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43 results for “population statistics”
Quantifying changes in fish population stability using statistical early warnings of regime shifts
This data package describes long-term trends in metrics describing population stability and used as statistical early warnings of regime shifts in 29 fish species that inhabit the San Francisco Bay-Delta in central California, USA. Metrics used in this study include spatial synchrony, temporal coefficient of variation (CV), and lag-1 temporal autocorrelation. Trends were measured using ordinary least squares linear regression. These derived data were developed from abundance (as CPUE) time series based on three long-term fish monitoring studies included in https://doi.org/10.6073/pasta/a29a6e674b0f8797e13fbc4b08b92e5b; the Fall Midwater Trawl Survey, Delta Juvenile Monitoring Program, and Bay Study. Selected data were from fall months (September to December) in 1980-2023, from midwater trawl and beach seine surveys for which sampling effort (e.g., tow volume) was recorded. Data on fish exceeding maximum length thresholds for age-0 fish were discarded, except for white sturgeon, where the maximum length threshold corresponded to approximately 10 years of age, the onset of reproductive maturity. Observations from different sampling stations were aggregated into 10 sub-regions (South San Francisco Bay, Central San Francisco Bay, San Pablo Bay, Napa River, Suisun Bay, Delta Confluence, South Delta, North Delta, San Joaquin River, Sacramento River, and midwater trawl samples and beach seine samples were considered separately because the methods sample distinct habitat types. Combinations of sub-region and sampling method were considered distinct spatial units. EWI metrics were measured in 5-year rolling windows to permit assessment of changes over time. The temporal CV and lag-1 autocorrelation were measured on individual spatial unit time series, ignoring windows with >1 year of missing data. The coefficient of variation divides the standard deviation by the mean. Lag-1 autocorrelation was measured as Pearson correlation. Spatial synchrony was measured across spatial un
Population Statistics on NCT02332590
<p>Data presented as mean or median (change), in parts with quantiles (Q1, Q3) published by</p> <table> <tbody> <tr> <td> <p>C. Gaby, G. Burmester, V. Strand, J. Msihid, M. Zilberstein, T. Kimura, B. van Hoogstraten, S. H. Boklage, J. Sadeh, M. H. G. Neil and A. Boyapati, "Sarilumab and adalimumab differential effects on bone remodelling and cardiovascular risk biomarkers, and predictions of treatment outcomes," <em>Arthritis Research & Therapy, </em>vol. 22, no. 1, p. 70, 2020.</p> </td> </tr> </tbody> </table>
Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population - Supporting Material
<p>Supporting material for the study:</p> <p><strong>"Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population."</strong></p> <p><strong>Authors:</strong></p> <p>Cathleen Petit-Cailleux1, Hendrik Davi1, François Lefèvre1, Joseph Garrigue<strong>2</strong>, Jean-André Magdalou<strong>2</strong>, Christophe Hurson<strong>2,3</strong><strong>, </strong>Elodie Magnanou<strong>2,4</strong>, and Sylvie Oddou-Muratorio1.</p> <p> </p> <p>Adresses</p> <p>1INRA, UR 629 Ecologie des Forêts Méditerranéennes, URFM, Avignon, France</p> <p><strong>2</strong>Réserve Naturelle Nationale de la Forêt de la Massane, France</p> <p><strong>3</strong>Fédération des Réserves Naturelles Catalanes, Prades, France</p> <p><strong>4</strong>Sorbonne Université, CNRS, Biologie Intégrative des Organismes Marins, BIOM, F-66650 Banyuls-sur-Mer, France</p> <p><strong>ORCID:</strong></p> <p>Cathleen Petit-Cailleux: <a href="https://orcid.org/0000-0001-7714-6583">https://orcid.org/0000-0001-7714-6583</a></p> <p>François Lefèvre : <a href="https://orcid.org/0000-0003-2242-7251">https://orcid.org/0000-0003-2242-7251</a></p> <p>Sylvie Oddou-Muratorio <a href="https://orcid.org/0000-0003-2374-8313">https://orcid.org/0000-0003-2374-8313</a></p> <p> </p> <p>-------------</p> <p>Raw data of the Table_Massane_moratlity_trees.csv and climate can be obtained from Joseph Garrigue, Jean-André Magdalou and Christophe Hurson.</p> <p>The inventories files and daily climate are the input dataset to run CASTANEA models.</p> <p>All details are provided in the article.</p>
Statistical Data of Vienna's population
