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.
Introductions of non-native lineages increase opportunities for hybridization. Non-native lineages of the common wall lizard, , 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.
The Noble False Widow, Steatodanobilis (Thorell, 1875) (Araneae, Theridiidae), is, due to its relatively large size and potential medical importance, one of the most notable invasive spider species worldwide. Probably originating from the Canary Islands and Madeira, the species is well established in Western Europe and large parts of the Mediterranean area and has spread recently into California and South America, while Central European populations were not known until 2011. We report on long-time observations that reveal that at least two flourishing populations in Germany (Cologne) have been present for over five years, while in Ecuador one population has been observed between 2014 and 2018 and several other records were made in other parts of the country. Data obtained from the British Spider Recording Scheme demonstrate that the species moved significantly northwards since the report of the first populations in the very South of England, after several decades of relative stasis. The sudden northward expansion highly correlates with a massive rise in press coverage of the species. In the Americas, S.nobilis is currently known from four countries (USA, Chile, Ecuador, Colombia), and available DNA barcoding data obtained for specimens from this area suggest that multiple introductions occurred within each country. Using ecological niche modeling, we identified suitable climate regions for the species and discuss possible reasons for its current spread. We propose that seaside cities and villages with a temperate oceanic or Mediterranean climate are especially favourable potential habitats for S.nobilis and will face the highest colonization pressure in the future, while tropical upland regions with temperate climates are also vulnerable to invasion by S.nobilis.
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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.
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