Perhaps the principal difference is again epistemological: the scientist is concerned with causality, with understanding an essentially linear process of cause and effect. If causes of observed effects can be measured and understood, then predictive statements about future outcomes can be made and the natural world can be managed. But the non-western forager lives in a world not of linear causal events but of constantly reforming multidimensional interacting cycles, where nothing is simply a cause or an effect, but all factors are influences impacting other elements of the system-as-a-whole.

Linear approaches to analysis cannot be applied to cyclical systems, and, as everyone now realizes, ecosystems are in fact complex cycles of recirculating energy matter, and relationships. Nowhere does the Cartesian model of modern science fail so completely and utterly as in trying to explain the workings of natural ecosystems.

The Current Scientific Revolution and Understanding Nature

Physicists, as the leaders in the scientific revolution now underway, increasingly utilize words such as organic, holistic, systemic, and ecological in their understanding of the workings of natural events (e.g., Capra 1982:66). The recent findings of modern physicists are becoming similar to views held in many ancient mystical traditions, even though these traditional systems of thought are not necessarily known to the scientists who make these recent rediscoveries (ibid: 66-67).

In relation to scientists increasingly appreciating the inherent limitations of the classical scientific way of analysing nature, or ecological systems, reference was earlier made to the traditional ecological knowledge-based approach that denies the usefulness of a reductionist approach to seeking cause and effect as an operational principle for serious enquiry. In this regard, it is as well to consider that scientists now also understand that, at a fundamental level, certain phenomena are best understood not as being composed of isolated entities that can be studied as such, but rather they can better be understood by means of the influence they have on other phenomena. In other words, by means of their systemic relationships, outside of which they in fact cease to be definable.

So fundamental is this realization to some leading thinkers, that one such, Gregory Bateson, has argued "that relationships should be used as a basis for all definitions, and this should be taught to our children in elementary school. Anything...should be defined not by what it is in itself, but by its relations to other things" (ibid:70). It appears then, that in some important respects, the leading edge of scientific thinking is coming into remarkable alignment with the TEK-based system of understanding what is the appropriate way of comprehending nature.

The question posed earlier, and that still needs to be asked (as modern science appears to be without a workable methodology in relation to ecological understanding) is: "but does the alternative (i.e., TEK) work?" That depends on the criteria to be applied in assessing the "success" of TEK. How does one assess its degree of "rightness" or "truth"?

Does TEK add anything useful to modern understanding?

Some might argue that, as TEK has provided the basis for whole groups of people surviving as food-gatherers, often in seemingly inhospitable environments, then the long-term persistence of these particular human societies should be evidence enough that it does work, at least most of the time. This "most of the time" rider would accommodate the obvious fact that sometimes people did not succeed, and either died of starvation or periodically suffered from serious food shortages.

However, such a means of assessing TEK has obvious shortcomings. For example, people (and in fact all predators) are obviously "smarter" than the prey species they hunt or fish, so for purely biologically determined reasons it can be assumed that people (as other predators) will naturally survive. If this were not so, the human population in question would not be present to be studied and assessed.

Perhaps the best way of trying to assess the efficacy of the TEK approach to understanding nature, is to look at some recent examples where it has been contrasted with scientific understanding of the same event. Here, I merely contrast a few examples that I have personal knowledge of, relating to events having taken place over the past several decades in the North American arctic regions.

Case I

This relates to Inuit knowledge that survival of Peary caribou in the High Arctic depends upon the social structure of the small herds in winter. Therefore, the management of these caribou for sustained harvesting requires, in addition to an overall quota system, the nonselective hunting of all animals encountered opportunistically rather than through the management system instituted by scientists where selective hunting of large males is advocated with a prohibition on hunting females and immature animals. The TEK view holds that only hunting large males will quickly result in the accelerated death of the remaining population, a view that has been born out by subsequent monitoring of the south Ellesmere Island regional population (Freeman 1985).

Case 2

Inuit TEK of the social structure and behaviour of musk-oxen (an animal not at the time hunted due to a 50-year-old management restriction) argued that scientists' ideas of "solitary and surplus" males were incorrect, and that such animals play an important role in enhancing musk-oxen population survival. Therefore, instituting a program to harvest such "surplus" animals would prove unwise. Such views, contradicting scientists' conventional wisdom, were nevertheless independently corroborated (Freeman 1971; 1985).

Case 3

Scientific surveys indicated the Beaufort Sea bowhead whale population was very depleted, with only about 800 whales surviving in 1977. Local hunters stated the whale population was about 7000. They also took issue with assumptions underlying scientists' population estimates (e.g., that whales only migrated in open water leads, and were incapable of swimming under the ice offshore and did not feed during migration). On the other hand, Inuit hunters believe whales migrate hundreds of miles offshore under the ice and therefore cannot be censured by visual means alone. On the basis of these methodological criticisms, a sophisticated survey technique was developed, incorporating Inuit assumptions (later verified). Using the new census methods the 1991 bowhead population was conservatively estimated to be in excess of 8000 whales, despite an annual harvest of between 20 and 40 whales over the past decade. The findings tended to confum the Inuit 1977 population assessment of about 7000 animals (Freeman 1989a).