<p>Statistical analysis of the population of Vienna by districts from 2001 to 2015.</p> <p>Input Data is taken from https://www.data.gv.at/katalog/dataset/stadt-wien_viebevlkerungseit1869wien/resource/f55512e6-81ef-4fa9-a01f-19f9c5f838c2.</p> <p>The source code for experiment which produces the data provided here can be found on https://bitbucket.org/BerwanY/dp3</p> <p>The csv-files of the districts population are containing the years as labels and the population for every year in the first row. The overview of vienna's population csv-file contains as first label 'YEAR', where the other label are the districts. So every row contains the population data of every district for one year.</p> <p>The csv-files are named as follows:</p> <ul> <li>For districts: 'district_<em>DISTRICTNUMBER</em>.csv'</li> <li>Overview: 'district_all.csv'</li> </ul> <p>, where DISTRICTNUMBER is replaced with the corresponding code of the district.</p>
Data associated with the manuscript "Simple statistical models can be sufficient for testing hypotheses with population time series data"
<p>This is a revised version of the archive of R code and data used in the manuscript, <em>Simple statistical models can be sufficient for testing hypotheses with population time series data. </em>The data are in three files. <em>etodata1.csv</em> and <em>etodata2.csv</em> contain two versions of the same data for shoal-dwelling fishes in the Etowah River and associated environmental covariates. <em>knz_dat</em> contains data for small mammals collected in the Konza Prairie Biological Station and associated environmental covariates. The R code consists of four primary files that call nine auxiliary files. CaseStudy1-main_code and CaseStudy2-main_code are the primary files for running the two case studies. Simulations1 and Simulations2 are the files for running the two batteries of simulations. We thank the Konza Prairie Biological Station and Konza Prairie Long-Term Ecological Research Program supported by the National Science Foundation (DEB-1440484) for collecting and providing access to mammal community data. More details are in the manuscript and supporting information. </p>
Fig. 1 in Golden jackal (Canis aureus Linnaeus, 1758) and Red fox (Vulpes vulpes Linnaeus, 1758) population dynamics in Sarnena Sredna Gora Mts., Bulgaria based on hunting statistics
Fig. 1. Golden jackal (Canis aureus L.) and Red fox (Vulpes vulpes L.) population dynamics trends in Sarnena Sredna Gora Mts., Bulgaria, for a period of 11 years based on the analysis of the hunting data base (number of shot individuals)
Illustrating potential effects of alternate control populations on real-world evidence-based statistical analyses
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Data from: Intraspecific DNA contamination distorts subtle population structure in a marine fish: decontamination of herring samples before restriction-site associated (RAD) sequencing and its effects on population genetic statistics
Wild specimens are often collected in challenging field conditions, where samples may be contaminated with the DNA of conspecific individuals. This contamination can result in false genotype calls, which are difficult to detect, but may also cause inaccurate estimates of heterozygosity, allele frequencies, and genetic differentiation. Marine broadcast spawners are especially problematic, because population genetic differentiation is low and samples are often collected in bulk and sometimes from active spawning aggregations. Here, we used contaminated and clean Pacific herring (Clupea pallasi) samples to test (i) the efficacy of bleach decontamination, (ii) the effect of decontamination on RAD genotypes, and (iii) the consequences of contaminated samples on population genetic analyses. We collected fin tissue samples from actively spawning (and thus contaminated) wild herring and non-spawning (uncontaminated) herring. Samples were soaked for 10 minutes in bleach or left untreated, and extracted DNA was used to prepare DNA libraries using a restriction-site associated DNA (RAD) approach. Our results demonstrate that intraspecific DNA contamination affects patterns of individual and population variability, causes an excess of heterozygotes, and biases estimates of population structure. Bleach decontamination was effective at removing intraspecific DNA contamination and compatible with RAD sequencing, producing high-quality sequences, reproducible genotypes, and low levels of missing data. Although sperm contamination may be specific to broadcast spawners, intraspecific contamination of samples may be common and difficult to detect from high-throughput sequencing data, and can impact downstream analyses.
