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544 results for “integrated model”
Integrated experimental and techno-economic modeling of renewable natural gas production from prairie biomass
This study coupled experimental and techno-economic modeling to evaluate the economic prospects of utilizing prairie biomass as a feedstock for anaerobic digestion. Anaerobic digestion experiments were performed using 15 lab-scale bioreactors under semi-continuous operation, designed based off a box-Behnken design with three factors. Response variables included biogas and biomethane yields, in addition to numerous digestate physico-chemical characteristics. Statistical models were developed from the experimental data to predict these responses and were subsequently incorporated into a techno-economic model developed in Python using BioSTEAM. In addition to optimizing key anaerobic digestion parameters, four scenarios were evaluated investigating liquid digestate recirculation, as well as methane recovery from the liquid digestate in a two-stage anaerobic digestion process.
Integrative modeling results of in-cell architecture of an actively transcribing-translating expressome
<p>Repository containing good-scoring models, input files, modeling and analysis protocols for the integrative modeling of the M. pneumoniae expressome from in-cell cryo-electron tomography and crosslinking mass spectrometry using IMP.</p>
Supplementary data to *Benchmarking of numerical integration methods for ODE models of biological systems*
<p>This archive contains supplementary data and code for the manuscript <strong>Benchmarking of numerical integration methods for ODE models of biological systems </strong>by<strong> Städter et al. 2020</strong>. It contains</p> <ul> <li>scripts to automatically download and install all required packages and models,</li> <li>scripts to compile the models and to perform the study,</li> <li>value files containing all data underlying the analyses in the manuscript,</li> <li>scripts to generate the manuscript figures.</li> </ul> <p>There is a <strong>README.md </strong>file with further information, in particular on what scripts to execute to reproduce the study.</p>
FRIM - Fruit Integrative Modelling
<p>FRIM - Fruit Integrative Modelling</p> <p>Implementation of the FRIM Dataset for ODAM (Open Data for Access and Mining), a EDTMS (Experimental Data Table Management System).</p> <p>See https://www.slideshare.net/danieljacob771282/odam-open-data-access-and-minin for further information</p> <p>Simply unzip the ZIP file under the data repository of your local instance of the ODAM system.<br> </p> <p>(C) INRA UMR 1332 BFP - Metabolism Team - Yves Gibon - 2014</p>
Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions
<p><strong><span>Aim</span></strong></p> <p><span>Species distribution models (SDMs) that integrate presence-only and presence-absence data offer a promising avenue to improve information on species' geographic distributions. The use of such 'integrated SDMs' on a species range-wide extent has been constrained by the often-limited presence-absence data and by the heterogeneous sampling of the presence-only data. Here, we evaluate integrated SDMs for studying species ranges with a novel expert range map-based evaluation. We build a new understanding about how integrated SDMs address issues of estimation accuracy and data deficiency and thereby offer advantages over traditional SDMs.</span></p> <p><strong><span>Location</span></strong></p> <p><span>South and Central America.</span></p> <p><strong><span>Time period</span></strong></p> <p><span>1979-2017.</span></p> <p><strong><span>Major taxa studied</span></strong></p> <p><span>Hummingbirds.</span></p> <p><strong><span>Methods</span></strong></p> <p><span>We build integrated SDMs by linking two observation models – one for each data type – to the same underlying spatial process.</span> <span>We validate SDMs with two schemes: i) cross-validation with presence-absence data and ii) comparison with respect to the species' whole range as defined with IUCN range maps. We also compare models relative to the estimated response curves and compute the association between the benefit of the data integration and the number of presence records in each data set.</span></p> <p><strong><span>Results</span></strong></p> <p><span>The integrated SDM accounting for the spatially varying sampling intensity of the presence-only data was one of the top-performing models in both model validation schemes. Presence-only data alleviated overly large niche estimates, and data integration was beneficial compared to modelling solely presence-only data for species that had few presence points when predicting the species' whole range. On the community level, integrated models improved the species richness prediction.</span></p> <p><strong><span>Main conclusions</span></strong></p> <p><span>Integrated SDMs combining presence-only and presence-absence data are successfully able to borrow strengths from both data types and offer improved predictions of species' ranges. Integrated SDMs can potentially alleviate the impacts of taxonomically and geographically uneven sampling and to leverage the detailed sampling information in presence-absence data.</span></p>
