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242 results for “occupancy data”
Data from: Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets
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Data from: Odonate species occupancy frequency distribution and abundance – occupancy relationship patterns in temporal and permanent water bodies in a subtropical area
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Data and code from: Addressing widespread detection heterogeneity in avian occupancy modeling using passive acoustic surveys
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Processed data for the analysis of human mobility changes from COVID-19 lockdown on bird occupancy in North Carolina, USA
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Data from: Using camera traps to estimate habitat preferences and occupancy patterns of vertebrates in boreal wetlands
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Data from: Northern pikas experience reduced occupancy due to surrounding human land use despite the occurrence of suitable microclimates
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Data from: Bat winter foraging habitat use in working forests: A multispecies spatial occupancy approach
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Data from: Anthropogenic and environmental factors determine occupancy and rarity of large carnivores in the Omo valley, Southwest Ethiopia
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Data from: Sequential use of niche and occupancy models identifies conservation and research priority areas for two data-poor endemic birds from the Colombian Andes
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Data from: Disentangling elevational richness: a multi-scale hierarchical Bayesian occupancy model of Colorado ant communities
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Data for: The indoor mycobiomes of daycare centers are affected by occupancy and climate
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Data from: Integrating multiple sign types to improve occupancy estimation for inconspicuous species
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Data from: Habitat-dependent occupancy and movement in a migrant songbird highlights the importance of mangroves and forested lagoons in Panama and Colombia
Climate change is predicted to impact tropical mangrove forests due to decreased rainfall, sea-level rise, and increased seasonality of flooding. Such changes are likely to influence habitat quality for migratory songbirds occupying mangrove wetlands during the tropical dry season. Overwintering habitat quality is known to be associated with fitness in migratory songbirds, yet studies have focused primarily on territorial species. Little is known about the ecology of non-territorial species that may display more complex movement patterns within and among habitats of differing quality. In this study, we assess within season survival and movement at two spatio-temporal scales of a non-territorial overwintering bird, the prothonotary warbler (Protonotaria citrea), that depends on mangroves and tropical lowland forests. Specifically, we (1) estimated within-patch survival and persistence over a six-week period using radio-tagged birds in central Panama and (2) modelled abundance and occupancy dynamics at survey points throughout eastern Panama and northern Colombia as the dry season progressed. We found that site persistence was highest in mangroves; however, the probability of survival did not differ among habitats. The probability of warbler occupancy increased with canopy cover, and wet habitats were least likely to experience local extinction as the dry season progressed. We also found that warbler abundance is highest in forests with the tallest canopies. This study is one of the first to demonstrate habitat-dependent occupancy and movement in a non-territorial overwintering migrant songbird, and our findings highlight the need to conserve intact, mature mangrove and lowland forests.
Data: Using environmental DNA and occupancy modeling to estimate rangewide metapopulation dynamics
<p>We demonstrate the power of combining two emergent tools for resolving rangewide metapopulation dynamics. First, we employed environmental DNA (eDNA) surveys to efficiently generate multi-season rangewide site occupancy histories. Second, we developed a novel<i> </i>dynamic, spatial multiscale occupancy model to estimate metapopulation dynamics. The model incorporates spatial relationships, explicitly accounts for non-detection bias and allows direct evaluation of the drivers of extinction and colonization. We applied these tools to examine metapopulation dynamics of endangered tidewater goby, a species endemic to California estuarine habitats. We analyzed rangewide eDNA data from 190 geographically isolated sites (813 total water samples) surveyed from two years (2016 and 2017). Rangewide estimates of the proportion of sites that were occupied varied little between 2016 (0.52) and 2017 (0.51). However, there was evidence of extinction and colonization dynamics. The probability of extinction of an occupied site (0.106) and probability of colonization of an unoccupied site (0.085) were nearly equal. Stability in site occupancy proportions combined with nearly equal rates of extinction and colonization suggests a dynamic equilibrium between the two years surveyed. Assessment of covariate effects revealed that colonization probability increased as the number of occupied neighboring sites increased and as distance between occupied sites decreased. We show that eDNA surveys can rapidly provide a snapshot of a species distribution over a broad geographic range, and when these surveys are paired with occupancy modeling, can uncover metapopulation dynamics and their drivers.</p>
