Isolating the Impacts of Land Use/Cover Change and Climate Change on the GPP in the Heihe River Basin of China

Terrestrial gross primary production (GPP) is a key indicator of the ecosystem response to climate change and land use/cover change (LUCC) in arid areas. The available global GPP data sets cannot meet the demands for local applications in arid areas due to sparse vegetation and extreme climate condi...

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Veröffentlicht in:Journal of geophysical research. Biogeosciences 2020-10, Vol.125 (10), p.n/a
Hauptverfasser: You, Nanshan, Meng, Jijun, Zhu, Lijun, Jiang, Song, Zhu, Likai, Li, Feng, Kuo, Li‐Jen
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container_title Journal of geophysical research. Biogeosciences
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creator You, Nanshan
Meng, Jijun
Zhu, Lijun
Jiang, Song
Zhu, Likai
Li, Feng
Kuo, Li‐Jen
description Terrestrial gross primary production (GPP) is a key indicator of the ecosystem response to climate change and land use/cover change (LUCC) in arid areas. The available global GPP data sets cannot meet the demands for local applications in arid areas due to sparse vegetation and extreme climate conditions. Here, we developed a novel GPP estimation model for the Heihe River Basin (HRB), the second largest inland river basin in northern China, and disentangled the impacts of climate change and LUCC on GPP. First, we calibrated the vegetation photosynthesis model (VPM) using CO2 flux observations from multiple stations in the HRB and developed a modified local GPP model (HRB‐VPM). Then, we decoupled the joint effects of LUCC and climate change on GPP based on the log and differential transformation method. The results showed that HRB‐VPM outperformed Moderate Resolution Imaging Spectroradiometer and VPM GPP models in arid ecosystems. The root mean square error of HRB‐VPM was 4.9 and 1.5 gCm−2 day−1 lower than those of the Moderate Resolution Imaging Spectroradiometer and VPM models, respectively. We concluded that the underlying driving forces of the GPP changes were distinct across the HRB. In the upper reach, climate change accounted for 65.8% of GPP changes, while in the middle and lower reaches, LUCC contributed to 75.1% of GPP changes. Our research provides an effective way to monitor arid ecosystem degradation and is useful for mitigating the negative impacts of human activities and future climate change. Plain Language Summary Climate change and intensive human activities exert profound influences on vegetation productivity, which has caused widespread ecosystem degradation in arid areas. Monitoring vegetation productivity and disentangling their anthropogenic and natural driving forces in arid ecosystems remain challenging. Here, we proposed a methodology to accurately estimate gross primary production (GPP) and distinguish its responses to human activities and climate change in the Heihe River Basin, the second largest inland river basin in northern China. We found that the dominant drivers of GPP changes differed across the Heihe River Basin. GPP was dominantly driven by climate change in the upper reach, while it was mainly controlled by land use/cover change in the middle and lower reaches. Our research provides an effective way to monitor arid ecosystem degradation and is helpful for mitigating the negative impacts of human activities and climate
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The available global GPP data sets cannot meet the demands for local applications in arid areas due to sparse vegetation and extreme climate conditions. Here, we developed a novel GPP estimation model for the Heihe River Basin (HRB), the second largest inland river basin in northern China, and disentangled the impacts of climate change and LUCC on GPP. First, we calibrated the vegetation photosynthesis model (VPM) using CO2 flux observations from multiple stations in the HRB and developed a modified local GPP model (HRB‐VPM). Then, we decoupled the joint effects of LUCC and climate change on GPP based on the log and differential transformation method. The results showed that HRB‐VPM outperformed Moderate Resolution Imaging Spectroradiometer and VPM GPP models in arid ecosystems. The root mean square error of HRB‐VPM was 4.9 and 1.5 gCm−2 day−1 lower than those of the Moderate Resolution Imaging Spectroradiometer and VPM models, respectively. We concluded that the underlying driving forces of the GPP changes were distinct across the HRB. In the upper reach, climate change accounted for 65.8% of GPP changes, while in the middle and lower reaches, LUCC contributed to 75.1% of