Wildlife Populations Research Articles

Interactions between migration and immunity among oriental armyworm populations infected with the insect pathogenic fungus, Beauveria bassiana.

Migration and immunity are behavioral and physiological traits that protect organisms from environmental stressors or pathogen infection. Shifting from migration to residency has become more common in some wildlife populations owing to environmental changes. However, other biological shifts, such as interactions between migration and immunity among populations within a species are largely unexplored for many agricultural migratory pests. In the field, entomopathogenic fungi infection and transmission, particularly Beauveria bassiana, can cause reduced fitness and population declines across a broad range of insect species. Here, we investigated migration-immunity interactions between migrant and resident populations of the oriental armyworm, Mythimna separata, infected with B. bassiana (the sole fungus used in this work). We found that migratory M. separata exerted stronger pathogen resistance, faster development and lower pupal weight than residents. High-dose infections (5.0 × 105 and 5.0 × 106 conidia mL-1) led to seriously decreased reproductive capacity in migrants and residents. Low-dose infections (1.0 × 104 and 5.0 × 104 conidia mL-1) led to significantly increased host flight capacities. Consecutive flight tests showed that five flight nights inhibited the reproduction of paternal infected M. separata populations. The flights also led to far-reaching transgenerational impairment of larval development and immune defense among offspring populations. By contrast, two flight nights enhanced the reproductive capacities of both M. separata populations and did not exert negative transgenerational effects on offspring populations, which may facilitate migration. This study provides insights into interactions between migration and immunity among M. separata populations. These insights will guide development of future monitoring and management technologies of this pest. © 2024 Society of Chemical Industry.

How many sequences should I track when applying the random encounter model to camera trap data?

AbstractThe random encounter model (REM) is a camera trapping method to estimate population density (i.e. number of individuals per unit area) without the need for individual recognition. The REM can be applied considering camera trap data only by tracking the passages of animals in front of the camera (i.e. sequences). However, it has not been assessed how the number of sequences tracked (i.e. trajectory of the animal reconstructed) influences the REM estimates. In this context, we aimed to gain further insights into the relationship between the number of sequences tracked and reliability in REM estimates to optimize its applicability. We monitored multiple species using camera traps, and we applied REM to estimate population density. We considered red fox Vulpes vulpes, roe deer Capreolus capreolus, fallow deer Dama dama, red deer Cervus elaphus and wild boar Sus scrofa as model species. We tracked from a minimum of 154 (red fox) to a maximum of 527 (red deer) sequences per species, and we then sampled the dataset to simulate different scenarios in which a lower number of sequences were tracked (20, 40, 80 and 160). We also assessed the effect of adjusting the survey period to the minimum necessary to record the desired number of sequences. Our results suggest that tracking around 100 sequences returns a precision level equivalent to the one obtained by tracking a considerably higher number of sequences and reduced and optimized the human effort necessary to apply REM. Tracking less than 40 sequences could result in low precise density estimates. Our results also highlighted the relevance of considering study periods of ca. 2 months to increase the number of sequences recorded and tracking a random sample of them. Our results contribute to the optimization and harmonization of REM as a reference method to estimate wildlife population density without the need for individual identification. We make clear recommendations on the cost‐effective sample size for estimating REM parameters, optimizing the human effort when applying REM, and discouraging REM applications based on low sample sizes.

Identification of landscape features structuring movement connectivity for Namibian elephants

