This repository contains hydrologic data collected at the Fenton Tract Research Forest. The purpose of these data are to understand hydrologic flowpaths through forest soils and to study the impact of forest cover of local and regional hydrologic fluxes.

Meteorological Data - Fenton Tract Isotopes: contains precipitation, groundwater, and stream isotopic measurements.

Hemlock Site - Hemlock Site GW: 15-minute groundwater elevation data recorded in the riparian hemlock site adjacent to the Fenton River - Hemlock Site Soil VWC: Soil volumetric water content measurements in the riparian hemlock site adjacent to the Fenton River - Hemlock Site Soil Xylem Isotopes: 2H and 18O measurements of soil and xylem water isotopic ratios in the riparian hemlock site adjacent to the Fenton River - Hemlock Site CVE: Cryogenic Vacuum Extraction notes for soil and xylem samples - Hemlock tree core relative water content and turgid water contents for 2H correction - Hemlock Site Root Profiles - three root profiles measured across the hemlock site - Hemlock Site - tree characteristics (DBH, elevation, distance from stream, location)

Maple Sites (Sites A and B) - tree heights and diameters from subplots - root mass distribution - Soil and xylem water isotopic compositions - soil Volumetric Water Content (VWC)

Rehydration - Tree core rehydration experimental results showing 2H and 18O enrichment during CVE using cores collected across the Fenton Tract

Time-of-Day Analysis - Tree core xylem water isotopic compositions (2H and 18O) for oak and maple trees sampled in the AM and PM.

Sites A, B and C - 2H and 18O measurements of soil and xylem water isotopic ratios - soil Volumetric Water Content (VWC) - Whole tree transpiration (mm/day) - Tree characteristics (DBH, Height, basal area)

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). TREE MEASUREMENTS WFS LAYERS: Shows the distribution of measured trees, with each point representing multiple / stacked trees that have been measured at a site location SITES SUMMARY WMS & WFS LAYER: Shows the distribution of magplot sites nationwide, with each point representing the location of a site. NOTES: The MAGPlot release (v1.0.0 and v1.1.0) 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 WFS (Web Feature Service) and WMS (Web Map Service) layers from the “Data and Resources” section below. Sample WFS requests to download MAGPlot data without a GIS client are available in the supplementary materials package linked 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 ACKNOWLEDGEMENTS: 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

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, domain-specific databases, and the top journals compare how much data is in institutional vs. domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

The Knowledge Repository for Non-Wood Forest Products is a collection of information on innovation about non-wood forest products gathered from experts and practitioners during the INCREDIBLE project. It brings together, in a single platform, knowledge about cork, pine oleoresin, wild mushrooms & truffles, aromatic & medicinal plants and wild nuts & berries, around various themes, from Portugal, Spain, France, Italy, Croatia, Greece and Tunisia.

Each piece of knowledge is summarised in a factsheet, that can concern one or several non-wood forest products, as some issues or solutions are transversal. The factsheets can either contain practical knowledge (success stories, good practices, technical reports) or more theoretical or academic results (research results, databases, policies). The factsheets can also be identified by the position in the value chain to which the knowledge applies, from forestry to end-consumers.

The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102).

This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).

The raw data from the forest inventory correspond to the set of data collected in the forest (including population) in metropolitan territory by IWT field officers. These data cover the characteristics of inventory plots (6,000 per year), tree measurements and observations (60,000 per year), and eco-floristic data. The geographical coordinates of the plots are provided to the nearest kilometre.