Summary statistics of North American plant populations
<p>Summary statistics of North American plant populations calculated by using the microsatellites of invasive and native species from multiple studies. The packages “hierfstat” (Goudet and Jombart, 2015), “vegan” (Oksanen <em>et al.</em>, 2017) and “sp” (Pebesma and Bivand, 2005; Bivand <em>et al.</em>, 2013) were used in RStudio to calculate the averaged heterozygosity over all subpopulations (<em>H</em><sub>S</sub>), the proportion of genetic variation due to differences among populations (<em>F</em><sub>ST</sub>p), the degree of non-random mating within subpopulations (<em>F</em><sub>IS</sub>) and the correlation between geographic and genetic distance (<em>r)</em>. STRUCTURE (Pritchard <em>et al.</em>, 2000) was used to calculate the number of genetic clusters (<em>K)</em> (5 iterations, burnin length 1000, 10000 MCMC reps after burnin). STRUCTURE HARVESTER (Earl & vonHoldt, 2012) was consulted to determine Evanno’s ΔK (Evanno <em>et al.</em>, 2005).</p>
Population in Jakarta 2022 (Source form: Central Bureau of Statistics)
<p>The population pyramid graph above illustrates the population distribution in Jakarta in 2022. The 0-4 age group has a larger population compared to several age groups above it. The 30-34 age group has a slightly larger male population (388,746) than the female population (431,768). For the 65+ age group, the male and female populations are relatively balanced with slightly more females.</p> <p>This population pyramid shows a young population structure, with a wider base in the younger age group (0-19 years) and then starting to narrow in the older age group. This is an indication that Jakarta still has a fairly young population with the potential for a large population in the future.</p>
Dataset for: Estimating pregnancy rate from blubber progesterone levels of a blindly biopsied beluga population poses methodological, analytical and statistical challenges
<p class="MsoBodyText"><span>Beluga (<em>Delphinapterus leucas</em>) from the St. Lawrence Estuary, Canada, have been declining since the early 2000s, suggesting recruitment issues as a result of low fecundity, abnormal abortion rates or poor calf or juvenile survival. Pregnancy is difficult to observe in cetaceans, making the ground-truthing of pregnancy estimates in wild individuals challenging. Blubber progesterone concentrations were contrasted among 62 SLE beluga with a known reproductive state (i.e., pregnant, resting, parturient, and lactating females), that were found dead in 1997–2019. The suitability of a threshold obtained from decaying carcasses to assess reproductive state and pregnancy rate of freshly-dead or free-ranging and blindly-sampled beluga was examined using three statistical approaches and two datasets (135 freshly-harvested carcasses in Nunavik, and 65 biopsy-sampled SLE beluga). Progesterone concentrations in decaying carcasses were considerably higher in known-pregnant (mean </span><span>±</span><span> sd: </span><span>365 </span><span>±</span><span> 244 ng g<sup>-1</sup> of tissue) </span><span>than resting (</span><span>3.1 </span><span>±</span><span> 4.5 ng g<sup>-1</sup> of tissue</span><span>) or lactating (</span><span>38.4 </span><span>±</span><span> 100 ng g<sup>-1</sup> of tissue</span><span>) females. An approach based on statistical mixtures of distributions and a logistic regression was compared to the commonly-used, fixed threshold approach (here, 100 ng g<sup>-1</sup>) for discriminating pregnant from non-pregnant females. The error rate for classifying individuals of known reproductive status was the lowest for the fixed threshold and logistic regression approaches, but the mixture approach required limited <em>a priori</em> knowledge for clustering individuals of unknown pregnancy status. Mismatches in assignations occurred at lipid content <10% of sample weight. Our results emphasize the importance of reporting lipid contents and progesterone concentrations in both units (ng g<sup>-1 </sup>of tissue and ng g<sup>-1</sup> of lipid) when sample mass is low. By highlighting ways to circumvent potential biases in field sampling associated with capturability of different segments of a population, this study also enhances the usefulness of the technique for estimating pregnancy rate of free-ranging population. </span></p>
