All protected areas, which are elements of the KSOCh (national system of protected areas): nature reserves, national parks, landscape park and areas of protected landscape, have been verified in 2002. The list of protected areas is based on the reports on protected areas in natural units of space delineated on the basis of geomorphic characteristics.

The United States Geological Survey (USGS) - Science Analytics and Synthesis (SAS) - Gap Analysis Project (GAP) manages the Protected Areas Database of the United States (PAD-US), an Arc10x geodatabase, that includes a full inventory of areas dedicated to the preservation of biological diversity and to other natural, recreation, historic, and cultural uses, managed for these purposes through legal or other effective means (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/protected-areas). The PAD-US is developed in partnership with many organizations, including coordination groups at the [U.S.] Federal level, lead organizations for each State, and a number of national and other non-governmental organizations whose work is closely related to the PAD-US. Learn more about the USGS PAD-US partners program here: www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards. The United Nations Environmental Program - World Conservation Monitoring Centre (UNEP-WCMC) tracks global progress toward biodiversity protection targets enacted by the Convention on Biological Diversity (CBD) through the World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) available at: www.protectedplanet.net. See the Aichi Target 11 dashboard (www.protectedplanet.net/en/thematic-areas/global-partnership-on-aichi-target-11) for official protection statistics recognized globally and developed for the CBD, or here for more information and statistics on the United States of America's protected areas: www.protectedplanet.net/country/USA. It is important to note statistics published by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Center (www.marineprotectedareas.noaa.gov/dataanalysis/mpainventory/) and the USGS-GAP (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-statistics-and-reports) differ from statistics published by the UNEP-WCMC as methods to remove overlapping designations differ slightly and U.S. Territories are reported separately by the UNEP-WCMC (e.g. The largest MPA, "Pacific Remote Islands Marine Monument" is attributed to the United States Minor Outlying Islands statistics). At the time of PAD-US 2.1 publication (USGS-GAP, 2020), NOAA reported 26% of U.S. marine waters (including the Great Lakes) as protected in an MPA that meets the International Union for Conservation of Nature (IUCN) definition of biodiversity protection (www.iucn.org/theme/protected-areas/about). USGS-GAP released PAD-US 3.0 Statistics and Reports in the summer of 2022. The relationship between the USGS, the NOAA, and the UNEP-WCMC is as follows: - USGS manages and publishes the full inventory of U.S. marine and terrestrial protected areas data in the PAD-US representing many values, developed in collaboration with a partnership network in the U.S. and; - USGS is the primary source of U.S. marine and terrestrial protected areas data for the WDPA, developed from a subset of the PAD-US in collaboration with the NOAA, other agencies and non-governmental organizations in the U.S., and the UNEP-WCMC and; - UNEP-WCMC is the authoritative source of global protected area statistics from the WDPA and WD-OECM and; - NOAA is the authoritative source of MPA data in the PAD-US and MPA statistics in the U.S. and; - USGS is the authoritative source of PAD-US statistics (including areas primarily managed for biodiversity, multiple uses including natural resource extraction, and public access). The PAD-US 3.0 Combined Marine, Fee, Designation, Easement feature class (GAP Status Code 1 and 2 only) is the source of protected areas data in this WDPA update. Tribal areas and military lands represented in the PAD-US Proclamation feature class as GAP Status Code 4 (no known mandate for biodiversity protection) are not included as spatial data to represent internal protected areas are not available at this time. The USGS submitted more than 51,000 protected areas from PAD-US 3.0, including all 50 U.S. States and 6 U.S. Territories, to the UNEP-WCMC for inclusion in the WDPA, available at www.protectedplanet.net. The NOAA is the sole source of MPAs in PAD-US and the National Conservation Easement Database (NCED, www.conservationeasement.us/) is the source of conservation easements. The USGS aggregates authoritative federal lands data directly from managing agencies for PAD-US (https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup), while a network of State data-stewards provide state, local government lands, and some land trust preserves. National nongovernmental organizations contribute spatial data directly (www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards). The USGS translates the biodiversity focused subset of PAD-US into the WDPA schema (UNEP-WCMC, 2019) for efficient aggregation by the UNEP-WCMC. The USGS maintains WDPA Site Identifiers (WDPAID, WDPA_PID), a persistent identifier for each protected area, provided by UNEP-WCMC. Agency partners are encouraged to track WDPA Site Identifier values in source datasets to improve the efficiency and accuracy of PAD-US and WDPA updates. The IUCN protected areas in the U.S. are managed by thousands of agencies and organizations across the country and include over 51,000 designated sites such as National Parks, National Wildlife Refuges, National Monuments, Wilderness Areas, some State Parks, State Wildlife Management Areas, Local Nature Preserves, City Natural Areas, The Nature Conservancy and other Land Trust Preserves, and Conservation Easements. The boundaries of these protected places (some overlap) are represented as polygons in the PAD-US, along with informative descriptions such as Unit Name, Manager Name, and Designation Type. As the WDPA is a global dataset, their data standards (UNEP-WCMC 2019) require simplification to reduce the number of records included, focusing on the protected area site name and management authority as described in the Supplemental Information section in this metadata record. Given the numerous organizations involved, sites may be added or removed from the WDPA between PAD-US updates. These differences may reflect actual change in protected area status; however, they also reflect the dynamic nature of spatial data or Geographic Information Systems (GIS). Many agencies and non-governmental organizations are working to improve the accuracy of protected area boundaries, the consistency of attributes, and inventory completeness between PAD-US updates. In addition, USGS continually seeks partners to review and refine the assignment of conservation measures in the PAD-US.

