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42 results for “wildlife populations”
Bacterial zoonoses impacts to conservation of wildlife populations: A global synthesis
<p>Emerging infectious diseases have significantly increased in recent years; approximately 60% of these emerging diseases are of zoonotic origin, and of those, around 70% were identified to start with wild animals. To better understand the impacts of zoonotic diseases on wildlife, there is a need to identify the distribution and impact of zoonotic pathogens in wildlife, particular those species with threatened populations. To investigate this question, we constructed a zoonotic disease database identifying wildlife hosts for each bacterial zoonotic disease and recorded clinical signs of disease for each host-pathogen relationship if found. Species of least concern were found to have a significantly higher prevalence and richness of zoonotic bacterial diseases (n= 0.0608, x<sup>2</sup>= 5.898, p=0.01516). The taxonomic level Order was found to be the best predictor for pathogen richness, and the Artiodactyla and Carnivora contain a significantly higher pathogen richness than other vertebrate Orders. Species with the greatest pathogen richness include the wild boar (<em>Sus scrofa</em>, n=66), Northern raccoon (<em>Procyon lotor</em>, n=16) and the red fox (<em>Vulpes vulpes</em>, n=41). Our results indicate bacterial zoonoses are not likely to be a driving factor of species population declines, and future zoonotic disease surveillance efforts should target species in the Artiodactyla and Carnivora families. The wild boar (<em>Sus scrofa</em>) in particular may be a good candidate for zoonotic disease monitoring due to its high pathogen richness, wide range, and large population. Understanding the impacts and distribution of bacterial zoonoses in wildlife populations can help in planning for future wildlife management efforts, particularly in species of conservation concern and wildlife disease monitoring.</p>
Data from: When can model-based estimates replace surveys of wildlife populations that span many discrete management units?
<p>Monitoring widely distributed species on a budget presents challenges for the spatio-temporal allocation of survey effort. When there are multiple discrete units to monitor, survey alternatives such as model-based estimates can be useful to fill information-gaps but may not reliably reflect biological complexity and change. The spatio-temporal allocation of survey effort that minimizes uncertainty for the greatest number of units within a budget can help to ensure monitoring efforts are optimized.</p> <p>We used aerial survey-based population estimates of moose (Alces alces) across 30 Wildlife Management Units (WMUs) in Ontario, Canada to parameterize simulated populations and test the performance of different monitoring scenarios in capturing WMU-specific annual variation and trends. Firstly, we tested scenarios that prioritized conducting a survey for a unit based on one of three management criteria: population state, population uncertainty, or number of years between surveys. Also incorporated in the decision framework were WMU-specific costs and annual budget constraints. Secondly, we tested how using model-based estimates to fill information-gaps improved population and trend estimates. Lastly, we assessed how the utility (based on minimizing population uncertainty) of using a model-based estimate rather than conducting a survey was impacted by population density, severity of environmental stressors, and years since the last survey.</p> <p>Interval-based monitoring that minimized the number of years between surveys captured accurate trends for the highest number of WMUs, but annual variation was poorly captured regardless of management criteria prioritized. Using model-based estimates to fill information gaps improved trend estimation. Further, the utility of conducting a survey increased with time since the last survey and was greater for populations with low densities when the severity of environmental stressors was high, while being greater for populations with high densities when environmental severity was low.</p> <p>Overall, the utility of aerial survey monitoring was strongly associated with WMU-specific monitoring precision and the predictive power of model-based estimates. If long-term trends are evident then there is greater value in using alternatives such as model-based predictions to replace surveys, but model-based estimates may be a poor substitute when there is strong annual variation and when using a simple model.</p>
Data from: Population and community consequences of perceived risk from humans in wildlife
<p><span>Human activities catalyze risk avoidance behaviors in wildlife across taxa and systems. However, the broader ecological significance of human-induced risk perception remains unclear, with a limited understanding of how phenotypic responses scale up to affect population or community dynamics. We conducted a comprehensive literature review of non-consumptive effects (NCE; population effects) and trait-mediated indirect effects (TMIE; community effects) of anthropogenic disturbances. This dataset includes all papers identified from the comprehensive review of the different types of human-induced behavioral and physiological phenotypic change and their influence on vital rates and population parameters in wildlife. All papers in this database tested for a human-induced NCE or TMIE in wildlife but not all found evidence for an effect. Many of the papers did not explicitly measure the presumed phenotypic change linking human activity to vital rates or population parameters. The authors, paper title, journal, publication year, type of human disturbance, species, system, phenotypic response measured, demographic response measured, if a demographic effect was found, and whether an NCE or TMIE was tested are all included in the dataset. In addition, we include the source of the paper in our dataset (i.e. whether it came up in our Web of Science search, as a citing paper of Frid and Dill (2002), or in a review paper on human-induced fear in wildlife; column A). The papers in which multiple NCE or TMIE pathways were tested may have multiple values in a single cell. Papers are sorted alphabetically by author. Evidence for human-induced NCEs and TMIEs is mixed, with half of published studies finding a relationship between human activities, phenotypic change, and population outcomes. Strong research biases in taxa, systems, human disturbance type, and demographic measures prevent unified inference about the prevalence of population responses to human activities. Coexistence with and conservation of wildlife requires additional research linking human-induced phenotypic change to population and community outcomes.</span></p>
Trypanosoma cruzi in Mexican Neotropical vectors and mammals: Wildlife, livestock, pets, and human population
<p><span>The aim of the present study has been to provide primary evidence of <em>Trypanosoma cruzi</em> landscape genetics in the Mexican Neotropics.</span><span> <em>T. cruzi</em> and DTU prevalence were analyzed in landscape communities of vectors, wildlife, livestock, pets, and sympatric human populations using endpoint PCR and sequencing of all relevant amplicons from mitochondrial (kDNA) and nuclear (ME, 18S, 24Sα) gene markers. Although 98% of the infected sample set (N=2963) contained single or mixed infections of DTUI (TcI, 96.2%) and TcVI (22.6%), TcIV and TcII were identified. The sensitivity of individual markers varied and was dependent on the host taxon; kDNA, ME, and 18S combined identified 95% of infections. ME genotyped 90% of vector infections, but 60% of mammals (36% wildlife), while neither 18S nor 24Sα typed more than 20% of mammal infections. Available gene fragments to identify or genotype <em>T. cruzi</em> are not universally sensitive for all landscape parasite populations, highlighting important <em>T. cruzi</em> heterogeneity among mammal reservoir taxa and triatomine species.</span></p>
