Diazo copy of Hubbard Brook Watershed Map generated stereophoto- grammetrically based on May, 1956 aerial photography. Shows New Hampshire state plane coordinate system reference points which were projected into UTM Zone 19 and used as reference tics. The experimental forest boundary was manually digitized. The eastern boundary was truncated by a new boundary delineated on a paper diazo copy of the Hubbard Brook Watershed Map supplied by Wayne Martin of the USFS. Data distributed as shapefile in Coordinate system EPSG:26919 - NAD83 / UTM zone 19N.

Initializing forest landscape models (FLMs) to simulate changes in tree species composition requires accurate fine-scale forest attribute information mapped contiguously over large areas. Nearest-neighbor imputation maps have high potential for use as the initial condition within FLMs, but the tendency for field plots to be imputed over large geographical distances results in species frequently mapped outside of their home ranges, which is problematic. We developed an approach for evaluating and selecting field plots for imputation based on their similarity in feature-space, their species composition, and their geographical distance between source and imputation to produce a map that is appropriate for initializing an FLM. We applied this approach to map 13m ha of forest throughout the six New England states (Rhode Island, Connecticut, Massachusetts, New Hampshire, Vermont, and Maine). The map itself is a .img raster file of FIA plot CN numbers. To access FIA data from this map, one has to link the mapcodes in this map to FIA data supplied by USDA FIA database (http://apps.fs.fed.us/fiadb-downloads/datamart.html).

This data package contains 3 GIS layers showing generalized forest types across New England as delineated in older forestry publications. These were digitized so that they can be used to illustrate broad vegetation patterns across the region in modern publications. These GIS layers include maps drawn by Hawley and Hawes (1912), RT Fisher (1933), and Westveld and the Committee on Silviculture, New England Section, Society of American Foresters (1956).

Private map (managed forest code 50) used in the Story Map of Forest Management in Canada, 2017.Private lands were identified using provincial and territorial land ownership datasets. Detailed ownership datasets were not available in all jurisdictions, so proxies were used where necessary. In Saskatchewan, lands south of the province's Commercial Forest Zone were classified as Private. This includes some Crown lands, but these are generally small and not included in forest management plans or leased for commercial forestry purposes.Source: This web map shows the private areas used in the map of forest management in Canada, 2017 and includes the following tiled layer:Private (Managed Forest Code 50)Data provided by Alberta Agriculture and Forestry; British Columbia Ministry of Forests; Manitoba Sustainable Development; Natural Resources Canada; New Brunswick Department of Energy and Resource Development; Newfoundland & Labrador Department of Fisheries and Land Resources; Northwest Territories Department of Environment and Natural Resources; Nova Scotia Department of Lands and Forestry; Ontario Ministry of Natural Resources and Forestry; Prince Edward Island Department of Communities, Land & Environment; Québec Ministère des Forêts, de la Faune et des Parcs; Saskatchewan Ministry of Environment; and Yukon Energy, Mines and Resources.

Background 1996-2000: The PNG Forestry Authority (PNGFA) with support from CSIRO developed the Forest Inventory Mapping (FIM) System to specifically map forest and vegetation types using forest mapping units or boundaries (or FMU) derived from aerial photography in 1973-4 at 1:100,000 scale and other relevant map overlays.

Source: "Map of The Adirondack Forest Preserve And Adjoining Territory, State Forest Commission, 1893" on file at The Adirondack Museum, Blue Mountain Lake, NY.

Depicts the 1892 boundary of the Adirondack Park, also know as the Blue Line. Adirondack Park Agency staff visually transferred the historic boundary to a 1:250,000 scale map using Great Lot Lines as reference. Boundaries are approximate. Reviewed as of September 2020.

The nature management plan for the province of Utrecht 2024-2025 indicates for which areas outside NNN a subsidy may be requested for the construction of new forest. Map 1 'Search area forest outside NNN' is based on this dataset.

Description

This dataset explores threats to New Caledonia's forests, focusing on the probability of deforestation within hotspots of tree community diversity.

