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58 results for “population dynamics models”
Data from: Integrated modeling predicts shifts in waterbird population dynamics under climate change
Climate change has been identified as one of the most important drivers of wildlife population dynamics. The in-depth knowledge of the complex relationships between climate and population sizes through density dependent demographic processes is important for understanding and predicting population shifts under climate change, which requires integrated population models (IPMs) that unify the analyses of demography and abundance data. In this study we developed an IPM based on Gaussian approximation to dynamic N-mixture models for large scale population data. We then analyzed four decades (1972-2013) of Mallard (Anas platyrhynchos) breeding population survey, band-recovery, and climate data covering a large spatial extent from North American prairies through boreal habitat to Alaska. We aimed to test the hypothesis that climate change will cause shifts in population dynamics if climatic effects on demographic parameters that have substantial contribution to population growth vary spatially. More specifically, we examined the spatial variation of climatic effects on density dependent population demography, identified the key demographic parameters that are influential to population growth, and forecasted population responses to climate change. Our results revealed that recruitment, which explained more variance of population growth than survival, was sensitive to the temporal variation of precipitation in the southern portion of the study area but not in the north. Survival, by contrast, was insensitive to climatic variation. We then forecasted a decrease in Mallard breeding population density in the south and an increase in the northwestern portion of the study area, indicating potential shifts in population dynamics under future climate change. Our results implied that different strategies need to be considered across regions to conserve waterfowl populations in the face of climate change. Our modelling approach can be adapted for other species and thus has wide application to understanding and predicting population dynamics in the presence of global change.
Data from: Integrating genetic analysis of mixed populations with a spatially-explicit population dynamics model
Inferring the dynamics of populations in time and space is a central challenge in ecology. Intra-specific structure (for example genetically distinct sub-populations or meta-populations) may require methods that can jointly infer the dynamics of multiple populations. This is of particular importance for harvested species, for which management must balance utilization of productive populations with protection of weak ones. Here we present a novel method for simultaneous learning about the spatio-temporal dynamics of multiple populations that combines genetic data with prior information about abundance and movement in an integrated population modelling approach. We apply the Bayesian genetic mixed stock analysis to 17 wild and 10 hatchery-reared Baltic salmon (S. salar) stocks, quantifying uncertainty in stock composition in time and space, and in population dynamics parameters such as migration timing and speed. Our results indicate that the commonly used "equal prior probabilities" assumption may not be appropriate for all mixed stock analyses. Incorporation of prior information about stock abundance and movement resulted in more precise and plausible estimates of mixture compositions in time and space. Inclusion of a population dynamics model also allowed robust interpolation of expected catch composition at areas and times with no genetic observations. The genetic data were informative about stock-specific movement patterns, updating priors for migration path, timing and speed. The model we present here forms the basis for optimizing the spatial and temporal allocation of harvest to support the management of mixed populations of migratory species.
Data from: Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history
Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive.
Data from: Population dynamics of an Arctiid caterpillar-tachinid parasitoid system using state-space models
1. Population dynamics of insect host–parasitoid systems are important in many natural and managed ecosystems and have inspired much ecological theory. However, ecologists have a limited knowledge about the relative strengths of species interactions, abiotic effects and density dependence in natural host–parasitoid dynamics. Statistical time-series analyses would be more informative by incorporating multiple factors, measurement error and noisy dynamics. 2. We use a novel maximum likelihood and model-selection analysis of a state-space model for host–parasitoid dynamics to examine 21 years of annual census data for woolly bear caterpillars (Platyprepia virginalis) and their locally host-specific tachinid parasitoids (Thelaira americana). 3. Caterpillar densities varied by three orders of magnitude and were driven by density dependence and precipitation from the previous March but not detectably by parasitoids, despite variable and sometimes high (>50%) parasitism. 4. Fly fluctuations, as estimated from per cent parasitism, were affected by density dependence and precipitation from the previous July. There was marginal evidence that host abundance drives fly fluctuations as a generic linear effect but no evidence for classical Nicholson–Bailey coupling. 5. The state-space model analysis includes new methods for likelihood calculation and allows a balanced consideration of effect magnitude and statistical significance in a nonlinear model with multiple alternative explanatory variables.
