IDENTIFYING POPULATIONS FOR CONSERVATION ON THE BASIS OF GENETIC-MARKERS

Citation
Rj. Petit et al., IDENTIFYING POPULATIONS FOR CONSERVATION ON THE BASIS OF GENETIC-MARKERS, Conservation biology, 12(4), 1998, pp. 844-855
Citations number
37
Categorie Soggetti
Environmental Sciences",Ecology,"Biology Miscellaneous",Biology
Journal title
ISSN journal
08888892
Volume
12
Issue
4
Year of publication
1998
Pages
844 - 855
Database
ISI
SICI code
0888-8892(1998)12:4<844:IPFCOT>2.0.ZU;2-6
Abstract
To select candidate populations of wild species to be given priority f or conservation, genetic criteria gained from the study of molecular m arkers may be useful. Traditionally, diversity measures such as expect ed heterozygosity or percentage of polymorphic loci have been consider ed. For conservation we propose instead that priority should be given to measures of allelic richness. To standardize the results of allelic richness across populations, we sued the technique of rarefaction. Th is technique allows evaluation of the expected number of different all eles among equal-sized samples drawn from several different population s. We also show how the contribution of each population to total diver sity can be partitioned into two components. The first is related to t he level of diversity of the population and the second to its divergen ce from the other populations. For conservation purposes the uniquenes s of a population-in terms of its allelic composition-may be at least as important as its diversity level. These new descriptors are illustr ated by means of isozyme and chloroplast DNA data obtained for an enda ngered tree species, the argan tree of Morocco (Argania spinosa (L.) S keels). With these analyses the conservation value of the argan tree p opulations, especially those of two isolates present in the north of t he country, can be better appreciated. The methods proposed to identif y priority areas for conservation of the genetic resources of the arga n tree are compared to those sometimes advocated in the case of reserv e design, where one of the goals is to maximize species richness.