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491 results for “population modelling”
Data from: Accuracy of genomic selection models in a large population of open-pollinated families in white spruce
Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach.
Data from: Multi-scale model of regional population decline in little brown bats due to white-nose syndrome
The introduced fungal pathogen Pseudogymnoascus destructans is causing decline of several species of bats in North America, with some even at risk of extinction or extirpation. The severity of the epidemic of white-nose syndrome caused by P. destructans has prompted investigation of the transmission and virulence of infection at multiple scales, but linking these scales is necessary to quantify the mechanisms of transmission and assess population-scale declines. We build a model connecting within-cave disease dynamics of little brown bats to regional scale dispersal, reproduction, and disease spread, including multiple plausible mechanisms of transmission. We parameterize the model using the approach of plausible parameter sets, by comparing stochastic simulation results to statistical probes from empirical data on within-cave prevalence and survival, as well as between-cave spread across a region. Our results are consistent with frequency-dependent transmission between bats, support an important role of environmental transmission, and show very little effect of dispersal among colonies on metapopulation survival. The model also offers a generalizable method to assess hypotheses about cave-to-cave transmission and to identify gaps in knowledge about key processes, and could be expanded to include additional mechanisms or bat species as research on this detrimental fungus progresses.
Data from: A spatially explicit hierarchical model to characterize population viability
Many of the processes that govern the viability of animal populations vary spatially, yet population viability analyses (PVAs) that account explicitly for spatial variation are rare. We develop a PVA model that incorporates autocorrelation into the analysis of local demographic information to produce spatially explicit estimates of demography and viability at relatively fine spatial scales across a large spatial extent. We use a hierarchical, spatial autoregressive model for capture-recapture data from multiple locations to obtain spatially explicit estimates of adult survival (Φad), juvenile survival (Φjuv), and juvenile-to-adult transition rates (ψ), and a spatial autoregressive model for recruitment data from multiple locations to obtain spatially explicit estimates of recruitment (R). We combine local estimates of demographic rates in stage-structured population models to estimate the rate of population change (λ), then use estimates of λ (and its uncertainty) to forecast changes in local abundance and produce spatially explicit estimates of viability (probability of extirpation, Pex). We apply the model to demographic data for the Sonoran desert tortoise (Gopherus morafkai) collected across its geographic range in Arizona. There was modest spatial variation in λ (0.94–1.03), which reflected spatial variation in Φad (0.85–0.95), Φjuv (0.70–0.89), and ψ (0.07–0.13). Recruitment data were too sparse for spatially explicit estimates, therefore we used a range-wide estimate (R = 0.32 one-year old females per female per year). Spatial patterns in demographic rates were complex, but Φad, Φjuv, and λ tended to be lower and ψ higher in the northwestern portion of the range. Spatial patterns in Pex varied with local abundance. For local abundances > 500, Pex was near zero (Pex approached one in the northwestern portion of the range and remained low elsewhere. When local abundances were Pex > 0.25). This approach to PVA offers the potential to reveal spatial patterns in demography and viability that can inform conservation and management at multiple spatial scales, provide insight into scale-related investigations in population ecology, and improve basic ecological knowledge of landscape-level phenomena.
Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)
The central-marginal hypothesis (CMH) predicts that population size, genetic diversity, and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size, and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core-to-edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean center on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core to edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.
Data from: Population genetic data of a model symbiotic cnidarian system reveal remarkable symbiotic specificity and vectored introductions across ocean basins
The Aiptasia-Symbiodinium symbiosis is a promising model for experimental studies of cnidarian-dinoflagellate associations, yet relatively little is known regarding the genetic diversity of either symbiotic partner. To address this we collected Aiptasia from 17 localities throughout the world and examined the genetic diversity of both anemones and their endosymbionts. Based on newly-developed SCAR markers, Aiptasia consisted of two genetically-distinct populations, one Aiptasia lineage from Florida and a second network of Aiptasia genotypes found at other localities. These populations did not conform to the distributions of described Aiptasia species, suggesting that taxonomic re-evaluation is needed in light of molecular genetics. Associations with Symbiodinium further demonstrated the distinctions among Aiptasia populations. According to 18S-RFLP, ITS2-DGGE, and microsatellite flanker region sequencing, Florida anemones engaged in diverse symbioses predominantly with members of Symbiodinium Clades A and B, but also C, whereas anemones from elsewhere harboured only S. minutum within Clade B. Symbiodinium minutum apparently does not form a stable symbiosis with other hosts, which implies a highly-specific symbiosis. Fine-scale differences among S. minutum populations were quantified using six microsatellite loci. Populations of S. minutum had low genotypic diversity and high clonality (R=0.14). Furthermore, minimal population structure was observed among regions and ocean basins, due to allele and genotype sharing. The lack of genetic structure and low genotypic diversity suggest recent vectoring of Aiptasia and S. minutum across localities. This first ever molecular-genetic study of a globally-distributed cnidarian and its Symbiodinium assemblages reveals host-symbiont specificity and widely-distributed populations in an important model system.
