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154 results for “ecosystem assessment”
NGE01 Chronic Addition of Nitrogen Gradient Experiment (ChANGE): Assessing threshold responses of plant community composition and ecosystem processes at Konza Prairie
Chronic nutrient additions can lead to drastic shifts in the plant community through time, both within tallgrass prairie in other grassland ecosystems worldwide. Nutrient addition experiments have answered many questions about patterns of diversity loss and community shifts; however, the level of nutrients which must be added to cause community shifts is unknown. To date, all nitrogen (N) addition experiments at Konza have added 10 g m-2 (e.g., NutNet Plots; Phosphorus (P) Plots; Belowground Plots), yet current rates of N deposition are one-tenth of that level. Even predicted rates of future N deposition in grasslands are not expected to exceed 5 g m-2 by the year 2050 and will likely be around 2 g m-2 for most of the US. This mismatch begs the question will 10 g/m2 affect grasslands the same way 2 or 5 g m-2 will? There are two main goals for this long-term experiment (1) to identify the nutrient threshold needed to drive plant community change with nutrient additions, and (2) to determine what factors underlie those threshold responses (build up of nutrients, mycorrhizal loss, invertebrate herbivory). Konza ChANGE is part of a multi-site experiment spanning grasslands on two different continents: North America – tallgrass prairie (KNZ) and shortgrass steppe (SGS), and China – three sites in Inner Mongolia. By including multiple grasslands, we expand our ability to make generalizations about how grasslands are affected by N additions, and whether thresholds, if they exist, vary with precipitation, natural nutrient availability, and species identity/composition. Research Questions: (1) Do ecosystems have N tolerance thresholds above which community composition will change, and does that differ between grassland types (i.e. mesic and xeric grasslands)? (2) Does adding a large amount of nutrients in one season result in an equivalent community change as adding a small amount over multiple years? (For example does 5 g m-2 for 6 years create the same community change as
Data and script for "On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"
<p>Data and R script necessary to replicate the results of Riva et al. 2024 ("On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"; minor revisions, Biological Conservation).</p>
CEE01 The Climate Extremes Experiment (CEE): Assessing ecosystem resistance and resilience to repeated climate extremes at Konza Prairie
Climate extremes, such as drought, are increasing in frequency and intensity, and the ecological consequences of these extreme events can be substantial and widespread. Yet, little is known about the factors that determine recovery (or resilience) of ecosystem function post-drought. Such knowledge is particularly important because post-drought recovery periods can be protracted depending on drought legacy effects (e.g., loss key plant populations, altered community structure and/or biogeochemical processes). These drought legacies may alter ecosystem function for many years post-drought and may impact future sensitivity (both resistance and resilience) to climate extremes. With forecasts of more frequent drought, there is an imperative to understand whether and how post-drought legacies will affect ecosystem response to future drought events. To address this knowledge gap, we experimentally imposed over an eight year period two extreme growing season droughts, each two years in duration followed by a two-year recovery period, in annually burned tallgrass prairie.
Data and R Code from "A novel approach to sustainability assessment of food supply chains using networks of ecosystem services"
<p>Data and R code from this paper applying network analysis (iGraph) to two case studies pre and post agroecological transitions in Central America and Tanzania, Africa from the IPES-Food report. Further descriptions of this data and code can be found within the extended manuscript. R Code relies on the data from the scenarios (e.g., Nodes and Relations CSVs) and creates the output network metrics (e.g., Node Metric CSVs). </p>
Assessing change in ecosystem processes twenty four years after the 1988 Yellowstone Wildfires, 2013
The extent of young postfire conifer forests is growing throughout western North America as the frequency and size of high-severity fires increase, making it important to understand ecosystem structure and function in early seral forests. Understanding nitrogen (N) dynamics during postfire stand development is especially important because northern conifers are often N limited. We re-sampled lodgepole pine (Pinus contorta var. latifolia) stands that regenerated naturally after the 1988 fires in Yellowstone National Park (Wyoming, USA) to ask: (1) How have N pools and fluxes changed over a decade (15 to 25 years postfire) of very rapid forest growth? (2) At postfire year 25, how do N pools and fluxes vary with lodgepole pine density and productivity? Lodgepole pine foliage, litter (annual litterfall, forest-floor litter), and mineral soils were sampled in 14 plots (0.25-ha) that varied in postfire lodgepole pine density (1,500 to 344,000 stems ha-1) and aboveground net primary production (ANPP; 1.4 to 16.1 Mg ha-1 yr-1). Previous data collected 15 and 17 years postfire (i.e., 2003 and 2005) provided a reference for assessing change in ecosystem process rates over time. At that time, lodgepole pine foliar nitrogen (N) concentrations had not yet suggested N limitation, and tree density and net primary production strongly influenced ecosystem carbon (C) and N stocks. These data were collected in 2012 and 2013 and are associated with the following publication: Turner, M. G., T. G. Whitby, and W. H. Romme. 2019. Feast not famine: Nitrogen pools recover rapidly in 25-yr old postfire lodgepole pine. Ecology (In press).
