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102 results for “Data Model comparison”
Data from: Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches
PLEASE NOTE, THESE DATA ARE ALSO REFERRED TO IN TWO OTHER PUBLICATIONS. PLEASE SEE http://dx.doi.org/10.1111/j.1365-2486.2008.01766.x AND http://dx.doi.org/10.1111/2041-210X.12222 FOR MORE INFORMATION. Aim: This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location: Two study areas in the Alps of Switzerland. Methods: We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results: The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient. Main conclusions: Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.
Data from: Comparison of solar-induced chlorophyll fluorescence, light-use efficiency, and process-based GPP models in maize
Accurately quantifying cropland gross primary production (GPP) is of great importance to monitor cropland status and carbon budgets. Satellite-based light-use efficiency (LUE) models and process-based terrestrial biosphere models (TBMs) have been widely used to quantify cropland GPP at different scales in past decades. However, model estimates of GPP are still subject to large uncertainties, especially for croplands. More recently, space-borne solar-induced chlorophyll fluorescence (SIF) has shown the ability to monitor photosynthesis from space, providing new insights into actual photosynthesis monitoring. In this study, we examined the potential of SIF data to describe maize phenology and evaluated three GPP modeling approaches (space-borne SIF retrievals, a LUE-based Vegetation Photosynthesis Model (VPM), and a process-based Soil Canopy Observation of Photochemistry and Energy flux (SCOPE) model constrained by SIF) at a maize (Zea mays L.) site in Mead, Nebraska, USA. The result shows that SIF captured the seasonal variations (particularly during the early and late growing season) of tower-derived GPP (GPP_EC) much better than did satellite-based vegetation indices (enhanced vegetation index, EVI and land surface water index, LSWI). Consequently, SIF was strongly correlated with GPP_EC than were EVI and LSWI. Evaluation of GPP estimates against GPP_EC during the growing season demonstrated that all three modeling approaches provided reasonable estimates of maize GPP, with Pearson's correlation coefficients (r) of 0.97, 0.94, and 0.93 for the SCOPE, VPM, and SIF models, respectively. The SCOPE model provided the best simulation of maize GPP when SIF observations were incorporated through optimizing the key parameter of maximum carboxylation capacity (Vcmax). Our results illustrate the potential of SIF data to offer an additional way to investigate the seasonality of photosynthetic activity, to constrain process-based models for improving GPP estimates, and to reasonably estimate GPP by integrating SIF and GPP_EC data without dependency on climate inputs and satellite-based vegetation indices.
Data from: Model-based comparisons of phylogeographic scenarios resolve the intraspecific divergence of cactophilic Drosophila mojavensis
The cactophilic fly Drosophila mojavensis exhibits considerable intraspecific genetic structure across allopatric geographic regions and shows associations with different host cactus species across its range. The divergence between these populations has been studied for more than 60 years, yet their exact historical relationships have not been resolved. We analysed sequence data from 15 intronic X-linked loci across populations from Baja California, mainland Sonora-Arizona and Mojave Desert regions under an isolation-with-migration model to assess multiple scenarios of divergence. We also compared the results with a pre-existing sequence dataset of 8 autosomal loci. We derived a population tree with Baja California placed at its base and link their isolation to Pleistocene climatic oscillations. Our estimates suggest the Baja California population diverged from an ancestral Mojave Desert/mainland Sonora-Arizona group around 230-270 Kya, while the split between the Mojave Desert and mainland Sonora-Arizona populations occurred one glacial cycle later, 117-135 Kya years ago. Although we found these three populations to be effectively allopatric, model ranking could not rule out the possibility of a low-level of gene flow between two of them. Finally, the Mojave Desert population showed a small effective population size, consistent with a historical population bottleneck. We show that model-based inference from multiple loci can provide accurate information on the historical relationships of closely related groups allowing us to set into historical context a classic system of incipient ecological speciation.
