The Southeastern Ecological Framework Project is a GIS-based analysis to identify ecologically significant areas and connectivity in the southeast region of the US. The states included in the project are Florida, Georgia, Alabama, Mississippi, South Carolina, North Carolina, Tennessee and Kentucky

The project began in October 1998 and was completed in December 2001 by the University of Florida GeoPlan Center and sponsored by the US Environmental Protection Agency Region 4. Region 4 Planning & Analysis Branch continues to use this data to facilitate EPA programs and to work with state and federal agencies and local groups to make sound conservation decisions. Efforts to apply this methodology to other EPA Regions is being considered.

The Southeastern Ecological Framework Final Report is available for download as a .PDF. This document requires Adobe Acrobat Reader 5.0 software for viewing, which can be downloaded for free from the Adobe website.

Project Goals and Objectives:

1. identify primary ecological areas that are protected by some type of conservation or ecosystem management program,

2. identify a green infrastructure network that connects these primary ecological areas,

3. identify the important ecological characteristics of the ecological areas and connecting green infrastructure,

4. develop an understanding of the spatial scale issues involved in analyzing the ecological connectivity at local, state and regional scales, and

5. develop protocol for dissemination of the information.

This analysis was conducted using landscape ecology principles and Geographic Information Systems (GIS) tools. The product(s) of this study can be used by local, state and federal agencies in developing a regional atlas of environmental issues and conflicts and threats to the natural ecosystems caused by human environmental impacts. State, local and private entities can utilize the information to address various environmental resource allocation issues.

[Summary provided by the University of Florida]

Produced as part of the St. Lawrence Action Plan, the Atlas of Territories of Interest for Conservation in the St. Lawrence Lowlands shows the sites where conservation needs are the most pressing. The conservation targets selected (coarse filter) are forest environments, wetlands, open environments (wastelands, perennial crops) and aquatic environments to which are added elements of the fine filter such as exceptional aquatic environments associated with the St. Lawrence corridor (e.g. spawning grounds), alvars, bird colonies, wildlife elements (e.g. nesting sites of Bank Swallows and Chimney Swift, etc.) and important floristic occurrences. Our objective is to determine the sites of interest until a representative threshold of 20% is reached. The geospatial data associated with sites of interest for conservation, the user guide, the methodological report, the metadata as well as the detailed mapping of land use in the St. Lawrence Lowlands, which was an essential basic data for producing this atlas, are available for download. Users can therefore more accurately consult the spatial distribution of sites of interest and the conservation value associated with each plot of habitat for conservation targets (forest environments, wetlands, wastelands, perennial crops, aquatic environments) using geographic information systems (e.g. ArcGIS). Users can also adapt the analysis of this data to their territorial reality and according to specific objectives specific to their interests. Since the conservation of natural environments and species in precarious situations is a shared responsibility, this Atlas will make it possible to meet the priorities of the many organizations involved in the conservation of natural environments in the St. Lawrence Lowlands.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

An RCIS is a voluntary, non-regulatory, and non-binding conservation assessment that includes information and analyses relating to the conservation of focal species, their associated habitats, and the conservation status of the RCIS land base. The Antelope Valley RCIS is based on the best available biological and land use planning information, and presents conservation goals and objectives for the RCIS area that were developed for the focal species and natural communities of the RCIS area. The core habitat areas (cores) are large, contiguous patches of habitat with higher conservation value, and the linkages are important swaths of habitat that link the cores together to allow species to move and disperse between the habitat core areas and to areas outside of the RCIS area. To be used for planning purposes by The State of California and Antelope Valley Regional Conservation Framework stakeholders.See https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=175455&inline for the AVRCIS document.The RCIS area was divided into 15 core habitat areas and 18 landscape linkages for connecting the habitat core areas (or connecting to habitat outside the RCIS area). The habitat core areas and landscape linkages were identified using the conservation values maps from each of the three species groups, the habitat connectivity maps for large and small species, the landscape intactness map, the protected lands map, and the climate stability and climate refugia maps. The core habitat areas (cores) are large, contiguous patches of habitat with higher conservation value, and the linkages are important swaths of habitat that link the cores together to allow species to move and disperse between the habitat core areas and to areas outside of the RCIS area. Other important considerations in determining the boundaries of the cores and linkages were the location of existing protected areas, natural and human-made features visible on aerial imagery, and the location of foreseeable potential future urbanization such as major transportation projects, subdivisions, and renewable energy projects. Boundaries of cores were delineated to capture the largest concentrations of areas with high conservation value in the RCIS area while limiting the overlap with foreseeable future development. The delineation of landscape linkages was based on modeled connectivity pathways (Section 3.2.1.3, Habitat Connectivity and Climate Change) and an examination of aerial imagery to avoid defining linkages in areas with obvious barriers to movement. In many instances, linkages were delineated across major roadways if alternative paths for connecting core areas were unavailable.Preprocessing Methods: Filtered for cores and linkages (field name "CoreLinkag" is not equal to "None"). Dissolved all cores and linkages lands into one feature.Fishnet & Report Processing Methods: The fishnet summarizes acres of cores and linkages within each grid cell. To calculate the report measure, total acres of cores and linkages were summed for an area of interest.

