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466 results for “priority”
Mehrabi et al. 2022. Research priorities for global food security under extreme events. Supplementary data and code.
<p>Data and script for reproducing the final results shown in Mehrabi et al., Research priorities for global food security under extreme events, One Earth (2022), https://doi.org/10.1016/j.oneear.2022.06.008.</p> <p>Simply download and read the Mehrabi2022_EEGFS.pdf or the Mehrabi2022_EEGFS.Rmd file from which it was created.</p>
A Priority Map for Vision-Language Navigation - Datasets
<p>This archive contains full versions of the datasets and additional data presented in the following paper:</p> <p>A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues</p> <p>A priority map module (PM-VLN) boosts the performance of transformer-based architectures in navigation tasks by combining temporal sequence alignment and feature-level localisation in cross-modal inputs. The module is pretrained on trajectory estimation and a multi-objective task that pairs location estimation with cross-modal sentence prediction. Two datasets are introduced for the auxiliary tasks:</p> <p> - TR-NY-PIT-central - a set of path traces for routes in two urban locations.</p> <p> - MC-10 - a set of samples with multimodal inputs representing landmarks in 10 US cities.</p> <p>Full details and links for this research are available at the following link:</p> <p>https://jasonarmitage-res.github.io/projects/priority_map/</p> <p>Additional data comprising path traces for routes in Manhattan and language tokens for the Touchdown task are provided for training and evaluating the PM-VLN and framework on the Touchdown benchmark. Please refer to the following link for details on the Touchdown dataset and StreetLearn environment:</p> <p>https://sites.google.com/view/streetlearn/touchdown</p>
NOAA NCCOS Assessment: Priority Areas Recommended for Shallow Coral Reef Management in the South Florida Coast from 2021-04-26 to 2021-05-21
<p>The National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process, and online application (Buja and Christensen 2019) to identify mapping needs along the south Florida coast to support shallow coral reef management by NOAA’s Coral Reef Conservation Program (CRCP). Eighteen participants from local federal, state, academic, and other institutions entered their priorities in an online participatory Geographic Information System (pGIS). Participants used virtual coins to denote their priorities in 10.4 km<sup>2</sup> hexagonal grid cells overlaid on the study area. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important, what data types were needed, and data collection methodologies using a pre-set list of options. Results were compiled, summarized, and mapped to identify high priority areas, reasons for those priorities, and information needs. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in south Florida.</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coast of south Florida. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the pGIS process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online pGIS, the study area was divided into 1761 hexagonal grid cells 10.4 km<sup>2</sup> in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. The pGIS was used by 18 participants to convey their recommendations. Each participant was provided with 530 virtual coins to place into grid cells that they wished to prioritize. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 53 coins could be placed into an individual grid cell by each respondent. Respondents also reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported what data types were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: habitat map/characterization, shoreline characterization, ground truthing (e.g. photos and videos collected using ROVs or AUVs), elevation (e.g. bathymetry and topography), backscatter and intensity (e.g. surfaces used to delineate between hard and soft substrate), 2D map product (e.g. static images used to visualize bottom type, presence/absence of taxa), georectified photomosaics (e.g. 3D products created from structure for motion), and water column (e.g. for fish biomass detection). Respondents also reported what method of data collection was desired in each priority cell. Only one response was required and were selected from the following list: satellite, lidar, multibeam echosounder, split beam echosounder, side-scan sonar, photogrammetry, drop-camera, and uncrewed systems. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 10.4 km<sup>2</sup> grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data products. Also included is a ranking of each grid cell based on the total number of coins, management uses, and agencies allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al., 2022.</p> <p> </p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Puerto Rico and the U.S. Virgin Islands, 2021-11-03 to 2022-01-14
