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108 results for “spatial assessment”

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zenodo36/100

Spatial slip rate distribution along the SE Xianshuihe fault, eastern Tibet, and earthquake hazard assessment

<p><strong><em>Table 2:&nbsp;</em></strong><em><sup>10</sup></em><em>Be surface-exposure ages of Zheduotang (ZDT) and Moxi (MX) sites of the SE Xianshuihe fault.</em></p>

opencc-by-4.0Jul 2021View details →
zenodo36/100

A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture

<p><strong>Abstract:</strong></p> <p>(from [1])</p> <blockquote> <p>For the smeared approximation of a discrete crack, phase-field fracture simulations of brittle materials require suitable finite element meshes in regions where crack propagation is expected to get an accurate resolution of the phase-field function. The intuitive option is to pre-refine the mesh in regions of the expected crack paths. However, this could lead to very computationally intensive simulations due to the high number of elements. Alternatively, adaptive spatial refinement of the finite element mesh is utilized based on appropriate error indicators to obtain the required accuracy in the areas of crack propagation. Different error indicators can be used: the most common one for phase-field fracture simulations is the threshold-based approach, in which elements are refined depending on the value of the phase-field function. Alternatively, the Kelly error indicator can be used as a criterion for spatial adaptivity. It considers the jumps in the gradients of the phase-field function between the elements. We additionally introduce here an error indicator based on configurational forces, that depend on the Eshelby stress tensor. For mode I loading in linear elastic fracture mechanics, the configurational forces have a close connection to the <span class="math-tex">\(\mathscr{J}\)</span>-Integral and the critical fracture energy <span class="math-tex">\(\mathrm{G}_\mathrm{c}\)</span> , respectively. Therefore, a suitable norm of the configurational forces is introduced as an error indicator here. These three error indicators are introduced and compared to each other in terms of accuracy and efficiency by means of numerical examples for crack growth in the single edge notched shear test.</p> </blockquote> <p><strong>Contact:</strong></p> <p>Maurice Rohracker</p> <p>Institute of Applied Mechanics</p> <p>Friedrich-Alexander-Universit&auml;t Erlangen-N&uuml;rnberg</p> <p>Egerlandstr. 5</p> <p>91058 Erlangen</p> <p><strong>Software:</strong></p> <p>All phase-field fracture simulations were performed with <em>deal.II</em> [2], version 9.2.0, on the HPC cluster <em>Meggie</em> of NHR@FAU. The authors gratefully acknowledge the scientific support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universit&auml;t Erlangen-N&uuml;rnberg (FAU). The hardware is funded by the German Research Foundation (DFG).</p> <p><strong>License:</strong></p> <p>Creative Commons Attribution 4.0 International</p> <p><strong>Context:</strong></p> <p>Dataset supplementing preprint:</p> <p>[1] M.Rohracker, P.Kumar, J.Mergheim, &quot;A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture&quot;,&nbsp;Forces in Mechanics, 2022, <a href="https://doi.org/10.1016/j.finmec.2022.100157">10.1016/j.finmec.2022.100157</a>.</p> <p>This dataset contains the complete results presented in [1], which include global variables, field variables, and meshes.</p> <p><strong>File structure:</strong></p> <p>The file structure is explained in more detail in the shipped <em>README.md</em> in the dataset folder.</p> <p><strong>References:</strong></p> <p>[1] M.Rohracker, P.Kumar, J.Mergheim, &quot;A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture&quot;, Forces in Mechanics, 2022, <a href="https://doi.org/10.1016/j.finmec.2022.100157">10.1016/j.finmec.2022.100157</a>.</p> <p>[2] D. Arndt, W. Bangerth, B. Blais, T. C. Clevenger, M. Fehling, A. V. Grayver, T. Heister, L. Heltai, M. Kronbichler, M. Maier, P. Munch, J.-P. Pelteret, R. Rastak, I. Thomas, B. Turcksin, Z. Wang, D. Wells, <strong>The deal.II Library, Version 9.2</strong> Journal of Numerical Mathematics, vol. 28, p. 131-146, 2020.</p>

opencc-by-4.0Dec 2022View details →
dryad36/100

Data from a flexible framework to assess patterns and drivers of beta diversity across spatial scales

Open the record for dataset details and reuse information.

publicNov 2023View details →
dryad36/100

Data from: A genomic assessment of population structure and gene flow in an aquatic salamander identifies the roles of spatial scale, barriers, and river architecture

Open the record for dataset details and reuse information.

publicFeb 2019View details →
dryad36/100

Data from: Bringing multivariate support to multiscale codependence analysis: assessing the drivers of community structure across spatial scales

Open the record for dataset details and reuse information.

publicAug 2018View details →
dryad36/100

Comparative Spatial Paleoecology: Assessing Niche Competition between Eocene North American Multituberculates and Rodents Regarding Forest Resources to Elucidate the Cause of Multituberculate Extinction

Open the record for dataset details and reuse information.

