Open AccessJoint effects of population size and isolation on genetic erosion in fragmented populations: finding fragmentation thresholds for management
Author(s) -
Méndez María,
Vögeli Matthias,
Tella José L.,
Godoy José A.
Publication year - 2014
Publication title -
evolutionary applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 68
ISSN - 1752-4571
DOI - 10.1111/eva.12154
Subject(s) - biology , population fragmentation , habitat fragmentation , genetic erosion , population size , isolation by distance , genetic diversity , population , ecology , effective population size , endangered species , fragmentation (computing) , small population size , genetic variation , inbreeding , habitat , genetic drift , selection (genetic algorithm) , local adaptation , genetic structure , demography , gene flow , genetics , sociology , gene , artificial intelligence , computer science
Abstract Size and isolation of local populations are main parameters of interest when assessing the genetic consequences of habitat fragmentation. However, their relative influence on the genetic erosion of local populations remains unclear. In this study, we first analysed how size and isolation of habitat patches influence the genetic variation of local populations of the D upont's lark ( C hersophilus duponti ), an endangered songbird. An information‐theoretic approach to model selection allowed us to address the importance of interactions between habitat variables, an aspect seldom considered in fragmentation studies, but which explained up to 65% of the variance in genetic parameters. Genetic diversity and inbreeding were influenced by the size of local populations depending on their degree of isolation, and genetic differentiation was positively related to isolation. We then identified a minimum local population of 19 male territories and a maximum distance of 30 km to the nearest population as thresholds from which genetic erosion becomes apparent. Our results alert on possibly misleading conclusions and suboptimal management recommendations when only additive effects are taken into account and encourage the use of most explanatory but easy‐to‐measure variables for the evaluation of genetic risks in conservation programmes.