<p>Description:</p> <p>The National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process, and online application (Buja and Christensen 2019) to identify mapping needs along the Puerto Rico and U.S. Virgin Island (USVI) coasts to support shallow coral reef management by NOAA’s Coral Reef Conservation Program (CRCP). Participants from local, federal, academic, and other institutions (sixteen in Puerto Rico, eighteen in USVI), entered their priorities in an online participatory Geographic Information System (pGIS). Participants used virtual coins to denote their priorities in 2.6 km<sup>2</sup> hexagonal grid cells overlaid on the study area, individually for Puerto Rico and USVI. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important, what data types were needed, and data collection methodologies using a pre-set list of options. Results were compiled, summarized, and mapped to identify high priority areas, reasons for those priorities, and information needs. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Puerto Rico and USVI.</p> <p> </p> <p>Purpose:</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of Puerto Rico and USVI. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p> </p> <p>Methods:</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the pGIS process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online pGIS, the Puerto Rico study area was divided into 2007 hexagonal grid cells 2.6 km2 in size. The USVI study area was divided into 644 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. The pGIS was used by 16 participants in Puerto Rico and 18 participants in USVI to convey their recommendations. Each Puerto Rico participant was provided with 600 virtual coins to place into grid cells that they wished to prioritize. Each USVI participant was provided with 200 coins. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 60 coins could be placed into an individual grid cell in Puerto Rico by each respondent, and a maximum of 20 coins could be place into an individual grid cell in USVI. Respondents also reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported requirements of data were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al. 2022, in prep.</p> <p> </p>
Dataset: Priority Technology Holdings, Inc. (PRTH) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
which has priority over all other available names (Lanza and Broadley 2014). More recently, Broadley et al. (2018) split Gonionotophis into four genera, with brussauxi being the only Angolan species remaining in the genus. MAP 291. Distribution of Gonionotophis brussauxi in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
which has priority over all other available names (Lanza and Broadley 2014). More recently, Broadley et al. (2018) split Gonionotophis into four genera, with brussauxi being the only Angolan species remaining in the genus. MAP 291. Distribution of Gonionotophis brussauxi in Angola.
Shifting metabolic priorities among key protistan taxa within and below the euphotic zone
<p>Dataset for submitted publication: <strong>Sarah K. Hu</strong>, Zhenfeng Liu, Harriet Alexander, Victoria Campbell, Paige Connell, Karla B. Heidelberg, Sonya Dyhrman, & David A. Caron. <em>Shifting metabolic priorities among key protistan taxonomic groups within and below the euphotic zone.</em> <strong>In press.</strong> Environmental Microbiology. <a href="https://doi.org/10.1111/1462-2920.14259">https://doi.org/10.1111/1462-2920.14259</a></p> <p>See associated GitHub repository: https://github.com/shu251/SPOT_metatranscriptome</p> <p><strong>Abstract</strong></p> <p>A metatranscriptome study targeting the protistan community was conducted off the coast of Southern California, at the San Pedro Ocean Time-series station at the surface, 150 m (oxycline), and 890 m to link putative metabolic patterns to distinct protistan lineages. Comparison of relative transcript abundances revealed depth-related shifts in the nutritional modes of key taxonomic groups. Eukaryotic gene expression in the sunlit surface environment was dominated by phototrophs, such as diatoms and chlorophytes, and high abundances of transcripts associated with synthesis pathways (e.g. photosynthesis, carbon fixation, fatty acid synthesis). Sub-euphotic depths (150 m and 890 m) exhibited strong contributions from dinoflagellates and ciliates, and were characterized by transcripts relating to digestion or intracellular nutrient recycling (e.g. breakdown of fatty acids and V-type ATPases). These transcriptional patterns underlie the distinct nutritional modes of ecologically important protistan lineages that drive marine food webs, and provide a framework to investigate trophic dynamics across diverse protistan communities.</p> <p>Most recent version - March 16, 2018</p>
S15 | NORMANPRI | NORMAN Priority List
<p>This is the collection associated with list S15 NORMANPRI on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S15</p> <p>NORMANPRI</p> <p><strong>NORMAN Priority List</strong></p> <p>NORMAN Priority <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/NORMAN_PriorityList_2016.csv">CSV</a> (13/7/2017)</p> <p>CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/normanpri">NORMAN Priority List</a></p> <p>Further curation in progress…</p> <p><a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/NORMAN_PriorityList_2016_InChIKeys.txt">NORMAN Priority InChIKeys</a> (16/05/2017)</p> <p>Priority substances from NORMAN WG-1 (Prioritisation), provided by Valeria Dulio.</p>
Fig. 2 in Conservation Of The Javan Gibbon Hylobates Moloch: Population Estimates, Local Extinctions, And Conservation Priorities
Fig. 2. Relation between number of groups calling per day and number of census days in the Telaga Warna Nature Reserve (Sept 1999) and Lingo Asri, Dieng mountains (Sept 1998).
