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319 results for “Population estimation”
Estimating the abundance of the critically endangered Baltic Proper harbour porpoise (Phocoena phocoena) population using passive acoustic monitoring
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An individual-based model trained on multiple data sources estimates population connectivity and facilitates aggregation of harvest management units
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Data from: An open spatial capture–recapture model for estimating density, movement, and population dynamics from line-transect surveys
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A comparison of density estimation methods for monitoring marked and unmarked animal populations
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Data from: Estimating fish population abundance by integrating quantitative data on environmental DNA and hydrodynamic modeling
<p>Molecular analysis of DNA left in the environment, known as environmental DNA (eDNA), has proven to be a powerful and cost-effective approach to infer occurrence of species. Nonetheless, relating measurements of eDNA concentration to population abundance remains difficult because detailed knowledge on the processes that govern spatial and temporal distribution of eDNA should be integrated to reconstruct the underlying distribution and abundance of a target species. In this study, we propose a general framework of abundance estimation for aquatic systems on the basis of spatially replicated measurements of eDNA. The proposed method explicitly accounts for production, transport, and degradation of eDNA by utilizing numerical hydrodynamic models that can simulate the distribution of eDNA concentrations within an aquatic area. It turns out that, under certain assumptions, population abundance can be estimated via a Bayesian inference of a generalized linear model. Application to a Japanese jack mackerel (<em>Trachurus japonicus</em>) population in Maizuru Bay revealed that the proposed method gives an estimate of population abundance comparable to that of a quantitative echo sounder method. Furthermore, the method successfully identified a source of exogenous input of eDNA (a fish market), which may render a quantitative application of eDNA difficult to interpret unless its effect is taken into account. These findings indicate the ability of eDNA to reliably reflect population abundance of aquatic macroorganisms; when the "ecology of eDNA" is adequately accounted for, population abundance can be quantified on the basis of measurements of eDNA concentration.</p>
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
<p>Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.</p>
Influence of Quaternary environmental changes on mole populations inferred from mitochondrial sequences and evolutionary rate estimation
<p><span><span><span><span><span><span><span><span><span><span><span>Quaternary environmental changes fundamentally influenced genetic diversity of the temperate-zone terrestrial animals, including those on the Japanese Archipelago. The genetic diversity of present-day populations are taxon and region specific, but its determinants are poorly understood. Here, we analyzed cytochrome <i>b</i> gene (<i>Cytb</i>) sequences (1,140 bp) of mitochondrial DNA (mtDNA) to elucidate factors determining the genetic variation in three species of large moles: <i>Mogera imaizumii</i> and <i>Mogera wogura</i> occur in Northern and Southern mainland Japan (Honshu, Shikoku, and Kyushu), and <i>Mogera robusta </i>occurs on the nearby Asian continent<i>.</i> Network construction with the <i>Cytb</i> sequences revealed 10 star-shaped clusters with apparent geographic affinity. Mismatch distribution analysis showed that modes of pairwise nucleotide differences (t values) were grouped into five classes in terms of the level, implying the occurrence of five stages for the rapid expansion. It is conceivable that a severe cold periods and a subsequent warm periods during the late Quaternary are responsible for the population expansion events. The first and third oldest events include island-derived haplotypes, indicative of involvement of land bridge formation between remote islands, hence suggesting association of the ends of the penultimate (PGM, ca. 130,000 years ago) and last (LGM, ca. 15,000 years ago) glacial maxima, respectively. Since the third one is followed by the fourth one, it is plausible that the termination of Younger Dryas and subsequent abrupt warming at ca. 11,500 years ago facilitated the fourth expansion event. The second is most likely corresponding to the early marine isotope stage (MIS) 3 (ca. 53,000 years ago) when the glaciation and subsequent warming period are predicted to have influenced biodiversity. Utilization of the critical times of 130,000, 53,000, 15,000, and 11,500, years ago as calibration points yielded evolutionary rates of 0.03, 0.045, 0.10 and 0.10 substitutions/site/million years, respectively, showing the time-dependent manner whose pattern is similar to that seen in small rodents reported in our previous studies. The age of the fifth expansion event was calculated to be 5,800 years ago with the rate of 0.10 substitutions/site/million years ago, during the mid-Holocene, suggestive of influence of humans or other unspecified reason, such as the Jomon marine transgression. </span></span></span></span></span></span></span></span></span></span></span></p>
Estimating the inbreeding level and genetic relatedness in an isolated population of critically endangered Sichuan taimen (Hucho bleekeri) using genome wide SNP markers