ContextHuman modification of landscapes poses a significant threat to wildlife, particularly in Africa where population growth and land conversion are expected to increase. Habitat loss and fragmentation have led to declines in wildlife populations, highlighting the need to identify and preserve critical habitats, including core use areas and connectivity between them. Most recently, the identification of habitat corridors has become a key objective.ObjectivesOur study objectives are to (1) empirically quantify connectivity across the Kunene—Etosha landscape in Northwestern Namibia using GPS tracking data on wild African elephants, and (2) assess the landscape features (i.e., geologic, biotic, and human-made) influencing connectivity and corridor types (e.g., fast movement corridors versus slow multi-use movement corridors).MethodsWe used GPS telemetry data from 66 elephants collared in Northwestern Namibia to empirically quantify connectivity using a graph theoretic approach and assess landscape features influencing connectivity. Based on the ‘movescape’ approach, we identify different types of corridors and examined how landscape features differed across these corridors using multiple regression models on locations classified into different types of use categories by machine learning algorithms.ResultsOur results revealed strong variation in connectivity across the landscape, with paths of high connectivity near water sources between the study areas. We found that factors related to water sources and human presence primarily influenced connectivity. Water holes serve as hubs across the ecosystem for both male and female elephants with lower use areas peripheral to areas with water. Connectivity between Kunene and Etosha National Park was relatively rare among the collared elephants, but we highlight the key areas used to move between the two regions.ConclusionWater was the key feature structuring space use, and human presence influenced connectivity between water points, highlighting the importance of landscape planning in relation to limited water sources and human activities. Our results suggest that focusing management efforts on areas where water is limited for both elephants and humans will be important to reduce conflict and maintain ecosystem connectivity.

The complex effects of modern oncogenic environments on the fitness, evolution and conservation of wildlife species.

Growing evidence indicates that human activities are causing cancer rates to rise in both human and wildlife populations. This is due to the inability of ancestral anti-cancer defences to cope with modern environmental risks. The evolutionary mismatch between modern oncogenic risks and evolved cancer defences has far-reaching effects on various biological aspects at different timeframes, demanding a comprehensive study of the biology and evolutionary ecology of the affected species. Firstly, the increased activation of anti-cancer defences leads to excessive energy expenditure, affecting other biological functions and potentially causing health issues like autoimmune diseases. Secondly, tumorigenesis itself can impact important fitness-related parameters such as competitiveness, predator evasion, resistance to parasites, and dispersal capacity. Thirdly, rising cancer risks can influence the species' life-history traits, often favoring early reproduction to offset fitness costs associated with cancer. However, this strategy has its limits, and it may not ensure the sustainability of the species if cancer risks continue to rise. Lastly, some species may evolve additional anti-cancer defences, with uncertain consequences for their biology and future evolutionary path. In summary, we argue that the effects of increased exposure to cancer-causing substances on wildlife are complex, ranging from immediate responses to long-term evolutionary changes. Understanding these processes, especially in the context of conservation biology, is urgently needed.

Correcting for measurement errors in a long‐term aerial survey with auxiliary photographic data

AbstractLong‐term, large‐scale monitoring of wildlife populations is an integral part of conservation research and management. However, some traditional monitoring protocols lack the information needed to account for sources of measurement error in data analyses. Ignoring measurement error, such as partial availability, imperfect detection, and species misidentification, can lead to mischaracterizations of population states and processes. Accounting for measurement error is key to robust monitoring of populations, which can inform a wide variety of decisions, including harvest, habitat restoration, and determination of the legal status of species. We undertook an effort to retroactively minimize bias in a large‐scale, long‐term monitoring program for marine birds in the Salish Sea, Washington, USA, by conducting an auxiliary study to jointly estimate components of measurement error. We built a novel model in a Bayesian framework that simultaneously harnessed human observer and photographic data types to produce estimates necessary to correct for the effects of partial availability, imperfect detection, and species misidentification. Across all 31 species identified in photographs, both observers had instances of undercounting and overcounting birds but tended to undercount (observers undercounted totals across all species on 69.3%–78.9% of transects). We estimated species‐specific correction factors that can be used to correct both historical and future counts from the Salish Sea survey, which has been running since 1992. Our novel modeling framework can be applied in other multispecies monitoring contexts where minimal photographic data can be collected for the purposes of correcting for measurement error in large‐scale, long‐term datasets.

Surveillance of SARS-CoV-2 Infection in Rodent Populations in Tokyo, Japan.

