Fire is a global phenomenon and a major source of aerosols from the terrestrial biosphere to the atmosphere.Most previous studies quantified the effect of fire aerosols on climate and atmospheric circulation,or on the...Fire is a global phenomenon and a major source of aerosols from the terrestrial biosphere to the atmosphere.Most previous studies quantified the effect of fire aerosols on climate and atmospheric circulation,or on the regional and site-scale terrestrial ecosystem productivity.So far,only one work has quantified their global impacts on terrestrial ecosystem productivity based on offline simulations,which,however,did not consider the impacts of aerosol–cloud interactions and aerosol–climate feedbacks.This study quantitatively assesses the influence of fire aerosols on the global annual gross primary productivity(GPP)of terrestrial ecosystems using simulations with the fully coupled global Earth system model CESM1.2.Results show that fire aerosols generally decrease GPP in vegetated areas,with a global total of−1.6 Pg C yr^−1,mainly because fire aerosols cool and dry the land surface and weaken the direct photosynthetically active radiation(PAR).The exception to this is the Amazon region,which is mainly due to a fire-aerosol-induced wetter land surface and increased diffuse PAR.This study emphasizes the importance of the influence of fire aerosols on climate in quantifying global-scale fire aerosols’impacts on terrestrial ecosystem productivity.展开更多
As an important product of Moderate Resolution Imaging Spectroradiometer(MODIS), MOD17A2 provides dramatic improvements in our ability to accurately and continuously monitor global terrestrial primary production, whic...As an important product of Moderate Resolution Imaging Spectroradiometer(MODIS), MOD17A2 provides dramatic improvements in our ability to accurately and continuously monitor global terrestrial primary production, which is also significant in effort to advance scientific research and eco-environmental management. Over the past decades, forests have moderated climate change by sequestrating about one-quarter of the carbon emitted by human activities through fossil fuels burning and land use/land cover change. Thus, the carbon uptake by forests reduces the rate at which carbon accumulates in the atmosphere. However, the sensitivity of near real-time MODIS gross primary productivity(GPP) product is directly constrained by uncertainties in the modeling process, especially in complicated forest ecosystems. Although there have been plenty of studies to verify MODIS GPP with ground-based measurements using the eddy covariance(EC) technique, few have comprehensively validated the performance of MODIS estimates(Collection 5) across diverse forest types. Therefore, the present study examined the degree of correspondence between MODIS-derived GPP and EC-measured GPP at seasonal and interannual time scales for the main forest ecosystems, including evergreen broadleaf forest(EBF), evergreen needleleaf forest(ENF), deciduous broadleaf forest(DBF), and mixed forest(MF) relying on 16 flux towers with a total of 68 site-year datasets. Overall, site-specific evaluation of multi-year mean annual GPP estimates indicates that the current MOD17A2 product works highly effectively for MF and DBF, moderately effectively for ENF, and ineffectively for EBF. Except for tropical forest, MODIS estimates could capture the broad trends of GPP at 8-day time scale for all other sites surveyed. On the annual time scale, the best performance was observed in MF, followed by ENF, DBF, and EBF. Trend analyses also revealed the poor performance of MODIS GPP product in EBF and DBF. Thus, improvements in the sensitivity of MOD17A2 to forest productivity require continued efforts.展开更多
The Chaobai River Basin,which is a crucial ecological barrier and primary water source area within the Beijing-Tianjin-Hebei region,possesses substantial ecological significance.The gross ecosystem product(GEP)in the ...The Chaobai River Basin,which is a crucial ecological barrier and primary water source area within the Beijing-Tianjin-Hebei region,possesses substantial ecological significance.The gross ecosystem product(GEP)in the Chaobai River Basin is a reflection of ecosystem conditions and quantifies nature’s contributions to humanity,which provides a basis for basin ecosystem service management and decision-making.This study investigated the spatiotemporal evolution of GEP in the upper Chaobai River Basin and explored the driving factors influencing GEP spatial differentiation.Ecosystem patterns from 2005 to 2020 were analyzed,and GEP was calculated for 2005,2010,2015,and 2020.The driving factors influencing GEP spatial differentiation were identified using the optimal parameter-based geographical detector(OPGD)model.The key findings are as follows:(1)From 2005 to 2020,the main ecosystem types were forest,grassland,and agriculture.Urban areas experienced significant changes,and conversions mainly occurred among urban,water,grassland and agricultural ecosystems.(2)Temporally,the GEP in the basin increased from 2005 to 2020,with regulation services dominating.At the county(district)scale,GEP exhibited a north-west-high and south-east-low pattern,showing spatial differences between per-unit-area GEP and county(district)GEP,while the spatial variations in per capita GEP and county(district)GEP were similar.(3)Differences in the spatial distribution of GEP were influenced by regional natural geographical and socioeconomic factors.Among these factors,gross domestic product,population density,and land-use degree density contributed significantly.Interactions among different driving forces noticeably impacted GEP spatial differentiation.These findings underscore the necessity of incorporating factors such as population density and the intensity of land-use development into ecosystem management decision-making processes in the upper reaches of the Chaobai River Basin.Future policies should be devised to regulate human activities,thereby ensuring the stability and enhancement of GEP.展开更多
基金This study was co-supported by the National Key R&D Program of China[grant number 2017YFA0604302]the National Natural Science Foundation of China[grant numbers 41475099 and 41875137]the Chinese Academy of Sciences Key Research Program of Frontier Sciences[grant number QYZDY-SSW-DQC002].