<p>Sichuan taimen (Hucho bleekeri) is critically endangered fish listed in The Red List of Threatened Species compiled by the International Union for Conservation of Nature (IUCN). Specific locus amplified fragment sequencing (SLAF-seq)-based genotyping was performed for Sichuan taimen with 43 yearling individuals from 3 locations in Taibai River (a tributary of Yangtze River) that has been sequestered from its access to the ocean for more than 30 years since late 1980s. Applying the inbreeding level and genetic relatedness estimation using 15,396 genome wide SNP markers, we found that the inbreeding level of this whole isolated population was at a low level (average F=2.6×10-3±0.079), and the means of coancestry coefficients within and between the three sampling locations were all very low (close to 0), too. Genomic differentiation was negatively correlated with the geographical distances between the sampling locations (p < 0.001) and the 43 individuals could be considered as genetically independent two groups. The low levels of genomic inbreeding and relatedness indicated a relatively large number of sexually mature individuals were involved in reproduction in Taibai River. This study suggested a genomic-relatedness-guided breeding and conservation strategy for wild fish species without pedigree information records.</p>
Data from: Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil
Many studies propose that Quaternary climatic cycles contracted and /or expanded the ranges of species and biomes. Strong expansion-contraction dynamics of biomes presume concerted demographic changes of associated fauna. The analysis of temporal concordance of demographic changes can be used to test the influence of Quaternary climate on diversification processes. Hierarchical approximate Bayesian computation (hABC) is a powerful and flexible approach that models genetic data from multiple species, and can be used to estimate the temporal concordance of demographic processes. Using available single-locus data we can now perform large-scale analyses, both in terms of number of species and geographic scope. Here we first compared the power of four alternative hABC models for a collection of single-locus data. We found that the model incorporating an a priori hypothesis about the timing of simultaneous demographic change had the best performance. Secondly, we applied the hABC models to a dataset of 7 squamate and 4 amphibian species occurring in the Seasonally Dry Tropical Forests (Caatinga) in Northeastern Brazil, which, according to paleoclimatic evidence, experienced an increase in aridity during the Pleistocene. If this increase was important for the diversification of associated xeric-adapted species, simultaneous population expansions should be evident at the community level. We found a strong signal of synchronous population expansion in the Late Pleistocene, supporting the expansion of the Caatinga during this time. This expansion likely enhanced the formation of communities adapted to high aridity and seasonality and caused regional extirpation of taxa adapted to wet forest.
Data from: Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements
Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space, and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi-state mark recapture methods using a hierarchical N-mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state-space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N-mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.
Population structure of five native sheep breeds of Sweden estimated with high density SNP genotypes
Background <p>Native Swedish sheep breeds are part of the North European short-tailed sheep group; characterized in part by their genetic uniqueness. Our objective was to study the population structure of native Swedish sheep. Five breeds were genotyped using the 600 K SNP array. Dalapäls and Klövsjö sheep are from the middle of Sweden; Gotland and Gute sheep from Gotland, an island in the Baltic Sea; and Fjällnäs sheep from northern Sweden. We studied population structure by: principal component analysis (PCA), cluster-based analysis of admixture, and an estimated population tree.</p> Results <p>The analyses of the five Swedish breeds revealed that these breeds are five distinct breeds, while Gute and Gotland are more closely related to each other as seen in all analyses. All breeds had long branch lengths in the population tree indicating they've been subjected to drift. We repeated our analyses using 39 K SNP and including 50 K SNP genotypes from other European and southwestern Asian breeds from the Sheep HapMap project and 600 K SNP genotypes from a dataset of French sheep. Results arranged breeds into five groups: south-west Asia, south-west Europe, central Europe, north Europe and north European short-tailed sheep. Within this last group, Norwegian and Icelandic breeds, Finn and Romanov sheep, Scottish breeds, and Gute and Gotland sheep were more closely related while the remaining Swedish breeds and Ouessant sheep were distinct from all breeds and had longer branches in the population tree.</p> Conclusions <p>We showed population structure of five Swedish breeds and their structure within European and southwestern Asian breeds. Swedish breeds are unique, distinct breeds that have been subjected to drift but group with other north European short-tailed sheep.</p>
Intersession reliability of population receptive field estimates
<p>Proccessed pRF data comparing parameter estimates in visual regions across two days. Requires Matlab and SamSrf toolbox (https://figshare.com/articles/SamSrf_toolbox_for_pRF_mapping/1344765).</p>
Code and data for: Shining a light on elusive lynx: density estimation of three Eurasian lynx populations in Ukraine and Belarus
