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M A Burgman

Publications and source records attributed to M A Burgman.

3 recordsLinked to original sources

Genetic variation in the vulnerable and endemic Monkey Puzzle tree, detected using RAPDs.

Araucaria araucana (Monkey Puzzle), a southern South American tree species of exceptional cultural and economic importance, is of conservation concern owing to extensive historical clearance and current human pressures. Random amplified polymorphic DNA (RAPD) markers were used to characterise genetic heterogeneity within and among 13 populations of this species from throughout its natural range. Extensive genetic variability was detected and partitioned by analysis of molecular variance, with the majority of variation existing within populations (87.2%), but significant differentiation was recorded among populations (12.8%). Estimates of Shannon's genetic diversity and percent polymorphism were relatively high for all populations and provide no evidence for a major reduction in genetic diversity from historical events, such as glaciation. All pairwise genetic distance values derived from analysis of molecular variance (Phi(ST)) were significant when individual pairs of populations were compared. Although populations are geographically divided into Chilean Coastal, Chilean Andes and Argentinean regions, this grouping explained only 1.77% of the total variation. Within Andean groups there was evidence of a trend of genetic distance with increasing latitude, and clustering of populations across the Andes, suggesting postglacial migration routes from multiple refugia. Implications of these results for the conservation and use of the genetic resource of this species are discussed.

Conservation of Natural Resources↗

Predictive accuracy of population viability analysis in conservation biology.

Population viability analysis (PVA) is widely applied in conservation biology to predict extinction risks for threatened species and to compare alternative options for their management. It can also be used as a basis for listing species as endangered under World Conservation Union criteria. However, there is considerable scepticism regarding the predictive accuracy of PVA, mainly because of a lack of validation in real systems. Here we conducted a retrospective test of PVA based on 21 long-term ecological studies--the first comprehensive and replicated evaluation of the predictive powers of PVA. Parameters were estimated from the first half of each data set and the second half was used to evaluate the performance of the model. Contrary to recent criticisms, we found that PVA predictions were surprisingly accurate. The risk of population decline closely matched observed outcomes, there was no significant bias, and population size projections did not differ significantly from reality. Furthermore, the predictions of the five PVA software packages were highly concordant. We conclude that PVA is a valid and sufficiently accurate tool for categorizing and managing endangered species.

Animals↗