Data from: Occupancy models for data with false positive and false negative errors and heterogeneity across sites and surveys
False positive detections, such as species misidentifications, occur in ecological data, although many models do not account for them. Consequently, these models are expected to generate biased inference. The main challenge in an analysis of data with false positives is to distinguish false positive and false negative processes while modeling realistic levels of heterogeneity in occupancy and detection probabilities without restrictive assumptions about parameter spaces. Building on previous attempts to account for false positive and false negative detections in occupancy models, we present hierarchical Bayesian models that utilize a subset of data with either confirmed detections of a species' presence (CP model) or both confirmed presences and confirmed absences (CACP model). We demonstrate that our models overcome the challenges associated with false positive data by evaluating model performance in Monte Carlo simulations of a variety of scenarios. Our models also have the ability to improve inference by incorporating previous knowledge through informative priors. We describe an example application of the CP model to quantify the relationship between songbird occupancy and residential development, plus we provide instructions for ecologists to use the CACP and CP models in their own research. Monte Carlo simulation results indicated that, when data contained false positive detections, the CACP and CP models generated more accurate and precise posterior probability distributions than a model that assumed data did not have false positive errors. For the scenarios we expect to be most generally applicable, those with heterogeneity in occupancy and detection, the CACP and CP models generated essentially unbiased posterior occupancy probabilities. The CACP model with vague priors generated unbiased posterior distributions for covariate coefficients. The CP model generated unbiased posterior distributions for covariate coefficients with vague or informative priors, depending on the function relating covariates to occupancy probabilities. We conclude that the CACP and CP models generate accurate inference in situations with false positive data for which previous models were not suitable.
Data from: Camera-based occupancy monitoring at large scales: power to detect trends in grizzly bears across the Canadian Rockies
Monitoring carnivores is critical for conservation, yet challenging because they are rare and elusive. Few methods exist for monitoring wide-ranging species over large spatial and sufficiently long temporal scales to detect trends. Remote cameras are an emerging technology for monitoring large carnivores around the world because of their low cost, non-invasive methodology, and their ability to capture pictures of species of concern that are difficult to monitor. For species without uniquely identifiable spots, stripes, or other markings, cameras collect detection/non-detection data that are well suited for monitoring trends in occupancy as its own independent useful metric of species distribution, as well as an index for abundance. As with any new monitoring method, prospective power analysis is essential to ensure meaningful trends can be detected. Here we test camera-based occupancy models as a method to monitor changes in occupancy of a threatened species, grizzly bears (Ursus arctos), at large landscape scales, across 5 Canadian national parks (~21,000 km2). With n = 183 cameras, the top occupancy model estimated regional occupancy to be 0.79 across all 5 parks. We evaluate the statistical power to detect simulated 5–40% declines in occupancy between two sampling years and test applied questions of how power is affected by the spatial scale of interest (park level vs. regional level), the number of cameras deployed, and duration of camera deployment. We also explore several ecological mechanisms (i.e., spatial patterns) of decline in occupancy, and examine how power changes when focusing only on grizzly bears family groups. As hypothesized, statistical power increased with the number of cameras and with the number of days deployed. Power was unaffected, however, by the ecological mechanisms of decline, indicating that our systematic sampling design can detect a decline regardless of whether occupancy declined due to range edge attrition, ecological trap or other mechanisms. Despite their lower occupancy, power was similarly high for grizzly bear family groups compared to grizzly bears in general. We highlight which study design attributes contributed to high power and we provide advice for establishing cost-effective camera-based programs for monitoring large carnivore occupancy at large spatial scales.
