High-resolution spatial distribution of vegetation biomass and its environmental response on Qinghai-Tibet Plateau: Intensive grid-field survey. (May 2023)
- Record Type:
- Journal Article
- Title:
- High-resolution spatial distribution of vegetation biomass and its environmental response on Qinghai-Tibet Plateau: Intensive grid-field survey. (May 2023)
- Main Title:
- High-resolution spatial distribution of vegetation biomass and its environmental response on Qinghai-Tibet Plateau: Intensive grid-field survey
- Authors:
- Zhu, Xingyu
Hou, Jihua
Li, Mingxu
Xu, Li
Li, Xin
Li, Ying
Cheng, Changjin
Zhao, Wenzong
He, Nianpeng - Abstract:
- Highlights: An intensive grid-field survey on the Qinghai-Tibet Plateau (QTP). UVGS and MAP are important factors affecting biomass on the QTP. QTP biomass spatial map with 1 km resolution was simulated by random forest. The estimate of plant biomass was 3.16 Gt on the TP, mainly from forest (1.80 Gt). The high-resolution maps of biomass facilitate regional management and conservation. Abstract: Due to the complexity of extremely high altitude, topography, and climate, accurately estimating regional biomass is essential yet challenging in alpine regions such as the Qinghai-Tibet Plateau (QTP). Here, we conducted an intensive grid-field survey using a matched-measured biomass dataset of 2, 040 field plots on the QTP to obtain high-resolution biomass estimates and their unique response to the environment. The biomass differed significantly among different vegetation types and was highest in evergreen coniferous forests and lowest in alpine grasslands. In addition to traditional mean temperature and precipitation, ultraviolet radiation of growing season ( UV GS ), and the partial pressure of CO2 ( P CO2 ) were also important factors influencing the spatial variation of vegetation biomass on the QTP. Furthermore, we simulated the spatial distribution of aboveground, belowground, and total biomass on the QTP at a 1-km resolution using the random forest algorithm, with the coefficient of determination (R 2 ) as 0.78, 0.57, and 0.72, respectively. The new estimate of vegetationHighlights: An intensive grid-field survey on the Qinghai-Tibet Plateau (QTP). UVGS and MAP are important factors affecting biomass on the QTP. QTP biomass spatial map with 1 km resolution was simulated by random forest. The estimate of plant biomass was 3.16 Gt on the TP, mainly from forest (1.80 Gt). The high-resolution maps of biomass facilitate regional management and conservation. Abstract: Due to the complexity of extremely high altitude, topography, and climate, accurately estimating regional biomass is essential yet challenging in alpine regions such as the Qinghai-Tibet Plateau (QTP). Here, we conducted an intensive grid-field survey using a matched-measured biomass dataset of 2, 040 field plots on the QTP to obtain high-resolution biomass estimates and their unique response to the environment. The biomass differed significantly among different vegetation types and was highest in evergreen coniferous forests and lowest in alpine grasslands. In addition to traditional mean temperature and precipitation, ultraviolet radiation of growing season ( UV GS ), and the partial pressure of CO2 ( P CO2 ) were also important factors influencing the spatial variation of vegetation biomass on the QTP. Furthermore, we simulated the spatial distribution of aboveground, belowground, and total biomass on the QTP at a 1-km resolution using the random forest algorithm, with the coefficient of determination (R 2 ) as 0.78, 0.57, and 0.72, respectively. The new estimate of vegetation biomass on the QTP with the intensive field-survey data was 3.16 Gt, including 1.80 Gt in forests, 0.77 Gt in shrubs, 0.52 Gt in grasslands, and 0.07 Gt in deserts. Because of the unique response of biomass to the external environment, such as UV GS and P CO2, we assessed the underlying response of terrestrial ecosystems to global change more comprehensively, especially for sensitive alpine or high-latitude regions in the future. The high-resolution biomass maps may serve as support for regional carbon sink assessment and ecosystem management and conservation, and may provide important parameters for ecological process modeling. … (more)
- Is Part Of:
- Ecological indicators. Volume 149(2023)
- Journal:
- Ecological indicators
- Issue:
- Volume 149(2023)
- Issue Display:
- Volume 149, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 149
- Issue:
- 2023
- Issue Sort Value:
- 2023-0149-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-05
- Subjects:
- Biomass -- Productivity -- Qinghai-Tibet Plateau -- Spatial variation -- Machine learning -- Adaptation
AGB Aboveground biomass -- BGB Belowground biomass -- TB Total biomass -- QTP Qinghai-Tibet Plateau -- ADG Alpine desert grassland -- AG Alpine grassland -- AMG Alpine meadow grassland -- ECS Evergreen coniferous shrubs -- DBS Deciduous broad-leaved shrubs -- EBS Evergreen broad-leaved shrubs -- EBF Evergreen broad-leaved forest -- ECF Evergreen coniferous forest -- DBF Deciduous broad-leaved forest -- CBF Coniferous and broad-leaved mixed forest -- MAT Mean annual temperature -- TGS Mean temperature of growing season -- Tcoldest Mean temperature of coldest quarter -- MAP Mean annual precipitation -- PGS Mean precipitation of growing season -- Pcoldest Precipitation of coldest quarter -- SOC Soil organic carbon -- TN Total nitrogen -- pHSoil Soil pH -- PCO2 Partial atmospheric carbon dioxide pressure -- PO2 Partial atmospheric oxygen pressure -- UVGS Ultraviolet radiation of growing season -- NDVI Normalized difference vegetation index
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2023.110167 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
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- Legaldeposit
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