Beninde Joscha, Feldmeier Stephan, Werner Maike, Peroverde Daniel, Schulte Ulrich, Hochkirch Axel, Veith Michael
Department of Biogeography, Trier University, Universitätsring 15, 54296, Trier, Germany.
Zoological Institute & Museum, Ernst-Moritz-Arndt-Universität Greifswald, Johann Sebastian Bach-Str. 11/12, 17487, Greifswald, Germany.
Mol Ecol. 2016 Oct;25(20):4984-5000. doi: 10.1111/mec.13810. Epub 2016 Sep 29.
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.
功能连通性对于种群的长期存续至关重要。然而，许多研究在评估连通性时仅关注结构连通性。城市景观，即城市风貌，尤其具有动态性，并且包含众多对动物移动具有潜在人为阻碍的因素，例如道路、交通或建筑物。为了评估和比较城市蜥蜴栖息地的结构连通性以及基因流的功能连通性，我们在此将物种分布模型（SDMs）与基于个体的景观遗传优化程序相结合。物种分布模型中最重要的环境因素是结构多样性和基质类型，结构多样性处于高和中等水平以及开阔和岩石/砾石基质对结构连通性贡献最大。相比之下，在景观遗传优化之后，水体覆盖是所有环境因素中最佳的模型。因此，河流是基因流的主要障碍，而在典型的人为因素中只有建筑物显示出有影响。尽管如此，将物种分布模型作为景观遗传优化的基础为功能连通性提供了排名最高的模型。以这种方式优化物种分布模型可为城市景观及其他地方的基因流模型提供坚实基础，而仅存在和存在 - 缺失建模方法在性能上存在差异。此外，基于物种分布模型因素重要性对结果的解释可能会产生误导，这就要求在物种分布模型优化之后进行更深入的分析。此类方法可应用于管理策略，例如旨在连接本地普通壁蜥种群或将它们与目前在中欧许多城市扩散的非本地引入种群隔离开来。
