Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
89
datasets available to search
ShareScore release 0.9.0
Dataset results
89 results for “demographic modelling”
Investigating dynamics between energy use and socio-demographic characteristics in spatial modeling of residential energy consumption
<p>Files represent datasets (2017 Residential Building Stock Assessment and American Community Survey 2012-2017 5-year estimate) and R-code associated with the analysis. </p>
Model codes and simulation data for "Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)"
<p>ModelE-BiomeE v1.0 model codes and data This folder contains the simulation data and model codes that were used in the paper ‘Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS’s Earth system model (ModelE-BiomeE v.1.0)’ (https://doi.org/10.5194/gmd-2022-72). We included the data simulated by ModelE-BiomeE v.1.0 with settings of full demography (folder FullDemography) and single cohort (folder SingleCohort), and initial settings of land grids and vegetation data (folder GlobalVegetation). The codes include the full ModelE 2.1, module BiomeE files in ModelE, and the standalone BiomeE. In the folder FullDemography, we have 4 netcdf files for global output and 25 files for single grids output. The files ‘FullDM_2588_JAN.nc’ and ‘FullDM_2588_JUL.nc’ are the original model output of January and July in the year 2588. The file ‘FullDM_2588_Annual.nc’ is the yearly summary of model simulations. The file ‘FullDM_Selected.nc’ is an annual summary of 588 years of model simulation only with selected variables. The csv files are for single grids output at the time steps of daily and yearly. The last digit 1~8 represents the sites of 'BNC','MNT','HF','OKR','KZ','SV','WGK','TPJ', respectively (Table 1). Table 1 Site ID and file number ['BNC', 'MNT', 'HF', 'OKR', 'KZ', 'SV', 'WGK', 'TPJ'] ['8991', '8992', '8993', '8994', '8995', '8996', '8997', '8998'] ['8971', '8972', '8973', '8974', '8975', '8976', '8977', '8978'] ['8961', '8962', '8963', '8974', '8965', '8966', '8977', '8968'] Please refer to Table 2 in the paper for the detail of these 8 sites. ‘DailyLAIGPP.csv’ is a summary of all ‘DailyEcosystem’ files with LAI and GPP data. We included the Python scripts that can be used to generate the figures in out paper (Plotting-BiomeE-MsTMIP.py, Plotting-Scatter-Comparison.py, PlottingBiomeEMaps.py, and PlottingGridOutput.py). For the convenience of readers (in reproducing our figures), we included the summary of reanalysis of the data from observations and MsTMIP in folder ‘Sum-Obs-Simu’. Please refer to the original sources listed in our paper for the detail of these data.</p>
Supplementary material for "Palaeo-demographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia"
<p>This Supplementary material encompasses the archaeological radiocarbon dates for the Iberian Peninsula analyzed in the article “<em>Palaeo-demographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia</em>". Specifically:</p> <ul> <li>‘<strong>PALEODEM_dataset.csv</strong>’ provides the dataset in comma-separated format. Contains the compiled raw data of each radiocarbon date used by every analytical procedure.</li> <li>‘<strong>PALEODEM_sites.xlsx</strong>’ is a spreadsheet containing the basic information of each archaeological site analyzed in this work. The columns include ID_site, name of Archaeological site, n<sup>o</sup> of <sup>14</sup>C dates, n<sup>o</sup> of assemblages, Regional Unit of correspondence, and bibliographical Reference.</li> <li>‘<strong>REFERENCES for PALEODEM_sites.docx</strong>’ is a text archive that collects the bibliographical references listed in the above mentioned ‘Reference’ column, that have been the main sources of archaeological information.</li> </ul>
Data from: Exploring rainforest diversification using demographic model testing in the African foam-nest treefrog (Chiromantis rufescens)
Aim: Species with wide distributions spanning the African Guinean and Congolian rainforests are often composed of genetically distinct populations or cryptic species with geographic distributions that mirror the locations of the remaining forest habitats. We used phylogeographic inference and demographic model testing to evaluate diversification models in a widespread rainforest species, the African Foam-nest Treefrog (Chiromantis rufescens). Location: Guinean and Congolian rainforests, West and Central Africa. Taxon: Chiromantis rufescens. Methods: We collected mitochondrial DNA (mtDNA) and single nucleotide polymorphism (SNP) data for 130 samples of Chiromantis rufescens. After estimating population structure and inferring species trees using coalescent methods, we tested demographic models to evaluate alternative population divergence histories that varied with respect to gene flow, population size change, and periods of isolation and secondary contact. Species distribution models were used to identify regions of climatic stability that could have served as forest refugia since the Last Interglacial. Results: Population structure within Chiromantis rufescens resembles the major biogeographic regions of the Guinean and Congolian forests. Coalescent-based phylogenetic analyses provide strong support for an early divergence between the western Upper Guinean forest and the remaining populations. Demographic inferences support diversification models with gene flow and population size changes even in cases where contemporary populations are currently allopatric, which provides support for forest refugia and barrier models. Species distribution models suggest that forest refugia were available for each of the populations throughout the Pleistocene. Main conclusions: Considering historical demography is essential for understanding population diversification, especially in complex landscapes such as those found in the Guineo-Congolian forest. Population demographic inferences help connect patterns of genetic variation to diversification model predictions. The diversification history of Chiromantis rufescens was shaped by a variety of processes, including vicariance from river barriers, forest fragmentation, and adaptive evolution along environmental gradients.
Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
<p>This archive contains the empirical data analysed in the paper 'Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets' by Touzalin et al. (https://doi.org/10.24072/pci.ecology.100416). The dataset is provided as a .Rdata file ('TLoss_GMdata.Rdata'), and full description of the content is provided in the file 'Readme_TLdata.csv'. All additional details are available in the main text (https://doi.org/10.24072/pci.ecology.100416) or in the supporting information (https://doi.org/10.5281/zenodo.10204538).</p>
Extending Grime's CSR model to predict plant demographic responses across resource availability gradients: evidence from the Patagonian steppes
<p>Sexual reproduction, growth, and survival are crucial demographic strategies for plant population viability. Here, we propose a conceptual model predicting demographic responses of species based on their ecological strategy and the heterogeneity of environmental conditions within a biogeographical unit and then applied it to a case study from a 5-degree latitudinal gradient in the Patagonian steppes. We also aim to disentangle genetic from environmental effects on demographic responses. We performed <em>in-situ </em>and common garden experiments with two species from six local populations of the Occidental Phytogeographical District of the Patagonian steppes. Species differ in key ecological traits, and thus fit into Grime´s model for evolutionary strategies in plants: one as competitive species and the other as stress-tolerant species. We calculated population growth rate (λ) and performed elasticity analyses to compare the contribution of each demographic strategy to population fitness between species and among local populations distributed along 600 km latitudinal gradient with differences in mean annual precipitation (MAP). We highlight four results. First, the competitive species change from sexual reproduction to growth as MAP increases. Second, the stress-tolerant species relied on growth and survival along the MAP gradient. Third, interannual variation in resource availability modulated demographic responses for both strategies. Fourth, based on the comparison of the <em>in-situ</em> and common garden experiments, we submit that demographic responses were genetically driven. Our study shows that demographic responses can be roughly predicted by the ecological strategy across environmental gradients. We show that differences arise not only between species, but also were genetically driven differences within species among local populations. Scaling up plant-level responses to population-level dynamics allows for a process-based understanding of current and future biogeographical species organization. Furthermore, conservation and restoration efforts should be guided by demographic strategies underlying population viability.</p>
Evaluating the suitability of close-kin mark-recapture as a demographic modelling tool for a critically endangered elasmobranch population
<p>Estimating the demographic parameters of contemporary populations is essential to the success of elasmobranch conservation programmes, and to understanding their recent evolutionary history. For benthic elasmobranchs such as skates, traditional fisheries-independent approaches are often unsuitable as the data may be subject to various sources of bias, whilst low recapture rates can render mark-recapture programmes ineffectual. Close-kin mark-recapture (CKMR), a novel demographic modelling approach based on the genetic identification of close relatives within a sample, represents a promising alternative approach as it does not require physical recaptures. We evaluated the suitability of CKMR as a demographic modelling tool for the critically endangered blue skate (<em>Dipturus batis</em>) in the Celtic Sea using samples collected during fisheries-dependent trammel-net surveys that ran from 2011 to 2017. We identified three full-sibling and 16 half-sibling pairs among 662 skates, which were genotyped across 6,291 genome-wide single nucleotide polymorphisms (SNPs), 15 of which were cross-cohort half-sibling pairs that were included in a CKMR model. Despite limitations owing to a lack of validated life-history trait parameters for the species, we produced the first estimates of adult breeding abundance, population growth rate, and annual adult survival rate for <em>D. batis</em> in the Celtic Sea. The results were compared to estimates of genetic diversity, effective population size (N<sub>e</sub>), and catch per unit effort (CPUE) estimates from the trammel-net survey. Although each method was characterised by wide uncertainty bounds, together they suggested a stable population size across the time-series. Recommendations for the implementation of CKMR as a conservation tool for data-limited elasmobranchs are discussed. In addition, the spatio-temporal distribution of the 19 sibling pairs revealed a pattern of site-fidelity in <em>D</em>. <em>batis</em>, and supported field observations suggesting an area of critical habitat that could qualify for protection might occur near the Isles of Scilly.</p>
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>
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>
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