The probability of deforestation was derived from the "Spatial scenario of tropical deforestation and carbon emissions for the 21st century" (Vielledent et al., 2023), available as downloadable GeoTIFFs for New Caledonia for the years 2050 and 2100

Hotspots of tree community diversity were identified using the 'Core Forest' class extracted from the dataset 'Classification of New Caledonia Forests According to Edge and Elevation Effects'. Core forest are defined as forest areas located more than 300 meters from the forest edge, characterized by potentially richer tree communities.

To assess habitat quality, each core forest fragment was surrounded by a 500-meter buffer zone. We evaluated forest habitat metrics including forest cover, forest type distribution, and fragmentation index within these buffer zones. Additionally, we analyzed the areas of forest threatened by deforestation in 2050 and 2100. The resulting maps provide decision-making support for stakeholders involved in conserving New Caledonia's forests. The fragmentation index used is the effective mesh size (meff), originally proposed by Jaeger (2000) and updated by Moser and al. (2007) to address boundary effects. A higher index value indicates less fragmented forest.

Content

This dataset was generated, analyzed, and validated using a suite of open-source software tools, including QGIS, PostgreSQL, PostGIS, Python, and the GDAL library, operating on a Linux platform. The compressed file includes six essential files formatted for an ESRI GIS system, utilizing the WGS84 international coordinate system. It is compatible for upload into spatial databases such as PostgreSQL/PostGIS.

Each entry in the attribute table represents a buffer area containing one or several core forests, with the following fields (restricted to 10 characters):

Field Type Description

id_buffer INTEGER Unique identifier for the buffer

area_ha NUMERIC (2 DECIMALS) Area of the buffer in hectares

frag_index NUMERIC Forest fragmentation meff index within the buffer

forest_cov NUMERIC (2 DECIMALS) Proportion of forest within the buffer area (%)

edge_r NUMERIC (2 DECIMALS) Proportion of forest area classified as edge forest (%)

mature_r NUMERIC (2 DECIMALS) Proportion of forest area classified as mature forest (%)

core_r NUMERIC (2 DECIMALS) Proportion of forest area classified as core forest (%)

defor_2050 NUMERIC (2 DECIMALS) Proportion of forest threatened by deforestation in 2050 (%)

defor_2100 NUMERIC (2 DECIMALS) Proportion of forest threatened by deforestation in 2100 (%)

pn BOOLEAN True or False, indicating if the polygon overlaps with the Northern province

ps BOOLEAN True or False, indicating if the polygon overlaps with the Southern province

Limitations

This analysis of forest conservation issues aims to foster dialogue between forest ecologists and forest management strategies in New Caledonia. It should not be applied blindly based solely on the few quantitative variables proposed.

Various scenarios can utilize these metrics, and we urge managers to initially define conservation objectives (such as maximizing biodiversity, reducing fragmentation, restoring disturbed environments, etc.) and consider constraints (such as accessibility, budget, feasibility, etc.) before utilizing this dataset.

While threats was projected for future scenarios, conservation efforts should also prioritize preserving forests in their current state, including addressing increasing fragmentation and biodiversity loss. We encourage users to explore these metrics and their correlation with other quantitative or qualitative variables to gain a deeper understanding of conservation challenges in New Caledonia's forests.

Bedrock Geologic Map of Hubbard Brook Experimental Forest and maps of fractures and geology in roadcuts along Interstate-93, Grafton County, New Hampshire. Two maps are included in this data set. Interstate I-93 map includes plots summarizing data for fractures shown on map roadcuts. Citation: Barton, C. C., R. H. Camerlo and S. W. Bailey. 1997. Bedrock Geologic Map of Hubbard Brook Experimental Forest and maps of fractures and geology in roadcuts along Interstate-93, Grafton County, New Hampshire. Sheet 1, Scale 1:12,000; Sheet 2, Scale 1:200. U.S. Geological Survey, Miscellaneous Investigations Series, Map I-2562 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