文摘Fire is a global phenomenon and a major source of aerosols from the terrestrial biosphere to the atmosphere.Most previous studies quantified the effect of fire aerosols on climate and atmospheric circulation,or on the regional and site-scale terrestrial ecosystem productivity.So far,only one work has quantified their global impacts on terrestrial ecosystem productivity based on offline simulations,which,however,did not consider the impacts of aerosol–cloud interactions and aerosol–climate feedbacks.This study quantitatively assesses the influence of fire aerosols on the global annual gross primary productivity(GPP)of terrestrial ecosystems using simulations with the fully coupled global Earth system model CESM1.2.Results show that fire aerosols generally decrease GPP in vegetated areas,with a global total of−1.6 Pg C yr^−1,mainly because fire aerosols cool and dry the land surface and weaken the direct photosynthetically active radiation(PAR).The exception to this is the Amazon region,which is mainly due to a fire-aerosol-induced wetter land surface and increased diffuse PAR.This study emphasizes the importance of the influence of fire aerosols on climate in quantifying global-scale fire aerosols’impacts on terrestrial ecosystem productivity.
基金Under the auspices of National Natural Science Foundation of China(No.41401221,41271500,41201496)Opening Fund of Key Laboratory of Poyang Lake Wetland and Watershed Research(Jiangxi Normal University),Ministry of Education,China(No.PK2014002)
文摘As an important product of Moderate Resolution Imaging Spectroradiometer(MODIS), MOD17A2 provides dramatic improvements in our ability to accurately and continuously monitor global terrestrial primary production, which is also significant in effort to advance scientific research and eco-environmental management. Over the past decades, forests have moderated climate change by sequestrating about one-quarter of the carbon emitted by human activities through fossil fuels burning and land use/land cover change. Thus, the carbon uptake by forests reduces the rate at which carbon accumulates in the atmosphere. However, the sensitivity of near real-time MODIS gross primary productivity(GPP) product is directly constrained by uncertainties in the modeling process, especially in complicated forest ecosystems. Although there have been plenty of studies to verify MODIS GPP with ground-based measurements using the eddy covariance(EC) technique, few have comprehensively validated the performance of MODIS estimates(Collection 5) across diverse forest types. Therefore, the present study examined the degree of correspondence between MODIS-derived GPP and EC-measured GPP at seasonal and interannual time scales for the main forest ecosystems, including evergreen broadleaf forest(EBF), evergreen needleleaf forest(ENF), deciduous broadleaf forest(DBF), and mixed forest(MF) relying on 16 flux towers with a total of 68 site-year datasets. Overall, site-specific evaluation of multi-year mean annual GPP estimates indicates that the current MOD17A2 product works highly effectively for MF and DBF, moderately effectively for ENF, and ineffectively for EBF. Except for tropical forest, MODIS estimates could capture the broad trends of GPP at 8-day time scale for all other sites surveyed. On the annual time scale, the best performance was observed in MF, followed by ENF, DBF, and EBF. Trend analyses also revealed the poor performance of MODIS GPP product in EBF and DBF. Thus, improvements in the sensitivity of MOD17A2 to forest productivity require continued efforts.
基金the National Key Research and Development Program of China(No.2022YFF1301804)the Beijing Municipal Education Commission through the Innovative Transdisciplinary Program“Ecological Restoration Engineering”(No.GJJXK210102).
文摘The Chaobai River Basin,which is a crucial ecological barrier and primary water source area within the Beijing-Tianjin-Hebei region,possesses substantial ecological significance.The gross ecosystem product(GEP)in the Chaobai River Basin is a reflection of ecosystem conditions and quantifies nature’s contributions to humanity,which provides a basis for basin ecosystem service management and decision-making.This study investigated the spatiotemporal evolution of GEP in the upper Chaobai River Basin and explored the driving factors influencing GEP spatial differentiation.Ecosystem patterns from 2005 to 2020 were analyzed,and GEP was calculated for 2005,2010,2015,and 2020.The driving factors influencing GEP spatial differentiation were identified using the optimal parameter-based geographical detector(OPGD)model.The key findings are as follows:(1)From 2005 to 2020,the main ecosystem types were forest,grassland,and agriculture.Urban areas experienced significant changes,and conversions mainly occurred among urban,water,grassland and agricultural ecosystems.(2)Temporally,the GEP in the basin increased from 2005 to 2020,with regulation services dominating.At the county(district)scale,GEP exhibited a north-west-high and south-east-low pattern,showing spatial differences between per-unit-area GEP and county(district)GEP,while the spatial variations in per capita GEP and county(district)GEP were similar.(3)Differences in the spatial distribution of GEP were influenced by regional natural geographical and socioeconomic factors.Among these factors,gross domestic product,population density,and land-use degree density contributed significantly.Interactions among different driving forces noticeably impacted GEP spatial differentiation.These findings underscore the necessity of incorporating factors such as population density and the intensity of land-use development into ecosystem management decision-making processes in the upper reaches of the Chaobai River Basin.Future policies should be devised to regulate human activities,thereby ensuring the stability and enhancement of GEP.