Data from: Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits
Tree allometric relationships are widely employed for estimating forest biomass and production and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to capture changes in scaling during ontogeny and physical limits to maximum tree size and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter for 162 species from the Barro Colorado Nature Monument, Panama. We fit nonlinear, hierarchical models informed by species traits – wood density, mean sapling growth, or sapling mortality – and assessed the performance of three alternative functional forms: the scale-invariant power function and the saturating Weibull and generalized Michaelis–Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach for improving estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical plant functional types in vegetation models.
Data from: Phylogeographic inference using Bayesian model comparison across a fragmented chorus frog species complex
Fragmented species complexes provide an interesting system for investigating biogeographic history and the present distribution of genetic variation. Recent advances in sequencing technology and statistical phylogeography enable the collection and rigorous analysis of large multilocus data sets, but designing studies that produce meaningful phylogeographic inferences remains challenging. We implemented a Bayesian model comparison approach to investigate previous biogeographic hypotheses while simultaneously inferring the presence of genetic structure in a chorus frog species complex. The Illinois chorus frog (Pseudacris illinoensis), originally described as a subspecies of the broadly distributed Strecker's chorus frog (Pseudacris streckeri), occurs in small, disjunct regions associated with scarce sand prairie habitats that have been impacted by human development. We used high-throughput sequencing to develop and collect a multitiered genetic data set comprised of three different marker types (23 anonymous nuclear sequence loci, four mitochondrial genes and 14 microsatellite loci) designed to address questions across different evolutionary timescales. Phylogenetic analyses uncovered a deep divergence between populations in the Edwards Plateau of central Texas and all other P. streckeri/P. illinoensis populations, but suggest the disjunct distribution of P. illinoensis occurred more recently. Our best-supported migration model is consistent with the hypothesis that central Texas represented a refugium from which populations expanded via multiple routes. This model also indicates that disjunct northern and southern regions of P. illinoensis should be considered genetically distinct management units. Our study provides an evolutionary context for future studies and conservation efforts in P. illinoensis and demonstrates the utility of model-based approaches for phylogeographic inference.
Data from: Prospective comparison of two models of integrating early infant male circumcision with maternal child health services in Kenya: the Mtoto Msafi Mbili Study
As countries scale up adult voluntary medical male circumcision (VMMC) for HIV prevention, they are looking ahead to long term sustainable strategies, including introduction of early infant male circumcision (EIMC). To address the lack of evidence regarding introduction of EIMC services in sub-Saharan African settings, we conducted a simultaneous, prospective comparison of two models of EIMC service delivery in Homa Bay County, Kenya. In one division a standard delivery package (SDP) was introduced and included health facility-based provision of EIMC services with community engagement for client referral versus in a different division a standard package plus (SDPplus) that included community-delivered EIMC services. Babies 1–60 days old were eligible for EIMC. A representative sample of mothers and fathers of baby boys at 16 health facilities was surveyed. We examined differences between mothers and fathers in the SDP and SDPplus divisions and identified factors associated with EIMC uptake. We report adjusted prevalence ratios (aPR). Of 1660 mothers interviewed, 1501 (89%) gave approval to contact the father, and 1259 fathers (84%) were interviewed. The proportion of babies circumcised was slightly greater in the SDPplus division than the SDP division (27.3% vs 23.7%), but the difference was not significant (p = 0.08). In adjusted analyses, however, the prevalence of babies being circumcised was greater in the SDPplus division (aPR = 1.23, 95% CI:1.04–1.45) and the factors associated with a baby being circumcised were the mother having received information about EIMC (during pregnancy, aPR = 4.81, 95% CI: 2.21–3.42), having discussed circumcision with the father if married or cohabiting (aPR = 5.39, 95% CI: 3.31–8.80) or being single (aPR = 5.67, 95% CI: 3.31–9.69), perceiving herself to be living with HIV (aPR = 1.39, 95% CI: 1.15–1.67), or having a post-secondary education (aPR = 1.33, 95% CI: 1.04–1.69), and the father being Muslim (aPR = 1.85, 95% CI: 1.29–2.65) or circumcised (aPR = 1.34, 95% CI: 1.13–1.59). The median age of 2117 babies circumcised was 8 days (IQR: 1–36), and the median weight was 3.6 kg (IQR: 3.2–4.4). There were 6 moderate adverse events (AEs) (0.28%); 5 severe AEs (0.24%), all involving an injury to the glans penis, requiring hospitalization and corrective surgery; and one death probably related to the procedure. There were no AEs among the 365 procedures performed outside health facilities. Information and education campaigns must reach members of the general population, especially men and fathers, who are influential to the EIMC decision. Serious AEs using the Mogen clamp are rare, but do occur and require efficient, reliable emergency back-up. Our results can assist countries considering scale-up of EIMC services for HIV prevention as their adult VMMC programs mature.