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.
Data from: Host resistance, population structure and the long-term persistence of bubonic plague: contributions of a modelling approach in the Malagasy focus
Although bubonic plague is an endemic zoonosis in many countries around the world, the factors responsible for the persistence of this highly virulent disease remain poorly known. Classically, the endemic persistence of plague is suspected to be due to the coexistence of plague resistant and plague susceptible rodents in natural foci, and/or to a metapopulation structure of reservoirs. Here, we test separately the effect of each of these factors on the long-term persistence of plague. We analyse the dynamics and equilibria of a model of plague propagation, consistent with plague ecology in Madagascar, a major focus where this disease is endemic since the 1920s in central highlands. By combining deterministic and stochastic analyses of this model, and including sensitivity analyses, we show that (i) endemicity is favoured by intermediate host population sizes, (ii) in large host populations, the presence of resistant rats is sufficient to explain long-term persistence of plague, and (iii) the metapopulation structure of susceptible host populations alone can also account for plague endemicity, thanks to both subdivision and the subsequent reduction in the size of subpopulations, and extinction-recolonization dynamics of the disease. In the light of these results, we suggest scenarios to explain the localized presence of plague in Madagascar.
Supplemental Materials - Performance Figures for "A Model for Predicting the (re)-occurrence of a ≥40% eGFR Decline in a large Population-based cohort of Persons with or At-Risk of Chronic Kidney Disease " paper
<p>The zip file contains performance metrics figures for each dynamic Bayesian Network (DBN) model, stratified by comorbidities, race, CKD stages, and ethnicity.</p> <p>Contains:</p> <ul> <li>Stratified: Bootstrapping of 1000 iterations and 1000 samples with stratified proportions (as in the original population of the test set) of rapid eGFR decliners and non-decliners.</li> </ul> <p> </p> <p>Second zip contains DBN structures as matrices for 2 periods study entry to entry period and entry period to year 1 for all sites in 2 excel files.</p>
Mechanistic insights into silver-gold nanoalloy formation by two-dimensional population balance modeling
<p>This is the raw data for the manuscript:</p><p>Mechanistic insights into silver-gold nanoalloy formation by two-dimensional population balance modeling<br><br>Abstract:<br><br>The large-scale synthesis of nanoparticles (NPs) with defined properties requires detailed understanding of the underlying formation mechanisms and kinetics. The formation mechanisms of bimetallic NPs are still not sufficiently understood due to the complex reaction chemistry, which makes the control of the supersaturation within the reactor, as the thermodynamic driving force, challenging. Particle size, chemical composition, and the distribution of the elements within the particles change dynamically during particle formation. In this work, we propose a mechanism for the formation of bimetallic silver-gold alloy NPs via a green liquid-phase co-reduction synthesis and develop a two-dimensional population balance model to quantitatively describe the evolution of particle size, composition, and optical properties. We shed light on the complex multi-stage formation mechanism of a highly relevant bimetallic NP system and lay the foundation for tailoring the process conditions to achieve desired optical particle properties and to develop predictive property-process relationships.</p><p> </p><p>All data are sorted according to their appearance in the figures of the main manuscript.</p>
Modelled 1-km resolution population densities for 49 bird species in the UK between 2007 and 2009
<p>This is a dataset derived from the BTO/JNCC/RSPB Breeding Bird Survey (BBS) used to produce <a href="https://www.bto.org/our-science/projects/breeding-bird-survey/latest-results/maps-population-density-and-trends">modelled maps of population density</a> for 49 bird species at 1-km square resolution across the UK between 2007 and 2009. </p> <p>Acknowledgement: These data may be used subject to the appropriate acknowledgement of the BTO/JNCC/RSPB Breeding Bird Survey. Acknowledgements should be in the form of the most recent BBS Report citation, available <a href="https://www.bto.org/our-work/science/publications/reports/bbs-reports" target="_blank" rel="noopener">online</a>, or as follows: “<em>The BTO/JNCC/RSPB Breeding Bird Survey is a partnership jointly funded by the BTO, RSPB and JNCC, with fieldwork conducted by volunteers.</em>”</p> <p>Please refer to the metadata for a more detailed description, and for information on dataset usage.</p> <p>........................................................................................</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Fig. 8 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 8. Myosotis antarctica subsp. traillii photographs and distribution map. (a) Habit. (b, d) Rosette leaf tips: (b) adaxial and (d) abaxial sides. (c) Flower. (e) Nutlets. (f) Map of georeferenced herbarium specimens observed by J. M. Prebble (35). Whie scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, e by J. M. Prebble (a: WELT SP100487, Tiwai Point, Southland, South Island; e: WELT SP104518, cultivated ex Mason Bay, Stewart Island). b, c © Te Papa by H. M. Meudt (b: WELT SP090544, Manihi Rd, Taranaki, North Island; c: WELT SP090629, Hukanui, Gisborne, North Island; d: WELT SP090631, Waipuna, Gisborne, North Island).