TNC Lands - This layer contains the centroid of each polygon in the TNC lands layer, and is used solely for display purposes at small scales. A spatial dataset of public and private lands and waters secured by a conservation situation that includes an explicit level of security from future conversion and current incompatible uses. Includes spatial data from TNC's Conservation Lands System (CLS) database, which is the legal database of record for all TNC land transactions (fee, easement, lease and deed restrictions). Conservation Management Status (CMS) is a measure derived from the intent, duration and the effective management potential of spatial features of interest ("conservation situations") in the dataset. It is defined as a measure of the likelihood that an existing conservation situation is sufficient to secure biodiversity and allow for its persistence. For more information about the attributes, see http://maps.tnc.org/datadictionary/ Conservation Projects - This is a layer of conservation project boundaries from ConPro, a system maintained by The Nature Conservancy but which contains information from several conservation organizations. Each polygon represents the extent of a conservation project. Note that all attribute information about the projects are maintained in ConPro (http://conpro.tnc.org), sent to the CP_STEWARD.PROJECTS join table in SDE as edits are made, and joined to the spatial data via ConPro project_id. This layer includes sensitive conservation project boundaries for some Nature Conservancy projects, and as such the full layer is for internal TNC use only, unless using the subset of data where the "Public?" field is set to 1 ('Yes'). A subset of this data is available to the public (and the entire dataset is visible to TNC staff) at http://maps.tnc.org/. All ConPro users are welcome to submit updates to this data at any time, although for non-TNC projects spatial data is only supported for public projects. Ecoregional Portfolio - The TNC Ecoregional Portfolio Core Data Set is one of a set of Core Conservation Data Sets managed in GIS by The Nature Conservancy's network of Conservation Data Nodes. This Core Data Set will enable TNC to more effectively deliver data and products of ecoregional assessments to key conservation partners. The data set is being developed in phases. The first phase aggregates all maps of terrestrial ecoregional portfolios developed by The Conservancy across the fifty United States. Subsequent phases of this data set will include biodiversity conservation targets (species and ecosystems) and goals for their conservation, as well as adding existing freshwater and marine portfolios to the terrestrial portfolio developed in the current data set. Each TNC ecoregional portfolio site (aka 'priority conservation area') represents not a conserved area, but a proposed conservation area as part of a hypothetical conservation reserve design which would meet conservation goals established by The Nature Conservancy. Each portfolio site is identified in the attribute table by a name and the ecoregional assessment area, or ecoregional portfolio, to which the site belongs. More information on TNC ecoregional portfolios can be found at: http://www.nature.org/aboutus/howwework/cbd/science/art19228.html# Deeper information can also be accessed here: http://conserveonline.org/workspaces/cbdgateway/era/index_html This dataset is a Conservancy Core Conservation Dataset. The purpose of core datasets is to make prioritized GIS data available throughout The Nature Conservancy and, as appropriate, make data available to the public in a format that can be easily maintained, shared, and leveraged through new GIS and web technologies. The Nature Conservancy's Core Conservation Datasets include: - TNC Ecoregional Portfolio Core Dataset TNC Lands Core Dataset - TNC Conservation Projects Core Dataset. Ecoregional Assessment Status - Terrestrial Ecoregional Assessments of The Nature Conservancy

Journal for Nature Conservation 64 (2021) 126078 The ease of use and availability of unmanned aircraft systems (UAS) recently pervaded a wide range of topics and applications. In nature conservation and for the management of protected areas (PAs), UAS are still not an established approach compared to other methods such as satellite-based remote sensing, although several research articles have already discussed their use. In this context, UAS are even denoted as conservation drones', suggesting that their use is beneficial in terms of accomplishing various tasks such as land-cover mapping, vegetation monitoring, biomass estimation, and animal detection. However, although disturbance of wildlife or other issues caused by UAS are debated and guidelines for the use of UAS in wildlife studies suggest precautionary measures, the implications of the use of UAS in PAs has not been analyzed in detail yet. Therefore, by reviewing research articles, the present paper aims to show whether the use of UAS in PAs is relevant or irrelevant for the PA management in terms of biodiversity conservation, considers a controversial debate of the potential threats, and investigates whether the type of PA concerned matters in this context. We showed that a majority (73%) of selected articles (89) report the use of UAS in PAs as relevant for the PA management in terms of biodiversity. However, most of these studies did not consider impacts of UAS on wildlife or the environment. The possibility of disturbances was discussed in 15 (approx. 17%) of the reviewed works, of which most concluded that the effects were negligible or non-existent. Only in three articles (approx. 3%) an impact has been demonstrated. While most research studies discussing UAS in PAs do not report nor mention any impacts, UAS are banned in many PAs. Therefore, the use of UAS in PAs as conservation drones' and the related pros and cons need to be carefully considered by the PA managers and stakeholders concerned.