Discerning whether certain timber species were harvested from natural forests versus less restricted planted forests can help ascertain the legality of wood products that enter the global market. However, readily available global planted forest data to the species level have been scarce. We confronted the need for such data by developing a two-pronged dataset, consisting of ‘polygon’ and ‘non-polygon’ location-based data, collectively, Planted Forest Timber Data. We obtained the polygon data from the World Resources Institute’s Spatial Database of Planted Trees v2.0, extracting data specific to traded timber species. We derived the non-polygon data from peer-reviewed literature and government documents. The polygon dataset encompasses 27 countries and 253 species and the non-polygon dataset spans 91 countries and 447 species. The polygon data are stored among 27 geopackages, one for each country. Each summarized row of polygon data contains up to 13 possible fields. The non-polygon data..., The Planted Forest Timber Data is composed of two types of information, polygon and non-polygon data, divided into two distinct living datasets. The polygon dataset includes visual delineations of the planted forest boundaries. These data are organized into GeoPackages with an accompanying summary table that links the collective data together. The planted forest plots in the non-polygon dataset do not have delineated boundaries, but still have species information at least at the country level. The polygon dataset is composed of a subset of the Spatial Database of Planted Trees v2.0, specifically the portion of data that pertained to tree species commonly associated with the timber trade. We used government Lacey Act data and the Botanic Gardens Conservation International’s Working List of Commercial Timber Species to identify and isolate the species that qualify as timber. We also calculated the area of each planted forest plot. We assembled the non-polygon dataset by querying scientifi..., , # Global planted forest data for timber species

Access the polygon dataset on Zenodo (https://zenodo.org/records/14010483) Access the non-polygon dataset on Dryad (https://doi.org/10.5061/dryad.2280gb626) Access the article associated with the polygon and non-polygon datasets on Nature (https://doi.org/10.1038/s41597-024-04125-y)

The Planted Forest Timber Data (PFTD) consists of two living datasets, polygon and non-polygon. These data include planted forest plots for timber to the species level, with locations at least to the country level. Between the two datasets, the planted forests range from small experimental plots to large commercial operations. The polygon data includes visual delineations of the planted forest boundaries. The non-polygon data lack delineated boundaries but have species information at least at the country level. The data were obtained...,

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 DISTURBANCES LAYER:

Shows the most recently recorded disturbance class at each MAGPlot site. These disturbance classes are broad categories, with more detailed disturbance types 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 repository includes output data from the following article:

Vieilledent G., C. Grinand, F. A. Rakotomalala, R. Ranaivosoa, J.-R. Rakotoarijaona, T. F. Allnutt, and F. Achard. Combining global tree cover loss data with historical national forest-cover maps to look at six decades of deforestation and forest fragmentation in Madagascar.

This repository includes Madagascar forest cover (forXXXX.tif), forest density (fordensXXXX.tif), distance to forest edge (dist_edge_XXXX.tif) and forest fragmentation index (fragXXXX.tif) for the years 1953, 1973, 1990, 2000, 2005, 2010 and 2014. Data are available as GeoTIFF raster files at 30m resolution in the UTM 38S projection (EPSG:32738).

The data in this repository is available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

This repository includes two datasets. The first is a collection of polygons covering mines globally and the associated forest cover loss from 2000 to 2019. The polygons were derived by merging the "global-scale mining polygons version 2" (Maus et al., 2022) and mining and quarry polygon features extracted from the OpenStreetMap database (OpenStreetMap contributors, 2017). To remove double counting of areas the overlaps between the datasets were resolved by uniting intersecting features into single polygon features, i.e. keeping only the external borders of intersecting features. A random visual check was conducted, and a few small manual editing of polygons was performed where errors were identified.

The resulting dataset is encoded as a Geopackage in the file 'global_mining_polygons.gpkg'. The GeoPackage includes a single layer with 192,584 entries called 'mining_polygons' with the following attributes:

• id unique feature identifier
• isoa3 ISO 3166-1 alpha-3 country codes
• country country names
• area area of the polygon in squared kilometres
• geom the geometry of the features in geographical coordinates WGS84

The second dataset provides annual time series of global tree cover loss within mines from 2000 to 2019, covering all polygons in the above dataset. The area of tree cover loss for each polygon was calculated from the Global Forest Change database (Hansen et al., 2013). Each polygon also has additional string attributes with biomes derived from Ecoregions 2017 ^{© Resolve} (Dinerstein et al., 2017) and the level of protection derived from The World Database on Protected Areas (UNEP-WCMC and IUCN, 2022).