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>
Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
<p><strong>Aim</strong>: Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors of range shifts, with the identification of general trends being of great interest for conservation efforts. However, studies reviewing relationships between traits and range shifts have questioned the existence of such generalized trends, due to mixed results and weak correlations, as well as analytical shortcomings. The aim of this study was to test this relationship empirically, using analytical approaches that account for common sources of bias when assessing range trends.<br><strong>Location</strong>: Tanzania, East Africa.<br><strong>Time period</strong>: 1980-1999 and 2000-2020.<br><strong>Major taxa studied</strong>: 57 savannah specialist birds found in Tanzania, belonging to 26 families and 11 orders.<br><strong>Methods</strong>: We applied recently developed integrated spatio-temporal species distribution models in R-INLA, combining citizen science and bird atlas data to estimate ranges of species, quantify range shifts, and test the predictive power of traditional trait groups, as well as exposure-related and sensitivity traits. We based our study on 40 years of bird observations in East African savannahs, a biome that has experienced increasing climatic and non-climatic pressures over recent decades. We correlated patterns of change with species traits.<br><strong>Results</strong>: We find indications of relationships identified by previous research, but low average explanatory power of traits from an ecological perspective, confirming the lack of meaningful general associations. However, our analysis finds compelling species-specific results.<br><strong>Main conclusions</strong>: We highlight the importance of individual assessments, while demonstrating the usefulness of our analytical approach for analyses of range shifts.</p>
Scripts and data for: Integrating different facets of diversity into food web models: how adaptation among and within functional groups shape ecosystem functioning
<p>Adaptation of communities to environmental fluctuations can emerge from different facets of biodiversity, which may impact ecosystem functioning differently. Previous work examined how ecosystem functions can be influenced by two sources of adaptive potential: sorting (i.e., changes in community composition due to fitness differences) can occur when multiple species or groups are present (richness), and trait adaptability (i.e., trait adjustments within species or functional groups) can emerge from genetic or phenotypic diversity. However, their effect is typically studied separately, and often in the context of only one trophic level. Therefore, we used a bitrophic trait-based model varying in richness and in the presence of trait adaptability at each trophic level, to investigate how sorting and trait adaptability, at one or two trophic levels, separately or jointly shape ecosystem functions. We found that the adaptive potential emerging from any facet of diversity-induced changes in trophic interactions, in turn, affects biomass distributions within and across trophic levels, dynamical behaviour, and synchrony of biomass dynamics within a trophic level. Particularly, sorting and trait adaptability could contribute to a similar degree and at a similar time to temporal changes in ecosystem functions, but their respective contribution depended on the speed of trait adaptation, the trait range between similar functional groups, and trophic interactions. We thus suggest to consider multiple facets of diversity and their corresponding sources of adaptive potential to deepen our mechanistic understanding of ecosystem functioning, especially in a context of rapid biodiversity change.</p>
Data for fitting a statistical global burned area model for seamless integration into Dynamic Global Vegetation Models
<p>The dataset is a large R data.table object saved in RDS format. It contains global, monthly data spanning the period from 2002 to 2018, with a 0.5 degrees spatial resolution. The dataset is utilized to develop and validate statistical models for predicting global burnt areas resulting from wildfires.</p>