Problem Statement

👉 Download the case studies here

Conservation organizations faced challenges in monitoring and analyzing environmental parameters across vast and remote areas. Traditional methods were time-consuming, resource-intensive, and provided limited real-time data. These limitations hindered proactive decision-making for conservation and sustainability initiatives. The organization sought an intelligent solution to monitor environmental changes, identify threats, and support sustainability goals.

Challenge

Developing an environmental monitoring system required addressing the following challenges:

Collecting and processing diverse environmental data, including air quality, water levels, temperature, and biodiversity, in real time.

Deploying sensors and systems in remote and harsh environments while ensuring reliability.

Analyzing large datasets to detect patterns and trends that inform conservation actions.

Solution Provided

An advanced environmental monitoring system was developed using AI-driven data analytics, IoT sensors, and machine learning models. The solution was designed to:

Continuously monitor key environmental parameters using IoT-enabled sensors deployed in target areas.

Analyze data to identify trends, detect anomalies, and predict potential threats.

Provide real-time dashboards and reports to conservationists for proactive decision-making.

Development Steps

Data Collection

Installed IoT sensors to capture environmental parameters, including air and water quality, soil moisture, temperature, and wildlife activity.

Preprocessing

Standardized and cleaned data to ensure accuracy and compatibility for machine learning analysis.

Model Development

Built machine learning models to identify environmental trends and detect anomalies. Developed predictive analytics algorithms to forecast potential environmental risks, such as droughts or pollution events.

Validation

Tested the system on historical environmental data and real-time inputs to ensure accuracy and reliability in diverse scenarios.

Deployment

Deployed the system in key conservation areas, integrating it with cloud platforms for real-time data access and remote monitoring.

Continuous Monitoring & Improvement

Established a feedback loop to refine models based on ongoing data collection and conservation feedback.

Results

Enhanced Environmental Data Accuracy

IoT-enabled sensors provided accurate, real-time data, improving the reliability of environmental monitoring efforts.

Proactive Conservation Measures

Predictive analytics enabled early detection of threats such as deforestation, pollution, and habitat degradation, supporting timely interventions.

Promoted Sustainability Initiatives

The system provided actionable insights that guided sustainability programs and resource management efforts.

Improved Decision-Making

Conservationists used real-time dashboards and analytics to make data-driven decisions, optimizing the allocation of resources.

Scalable and Robust Solution

The system scaled seamlessly to cover additional monitoring areas and adapted to new environmental metrics as needed.

Journal for Nature Conservation 64 (2021) 126078 The ease of use and availability of unmanned aircraft systems (UAS) recently pervaded a wide range of topics and applications. In nature conservation and for the management of protected areas (PAs), UAS are still not an established approach compared to other methods such as satellite-based remote sensing, although several research articles have already discussed their use. In this context, UAS are even denoted as conservation drones, suggesting that their use is beneficial in terms of accomplishing various tasks such as land-cover mapping, vegetation monitoring, biomass estimation, and animal detection. However, although disturbance of wildlife or other issues caused by UAS are debated and guidelines for the use of UAS in wildlife studies suggest precautionary measures, the implications of the use of UAS in PAs has not been analysed in detail yet. Therefore, by reviewing research articles, the present paper aims to show whether the use of UAS in PAs is relevant or irrelevant for the PA management in terms of biodiversity conservation, considers a controversial debate of the potential threats, and investigates whether the type of PA concerned matters in this context. We showed that a majority (73 %) of selected articles (89) report the use of UAS in PAs as relevant for the PA management in terms of biodiversity. However, most of these studies did not consider impacts of UAS on wildlife or the environment. The possibility of disturbances was discussed in 15 (approx. 17 %) of the reviewed works, of which most concluded that the effects were negligible or non-existent. Only in three articles (approx. 3 %) an impact has been demonstrated. While most research studies discussing UAS in PAs do not report nor mention any impacts, UAS are banned in many PAs. Therefore, the use of UAS in PAs as conservation drones’ and the related pros and cons need to be carefully considered by the PA managers and stakeholders concerned.

Local nature conservation sites (LNCS) is a non-statutory designation given by local authorities to areas of locally important nature and landscapes. NatureScot, on behalf of the Local Nature Conservation Sites Working Group, published guidance (https://www.nature.scot/professional-advice/protected-areas-and-species/protected-areas/local-designations/local-nature-conservation-sites) for local authorities on the establishment and management of LNCS systems in Scotland.