Data from: Stream community richness predicts apex predator occupancy dynamics in riparian systems
Streams and adjacent riparian habitats represent linked terrestrial and aquatic ecosystems that exchange materials and energy. Recognized relationships among apex predators and ecosystem biodiversity led us to hypothesize that these predators in riparian-stream systems were more likely to be found in sites with high stream quality, defined as increased ecosystem function and integrity. In our freshwater study system, river otter (Lontra canadensis) and mink (Neovison vison) play critical roles as apex predators. We used multi-season occupancy modelling across 3 sampling years (2012-2014) to compare aspects of the stream communities that explain occupancy dynamics of river otter and mink, including their interactions with other semi-aquatic mammals. We surveyed for semi-aquatic mammals at 77 sites in 12 major watersheds in southern Illinois, USA (44,526 km<sup>2</sup>). Naïve occupancy differed among years but generally increased for river otter, and remained high (≥93.5%) for mink. Increasing substrate availability increased detectability of river otter, whereas mink detection varied by survey period. Occupancy of river otter during the initial survey period was higher in sites closer to reintroduction points. Probability of colonization of river otter was positively associated with macroinvertebrate index of biotic integrity, fish species richness, and beaver presence. Sites with high species richness of fish families preferred by river otter also had increased river otter persistence. Mink occupied sites with increased fish richness, muskrat presence, and mussel community index. Taken together, our results show occupancy of both mink and river otter were predicted by aspects of prey diversity and presence, indicating the importance of community composition in occupancy dynamics of riparian predators. Ultimately, these relationships suggest that habitat heterogeneity and system stability are important to apex predator site use. However, the relative role of bottom-up and top-down forcing in stream systems remains to be resolved.
Data from: Restricted morphospace occupancy of early Cambrian reef-building archaeocyaths
The evolution of novel morphologies can signify expansion of a clade into new niches. This can be studied in the fossil record by investigating the morphospace occupancy of organisms, with small morphospaces signifying low morphological disparity and more diffuse morphospaces suggesting a broader range of morphologies adapted to different environments. Morphological disparity of many taxa (arthropods, crinoids, etc.) from the Cambrian to modern intervals have been studied in this manner. However, no study has investigated this in archaeocyaths, which, as reef builders, can have a disproportionate effect on early Cambrian biodiversity relative to their frequency. Here, we collect morphological data on archaeocyathan sponges, mostly from Laurentia. Over 600 museum specimens and 400 field samples were measured for traditional morphometric characters as well as discrete gross morphological characteristics. We find that archaeocyaths have an average cup/individual (body) diameter of 10.6 mm. This is significantly smaller than a selected group of modern demosponges and lithistid sponges which measure 94.1 mm and 66.8 mm in diameter respectively and each has a larger size variance. Archaeocyath gross morphologies are also highly constrained to a few simple morphologies (3-6 categories) while modern demosponges and lithistids are more diverse (9 categories each). These data indicate that Laurentian archaeocyaths were restricted in their morphological disparity, potentially due to limitations imposed by having a robust calcareous skeleton while still maintaining a large intervallum cavity space to facilitate passive entrainment. The fact that these Cambrian reef builders were restricted in their morphological complexity may have had a strong influence on the biodiversity of early Phanerozoic ecosystems. Furthermore, a clade limited to only a few specific morphologies is at an increased risk of extinction.
Data from: Does the niche-breadth or trade-off hypothesis explain the abundance-occupancy relationship in avian haemosporidia?
Two hypotheses have been proposed to explain the abundance-occupancy relationship (AOR) in parasites. The niche-breadth hypothesis suggests that host generalists are more abundant and efficient at colonizing different host communities than specialists. The trade-off hypothesis argues that host specialists achieve high density across their hosts' ranges, whereas generalists incur the high cost of adaptation to diverse immuno-defense systems. We tested these hypotheses using 386 haemosporidian cytochrome-b lineages (1894 sequences) recovered from 2318 birds of 103 species sampled in NW Africa, NW Iberia, W Greater Caucasus, and Transcaucasia. The number of regions occupied by lineages was associated with their frequency suggesting the presence of AOR in avian Haemosporidia. However, neither hypothesis provided a better explanation for the AOR. Although, the host-generalist Plasmodium SGS1 was over 3 times more abundant than other widespread lineages, both host specialists and generalists were successful in colonizing all study regions and achieved overall high prevalence.
Data from: Examining the occupancy-density relationship for a low-density carnivore
1. The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools. 2. For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive lab processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions. 3. Here, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70 096 km2 region of western New York, USA. We fit occupancy and Royle-Nichols models to species detection–non-detection data collected by cameras, and spatial capture-recapture models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km2 grid cells was modeled as a function of landscape attributes known to influence fisher distribution. 4. We found a close relationship between grid-cell estimates of fisher state variables from the models using detection–non-detection data and those from the spatial capture-recapture model, likely due to informative spatial covariates across a large landscape extent and a grid-cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially-explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data. 5. Synthesis and applications. Our work provides empirical evidence that models using detection-non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.