Cityscape genetics: structural vs. functional connectivity of an urban lizard population

被引:51
作者
Beninde, Joscha [1 ]
Feldmeier, Stephan [1 ]
Werner, Maike [2 ]
Peroverde, Daniel [1 ]
Schulte, Ulrich [3 ]
Hochkirch, Axel [1 ]
Veith, Michael [1 ]
机构
[1] Univ Trier, Dept Biogeog, Univ Ring 15, D-54296 Trier, Germany
[2] Univ Greifswald, Museum & Inst Zool, Johann Sebastian Bach Str 11-12, D-17487 Greifswald, Germany
[3] Fed Agcy Nat Conservat BfN, Konstantinstr 110, D-53179 Bonn, Germany
关键词
biodiversity; conservation; corridor; dispersal; ecology; isolation; management; movement; reptiles; urbanization; WALL LIZARD; SPECIES DISTRIBUTIONS; MICROSATELLITE LOCI; LANDSCAPE GENETICS; PODARCIS-MURALIS; DIFFERENTIATION; SOFTWARE; HABITAT; FLOW; BIODIVERSITY;
D O I
10.1111/mec.13810
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Functional connectivity is essential for the long-term persistence of populations. However, many studies assess connectivity with a focus on structural connectivity only. Cityscapes, namely urban landscapes, are particularly dynamic and include numerous potential anthropogenic barriers to animal movements, such as roads, traffic or buildings. To assess and compare structural connectivity of habitats and functional connectivity of gene flow of an urban lizard, we here combined species distribution models (SDMs) with an individual-based landscape genetic optimization procedure. The most important environmental factors of the SDMs are structural diversity and substrate type, with high and medium levels of structural diversity as well as open and rocky/gravel substrates contributing most to structural connectivity. By contrast, water cover was the best model of all environmental factors following landscape genetic optimization. The river is thus a major barrier to gene flow, while of the typical anthropogenic factors only buildings showed an effect. Nonetheless, using SDMs as a basis for landscape genetic optimization provided the highest ranked model for functional connectivity. Optimizing SDMs in this way can provide a sound basis for models of gene flow of the cityscape, and elsewhere, while presence-only and presence-absence modelling approaches showed differences in performance. Additionally, interpretation of results based on SDM factor importance can be misleading, dictating more thorough analyses following optimization of SDMs. Such approaches can be adopted for management strategies, for example aiming to connect native common wall lizard populations or disconnect them from non-native introduced populations, which are currently spreading in many cities in Central Europe.
引用
收藏
页码:4984 / 5000
页数:17
相关论文
共 100 条
[21]   Genetic structure is influenced by landscape features: empirical evidence from a roe deer population [J].
Coulon, A ;
Guillot, G ;
Cosson, JF ;
Angibault, JMA ;
Aulagnier, S ;
Cargnelutti, B ;
Galan, M ;
Hewison, AJM .
MOLECULAR ECOLOGY, 2006, 15 (06) :1669-1679
[22]   Spurious correlations and inference in landscape genetics [J].
Cushman, Samuel A. ;
Landguth, Erin L. .
MOLECULAR ECOLOGY, 2010, 19 (17) :3592-3602
[23]   A Rapid, Strong, and Convergent Genetic Response to Urban Habitat Fragmentation in Four Divergent and Widespread Vertebrates [J].
Delaney, Kathleen Semple ;
Riley, Seth P. D. ;
Fisher, Robert N. .
PLOS ONE, 2010, 5 (09) :1-11
[24]   Collinearity: a review of methods to deal with it and a simulation study evaluating their performance [J].
Dormann, Carsten F. ;
Elith, Jane ;
Bacher, Sven ;
Buchmann, Carsten ;
Carl, Gudrun ;
Carre, Gabriel ;
Garcia Marquez, Jaime R. ;
Gruber, Bernd ;
Lafourcade, Bruno ;
Leitao, Pedro J. ;
Muenkemueller, Tamara ;
McClean, Colin ;
Osborne, Patrick E. ;
Reineking, Bjoern ;
Schroeder, Boris ;
Skidmore, Andrew K. ;
Zurell, Damaris ;
Lautenbach, Sven .
ECOGRAPHY, 2013, 36 (01) :27-46
[25]   Spatial dynamics of the knob-tailed gecko Nephrurus stellatus in a fragmented agricultural landscape [J].
Driscoll, Don A. ;
Whitehead, Catherine A. ;
Lazzari, Juliana .
LANDSCAPE ECOLOGY, 2012, 27 (06) :829-841
[26]   STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method [J].
Earl, Dent A. ;
vonHoldt, Bridgett M. .
CONSERVATION GENETICS RESOURCES, 2012, 4 (02) :359-361
[27]   A statistical explanation of MaxEnt for ecologists [J].
Elith, Jane ;
Phillips, Steven J. ;
Hastie, Trevor ;
Dudik, Miroslav ;
Chee, Yung En ;
Yates, Colin J. .
DIVERSITY AND DISTRIBUTIONS, 2011, 17 (01) :43-57
[28]   The art of modelling range-shifting species [J].
Elith, Jane ;
Kearney, Michael ;
Phillips, Steven .
METHODS IN ECOLOGY AND EVOLUTION, 2010, 1 (04) :330-342
[29]   Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models [J].
Elith, Jane ;
Graham, Catherine H. .
ECOGRAPHY, 2009, 32 (01) :66-77
[30]   Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change [J].
Epps, Clinton W. ;
Keyghobadi, Nusha .
MOLECULAR ECOLOGY, 2015, 24 (24) :6021-6040