Dataset for: Estimating pregnancy rate from blubber progesterone levels of a blindly biopsied beluga population poses methodological, analytical and statistical challenges
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Data from: Intraspecific DNA contamination distorts subtle population structure in a marine fish: decontamination of herring samples before restriction-site associated (RAD) sequencing and its effects on population genetic statistics
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Data from: Biological and statistical processes jointly drive population aggregation: using host–parasite interactions to understand Taylor's power law
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Data from: A statistical framework to explore ontogenetic growth variation among individuals and populations: a marine fish example
Growth is a fundamental biological process, driven by a multitude of intrinsic (within-individual) and extrinsic (environmental) factors, that underpins individual fitness and population demographics. Focussing on the comprehensive information stored in aquatic and terrestrial organism hard parts, we develop a series of increasingly complex hierarchical models to explore spatial and temporal sources of growth variation, ranging in resolution from within individuals to across a species. We apply this modelling framework to an extensive data set of otolith increment measurements from tiger flathead (Platycephalus richardsoni), a demersal commercially exploited fish that inhabits the warming waters of south-east Australia. We recreated growth histories (biochronology) up to four decades in length from seven fishing areas spanning this species' range. The dominant pattern in annual growth was an age-dependent, allometric decline that varied amongst individuals, sexes, fishing areas, years and cohorts. We found evidence for among-area differences in growth rate selectivity whereby younger fish at capture were generally faster growers. Temporal growth variation was partitioned into two main sources: extrinsic year-to-year annual fluctuations in environmental conditions and persistent cohort-specific growth differences, reflecting density dependence and/or juvenile experience. Despite low levels of among-individual growth synchrony within areas, we detected a regionally coherent signal of increasing average growth rate through time, a trend related to oceanic warming. At the southerly (poleward) range limit, growth was only weakly related to temperature, but further north in warmer waters this relationship strengthened until at the species' equatorward range limit, growth declined with increasing temperatures. We partitioned these species-wide and area-specific phenotypic responses into within and among-individual components using a reaction norm approach. Individual tiger flathead likely possess sufficient growth plasticity to successfully adapt to warming waters across much of their range, but increased future warming in the north will continue to depress growth, affecting individual fitness and even population persistence. Our modelling framework is directly applicable to other long-term, individual-based, data sets such as those derived from tree rings, corals, and tag-recapture studies, and provides an unprecedented level of resolution into the drivers of growth variation and the ecological and evolutionary implications of environmental and climatic change.