Dataset for Integrated Species Distribution Model for pikeperch larvae in the Porvoo-Sipoo archipelago
<p>This record contains the data required to run the code for fitting the Integrated Species Distribution Model described in <a href="https://arxiv.org/abs/2206.08817">arXiv:2206.08817 [stat.ME].</a></p> <h1>Files in this record</h1> <ul> <li><strong>transect_data.csv</strong> Line transect observations from Porvoo-Sipoo archipelago, Finland on June 2017.</li> <li><strong>expert_assessments.tif</strong> Rasterized, anonymous expert assessments. Categorical values denoting how likely a given location is to be a spawning location for pikeperch. 4 categories, with smaller values corresponding to higher probabilities.</li> <li><strong>covariate_raster_example.tif</strong> Rasterized example environmental covariate values. These are similarly structured as the covariate data used in the study and compatible with the analysis code. However, since we do not have the permission to release the original data set, these values are instead generated based on the projected planar coordinates such that they have roughly similar spatial gradients as the original covariates.</li> </ul> <h1>Detailed descriptions</h1> <h2>Transect data</h2> <h3>Location and replicate identifiers</h3> <ul> <li> <p><strong>id</strong> : transect identifier. Replicates of the same transect have the same identifier.</p> </li> <li> <p><strong>id2</strong> : alternate transect identifier, unique for each transect.</p> </li> <li> <p><strong>repeated</strong> : whether transect was replicated or not.</p> </li> <li> <p><strong>X_euref</strong> : easting coordinate, EUREF_FIN_TM35FIN, for the transect starting location in [meters]</p> </li> <li> <p><strong>Y_euref</strong> : northing coordinate, EUREF_FIN_TM35FIN, for the transect starting location in [meters]</p> </li> <li><strong>date</strong> : date of the measurement, DD/MM/YYYY</li> <li><strong>week</strong> : week number of the measurement date</li> </ul> <h3>In situ measurements</h3> <ul> <li> <p><strong>volume</strong> : Transect water volume [m^3]. Transect length (500m) multiplied by sampler surface area. Used as survey effort.</p> </li> <li> <p><strong>heading</strong> : compass heading (direction) for the transect, in [degrees].</p> </li> <li> <p><strong>SumKUHA</strong> : total pikeperch (<em>Sander lucioperca</em>, kuha in Finnish) larvae count in each transect [scalar]</p> </li> </ul> <h2>Expert assessments</h2> <p>The raster contains assessments from 10 local experts encoded as separate raster layers (Expert_1, Expert_2, ..., Expert_10). Raster resolution is 50m x 50m and the planar coordinates are based on the same coordinate reference system as the transect observations (UTM zone 35).</p> <p>The assessments are coded as integers with values between 1 and 4, with smaller values corresponding to higher probabilities.</p> <h2>Covariate raster example</h2> <p>This raster has the same spatial dimensions and uses the same coordinate reference system as the expert assessment raster and has three layers, one for each covariate. The covariate values are generated based on the spatial coordinates such that each covariate has similar spatial gradient as the original covariate. The covarites have the same names as in the original covariate data (<strong>dptLUKE</strong>, <strong>dist10m</strong> and <strong>lined3km</strong>).</p> <h1>Creators</h1> <p>Transect data collected and curated by Sanna Kuningas.</p> <p>Original covariate rasters curated by Sanna Kuningas from data sets collected by the Finnish Environment Institute and the Natural Resources Institute Finland.</p> <p>Expert assessments originally digitized and rasterized by Jussi Mäkinen. Additional refinement to assessment rasters by Karel Kaurila.</p> <p>Preparation for publishing on Zenodo for all of the data sets by Karel Kaurila.</p> <h2>Change log</h2> <ul> <li> 2025 Jan 31: Included columns <strong>date</strong> and <strong>week</strong> for <strong>transect_data.csv</strong>.</li> </ul>
Resource Description Framework (RDF) Modeling of Named Entity Co-occurrences in Biomedical Literature and Its Integration with PubChemRDF