GPP changes. Our research provides an effective way to monitor arid ecosystem degradation and is useful for mitigating the negative impacts of human activities and future climate change. Plain Language Summary Climate change and intensive human activities exert profound influences on vegetation productivity, which has caused widespread ecosystem degradation in arid areas. Monitoring vegetation productivity and disentangling their anthropogenic and natural driving forces in arid ecosystems remain challenging. Here, we proposed a methodology to accurately estimate gross primary production (GPP) and distinguish its responses to human activities and climate change in the Heihe River Basin, the second largest inland river basin in northern China. We found that the dominant drivers of GPP changes differed across the Heihe River Basin. GPP was dominantly driven by climate change in the upper reach, while it was mainly controlled by land use/cover change in the middle and lower reaches. Our research provides an effective way to monitor arid ecosystem degradation and is helpful for mitigating the negative impacts of human activities and climate change on arid ecosystems. Key Points HRB‐VPM outperformed the GLOBAL‐VPM and MOD17 model in the arid Heihe River Basin Climate change dominated the change in GPP in the upper reach, while land use/cover change controlled GPP in the middle and lower reaches Log and differential transformation can effectively isolate the impacts of land use/cover change and climate change on GPP</description><identifier>ISSN: 2169-8953</identifier><identifier>EISSN: 2169-8961</identifier><identifier>DOI: 10.1029/2020JG005734</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Anthropogenic factors ; Arid regions ; attritube analyses ; Carbon dioxide ; Climate change ; Climate effects ; Climatic conditions ; Ecological monitoring ; Ecosystem degradation ; Ecosystems ; Environment models ; Environmental impact ; Forces ; GPP ; Human influences ; Imaging techniques ; interannual variability ; Land use ; land use and land cover change ; Photosynthesis ; Primary production ; Productivity ; Resolution ; River basins ; River ecology ; Rivers ; Spectroradiometers ; Vegetation ; VPM</subject><ispartof>Journal of geophysical research. 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Biogeosciences</title><description>Terrestrial gross primary production (GPP) is a key indicator of the ecosystem response to climate change and land use/cover change (LUCC) in arid areas. The available global GPP data sets cannot meet the demands for local applications in arid areas due to sparse vegetation and extreme climate conditions. Here, we developed a novel GPP estimation model for the Heihe River Basin (HRB), the second largest inland river basin in northern China, and disentangled the impacts of climate change and LUCC on GPP. First, we calibrated the vegetation photosynthesis model (VPM) using CO2 flux observations from multiple stations in the HRB and developed a modified local GPP model (HRB‐VPM). Then, we decoupled the joint effects of LUCC and climate change on GPP based on the log and differential transformation method. The results showed that HRB‐VPM outperformed Moderate Resolution Imaging Spectroradiometer and VPM GPP models in arid ecosystems. The root mean square error of HRB‐VPM was 4.9 and 1.5 gCm−2 day−1 lower than those of the Moderate Resolution Imaging Spectroradiometer and VPM models, respectively. We concluded that the underlying driving forces of the GPP changes were distinct across the HRB. In the upper reach, climate change accounted for 65.8% of GPP changes, while in the middle and lower reaches, LUCC contributed to 75.1% of GPP changes. Our research provides an effective way to monitor arid ecosystem degradation and is useful for mitigating the negative impacts of human activities and future climate change. Plain Language Summary Climate change and intensive human activities exert profound influences on vegetation productivity, which has caused widespread ecosystem degradation in arid areas. Monitoring vegetation productivity and disentangling their anthropogenic and natural driving forces in arid ecosystems remain challenging. Here, we proposed a methodology to accurately estimate gross primary production (GPP) and distinguish its responses to human activities and climate change in the Heihe River Basin, the second largest inland river basin in northern China. We found that the dominant drivers of GPP changes differed across the Heihe River Basin. GPP was dominantly driven by climate change in the upper reach, while it was mainly controlled by land use/cover change in the middle and lower reaches. Our research provides an effective way to monitor arid ecosystem degradation and is helpful for mitigating the negative impacts of human activities and climate change on arid ecosystems. 