Baltimore Ecosystem Study: Stewardship Mapping And Assessment Project (STEW-MAP) survey results 2011 and 2019
Addressing the challenges of sustainable and equitable city management in the 21st century requires innovative solutions and integration from a range of dedicated actors. In order to form and fortify partnerships of multi-sectoral collaboration, expand effective governance, and build collective resiliency it is important to understand the network of existing stewardship organizations. The term ‘stewardship’ encompasses a spectrum of local agents dedicated to the evolving process of community care and restoration. Groups involved in stewardship across Baltimore are catalysts of change through a variety of conservation, management, monitoring, transformation, education, and advocacy activities for the local environment – many with common goals of joint resource management, distributive justice, and community power sharing. The “environment” here is intentionally broadly defined as land, air, water, energy and more. The Stewardship Mapping and Assessment Project (STEW-MAP) is a method of data collection and visualization that tracks the characteristics of organizations and their financial and informational flows across sectors and geographic boundaries. The survey includes questions about three facets of environmental stewardship groups: 1) organizational characteristics, 2) collaboration networks, and 3) stewardship “turfs” where each organization works. The data have been analyzed alongside landcover and demographic data and used in multi-city studies incorporating similar datasets across major urban areas of the U.S. Additional information about the growing network of cities conducting stewmap can be found here: https://www.nrs.fs.usda.gov/STEW-MAP/ Romolini, Michele; Grove, J. Morgan; Locke, Dexter H. 2013. Assessing and comparing relationships between urban environmental stewardship networks and land cover in Baltimore and Seattle. Landscape and Urban Planning. 120: 190-207. https://www.fs.usda.gov/research/treesearch/44985 Johnson, M., D. H. Locke, E. Svendsen, L
Data from: Recommendations for assessing earthworm populations in Brazilian ecosystems
<p><strong>Earthworms are often related to fertile soils and frequently used as environmental quality indicators. However, to optimize their use as bioindicators, their populations must be evaluated together with environmental and anthropogenic variables regulating earthworm communities. In this review we identify the earthworm, soil chemical, physical, environmental and management-related variables evaluated in 124 published studies that quantified earthworm abundance (>7300 samples) in 765 sites with different types of climate, soils, land use and management systems in Brazil. Most soil chemical and physical attributes (except pH) were less reported (<50% of studies) than other environmental variables such as sampling date, altitude, temperature, precipitation, climate and soil type and land use (all >50% of studies). Earthworms were rarely identified (24%) and few studies (31%) measured their biomass, although most provided adequate information on sampling protocol. Based on the importance in regulating earthworm populations, we propose a set of variables that should be evaluated when studying earthworm communities </strong>and other macrofauna groups<strong>. This should help guide future studies on earthworms in Brazil and other countries, optimize data collection and replicability, allow comparisons between different studies and promote the use of earthworms as soil quality bioindicators.</strong></p>
A comprehensive data-based assessment of forest ecosystem carbon stocks in the U.S. 1907-2012
<p>This excel file contains data on forest ecosystem Carbon stocks in the United States from 1907-2012 used to create figures 2 (a) (b), 3, 4, 5 (a) (b) presented in the article "A comprehensive data-based assessment of forest ecosystem carbon stocks in the U.S. 1907-2012".</p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in American Samoa, 2023-06-06 to 2023-08-07
<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 depth) surrounding American Samoa. 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 nine 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 American Samoa.</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 coast of the American Samoa. 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 160 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry layers, 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 participant was provided with 50 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 5 coins could be placed into an individual grid cell. 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: Hile et al. 2023, in prep.</p>
Ecosystem-based marine spatial planning assessment tool video tutorial