<p>This Zenodo record contains the co-occurrence RDF data generated in the work described in the paper “<strong>A resource description framework (RDF) model of named entity co-occurrences in biomedical literature and its integration with PubChemRDF</strong>” by Li et al., published in the Journal of Cheminformatics (<a href="https://doi.org/10.1186/s13321-025-01017-0" target="_blank" rel="noopener">https://doi.org/10.1186/s13321-025-01017-0</a>). It also contains the SPARQL query examples, the RDF schema in SHACL and ShEx, and the validation scripts.</p> <p>All content in this Zenodo record is for archival purposes. The latest version of the co-occurrence RDF data and other PubChemRDF data can be accessed via the PubChem FTP site (<a href="https://ftp.ncbi.nlm.nih.gov/pubchem/RDF/" target="_blank" rel="noopener">https://ftp.ncbi.nlm.nih.gov/pubchem/RDF/</a>). The up-to-date RDF schema in various formats is available on the PubChemRDF Schema page (<a href="https://pubchem.ncbi.nlm.nih.gov/docs/rdf-schema" target="_blank" rel="noopener">https://pubchem.ncbi.nlm.nih.gov/docs/rdf-schema</a>). A set of SPARQL query examples can be found on the PubChemRDF use case pages (<a href="https://pubchem.ncbi.nlm.nih.gov/docs/rdf-use-cases" target="_blank" rel="noopener">https://pubchem.ncbi.nlm.nih.gov/docs/rdf-use-cases</a>).</p>
Data from: Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management
<p><span>1. Species' ranges are changing at accelerating rates. Species distribution models (SDMs) are powerful tools that help rangers and decision-makers prepare for reintroductions, range shifts, reductions, and/or expansions by predicting habitat suitability across landscapes. Yet, range-expanding or -shifting species in particular face other challenges that traditional SDM procedures cannot quantify, due to large differences between a species' currently-occupied range and potential future range. The realism of SDMs is thus lost and not as useful for conservation management in practice. Here, we address these challenges with an extended assessment of habitat suitability through an <i>integrated SDM database (iSDMdb)</i>.</span></p> <p><span>2. The<i> iSDMdb</i> is a spatial database of predicted sites in a species' prediction range, derived from SDM results, and is a single spatial feature that contains additional, user-friendly data fields that synthesise and summarise SDM predictions and uncertainty, human impacts, restoration features, novel preferences in novel spaces, and management priorities. To illustrate its utility<i>,</i> we used the endangered New Zealand sea lion (<i>Phocarctos hookeri</i>). We consulted with wildlife rangers, decision-makers, and sea lion experts to supplement SDM predictions with additional, more realistic, and applicable information for management. </span></p> <p><span>3. Almost half the data fields included in this database resulted from engaging with these end-users during our study. The SDM found 395 predicted sites. However, the <i>iSDMdb</i>'s additional assessments showed that the actual suitability of most sites (90%) was questionable due to human impacts. >50% of sites contained unnatural barriers (fences, grazing grasslands), and 75% of sites had roads located within the species' range of inland movement. Just 5% of the predicted sites were mostly (>80%) protected.</span></p> <p><span>4. Integrating SDM results with supplemental assessments provides a way to address SDM limitations, especially for range-expanding or -shifting species. SDM products for conservation applications have been critiqued for lacking transparency and interpretation support, and ineffectively communicating uncertainty. The <i>iSDMdb</i> addresses these issues and enhances the practical relevance and utility of SDMs for stakeholders, rangers, and decision-makers. We exemplify how to build an <i>iSDMdb</i> using open-source tools, and how to make diverse, complex assessments more accessible for end-users.</span></p>
Research compendium for 'The contribution of integrated 3D model analysis to Protoaurignacian stone tool design'
<p><strong>Abstract:</strong> Protoaurignacian foragers relied heavily on the production and use of bladelets. Techno-typological studies of these implements have provided insights into important aspects of cultural variability. However, new technologies have seldom been used to quantify patterns of stone tool design. Taking advantage of a new scanning protocol and open-source software, we conduct the first 3D analysis of a Protoaurignacian assemblage, focusing on the selection and modification of blades and bladelets. We study a large sample of complete blanks and retouched tools from the early Protoaurignacian assemblage at Fumane Cave in northeastern Italy. Our main goal is to validate and refine previous techno-typological considerations employing a 3D geometric morphometrics approach complemented by 2D analysis of cross-section outlines and computations of retouch angle. The encouraging results show the merits of the proposed integrated approach and confirm that bladelets were the main focus of stone knapping at the site. Among modified bladelets, various retouching techniques were applied to achieve specific shape objectives. We suggest that the variability observed among retouched bladelets relates to the design of multi-part artifacts that need to be further explored via renewed experimental and functional studies.