Data for: Sex-biased infections scale to population impacts for an emerging wildlife disease
<p>Demographic factors are fundamental in shaping infectious disease dynamics. Aspects of populations that create structure, like age and sex, can affect patterns of transmission, infection intensity and population outcomes. However, studies rarely link these processes from individual to population-scale effects. Moreover, the mechanisms underlying demographic differences in disease are frequently unclear. Here, we explore sex-biased infections for a multi-host fungal disease of bats, white-nose syndrome, and link disease-associated mortality between sexes, the distortion of sex ratios, and the potential mechanisms underlying sex differences in infection. We collected data on host traits, infection intensity, and survival of five bat species at 42 sites across seven years. We found females were more infected than males for all five species. Females also had lower apparent survival over winter and accounted for a smaller proportion of populations over time. Notably, female-biased infections were evident by early hibernation and likely driven by sex-based differences in autumn mating behavior. Male bats were more active during autumn which likely reduced replication of the cool-growing fungus. Higher disease impacts in female bats may have cascading effects on bat populations beyond the hibernation season by limiting recruitment and increasing the risk of Allee effects.</p>
Data for: Sex-biased infections scale to population impacts for an emerging wildlife disease
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Data from: Population and community consequences of perceived risk from humans in wildlife
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Landscape-level toxicant exposure mediates infection impacts on wildlife populations
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Estimating wildlife populations and their dynamics using multiple data sources and a hierarchical integrated model: the case of California's black bears
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Data from: When can model-based estimates replace surveys of wildlife populations that span many discrete management units?
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Trypanosoma cruzi in Mexican Neotropical vectors and mammals: Wildlife, livestock, pets, and human population
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Bacterial zoonoses impacts to conservation of wildlife populations: A global synthesis
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Data from: A novel approach to wildlife transcriptomics provides evidence of disease-mediated differential expression and changes to the microbiome of amphibian populations
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Data from: An integrated framework to identify wildlife populations under threat from climate change
Climate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population-level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype-environment association analysis we identify potential climate-adaptive SNPs in our genomic dataset and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.
Data from: Long-term persistence of wildlife populations in a pastoral area
<p>Facilitating coexistence between people and wildlife is a major conservation challenge in East Africa. Some conservation models aim to balance the needs of people and wildlife, but the effectiveness of these models is rarely assessed. Using a case-study approach, we assessed the ecological performance of a pastoral area in northern Tanzania (Manyara Ranch) and established a long-term wildlife population monitoring programme (carried out intermittently from 2003-2008 and regularly from 2011-2019) embedded in a distance sampling framework. By comparing density estimates of the road-transect based long-term monitoring to estimates derived from systematically distributed transects, we found that the bias associated with non-random placement of transects was non-significant. Overall, cattle, and sheep and goat reached the greatest densities and several wildlife species occurred at densities similar (zebra, wildebeest, waterbuck, Kirk's dik-dik) or possibly even greater (giraffe, eland, lesser kudu, Grant's gazelle, Thomson's gazelle) than in adjacent national parks in the same ecosystem. Generalized linear mixed models suggested that most wildlife species (8 out of 14) reached greatest densities during the dry season, that wildlife population densities either remained constant or increased over the 17-year period, that herbivorous livestock species remained constant, while domestic dog population decreased over time. Cross-species correlations did not provide evidence for interference competition between grazing or mixed livestock species and wildlife species but indicate possible negative relationships between domestic dog and warthog populations. Overall, wildlife and livestock populations in Manyara Ranch appear to coexist over the 17-year span. Most likely, this is facilitated by existing connectivity to adjacent protected areas, effective anti-poaching efforts, spatio-temporal grazing restrictions, favourable environmental conditions of the ranch and spatial heterogeneity of surface water and habitats. This long-term case study illustrates the potential of rangelands to simultaneously support wildlife conservation and human livelihood goals if livestock grazing is restricted in space, time and numbers.</p>
Data from: An integrated framework to identify wildlife populations under threat from climate change
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Data from: Estimating effective population size of guanacos in Patagonia: an integrative approach for wildlife conservation
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Data from: Long-term persistence of wildlife populations in a pastoral area
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Drones, automatic counting tools and artificial neural networks in wildlife population censusing
<p>1. The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non-breeding periods was investigated.</p> <p>2. In 96% of 343 cases, drone counting was successful. 18.8% of non-breeding birds and 3.6% of breeding birds exhibited adverse reactions: the former birds were flushed, whereas the latter attempted to attack the drone.</p> <p>3. The automatic counting of birds was best done with ImageJ/Fiji microbiology software – the average counting rate was 100 birds in 64 seconds.</p> <p>4. Machine learning using neural network algorithms proved to be an effective and quick way of counting birds – 100 birds in 7 seconds. However, the preparation of images and machine learning time is time-consuming, so this method is recommended only for large data sets and large bird assemblages.</p> <p>5. The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behaviour of the target animals.</p>
Data from: Population-scale treatment informs solutions for control of environmentally transmitted wildlife disease
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.