This dataset is encoded in CSV format in the file 'global_mining_forest_loss.csv', which includes 416,412 entries and 53 variables, such that:

• id unique feature identifier
• id_hcluster unique feature identifier
• list_of_commodities a comma-separated list of commodities
• isoa3 ISO 3166-1 alpha-3 country codes
• country country names
• ecoregion ecoregion name
• biome biome name
• year the year
• area_forest_loss_XXX_YYY

The values of tree cover loss are disaggregated per initial percentage of tree cover (XXX) and per protection level (YYY).

• XXX can take one of:
  • 000: total tree cover loss independently from the initial tree cover
  • 025: tree cover loss on pixels with initial tree cover between 0 and 25%
  • 050: tree cover loss on pixels with initial tree cover between 25 and 50%
  • 075: tree cover loss on pixels with initial tree cover between 50 and 75%
  • 100: tree cover loss on pixels with initial tree cover between 75 and 100%
• YYY can take one of:
  • la: tree cover loss within strict nature reserve
  • Ib: tree cover loss within wilderness area
  • II: tree cover loss within national park
  • III: tree cover loss within natural monument or feature
  • IV: tree cover loss within habitat/species management area
  • V: tree cover loss within protected landscape/seascape
  • VI: tree cover loss within PA with sustainable use of natural resources
  • p: tree cover loss within any type of protection, including not applicable, not assigned, or not reported
  • none: when YYY is omitted, total tree cover loss within the polygon

For details about the protection levels definition see the UNEP-WCMC and IUCN (2022). The id can be used to link polygons to forest loss data.

The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102). This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).

Detailed documentation of the CTFS MySQL database for handling data from repeated measurements of forest census plots is available to the public at this SI Library web site. This supports the published article cited below, available at http://ctfs.arnarb.harvard.edu/Public/pdfs/ConditEtAl_FORECO2014.pdf. The Barro Colorado plot database is available to the public and can be downloaded in full from another Smithsonian archive (http://dx.doi.org/10.5479/data.bci.20130603). The documentation support a published article describing the database and its purpose (citation below).

Lib4RI analyzed publication data in the institutional repository of the Swiss Federal Institute for Forest, Snow and Landscape Research (DORA WSL, https://www.dora.lib4ri.ch/wsl/) covering the years 2019 to 2022. This analysis aims to produce absolute figures on the proportion of open and closed scientific publications authored by researchers affiliated with the Swiss Federal Institute for Forest, Snow and Landscape Research as part of the annual survey 2023 conducted by the Swiss Open Access Monitor (Repository Monitor, https://oamonitor.ch/charts-data/repository-monitor/).
The analysis covered four resource types: journal articles, books, book chapters, and conference papers. Only basic Open Access status is considered, based on the availability of full text (open | closed) in DORA WSL. Publications under embargo at the time of data collection are classified as closed.

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).

SITES LEADING GENUS BY STEM COUNT LAYER:

Shows the leading genus at each site for the most recently measured year, determined by counting the number of stems of each genus type.

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) 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

### Data and code for "increasing aridity causes larger and more severe forest fires across Europe"

This repository holds code and data for the publication in GCB entitled: Increasing aridity causes larger and more severe forest fires across Europe (manuscript accepted)

# scripts

all scripts are in the folder "lib". In order to perform the full analysis, please follow through all scripts.
we provide the results of some steps in order to reduce runtime for the user. we indicate this in the headings of the scripts.

1. in the first script we prepare the ERA5-Land data. The code for the download is provided.
The user needs a CDS API for downloading.

2. the data from the ERA5-Land summer VPD is extracted for the fire complexes

3. calculation of the maximum fire size to total burned area relationship

4. the models are calibrated and compared. In this script the figure 3 and 4 are created

5. preparation of the future climate dataset. Again, the script for the download is provided but the user needs an API.

