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.
51
datasets available to search
ShareScore release 0.9.0
Dataset results
51 results for “integrated population model”
An integrated population model reveals source-sink dynamics for competitively subordinate African wild dogs linked to anthropogenic prey depletion
<ol> <li>Many African large carnivore populations are declining due to decline of the herbivore populations on which they depend. The densities of apex carnivores like the lion and spotted hyena correlate strongly with prey density, but competitive subordinates like the African wild dog benefit from competitive release when the density of apex carnivores is low, so the expected effect of a simultaneous decrease in resources and dominant competitors is not obvious. </li> <li>Wild dogs in Zambia's Luangwa Valley Ecosystem occupy four ecologically similar areas with well-described differences in the densities of prey and dominant competitors, due to spatial variation in illegal offtake.</li> <li>We used long-term data to fit a Bayesian integrated population model (IPM) of the demography and dynamics of wild dogs in these four regions. The IPM used Leslie projection to link a Cormack-Jolly-Seber model of area-specific survival (allowing for individual heterogeneity in detection), a zero-inflated Poisson model of area-specific fecundity, and a state-space model of population size that used estimates from a closed mark-capture model as the counts from which (latent) population size was estimated.</li> <li>The IPM showed that both survival and reproduction were lowest in the region with the lowest density of preferred prey (puku, <em>Kobus vardonii</em>, and impala, <em>Aepyceros</em> <em>melampus</em>), despite little use of this area by lions. Survival and reproduction were highest in the region with the highest prey density, and intermediate in the two regions with intermediate prey density. The population growth rate (λ) was positive for the population as a whole, strongly positive in the region with the highest prey density, and strongly negative in the region with the lowest prey density.</li> <li>It has long been thought that the benefits of competitive release protect African wild dogs from the costs of low prey density. Our results show that the costs of prey depletion overwhelm the benefits of competitive release and cause local population decline where anthropogenic prey depletion is strong. Because competition is important in many guilds and humans are affecting resources of many types, it is likely that similarly fundamental shifts in population limitation are arising in many systems.</li> </ol>
Integrated population model for the Mallard in the Netherlands
<p><span>Europe's highest densities of breeding Mallards (<em>Anas platyrhynchos</em>) are found in the Netherlands, but the breeding population there has declined by ~30% since the 1990s. The exact cause of this decline has remained unclear.</span><span> </span><span>Here, we used an integrated population model to jointly analyze Mallard population survey, nest survey, duckling survival and band-recovery data. We used this approach to holistically estimate all relevant vital rates, including duckling survival rates for years for which no explicit data were available. Mean vital rate estimates were high for nest success (0.38 ±0.01) and egg hatch rate (0.96 ±0.001), but relatively low for clutch size (8.2 ±0.05) compared to populations in other regions. Estimates for duckling survival rate for the three years for which explicit data were available were low (0.16-0.27) compared to historical observations, but were comparable to rates reported for other regions with declining populations. Finally, mean survival rate was low for ducklings (0.18 ±0.02), but high and stable for adults (0.71 ±0.03). Population growth rate was only affected by variation in duckling survival, but since this is a predominantly latent state variable, this result should be interpreted with caution. However, it does strongly indicate that none of the other vital rates, all of which were supported by data, was able to sufficiently explain the population decline. Together with a comparison with historic vital rates, these findings point to a reduced duckling survival rate as the likely cause of the decline. Candidate drivers of reduced duckling survival are increased predation pressure and reduced food availability, but this requires future study. Integrated population modeling can provide valuable insights into population dynamics even when empirical data for a key parameter are partly missing.</span></p>
Two-sex integrated population model reveals intersexual differences in life history strategies in Cooper's Hawks
<p>This site contains data files and model code for a dynamic nesting territory occupance model and 2-sex integrated population model for Cooper's hawks in Albuquerque, New Mexico, USA, 2011 - 2020.</p>
Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
<p>Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (<em>Ambystoma</em> <em>californiense</em>; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species.</p>
Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
<ol> <li>Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics.</li> <li>We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth.</li> <li>We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction.</li> <li>Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%.</li> <li>Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.</li> </ol>
Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
Open the record for dataset details and reuse information.
Integrated population model for the Mallard in the Netherlands
Open the record for dataset details and reuse information.
Two-sex integrated population model reveals intersexual differences in life history strategies in Cooper’s Hawks
Open the record for dataset details and reuse information.
An integrated population model reveals source-sink dynamics for competitively subordinate African wild dogs linked to anthropogenic prey depletion
Open the record for dataset details and reuse information.
Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
Open the record for dataset details and reuse information.
Data for: An integrated population model and population viability assessment for the southern population of a data-poor species
Open the record for dataset details and reuse information.
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>
Data from: Evaluating population viability and efficacy of conservation management using integrated population models
Predicting population responses to environmental conditions or management scenarios is a fundamental challenge for conservation. Proper consideration of demographic, environmental and parameter uncertainties is essential for projecting population trends and optimal conservation strategies. We developed a coupled integrated population model-Bayesian population viability analysis to assess the (1) impact of demographic rates (survival, fecundity, immigration) on past population dynamics; (2) population viability 10 years into the future; and (3) efficacy of possible management strategies for the federally endangered Great Lakes piping plover Charadrius melodus population. Our model synthesizes long-term population survey, nest monitoring and mark–resight data, while accounting for multiple sources of uncertainty. We incorporated latent abundance of eastern North American merlins Falco columbarius, a primary predator of adult plovers, as a covariate on adult survival via a parallel state-space model, accounting for the influence of an imperfectly observed process (i.e. predation pressure) on population viability. Mean plover abundance increased from 18 pairs in 1993 to 75 pairs in 2016, but annual population growth (math formula) was projected to be 0.95 (95% CI 0.72–1.12), suggesting a potential decline to 67 pairs within 10 years. Without accounting for an expanding merlin population, we would have concluded that the plover population was projected to increase (math formula = 1.02; 95% CI 0.94–1.09) to 91 pairs by 2026. We compared four conservation scenarios: (1) no proposed management; (2) increased control of chick predators (e.g. Corvidae, Laridae, mammals); (3) increased merlin control; and (4) simultaneous chick predator and merlin control. Compared to the null scenario, chick predator control reduced quasi-extinction probability from 11.9% to 8.7%, merlin control more than halved (3.5%) the probability and simultaneous control reduced quasi-extinction probability to 2.6%. Synthesis and applications. Piping plover recovery actions should consider systematic predator control, rather than current ad hoc protocols, especially given the predicted increase in regional merlin abundance. This approach of combining integrated population models with Bayesian population viability analysis to identify limiting components of the population cycle and evaluate alternative management strategies for conservation decision-making shows great utility for aiding recovery of threatened populations.
Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
Quantitatively linking individual variation in functional traits to demography is a necessary step to advance our understanding of trait-based ecological processes. We constructed a population model for Asclepias syriaca to identify how functional traits affect vital rates and population growth and whether tradeoffs in chemical defense and demography alter population growth. Plants with higher foliar cardenolides had lower fiber, cellulose, and lignin levels, as well as decreased sexual and clonal reproduction. Average cardenolide concentrations had the strongest effect on population growth. In both the sexual and clonal pathway, the tradeoff between reproduction and defense affected population growth. We found that both increasing the mean of the distribution of individual plant values for cardenolides and herbivory decreased population growth. However, increasing the variance in both defense and herbivory increased population growth. Functional traits can impact population growth and quantifying individual-level variation in traits should be included in assessments of population-level processes.
Data from: Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales
<p>Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual-level data are available for some species. Integrated population modelling (IPM) offers a mechanism for leveraging these datasets into a single estimation framework. IPMs that incorporate both population- and individual-level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population-level visual survey data, individual-level capture-recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; <i>Delphinapterus leucas</i>) as a case study. Our state-space IPM included a population process model and three observational submodels: 1) a group detection model to describe group size estimates from aerial survey data; 2) a capture-recapture model to describe individual photographic capture-recapture data; and 3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three datasets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect datasets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.</p>
A big data–model integration approach for predicting epizootics and population recovery in a keystone species
<p>Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex non-linear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a non-parametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, <em>Cynomys ludovicianus</em>) and sylvatic plague as an example. We synthesized colony data between 2001–2020 from eight USDA Forest Service National Grasslands across the range of BTPD in central North America. We then modeled extinctions due to plague and colony recovery of BTPD in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summer/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally > 0.80). Thus, these spatially-explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host-pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially-explicit forecasting of disease-induced population fluctuations, for use in natural resource management decision-making.</p>
Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
Open the record for dataset details and reuse information.
A big data–model integration approach for predicting epizootics and population recovery in a keystone species
Open the record for dataset details and reuse information.
Estimating wildlife populations and their dynamics using multiple data sources and a hierarchical integrated model: the case of California's black bears
Open the record for dataset details and reuse information.
Data from: Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales
Open the record for dataset details and reuse information.
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.