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Urbanization is a major contributor to the loss of biodiversity. Its rapid progress is mostly at the expense of natural ecosystems and the species inhabiting them. While some species can adjust quickly and thrive in cities, many others cannot. To support biodiversity conservation and guide management decisions in urban areas, it is important to find robust methods to estimate the urban affinity of species (i.e. their tendency to live in urban areas) and understand how it is associated with their traits. Since previous studies mainly relied on discrete classifications of species' urban affinity, often involving inconsistent assessments or variable parameters, their results were difficult to compare. To address this issue, we developed and evaluated a set of continuous indices that quantify species' urban affinity based on publicly available occurrence data. We investigated the extent to which a species' position along the urban affinity gradient depends on the chosen index and how this choice affects inferences about the relationship between urban affinity and a set of morphological, sensory and functional traits. While these indices are applicable to a wide range of taxonomic groups, we examined their performance using a global set of 356 bat species. As bats vary in sensitivity to anthropogenic disturbances, they provide an interesting case study. We found that different types of indices resulted in different rankings of species on the urban affinity spectrum, but this had little effect on the association of traits with urban affinity. Our results suggest that bat species predisposed to urban life are characterized by low echolocation call frequencies, relatively long call durations, small body size and flexibility in the selection of the roost type. We conclude that simple indices are appropriate and practical, and propose to apply them to more taxa to improve our understanding of how urbanization favours or filters species with particular traits.
Relative importance of plastic and genetic responses to weather conditions in long-lived bats
(2022)
In the light of the accelerating pace of environmental change, it is imperative to understand how populations and species can adapt to altered environmental conditions. This is a crucial step in predicting current and future population persistence and limits thereof. Genetic adaption and phenotypic plasticity are two main mechanisms that can mediate the process of adaptation and are of particular importance for non-dispersing species. While phenotypic plasticity may enable individuals to cope with short term environmental changes, genetic adaptation will often be required for populations to survive in situ over longer time spans. However, a rapid genetic response is expected particularly in species with fast life histories or large population sizes, leaving species with slow life histories potentially at higher extinction risk. The Bechstein’s bat (Myotis bechsteinii) is a mammal of 10 g weight that - despite its small size - is characterized by a slow life history, with low reproductive output and long lifespan, and is already considered to be of high conservation concern. Past work demonstrated body size to be a highly fitness-relevant trait in Bechstein’s bats. Body size is further known to be a pivotal trait shaping the pace of life histories in numerous species. Simultaneously, many studies reported noteworthy changes in body size as a response to shifting environments across different taxa. This suggested a potential for high plasticity in this trait in Bechstein’s bats as well; however, changes in body size could have vital impacts on demographic rates.
Therefore, this dissertation investigated the following questions: firstly, what shapes the fundamental development of body size in M. bechsteinii, and, specifically, is there an impact of weather conditions on body size? If so, in what form and magnitude? Secondly, how does body size subsequently influence the pace of life in females? What is the cost of a faster or slower pace of life, and how does fitness compare across individuals with slow and fast life histories? And finally, to what extent can changes in body size be attributed to either phenotypic plasticity or genetic adaptation? What is the evolutionary potential of body size in the populations? And, consequently, what implications can we draw regarding population persistence of these colonies?
To answer these questions, we analyzed a long-term dataset of over two decades collected from four wild Bechstein’s bat colonies. We used individual-based data on survival, reproduction and body size, built multi-generational pedigrees, and combined everything with meteorological data. In Manuscript 1 we found that, in contrast to the declining body size observed in many species, body size in Bechstein’s bats increased significantly over the last decades. We demonstrated that ambient temperature was linked to the development of body size and identified a sensitive time period in the prenatal growth phase, in which body size was most susceptible to the impact of temperature. We established that warmer summers resulted in larger bats, but that these large bats had higher mortality risks throughout their lives. Manuscript 2 then revealed the influence of body size on the pace of life in Bechstein’s bats and demonstrated high plasticity in intraspecific life history strategies. Large females were characterized by a faster pace of life and shorter lifespans, but surprisingly, lifetime reproductive success remained remarkably stable across individuals with different body sizes. The acceleration of their pace of life means that larger females compensated for their reduced longevity by an earlier reproduction and higher fecundity to reach similar overall fitness. Ultimately, differences in body size resulted in changes in population growth rate via the impact of size on generation times. Results of Manuscript 3 were then able to clarify the extent to which changes in body size were founded on either phenotypic plasticity or genetic adaptation. We demonstrated a particularly low heritability in hot summers, indicating that variance in body size was mostly driven by phenotypic plasticity, with few genetic constraints. During cold summers, behavioural adaptations by reproducing bats seem to be able to mitigate negative effects of cold temperatures. These behaviours, such as social aggregation or preference for warm roosts, are, however, essentially irrelevant in hot environments. In addition, a low evolvability of forearm length points to a low capacity to respond to selection pressures associated with the trait.
