96
7
“Best” Abundance Estimates and
Best Management: Why They Are
Not the Same
Barbara L. Taylor and Paul R. Wade
Introduction
In New Principles for the Conservation of Wild Living Resources, Holt and Talbot
(1978) give their second principle as, “Management decisions should include a
safety factor to allow for the facts that knowledge is limited and institutions are
imperfect.” Inclusion of uncertainty in management has been difficult partly
because of the failure of scientists to explain adequately the importance of incorporating estimates of uncertainty and the consequences of not accounting for this
uncertainty in management decisions to policy makers and managers. On the
surface, using the best estimates of abundance for management purposes seems
sound. This chapter explains why using the mean estimate of abundance (N MEAN ,
often referred to as the “best” estimate) counterintuitively can result in poor
management practices. We illustrate the benefits of using estimates of uncertainty
with a management scheme incorporated in the 1994 amendments to the Marine
Mammal Protection Act (MMPA) and will therefore use marine mammal examples, although the lessons generalize to many species.
Why should management be concerned with uncertainty in abundance estimates? Consider the following cases: animals from two populations are incidentally killed in fishery interactions. Population A is well known, but considerable
uncertainty exists about population B. How should management proceed in the
short term when decisions must be based on best current information? Relatively
good estimates may be made for the number of animals that could be killed by the
fishery without depleting A. Difficulties arise, however, with population B. Let us
assume that the best abundance estimates for both populations are about the same.
Confidence in the estimates, however, differs greatly. Is the best management
strategy to limit incidental kill based on no more than some small fraction of the
best estimate (N MEAN ) or to somehow incorporate the level of uncertainty concerning the populations into our management decision? Using a lower percentile of an
abundance distribution (N MIN ) incorporates uncertainty. It embodies Holt and
Talbot’s (1978) statement: “The magnitude of the safety factor should be proportional to the magnitude of risk.” To compare management strategies using N MEAN
and N MIN , we must first understand what these terms mean.
7
“Best” Abundance Estimates and
Best Management: Why They Are
Not the Same
Barbara L. Taylor and Paul R. Wade
Introduction
In New Principles for the Conservation of Wild Living Resources, Holt and Talbot
(1978) give their second principle as, “Management decisions should include a
safety factor to allow for the facts that knowledge is limited and institutions are
imperfect.” Inclusion of uncertainty in management has been difficult partly
because of the failure of scientists to explain adequately the importance of incorporating estimates of uncertainty and the consequences of not accounting for this
uncertainty in management decisions to policy makers and managers. On the
surface, using the best estimates of abundance for management purposes seems
sound. This chapter explains why using the mean estimate of abundance (N MEAN ,
often referred to as the “best” estimate) counterintuitively can result in poor
management practices. We illustrate the benefits of using estimates of uncertainty
with a management scheme incorporated in the 1994 amendments to the Marine
Mammal Protection Act (MMPA) and will therefore use marine mammal examples, although the lessons generalize to many species.
Why should management be concerned with uncertainty in abundance estimates? Consider the following cases: animals from two populations are incidentally killed in fishery interactions. Population A is well known, but considerable
uncertainty exists about population B. How should management proceed in the
short term when decisions must be based on best current information? Relatively
good estimates may be made for the number of animals that could be killed by the
fishery without depleting A. Difficulties arise, however, with population B. Let us
assume that the best abundance estimates for both populations are about the same.
Confidence in the estimates, however, differs greatly. Is the best management
strategy to limit incidental kill based on no more than some small fraction of the
best estimate (N MEAN ) or to somehow incorporate the level of uncertainty concerning the populations into our management decision? Using a lower percentile of an
abundance distribution (N MIN ) incorporates uncertainty. It embodies Holt and
Talbot’s (1978) statement: “The magnitude of the safety factor should be proportional to the magnitude of risk.” To compare management strategies using N MEAN
and N MIN , we must first understand what these terms mean.