Ráðunautafundur - 15.02.1989, Blaðsíða 10

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routinely occurs even when scientific knowledge is totally absent. For example
(Romesburg, 1981), macroeconomic policy in the United States is largely geared to
projected images made by computer simulation models of the economy. The elaborate
mathematical equations comprising these models represent untested economic theory,
and by even the loosest standards of science their predications fail to agree with
economic facts as revealed in the future. Likewise, most of the planning involved in
grazing management is based upon common sense, rule-of-thumb knowledge, hunches
and untested theories, rather than scientific knowledge. This is not necessarily the
fault of the manager. In many cases, the manager is doing the best possible given
the lack of scientific knowledge. I believe the lack of knowledge occurs because
range scientists have not fully used the methods of science.
Science
There is no single scientific method. Rather, there are several each suited to a
different purpose. Of the three main methods of science used in virtually all fields,
range scientists rely primarily on induction, to a limited extent on retroduction and
almost never on hypothetico-deduction to study the processes of most importance to
grazing management has resulted in a lack of reliable knowledge.
Induction is useful for finding laws of association between classes of facts
(Romesburg, 1981). For example, if we observe over many trials that diet selection
by livestock is positively correlated with living plant parts or that habitat use by
livestock is positively correlated with riparian areas, we would be using induction if
we declare a law of association. Induction has a limitation: It can only give
knowledge about possible associations among classes of facts. This can be useful in
planning, provided the associations always hold, but it cannot give knowledge about
the processes of nature. Hence, induction can be used repeatedly without diminishing
the question ’why?’. When we ask ’why?’ we are asking for an explanation, an
abstract process that provides a reason for the facts.
Retroduction is useful for finding research hypotheses that are explanations for
the facts (Romesburg, 1981). For example, if we observe livestock ingesting the most
nutritious plant parts available on a range and our best guess for the reason for
this behavior is that livestock can relate foods with their post-ingestive
consequences, we would be using retroduction to provide an explanation (research
hypothesis) for the observed facts relating to the process of livestock foraging
behavior. Retroduction is essential for elucidating alternative research hypotheses.
However, retroduction per se is not a reliable source of knowledge because
alternative explanations can often be given for the same set of facts.
Hypothetico-deduction complements retroduction by subjecting alternative
explanations to experimental verification (Romesburg, 1981). Starting with a research