Case 4

In 1979 biologists warned, from the results of aerial censuses, that the barren-ground caribou west of Hudson Bay were seriously depleted and overhunted. The Inuit hunters disputed these findings and the prognosis that the herds were about to become extinct. Scientists claimed a decrease of approximately 100 000 animals had occurred in just a few years. Inuit countered that the census techniques were deficient and that recent changes in seasonal caribou distribution also contributed to the low census figures. To resolve the conflict, surveys were carried out by census techniques suggested by Inuit hunters. The result was that population estimates increased by approximately 100 000 caribou, thus confuming that the herds were not threatened by "overhunting" and extinction (Freeman 1989b).

Conclusion

This paper suggests that a large quantity of information now exists in the published scientific literature to suggest that traditional ecological knowledge and its application to enlightened environmental assessment and management should be taken seriously. No one group of observers has a monopoly on truth, and the history of western science makes it quite clear that the scientific truths of today will, in ever-decreasing intervals of time, constitute the bulk of tomorrow's discarded hypotheses and superseded knowledge.

As scientists and philosophers working at the frontiers of knowledge increasingly find, the world view and technologies of many ancient cultures have a great deal to offer, whether in "new" health, or in ways of conserving ground water or increasing crop and time-tested understandings and approaches existing in regard to sustainable use of wild natural resources, and the future will likely increasingly benefit by the critical assessment, and where appropriate application, of such efficacious means of managing our embattled environment.

Milton M.R. Freeman is Professor of Anthropology at the University of Alberta and Senior Research Scholar with the Canadian Circumpolar Institute. This paper was originally prepared for the Environmental Committee, Municipality of Sanikiluaq, N.W.T.
 

References Cited

Berkes, F. (editor) 1989. Common property resources: ecology and community based sustainable development. London: Belhaven Press.

Capra, F. 1982. The Turning Point: Science, Society and the Rising Culture. London: Fontana, Collins.

Craig, D. 1989. Resolution of conflict in Australian water management: Aboriginal interests and perspectives. Centre for Resource and Environmental Studies, Australian National University, Canberra

Freemam, M.M.R. 1971. "Population characteristics of musk-ox in the Jones Sound region of the Northwest Territories." Journal of Wildlife Management 35:105-110.

Freeman, M.M.R. 1975. "Assessing movement in an arctic caribou population." Journal of Environmental Management 3:251-257.

Freeman, M.M.R. 1985. "Appeal to tradition: different perspectives on wildlife management." In J. Brosted, J. Dahl et al. (editors) Native Power: the Quest for Autonomy and Nationhood of Aboriginal Peoples, pp. 265-281. Oslo: Universitetsforlaget.

Freeman, M.M.R. 1989a. "The Alaska Eskimo Whaling Commission: successful co-management under extreme conditions." In E. Pinkerton (editor) Co-operative Management of Local Fisheries, pp. 137-153. Vancouver: University of British Columbia Press.

Freeman, M.M.R. 1989b. "Graphs and gaffs: a cautionary tale in the common property resource debate." In E Berkes (editor) Common Property Resources:

Ecology and Community-based Sustainable Development, pp. 92-109. London: Belhaven Press.

Freeman, M.M.R. and L.N. Carbyn (editors) 1988. Traditional Knowledge and Renewable Resources Management in Northern Regions. Occasional Paper No. 20, Boreal Institute for Northern Studies, Edmonton.

Freemam, M.M.R., Y. Matsuda and K. Ruddle (editors) 1991. Adaptive Marine Resource Management Systems in the Pacific. Philadelphia, Tokyo, Melbourne: Harwood Academic Publishers.

Mayr, E., E.G. Linsley and R.L. Usinger 1953. Methods and Principles of Systematic Zoology. New York: McGraw-Hill.

McCay, B.J. and J. Acheson 1987. The Question of the Commons. Tucson: University of Arizona Press.

Nakashima, D.J. 1990. Application of native knowledge in EIA: Inuit, eiders and Hudson Bay oil. Report prepared for the Canadian Environmental Assessment Research Council, Hull.

Ruddle, K. and R. Johannes (editors) 1990. The traditional Knowledge and Management of Coastal Systems in Asia and the Pacific. Jakarta: UNESCO (2nd edition).

Tanaka, S. 1986. On a practical method for stock assessment. Document SC/A86/CA5, International Whaling Commission, Cambridge.

Williams, N.M. and E.S. Hunn (editors) 1982. Resource Managers: North American and Australian Hunter-gatherers. Boulder, CO: Westview Press.


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