<p><span>Aiming at promoting the capacity building of competent authorities, scientists and consultants, a novel tool is proposed for assessing the alignment of marine spatial planning processes with ecosystem-based approach principles and to guide its operationalization.</span></p> <p><span>The EB-MSP assessment tool is developed with the ambition of providing a fit-for-purpose tool to overcome the ecosystem-based marine spatial planning implementation barriers reported by experts and managers.</span></p> <p><span>The EB-MSP assessment tool is designed to apply to any spatial plan, regardless of its stage of development: assessment of existing plans, plans in progress; or different national plans in a transboundary region.</span></p> <p><span>The EB-MSP tool can be accessed at https://aztidata.es/EB-MSP</span></p> <p><span>The EB-MSP assessment tool leads users through a step-by-step procedure for evaluating a specific plan.</span></p> <p><span>Upon first access, the user must register. This way, the users can conduct multiple assessments in a single session or different sessions, and can retrieve the information from previous sessions.</span></p> <p><span>The evaluation can be conducted by documenting the actions adopted during the planning process stages, or by examining how ecosystem-based marine spatial planning cross-cutting topics, have been incorporated into the plan.</span></p> <p><span>The user has to provide information about 130 statements that reflect the actions or tasks adopted during the planning process.</span></p> <p><span>For each action, six complementary fields of information have to be provided by the user:</span></p> <ol> <li><span><span><span> </span></span></span><span>the degree of implementation of the action; </span></li> <li><span><span><span> </span></span></span><span>the relevance of the action for the assessed planning site; </span></li> <li><span><span><span> </span></span></span><span>the main source of knowledge base supporting the action; </span></li> <li><span><span><span> </span></span></span><span>the respondent's confidence; </span></li> <li><span><span><span> </span></span></span><span>approaches, tools and methods implemented; and </span></li> <li><span><span><span> </span></span></span><span>justification of the responses</span></li> </ol> <p><span>Once the assessment is performed, the results are displayed as dynamic graphs that can be downloaded.</span></p> <p><span>The responses are also stored in a table, which can be downloaded as an Excel spreadsheet.</span></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>
Fig.1 in Preliminary Biophysical Assessment Of Forest Ecosystem Services: Two Model Area Examples
Fig.1. Ecosystem service class: biomass energy products. Indicator: potential energy wood supply within felling limits.
Fig. 2 in Preliminary Biophysical Assessment Of Forest Ecosystem Services: Two Model Area Examples
Fig. 2. Ecosystem service class: global climate regulation by reduction of GHG concentration. Indicator: Estimated carbon stock in live above-ground tree biomass.
Summary for policymakers of the assessment report on land degradation and restoration of the Intergovernmental SciencePolicy Platform on Biodiversity and Ecosystem Services: Figure SPM.1
<p>The purpose of Figure SPM.1 is to support the statement that land degradation occurs just about everywhere in the world (i.e. it is ‘pervasive’), takes many forms, and that examples of successful restoration are also widespread. The figure consists of a backdrop map of the world from a multiple land degradation perspective, showing the level of uncertainty between studies, overlaid with dots representing all the places specifically mentioned in the eight chapters of the main Assessment Report on Land Degradation and Restoration, including case studies of both degradation and restoration. Around the map are brief notes regarding the main forms of degradation encountered.</p>
Multi-disciplinary survey data for the assessment of regulating and recreational ecosystem services in urban parks under heat and drought conditions
<p>The research group GreenEquityHEALTH provides quantified knowledge on how urban green spaces contribute to the mitigation of climate change induced challenges and challenges from urbanization to improve health, well-being and environmental justice. The project identifies the mediating pathways or direct effects of divers urban green spaces that act to either promote health, encourage healthy behaviours like social interaction or physical activity, or to decrease risk factors such as air pollution or urban heat.</p> <p>Here we present core data of our interdisciplinary multi-method campaigns that included in-situ stationary and aerial (remote sensing-based) environmental measurements, mobile air quality measurements, and social science-informed surveys, namely, park vistor observations and countings and a questionnaire survey.