Statistics of population in Upper Austria
<p>The result of the experiment 'Statistics of population in Upper Austria'.</p> <p>Contains a database dump of a Postgres version 9.5.2</p> <p>Metadata can be obtained here: https://www.data.gv.at/katalog/dataset/e108dcc3-1304-4076-8619-f2185c37ef81</p> <p>The population table contains the data from the Link but filtered. Only the following columns are available. The metadata of the columns are the same as in the link above.</p> <ul> <li>lau2_code </li> <li>lau2_name </li> <li>year </li> <li>sex </li> <li>age_total</li> </ul> <p>In the calculation table the result is stored. The following columns exists:</p> <ul> <li>year </li> <li>sex </li> <li>mean</li> </ul> <p>'Year' is the year when the data was observed. </p> <p>'Sex' represents the gender of the population and can have the values 0,1,2 (1 = male, 2 = female, 0 = total)</p> <p>'mean' is the average population per village.</p> <p> </p>
Missing data in sea turtle population monitoring: a Bayesian statistical framework accounting for incomplete sampling
<p>Monitoring how populations respond to sustained conservation measures is essential to detect changes in their population status and determine the effectiveness of any interventions. In the case of sea turtles, their populations are difficult to assess because of their complicated life histories. Ground-derived clutch counts are most often used as an index of population size for sea turtles; however, data are often incomplete with varying sampling intensity within and among sites and seasons. To address these issues, we: (1) develop a Bayesian statistical modelling framework that can be used to account for sampling uncertainties in a robust probabilistic manner within a given site and season; and (2) apply this to a previously unpublished long-term sea turtle dataset (n = 17 years) collated for the Republic of the Congo, which hosts two sympatrically nesting species of sea turtle (leatherback turtle [<em>Dermochelys coriacea</em>] and olive ridley turtle [<em>Lepidochelys olivacea</em>]). The results of this analysis suggest that leatherback turtle nesting levels dropped initially and then settled into quasi-cyclical levels of interannual variability, with an average of 573 (mean, 95% prediction interval: 554–626) clutches laid annually between 2012 and 2017. In contrast, nesting abundance for olive ridley turtles has increased more recently, with an average of 1,087 (mean, 95% prediction interval: 1,057–1,153) clutches laid annually between 2012 and 2017. These findings highlight the regional and global importance of this rookery with the Republic of the Congo, hosting the second largest documented populations of olive ridley and the third largest for leatherback turtles in Central Africa; and the fourth largest non-arribada olive ridley rookery globally. Furthermore, whilst the results show that Congo's single marine and coastal national park provides protection for over half of sea turtle clutches laid in the country, there is scope for further protection along the coast. Although large parts of the African coastline remain to be adequately monitored, the modelling approach used here will be invaluable to inform future status assessments for sea turtles given that most datasets are temporally and spatially fragmented. </p>
Dataset for "Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions" in the Annals of Applied Statistics
<p>This is the dataset to be used for the paper in the Annals of Applied Statistics titled:</p> <p><strong>"Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions"</strong></p> <p>Download, unzip and place in the ./<strong>paper-data</strong> directory in the R package repository <a href="https://github.com/sangwon-hyun/flowmix">https://github.com/sangwon-hyun/flowmix</a>. Then, run the code in <strong>./paper-code</strong> to produce the figures and tables.</p>
Simulation and empirical data for "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations"
<p>Simulation data and empirical data used to generate figures from "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations". Can be used with code provided on the associated github to regenerate the figures. </p>
Data from: Genetic sex assignment in wild populations using GBS data: a statistical threshold approach
Establishing the sex of individuals in wild systems can be challenging and often requires genetic testing. Genotyping-by-sequencing (GBS) and other reduced representation DNA sequencing (RRS) protocols (e.g., RADseq, ddRAD) have enabled the analysis of genetic data on an unprecedented scale. Here, we present a novel approach for the discovery and statistical validation of sex-specific loci in GBS datasets. We used GBS to genotype 166 New Zealand fur seals (NZFS, Arctocephalus forsteri) of known sex. We retained monomorphic loci as potential sex-specific markers in the locus discovery phase. We then used (i) a sex-specific locus threshold (SSLT) to identify significantly male-specific loci within our dataset and (ii) a significant sex-assignment threshold (SSAT) to confidently assign sex in silico the presence or absence of significantly male-specific loci to individuals in our dataset treated as unknowns (98.9% accuracy for females; 95.8% for males, estimated via cross-validation). Furthermore, we assigned sex to 86 individuals of true unknown sex using our SSAT, and assessed the effect of SSLT adjustments on these assignments. From 90 verified sex-specific loci, we developed a panel of three sex-specific PCR primers that we used to ascertain sex independently of our GBS data, which we show amplify reliably in at least three other pinniped species. Using monomorphic loci normally discarded from large SNP datasets is an effective way to identify robust sex-linked markers for non-model species. Our novel pipeline can be used to identify and statistically validate monomorphic and polymorphic sex-specific markers across a range of species and RRS datasets.
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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.