Short description: A network of natural and semi-natural areas which support critical ecosystem services, including connected native species habitats, and which provide for implementation of living infrastructure, active travel, climate adaptation and community wellbeing outcomes. An output of the Connecting Nature, Connecting People program, developed to guide land use and management decisions.Coordinate system: GDA2020 MGA zone 55METHODSData collection / creation: The ecological network was initially derived from potential habitat and connectivity model outputs for grassland, woodland and aquatic-riparian ecosystems. These model outputs indicate potential habitat areas, fragmentation and whether a patch is big enough to provide core or corridor habitat functions for specific taxa groups. The network was created by identifying key patches of core habitat and corridors, as well as missing links that could reconnect fragmented patches. These were reviewed by several ecologists until the proposed network was agreed upon.These agreed areas were converted to spatial data. Polygons were drawn around the relevant potential habitat and connectivity model outputs to simplify the data and visualise connections between habitat patches. The output was overlaid over other environmental data, including sensitive ecological communities, threatened species records, waterways and many more. Boundaries were adjusted to reflect these values as needed.The ecological network was reviewed by subject matter experts and tested in a draft policy document released for public comment. Further revisions to boundaries were made following feedback. The final layer was dissolved and checked for geometry issues. NOTES ON USEQuality: The network considers an abundance and variety of datasets, including protected areas, potential habitat and connectivity maps, distribution of sensitive ecological communities, threatened species records, waterways, restoration projects, urban open spaces and community sites. Data was sourced from authoritative sources where possible. The network was verified and refined through wide distribution and review of the draft dataset, including by ACT Government ecologists and community members. Where possible, polygon boundaries were drawn around existing features (such as lakes or mapped habitat). Polygons were checked against the most recent aerial imagery to verify values and boundaries. This broad review of existing data and consultation on the output provides confidence the output represents the extent of our collective knowledge and provides a holistic illustration of known values.Limitations: The urban ACT Ecological network is a concept only. Polygon boundaries are hand drawn and imprecise. The data has not been ground-truthed. Boundaries should be considered approximate and verified with additional data and ground surveys. Further, the network does not assess feasibility or priorities. It does not consider species presence or absence, habitat condition, management regimes or tenure. This information should be gathered for decision making by referring to other environmental datasets, undertaking ground surveys and consulting with subject matter experts. Data refinement: The dataset could be further improved by testing corridors against a feasibility ruleset (e.g. distance between core patches, width). Additionally, future research may support a wider range of uses by adopting a more technical approach to establish polygon boundaries or areas of interest. This would support higher spatial accuracy and enable greater certainty on what areas are within the network. A quantitative approach could support spatial statistics to aid decision making, e.g. through the ability to prioritise corridors. The Least-Cost Pathway Method is recommended for further study.SHARINGLicenses/restrictions on use: Creative Commons By Attribution 4.0 (Australian Capital Territory)How to cite this data: ACT Government, 2023. Urban ACT Ecological Network, version 2. Polygon layer developed by Office of Nature Conservation, CED, ACT Government.CONTACTFor accessibility issues or data enquiries please contact the Connecting Nature, Connecting People team, cncp@act.gov.au.