Collection: This collection contains derived datasets utilised in the National Biodiversity Assessment System (NBAS), developed as part of the Ecological Knowledge System (EKS). The EKS is a partnership between CSIRO and the Department of Climate Change, Energy, the Environment and Water (DCCEEW) to establish a transparent and authoritative source of information, biodiversity assessment and forecast capability for the Nature Repair Market. The NBAS is a software and data package that provides a nationally consistent approach to forecasting the expected biodiversity benefits of a given project within the Nature Repair Market scheme.

This collection comprises information about the ecosystem typology used in the NBAS. It contains (1) a raster that denotes the location and boundaries of the ecosystem types as defined in NBAS (i.e. the intersections between the National Vegetation Information System (NVIS) major vegetation groups (MVGs) and Conservation Management Zones (CMZs), (2) an ecosystem identification key for each ecosystem type in the raster, and (3) an NBAS ecosystem typology table which reports the pre-1750 and extant ecosystem extent data, excluding MVGs that represent unclassified ecosystems, bare ground, inland water, and predominately non-terrestrial based ecosystems. These datasets are used in the NBAS to forecast expected biodiversity benefits of nature repair projects.

The NBAS is implemented via the PLANR tool (https://planr.gov.au/).

This data collection is based on research created under the Project An Ecological Knowledge System for the Nature Repair Market scheme, which was funded by DCCEEW. The Commonwealth owns the intellectual property rights in any material developed while carrying out the Project. Copyright is retained by CSIRO (2025).

Background: The NBAS provides a nationally consistent approach to assessing a project site’s current contribution to conserving biodiversity and forecasting the biodiversity benefits expected to result from project activities. The NBAS uses proportional persistence of native biodiversity as the ‘common currency’ of project assessment. Biodiversity persistence estimates the proportion of biodiversity that could be expected to exist without significant loss or decline, both now and into the foreseeable future.

The NBAS (Version 1) outputs the following metrics: • Ecosystem condition, which represents the capacity of an area to provide the structures and functions necessary for the persistence of all native species naturally expected to occur in that area if it were in an intact (or reference) state.

Ecosystem condition scores range from 0.0 (ecosystem integrity extinguished, ecosystem completely removed) to a maximum of 1.0 (ecosystem integrity in reference condition). • Landscape connectivity, which estimates the system level contribution that a given area is estimated to make to enhancing the connectivity of habitat across the broader landscape. • The conservation significance of the ecosystem types being protected or enhanced, accounting for their natural rarity and their level of depletion and degradation. • The overall contribution that an area makes to enhancing biodiversity persistence at a system level, integrating the effects of the above three components.

Lineage: The NBAS products in this repository are derived from the following publicly available datasets (see Related Links): • NVIS 6.0 pre-1750 Major Vegetation Groups (MVGs): Major Vegetation Groups are based on the structure, growth form, and floristic composition of the dominant vegetation layer. • Conservation Management Zones (CMZs) of Australia (2018): The 23 Conservation Management Zones of Australia are geographic areas, classified according to their ecological and threat characteristics. The zones are also aligned with the IBRA. • Generalised Dissimilarity Model (GDM): Eight 90 m GDM-transformed environmental grids and two geographic distance grids (x, y) generated from a GDM fitted to data from 115,086 plant community survey plots across Australia. • Habitat Condition Assessment System (HCAS): This dataset uses remote sensing data to estimate ecological condition nationwide. NBAS relies on 90 m resolution data from the most recent short-term epoch (2020–2022).

To generate the ecosystem-typology raster, NVIS MVGs were intersected with CMZs. This intersection results in 485 ecosystem type combinations which form the ecosystem typology used in the NBAS. The ecosystem ID key provides the name and number of the MVG and the CMZ from which each ecosystem type in the raster is derived. The intersection of MVG and CMZ sometimes divides MVGs into smaller subunits when they cross multiple CMZ boundaries. As a result, some of these ecosystem types may appear much ‘rarer’ than they are, given their close relationship to other subunits within the same MVG. To address this, the extent of each MVG subunit (MVG within a CMZ) is modified based on the proportion of species expected to be shared with other subunits within the same MVG using a GDM. The result of this analysis reflects the modified pre-1750 area of each ecosystem type which is then used as an input to the conservation significance metric. The sum of all HCAS condition values occurring within each ecosystem type is combined with a connectivity adjustment to provide an estimate of the ‘effective’ remaining area of each ecosystem type. An equivalent modification for compositional similarity is also applied to the effective remaining area of each ecosystem type.

