Modeling leaf area index in North America using a process‐based terrestrial ecosystem model

Abstract Leaf area index (LAI) is often used to quantify plant production and evapotranspiration with terrestrial ecosystem models (TEMs). This study evaluated the LAI simulation in North America using a data assimilation technique and a process‐based TEM as well as in situ and satellite data. We fi...

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Published in:Ecosphere
Main Authors: Yang Qu, Qianlai Zhuang
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2018
Subjects:
Online Access:https://doi.org/10.1002/ecs2.2046
https://doaj.org/article/d32061be432b4b3e8749ad002fac85be
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spelling ftdoajarticles:oai:doaj.org/article:d32061be432b4b3e8749ad002fac85be 2023-05-15T18:40:20+02:00 Modeling leaf area index in North America using a process‐based terrestrial ecosystem model Yang Qu Qianlai Zhuang 2018-01-01T00:00:00Z https://doi.org/10.1002/ecs2.2046 https://doaj.org/article/d32061be432b4b3e8749ad002fac85be EN eng Wiley https://doi.org/10.1002/ecs2.2046 https://doaj.org/toc/2150-8925 2150-8925 doi:10.1002/ecs2.2046 https://doaj.org/article/d32061be432b4b3e8749ad002fac85be Ecosphere, Vol 9, Iss 1, Pp n/a-n/a (2018) leaf area index (LAI) model parameterization phenology terrestrial ecosystem model (TEM) Ecology QH540-549.5 article 2018 ftdoajarticles https://doi.org/10.1002/ecs2.2046 2022-12-31T11:51:07Z Abstract Leaf area index (LAI) is often used to quantify plant production and evapotranspiration with terrestrial ecosystem models (TEMs). This study evaluated the LAI simulation in North America using a data assimilation technique and a process‐based TEM as well as in situ and satellite data. We first optimized the parameters related to LAI in the TEM using a Markov Chain Monte Carlo method, and AmeriFlux site‐level and regional LAI data from advanced very high‐resolution radiometer. The parameterized model was then verified with the observed monthly LAI of major ecosystem types at site level. Simulated LAI was compared well with the observed data at sites of Harvard Forest (R2 = 0.96), University of Michigan Biological Station (R2 = 0.87), Howland Forest (R2 = 0.96), Morgan Monroe State Forest (R2 = 0.85), Shidler Tallgrass Prairie (R2 = 0.82), and Donaldson (R2 = 0.75). The root‐mean‐square error (RMSE) between modeled and satellite‐based monthly LAI in North America is 1.4 m2/m2 for the period of 1985–2010. The simulated average monthly LAI in recent three decades increased by (3 ± 0.5)% in the region, with 1.24, 1.46, and 2.21 m2/m2 on average, in Alaska, Canada, and the conterminous United States, respectively, which is consistent with satellite data. The model performed well for wet tundra, boreal forest, temperate coniferous forests, temperate deciduous forests, grasslands, and xeric shrublands (RMSE < 1.5 m2/m2), but not for alpine tundra and xeric woodlands (RMSE > 1.5 m2/m2). Both the spring and fall LAI in the 2000s are higher than that in the 1980s in the region, suggesting that the leaf phenology has an earlier onset and later senescence in the 2000s. The average LAI increased in April and September by 0.03 and 0.24 m2/m2, respectively. This study provides a way to quantify LAI with ecosystem models, which will improve future carbon and water cycling studies. Article in Journal/Newspaper Tundra Alaska Directory of Open Access Journals: DOAJ Articles Canada Monroe ENVELOPE(-46.050,-46.050,-60.600,-60.600) Donaldson ENVELOPE(172.200,172.200,-84.617,-84.617) Ecosphere 9 1
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic leaf area index (LAI)
model parameterization
phenology
terrestrial ecosystem model (TEM)
Ecology
QH540-549.5
spellingShingle leaf area index (LAI)
model parameterization
phenology
terrestrial ecosystem model (TEM)
Ecology
QH540-549.5
Yang Qu
Qianlai Zhuang
Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
topic_facet leaf area index (LAI)
model parameterization
phenology
terrestrial ecosystem model (TEM)
Ecology
QH540-549.5
description Abstract Leaf area index (LAI) is often used to quantify plant production and evapotranspiration with terrestrial ecosystem models (TEMs). This study evaluated the LAI simulation in North America using a data assimilation technique and a process‐based TEM as well as in situ and satellite data. We first optimized the parameters related to LAI in the TEM using a Markov Chain Monte Carlo method, and AmeriFlux site‐level and regional LAI data from advanced very high‐resolution radiometer. The parameterized model was then verified with the observed monthly LAI of major ecosystem types at site level. Simulated LAI was compared well with the observed data at sites of Harvard Forest (R2 = 0.96), University of Michigan Biological Station (R2 = 0.87), Howland Forest (R2 = 0.96), Morgan Monroe State Forest (R2 = 0.85), Shidler Tallgrass Prairie (R2 = 0.82), and Donaldson (R2 = 0.75). The root‐mean‐square error (RMSE) between modeled and satellite‐based monthly LAI in North America is 1.4 m2/m2 for the period of 1985–2010. The simulated average monthly LAI in recent three decades increased by (3 ± 0.5)% in the region, with 1.24, 1.46, and 2.21 m2/m2 on average, in Alaska, Canada, and the conterminous United States, respectively, which is consistent with satellite data. The model performed well for wet tundra, boreal forest, temperate coniferous forests, temperate deciduous forests, grasslands, and xeric shrublands (RMSE < 1.5 m2/m2), but not for alpine tundra and xeric woodlands (RMSE > 1.5 m2/m2). Both the spring and fall LAI in the 2000s are higher than that in the 1980s in the region, suggesting that the leaf phenology has an earlier onset and later senescence in the 2000s. The average LAI increased in April and September by 0.03 and 0.24 m2/m2, respectively. This study provides a way to quantify LAI with ecosystem models, which will improve future carbon and water cycling studies.
format Article in Journal/Newspaper
author Yang Qu
Qianlai Zhuang
author_facet Yang Qu
Qianlai Zhuang
author_sort Yang Qu
title Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
title_short Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
title_full Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
title_fullStr Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
title_full_unstemmed Modeling leaf area index in North America using a process‐based terrestrial ecosystem model
title_sort modeling leaf area index in north america using a process‐based terrestrial ecosystem model
publisher Wiley
publishDate 2018
url https://doi.org/10.1002/ecs2.2046
https://doaj.org/article/d32061be432b4b3e8749ad002fac85be
long_lat ENVELOPE(-46.050,-46.050,-60.600,-60.600)
ENVELOPE(172.200,172.200,-84.617,-84.617)
geographic Canada
Monroe
Donaldson
geographic_facet Canada
Monroe
Donaldson
genre Tundra
Alaska
genre_facet Tundra
Alaska
op_source Ecosphere, Vol 9, Iss 1, Pp n/a-n/a (2018)
op_relation https://doi.org/10.1002/ecs2.2046
https://doaj.org/toc/2150-8925
2150-8925
doi:10.1002/ecs2.2046
https://doaj.org/article/d32061be432b4b3e8749ad002fac85be
op_doi https://doi.org/10.1002/ecs2.2046
container_title Ecosphere
container_volume 9
container_issue 1
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