The maintenance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among wildlife populations poses a potential risk for the emergence of novel variants. Therefore, monitoring SARS-CoV-2 infection among animals is crucial. As urban rodents live in close proximity to human habitats, there is concern that they may be a potential source of zoonoses. To examine the prevalence of SARS-CoV-2 in rodent populations, we analyzed 128 serum samples and 129 oral swabs collected from 128 brown rats (Rattus norvegicus) and 2 black rats (Rattus rattus) captured for pest control purposes in Tokyo, Japan, between May and December 2023. A virus-neutralizing test using the Omicron variant revealed no evidence of SARS-CoV-2 infection in these populations. Real-time RT-PCR from oral swabs did not detect any SARS-CoV-2 RNA-positive rats. These results indicate the low probability of SARS-CoV-2 circulation among rat populations in Tokyo.

Wildlife Tracker using Deep Learning

Wildlife tracker using deep learning is a project aimed at developing a system that can automatically detect wild animals using deep learning techniques. Conservationists and researchers face challenges in accurately and efficiently detecting and monitoring wildlife populations in vast and often remote habitats. Traditional methods of wildlife monitoring, such as manual surveys or camera traps, are labour-intensive, time-consuming, and may not provide real-time insights into population dynamics or threats facing wildlife species. The proposed system aims to address these challenges by developing an automated animal detection system using the YOLOv8 object detection model. The system will be trained on a diverse dataset of wildlife images, encompassing various species and environmental conditions. Upon deployment, the system will analyse input images and accurately identify and localize animals within the scene in real-time. Through this approach, the system will provide conservationists and researchers with timely and actionable information for monitoring wildlife populations, assessing habitat health, and implementing targeted conservation interventions. Evaluation of the system's performance will involve metrics such as detection accuracy, precision, recall, and processing speed, ensuring reliable and efficient wildlife detection capabilities. Overall, the proposed system seeks to enhance wildlife conservation efforts by leveraging advanced technology to improve wildlife monitoring and management practices and provide real-time alert.

A novel technique for estimating age and demography of long-lived seabirds (genus Pterodroma) using an epigenetic clock for Gould's petrel (Pterodroma leucoptera).

Understanding the demography of wildlife populations is a key component for ecological research, and where necessary, supporting the conservation and management of long-lived animals. However, many animals lack phenological changes with which to determine individual age; therefore, gathering this fundamental information presents difficulties. More so for species that are rare, highly mobile, migratory and those that reside in inaccessible habitats. Until recently, the primary method to measure demography is through labour intensive mark-recapture approaches, necessitating decades of effort for long-lived species. Gadfly petrels (genus: Pterodroma) are one such taxa that are overrepresented with threatened and declining species, and for which numerous aspects of their ecology present challenges for research, monitoring and recovery efforts. To overcome some of these challenges, we developed the first DNA methylation (DNAm) demography technique to estimate the age of petrels, using the epigenetic clock of Gould's petrels (Pterodroma leucoptera). We collected reference blood samples from known-aged Gould's petrels at a long-term monitored population on Cabbage Tree Island, Australia. Epigenetic ages were successfully estimated for 121 individuals ranging in age from zero (fledgling) to 30 years of age, showing a mean error of 2.24 ± 0.17 years between the estimated and real age across the population. This is the first development of an epigenetic clock using multiplex PCR sequencing in a bird. This method enables demography to be measured with relative accuracy in a single sampling trip. This technique can provide information for emerging demographic risks that can mask declines in long-lived seabird populations and be applied to other Pterodroma populations.

Clinical Coxiella burnetii infection in sable and roan antelope in South Africa.

Various zoonotic microorganisms cause reproductive problems such as abortions and stillbirths, leading to economic losses on farms, particularly within livestock. In South Africa, bovine brucellosis is endemic in cattle, and from 2013-2018, outbreaks ofBrucella melitensisoccurred in sable.Coxiella burnetii, the agent responsible for the zoonotic disease known as Q-fever and/or coxiellosis, also causes reproductive problems and infects multiple domestic animal species worldwide, including humans. However, little is known of this disease in wildlife. With the expansion of the wildlife industry in South Africa, diseases like brucellosis and coxiellosis can significantly impact herd breeding success because of challenges in identifying, managing and treating diseases in wildlife populations. This study investigated samples obtained from aborted sable and roan antelope, initially suspected to be brucellosis, from game farms in South Africa using serology tests and ruminant VetMAX™ polymerase chain reaction (PCR) abortion kit. The presence ofC. burnetiiwas confirmed with PCR in a sable abortion case, while samples from both sable and roan were seropositive forC. burnetiiindirect enzyme-linked immunosorbent assay (iELISA). This study represents the initial report ofC. burnetiiinfection in sable and roan antelope in South Africa. Epidemiological investigations are crucial to assess the risk ofC. burnetiiin sable and roan populations, as well as wildlife and livestock in general, across South Africa. This is important in intensive farming practices, particularly as Q-fever, being a zoonotic disease, poses a particular threat to the health of veterinarians and farm workers as well as domestic animals.Contribution:A report of clinicalC. burnetiiinfection in the wildlife industry contributes towards the limited knowledge of this zoonotic disease in South Africa.