The NBAS ecosystem typology provides the unadjusted and modified pre-1750 area, and the unadjusted and modified current effective area (accounting for ecosystem condition via HCAS and connectivity) for each ecosystem type. The typology table does not include MVGs that represent unclassified ecosystems, bare ground, inland water, and predominately non-terrestrial based ecosystems. Excluded MVGs are:: • 23 Mangroves • 24 Inland Aquatic - freshwater, salt lakes, lagoons • 26 Unclassified native vegetation • 27 Naturally bare - sand, rock, claypan, mudflat • 28 Sea and estuaries • 30 Unclassified forest

Further details of this analysis can be found in Section 3 and Section 4.2 of the Ecological Knowledge System (EKS) for the Nature Repair Market: Technical Report (see Related Links).

The site “Preservation and restoration of water systems” is based on the Regional Water Programme and based on watercourses with the function of water nature,

(wet) ecological connection zones and areas referred to in the reconstruction and area plans as “space for brook and creek restoration”. In these areas, the policy is based on a regional interest aimed at preserving, improving and restoring the natural water system. Within the areas, measures have been or are being carried out in the field of morphology, such as the re-membrance of streams, the construction of pee-dras zones and the restoration of torment. That is why there is also a need for space next to the watercourse in order to be able to implement the measures properly. Many of the measures are also an obligation stemming from the European Water Framework Directive. Within the areas, instruction rules apply to limitations on functions and activities that hinder or make unnecessarily costly the realisation of water system repair.

description: The CAGES program (Comparative Assessment of Gulf Estuarine Systems) is designed to examine the differences between estuarine ecosystems and investigate why some are more productive than others. The program focuses on estuarine areas important to commercial fisheries and includes data on commercial finfish and invertebrate species, as well as other species commonly captured in trawl sampling. This Florida dataset is a subset of the CAGES Relational Database which is a compilation of fishery-independent data contributed by natural resource agencies of the Gulf States (Texas, Louisiana, Mississippi, Alabama, and Florida). This data set includes trawl and associated hydrographic data collected under the Fisheries-Independent Monitoring (FIM) Program, part of the Fish and Wildlife Research Institute (FWRI) of the Florida Fish and Wildlife Conservation Commission (FFWCC). Trawl data were used to calculate CPUE (catch per unit effort) at each station for the years 1989 through 2005.; abstract: The CAGES program (Comparative Assessment of Gulf Estuarine Systems) is designed to examine the differences between estuarine ecosystems and investigate why some are more productive than others. The program focuses on estuarine areas important to commercial fisheries and includes data on commercial finfish and invertebrate species, as well as other species commonly captured in trawl sampling. This Florida dataset is a subset of the CAGES Relational Database which is a compilation of fishery-independent data contributed by natural resource agencies of the Gulf States (Texas, Louisiana, Mississippi, Alabama, and Florida). This data set includes trawl and associated hydrographic data collected under the Fisheries-Independent Monitoring (FIM) Program, part of the Fish and Wildlife Research Institute (FWRI) of the Florida Fish and Wildlife Conservation Commission (FFWCC). Trawl data were used to calculate CPUE (catch per unit effort) at each station for the years 1989 through 2005.

Natureserve Ecological Systems overlaid on National Vegetation Classification System detailed vegetation vector mapping. Natureserve Ecological Systems is a national 30m raster. To permit it to be overlaid on other ecological data and to enable popup reports, it was rendered into a point raster with test symbology and popup configuration, and overlaid on precision vector maps of the Northern Sierra Foothills, based on the National Vegetation Classification Systems, from California Native Plant Society and California State Dept of Fish and GameNatureServe has developed a mid-scale ecological classification for uplands and wetlands, useful for conservation and environmental planning. Terrestrial Ecological Systems represent recurring groups of plant communities that are found in similar physical environments and are influenced by similar dynamic ecological processes, such as fire or flooding. Our classification describes over 800 upland and wetland ecological system types found in the United States, and in adjacent portions of Mexico and Canada.Terrestrial ecological systems have formed the basis for map legends on national mapping efforts, including the inter-agency Landfire and Gap Analysis Program efforts. NatureServe ecologists have combined results of these efforts into a national map. Since terrestrial ecological systems are linked to the National Vegetation Classification, this national map information may be displayed at multiple levels of the National Vegetation Classification hierarchy. Current ecological systems descriptions can be accessed on our NatureServe Explorer website. Click on the “Ecological Communities and Systems” tab. Vector Vegetation Maps: CNPS and California Dept of Fish & GameThe principal goals of the Vegetation Program are to develop, promote, and maintain a uniform vegetation classification that will be adopted by private, state, and federal resource agencies with jurisdiction over land management, and to develop defensible definitions of the rare vegetation of the state.The CNPS Vegetation Program and Aerial Information Systems were contracted to produce a fine-scale vegetation map of the northern Sierra Nevada foothills with funding from the California Department of Fish and Game’s Wildlife Conservation Board, Resources Legacy Fund Foundation, and the Sierra Nevada Conservancy. The complete vegetation map, spanning across more than 2.6 million acres of the foothills from southern Shasta to northern Madera County, is now available. You can view the vegetation report here, or you can access it from the Reports page; You can also view this and other vegetation layers using the Department of Fish and Game’s BIOS Public Data Viewer. Directions for using this data viewer can be accessed hereNVC: National Vegetation Classification SystemThe Classification System is an FGDC standard through the physiognomic (first 5 levels). Work continues through the USGS-NPS Vegetation Mapping Program, in association with USGS/CSS (CBI), USGS/CSS (GAP), EPA (EMAP), U.S. Fish and Wildlife Service, National Park Service, NatureServe, The Nature Conservancy, Ecological Society of America (Vegetation Section), and the FGDC Vegetation Subcommittee on the floristic levels (lower 2 levels) of the standard. The lower levels of the Classification have several thousand cover types and associations to date. Work will continue for an indefinite period as new classes are proposed and existing classes are refined or aggregated. The previous NVC standard was adopted in 1997 (FGDC 1997) and the hierachy did not incorporate biogeography, but structure and phenology were emphasized at the highest levels. Officially the 1997 standard, the alliances and associations were not formally adopted, but the work on them has been supported through a variety or projects and NatureServe has worked intensively on those levels. NatureServe has maintained the hierarchy and serves that data through NatureServe Explorer.The new standard will bring over much of the content of the existing types, especially at the association level, but the hierachy is different enough that alliances will change. Groups and macrogroups in the new hierarchy will be closes to what you are interested in. The new structure incorporates biogeography indirectly through species composition shifts. So the new alliances will be informed by the existing alliances, but likely to split and be grouped. In fact that is likely to be the last level that settles down after the reworking from above and below. Associations should be most stable with changes occurring over time as new field data and analyses are run.

NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 3.0 https://doi.org/10.5066/P9Q9LQ4B. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using over twenty-five attributes and five feature classes representing the U.S. protected areas network in separate feature classes: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. Five additional feature classes include various combinations of the primary layers (for example, Combined_Fee_Easement) to support data management, queries, web mapping services, and analyses. This PAD-US Version 2.1 dataset includes a variety of updates and new data from the previous Version 2.0 dataset (USGS, 2018 https://doi.org/10.5066/P955KPLE ), achieving the primary goal to "Complete the PAD-US Inventory by 2020" (https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision) by addressing known data gaps with newly available data. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in PAD-US, along with continued improvements and regular maintenance of the federal theme. Completing the PAD-US Inventory: 1) Integration of over 75,000 city parks in all 50 States (and the District of Columbia) from The Trust for Public Land's (TPL) ParkServe data development initiative (https://parkserve.tpl.org/) added nearly 2.7 million acres of protected area and significantly reduced the primary known data gap in previous PAD-US versions (local government lands). 2) First-time integration of the Census American Indian/Alaskan Native Areas (AIA) dataset (https://www2.census.gov/geo/tiger/TIGER2019/AIANNH) representing the boundaries for federally recognized American Indian reservations and off-reservation trust lands across the nation (as of January 1, 2020, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey) addressed another major PAD-US data gap. 3) Aggregation of nearly 5,000 protected areas owned by local land trusts in 13 states, aggregated by Ducks Unlimited through data calls for easements to update the National Conservation Easement Database (https://www.conservationeasement.us/), increased PAD-US protected areas by over 350,000 acres. Maintaining regular Federal updates: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 2) Complete National Marine Protected Areas (MPA) update: from the National Oceanic and Atmospheric Administration (NOAA) MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; Other changes: 1) PAD-US field name change - The "Public Access" field name changed from 'Access' to 'Pub_Access' to avoid unintended scripting errors associated with the script command 'access'. 2) Additional field - The "Feature Class" (FeatClass) field was added to all layers within PAD-US 2.1 (only included in the "Combined" layers of PAD-US 2.0 to describe which feature class data originated from). 3) Categorical GAP Status Code default changes - National Monuments are categorically assigned GAP Status Code = 2 (previously GAP 3), in the absence of other information, to better represent biodiversity protection restrictions associated with the designation. The Bureau of Land Management Areas of Environmental Concern (ACECs) are categorically assigned GAP Status Code = 3 (previously GAP 2) as the areas are administratively protected, not permanent. More information is available upon request. 4) Agency Name (FWS) geodatabase domain description changed to U.S. Fish and Wildlife Service (previously U.S. Fish & Wildlife Service). 5) Select areas in the provisional PAD-US 2.1 Proclamation feature class were removed following a consultation with the data-steward (Census Bureau). Tribal designated statistical areas are purely a geographic area for providing Census statistics with no land base. Most affected areas are relatively small; however, 4,341,120 acres and 37 records were removed in total. Contact Mason Croft (masoncroft@boisestate) for more information about how to identify these records. For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual .

The primary function of the Nature Conservation Information System is to help the work of national parks and conservation authorities by providing a country-wide database and an application developed specifically for the needs of nature conservation professionals. In addition several pieces of information and many maps are produced within the system, which can be used to provide information for the general public. [ Modeling Paradigm: Other: please specify (e.g. EDSS, creative space, expert system etc) ] [ Model Ecosystem: Agriculture & apiculture (examples: arable farming, animal husbandry, horticulture, olive production, pollination, biofuels), Foresty (examples: coppicing, paper, timber, charcoal, cork), Tourism and access-based recreation (examples: rambling, climbing, skiing, boating, camping, golf, dog-walking, horse-riding), Biodiversity conservation (examples: protection, reserves, re-introduction, alien species), Heritage conservation (examples: archeology, buildings, site erosion) ]

This GIS data set represents the Wildlife Management Area system administered by the Florida Fish and Wildlife Conservation Commission (FWC). These data are intended as a general reference map only. More information on activities permitted in individual areas can be found from the links on FWC's Web site: http://www.myfwc.com/RECREATION/WMASites_index.htm

With the Nature Information System, you can get to know the diverse nature of Helsinki. The most important natural resources of the system are nature conservation sites, valuable flora and fauna sites, important bird areas, important bat areas, polypore sites and small water sites.

The data is available for download in several formats, including JSON, KML, CSV, Esri Shape, and XML. Available formats can always be found under OutputFormat in the GetCapabilities query for the service. More information and instructions on using the WFS API can be found in the guide (in Finnish).

The data published as open data in Helsinki’s nature information system consists of the following WFS interface levels, which are grouped into protected feature/ features to be protected, valuable nature features, water system data and other nature data. The data is in a form that can be opened with several geographic data programs.

Previewing the data in the map.hel.fi service:

• Springs locations
• Environment and nature related layers can be found on the website: https://kartta.hel.fi/ > Layers > Environment and Nature

Coordinate systems:

• Maintained in ETRS-GK25 (EPSG:3879)

API address:

• WMS API: https://kartta.hel.fi/ws/geoserver/avoindata/wms
• WFS API: https://kartta.hel.fi/ws/geoserver/avoindata/wfs

Layers:

• LTJ_open_value_capture targets
• LTJ_avoin_arvo_lahokaviosammal_organ batteries
• LTJ_avoin_arvo_lahokaviosammal_support areas
• LTJ_avoin_arvo_liitto_squirrel_habitat areas
• LTJ_avoin_arvo_liitto_squirrel_core areas
• LTJ_open_value_accurate_bat areas
• LTJ_open_value_target_bird areas
• LTJ_avoin_arvo_tarkeat_reptile_and_frog targets
• LTJ_open_valuable_geological_regional
• LTJ_open_valuable_geological_linear
• LTJ_open_valuable_plant sites
• LTJ_open_ecological_connections_2015
• LTJ_open_habitats_biotope data
• LTJ_open_habitats_vital
• LTJ_open_habitats_threatened
• LTJ_avoin_metsaverkko_2015
• LTJ_open_other_elain observations
• LTJ_avoin_other_nature sites
• LTJ_open_soothing_nature protection programme
• LTJ_open_soothed_natural monuments
• LTJ_open_soothed_nature reserves
• LTJ_open_soothed_Natura_regional
• LTJ_open_soothed_Natura_linear
• LTJ_open_soothed_protected_habitats
• LTJ_avoin_vesi_bays
• LTJ_avoin_vesi_lampit
• LTJ_avoin_vesi_puroja_ja_lampi_valuma_areas
• LTJ_avoin_vesi_purot

The data of the public version and open data of the Nature Information System has been filtered for nature protection reasons. The official version of the Nature Information System must be used for planning and research purposes.

Local nature conservation sites (LNCS) is a non-statutory designation given by local authorities to areas of locally important nature and landscapes. NatureScot, on behalf of the Local Nature Conservation Sites Working Group, published guidance (https://www.nature.scot/professional-advice/protected-areas-and-species/protected-areas/local-designations/local-nature-conservation-sites) for local authorities on the establishment and management of LNCS systems in Scotland.