<p>Understanding historical range shifts and population size variation provides important context for interpreting contemporary genetic diversity. Methods to predict changes in species distributions and model changes in effective population size (N<sub>e</sub>) using whole genomes make it feasible to examine how temporal dynamics influence diversity across populations. We investigate N<sub>e</sub> variation and climate-associated range shifts to examine the origins of a previously observed latitudinal heterozygosity gradient in the bumble bee <em>Bombus</em> <em>vancouverensis</em> Cresson (Hymenoptera: Apidae: <em>Bombus</em> Latreille) in western North America. We analyze whole genomes from a latitude-elevation cline using sequentially Markovian coalescent models of N<sub>e</sub> through time to test whether relatively low diversity in southern high-elevation populations is a result of long-term differences in N<sub>e</sub>. We use Maxent models of the species range over the last 130,000 years to evaluate range shifts and stability. N<sub>e</sub> fluctuates with climate across populations, but more genetically diverse northern populations have maintained greater Ne over the late Pleistocene and experienced larger expansions with climatically favorable time periods. Northern populations also experienced larger bottlenecks during the last glacial period which matched the loss of range area near these sites, however, bottlenecks were not sufficient to erode diversity maintained during periods of large N<sub>e</sub>. A genome sampled from an island population indicated a severe postglacial bottleneck, indicating that large recent post-glacial declines are detectable if they have occurred. Genetic diversity was not related to niche stability or glacial-period bottleneck size. Instead, spatial expansions and increased connectivity during favorable climates likely maintain diversity in the north while restriction to high elevations maintains relatively low diversity despite greater stability in southern regions. Results suggest genetic diversity gradients reflect long-term differences in N<sub>e</sub> dynamics and also emphasize the unique effects of isolation on insular habitats for bumble bees. Patterns are discussed in the context of conservation under climate change.</p>
Figure 4 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 4.Age–specific survival rate (lx), female age–specific fecundity (fx8), age–specific fecundity (mx), and agespecific maternity (lxmx) ofB. rubrioculusat five constant temperatures.
Figure 2 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 2.Observed Age-specific survival rate (lx) and Observed age–specific fecundity (mx) ofBryobia rubrioculus at five constant temperatures fitted to the Weibull's and Polynomial's estimates respectively.
Figure 3 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 3.Age–stage specific survival rate (sxj) ofBryobia rubrioculus at five constant temperatures.
Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity
<ol> <li>How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.</li> <li>Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. </li> <li>We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.</li> <li>We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.</li> <li>The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.</li> </ol>
Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity
Open the record for dataset details and reuse information.
Data from: Exploring rainforest diversification using demographic model testing in the African foam-nest treefrog (Chiromantis rufescens)
Open the record for dataset details and reuse information.
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
Open the record for dataset details and reuse information.
Evaluating the suitability of close-kin mark-recapture as a demographic modelling tool for a critically endangered elasmobranch population
Open the record for dataset details and reuse information.
Extending Grime’s CSR model to predict plant demographic responses across resource availability gradients: evidence from the Patagonian steppes
Open the record for dataset details and reuse information.
Using demographic model selection to untangle allopatric divergence and diversification mechanisms in the Rheum palmatum complex in the Eastern Asiatic Region
<p>Allopatric divergence is often initiated by geological uplift and restriction to sky-islands, climate oscillations, or river capture. However, it can be difficult to establish which mechanism was the most likely to generate the current phylogeographic structure of a species. Recently, genomic data in conjunction with a model testing framework have been applied to address this issue in animals. To test whether such an approach is also likely to be successful in plants we used population genomic data of the <i>Rheum palmatum</i> complex from the Eastern Asiatic Region, in conjunction with biogeographical reconstruction and demographic model selection to identify the potential mechanism(s) which have led to the current level of divergence. Our results indicate that the <i>R. palmatum</i> complex originated in the central Hengduan Mts. and possibly in regions further to the east, and then dispersed westward and eastward resulting in genetically distinct lineages. Populations are likely to have diverged in refugia during climate oscillations followed by subsequent expansion and secondary contact. However, model simulations within the western lineage of the <i>R. palmatum</i> complex cannot reject a restriction to sky-islands as a possible mechanism of diversification due to the genetically ambiguous position of one population. This highlights that genetically mixed populations might introduce ambiguity regarding the best diversification model in some cases. Although it might be possible to resolve this ambiguity using other data, sometimes this could prove to be difficult in complex biogeographic areas.</p>
ScienceDex guides
Understand access before you commit
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.