6. Extraction of the CMIP6 VPD.

7. Future climate analysis

8. Plotting of all figures that were not done in the previous scripts

# data

climate: we provide the climate grid. all other climate data can be downloaded following the instructions within the scripts.

complexes: we provide the fire complexes of each country. This data contains all information needed for the analysis including year, size, severity and polygon information. The complexes are based on the data from Senf & Seidl, 2021 (https://doi.org/10.1038/s41893-020-00609-y) which can be downloaded here: https://doi.org/10.5281/zenodo.7080016

countries: we provide the shapefiles of each country and Europe that are needed for the analysis in this folder.

ecoregions: Olson et al. terrestrial ecosystems should be downloaded from: https://www.arcgis.com/home/item.html?id=be0f9e21de7a4a61856dad78d1c79eae

models: we provide all final models used for the analysis.

results: we provide the results of the individual steps. This should help to reduce the runtime for the user.

# additional information

R version 3.6.3 (2020-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.5 LTS

Tabular data output from a series of modeling simulations for forest ecoystems of the continental United States (CONUS). We linked the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to project changes in forest ecosystem carbon balance resulting from land use, land use change, climate change, and disturbance from wildfire and insect mortality. The model was run at a 1-km spatial resolution on an annual timestep for the years 2001 to 2020. We simulated four unique scenarios, consisting of a climate change only scenario, a land-use change only scenario, a combined climate and land-use change scenario, and a no change scenario. Results presented here have been aggregated from the individual cell level and summarized for either the entire CONUS or for individual States. Model input data and the R code used to generate it, as well as R code used to summarize and analyze model output data, can be found in a GitHub repository (https://github.com/bsleeter/).

This dataset tracks the updates made on the dataset "Evergreen Forest Elementary Update" as a repository for previous versions of the data and metadata.

The Wildlands and Woodlands (W&W) initiative is a broad, collaborative effort to protect 70% of New England in forest over the next 50 years. At the heart of this initiative is the awareness that our wooded landscapes provide immeasurable economic, environmental, and cultural benefits and the conviction that we should understand these systems better, manage them wisely, and conserve them for the future. As part of W&W, Stewardship Science seeks to encourage widespread application of an accessible approach to monitoring forests that interested landowners or conservation-minded individuals can use to track changes in their woods over time. Whether the motivation is active management for timber, understanding how forests are being shaped by factors ranging from climate change and ice storms to insect pests, or simple pleasure in observing nature’s dynamics, anyone equipped with a notebook, tape measure, pencil, and the willingness to puzzle through a book of tree identification can readily develop a robust and valuable set of observations. This idea is not new. For over 150 years, leading conservationists and ecological thinkers beginning with Henry David Thoreau have argued that there is much to be learned through simple, long-term measurements of forest growth and change. Yet there are still remarkably few examples of private landowners, land trusts, timber companies, or conservation organizations that base their understanding and management practices on a regular system of observations and measurements. Because the vast majority of forestland in New England is privately owned, most of these lands remain unmonitored, and management plans are often drawn up from casual rather than systematic observation. For more background information on the project, please see the Wildlands & Woodlands Stewardship Science manual. This data package contains vegetation and environmental data on 64 20x20m plots set up in four areas across New England by staff and summer field crews from the Harvard Forest. These plots were set up on properties owned by different conservation-minded organizations and families with the broad intent of sampling across different management regimes (managed vs. unmanaged), across contrasting forest tree communities, and across different forest ages. The sampled areas include properties in southern Petersham, northeast Vermont, and central Maine. These data are part of a central W&W Stewardship Science data repository created by the Harvard Forest to hold data collected by our Stewardship Science partners at Highstead and elsewhere. It is hoped that researchers will use these plots to inform land managers and engage landowners now, and especially in the future; as the plots get resampled, they will provide valuable insights on short-and long-term forest change.

There are currently 95 conservation unit mapped out and registered on this database (april 2017). This database contains description/identification, abundance and geographical data on 8 forest tree species.

Open AccessYNP Chronosequence Carbon DataThis data file includes field data collected between 2004 and 2007 in and around Yellowstone National Park. It includes data from 77 lodgepole pine stands ranging in age from 12 years to 335 years old. Data include stand structural data as well as carbon data for all carbon pools in each stand. It is an MS Excel file with a tab describing each data column and a tab with the data themselves.