Data from: Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations.
Including population and environmental dynamic heterogeneities in continuum models of collective behaviour with applications to locust foraging and group structure Data and Code
<p>This dataset includes all data used for the creation of "Including dynamic population and environmental heterogeneity in continuum models of collective behaviour with applications to locust foraging and group structure" as well as a snapshot of the code used.<br><br>Each zip should be unzippable and the code should operate with only the contents of the zip file.</p>
Figure 1 in A theoretical composite model for population sex-specific shell size dynamics in Strombidae (Gastropoda, Neostromboidae)
Figure 1. Modelling male and females population distribution curves showing the mean size (μ) of each sex and the (1) Sex dependant factors: a) time to maturity; b) intra-male competition; c) femalespecific sexual selection; d) fecundity; (2) Inter-sex dependant factors: e) time to maturity; f) sex bias towards larger numbers of females; and (3) Population factors: g) environmental conditions; and h) universal size regulators that affect the size ratio between females and males.
The appendix for dynamic model of respiratory infectious disease transmission by population mobility based on city network
<p>First, a scale-free city network was established, and the shortest path between any two nodes was determined. Second, the movement path of tourists was designed based on the shortest path. Subsequently, every infected person's information, such as the city, infection time, onset, and hospitalisation, was confirmed based on their movement path. Third, the features of the transmission path and time distribution of the epidemic were characterised after summarising the information. Finally, the reliability of the model was verified.</p>
Data from: A dynamical model for invasive round goby populations reveals efficient and effective management options
1. When prevention of invasive species' introductions fails, society faces the challenge to manage these invasive species in an effective and efficient way. The success of this depends on biological aspects and on cooperation between decision makers and scientists. Using the case of the round goby Neogobius melanostomus, one of Europe's worst invasive species, we propose an approach guiding scientists to co-produce effective and efficient population control measures in collaboration with decision makers. 2. We surveyed the effectiveness, urgency and simplicity perceived by decision makers as well as the support of two population control options: removal of eggs and/or adults. Using a field study and a dynamical population model, we investigated the effectiveness and efficiency for both options in different population contexts. 3. Decision makers initially seemed to lack a clear preference for either control option. After being presented with preliminary field and modelling results, decision makers mostly approved measures being developed to implement the two control options. 4. Starting population control early after detecting the species requires in total fewer years for eradication than controlling an established population: to reach an eradication success rate of 95%, 13 years for early start vs. 18 years for late start are needed when removing eggs and adults; when removing adults only, 20 vs. 29 years are needed. Removing eggs and adults combined results in a yearly effort of 5.01 h m-2, while removing adults only results in a yearly effort of 1.76 h m-2. Thus, removing adults only proved to be the most efficient option to eradicate the population. Nonetheless, considerable effort is needed: when removing less than 57% of the adult population, eradication is not feasible, even assuming low survival and fecundity rates for the population. Further, inflow of new propagules renders eradication efforts ineffective. 5. Synthesis and applications. Scientists who aim to support decision makers in finding an optimal control strategy for invasive species need to be able to provide scientific knowledge on effectiveness and efficiency of different options. For round goby and most non-native species, eradication is only feasible if started early in recently arrived populations and if inflow of new propagules can be prevented.
Data from: Integrating genetic analysis of mixed populations with a spatially-explicit population dynamics model
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Data from: Maiasaura, a model organism for extinct vertebrate population biology: a large sample statistical assessment of growth dynamics and survivorship
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Data from: A dynamical model for invasive round goby populations reveals efficient and effective management options
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Data from: Assessing the dynamics of natural populations by fitting individual based models with approximate Bayesian computation
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Data from: Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history
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Data from: Matrix models of hierarchical demography: linking group- and population-level dynamics in cooperative breeders
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A spatially explicit model to simulate the population dynamics of gypsy moth (Lymantria dispar)
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Data from: Population dynamics of an Arctiid caterpillar-tachinid parasitoid system using state-space models
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Data from: Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models
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Data from: Integrated modeling predicts shifts in waterbird population dynamics under climate change
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Data From: Applying empirical dynamic modeling to distinguish abiotic and biotic drivers of population fluctuations in sympatric fishes
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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)
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.