Data from: Controlled comparison of species- and community-level models across novel climates and communities
Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa.
Data from: A rapid and scalable method for multilocus species delimitation using Bayesian model comparison and rooted triplets
Multilocus sequence data provide far greater power to resolve species limits than the single locus data typically used for broad surveys of clades. However, current statistical methods based on a multispecies coalescent framework are computationally demanding, because of the number of possible delimitations that must be compared and time-consuming likelihood calculations. New methods are therefore needed to open up the power of multilocus approaches to larger systematic surveys. Here, we present a rapid and scalable method that introduces 2 new innovations. First, the method reduces the complexity of likelihood calculations by decomposing the tree into rooted triplets. The distribution of topologies for a triplet across multiple loci has a uniform trinomial distribution when the 3 individuals belong to the same species, but a skewed distribution if they belong to separate species with a form that is specified by the multispecies coalescent. A Bayesian model comparison framework was developed and the best delimitation found by comparing the product of posterior probabilities of all triplets. The second innovation is a new dynamic programming algorithm for finding the optimum delimitation from all those compatible with a guide tree by successively analyzing subtrees defined by each node. This algorithm removes the need for heuristic searches used by current methods, and guarantees that the best solution is found and potentially could be used in other systematic applications. We assessed the performance of the method with simulated, published, and newly generated data. Analyses of simulated data demonstrate that the combined method has favorable statistical properties and scalability with increasing sample sizes. Analyses of empirical data from both eukaryotes and prokaryotes demonstrate its potential for delimiting species in real cases.
Data from: A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods
Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3–40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31–0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04–0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.
Data for: The Precipitation Response to Warming and CO2 Increase: A Comparison of a Global Storm Resolving Model and CMIP6 Models
<p>Data to reproduce figures in manuscript "The Precipitation Response to Warming and CO$_2$ Increase: A Comparison of a Global Storm Resolving Model and CMIP6 Models" submitted to GRL</p>
MD data for the article "Structure comparison of beta amyloid peptide Aβ 1-42 isoforms. Molecular dynamics modeling" by Anna P. Tolstova, Alexander A. Makarov, Alexei A. Adzhubei.