<p class="MsoNormal"><span>The Eurasian lynx is a large carnivore widely distributed across Eurasia. However, our understanding of population status is heterogeneous across their range, with some populations isolated that are at risk of reduced genetic variation and a complete lack of information about others. In many European countries, Eurasian lynx are monitored through demographic studies crucial for their conservation and management. Even so, there are only rough and fragmented population assessments from Ukraine and Belarus, despite strict protection in both countries and their importance for lynx connectivity across Europe. We monitored lynx from October 2020 to March 2021 and used camera-trapping in combination with spatial capture-recapture (SCR) methods in a Bayesian Framework to provide the first SCR density estimation of three lynx populations across Ukraine and Belarus, including the Ukrainian Chornobyl Exclusion Zone, Southern Belarus, and the Ukrainian Carpathians. Our density estimates varied within our study areas ranging from 0.45 to 1.54 individuals/100 km<sup>2</sup>. This work</span><span> <span>provides a substantial scientific component to the overall understanding of lynx conservation for a region where only broad information is available </span></span><span>and opens the doors for further large-scale monitoring and trend assessments. </span><span>The crucial information we provide can greatly enhance the range-wide assessments of the status of this protected species. We also discuss the implications for Eurasian lynx conservation, despite the geopolitical realities impacting species monitoring in the region. Our work serves as a baseline, not only for future conservation interventions but also to evaluate the effects of disturbance and threats to these protected populations.</span></p>
Data from: using camera traps and N-mixture models to estimate population abundance: model selection really matters
<p>Estimating the abundance or density of wildlife populations is a critical part of species conservation and management, but estimates can vary greatly in precision and accuracy according to the data collection and statistical methods, sampling and ecological variation, and sample size. N-mixture models are a common method which has been applied to a wide range of taxa for estimating population abundance from non-invasive data representing the distribution of the species. We used population estimates from an aerial survey of moose and videos from camera traps to assess the sensitivity of N-mixture models to ecological conditions, the spatial scale at which they were measured, the criteria used to define independent detections, and model choice based on the common statistical criterion of parsimony. The most parsimonious N-mixture models were considerably biased, producing implausibly large and considerably imprecise estimates of the abundance of moose. Most of the other models produced estimates of abundance that were ecologically realistic and relatively accurate. The accuracy of population estimates produced by N-mixture models were not overly sensitive to the formulation of models, the scale at which ecological conditions were measured, or the criteria used to define independent detection and by extension sample size. Our results suggest that parsimony was a poor measure of the predictive accuracy of the population estimates produced with the N-mixture model. Collecting and processing data from the aerial survey was less expensive and took less time, but data from camera traps can provide valuable information on behavior of the target species as well as insights into multiple species in the community.</p>
Fecal standing crop with real time correction using scat detection dogs to estimate population density
<p>Population density is fundamental information for assessing the conservation status of species and support management and conservation actions for in situ populations, but is unknown for many forest species due to their difficulty in detection. The Fecal Standing Crop (FSC) method using detection dogs is an alternative for cryptic or elusive species. An intrinsic difficulty of FSC is the ability to find fecal samples in the field and to estimate the probability of which feces detection is influenced by degradation due to climatic conditions. Our goal was to propose a concurrent FSC parameter estimation using a scat detection dog under different climatic conditions and apply those parameters in a wild deer population. Ten fecal samples of gray brocket deer (Subulo gouazoubira) were placed weekly in a transect (24 x 1200 m) in both dry and wet seasons (12 weeks each). A scat detection dog was then employed to find experimental fecal samples to determine the FSC parameters that were subsequently used with naturally occurring fecal samples (also dog-detected) to estimate population density. The oldest dog found samples were 21 (Dry) and seven (Wet) days after placement, resulting in dog efficiency of 23% (Dry) and 30% (Wet). Adjusting the model to account for efficiency and scat durability, we estimated similar, seasonal, densities of 4.54 individuals km-2 (SD = 2.21, Dry) and 5.52 indiv. km-2 (SD = 3.71, Wet).</p> <p><em>Synthesis and applications:</em> Our results demonstrate that our concurrent methodology corrected the effects of weather and habitat on FSC parameters thereby allowing for accurate population density estimation. Additionally, this method can provide reasonably precise density estimates with a logistically feasible sample size, as demonstrated by simulation. Following our recommendations, this method allows a reliable estimate of population density because it incorporates any influence of study area, dog ability, and climate in fecal sample detection, providing fundamental information for the conservation of many cryptic and elusive species.</p>
Input data and code supporting the cod_v2 population estimates