Fig. 1 in Conservation Of The Javan Gibbon Hylobates Moloch: Population Estimates, Local Extinctions, And Conservation Priorities
Fig. 1. Current distribution of the Javan gibbon Hylobates moloch. Based on Kappeler, 1984, Asquith et al., 1995, Nijman 2001b, and present study. All areas where the species' presence has been confirmed are indicated in black; areas where the species' possible presence was reported by Andayani et al. (1999) are indicated in white. The three main study areas are: A, Telaga Warna Nature Reserve; B, Gunung Gede Pangrango National Park; C, Dieng mountains. The insert shows Java with all remaining forest patches on the island.
Fig. 3 in Advertisement calls of six glassfrog species in the Colombian Andes, and comments on priorities for future research and conservation
Fig. 3. Counts of glassfrog species for those with and without the call described, and categorized by: (A) IUCN conservation status categories; (B) Endemism or distribution range (see details in Materials and Methods); and (C) Occurrence in National Protected Areas.
Fig. 2 in Advertisement calls of six glassfrog species in the Colombian Andes, and comments on priorities for future research and conservation
Fig. 2. Spectrograms (top) and oscillograms (bottom) of the described glassfrogs advertisement calls. All calls are displayed at Blackman window (length = 512) and 80% overlap, at the same frequency range, and all but S. punctulata and C. huilensis are displayed at the same temporal scale.
Fig. 1 in Advertisement calls of six glassfrog species in the Colombian Andes, and comments on priorities for future research and conservation
Fig. 1. Fieldwork localities in the Central and Eastern Cordilleras where the advertisement calls were obtained.
Data and Code for "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility"
<p>This snapshot contains code and data for the preprint "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility".</p> <p>Instructions on re-using the data and running the code can be found in the README.md.</p> <p>Changes:</p> <ul> <li>Added survey instrument and informed consent.</li> </ul>
Quantifying wetness variability in aapa mires with Sentinel-2: towards improved monitoring of an EU priority habitat [Dataset]
<p>This repository contains data used in Jussila et al. 2023 paper "Quantifying wetness variability in aapa mires with Sentinel-2: towards improved monitoring of an EU priority habitat" (submitted). The files uploaded in the repository include (i) spatial polygon data of flark mires located in Finnish aapa mire occurrence zone, (ii) polygon subset of the flark mires observed in the study, focused on mires belonging to Natura 2000 network (ii) monthly information for April-September period in 2017-2020 of climatic water balance and Sentinel-2 -derived wetness metrics, as average values per mire, and (iii) training point data used to train the decision tree model which was used in the study to detect wet flark surfaces in the studied aapa mires. Retrieving the metrics from Sentinel-2 satellite imagery for the analysis of variability in wetness was executed with Sentinelhub Batch statistical API, and the process is documented in project GitHub repository: <a href="https://github.com/sykefi/feo-aapa">https://github.com/sykefi/feo-aapa</a>. </p> <p>Additional information of data is provided in the README file.</p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Hawaiʻi, 2022-07-08 to 2022-08-01
<p>Description</p> <p>NOAA's Coral Reef Conservation Program (CRCP) has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding the main Hawaiian Islands. The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts.</p> <p>To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of 17 participant groups entered their mapping priorities into the online tool. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Hawaiʻi.</p> <p>Purpose:</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the main Hawaiian Islands. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>Methods:</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the study area was divided into 1786 hexagonal grid cells 2.6 km<sup>2</sup> in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, protected areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each participant was provided with 540 virtual coins to place into grid cells to denote their mapping needs. They were instructed to place more coins in grid cells that were higher priority. A maximum of 54 coins could be placed into an individual grid cell by each respondent. Participants also selected from a drop-down list of predefined management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also selected what map product requirements were needed in priority cells by selecting a minimum of one, to a maximum of two choices from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 2.6 km<sup>2</sup> grid cells used in this prioritization and their associated coin values overall, as well as by management use and map product requirement. Other summary values include the number of participants, number of participating groups, number of management uses, and number of map product requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al. 2023, in prep.</p> <p> </p>
Priority effects determine how dispersal affects biodiversity in seasonal metacommunities
