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1,068 results for “demographic”
Fig. 4 in Gastrointestinal parasites of a reintroduced semi-wild plains bison (Bison bison bison) herd: Examining effects of demographic variation, deworming treatments, and management strategy
Fig. 4. The sum of FECs counted per gram of individual bison, demonstrating variation FECs between and among individuals. Black horizontal lines denote median values, while the top and bottom of boxes denote the upper and lower interquartile ranges (75th and 25th percentiles). Extending "whiskers" denote values of 1.5 times the interquartile range; points outside of this range constitute outliers.
Fig. 3 in Gastrointestinal parasites of a reintroduced semi-wild plains bison (Bison bison bison) herd: Examining effects of demographic variation, deworming treatments, and management strategy
Fig. 3. The sum of FECs types, including "STRONGs" (Strongyle-type), "COCCs" (Coccidia), "NEMAs" (Nematodirus), "TRICHs" (Trichuris), "MONs" (Moniezia) counted per gram of sample from bison of various age classes. Ages classes included "NC" (New Calf; 0–1), "YR" (Yearling; 1–2), "JA" (Juvenile to Adult Transition; 2–4), "YA" (Young Adult; 4–6), "PA" (Peak Adult; 6–9), "MA" (Mature Adult; 9+). Black horizontal lines denote median values, while the top and bottom of boxes denote the upper and lower interquartile ranges (75th and 25th percentiles). Extending "whiskers" denote values of 1.5 times the interquartile range; points outside of this range constitute outliers.
Fig. 2 in Gastrointestinal parasites of a reintroduced semi-wild plains bison (Bison bison bison) herd: Examining effects of demographic variation, deworming treatments, and management strategy
Fig. 2. The sum of FECs counted per gram of sample from bison of various age classes, including "NC" (New Calf; 0–1), "YR" (Yearling; 1–2), "JA" (Juvenile to Adult Transition; 2–4), "YA" (Young Adult; 4–6), "PA" (Peak Adult; 6–9), "MA" (Mature Adult; 9+). Black horizontal lines denote median values, while the top and bottom of boxes denote the upper and lower interquartile ranges (75th and 25th percentiles). Extending "whiskers" denote values of 1.5 times the interquartile range; points outside of this range constitute outliers.
Fig. 1 in Gastrointestinal parasites of a reintroduced semi-wild plains bison (Bison bison bison) herd: Examining effects of demographic variation, deworming treatments, and management strategy
Fig. 1. Aerial image of the Crane Trust bison pastures. The smaller North metapopulation was continuously grazed in the Visitor Center ("VC" – 50 acres) pasture (outlined in pink). The larger South metapopulation was rotated through Ruge-South Brown ("RS" – 387 acres) pasture (outlined in orange), Calving-Office ("CO" – 267 acres) pasture (outlined in yellow), and North Meadow ("NM" – 177 acres) pasture (outlined in green). The North (orange) and South (pink) metapopulation pastures were separated by a minimum distance of 200 m, including an 80 m channel of the Platte River. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Figs 2-5 in Accessing camera trap survey feasibility for estimating Blastocerus dichotomus (Cetartiodactyla, Cervidae) demographic parameters
Figs 2-5. Individual discrimination of marsh deer males (Blastocerus dichotomus Illiger, 1815) using antler morphology: a spike-antlered male (2) and two different branched antlers (3 and 4). The arrows indicate the different horn tips. Marsh deer female accompanied by a fawn (5).
Fig. 1 in Accessing camera trap survey feasibility for estimating Blastocerus dichotomus (Cetartiodactyla, Cervidae) demographic parameters
Fig. 1. Map outlining the aerial and camera trap surveys conducted at the Jataí Ecological Station, state of SÃo Paulo, Brazil in order to obtain marsh deer demographic parameters.
Fig. 2 in Demographic, environmental and physiological predictors of gastrointestinal parasites in urban raccoons
Fig. 2. Nematode and coccidia faecal egg/oocyst counts in raccoons are associated with raccoon age and the month (season) of sampling. (A) Baylisascaris nematodes; (B) strongyle type nematodes; (C) capillariid type nematodes; (D) coccidia.