</p> <p><strong>List of data and content</strong></p> <ul> <li>Aarial_survey: digital surface model, orthophoto and thermal infrared images as raster files (*.tif); flight and processing report (*.pdf)</li> <li>Air_quality: stationary PM measurement data (*.csv); coordinates (*.txt)</li> <li>Meteorology: stationary air temperature and humidity data (*.csv), sensor meta data (*.csv)</li> <li>ParkVisitor_Surveys: survey data and questionnaire replies (*.csv), survey sheets (*.docx), questionnaire form (*.pdf)</li> </ul> <p><strong>Data acquisition and processing</strong></p> <p>For details on the data (e.g. sensors, calibration, survey settings) please refer to the linked publication, incl. Supplementary Material.</p> <p><strong>Acknowledgments</strong><br> We would like to thank the City of Leipzig, Department for Urban Green and Waters, for supporting the project. We would like to thank Henrique Miguel Pereira (Head of Research Group Biodiversity Conservation of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig) for providing equipment for the meteorological field campaigns. We also thank Anhalt University of Applied Sciences, Institute of Geoinformation and Surveying with Lutz Bannehr for conducting the airborne campaigns, Marco Pohle and Helko Kotas (both Helmholtz Centre for Environmental Research - UFZ) for technical support, and Judith Rakowski for support during the field surveys. This work was carried out within the research project ‘Environmental-health Interactions in Cities<br> (GreenEquityHEALTH) – Challenges for Human Wellbeing under Global Changes’ (2017 to 2022) funded by the German Federal Ministry of Education and Research (BMBF), funding code: 01LN1705A.</p> <p><strong>Related publication</strong><br> Kabisch, N. et al. (2021). A methodological framework for the assessment of regulating and recreational ecosystem services in urban parks under heat and drought conditions. <em>Ecosystems and People</em>. <a href="https://doi.org/10.1080/26395916.2021.1958062">doi:10.1080/26395916.2021.1958062</a></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>
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>
Integration of environmental DNA metabarcoding technique to reinforce fish biodiversity assessments in seagrass ecosystems: A case study of Gazi Bay Seagrass meadows
<p><span>Assessing biodiversity in marine nearshore ecosystems is crucial for effective management, especially in the context of climate change and overexploitation of marine resources. Conventional methods often fall short in providing comprehensive information for managing seagrass ecosystems. However, the emergence of environmental DNA (eDNA) techniques has transformed the field by enabling non-invasive surveys that are cost-effective and provide detailed information with high resolution. In this study, we utilized eDNA to assess fish diversity and compared its effectiveness to conventional techniques such as catch assessment surveys and underwater surveys. </span>We sampled three habitats (A: mangrove-seagrass, B: seagrass only, and C: coral-seagrass) with 4 replicates. Site A recorded 8 fish species, site B had 16 species, and site C, characterized by coral and seagrass habitats, exhibited the highest fish diversity with 45 species (mean H' index = 2.455), underscoring its ecological importance. To ensure accurate taxonomic identification, we utilized an updated MiFish reference database containing a larger number of fish species compared to the initial library. This expanded reference database with 9,569 fish species, facilitated more precise identification and enhanced the reliability of our findings. Notably, the eDNA technique outperformed conventional methods by detecting 23 additional fish species that went undetected using traditional surveys. Moreover, our study documented five fish species previously unknown to occur within the study region, further emphasizing the value of eDNA analysis in uncovering hidden biodiversity. These findings strongly advocate for integrating eDNA techniques into the monitoring and assessment of biodiversity in shallow tropical habitats of the Western Indian Ocean. By leveraging eDNA surveys, we can gain valuable insights into fish diversity, discover hidden species, and make informed decisions for the conservation and management of these ecologically significant areas.</p>
Data from: Recommendations for assessing earthworm populations in Brazilian ecosystems
Open the record for dataset details and reuse information.
Integration of environmental DNA metabarcoding technique to reinforce fish biodiversity assessments in seagrass ecosystems: A case study of Gazi Bay Seagrass meadows
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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.