Realities, perceptions, and strategies for implementation of an ethical population management program for dogs and cats on university campuses.

Stray dogs and cats pose significant challenges for public health and animal welfare due to their potential involvement in zoonotic disease transmission, accidents, and aggressions. Large urban centers exacerbated challenges due to the presence of these animals in public areas with high human density. Ethical Population Management Programs (EPMP), rooted in the One Health approach, are crucial for addressing this issue comprehensively. This study aimed to demonstrate the approach on cats and dogs EPMP and evaluate the perceptions of academic community regarding EPMP implementation on a campus situated in urban territory. The study was conducted at the Pampulha campus of UFMG in Belo Horizonte, Brazil. In response to issues of animal abandonment and conflicts, the Permanent Commission for Animal Policies (CPPA-UFMG) was established in 2019 to manage the campus's dog, cat, and wildlife populations. The commission implemented the Trap-Neuter-Return (TNR) method, along with health assessments and vaccinations for animals. Interviews were conducted with campus staff to gauge their perception of animal management strategies. Retrospective and prospective analyses of the commission's actions were carried out to assess implementation processes and challenges. The animal population survey conducted on campus between July 2018 and September 2021 revealed a total of 266 animals recorded. Among these animals, 195 were cats (73.3%) and 71 were dogs (26.7%), with the majority being adults. Subsequent surveys in 2019 and 2021 showed a slight increase in the animal population, with measures such as sterilization contributing to population control. Perception analysis among campus users indicated strategies such as TNR were widely endorsed for population control. The employees perception questionnaire was applied to 115 individuals, representing 42 units/departments and five gates. Associations were found between these beliefs and support for institutional actions. The majority favored sterilization (92.17%) and agreed that TNR is an appropriate approach to population control. Overall, the study reflects a community concerned about animal welfare and supportive of measures to address population management and cruelty prevention. The continuous efforts of the university's CPPA have led to stability in the resident animal population, indicating success in achieving population control objectives.

The effects of variability in catch effort on the precision of statistical population reconstruction

Statistical population reconstruction (SPR) models have emerged as a robust and versatile framework for estimating the demographic dynamics of harvested wildlife populations using commonly collected age‐at‐harvest and catch‐effort data. Although numerous studies have suggested that higher interannual variability in catch effort may improve the accuracy and precision of reconstructed estimates, particularly in the absence of auxiliary data on annual abundance or survival, the extent and magnitude of these effects has not been explored. We examined the influence of catch‐effort variability, as measured by the ratio between years of highest and lowest effort, on the relative absolute deviation of reconstructed estimates of population abundance, as well as on the actual percent coverage and width of the corresponding confidence intervals. We used a Monte Carlo simulation to generate catch‐effort data with different levels of variability for populations experiencing a wide range of demographic and harvest conditions. For similar amounts of age‐at‐harvest data, using catch‐effort data with higher interannual variability resulted in reconstructed estimates of annual abundance that had significantly lower deviations from reality, better coverage, and narrower confidence intervals (as measured by the margin of error). These improvements were consistent and linear at low to medium levels of catch‐effort variability, but leveled off and became substantially less pronounced at higher levels. We found that the inclusion of auxiliary data largely mediated this relationship, although higher catch‐effort variability still resulted in more accurate and precise estimates of annual abundance even when these data were included. Our research highlights the need to include a thorough investigation of the available catch‐effort data alongside the established practices of assessing the number of years of available data, the average number of animals harvested each year, and the availability of auxiliary data from radio‐telemetry studies or other sources.