Funded under DFO's Marine Conservation Targets Program in partnership with the Huntsman Marine Science Centre (HMSC), this diver-based imagery and sample collection benthic survey documents the occurrence of sponges at 42 dive sites in the Eastern Shore Islands (ESI) Area of Interest (AOI, ~2089 km2) off the Atlantic coast of Nova Scotia, Canada from dive surveys conducted in summer 2021 and 2022. Water quality, species occurrences and counts, habitat, slope, and substrate characteristics were catalogued through diver log sheets, camera imagery, specimen vouchers, and high-resolution bathymetric data. A total of 54 dives to depths from 11 to 33 m (below sea level), collecting up to 147 still images, one-hour of video, and 17 specimen samples per site, resulted in 220 observations for 27 different sponge taxa. This included three new records for Canada (Hymedesmia stellifera, Plocamionida arndti, Hymedesmia jecusculum) and a range extension for a species new to science (Crellomima mehqisinpekonuta) which was recently described from the Bay of Fundy. There were also four species which may seem to be new to science (Halichondria sp., Hymedesmia sp., Protosuberires sp., and Sphaerotylus sp.). Sponges were found to occupy a diversity of micro-habitats, often several different ones in proximity. A total of eight distinct habitat classes were defined, based on varying abundances and diversity of sponges and associated benthic species. These are likely widely distributed among the many complex submerged seabed features within this AOI. Collected specimens were preserved and are stored at the Atlantic Reference Centre (ARC) in St. Andrew's, New Brunswick. Cite this data as: Goodwin, C., Cooper, J.A., Lawton, P., Teed, L.L. 2025. Sponge occurrence and associated species and habitat descriptions derived from the 2021 and 2022 SCUBA diving surveys in the Eastern Shore Islands Area of Interest, Nova Scotia. Version 1.4. Fisheries and Oceans Canada. Occurrence dataset. https://ipt.iobis.org/obiscanada/resource?r=eastern_shore_islands_sponge_survey_2021_2022&v=1.4

Location of Conservation Areas within Causeway Coast and Glens Borough Council.

Under the Planning (Listed Buildings and Conservation Areas) (Scotland) Act 1997 a local authority may determine which parts of its area are of special architectural or historic interest and may designate these as Conservation Areas. The public will normally be consulted on any proposal to designate conservation areas or to change their boundaries. There are over 600 Conservation Areas in Scotland. Many were designated in the early 1970s, but some have since been re-designated, merged, renamed, given smaller or larger boundaries and new ones have been added. They can cover historic land, battlefields, public parks, designed landscapes or railways but most contain groups of buildings extending over areas of a village, town or city. Further planning controls on development can be made by way of an Article 4 Direction, which may or may not be associated with a Conservation Area. We can capture Article 4 Directions separately - go to the upload for that data. However, the final published data layer will contain Conservation Areas, Conservation Areas with associated Article 4 Directions, Article 4 Directions associated with a Conservation Area, and a small number of discrete Article 4 Direction areas.

This dataset shows the results of mapping the connectivity of key values (natural heritage, indigenous heritage, social and historic and economic) of the Great Barrier Reef with its neighbouring regions (Torres Strait, Coral Sea and Great Sandy Strait). The purpose of this mapping process was to identify values that need joint management across multiple regions. It contains a spreadsheet containing the connection information obtained from expert elicitation, all maps derived from this information and all GIS files needed to recreate these maps. This dataset contains the connection strength for 59 attributes of the values between 7 regions (GBR Far Northern, GBR Cairns-Cooktown, GBR Whitsunday-Townsville, GBR Mackay-Capricorn, Torres Strait, Coral Sea and Great Sandy Strait) based on expert opinion. Each connection is assessed based on its strength, mechanism and confidence. Where a connection was known to not exist between two regions then this was also explicitly recorded. A video tutorial on this dataset and its maps is available from https://vimeo.com/335053846.

Methods:

The information for the connectivity maps was gathered from experts (~30) during a 3-day workshop in August 2017. Experts were provided with a template containing a map of Queensland and the neighbouring seas, with an overlay of the regions of interest to assess the connectivity. These were Torres Strait, GBR:Far North Queensland, GBR:Cairns to Cooktown, GBC: Townsville to Whitsundays, GBR: Mackay to Capricorn Bunkers and Great Sandy Strait (which includes Hervey bay). A range of reference maps showing locations of the values were provided, where this information could be obtained. As well as the map the template provided 7x7 table for filling in the connectivity strength and connection type between all combinations of these regions. The experts self-organised into groups to discuss and complete the template for each attribute to be mapped. Each expert was asked to estimate the strength of connection between each region as well as the connection mechanism and their confidence in the information. Due to the limited workshop time the experts were asked to focus on initially recording the connections between the GBR and its neighbouring regions and not to worry about the internal connections in the GBR, or long-distance connections along the Queensland coast. In the second half of the workshop the experts were asked to review the maps created and expand on the connections to include those internal to the GBR. After the workshop an initial set of maps were produced and reviewed by the project team and a range of issues were identified and resolved. Additional connectivity maps for some attributes were prepared after the workshop by the subject experts within the project team. The data gathered from these templates was translated into a spreadsheet, then processing into the graphic maps using QGIS to present the connectivity information. The following are the value attributes where their connectivity was mapped: Seagrass meadows: pan-regional species (e.g. Halophila spp. and Halodule spp.) Seagrass meadows: tropical/sub-tropical (Cymodocea serrulata, Syringodium isoetifolium) Seagrass meadows: tropical (Thalassia, Cymodocea, Thalassodendron, Enhalus, Rotundata) Seagrass meadows: Zostera muelleri Mangroves & saltmarsh Hard corals Crustose coralline algae Macroalgae Crown of thorns starfish larval flow Acropora larval flow Casuarina equisetifolia & Pandanus tectorius Argusia argentia Pisonia grandis: cay vegetation Inter-reef gardens (sponges + gorgonians) (Incomplete) Halimeda Upwellings Pelagic foraging seabirds Inshore and offshore foraging seabirds Migratory shorebirds Ornate rock lobster Yellowfin tuna Black marlin Spanish mackerel Tiger shark Grey nurse shark Humpback whales Dugongs Green turtles Hawksbill turtles Loggerhead turtles Flatback turtles Longfin & Shortfin Eels Red-spot king prawn Brown tiger prawn Eastern king prawns Great White Shark Sandfish (H. scabra) Black teatfish (H. whitmaei) Location of sea country Tangible cultural resources Location of place attachment Location of historic shipwrecks Location of places of social significance Location of commercial fishing activity Location of recreational use Location of tourism destinations Australian blacktip shark (C. tilstoni) Barramundi Common black tip shark (C. limbatus) Dogtooth tuna Grey mackerel Mud crab Coral trout (Plectropomus laevis) Coral trout (Plectropomus leopardus) Red throat emperor Reef manta Saucer scallop (Ylistrum balloti) Bull shark Grey reef shark

Limitations of the data:

The connectivity information in this dataset is only rough in nature, capturing the interconnections between 7 regions. The connectivity data is based on expert elicitation and so is limited by the knowledge of the experts that were available for the workshop. In most cases the experts had sufficient knowledge to create robust maps. There were however some cases where the knowledge of the participants was limited, or the available scientific knowledge on the topic was limited (particularly for the ‘inter-reefal gardens’ attribute) or the exact meaning of the value attribute was poorly understood or could not be agreed up on (particularly for the social and indigenous heritage maps). This information was noted with the maps. These connectivity maps should be considered as an initial assessment of the connections between each of the regions and should not be used as authoritative maps without consulting with additional sources of information. Each of the connectivity links between regions was recorded with a level of confidence, however these were self-reported, and each assessment was performed relatively quickly, with little time for reflection or review of all the available evidence. It is likely that in many cases the experts tended to have a bias to mark links with strong confidence. During subsequent revisions of some maps there were substantial corrections and adjustments even for connections with a strong confidence, indicating that there could be significant errors in the maps where the experts were not available for subsequent revisions. Each of the maps were reviewed by several project team members with broad general knowledge. Not all connection combinations were captured in this process due to the limited expert time available. A focus was made on capturing the connections between the GBR and its neighbouring regions. Where additional time was available the connections within 4 regions in the GBR was also captured. The connectivity maps only show connections between immediately neighbouring regions, not far connections such as between Torres Strait and Great Sandy Strait. In some cases the connection information for longer distances was recorded from the experts but not used in the mapping process. The coastline polygon and the region boundaries in the maps are not spatially accurate. They were simplified to make the maps more diagrammatic. This was done to reduce the chance of misinterpreting the connection arrows on the map as being spatially explicit.

