Identifying environmental controls on vegetation greenness phenology through model-data integration

Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenol...

Full description

Bibliographic Details
Main Authors: Forkel, M., Carvalhais, N., Schaphoff, S., V. Bloh, W., Migliavacca, M., Thurner, M., Thonicke, K.
Format: Text
Language:English
Published: München : European Geopyhsical Union 2014
Subjects:
550
Online Access:https://dx.doi.org/10.34657/1024
https://oa.tib.eu/renate/handle/123456789/536
id ftdatacite:10.34657/1024
record_format openpolar
spelling ftdatacite:10.34657/1024 2023-05-15T13:11:51+02:00 Identifying environmental controls on vegetation greenness phenology through model-data integration Forkel, M. Carvalhais, N. Schaphoff, S. V. Bloh, W. Migliavacca, M. Thurner, M. Thonicke, K. 2014 application/pdf https://dx.doi.org/10.34657/1024 https://oa.tib.eu/renate/handle/123456789/536 en eng München : European Geopyhsical Union Creative Commons Attribution 3.0 Unported CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 CC-BY Biogeochemistry boreal forest data set decadal variation ecological modeling environmental conditions growing season net primary production phenology seasonal variation vegetation dynamics water availability 550 article-journal ScholarlyArticle article Text 2014 ftdatacite https://doi.org/10.34657/1024 2022-04-01T09:37:59Z Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness. Text albedo Arctic Tundra DataCite Metadata Store (German National Library of Science and Technology) Arctic Browning ENVELOPE(164.050,164.050,-74.617,-74.617)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Biogeochemistry
boreal forest
data set
decadal variation
ecological modeling
environmental conditions
growing season
net primary production
phenology
seasonal variation
vegetation dynamics
water availability
550
spellingShingle Biogeochemistry
boreal forest
data set
decadal variation
ecological modeling
environmental conditions
growing season
net primary production
phenology
seasonal variation
vegetation dynamics
water availability
550
Forkel, M.
Carvalhais, N.
Schaphoff, S.
V. Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
Identifying environmental controls on vegetation greenness phenology through model-data integration
topic_facet Biogeochemistry
boreal forest
data set
decadal variation
ecological modeling
environmental conditions
growing season
net primary production
phenology
seasonal variation
vegetation dynamics
water availability
550
description Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.
format Text
author Forkel, M.
Carvalhais, N.
Schaphoff, S.
V. Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
author_facet Forkel, M.
Carvalhais, N.
Schaphoff, S.
V. Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
author_sort Forkel, M.
title Identifying environmental controls on vegetation greenness phenology through model-data integration
title_short Identifying environmental controls on vegetation greenness phenology through model-data integration
title_full Identifying environmental controls on vegetation greenness phenology through model-data integration
title_fullStr Identifying environmental controls on vegetation greenness phenology through model-data integration
title_full_unstemmed Identifying environmental controls on vegetation greenness phenology through model-data integration
title_sort identifying environmental controls on vegetation greenness phenology through model-data integration
publisher München : European Geopyhsical Union
publishDate 2014
url https://dx.doi.org/10.34657/1024
https://oa.tib.eu/renate/handle/123456789/536
long_lat ENVELOPE(164.050,164.050,-74.617,-74.617)
geographic Arctic
Browning
geographic_facet Arctic
Browning
genre albedo
Arctic
Tundra
genre_facet albedo
Arctic
Tundra
op_rights Creative Commons Attribution 3.0 Unported
CC BY 3.0 Unported
https://creativecommons.org/licenses/by/3.0/legalcode
cc-by-3.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.34657/1024
_version_ 1766249224468430848