Recovering connectivity through restoration corridors in a fragmented landscape in the magdalena river’s valley in Colombia

Forest fragmentation is one of the main drivers of global biodiversity loss leading to the isolation of wildlife populations. This study focuses on understanding the role of restoration corridors as a strategy promoting resilience and viability of mammal and bird populations in a fragmented landscape in Colombia. We installed 98 camera-trap stations − 8497 camera-trap days - in four different land cover categories: (1) forest fragments, (2) natural corridors, (3) stablished corridors and (4) pastures. We evaluated if restoration corridors do promote connectivity for large vertebrates and recover species richness and functional diversity lost in anthropogenically transformed pastures. We used indices of taxonomic and functional diversity and a non-metric multidimensional scaling to evaluate the influence of land cover over mammal and bird communities. Both, species richness and functional diversity have higher values in forests, followed by natural corridors and corridors and lower values in open pastures. Differences in species composition were greater between forests and pastures, and species composition of restoration corridors begins to resemble that of riparian forests and forest fragments. Our results provide initial evidence on the role of restoration corridors as an efficient strategy aimed to recover biodiversity and functional diversity in pervasively fragmented landscapes.

Using mobile acoustic monitoring and false‐positive N‐mixture models to estimate bat abundance and population trends

AbstractEstimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false‐positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white‐nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats (Perimyotis subflavus) and little brown bats (Myotis lucifugus), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population‐wide declines probably have not occurred in big brown bats (Eptesicus fuscus), a species known to be less affected by WNS. This study provides the first abundance‐based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false‐negative and false‐positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.

WILDPOP: AN INTERACTIVE TOOL FOR ESTIMATING OCCUPANCY AND ABUNDANCE OF WILDLIFE POPULATIONS

Species abundance or population size is an ecological parameter of critical importance for wildlife management and conservation decisions. Widely used data collection methods, such as sign surveys and remote cameras, often count non-identifiable individuals or individuals prone to misidentification. In ecological modeling, these individuals are considered unmarked, and a state-of-the-art modeling approach for such data is occupancy-type modeling for unmarked individuals, which explicitly incorporates imperfect detection. Hierarchical modeling of this kind requires advanced statistical analyses, typically conducted using the R software platform and the “unmarked” package. However, these models can be explored only by researchers with programming skills and a thorough understanding of hierarchical analysis of wildlife population data. To help researchers and practitioners implement these models, we have developed a Shiny web-based interactive tool for wildlife population assessment, which works with data collected by scientists and wildlife managers. This app facilitates the use of occupancy-type modeling for unmarked individuals (single-season single species occupancy and N-mixture models) for non-coder users. The app performs simulations for single-season single species occupancy and N-mixture models with or without covariates, and estimates occupancy and abundance employing users provided data. The results are displayed as text, tables, and graphs, helping users understand hierarchical modeling and answering real-life wildlife management questions.

Inbreeding and cognition in wild populations: a relationship that remains unnoticed

Anthropogenic activities are causing a steep decline of wildlife populations. Increased inbreeding in shrinking populations can substantially curb individual fitness and population viability. One potentially important but largely ignored component of inbreeding depression may be cognitive decline. Cognition affects an animal's capacity to respond to environmental disturbance, which, in the face of global change, may make the difference between persistence and extinction. While the effects of inbreeding on cognitive performance have been relatively well documented in humans, they remain largely unexplored in natural populations. Here we review the current (limited) knowledge on whether and how inbreeding impinges on animals' cognitive abilities. Insights into the relationship between inbreeding and cognition could prove valuable not only for comprehending the development and evolution of cognition but also for conservation.

Diet and seed dispersal of bearded capuchin monkeys (Sapajus libidinosus) in Brasilia National Park.