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Biogeosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>You, Nanshan</au><au>Meng, Jijun</au><au>Zhu, Lijun</au><au>Jiang, Song</au><au>Zhu, Likai</au><au>Li, Feng</au><au>Kuo, Li‐Jen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Isolating the Impacts of Land Use/Cover Change and Climate Change on the GPP in the Heihe River Basin of China</atitle><jtitle>Journal of geophysical research. Biogeosciences</jtitle><date>2020-10</date><risdate>2020</risdate><volume>125</volume><issue>10</issue><epage>n/a</epage><issn>2169-8953</issn><eissn>2169-8961</eissn><abstract>Terrestrial gross primary production (GPP) is a key indicator of the ecosystem response to climate change and land use/cover change (LUCC) in arid areas. The available global GPP data sets cannot meet the demands for local applications in arid areas due to sparse vegetation and extreme climate conditions. Here, we developed a novel GPP estimation model for the Heihe River Basin (HRB), the second largest inland river basin in northern China, and disentangled the impacts of climate change and LUCC on GPP. First, we calibrated the vegetation photosynthesis model (VPM) using CO2 flux observations from multiple stations in the HRB and developed a modified local GPP model (HRB‐VPM). Then, we decoupled the joint effects of LUCC and climate change on GPP based on the log and differential transformation method. The results showed that HRB‐VPM outperformed Moderate Resolution Imaging Spectroradiometer and VPM GPP models in arid ecosystems. The root mean square error of HRB‐VPM was 4.9 and 1.5 gCm−2 day−1 lower than those of the Moderate Resolution Imaging Spectroradiometer and VPM models, respectively. We concluded that the underlying driving forces of the GPP changes were distinct across the HRB. In the upper reach, climate change accounted for 65.8% of GPP changes, while in the middle and lower reaches, LUCC contributed to 75.1% of GPP changes. Our research provides an effective way to monitor arid ecosystem degradation and is useful for mitigating the negative impacts of human activities and future climate change. Plain Language Summary Climate change and intensive human activities exert profound influences on vegetation productivity, which has caused widespread ecosystem degradation in arid areas. Monitoring vegetation productivity and disentangling their anthropogenic and natural driving forces in arid ecosystems remain challenging. Here, we proposed a methodology to accurately estimate gross primary production (GPP) and distinguish its responses to human activities and climate change in the Heihe River Basin, the second largest inland river basin in northern China. We found that the dominant drivers of GPP changes differed across the Heihe River Basin. GPP was dominantly driven by climate change in the upper reach, while it was mainly controlled by land use/cover change in the middle and lower reaches. Our research provides an effective way to monitor arid ecosystem degradation and is helpful for mitigating the negative impacts of human activities and climate change on arid ecosystems. Key Points HRB‐VPM outperformed the GLOBAL‐VPM and MOD17 model in the arid Heihe River Basin Climate change dominated the change in GPP in the upper reach, while land use/cover change controlled GPP in the middle and lower reaches Log and differential transformation can effectively isolate the impacts of land use/cover change and climate change on GPP</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2020JG005734</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-3436-1782</orcidid><orcidid>https://orcid.org/0000-0001-8425-0119</orcidid><orcidid>https://orcid.org/0000-0001-7911-7700</orcidid></addata></record>
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subjects Anthropogenic factors
Arid regions
attritube analyses
Carbon dioxide
Climate change
Climate effects
Climatic conditions
Ecological monitoring
Ecosystem degradation
Ecosystems
Environment models
Environmental impact
Forces
GPP
Human influences
Imaging techniques
interannual variability
Land use
land use and land cover change
Photosynthesis
Primary production
Productivity
Resolution
River basins
River ecology
Rivers
Spectroradiometers
Vegetation
VPM
title Isolating the Impacts of Land Use/Cover Change and Climate Change on the GPP in the Heihe River Basin of China
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