Anthropogenic climate change is rapidly altering ecosystems, driving range shifts, range contractions, dwindling population sizes and local extinctions in many species. Some species, however, are expanding their ranges and seem to benefit from warming temperatures. This is the case for the wasp spider, Argiope bruennichi, which has undergone a range expansion from its historic range in the Mediterranean (“core”), now reaching as far as the Baltic states and Scandinavia (“edge”). The rate of this range expansion cannot be attributed to climate change alone, and it has been hypothesized that adaptive introgression lent the genetic variation upon which selection could act, enabling the rapid range expansion. In the present study, we first quantify the degree of local adaptation and phenotypic plasticity in cold tolerance in edge relative to core populations, and secondly investigate genomic and phenotypic turnover across the proposed introgression zone. With a reciprocal transplant common garden experiment, we provide strong support for the hypothesis that edge populations are locally adapted to colder winter conditions. We also find evidence of seasonal plasticity in the core populations, while edge populations have lost this plasticity. Our genome-wide analysis, using a combination of FST outlier and genetic-environment association tests, supports the hypothesis that adaptive introgression played a role in environmental adaptation.

Extra-organismal DNA (eoDNA) from material left behind by organisms (noninvasive DNA, e.g., feces, hair) or from environmental samples (eDNA, e.g., water, soil) is a valuable source of genetic information. However, the relatively low quality and quantity of eoDNA, which can be further degraded by environmental factors, results in reduced amplification and sequencing success. This is often compensated for through cost-and time-intensive replications of genotyping/sequencing procedures.Therefore, system-and site-specific quantifications of environmental degradation are needed to maximize sampling efficiency (e.g., fewer replicates, shorter sampling durations), and to improve species detection and abundance estimates. Using 10 environmentally diverse bat roosts as a case study, we developed a robust modeling pipeline to quantify the environmental factors degrading eoDNA, predict eoDNA quality, and estimate sampling-site-specific ideal exposure duration. Maximum humidity was the strongest eoDNA-degrading factor, followed by exposure duration and then maximum temperature. We also found a positive effect when hottest days occurred later.The strength of this effect fell between the strength of the effects of exposure duration and maximum temperature. With those predictors and information on sampling period (before or after offspring were born), we reliably predicted mean eoDNA quality per sampling visit at new sites with a mean squared error of 0.0349. Site-specific simulations revealed that reducing exposure duration to 2-8 days could substantially improve eoDNA quality for future sampling. Our pipeline identified high humidity and temperature as strong drivers of eoDNA degradation even in the absence of rain and direct sunlight. Furthermore, we outline the pipeline's utility for other systems and study goals, such as estimating sample age, improving eDNA-based species detection, and increasing the accuracy of abundance estimates.