The dietary ecology of a species can provide information on habitat requirements, food resources, and trophic interactions, important to guide conservation efforts of wildlife populations in endangered habitats. In this study, we investigated the dietary ecology of bearded capuchin monkeys (Sapajus libidinosus) in Brasilia National Park, in the endangered Cerrado biome of central Brazil. To obtain diet composition and evaluate the role of these primates as seed dispersers of local tree species, fecal sample collections and feeding observations were performed for a 7-month period. To determine whether seeds germinated better after passing through a primate gut, we conducted germination trials with (i) pulped seeds from trees, (ii) depulped seeds from trees, (iii) seeds from feces planted with feces, and (iv) seeds from feces planted without feces. During experimental procedures, 7308 seeds from 8 families and 10 species were planted. We found that S. libidinosus spent more time feeding on fruits than on any other food item and the diet consisted of 33 plant species from 21 families. However, 20% of their diet consisted of anthropic food. Most seeds planted with feces germinated faster compared to seeds in other experimental treatments, suggesting that passing through the gut and being deposited with fecal material is advantageous. The bearded capuchins also defecated many medium- (5 species) and large-sized (2 species) seeds that may be inaccessible to smaller arboreal frugivores. The results obtained emphasize the important role of bearded capuchins as seed dispersers for the maintenance and conservation of the endangered Cerrado biome.

Gastrointestinal parasites of Wolffsohn's viscacha (Chinchillidae: Lagidium wolffsohni), an endemic rodent species from the wild Patagonia.

Parasites are ubiquitous in wildlife populations and have a profound impact on population dynamics. Interest in parasites of wildlife has increased significantly in recent years, particularly in those with relevant conservation status. Patagonia is one of the wildest and remote areas of the world. The Wolffsohn's viscacha lives in a small mountainous area of Patagonia. Until now, little is known about the biology and ecology of this species. The aim of this research was to study the gastrointestinal parasite diversity in this rodent from a coprological survey. A total of 125 fecal samples from 25 colonies were examined. Each sample was rehydrated, homogenized, and analyzed using three parasitological techniques: spontaneous sedimentation, Mini-FLOTAC, and centrifugation-flotation in sucrose-saturated solution, followed by examination under optical microscopy. The samples, eggs, and oocysts of parasites were described, measured, and photographed. All colonies were positive for at least one parasite species. A total of 10 parasitic species were identified: Viscachataenia sp., possibly V. quadrata, Monoecocestus sp., an unidentified anoplocephalid, Heteroxynema sp., possibly H. (Cavioxyura) viscaciae, Helminthoxys sp., possibly H. effilatus, an unidentified strongylid-type egg, Trichuris sp., two morphologies of unidentified coccidians and Eimeria sp. This is the first exhaustive study of gastrointestinal parasites in L. wolffsohni and a large number of eggs and oocysts of parasites were found. Our results highlight the use of noninvasive techniques for the study of parasites of wildlife hosts; as in the case of this rodent with a remote habitat, which makes sampling difficult. The results of our study provide baseline information on gastrointestinal parasite infections in this species.

Enhancement of a Simple, Economic and Eco-Friendly Analytical Approach for the Extraction and Determination of Endocrine Disruptors from Plastics in Shrimp

The economic significance of the shrimp industry relies heavily on the comprehensive utilization of all of the shrimp’s parts. However, this importance is often threatened by common challenges such as disease and pollution, caused by prominent contaminants that are capable of exerting adverse effects either directly as physical pollutants or indirectly through the incorporation of additives or adsorbed chemicals. Among these substances are endocrine disruptors, which pose risks to both wildlife and human populations. In this study, 11 endocrine-disrupting compounds were determined (3 bisphenols, 3 phthalates, 3 pesticides, and 2 nonylphenols) through the development of a cost-effective, greener and cost-friendly method based on solid-phase matrix dispersion (MSPD) with high-performance liquid chromatography coupled with diode array detection (HPLC-DAD). Determinations were performed on different parts of the shrimp: the cephalothorax, abdomen, intestine and shell. Several variables were optimized in the extraction, separation and detection phases, resulting in average recoveries of about 90%. The limit of detection (LOD) varies depending on the analyte and matrix. At concentrations of 1 mg/kg in the cephalothorax+shells and 1.25 mg/kg in the abdomen+intestine, all compounds were detected, except for nonylphenols. The developed method has allowed the simultaneous determination of 11 endocrine disruptors in different parts of the shrimp samples. Furthermore, the MSPD has been demonstrated to be an efficacious, selective, and streamlined sample extraction method, eliminating the necessity for pretreatment steps such as centrifugation and filtration, as well as the use of large volumes of solvents.