publicJan 2025View details →
dryad36/100

Data from: Assessing spatial patterns of soil erosion in a high‐latitude rangeland

Open the record for dataset details and reuse information.

publicMar 2020View details →
dryad32/100

Combining seascape connectivity with cumulative impact assessment in support of ecosystem-based marine spatial planning

<p>1. Cumulative impact assessment (CIA) is a promising approach to guide marine spatial planning (MSP) and management. One limitation of CIA is the neglect of seascape connectivity, which may spread the impact of localised pressures to ambient areas, e.g. through lost dispersal and recruitment of organisms.</p> <p>2. We here, for the first time, incorporate seascape connectivity into a traditional CIA model using a connectivity matrix, exemplified by dispersal of propagules estimated through biophysical modelling. Two <i>connectivity impacts</i>are identified: the <i>source impact</i> represents downstream areas losing recruits because of reduced larval dispersal from sites affected by the pressure, and the <i>sink impact</i> represents loss of recruits originating from upstream areas prevented from settlement in the site affected by the local pressure.</p> <p>3. By including seascape connectivity into the Swedish MSP-guiding CIA tool Symphony we demonstrate how to practically account for remote effects of local environmental impact. Our example on blue mussel shows how reducing mussel fitness in a given area may have impacts on mussels far from the acting pressures. Overall, results indicate that connectivity impact for blue mussels plays a minor role in most areas, less than 10% of the ordinary cumulative impact. However, in some smaller areas, e.g. on offshore banks and the Danish Straits, seascape connectivity may increase ordinary cumulative impact with 20-30%. In an example of scenario-based CIA analyses of MSP projections, we demonstrate how impacts of particular management actions, e.g. shipping rerouting and wind power developments, can be tracked far from the original area of influence.</p> <p>4. Depending on the dispersal ability of ecosystem components, a local pressure may impact a considerable area through seascape connectivity, transgressing management units and national borders. Although the mean connectivity impact may be modest for a single ecosystem component, the consideration of seascape connectivity across multiple ecosystem components may significantly alter the mapping of cumulative impact and the assessment of different MSP scenarios.</p> <p>5. Synthesis and applications.<span><span><span><span><span><span><span><span><span><span><span> Our extension of Cumulative Impact Assessment offers a new method for mapping and practically integrating seascape connectivity with ecosystem-based MSP and other spatial instruments for policy making, such as marine protected areas.</span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroNov 2020View details →
zenodo32/100

Bibliometric assessment of marine spatial planning publications (2003-2019)

<p>Dataset of marine spatial planning (MSP) publications for the period 2003 -&nbsp;2019.</p>

opencc-by-4.0Dec 2020View details →
dryad32/100

Data from: Genetic assessment of population structure and connectivity in the threatened Mediterranean coral Astroides calycularis (Scleractinia, Dendrophylliidae) at different spatial scales

Understanding dispersal patterns, population structure and connectivity among populations is helpful in the management and conservation of threatened species. Molecular markers are useful tools as indirect estimators of these characteristics. In this study we assess the population genetic structure of the endemic Mediterranean coral Astroides calycularis in the Alboran Sea at local and regional scales, and at three localities outside of this basin. Bayesian clustering methods, traditional F-statistics and Dest statistics were used to determine the patterns of genetic structure. Likelihood and coalescence approaches were used to infer migration patterns and effective population sizes. The results obtained reveal a high level of connectivity among localities separated by as much as one kilometer and moderate levels of genetic differentiation among more distant localities, somewhat corresponding with a stepping-stone model of gene flow and connectivity. These data suggest that connectivity among populations of this coral is mainly driven by the biology of the species, with low dispersal abilities; in addition, hydrodynamic processes, oceanographic fronts and the distribution of rocky substrate along the coastline may influence larval dispersal.

opencc-zeroDec 2011View details →
dryad32/100

Data from: Spatial representativeness of environmental DNA metabarcoding signal for fish biodiversity assessment in a natural freshwater system

In the last few years, the study of environmental DNA (eDNA) has drawn attention for many reasons, including its advantages for monitoring and conservation purposes. So far, in aquatic environments, most of eDNA research has focused on the detection of single species using species-specific markers. Recently, species inventories based on the analysis of a single generalist marker targeting a larger taxonomic group (eDNA metabarcoding) have proven useful for bony fish and amphibian biodiversity surveys. This approach involves in situ filtering of large volumes of water followed by amplification and sequencing of a short discriminative fragment from the 12S rDNA mitochondrial gene. In this study, we went one step further by investigating the spatial representativeness (i.e. ecological reliability and signal variability in space) of eDNA metabarcoding for large-scale fish biodiversity assessment in a freshwater system including lentic and lotic environments. We tested the ability of this approach to characterize large-scale organization of fish communities along a longitudinal gradient, from a lake to the outflowing river. First, our results confirm that eDNA metabarcoding is more efficient than a single traditional sampling campaign to detect species presence, especially in rivers. Second, the species list obtained using this approach is comparable to the one obtained when cumulating all traditional sampling sessions since 1995 and 1988 for the lake and the river, respectively. In conclusion, eDNA metabarcoding gives a faithful description of local fish biodiversity in the study system, more specifically within a range of a few kilometers along the river in our study conditions, i.e. longer than a traditional fish sampling site.

