High Conservation Value Forests, Sweden (HCVFSw)
https://doi.org/10.5878/wa6j-4b84
HCVFSw has been developed through a machine learning algorithm (Random Forest Classifier) as a part of a research project financed by the Swedish Environmental Protection Agency. It is based on a large set of biophysical and socio-economic variables, including known occurrences of high conservation values forests (HCVF) and provides a wall-to-wall prediction of the relative likelihood that single hectares (100x100 m), dominated by forest (≥50%), constitute HCVF. The predictions are continuous from 100% to 0% (1 to 0). HCVFSw can therefore be regarded as a first step towards identifying areas that are in need of protection, conservation management and restoration as well for increased environmental concern during forestry operations. HCVFSw is primarily aimed for geographical planning and not a description of actual natural values in singel forest stands. HCVFSw may also be used to identify areas where forestry can continue without major conflicts with existing natural values
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
- Johan Svensson - Swedish University of Agricultural Sciences - Department of Wildlife, Fish, and Environmental Studies
Research principal:
Principal's reference number:
- MIUN 2023/448
Data contains personal data:
No
Citation:
Method and outcome
Method and outcome
Time period(s) investigated:
Variables:
1
Data format/data structure:
Data collection - Compilation/Synthesis
Data collection - Compilation/Synthesis
Mode of collection:
Compilation/Synthesis
Description of the mode of collection:
Open available data on the occurrence of High Conservation Value Forests and wall-to-wall geographical data on environmental variables (total 125 variables) that describes aspects of the Swedish forest landscape
Time period(s) for data collection:
1990-01-01 - 2022-04-01
Spatial resolution:
100 metres scale
Geographic coverage
Geographic coverage
Geographic location:
Geographic description:
HCVFSw describes all of Sweden but divided into four regions; north boreal, south boreal, hemiboreal and nemoral region
Administrative information
Administrative information
Responsible department/unit:
Department of Natural Sciences, Design and Sustainable Development
Other research principals:
Contributor(s):
Funding
Funding
Funding agency:
- Swedish Environmental Protection Agency
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Award number:
18/145
Award title:
Bättre sent än aldrig: indikatorer på skogslandskapets gröna infrastruktur
Topic and keywords
Topic and keywords
Standard för svensk indelning av forskningsämnen 2025:
INSPIRE topic categories:
Publications
Publications
Citation:
Bubnicki, J.W., Angelstam, P., Mikusiński, G., Svensson, J., Jonsson, B.G. 2024. The conservation value of forests can be predicted at the scale of 1 hectare Communications Earth & Environment 5:196
Citation:
Jonsson, B.G., Angelstam, P., Bubnicki, J.W., Mikusinski, G., Svensson, J. & Undin, M. 2024. "Naturvärdeskarta Skog: En sannolikhetsmodell för naturvärden på skogsmark". Swedish Environmental Protection Agency, report under print
Metadata
Metadata
Version 1
Mid Sweden University