This dataset created by the University of Sydney, includes time series digital soil map products of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Modelling was completed using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Products provide estimates of SOC concentrations and associated trends through time. Also important covariates required to drive this spatio-temporal modelling are identified using the Recursive Feature Elimination algorithm (RFE), which including a range of predictors that vary in space, time and space and time. \r \r Full description of the digital soil maps and methods are presented in:\r Moyce MC, Gray JM, Wilson BR, Jenkins BR, Young MA, Ugbaje SU, Bishop TFA, Yang X, Henderson LE, Milford HB, Tulau MJ, 2021. Determining baselines, drivers and trends of soil health and stability in New South Wales forests: NSW Forest Monitoring & Improvement Program, Final report v1.1 for NSW Natural Resources Commission by NSW Department of Planning, Industry and Environment and University of Sydney. \r \r The metadata's data packages section includes project scripts and code, final project report and an external Cloudstor link to download the predicted SOC map products, \r

Multi-Agency Ground Plot (MAGPlot) database (DB) is a pan-Canadian forest ground-plot data repository. The database synthesize forest ground plot data from various agencies, including the National Forest Inventory (NFI) and 12 Canadian jurisdictions: Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Northwest Territories (NT), Ontario (ON), Prince Edward Island (PE), Quebec (QC), Saskatchewan (SK), and Yukon Territory (YT), contributed in their original format. These datasets underwent data cleaning and quality assessment using the set of rules and standards set by the contributors and associated documentations, and were standardized, harmonized, and integrated into a single, centralized, and analysis-ready database. The primary objective of the MAGPlot project is to collate and harmonize forest ground plot data and to present the data in a findable, accessible, interoperable, and reusable (FAIR) format for pan-Canadian forest research. The current version includes both historical and contemporary forest ground plot data provided by data contributors. The standardized and harmonized dataset includes eight data tables (five site related and three tree measurement tables) in a relational database schema. Site-related tables contain information on geographical locations, treatments (e.g. stand tending, regeneration, and cutting), and disturbances caused by abiotic factors (e.g., weather, wildfires) or biotic factors (e.g., disease, insects, animals). Tree-related tables, on the other hand, focus on measured tree attributes, including biophysical and growth parameters (e.g., DBH, height, crown class), species, status, stem conditions (e.g., broken or dead tops), and health conditions. While most contributors provided large and small tree plot measurements, only NFI, AB, MB, and SK contributed datasets reported at regeneration plot level (e.g., stem count, regeneration species). Future versions are expected to include updated and/or new measurement records as well as additional tables and measured and compiled (e.g., tree volume and biomass) attributes. MAGPlot is hosted through Canada’s National Forest Information System (https://nfi.nfis.org/en/maps). --------------------------------------------------- LATEST SITE TREATMENTS LAYER: --------------------------------------------------- Shows the most recently applied treatment class for each MAGPlot site. These treatment classes are broad categories, with more specific treatment details available in the full dataset. ----------- NOTES: ----------- The MAGPlot release (v1.0 and v1.1) does not include NL and SK datasets due to pending Data Sharing Agreements, ongoing data processing, or restrictions on third-party sharing. These datasets will be included in future releases. While certain jurisdictions permit open or public data sharing, given that requestor signs and adheres the Data Use agreement, there are some jurisdictions that require a jurisdiction-specific request form to be signed in addition to the Data Use Agreement form. For the MAGPlot Data Dictionary, other metadata, datasets available for open sharing (with approximate locations), data requests (for other datasets or exact coordinates), and available data visualization products, please check all the folders in the “Data and Resources” section below. Coordinates in web services have been randomized within 5km of true location to preserve site integrity Access the WMS (Web Map Service) layers from the “Data and Resources” section below. A data request must be submitted to access historical datasets, datasets restricted by data-use agreements, or exact plot coordinates using the link below. NFI Data Request Form: https://nfi.nfis.org/en/datarequestform --------------------------------- ACKNOWLEDGEMENT: --------------------------------- We acknowledge and recognize the following agencies that have contributed data to the MAGPlot database: Government of Alberta - Ministry of Agriculture, Forestry, and Rural Economic Development - Forest Stewardship and Trade Branch Government of British Columbia - Ministry of Forests - Forest Analysis and Inventory Branch Government of Manitoba - Ministry of Economic, Development, Investment, Trade, and Natural Resources - Forestry and Peatlands Branch Government of New Brunswick - Ministry of Natural Resources and Energy Development - Forestry Division, Forest Planning and Stewardship Branch Government of Newfoundland & Labrador - Department of Fisheries, Forestry and Agriculture - Forestry Branch Government of Nova Scotia - Ministry of Natural Resources and Renewables - Department of Natural Resources and Renewables Government of Northwest Territories - Department of Environment & Climate Change - Forest Management Division Government of Ontario - Ministry of Natural Resources and Forestry - Science and Research Branch, Forest Resources Inventory Unit Government of Prince Edward Island - Department of Environment, Energy, and Climate Action - Forests, Fish, and Wildlife Division Government of Quebec - Ministry of Natural Resources and Forests - Forestry Sector Government of Saskatchewan - Ministry of Environment - Forest Service Branch Government of Yukon - Ministry of Energy, Mines, and Resources - Forest Management Branch Government of Canada - Natural Resources Canada - Canadian Forest Service - National Forest Inventory Projects Office

