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Complex microbial communities inhabit vertebrate digestive systems but thorough understanding of the ecological dynamics and functions of host-associated microbiota within natural habitats is limited. We investigate the role of environmental conditions in shaping gut and skin microbiota under natural conditions by performing a field survey and reciprocal transfer experiments with salamander larvae inhabiting two distinct habitats (ponds and streams). We show that gut and skin microbiota are habitat-specific, demonstrating environmental factors mediate community structure. Reciprocal transfer reveals that gut microbiota, but not skin microbiota, responds differentially to environmental change. Stream-to-pond larvae shift their gut microbiota to that of pond-to-pond larvae, whereas pond-to-stream larvae change to a community structure distinct from both habitat controls. Predicted functions, however, match that of larvae from the destination habitats in both cases. Thus, microbial function can be matched without taxonomic coherence and gut microbiota appears to exhibit metagenomic plasticity. Host-associated microbial communities can shift in structure or function when hosts change locations. Bletz et al . reciprocally transfer salamander larvae between pond and stream habitats to show that gut microbiomes shift in function, but not necessarily taxonomic identities, when hosts encounter a new environment.

For many species, population sizes are unknown despite their importance for conservation. For population size estimation, capture-mark-recapture (CMR) studies are often used, which include the necessity to identify each individual, mostly through individual markings or genetic characters. Invasive marking techniques, however, can negatively affect the individual fitness. Alternatives are low-impact techniques such as the use of photos for individual identification, for species with stable distinctive phenotypic traits. For the individual identification of photos, a variety of different software, with different requirements, is available. The European fire salamander ( Salamandra salamandra ) is a species in which individuals, both at the larval stage and as adults, have individual specific patterns that allow for individual identification. In this study, we compared the performance of five different software for the use of photographic identification for the European fire salamander: Amphibian & Reptile Wildbook (ARW), AmphIdent, I3S pattern+, ManderMatcher and Wild-ID. While adults can be identified by all five software, European fire salamander larvae can currently only be identified by two of the five (ARW and Wild-ID). We used one dataset of European fire salamander larval pictures taken in the laboratory and tested this dataset in two of the five software (ARW and Wild-ID). We used another dataset of European fire salamander adult pictures taken in the field and tested this using all five software. We compared the requirements of all software on the pictures used and calculated the False Rejection Rate (FRR) and the Recognition Rate (RR). For the larval dataset (421 pictures) we found that the ARW and Wild-ID performed equally well for individual identification (99.6% and 100% Recognition Rate, respectively). For the adult dataset (377 pictures), we found the best False Rejection Rate in ManderMatcher and the highest Recognition Rate in the ARW. Additionally, the ARW is the only program that requires no image pre-processing. In times of amphibian declines, non-invasive photo identification software allowing capture-mark-recapture studies help to gain knowledge on population sizes, distribution, movement and demography of a population and can thus help to support species conservation.

The combination of niche modelling and landscape genetics (genomics) helps to disentangle processes that have shaped population structure in the evolutionary past and presence of species. Herein, we integrate a comprehensive genomic dataset with ecological parameters and niche modelling for the threatened Kaiser’s newt, a newt species adapted to mountain spring-ponds in Iran. Genomic analysis suggests the existence of two highly differentiated clades North and South of the Dez River. Genetic variation between the two clades (76.62%) was much greater than within clades (16.25%), suggesting that the Dez River prevented gene flow. River disconnectivity, followed by geographic distance, contributed mostly to genetic differentiation between populations. Environmental niche and landscape resistance had no significant influence. Though a significant difference between climatic niches occupied by each clade at the landscape-scale, habitat niches at the local-scale were equivalent. ‘Niche similarity analysis’ supported niche conservatism between the two clades despite the southward shift in the climatic niche of the Southern clade. Accordingly, populations of different clades may occupy different climatic niches within their ancestral niche. Our results indicate that the change of climatic conditions of geographically and genetically separated populations does not necessarily result in the shift of an ecological niche.