</p> <p><strong>Overview of contents:</strong></p> <p>01. AGMT3-D project of the first dataset used in the study;</p> <p>02. AGMT3-D project of the second dataset used in the study;</p> <p>03. Raw outline data of the middle cross-section. Each specimens has a dedicate .txt file;</p> <p>04. Raw outline data of the upper cross-section. Each specimens has a dedicate .txt file;</p> <p>05. Angles3-D project with all files generated by the software (.mat and .xlsx formats) to quantify the mean retouch angle of retouched bladelets;</p> <p>06. R project and scripts for the 1) 2D shape analysis of the middle and upper cross-sections of retouched bladelets and the 2) design of all bivariate plots and boxplots with jittered points used in the paper. All related datasets, principal components, and generated figures are included in the folder;</p> <p>07. Folder with all figures published in the paper and in its supplementary materials;</p> <p>08. Dataset of the first study in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>09. Dataset of the second study in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>10. Dataset for the study of the upper cross-sections in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>11. Dataset for the study of the middle cross-sections in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>12. Dataset in .csv used to study the mean retouch angles;</p> <p>13. Supplementary information file in .pdf with all supplementary figures and tables.</p> <p><strong>Extra</strong>: All 3D meshes of blades and bladelets are available on Zenodo following this link: https://doi.org/10.5281/zenodo.6362150.</p>
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>
Integral projection model results of the planktonic foraminifer Trilobatus sacculifer
<p>Developmental plasticity, where traits change state in response to environmental cues, is well-studied in modern populations. It is also suspected to play a role in macroevolutionary dynamics, but due to a lack of long-term records the frequency of plasticity-led evolution in deep time remains unknown. Populations are dynamic entities, yet their representation in the fossil record is a static snapshot of often isolated individuals. Here, we apply for the first time contemporary integral projection models (IPMs) to fossil data to link individual development with expected population variation. IPMs describe the effects of individual growth in discrete steps on long-term population dynamics. We parameterize the models using modern and fossil data of the planktonic foraminifer <em>Trilobatus sacculifer</em>. Foraminifera grow by adding chambers in discrete stages and die at reproduction, making them excellent case studies for IPMs. Our results predict that somatic growth rates have almost twice as much influence on population dynamics than survival and more than eight times more influence than reproduction, suggesting that selection would primarily target somatic growth as the major determinant of fitness. As numerous palaeobiological systems record growth rate increments in single genetic individuals, and imaging technologies are increasingly available, our results open up the possibility of evidence-based inference of developmental plasticity spanning macroevolutionary dynamics. Given the centrality of ecology in palaeobiological thinking, our model is one approach to help bridge eco-evolutionary scales while directing attention towards the most relevant life-history traits to measure.</p>
Dataset for Integrated hydrodynamic and machine learning models
<p>The dataset is the supplement to our publication in <a href="https://www.nonlinear-processes-in-geophysics.net/">Nonlinear Processes in Geophysics</a> (https://doi.org/10.5194/npg-2021-36). To use this data, please give us credit by citing our article.</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>
Integrated Machine Learning model in Early Urban Flooding Warning System - Data
<p>AI_DATA.npy - Inundation data (mm) generated from MIKE+ model that has been converted to numpy array</p> <p>INDEX.npy - The index where inundation is > 0 </p> <p>source.tif - Source tif image for creating map from ML models</p>
FCH and FS Datasets for the paper "Integrating Multi-Source Remote Sensing Data for Mapping Boreal Forest Canopy Height and Species in interior Alaska in Support of Radar Modeling"
<p>This dataset provides forest canopy height and forest species in Delta Junction, interior Alaska in 2017. This dataset was produced based on the multi-source remote sensing datasets (AirMOSS, UAVSAR, Sentinel-1, Sentinel-2, topography), using a XGBoost approach.</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.