This is the web map for the Resources Viewer web experience that is on the Forestry GIS hub site. This map is intended to show the public locations of current and old sales, as well as upcoming sales. This map serves as a resource for public for be able to see proposed sales and may submit public comment based off the information in this map.

Wildlands in New England is the first U.S. study to map and characterize within one region all conserved lands that, by design, allow natural processes to unfold with no active management or intervention. These “forever wild lands” include federal Wilderness areas along with diverse public and private natural areas and reserves. Knowing the precise locations of Wildlands, their characteristics, and their protection status is important as both a baseline for advancing conservation initiatives and an urgent call to action for supporting nature and society. Wildlands play a unique role in the integrated approach to conservation and land planning advanced by the Wildlands, Woodlands, Farmlands & Communities (WWF&C) initiative, which calls for: at least 70 percent of the region to be protected forest; Wildlands to occupy at least 10 percent of the land; and all existing farmland to be permanently conserved. This research was conducted by WWF&C partners Harvard Forest (Harvard University), Highstead Foundation, and Northeast Wilderness Trust, in collaboration with over one hundred conservation organizations and municipal, state, and federal agencies. This dataset contains the Geographical Information System (GIS) polygon layer of Wildlands created by this project and used in all analyses for the 2023 report. Another GIS layer will be updated as new Wildlands are brought to our attention or created and will be available at https://wildlandsandwoodlands.org/ for researchers.

Polygon boundaries differentiating forest cover types located on State Forest lands.Service is updated as needed.For additional information see https://www.dec.ny.gov/lands/4972.html

This data set is a condensed forest cover type digital map of Saskatchewan and is a product of the Saskatchewan Environment and Resource Management, Forestry Branch - Inventory Unit (SERM-FBIU). This map was generalized from SERM township maps of vegetation cover at an approximate scale of 1:63,000 (1 in. = 1 mile). The cover information was iteratively generalized until it was compiled on a 1:1,000,000 scale map base. This data set was prepared by SERM-FBIU. The data is a condensed forest cover type map of Saskatchewan at a scale of 1:1,000,000.

This data set is the Former Soviet Union (FSU) portion of the Generalized World Forest Map (WCMC, 1998), a 1-kilometer resolution generalized forest cover map for the land area of the Former Soviet Union. There are five forest classes in the original global generalized map. Only two of those classes were distinguished in the geographical portion comprising the FSU.

The bedrock geology of the Hubbard Brook Experimental Forest, Grafton County, New Hampshire is described in this report of new field investigation. The database includes contacts of bedrock geologic units, faults, folds, and other structural geologic information, as well as the base maps on which the mapped geological features are registered. This report supersedes Barton (1997).