opencc-zeroDec 2015View details →
dryad32/100

Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.

opencc-zeroDec 2012View details →
zenodo32/100

FIGURE 1 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

FIGURE 1. General Niche-Environment System Factor Analysis (GNESFA) and Factor Analysis of the Niche, Taking the Environment as the Reference (FANTER) for Pristidactylus species. Left column: grey points show the distribution of the RUs (here the pixels) on the axes found by the analysis and black points correspond to the RUs used by the species. Right column: correlations between the environmental variables and the axes. References: P. achalensis A–B; P. nigroiugulus C–D.

opennotspecifiedDec 2017View details →
zenodo32/100

FIGURE 5 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

FIGURE 5. Area models for suitability habitat from the averaged replications output for: P. achalensis, A) Present model = 5008.55 km², B) Model for 2050 RCP 45 = 4054.00 km², C) Model for 2050 RCP 85 = 2677.83 km²; P. nigroiugulus, 2) Present model = 71957.34 km², E) Model for 2050 RCP 45 = 56162.45 km², F) Model for 2050 RCP 85 = 38501.27 km². References: Country / province names, protected areas perimeters dashed-green lines, protected areas intersected with suitable areas filled in solid green, localities in red dots, and defined accessible area (M) in the upper left box.

opennotspecifiedDec 2017View details →
zenodo32/100

FIGURE 4 in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

FIGURE 4. True skill statistic (TSS) performed on the replicates for each species. References: mod, number of model replicate; values close to 1 indicates perfect agreement, values near zero indicates a performance no better than random.

opennotspecifiedDec 2017View details →
zenodo32/100

FIGURE 3. RUs histograms for P in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

FIGURE 3. RUs histograms for P. nigroiugulus. The white columns show the distributions of available RUs, whereas grey columns show the distributions of used RUs.

opennotspecifiedDec 2017View details →
zenodo32/100

FIGURE 2. RUs histograms for P in Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

FIGURE 2. RUs histograms for P. achalensis. The white columns show the distributions of available RUs, whereas grey columns show the distributions of used RUs.

opennotspecifiedDec 2017View details →
zenodo32/100

Ecosystem-based marine spatial planning assessment results

<p>The dataset shows the results of the assessment of the Spanish and French maritime spatial planning processes</p>

opencc-by-4.0Nov 2024View details →
dryad32/100

The value of increased spatial resolution of pesticide usage data for assessing risk to endangered species: Data, notebooks, and results

<p>Decision makers often cite data quality as a limitation in environmental management. Value of information approaches evaluates the benefit of new data collection for management outcomes. Pesticide exposure risk assessment for endangered species is one context where data limitations may affect decisions and a value of information type approach could be useful for identifying optimal data <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>quality and resolution. Under the U.S. Federal Insecticide, Fungicide and Rodenticide Act, the U.S. Environmental Protection Agency (EPA) is responsible for registering pesticides before they can be sold and regularly reviewing pesticides. Section 7 of the Endangered Species Act requires that the EPA consider potential impacts of pesticides to listed endangered species and critical habitats in this process, and for the Services—U.S. Fish and Wildlife Service and National Marine Fisheries Service—to complete a formal Section 7 consultation if the EPA deems it necessary. The current process is time‐intensive, lacks transparency and confidence among stakeholders, and leaves hundreds of unreviewed pesticides on the market. Increasing the resolution of pesticide usage data could address these concerns by improving estimated overlaps between species ranges and pesticide usage. Thus, we evaluated the relative importance of different resolutions of pesticide usage data for assessing expected carbaryl exposure to endangered plant species endemic to California. We found that spatially explicit, township resolution usage data (~36</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span> <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>mile</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><sup>2</sup><span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>) excluded 33% of terrestrial plants (55/168) and 51% their critical habitats (27/53) from requiring a Section 7 consultation, while coarser resolution data excluded none. In contrast, the EPA's biological evaluation for carbaryl only excludes 4% of terrestrial plants (nationally) from requiring formal Section 7 consultation. This suggests high‐resolution data could increase pesticide review efficiency and decrease the amount of time pesticides remain on the market without a formal evaluation.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroOct 2021View details →
zenodo32/100

Supplementary material 2 from: Polce C, Maes J, Brander L, Cescatti A, Baranzelli C, Lavalle C, Zulian G (2016) Global change impacts on ecosystem services: a spatially explicit assessment for Europe. One Ecosystem 1: e9990. https://doi.org/10.3897/oneeco.1.e9990

Key between LUISA (Baranzelli et al., 2014) and CORINE LULC types, and scores for the potential contribution of each LULC type to provide relevant ES. Scores are based on the ES potential matrix by Burkhard et al. (2014), after appropriate rescaling. See main text for additional details.

opencc-by-4.0Oct 2016View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record