Recognizing the influence of pathogen diversity on infection dynamics is crucial for mitigating emerging infectious diseases. Characterising such diversity is often complex, for instance when multiple pathogen variants exist that interact differently with the environment and host. Here, we explore genotypic and phenotypic variation of Batrachochytrium salamandrivorans ( Bsal ), an emerging fungal pathogen that is driving declines among an increasing number of European amphibian species. For thirteen isolates, spanning most of the known temporal and geographical Bsal range in Europe, we mapped phenotypic diversity through numerous measurements that describe varying reproductive rates in vitro across a range of temperatures. Bsal isolates are revealed to have different thermal optima and tolerances, with phenotypic variation correlating with genomic diversity. Using a mechanistic niche model of the fire salamander ( Salamandra salamandra ) as an example, we illustrate how host steady-state body temperature and Bsal thermal range variation may influence pathogen growth through space and time across Europe. Our combined findings show how the identity of emergent pathogen variants may strongly influence when and which host populations are most at risk.

Population surveys are essential for conservation, but are often resource-intensive. Modern technologies, like drones, facilitate data collection but increase the analysis burden. Citizen Science (CS) offers a solution by engaging non-specialists in data analysis. We evaluated CS for monitoring marine iguanas, focusing on volunteers’ accuracy in detecting and counting individuals in aerial images. During three phases of our Zooniverse project, over 13,000 volunteers contributed 1,375,201 classifications from 57,838 images; each classified up to 30 times. Using a Gold Standard dataset of expert counts from 4,345 images, we evaluated optimal aggregation methods for CS-inputs. Volunteers achieved 68–94% accuracy in detection, with more false negatives than false positives. The standard ‘majority vote’ aggregation approach (where the answer given by the majority of individual inputs is selected) produced less accuracy than when a minimum threshold of five volunteers (from the total independent classifications) was used. Image quality significantly influenced accuracy; by excluding suboptimal pilot-phase data, volunteer counts were 91–92% accurate. HDBSCAN clustering yielded the best results. We conclude that volunteers can accurately identify and count marine iguanas from drone images, though there is a tendency for undercounting. However, even CS-based data analysis remains relatively resource-intensive, underscoring the need to develop an automated approach.

Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species' geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes. We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype‐environment associations and genomic offset) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD‐seq, ddRAD‐seq, whole genome sequencing data) representing environmental variation across the species geographic range. To demonstrate multi‐species applicability, we apply our toolbox to three georeferenced genomic datasets for co‐occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatus and A. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escalerai and M. crypticus). Our framework sets the stage for large scale, multi‐species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers.

Background Globally, the disease ecology of reptiles remains understudied, even for threatened and iconic species such as the Galápagos marine iguana ( Amblyrhynchus cristatus ). Although marine iguanas are parasitized by distinct species of ticks and mites, research on vector-borne diseases for this species is limited. Methods In this study, we detected 16S ribosomal RNA (rRNA) sequences of Candidatus Allocryptoplasma in transcriptomic data from marine iguana blood samples. These 16S rRNA sequences were further characterized through phylogenetic analysis and a haplotype network. Results Our analysis revealed the first molecular evidence for the infection of marine iguanas with Candidatus Allocryptoplasma, a candidate genus in the family Anaplasmataceae with unknown pathogenic potential, likely transmitted by ticks. Phylogenetic analysis of the novel 16S rRNA sequences together with available Anaplasmataceae sequences confirmed their assignment to this candidate genus. A haplotype network analysis indicated that the agent infecting the marine iguana represents a distinct lineage within the known Ca . Allocryptoplasma diversity. Conclusions Candidatus Allocryptoplasma had a high prevalence within marine iguanas, infecting individuals across most of the geographical range of this species. To elucidate the transmission dynamics of this bacterium in the Galápagos ecosystem, ectoparasites of the marine iguana and shared vertebrate hosts should be screened for infection with Ca . Allocryptoplasma. Graphical Abstract

