Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow. Issue 2 (1st March 2014)

• Record Type: Journal Article
• Authors: van Strien, Maarten J.; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine
• Is Part Of: Ecological applications. Volume 24:Issue 2(2014)
• Page Start: 327
• Page End: 339
• Publication Date: 2014-03-01
• Subjects: agricultural landscapes -- conservation management -- forecasting -- gene flow -- planning tool -- Stethophyma grossum; Ecology -- Periodicals; Environmental protection -- Periodicals; Biology, Economic -- Periodicals; 577.05
• DOI: 10.1890/13-0442.1
• Languages: English
• ISSNs: 1051-0761

Abstract

Abstract : For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape‐genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper ( Stethophyma grossum ), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (<3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable ( F ST and mean pairwise assignment probability). With a modified leave‐one‐out cross‐validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape‐change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape‐change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape‐genetic models in conservation and landscape planning.