Combining genetic and demographic data for prioritizing conservation actions: insights from a threatened fish species.
Ecol Evol
; 3(8): 2696-710, 2013 Aug.
Article
em En
| MEDLINE
| ID: mdl-24567833
ABSTRACT
Prioritizing and making efficient conservation plans for threatened populations requires information at both evolutionary and ecological timescales. Nevertheless, few studies integrate multidisciplinary approaches, mainly because of the difficulty for conservationists to assess simultaneously the evolutionary and ecological status of populations. Here, we sought to demonstrate how combining genetic and demographic analyses allows prioritizing and initiating conservation plans. To do so, we combined snapshot microsatellite data and a 30-year-long demographic survey on a threatened freshwater fish species (Parachondrostoma toxostoma) at the river basin scale. Our results revealed low levels of genetic diversity and weak effective population sizes (<63 individuals) in all populations. We further detected severe bottlenecks dating back to the last centuries (200-800 years ago), which may explain the differentiation of certain populations. The demographic survey revealed a general decrease in the spatial distribution and abundance of P. toxostoma over the last three decades. We conclude that demo-genetic approaches are essential for (1) identifying populations for which both evolutionary and ecological extinction risks are high; and (2) proposing conservation plans targeted toward these at risk populations, and accounting for the evolutionary history of populations. We suggest that demo-genetic approaches should be the norm in conservation practices. We combined genetic and demographic data from a threatened freshwater fish species (Parachondrostoma toxostoma) at the river basin scale for conservation purposes. Genetic diversity and effective population sizes are very low, probably due to the strong genetic bottlenecks detected in this study. The species spatial distribution and abundance also decreased during the last decades.
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Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Ecol Evol
Ano de publicação:
2013
Tipo de documento:
Article