An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data

Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface–atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management...

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Published in:Biogeosciences
Main Authors: T. Majasalmi, S. Eisner, R. Astrup, J. Fridman, R. M. Bright
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2018
Subjects:
Online Access:https://doi.org/10.5194/bg-15-399-2018
https://doaj.org/article/f7000b875fde45da9adf45609c2552e5
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spelling ftdoajarticles:oai:doaj.org/article:f7000b875fde45da9adf45609c2552e5 2023-05-15T16:11:49+02:00 An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data T. Majasalmi S. Eisner R. Astrup J. Fridman R. M. Bright 2018-01-01T00:00:00Z https://doi.org/10.5194/bg-15-399-2018 https://doaj.org/article/f7000b875fde45da9adf45609c2552e5 EN eng Copernicus Publications https://www.biogeosciences.net/15/399/2018/bg-15-399-2018.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-15-399-2018 1726-4170 1726-4189 https://doaj.org/article/f7000b875fde45da9adf45609c2552e5 Biogeosciences, Vol 15, Pp 399-412 (2018) Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.5194/bg-15-399-2018 2022-12-31T16:11:25Z Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface–atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAI max ), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products ( https://doi.org/10.21350/7zZEy5w3 ) showed that forest extent notably ( κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAI max ) of managed forests in Fennoscandia, we compared our LAI max map with reference LAI max maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAI max values used in three leading land models. Comparison of the LAI max maps showed that our product provides a spatially more realistic description of LAI max in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models. Article in Journal/Newspaper Fennoscandia Fennoscandian Directory of Open Access Journals: DOAJ Articles Norway Biogeosciences 15 2 399 412
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
spellingShingle Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
T. Majasalmi
S. Eisner
R. Astrup
J. Fridman
R. M. Bright
An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
topic_facet Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
description Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface–atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAI max ), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products ( https://doi.org/10.21350/7zZEy5w3 ) showed that forest extent notably ( κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAI max ) of managed forests in Fennoscandia, we compared our LAI max map with reference LAI max maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAI max values used in three leading land models. Comparison of the LAI max maps showed that our product provides a spatially more realistic description of LAI max in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.
format Article in Journal/Newspaper
author T. Majasalmi
S. Eisner
R. Astrup
J. Fridman
R. M. Bright
author_facet T. Majasalmi
S. Eisner
R. Astrup
J. Fridman
R. M. Bright
author_sort T. Majasalmi
title An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
title_short An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
title_full An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
title_fullStr An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
title_full_unstemmed An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
title_sort enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data
publisher Copernicus Publications
publishDate 2018
url https://doi.org/10.5194/bg-15-399-2018
https://doaj.org/article/f7000b875fde45da9adf45609c2552e5
geographic Norway
geographic_facet Norway
genre Fennoscandia
Fennoscandian
genre_facet Fennoscandia
Fennoscandian
op_source Biogeosciences, Vol 15, Pp 399-412 (2018)
op_relation https://www.biogeosciences.net/15/399/2018/bg-15-399-2018.pdf
https://doaj.org/toc/1726-4170
https://doaj.org/toc/1726-4189
doi:10.5194/bg-15-399-2018
1726-4170
1726-4189
https://doaj.org/article/f7000b875fde45da9adf45609c2552e5
op_doi https://doi.org/10.5194/bg-15-399-2018
container_title Biogeosciences
container_volume 15
container_issue 2
container_start_page 399
op_container_end_page 412
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