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246 results for “prioritization”
Presence observations for six tree species prioritized for forest landscape restoration in Ethiopia
<p><strong>Description:</strong></p><p>Geolocations of presence occurrences for a selection of six species (<i>Cordia africana</i>, <i>Croton macrostachyus</i>, <i>Eucalyptus globulus</i>, <i>Faidherbia albida</i>, <i>Grevillea robusta</i>, <i>Juniperus procera</i>) sourced from databases (GBIF, RAINBIO) and from the scientific literature.</p><p>Each record is associated with a DOI, link, or citation to the original source of the data. Observations were filtered using the R package <i>CoordinatesCleaner</i> (Zizka <i>et al</i>. 2019) with the <i>clean_coordinates </i>function to filter for errors that are common to biological collections.</p><p>The breakdown of the number of observations by species is: <i>Cordia africana</i> (84); <i>Croton macrostachyus</i> (129); <i>Eucalyptus globulus (</i>20); <i>Faidherbia albida </i>(31); <i>Grevillea robusta </i>(350); <i>Juniperus procera </i>(115).</p>
Introductory Motus Prioritization Tool Data (Open first)
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains required files to recreate the data analysis, print out maps based on predictions from the
Prioritized lists of alien species in Belgium and its regions
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a <a href="https://trias-project.github.io/indicators/" target="_blank" rel="noopener">indicator workflow</a> based on FAIR principles to feed <strong>policy relevant indicators for biological invasions in Belgium</strong> from openly published checklist and occurrence data on GBIF. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html">pipeline</a> that prioritizes alien species based on their emergence status. This prioritization is built upon the information contained in:</p> <ul> <li> The <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG) based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow.</li> <li>The <a href="../records/10527772" target="_blank" rel="noopener">species occurrence cube for non-native taxa in Belgium</a>.</li> </ul> <p>We provide two different prioritization strategies: hierarchical ranking and point strategy.</p> <p>We do the prioritzation for both Belgium and its three regions separately: Flanders, Wallonia and Brussels. Only the prioritization for Belgium takes into account the emergence status (number of occurrences and observed occupancy) in Natura2000 protected areas.</p> <h3>Hierarchical ranking</h3> <p>The ranking is based on the highest emerging status. The following priority rules are applied, in order of importance:</p> <ol> <li>The more recent, the higher priority is.</li> <li>Emerging statuses in protected areas are more important than the ones defined over entire Belgium.</li> <li>Emerging statuses from occupancy are more important than the ones from occurrences.</li> <li>The higher average minimal guaranteed growth (#occs/year), the higher priority is.</li> </ol> <h3>Points strategy</h3> <p>The points strategy is based on applying gain factors to emerging statuses using the number of observations in 2020 in Belgium/region as reference (gain factor = 1). The gain factor tables for both Belgium and its regions are available in the <a title="pipeline" href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html#42_Point_strategy">pipeline</a>.</p> <h2><strong>Files</strong></h2> <ul> <li><code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Brussels.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Brussels.tsv</code></li> </ul> <h2>Field values</h2> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region * in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>* </strong>in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 72</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 31.5</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the regin <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul>
Criteria for prioritizing selection of Mexican maize landrace accessions for conservation in situ or ex situ based on phylogenetic analysis
<p>Data for processed SSR markers in maize accessions. A database in Structured Query Language (SQL) is provided. Please see the text file "READMEmaizeSSR.pdf".</p>
Wyoming Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Montana Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Idaho Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
California Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
British Columbia and Alaska Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
New Mexico Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Colorado Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Arizona Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Nevada and Utah Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Oregon Prioritization package for expanding the Motus network in the Pacific Flyway
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all data used to model high occurrence of multiple priority species as well as predictive m
Washington Motus Prioritization Tool Data
Addressing survival and movement of priority migratory avian species of concern along the Pacific Flyway is paramount for their conservation. Yet, the migratory life stage is understudied in many avian species. The Motus radiotelemetry receiver network is an established system for tracking survival and movement of avian species. This network is an international collaborative that successfully identifies stopover site duration, connected migratory routes, post-fledging dispersal and survival, and adult survival and fidelity on a landscape-scale; parameters that cannot be easily estimated using non-tagged birds. While the Motus network is highly connected in eastern North America, the western part of the continent is lagging in coverage and connectivity, limiting the ability to obtain sample sizes large enough to robustly model demographic parameters from tagged birds. Thus, the expansion of the Motus network is a high priority for Pacific Flyway State Agencies. To date, no method exists for determining priority locations for new Motus receiving stations. With collaborations from States and the Canadian Province of British Columbia, we used eBird citizen scientist data to prioritize strategic locations for new Motus receiving stations throughout the Pacific Flyway. We model priority species’ co-occupancy of varying abundance states (i.e., absent, present, abundant, abundant in multiple weeks) with spatially varying Landsat (red and near infrared), water, land cover types, and weather covariates while accounting for variable detection with temporally varying survey effort covariates. Using occupancy model predictions, we identify high-use areas of the Pacific Flyway for establishing new Motus receiving towers that have high probabilities of intercepting high presence and /or abundance of multiple species of interest in a series of predictive occupancy maps. This package contains all the necessary files to recreate the data analysis, print out maps based on predictions
Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance
Open the record for dataset details and reuse information.