Fig. 1 in Demographic, environmental and physiological predictors of gastrointestinal parasites in urban raccoons
Fig. 1. Photographs of nematode eggs and oocysts taken at 40× magnification. (A) Ascarid type nematodes (likely Baylisascaris procyonis); (B) strongyle type nematodes (Placoconis lotoris or Molineus barbatus); (C) capillariid type nematodes (Capillaria procyonis or Capillaria putorii); (D) "large" oocysts; (E) "small" oocysts; (F) "long" oocysts. Scale bar = 20 μm in all photographs.
Fig. 4 in Demographic, environmental and physiological predictors of gastrointestinal parasites in urban raccoons
Fig. 4. Distribution of coinfections in juvenile raccoons sampled in October and yearling raccoons sampled in July. Raccoons could be infected by 0–4 types of parasite. There was no significant difference between cross-sectionally (A) and longitudinally (B) sampled raccoons in the mean number of types of parasite harboured as juveniles in October, suggesting that parasite coinfections do not contribute to overwinter mortality. However, raccoons tended to clear parasite infections rather than gain them during this interval (C).
Fig. 3 in Demographic, environmental and physiological predictors of gastrointestinal parasites in urban raccoons
Fig. 3. Changes in gastrointestinal nematode and coccidia infection status and faecal egg or oocyst count for raccoons that were sampled in both July and October of the same year, stratified by age class. (A) Baylisascaris nematodes; (B) strongyle type nematodes; (C) capillariid type nematodes; (D) coccidia. Juvenile raccoons tended to gain nematode infections between July and October. Both adult and juvenile raccoons that were infected with coccidia in July tended to remain infected when resampled in October. Change in egg count = October egg count – July egg count. On average, the faecal egg count of juvenile raccoons increased more than the adult faecal egg count for Baylisascaris, strongyle, and capillariid nematodes (Welch's two sample t-test; pvalue <0.05), but there was no difference in the change in oocyst count for adults vs juveniles.
Data: Testing the mating system model of parasite complex life cycle evolution reveals demographically driven mixed mating
<p>Abstract: Many parasite species use multiple host species to complete development; however, empirical tests of models that seek to understand factors impacting evolutionary changes or maintenance of host number in parasite life cycles are scarce. Specifically, Brown et al.’s (2001) mating system model, which posits multi-host life cycles are an adaptation to prevent inbreeding in hermaphroditic parasites and thus, preclude inbreeding depression, remains untested. The model assumes loss of a host results in parasite inbreeding and predicts host loss can only evolve if there is no parasite inbreeding depression. <a name="_Hlk169780726"></a>We provide the first empirical tests of this model using a novel approach we developed for assessing inbreeding depression from field-collected, parasite samples. The method compares genetically-based, selfing-rate estimates to a demographic-based selfing rate, which was derived from the closed mating system experienced by endoparasites. Results from the hermaphroditic trematode <em>Alloglossidium renale</em>, which has a derived 2-host life cycle, supported both the assumption and prediction of the mating system model as this highly inbred species had no indication of inbreeding depression. Additionally, comparisons of genetic and demographic selfing rates revealed <a name="_Hlk169781073"></a>a mixed mating system that could be explained completely by the parasite’s demography, i.e., its infection intensities.</p>
MANET: uncertainty in demographics – data on population projections
<p>This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future).</p> <p>More specifically, it contains:</p> <p>- in `other_pop_data` folder files from <a href="https://databank.worldbank.org/source/population-estimates-and-projections">World Bank,</a> the <a href="https://www.census.gov/data-tools/demo/idb/#/dashboard?COUNTRY_YEAR=2023&COUNTRY_YR_ANIM=2023">International Database</a> from the US Census, and from <a href="https://ghdx.healthdata.org/record/ihme-data/global-population-forecasts-2017-2100">IHME</a></p> <p>- in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from <a href="https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=10">IIASA</a> and as in the version 3.0 downloaded from <a href="https://data.ece.iiasa.ac.at/ssp/#/workspaces">IIASA workspace</a></p> <p>- in the `UN` folder, the demographic projections from <a href="https://population.un.org/wpp/Download/Standard/Population/">UN</a></p> <p>- `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases</p> <p>- `RFF.csv`, an overview file containing the population projections obtained by <a href="../record/6016583#.Y42iFuzP2rP">Resources For the Future</a> </p> <p>'- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from <a href="https://tntcat.iiasa.ac.at/AR5DB">AR5</a>, <a href="https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/downloads">SR 1.5</a>, and <a href="https://data.ene.iiasa.ac.at/ar6/#/workspaces">AR6</a></p> <p>This data in intended to be downloaded for use together with the package downloadable <a href="https://github.com/sgiarols/Climate_Scenario_Data_Science">here</a>.</p> <p>The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).</p>