Background Large-scale species monitoring remains a significant conservation challenge. Given the ongoing biodiversity crisis, the need for reliable and efficient methods has never been greater. Drone-based techniques have much to offer in this regard: they allow access to otherwise unreachable areas and enable the rapid collection of non-invasive field data. Herein, we describe the development of a drone-based method for the estimation of population size in Galápagos marine iguanas, Amblyrhynchus cristatus . As a large-bodied lizard that occurs in open coastal terrain, this endemic species is an ideal candidate for drone surveys. Almost all Amblyrhynchus subspecies are Endangered or Critically Endangered according to the IUCN yet since several colonies are inaccessible by foot, ground- based methods are unable to address the critical need for better census data. In order to establish a drone-based approach to estimate population size of marine iguanas, we surveyed in January 2021 four colonies on three focal islands (San Cristobal, Santa Fe and Espanola) using three techniques: simple counts (the standard method currently used by conservation managers), capture mark-resight (CMR), and drone-based counts. The surveys were performed within a 4-day window under similar ambient conditions. We then compared the approaches in terms of feasibility, outcome and effort. Results The highest population-size estimates were obtained using CMR, and drone-based counts were on average 14% closer to CMR estimates—and 17–35% higher—than those obtained by simple counts. In terms of field-time, drone-surveys can be faster than simple counts, but image analyses were highly time consuming. Conclusion Though CMR likely produces superior estimates, it cannot be performed in most cases due to lack of access and knowledge regarding colonies. Drone-based surveys outperformed ground-based simple counts in terms of outcome and this approach is therefore suitable for use across the range of the species. Moreover, the aerial approach is currently the only credible solution for accessing and surveying marine iguanas at highly remote colonies. The application of citizen science and other aids such as machine learning will alleviate the issue regarding time needed to analyze the images.

The effects of the direct interaction between hybridization and speciation—two major contrasting evolutionary processes—are poorly understood. We present here the evolutionary history of the Galápagos marine iguana (Amblyrhynchus cristatus) and reveal a case of incipient within-island speciation, which is paralleled by between-island hybridization. In-depth genome-wide analyses suggest that Amblyrhynchus diverged from its sister group, the Galápagos land iguanas, around 4.5 million years ago (Ma), but divergence among extant populations is exceedingly young (less than 50 000 years). Despite Amblyrhynchus appearing as a single long-branch species phylogenetically, we find strong population structure between islands, and one case of incipient speciation of sister lineages within the same island—ostensibly initiated by volcanic events. Hybridization between both lineages is exceedingly rare, yet frequent hybridization with migrants from nearby islands is evident. The contemporary snapshot provided by highly variable markers indicates that speciation events may have occurred throughout the evolutionary history of marine iguanas, though these events are not visible in the deeper phylogenetic trees. We hypothesize that the observed interplay of speciation and hybridization might be a mechanism by which local adaptations, generated by incipient speciation, can be absorbed into a common gene pool, thereby enhancing the evolutionary potential of the species as a whole.

Biodiversity is under increasing pressure from environmental change, although the scope and severity of these impacts remain incompletely understood. For many species, a lack of information about population‐specific responses to future environmental change hinders the development of effective conservation strategies. Here, we use an East African reed frog species complex as a model to explore spatial variation in vulnerability to future environmental changes. Our sampling across two threatened biodiversity hotspots spans the entire geographic range of H. mitchelli and H. rubrovermiculatus in Kenya, Tanzania, and Malawi. Using genome‐wide (ddRAD‐seq) data, we evaluate levels of neutral genetic diversity and local adaptations across sampling localities. We then integrate spatial approaches (genomic offset, modeled dispersal barriers, and Species Distribution Models) to predict how populations may respond differently to future environmental changes, such as climate warming and predicted land use changes. Based on our analyses, we characterize population structure and identify region‐specific management needs that reflect genetic variation among populations and the uneven impacts of predicted change across the landscape. Peripheral populations are most vulnerable to future environmental changes due to (i) low levels of neutral genetic diversity (Malawi and Pare mountains in Tanzania), (ii) putative signals of local adaptation to wetter conditions with predicted disruptions to genotype–environment associations (i.e., high genomic offset, Kenya and Northern Tanzania), and (iii) the projected contraction of suitable habitat, which is a pervasive threat to the species complex in general. Populations in Northern, Central, and Southern Tanzania show the lowest vulnerability to environmental change and may serve as important reservoirs of genetic diversity for potential future genetic rescue initiatives. Our study highlights how populations across different parts of species ranges may be unevenly affected by future global changes and provides a framework to predict which conservation actions may help mitigate these effects.