This paper applies the IUCN Global Standard for Nature based Solutions™ self-assessment tool (published in 2020) to two aquaculture case studies. Data from the case studies were compiled by the authors. In Zanzibar, secondary data were obtained through a previous project, which included a stakeholder workshop in Zanzibar (in 2019) and one deliverable published by the IUCN on Zanzibar of their catalogue “Aquaculture and Marine Conservation”. In Indonesia, the original data were provided by the Blue Natural Capital Funding Facility (BNCFF) and the associated local teams. The analysis of the data, the information provided, and the scoring itself were done by the authors, in association with local teams in both areas. The results of the two assessments, discussed in the paper and presented in detail in the Supplementary materials, can be considered original research, never previously published in a scientific journal. The concept of Nature-based Solutions (NbS) was proposed by the International Union for Conservation of Nature (IUCN) to protect, restore, and sustainably manage natural and modified ecosystems for achieving a variety of societal benefits. The IUCN released the IUCN Global Standard for NbS™ to help design, assess, strengthen, and upscale NbS interventions. In the current context of growing uncertainties for the future of coastlines and oceans, aquaculture has been recognized as a positive activity for achieving sustainable development in coastal communities; supporting food security, poverty alleviation, and economic resilience; and contributing to the conservation of marine ecosystems in some cases. However, the sustainability of aquaculture systems has often been criticized. Aquaculture initiatives in coastal areas can achieve both nature conservation and sustainable development objectives, but reflection on the conditions under which this would happen is needed. This article examines aquaculture systems through the lens of the NbS concept and the IUCN Global Standard for NbS™, along with other sustainability concepts and instruments currently used in the context of aquaculture. The application of the IUCN Global Standard for NbS™’s to two case studies is explored: seaweed farming in Zanzibar in marine conservation areas and shrimp farming coupled with mangrove restoration in Indonesia. The results show that the NbS concept underpinning the IUCN Global Standard for NbS™ could help in the overall assessment of aquaculture systems and improve their sustainability by highlighting both their positive outcomes and issues requiring further examination in relation to marine biodiversity benefits, socio-economic development, and/or governance. The IUCN Global Standard for NbS™ could provide an operational framework to implement existing concepts, such as the Ecosystem Approach to Aquaculture, contribute to clarifying critical issues in aquaculture development, and provide guidance for the development of a new type of aquaculture project, specifically designed as NbS. This finding advocates the context-dependent exploration and promotion of aquaculture projects as NbS.

This dataset is from a master's group thesis project at The Bren School of Environmental Science & Management at the University of California, Santa Barbara, and contains the final written report only (see below for the associated dataset containing the project analyses and data packages). The graduate student researchers who completed this project include: Tess Hooper, Daphne Virlar-Knight, Priscilla Hare, Robert Heim, and Jessica Gomez. This project, titled "Managing the Impacts of Environmental Education on Nature Preserves", focused on analyzing the potential ecological impacts that environmental education programming may have on sensitive plant and wildlife species on the Dangermond Preserve. Through mapping areas with sensitive plant and wildlife habitat, the group ranked environmental education trails on the preserve based on ecological impact. They also created a management tool that The Nature Conservancy can use to select trails that provide educational opportunities while reducing impacts to native biodiversity. Notably, the data indicates that all 12 education trails on the preserve pass through areas of low and high ecological impact, and that the best trail depends on each school group’s needs and The Nature Conservancy’s conservation goals. This project intends to help The Nature Conservancy manage its education programs on the Dangermond Preserve, and offers an approach that other land managers can use to inform decisions about balancing the trade-offs of environmental education in biologically diverse areas. The raw data used in the spatial analyses came from The Nature Conservancy and the following open source databases: 1. California Wildlife Habitat Relationship Systems 2. State Soil Geographic (STATSGO2) Data Base for California 3. 2014 California Basin Characteristic Model Downscaled Climate and Hydrology (30-year summaries) 4. Consortium of California Herbaria Analyses were conducted using ArcGIS, MaxENT, and RStudio. The project began in April 2019 and ended in June 2020. To access data files associated with this project, visit the dataset titled Managing the Ecological Impacts of Environmental Education on the Dangermond Preserve, The Bren School, University of California Santa Barbara, 2019-2020"

By the mid-1900s the guanaco (Lama guanicoe) approached extinction in southern South America due to habitat destruction and hunting. In order to maintain the ecological prominence of this iconic species, as well as assist in the management of populations that are emerging economically while increasing in conservation value, accurate and potentially rapid estimates of effective population size (Ne) (demographic and/or genetic) are essential. Estimates of Ne generally focus on the genetic effective population size; however, we posited that both parameters may be necessary to provide more accurate and timely estimates. Therefore, we examined the performance of three demographic and four genetic estimators of Ne of guanacos in Torres del Paine National Park, Chile, at different years and time intervals between 1987 and 1997. We compared our estimates with census estimates of the adult population size (Nac) during the same time period. Average Ne/Nac ratios of demographic estimates varied between 0.04 and 0.99 of the adult census size. Genetic estimates varied between 0.02 and 0.08 of the adult census size. Based upon group composition and population size (n = 82) of guanacos in 1975, the number of breeding adults was 44 animals. Mean Ne of the single-sample and temporal genetic estimators was 43.1, and 34.3, respectively; estimated Ne of one of the demographic estimators was 41. Our findings suggest that intermittent genetic estimates of Ne (via fecal samples, carcasses, blood collection during capture, and/or other non-invasive methods) can provide crucial information regarding the genetic integrity of increasingly isolated populations of wild South American camelids. Considering the overall performance of these estimators, and differences in how each functions, we recommend an integrative approach using both genetic and demographic estimators, to evaluate Ne for the wild South American camelids and other species with polygynous mating systems.

All protected areas, which are elements of the KSOCh (national system of protected areas): nature reserves, national parks, landscape park and areas of protected landscape, have been verified in 2002. The list of protected areas is based on the reports on protected areas in natural units of space delineated on the basis of geomorphic characteristics.