Format:

This dataset is made up of a spreadsheet that contains all the connectivity information recorded from the expert elicitation and all the GIS files needed to recreate the generated maps.

original/GBR_NESP-TWQ-3-3-3_Seascape-connectivity_Master_v2018-09-05.xlsx: ‘Values connectivity’: This sheet contains the raw connectivity codes transcribed from the templates produced prepared by the subject experts. This is the master copy of the connection information. Subsequent sheets in the spreadsheet are derived using formulas from this table. 1-Vertical-data: This is a transformation of the ‘Values connectivity’ sheet so that each source and destination connection is represented as a single row. This also has the connection mechanism codes split into individual columns to allow easier processing in the map generation. This sheet pulls in the spatial information for the arrows on the maps (‘LinkGeom’ attribute) or crosses that represent no connections (‘NoLinkGeom’) using lookup tables from the ‘Arrow-Geom-LUT’ and ‘NoConnection-Geom-LUT’ sheets. 2.Point-extract: This contains all the ‘no connection’ points from the ‘Values connectivity’ dataset. This was saved as working/ GBR_NESP-TWQ-3-3-3_Seascape-connectivity_no-con-pt.csv and used by the QGIS maps to draw all the crosses on the maps. This table is created by copy and pasting (values only) the ‘1-Vertical-data’ sheet when the ‘NoLinkGeom’ attribute is used to filter out all line features, by unchecking blank rows in the ‘NoLinkGeom’ filter. 2.Line-extract: This contains all the ‘connections’ between regions from the ‘Values connectivity’ dataset. This was saved as working/GBR_NESP-TWQ-3-3-3_Seascape-connectivity_arrows.csv and used by the QGIS maps to draw all the arrows on the maps. This table is created by copy and pasting (values only) the ‘1-Vertical-data’ sheet when the ‘LinkGeom’ attribute is used to filter out all point features, by unchecking blank rows in the ‘LinkGeom’ filter. Map-Atlas-Settings: This contains the metadata for each of the maps generated by QGIS. This sheet was exported as working/GBR_NESP-TWQ-3-3-3_Seascape-connectivity_map-atlas-settings.csv and used by QGIS to drive its Atlas feature to generate one map per row of this table. The AttribID is used to enable and disable the appropriate connections on the map being generated. The WKT attribute (Well Known Text) determines the bounding box of the map to be generated and the other attributes are used to display text on the map. map-image-metadata: This table contains metadata descriptions for each of the value attribute maps. This metadata was exported as a CSV and saved into the final generated JPEG maps using the eAtlas Image Metadata Editor Application

Under the Planning (Listed Buildings and Conservation Areas) (Scotland) Act 1997 a local authority may determine which parts of its area are of special architectural or historic interest and may designate these as Conservation Areas. The public will normally be consulted on any proposal to designate conservation areas or to change their boundaries. There are over 600 Conservation Areas in Scotland. Many were designated in the early 1970s, but some have since been re-designated, merged, renamed, given smaller or larger boundaries and new ones have been added. They can cover historic land, battlefields, public parks, designed landscapes or railways but most contain groups of buildings extending over areas of a village, town or city. Further planning controls on development can be made by way of an Article 4 Direction, which may or may not be associated with a Conservation Area. We can capture Article 4 Directions separately - go to the upload for that data. However, the final published data layer will contain Conservation Areas, Conservation Areas with associated Article 4 Directions, Article 4 Directions associated with a Conservation Area, and a small number of discrete Article 4 Direction areas.

Australian marine protected area management units, and information on their associated management plans, including whether they contain measurable or quantifiable Key Performance Indicators (KPIs) for economic, social, biodiversity, and Indigenous or cultural goals; action plans if the goals or objectives are not met; and the relevant over-arching legislation or policy management tool for the marine protected area management unit.

Rockville's maps are a product of its Geographic Information System (GIS), a computer-based tool that combines hardware, software and data for storing, displaying and analyzing information which has a geographic, or locational, association. At its very core the City of Rockville is a geographic entity, defined by its land area and everything that goes on within its boundary. Many types of physical and virtual assets are associated with geographic locations within the City. Data maintained in Rockville's GIS include streets and property parcels; zoning and neighborhoods; water, sewer, and storm drain utilities; parks and city facilities; and scores of other datasets.Using a GIS for analysis can result in better decision making because it helps to answer questions and solve problems related to where things are, how dense or sparse they may be, what kinds of patterns or relationships may exist, what's nearby or within an area of interest, and how things have changed over time. And because GIS data can be visualized through maps, it can make complex information easier to understand.