We can conclude that body size in M. bechsteinii has increased over the last two decades as a response to global warming and is only slightly constrained by its genetic underpinnings. We can further demonstrate a direct link between body size and the pace of life histories in the Bechstein’s bat populations and how changes in body size impact demographic rates via this linkage. In the context of climate change and hotter summers, our findings consequently suggest that body size will likely increase further if warm summers continue to become more frequent. Whether this plastic response of body size proves to be adaptive in the long term, however, remains to be seen. While, up to this point, switching to a faster life history has been successful in compensating fitness losses, this strategy requires sufficient habitat quality and is likely risky in times when extreme weather events are becoming more frequent, as predicted by most climate change scenarios.
Background
Hibernation allows species to conserve energy and thereby bridge unfavorable environmental conditions. At the same time, hibernation imposes substantial ecological and physiological costs. Understanding how hibernation timing differs within and between species can provide insights into the underlying drivers of this trade-off. However, this requires individualized long-term data that are often unavailable. Here, we used automatic monitoring techniques and a reproducible analysis pipeline to assess the individualized hibernation phenology of two sympatric bat species. Our study is based on data of more than 1100 RFID-tagged Daubenton’s bats (Myotis daubentonii) and Natterer’s bats (Myotis nattereri) collected over seven years at a hibernaculum in Germany. We used linear mixed models to analyze species-, sex- and age-specific differences in entrance, emergence and duration of the longest continuous period spent in the hibernaculum.
Results
Overall, Daubenton’s bats entered the hibernaculum earlier and emerged later than Natterer’s bats, resulting in a nearly twice as long hibernation duration. In both species, adult females entered earlier and emerged from hibernation later than adult males. Hibernation duration was shorter for juveniles than adults with the exception of adult male Natterer’s bats whose hibernation duration was shortest of all classes. Finally, hibernation timing differed among years, but yearly variations in entrance and emergence timing were not equally shifted in both species.
Conclusions
Our results suggest that even in sympatric species, and across sex and age classes, hibernation timing may be differentially affected by environmental conditions. This highlights the necessity of using individualized information when studying the impact of changing environments on hibernation phenology.
BatNet: a deep learning-based tool for automated bat species identification from camera trap images
(2023)
Automated monitoring technologies can increase the efficiency of ecological data collection and support data-driven conservation. Camera traps coupled with infrared light barriers can be used to monitor temperate-zone bat assemblages at underground hibernacula, where thousands of individuals of multiple species can aggregate in winter. However, the broad-scale adoption of such photo-monitoring techniques is limited by the time-consuming bottleneck of manual image processing. Here, we present BatNet, an open-source, deep learning-based tool for automated identification of 13 European bat species from camera trap images. BatNet includes a user-friendly graphical interface, where it can be retrained to identify new bat species or to create site-specific models to improve detection accuracy at new sites. Model accuracy was evaluated on images from both trained and untrained sites, and in an ecological context, where community- and species-level metrics (species diversity, relative abundance, and species-level activity patterns) were compared between human experts and BatNet. At trained sites, model performance was high across all species (F1-score: 0.98–1). At untrained sites, overall classification accuracy remained high (96.7–98.2%), when camera placement was comparable to the training images (<3 m from the entrance; <45° angle relative to the opening). For atypical camera placements (>3 m or >45° angle), retraining the detector model with 500 site-specific annotations achieved an accuracy of over 95% at all sites. In the ecological case study, all investigated metrics were nearly identical between human experts and BatNet. Finally, we exemplify the ability to retrain BatNet to identify a new bat species, achieving an F1-score of 0.99 while maintaining high classification accuracy for all original species. BatNet can be implemented directly to scale up the deployment of camera traps in Europe and enhance bat population monitoring. Moreover, the pretrained model can serve as a baseline for transfer learning to automatize the image-based identification of bat species worldwide.