Fig. 2 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 2. Maps of MaxEnt niche models for pygmy Myosotis in New Zealand and southern South America. (a) Myosotis glauca (light blue circles). (b) M. pygmaea (green circles). (c, h) M. "Volcanic Plateau" (grey triangles). (d) M. brevis (yellow cir-cles). (e) M. drucei (dark blue circles; excluding individuals identified as M. "Volcanic Plateau"). (f) M. drucei (dark blue circles) + M. pygmaea (green circles) + M. "Volcanic Plateau" (grey triangles) (g) M. antarctica (pink circles; Chilean locations), note scale is the same as for maps of New Zealand. a–f use models based on the nine-layer model (see Table 1), whereas g and h are based on the sevenlayer model.
Fig. 5 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 5. Myosotis glauca photographs and distribution map. (a) Habit. (b) Rosette leaves, adaxial and abaxial sides. (c) Calyces, left to right most to least mature. (d) Nutlets. (e) Map of georeferenced herbarium specimens observed by J. M. Prebble (16). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: all by J. M. Prebble (WELT SP093285, Nevis Valley, Otago).
Fig. 4 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 4. Myosotis brevis photographs and distribution map. (a) Habit. (b) Inflorescence showing cauline leaf abaxial side. (c) Inflorescence showing cauline leaf adaxial side, calyces, and flower. (d) Rosette leaf adaxial side showing colour morphs. (e) Flower. (f) Nutlet. (g) Map of georeferenced herbarium specimens observed by J. M. Prebble (25). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: a–e © Te Papa by H. M. Meudt (a: WELT SP090549, Te Ikaamaru Bay, Wellington; b, c: WELT SP090545, Ngawi, Wairarapa; d: WELT SP090543, Stent Road, Taranaki; e: WELT SP090550, Ohau Bay, Wellington); f by J. M. Prebble (WELT SP090543, cultivated ex Stent Road, Taranaki).
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I. (Fl. Antarct.) Part I, plate 38 (Hooker 1844). Illustration by W. H. Fitch. This image is in the public domain, downloaded from the Biodiversity Heritage Library (https:// www.biodiversitylibrary.org/page/13448452#page/81/ mode/1up, accessed 8 June 2021). Draft pencil drawings for this figure are attached to the type specimen of M. antarctica (K0007878799; visible online at http:// apps.kew.org/herbcat/getImage.do?imageBarcode= K000787899, accessed 8 June 2021), which was collected by J. D. Hooker from Campbell Island.
Fig. 6 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 6. Myosotis antarctica subsp. antarctica photographs and distribution maps. (a, b) Habit. (c) Rosette leaves abaxial and adaxial sides. (d) Flower. (e) Nutlets. (f) Map of mainland New Zealand distribution based on georeferenced herbarium specimens observed by J. M. Prebble (163). (g) Map of Campbell Island distribution based on georeferenced herbarium specimens observed by J. M. Prebble (14). (h) Map of Chilean distribution based on georeferenced herbarium specimens observed by J. M. Prebble (2). White scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, c, e by J. M. Prebble (a: WELT SP102777, Mt Azimuth, Campbell Island; c: WELT SP093293, Port Hills, Canterbury, South Island E: WELT SP100466, cultivated ex Mt Peel, Western Nelson. South Island). b, d © Te Papa by H. M. Meudt (b: WELT SP106592, Matiri Range, Western Nelson, South Island; d: WELT SP107322, Mt Starveall, Western Nelson, South Island).
Fig. 3 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 3. Plots displaying (a, c) omission and commission values and (b, d) area under the receiving operating characteristic curve (AUC) for two pygmy forget-me-not taxa: (a, b) M. "Volcanic Plateau" and (c, d) M. drucei, modelled using MaxEnt and all nine environmental layers for the New Zealand extent.
Fig. 1. Maps displaying all 290 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 1. Maps displaying all 290 occurrence points used for Myosotis pygmy species group niche modelling (Supplementary Table S1). Maps, clockwise from top: World, New Zealand, Campbell Island, and southern South America. Colour represents a priori species: M. antarctica (pink circles); M. drucei (dark blue circles); M. pygmaea (green circles); M. brevis (yellow circles); M. glauca (light blue circles); M. "Volcanic Plateau" (grey triangles).
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.
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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.