Demographic data of US Counties Estimation 2019
<p>US government demographic data for all US counties estimated in 2019 including state, county, region, area land, area water, coordinates, birth rate, death rate, immigrants, </p>
Supporting data and code for: Demographic and genetic impacts of powdery mildew in a young oak cohort
<p>This is a new release following the submission of the related PCI recommended manuscript to the <em>Annals of Forest Science</em> journal. It contains the necessary scripts to produce most of the analyses and figures of the manuscript. Apart from minor modifications following the recommendation in '<em>PCI Forest and Wood Sciences</em>', the main change is the addition of an extra dataset "Data_S2.txt" to the additional datasets. This dataset was previously included as a table in the 'supplementary material' file.</p>
Demographic Questions
<p>This file contains the demographic questions. </p>
Anderson Police Department Hate Crime Demographics 2023
<p>This dataset contains demographic information related to reported hate crimes within the jurisdiction of the Anderson Police Department. The data includes details on both victims and alleged perpetrators, with demographic variables such as age, gender, and race/ethnicity. The types of hate crimes covered in the dataset are based on classifications in accordance with relevant local and federal hate crime definitions.</p> <p>The dataset was obtained through a Public Records Act request and covers the time period from January 1st 2023 through December 31st 2023. This agency had no Hate Crimes to report in 2022. It was provided in MS Word format, where each row represents a unique hate crime incident and the columns capture demographic and other related variables.</p>
Simulated datasets from modelling demographic events and migration patterns
<p>These are datasets generated from multi-state model (MSM) project on understanding demographic events and migration patterns in two urban slums of Nairobi City in Kenya at the African Population and Health Research Center (APHRC). The project focuses on using MSM techniques to analyze residence demographic events in Nairobi urban slums, with an emphasis on key events such as:</p> <ul> <li>Births</li> <li>Deaths</li> <li>Migration (in-migration and out-migration)</li> <li>Changes in residence status (exit and entry)</li> </ul> <p>The primary aim of these datasets is to allow those who want to understand and model the demographic transitions in Nairobi's informal settlements, identifying factors that influence residence changes over time. </p>
Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories (dataset and R script)
<p>The present digital archive is the outcome of the paper: <strong>Palmisano, A., Bevan, A., Kabelindde, A., Roberts, N., and Shennan, S., 2021. <a href="https://doi.org/10.1007/s10963-021-09159-3">Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories</a>. <em>Journal of World Prehistory, 34 (3)</em>, </strong>381-432<strong>.</strong></p> <p>The dataset included here provides a collection of <strong>4,010</strong> radiocarbon dates from <strong>947</strong> archaeological sites for a period spanning between 11,000 and 1500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of one script written in R statistical computing language.</p> <p>List of versions:</p> <ul> <li><strong>1.0.</strong> 4 August 2021 - First public release of the dataset on Zenodo. </li> </ul>
Figure 2 in Application of demographic analysis for assessing effects of pesticides on the predatory mite, Phytoseiulus persimilis (Acari: Phytoseiidae)
Figure 2. Age specific survival rate (lx), fecundity (mx), maternity (lxmx) and age-stage specific fecundity (fxj) of offspring from Phytoseiulus persimilis females treated with LC25 of three pesticides compared with untreated females.
Figure 1 in Application of demographic analysis for assessing effects of pesticides on the predatory mite, Phytoseiulus persimilis (Acari: Phytoseiidae)
Figure 1. Age-stage specific survival rate (sxj) of offspring from Phytoseiulus persimilis females treated with LC25 of three pesticides compared with untreated females.
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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.