Contrasting patterns of spatial genetic structure in endangered southern damselfly (Coenagrion mercuriale) populations facing habitat fragmentation and urbanisation

AbstractAimHuman‐induced environmental changes result in habitat loss and fragmentation, impacting wildlife population genetic structure and evolution. Urbanised and geographically peripheral areas often represent unfavourable environments, reducing connectivity among populations and causing higher population genetic differentiation and lower intra‐population genetic diversity. We examined how geographic peripherality and anthropogenic pressures affect genetic diversity and genetic differentiation in the protected southern damselfly (Coenagrion mercuriale, Odonata), which has low dispersal capabilities and specific habitat requirements and whose populations are declining.LocationWe studied two areas: one in semi‐natural habitats at the periphery of the species geographic range (northern France) and the other more central to the species' range, in an urbanised area surrounding the city of Strasbourg (Alsace, eastern France).MethodsWe genotyped 2743 individuals from 128 populations using 11 microsatellite loci. We analysed the spatial distribution of neutral genetic diversity (allelic richness, heterozygosity, levels of inbreeding and genetic relatedness), the extent of genetic differentiation and population affiliations (sPCAs) within the two areas. We also examined fine‐scale patterns of gene flow in the urbanised area of Alsace by investigating patterns of isolation by distance and estimating effective migration surfaces (EEMS) method.ResultsNorthern peripheral populations showed lower levels of genetic diversity and higher levels of genetic differentiation than central Alsacian populations. Although located in anthropised habitats, geographically central Alsacian populations showed high levels of gene flow, with dispersal events mainly occurring overland and not restricted to watercourses. However, the highly urbanised city of Strasbourg negatively impacted nearby populations by reducing levels of genetic diversity and increasing population genetic differentiation.Main ConclusionsThese results showed the need for management action by restoring breeding sites and creating migratory corridors for peripheral southern damselfly populations. However, our results also highlighted the resilience of southern damselfly in central range populations facing strong urbanisation pressures.

Relating gut microbiome composition and life history metrics for pronghorn (Antilocapra americana) in the Red Desert, Wyoming.

Host microbial communities (hereafter, the 'microbiome') are recognized as an important aspect of host health and are gaining attention as a useful biomarker to understand the ecology and demographics of wildlife populations. Several studies indicate that the microbiome may contribute to the adaptive capacity of animals to changing environments associated with increasing habitat fragmentation and rapid climate change. To this end, we investigated the gut microbiome of pronghorn (Antilocapra americana), an iconic species in an environment that is undergoing both climatic and anthropogenic change. The bacterial composition of the pronghorn gut microbiome has yet to be described in the literature, and thus our study provides important baseline information about this species. We used 16S rRNA amplicon sequencing of fecal samples to characterize the gut microbiome of pronghorn-a facultative sagebrush (Artemisia spp.) specialist in many regions where they occur in western North America. We collected fecal pellets from 159 captured female pronghorn from four herds in the Red Desert of Wyoming during winters of 2013 and 2014. We found small, but significant differences in diversity of the gut microbiome relative to study area, capture period, and body fat measurements. In addition, we found a difference in gut microbiome composition in pronghorn across two regions separated by Interstate 80. Results indicated that the fecal microbiome may be a potential biomarker for the spatial ecology of free-ranging ungulates. The core gut microbiome of these animals-including bacteria in the phyla Firmicutes (now Bacillota) and Bacteroidota-remained relatively stable across populations and biological metrics. These findings provide a baseline for the gut microbiome of pronghorn that could potentially be used as a target in monitoring health and population structure of pronghorn relative to habitat fragmentation, climate change, and management practices.