<p>There are CMD and REMD trajectories for Aβ isoforms discussed in the paper together with final coordinate files for these trajectories. The resulting dataset of modeled structures includes wild type Aβ42, isoD7, pS8, D7H and H6R-Aβ42, and wild type Aβ16, isoD7, pS8, D7H and H6R-Aβ16.</p>
Master Thesis- Modeling of Electric Vehicle Charging Infrastructure and Comparison of Electric Vehicle Load Simulation with Empirical Charging Data
<p>All the data behind relevant plots in the thesis report are stored here</p>
Model data and namelists for Sterzinger et al. (2022) - "Do arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulations"
<p>Model data and namelists for "<a href="https://acp.copernicus.org/preprints/acp-2022-36/">Do arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulations</a>"</p> <p>Horizontally averaged data is provided in NetCDF4 files (oliktok.nc, ascos.nc, summit.nc) for all output variables. Horizontally averaged vertical momentum flux is provided in a separate file for each simulation (*_vert_momentum_flux.nc files).</p> <p>Info on variables is provided by the RAMS model variable guide PDF <a href="https://vandenheever.atmos.colostate.edu/vdhpage/rams/docs/RAMS-VariableList.pdf">available here</a>.</p> <p>Model namelists are provided for each simulation (*_RAMSIN files). ASCOS initialization sounding info is provided within the ASCOS_RAMSIN file - initialization soundings are provided in SOUND_IN files.</p>
Data for "Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison"
<p>All data recorded for reflectance and e-folding depth measurements associated with "Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison"</p>
Data for Streamflow Prediction: Comparison of SWAT vs. Random Forest Models in Diverse Catchments
<p>This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time series prediction across diverse catchments, and compares its results against SWAT predictions. We found strong evidence of RF's better performance by adding historical flows and time-lags for meteorological values over using only actual meteorological values. On a daily scale, RF demonstrated robust performance (Nash–Sutcliffe efficiency [<em>NSE</em>] > 0.5), whereas SWAT generally yielded unsatisfactory results (<em>NSE</em> < 0.5) and tended to overestimate daily streamflow by up to 27% (<em>PBIAS</em>). However, SWAT provided better monthly predictions, particularly in catchments with irregular flow patterns. Although both models faced challenges in predicting peak flows in snow-influenced catchments, RF outperformed SWAT in an arid catchment. RF also exhibited a notable advantage over SWAT in terms of computational efficiency. Overall, RF is a good choice for daily predictions with limited data, whereas SWAT is preferable for monthly predictions and understanding hydrological processes in depth.</p> <p>This repository contains the input data used for building the RF and SWAT models and the files describing the modeling results.</p> <p>The corresponding Zenodo code repository is available at <a href="../doi/10.5281/zenodo.11064973" target="_blank" rel="noopener">https://zenodo.org/doi/10.5281/zenodo.11064973</a>.</p>
Data for "SPH modelling of AGB wind morphology in hierarchical triple systems & comparison to observation of R Aql"
<div> <p>Additional material to Malfait et al. 2024, subm. "SPH modelling of AGB wind morphology in hierarchical triple systems & comparison to observation of R Aql"</p> <p>This contains input files and final output dumps of the Phantom simulations of this paper.</p> <p>The code used to perform the simulations is available at: <a href="https://github.com/danieljprice/phantom">https://github.com/danieljprice/phantom.</a></p> <p>Splash (<a href="https://github.com/danieljprice/splash">https://github.com/danieljprice/splash</a> ) and Plons (<a href="https://github.com/Ensor-code/plons">https://github.com/Ensor-code/plons</a> ) were used to create figures and plots from this data.</p> <p> </p> </div>
A model-data comparison of the hydrological response to Miocene warmth: leveraging the MioMIP1 opportunistic multi-model ensemble
<p>Supporting information for manuscript titled "A model-data comparison of the hydrological response to Miocene warmth: leveraging the MioMIP1 opportunistic multi-model ensemble"</p><p>Datasets S1. Early to Middle Miocene NetCDF files: E2MMIO280.nc, E2MMIO400.nc, E2MMIO560.nc, E2MMIO850.nc contains MioMIP1 climate variables used to make manuscript figures. </p><p>Datasets S2 Middle to Late Miocene NetCDF files: M2LMIO280.nc, M2LMIO400.nc, M2LMIO560.nc contains MioMIP1 climate variables used to make manuscript figures. </p><p>Datasets S3 Preindustrial NetCDF files: PI contains MioMIP1 climate variables used to make manuscript figures.</p><p>Dataset S4 CSV file MioMIP_MAP_compilation contains newly revised miocene reconstructed mean annual precipitation from proxies. </p>
Data from: Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: a comparison with traditional destructive approach
Open the record for dataset details and reuse information.
Data from: Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches
Open the record for dataset details and reuse information.
Data from: A rapid and scalable method for multilocus species delimitation using Bayesian model comparison and rooted triplets
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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.