<p><span>The arrival order of species frequently determines the outcome of their interactions. This phenomenon, called the priority effect, is ubiquitous in nature and determines local community structure, but we know surprisingly little about how it influences biodiversity across different spatial scales. Here, we use a seasonal metacommunity model to show that biodiversity patterns and the homogenizing effect of high dispersal depend on the specific mechanisms underlying priority effects. When priority effects are only driven by positive frequency dependence, dispersal-diversity relationships are sensitive to initial conditions but generally show a hump-shaped relationship: biodiversity declines when dispersal rates become high and allow the dominant competitor to exclude other species across patches. When spatiotemporal variation in phenological differences alters species' interaction strengths (trait-dependent priority effects), local, regional, and temporal diversity are surprisingly insensitive to variation in dispersal, regardless of the initial numeric advantage. Thus, trait-dependent priority effects can strongly reduce the effect of dispersal on biodiversity, preventing the homogenization of metacommunities. Our results suggest an alternative mechanism that maintains local and regional diversity without environmental heterogeneity, highlighting that accounting for the mechanisms underlying priority effects is fundamental to understanding patterns of biodiversity.</span></p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Guam and the Commonwealth of the Northern Mariana Islands, 2023-02-22 to 2023-06-12
<p>Description:<br> NOAA's Coral Reef Conservation Program (CRCP has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding Guam and the Commonwealth of the Northern Mariana Islands (CNMI). The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts.<br> To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of seven participant groups entered their mapping priorities into the online tool for Guam and ten participant groups for CNMI. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Guam and CNMI.</p> <p>Purpose:<br> The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the Guam and CNMI. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>Methods:<br> An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the Guam study area was divided into 153 hexagonal grid cells 2.6 km2 in size. The CNMI study area was divided into 330 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each Guam participant was provided with 50 virtual coins to place into grid cells that they wished to prioritize. Each CNMI participant was provided with 110 coins. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 5 coins could be placed into an individual grid cell in Guam by each respondent, and a maximum of 11 coins could be place into an individual grid cell in CNMI. Respondents also<br> reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported requirements of data were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefiles contain the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Hile et al. 2023, in prep.</p>
Structural and functional effects of global invasion pressure on benthic marine communities – patterns, challenges and priorities
<p>Here we present datasets underlying the results of the study examining patterns of structural and functional community-level change in a range of well-studied marine ecosystems with documented histories of bioinvasion. For the purpose of the study, the authors identified six regions with extensive bay-scale datasets on native and non-indigenous benthic species assemblages, allowing paired comparisons in time (years to decades; retrospective datasets) or space (high vs. low proximity to hotspots of NIS introductions within a region; cross-sectional datasets) representing differences in bioinvasion pressure (Table 1). These sites were: 1) coastal waters of British Columbia, Canada (BC); 2) San Francisco Bay, USA (SF); 3) Ilha Grande Bay, Brazil (BR); 4) North-Eastern Baltic Sea, Estonia (BS); 5) estuaries of New South Wales, Australia (AU) and 6) Waitematā Harbour, New Zealand (NZ). These six regions are generally at mid- to higher-latitudes, with one low-latitude site (BR). The study sites encompassed surveys of benthic communities: fouling assemblages (BC and AU), subtidal reefs (BR and BS), and soft-sediment benthos (SF, BS, and NZ).</p> <p>Three data files are provided for each study region and include:</p> <ul> <li>benthic community data (XX_species.csv)</li> <li>binary (0/1) biological trait information compiled for all species in the dataset (XX_traits.csv)</li> <li>additional explanatory variables considered for each study region - bioinvasion pressure and spatial variables (XX_env.csv)</li> </ul> <p>For detailed information on datasets and methods description please refer to the original manuscript by Zaiko et al.</p>
Stage-mediated priority effects and season lengths shape long-term competition dynamics
<p>The relative arrival time of species can affect their interactions and thus determine which species persist in a community. Although this phenomenon, called priority effect, is widespread in natural communities, it is unclear how it depends on the length of growing season. Using a seasonal stage-structured model, we show that differences in stages of interacting species could generate priority effects by altering the strength of stabilizing and equalizing coexistence mechanisms, changing outcomes between exclusion, coexistence, and positive frequency dependence. However, these priority effects are strongest in systems with just one or a few generations per season and diminish in systems where many overlapping generations per season dilute the importance of stage-specific interactions. Our model reveals a novel link between the number of generations in a season and the consequences of priority effects, suggesting that consequences of phenological shifts driven by climate change should depend on specific life histories of organisms.</p>
ScienceDex guides
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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.