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<br />structs may be followed in endangered fishes recovery. I
<br />simply present the "best of all possible worlds" scenario as
<br />a reference guide to sound genetic management, based on
<br />our current state of knowledge. It is then up to the individual
<br />manager to incorporate the constraints of reality into recov-
<br />ery programs and determine how closely each program can
<br />follow recommendations of theory. Finally, this is but a brief
<br />synthesis of the rapidly expanding field of conservation ge-
<br />netics. The concerned reader is strongly encouraged to study
<br />the more comprehensive works by Soule and Wilcox (1980),
<br />Frankel and Soule (1981), and especially Schonewald-Cox
<br />et al. (1983).
<br />Goals of Endangered
<br />Fishes Management
<br />Management of endangered fishes should be compatible
<br />with three conservation goals: maintenance of viable pop-
<br />ulations in the short term (= avoidance of extinction), main-
<br />tenance of the capacity of fishes to adapt to changing en-
<br />vironments, and maintenance of the capacity for continued
<br />speciation (Soule 1980). Extinction avoidance is the first and
<br />obvious goal of any conservation program, and is the most
<br />obvious aspect of conservation efforts. Howger, managers
<br />should not be satisfied simply with attainment of this goal.
<br />Since all environments ultimately change and will probably
<br />change at an ever-increasing rate through man's influence,
<br />conservation programs must also maintain the capacity of
<br />fishes to genetically adapt (i.e., evolve). This is a long-term
<br />goal that is critical to species maintenance in perpetuity (Fran-
<br />kel and Soule 1981),.and is the primary focus of conservation
<br />genetics. Finally, the ultimate aim of conservation programs
<br />should be the capacity for continued speciation. When con-
<br />fronted with only a few remaining individuals of an endan-
<br />gered species, it may seem ludicrous to be concerned with
<br />anything but the immediate salvage of that genome. How-
<br />ever, ignoring long-term goals will only postpone the in-
<br />evitable: extinction of a unique genetic line that is the result
<br />of millions of years of continuous evolution. Serious con-
<br />servation efforts must consider the ultimate, long-term goal
<br />of continued evolution. "The sights (of a conservation pro-
<br />gram] often are set for the short term, although perpetuity
<br />is its ultimate objective. Genetic wildlife conservation makes
<br />sense only in terms of an evolutionary time scale. Its sights
<br />must reach into the distant future" (Frankel 1974, p. 54).
<br />The Central Problem
<br />The central problem in conservation genetics is loss of
<br />genetic variation resulting in erosion of evolutionary flexi-
<br />bility. This potentially leads to a poorer match of organism
<br />to environment, increasing the probability of extinction
<br />(Simpson 1953). Managers of endangered species are pre-
<br />sented with remnants of a formerly larger, more diverse
<br />gene pool, and are charged with maintaining that pool in
<br />the face of continued environmental deterioration. Our ma-
<br />jor concern should be maintenance of existing genetic var-
<br />f„ ? H iance since evolutionary flexibility is a function of genetic
<br />Z A diversity (Fisher 1930; Simpson 1953). Total genetic variation
<br />,c within a species can be separated into at least two compo-
<br />r f? January - February 1986
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<br />nents (Chambers and Bayless 1983; Hamrick 1983). First, is
<br />variation within individual populations (demes) upon which
<br />natural selection acts. If this variation is reduced, there is
<br />less of a basis for future selective change (adaptation) within
<br />populations. Second, is variation among different popula-
<br />tions. Loss of variation at this level results in convergence
<br />of populations toward one "type" and a narrower range of
<br />"options" for the species. Both types of variation should be
<br />maximized to maintain full potential for evolutionary change
<br />within a species.
<br />Within-Population Variance
<br />Population size is the single most important factor in sus-
<br />taining a high level of genetic variation within a deme (Soule
<br />and Wilcox 1980; Frankel and Soule 1981). However, a sim-
<br />ple population census (N) alone is not indicative of the ge-
<br />netically effective population size (Ne), for many individuals
<br />may be pre- or post-reproductive and others may contribute
<br />nonproportionally to the next generation. Thus, Ne, defined
<br />as "the size of an idealized population that would have the
<br />same amount of inbreeding or of random gene frequency
<br />drift as the population under consideration" (Kimura and
<br />Crow 1963), is utilized in population genetic analyses. Ne
<br />is nearly always less than N because of three factors:
<br />1. Sex ratio-If the sex ratio of breeding adults departs
<br />from 1:1, Ne and genetic variation are reduced. The effective
<br />population size with respect to sex ratio _is determined as
<br />Ne = 4 Nm Nf where Nm and Nf are the number of breed-
<br />Nm + Nf
<br />ing males and breeding females, respectively (Frankel and
<br />Soule 1981). For example, with a population census of 100
<br />fish, we can compare Ne under the condition of 50 males
<br />and 50 females, versus 10 males and 90 females. For the
<br />former, Ne = 4(50)(50)/100 = 100 fish. In the latter, Ne =
<br />4(10)(90)/100 = 36. A population of 50 males and 50 females
<br />is nearly 2.8 times larger, in a genetic sense, than is one of
<br />10 males and 90 females.
<br />2. Progeny distribution-In an idealized population, the
<br />number of offspring per family is distributed in a Poisson
<br />fashion (Senner 1980; Frankel and Soule 1981). Deviations
<br />from this distribution, with some matings producing dis-
<br />proportionately more offspring, will bias the representation
<br />of contributed gametes in the next generation and thereby
<br />lower Ne. A biased progeny distribution will affect Ne
<br />as = 4N/(2 + (T') (Franklin 1980), where v' is variance in
<br />progeny distribution. For example, if 1000 breeding females
<br />reproduced in a Poisson fashion with a mean of two off-
<br />spring and a variance of two (in a Poisson distribution, var-
<br />iance =mean), Ne = 4(2000) 2 + 2 2000. However, if one fe-
<br />male produced 1001 offspring, and the remaining 999 fish
<br />produced one each, the mean remains at two, but variance
<br />is now 31.6 and Ne = 314(2000).6 + 31.6 = 238. The effective pop-
<br />ulation size of the next generation is thus drastically reduced
<br />by disproportionate offspring production.
<br />3. Population fluctuation-Whenever a population de-
<br />clines, the genetic variance for all future generations is con-
<br />tained in the few survivors. Since those individuals repre-
<br />sent only a sample of genetic variance contained in the original
<br />population, Ne is reduced by fluctuations to low levels. Ne
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