Dataset variants used in "Task-Driven Knowledge Graph Filtering Improves Prioritizing Drugs for Repurposing"
<p>This file contains all datasets and variants thereof used in the linked paper. We do not take credit for constructing the datasets, which has been done by the respective original authors (<a href="https://github.com/hetio/hetionet">https://github.com/hetio/hetionet</a>, <a href="https://github.com/gnn4dr/DRKG">https://github.com/gnn4dr/DRKG</a>). For our work we produced modified versions (called "subset" in the file) by applying our metapath based filtering approach. For validation purposed we also constructed ablation versions where one specific type of entities is missing (i.e. "nogene", "noside", etc).</p>
S88 | UBABIOCIDES | List of Prioritized Biocides from UBA
<p>This is the collection associated with list S88 UBABIOCIDES List of Prioritized Biocides from UBA on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>A merged list of prioritized biocidal active substances provided by UBA (German Environment Agency) with relevant transformation products of various environmental compartments from 10 different entry paths. <a href="https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/addendum_priolisten_final_0.pdf">Addendum</a> released Sept. 2021, updating <a href="https://www.umweltbundesamt.de/en/publikationen/are-biocide-emissions-into-the-environment-already">UBA Texte 114/2017</a>.</p> <p>We gratefully acknowledge German Environment Agency (UBA) for permission to add this dataset to the NORMAN Suspect List Exchange.</p> <p>Change log: v0.1.1: updated CSV</p>
Prioritization of semantic over visuo- perceptual aspects in multi-item working memory
<p>All data and code supporting Prioritization of semantic over visuo- perceptual aspects in multi-item working memory</p>
Benchmarking tools for transcription factor prioritization
<p><strong>Abstract:</strong></p> <p>Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora of cell types and cell states from the same genetic information. Due to the importance of regulatory elements, various sequencing methods have been developed to localise them in genomes, for example using ChIP-seq profiling of the histone mark H3K27ac that marks active regulatory regions. Moreover, multiple tools have been developed to predict TF binding to these regulatory elements based on DNA sequence. As altered gene expression is a hallmark of disease phenotypes, identifying TFs driving such gene expression programs is critical for the identification of novel drug targets.In this study, we curated 84 chromatin profiling experiments (H3K27ac ChIP-seq) where TFs were perturbed through e.g., genetic knockout or overexpression. We ran nine published tools to prioritize TFs using these real-world data sets and evaluated the performance of the methods in identifying the perturbed TFs. This allowed the nomination of three frontrunner tools, namely RcisTarget, MEIRLOP and monaLisa. Our analyses revealed opportunities and commonalities of tools that will help to guide further improvements and developments in the field.</p> <p><strong>Dataset description:</strong></p> <ul> <li>tf_tool_benchmark_atacseq_diffPeaks.tar.gz -Archive containing differential peak statistics, tool diff peak input files (fore- and background) for all currated ATAC-seq datasets. </li> <li>tf_tool_benchmark_h3K27ac_chipseq_diffPeaks.tar.gz - Archive containing differential peak statistics, tool diff peak input files (fore- and background) for all currated H3K27ac ChIP-seq datasets. </li> <li>tf_tool_benchmark_atacseq_results.tar.gz - Archive containing the raw tool results for each ATAC-seq dataset.</li> <li>tf_tool_benchmark_chipseq_results.tar.gz - Archive containing the raw tool results for each H3K27ac ChIP-seq dataset.</li> <li>tf_tool_benchmark_results.tar.gz - Archive containing tool results summary for plotting (rds files).</li> </ul> <p><strong>Contact: </strong>Sebastian Steinhauser - sebastian.steinhauser@novartis.com</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.