Ecosystem services offer a lens through which you can view the landscape and its natural resources. This lens may be helpful for those wanting to consider environmental impacts when needing to prioritize areas for management, restoration planning, urban planning, conservation and/or development.The goal of this map is to identify ecosystem services throughout New Hampshire as defined by the following:For the purposes of this project, ecosystem services can be thought of as:The ability to produce clean water (source: USFS Forest to Faucet database)Landscapes (geology, soil, climate etc.) that support biodiverse flora and fauna (source: TNC Resilient & Connected Landscapes --Resilient & Connected Network layer, NH Fish & Game WAP Tiers)Habitat for wildlife protection in order to live and reproduce (source: NH Fish & Game WAP Tiers)Connectivity for wildlife movement and migration in a changing climate (source: TNC Resilient & Connected Landscapes, Proximity to conserved & public lands)

Each of the inputs (water, wildlife tiers, resilient & connected network, and proximity to conserved & public lands) were given equal weight in the model design. Scores ranked from 2-15. Relative Rank was binned into Low, Moderate, and High categories. By selecting an area on the map, you can see the score and rank for that area as well as the inputs for how those were determined.This map of information is intended to guide regional decision making related to the above criteria and can be combined with other data to create a fuller picture for the users' needs. Please note, in highly urbanized areas and at very local scale, this map should be interpreted with caution. Not intended for city-level planning.For more information, please contact the NH Division of Forests & Lands (Dept of Natural & Cultural Resources).

This dataset consists of tick sampling and microclimate data from Exmoor, Richmond and New Forest study sites; as well as ARCGIS risk maps that model tick abundance driven by climate surfaces and host abundance. Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Many people take pleasure from activities in forests and wild lands in the UK and others are being encouraged to participate. Unfortunately, there are risks and one of the most insidious is the possibility (albeit tiny) of acquiring a disease from wild animals; for example, ticks can be vectors of the bacterial infection leading to Lyme Disease. Both diagnosis and treatment can be problematic so prevention of acquiring such disease is highly desirable. Surprisingly little is known about how best to warn countryside users about the potential for disease without scaring them away or spoiling their enjoyment. Answering such questions was the goal of this project, and required the integration of a diverse set of scientific skills, and an understanding of the views of those who manage countryside, those who have contracted zoonotic diseases and those who access the land. This project combined knowledge from three strands of work, namely risk assessment, risk perception and communication, and scenario analysis. The study sites were selected to provide a range of environmental conditions and countryside use. Peri-urban parkland, accessible lowland forest and heath and remote upland forest were chosen as represented by Richmond Park on the fringe of Greater London, the New Forest in Southern England, and Exmoor in South West England. The following additional data from this same research project are available at the UK Data Archive under study number 6892 (see online resources): Lyme disease risk perception data resulting from tick imagery vignette experiments, Lyme disease patient interviews and surveys, residents and countryside staff focus groups, forest manager interviews, and multiple scoring procedures of animal social representation; as well as Lyme and tick risk communication data resulting from interviews with organisations and content analysis of risk warning information leaflets, Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

This dataset includes four soil products using an empirical approach to assess soil condition indicators and complete a data gap analysis covering the Regional Forest Agreement regions of eastern NSW. \r \r In the empirical analysis, maps presented soil indicator values of topsoil pH, organic carbon and emerson aggregate stability for each of the 2162 soil map units, based on the unit's most representative soil profile available within the Soil and Land Information System (SALIS). Maps reflect values when the sampling occurred with temporal changes not being accounted for and used the 2008 woody vegetation coverage as the baseline extent. The dataset identifies the locations where data is missing or of poor quality, providing a confidence rating map as part of the evaluation process. \r \r Full description of the empirical maps and methods are presented in:\r Moyce MC, Gray JM, Wilson BR, Jenkins BR, Young MA, Ugbaje SU, Bishop TFA, Yang X, Henderson LE, Milford HB, Tulau MJ, 2021. _Determining baselines, drivers and trends of soil health and stability in New South Wales forests: NSW Forest Monitoring & Improvement Program_v1.1, Final report for NSW Natural Resources Commission by NSW Department of Planning, Industry and Environment and University of Sydney.