Admixture of hybrid swarms of native and introduced lizards in cities is determined by the cityscape structure and invasion history.

Introductions of non-native lineages increase opportunities for hybridization. Non-native lineages of the common wall lizard, Podarcis muralis, are frequently introduced in cities where they hybridize with native populations. We aimed at unravelling the invasion history and admixture of native and non-native wall lizards in four German cities using citywide, comprehensive sampling. We barcoded and genotyped 826 lizards and tested if gene flow in populations composed of admixed native and introduced lineages is facilitated by similar environmental factors to those in native populations by comparing fine-scale landscape genetic patterns. In cities with non-native lineages, lizards commonly occurred in numerous clusters of hybrid swarms, which showed variable lineage composition, consisting of up to four distinct evolutionary lineages. Hybrid swarms held vast genetic diversity and showed recent admixture with other hybrid swarms. Landscape genetic analyses showed differential effects of cityscape structures across cities, but identified water bodies as strong barriers to gene flow in both native and admixed populations. By contrast, railway tracks facilitated gene flow of admixed populations only. Our study shows that cities represent unique settings for hybridization, caused by multiple introductions of non-native taxa. Cityscape structure and invasion histories of cities will determine future evolutionary pathways at these novel hybrid zones.

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

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.

Exploring the Distribution of the Spreading Lethal Salamander Chytrid Fungus in Its Invasive Range in Europe - A Macroecological Approach.

The chytrid fungus Batrachochytrium salamandrivorans (Bsal) is a dangerous pathogen to salamanders and newts. Apparently native to Asia, it has recently been detected in Western Europe where it is expected to spread and to have dramatic effects on naïve hosts. Since 2010, Bsal has led to some catastrophic population declines of urodeles in the Netherlands and Belgium. More recently, it has been discovered in additional, more distant sites including sites in Germany. With the purpose to contribute to a better understanding of Bsal, we modelled its potential distribution in its invasive European range to gain insights about the factors driving this distribution. We computed Bsal Maxent models for two predictor sets, which represent different temporal resolutions, using three different background extents to account for different invasion stage scenarios. Beside 'classical' bioclimate, we employed weather data, which allowed us to emphasize predictors in accordance with the known pathogen's biology. The most important predictors as well as spatial predictions varied between invasion scenarios and predictor sets. The most reasonable model was based on weather data and the scenario of a recent pathogen introduction. It identified temperature predictors, which represent optimal growing conditions and heat limiting conditions, as the most explaining drivers of the current distribution. This model also predicted large areas in the study region as suitable for Bsal. The other models predicted considerably less, but shared some areas which we interpreted as most likely high risk zones. Our results indicate that growth relevant temperatures measured under laboratory conditions might also be relevant on a macroecological scale, if predictors with a high temporal resolution and relevance are used. Additionally, the conditions in our study area support the possibility of a further Bsal spread, especially when considering that our models might tend to underestimate the potential distribution of Bsal.