<p>The <strong><em>model.zip</em></strong> file contains input data and code supporting the cod_v2 population estimates. The file<strong> <em>modelData.RData</em></strong> provides the input data to the JAGS model and the file<em> <strong>modelCode.R</strong></em> contains the source code for the model in the JAGS language. The files can be used to run the model for further assessments and as a starting point for further model development.</p> <p>The data and the model were developed using the statistical software <strong>R version 4.0.2</strong> (https://cran.r-project.org/bin/windows/base/old/4.0.2) and <strong>JAGS 4.3.0</strong> (https://mcmc-jags.sourceforge.io), a program for analysis of Bayesian graphical models using Gibbs sampling, through the R package <strong>runjags 2.2.0</strong> (https://cran.r-project.org/web/packages/runjags).</p>
Recent estimate of Asian elephants in Borneo reveals a smaller population
<p>Asian elephants occurring in northern Borneo form a geographically isolated and genetically distinct population. Of this, the subpopulation of Central Sabah holds the greatest opportunity for long-term survival, due to a relatively large population size and occurrence over a vast, contiguous, and protected habitat. We surveyed this subpopulation in 2015 using advanced methods to obtain a population size estimate. We used the distance-sampling framework and laid out transects following a stratified random design for counting elephant dung piles; measured dung decay following the 'retrospective' method; and used Bayesian analysis to estimate dung decay rate and dung pile density. Thus, we estimated a posterior mean dung decay rate of 212 days (95% BCI: 133–319), an overall elephant density of 0.07 per km<sup>2</sup> (95% BCI: 0.03–0.11), and a population size of 387 elephants (95% BCI: 169–621). These estimates were far lower than the population size of 1132 individuals and density of 1.18 per km<sup>2 </sup>estimated in 2008. It is unlikely that there has been a steep population decline, as there were no drastic land-use changes between 2008 and 2015, nor were there other identifiable causes for a population decline. Therefore, it appears that the methodological and analytical flaws in the previous estimate are the most plausible reason for this observed difference. Given that the new estimate suggests a much smaller population, it is prudent and precautionary to use the new estimate as the basis for all policy decisions and conservation actions for elephants in Sabah.</p>
Divergence time estimation using ddRAD data and an isolation-with-migration model applied to water vole populations of Arvicola
<p>Molecular dating methods of population splits are crucial in evolutionary biology, but they present important difficulties due to the complexity of the genealogical relationships of genes and past migrations between populations. Using the double digest restriction-site associated DNA (ddRAD) technique and an isolation-with-migration (IM) model, we studied the evolutionary history of water vole populations of the genus <em>Arvicola</em>, a group of complex evolution with fossorial and semi-aquatic ecotypes. To do this, we first estimated mutation rates of ddRAD loci using a phylogenetic approach. An IM model was then used to estimate split times and other relevant demographic parameters. A set of 300 ddRAD loci that included 85 calibrated loci resulted in good mixing and model convergence. The results showed that the two populations of <em>A. scherman</em> present in the Iberian Peninsula split 34 thousand years ago, during the last glaciation. In addition, the much greater divergence from its sister species, <em>A. amphibius</em>, may help to clarify the controversial taxonomy of the genus. We conclude that this approach, based on ddRAD data and an IM model, is highly useful for analyzing the origin of populations and species.</p>
Estimated population exposed to floods with a global flood model (CaMa-Flood v4.00)
<p>This is a repository for data and codes to analyze the population exposed to floods at grid level (0.25deg) and country level. The flood hazard map is modeled from the global hydrodynamic model - Catchment-based Macro-scale Floodplain (CaMa-Flood) model. </p>
Estimating abundance in unmarked populations of Golden Eagle
<p> 1. Estimates of species abundance are of key importance in population and ecosystem level research but can be hard to obtain. Study designs using camera-traps are increasingly being used for large-scale monitoring of species that are elusive and/or occur naturally at low densities.</p> <p>2. Golden eagle (Aquila chrysaetos) is one such species, and we investigate whether existing large-scale monitoring programs using baited camera-traps can be used to estimate the abundance of golden eagles, as an alternative to traditional labour-intensive searches for active territories and nest sites during the breeding period.</p> <p>3. The camera-trap data allowed two measures of abundance to be estimated within each of four main study areas in mid and northern Norway; occupancy was measured as the probability of camera site use, and population size was measured as the number of eagle individuals using the camera sites within a study area. Spatial and temporal patterns in occupancy and population size were explored and evaluated against independent estimates of the breeding pair density in the study areas.</p> <p>4. Annual estimates of golden eagle occupancy showed low precision, while estimates of population size were more precise in relation to both estimated and anticipated abundance fluctuations. Estimates of population size may therefore be suitable for monitoring within study area temporal abundance trends, while estimates of occupancy seem unsuitable for such in golden eagles. Across study areas, patterns in both average occupancy and average population density estimated from population size, were consistent with the spatial pattern in average breeding pair densities (r = 0.99, and r = 0.89 respectively). This suggests that camera-trap based estimates of occupancy and population density reflect territory density at large spatial scales. In conclusion, our results suggest that baited camera-traps can be a cost-effective strategy for monitoring the abundance of golden eagles.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.