Coral reefs are critical for marine biodiversity and coastal protection but face severe threats from climate change and human activities.This study conducted seasonal surveys on the composition of biological communiti...Coral reefs are critical for marine biodiversity and coastal protection but face severe threats from climate change and human activities.This study conducted seasonal surveys on the composition of biological communities and organic carbon content in the restored,natural,and fragmented reef areas in the northern part of Wuzhizhou Island,while continuously monitoring carbonate system parameters in the restored area.Results showed improvements in substrate complexity and coral coverage,with increased fish and macrobenthos densities,particularly in spring and summer.Fish numbers and large benthic species densities were higher in the restored area than in the fragmented area.Organic carbon content was also higher in the restored areas,indicating ongoing nutrient accumulation.Seasonal fluctuations in carbonate system indicators reflected coral growth and calcification in spring and summer,with positive net ecosystem productivity(NEP)and net ecosystem calcification(NEC).In contrast,winter conditions led to negative NEC and nearzero NEP,indicating decalcification.Furthermore,the study emphasizes the critical roles of the biological carbon pump(BCP)and coral carbonate pump(CCP)in the restoration process.In spring and summer,the increase in species diversity and abundance in the restored area can enhance overall ecological stability,thereby supporting the function of the BCP.The CCP further supports this by regulating carbonate chemistry and enhancing the reef's capacity to adapt to environmental changes.These processes are crucial in fostering the long-term recovery of coral reef ecosystems.展开更多
Typhoons can induce significant changes in the upper ocean,increasing sea surface nutrients via mixing,entrainment,and upwelling,which often leads to a substantial phytoplankton bloom in an oligotrophic region of the ...Typhoons can induce significant changes in the upper ocean,increasing sea surface nutrients via mixing,entrainment,and upwelling,which often leads to a substantial phytoplankton bloom in an oligotrophic region of the South China Sea(SCS),subsequently triggers carbon cycling and ecosystem responses,and enhances local marine primary productivity.Using a coupled physical-biogeochemical model,we analyzed the dynamic and ecological responses of the shelf region near the Dongsha Islands in the SCS caused by the fast-moving Typhoon Hagupit,and investigated the underlying mechanisms of sea surface chlorophyll-a increase.Results indicate that after Hagupit,sea surface temperature along the typhoon path rapidly decreased by maximum of 5.2℃,and the chlorophyll a along the typhoon path increased.In the shelf region near the Dongsha Islands,the sea surface chlorophyll a increased from 0.07 mg/m3(weekly average)to 0.14 mg/m3after Hagupit.The maximum increase reached 0.16 mg/m3,occurred 6 days after Hagupit,which is more than twice the average concentration before the typhoon.In contrast,the subsurface chlorophyll a decreased from 0.18 to 0.10 mg/m3.Power spectral analysis of horizontal velocity indicated that Hagupit triggered strong near-inertial waves(NIWs),which had a period of approximately 31.45 h,slightly greater than the local inertial period,and lasted for about one week.Therefore,we believed that while fast-moving typhoons cannot induce strong Ekman pumping velocity(EPV)as slow-moving ones do,they can trigger NIWs.The NIWs enhanced turbulent mixing in the upper 60 m,causing directly a rapid increase in sea surface chlorophyll a and nutrients after the typhoon.Two to three days later,the nitrates uptake by sea surface phytoplankton increased,promoting phytoplankton growth.Therefore,the variability in upper-ocean chlorophyll a induced by fast-moving typhoons involves not only strong dynamic processes but also significant participation of marine biological processes.展开更多
沟槽系统(Spur and Groove System)是一种典型的礁前斜坡地貌,由间隔规则、分布平行的长条状沙脊(Spur)和槽谷(Groove)组成。在沟槽系统形成、发展和维持的过程中,存在相对稳定的水动力环境,为研究其水动力特性提供了必要条件。本文基...沟槽系统(Spur and Groove System)是一种典型的礁前斜坡地貌,由间隔规则、分布平行的长条状沙脊(Spur)和槽谷(Groove)组成。在沟槽系统形成、发展和维持的过程中,存在相对稳定的水动力环境,为研究其水动力特性提供了必要条件。本文基于非静压模型NHWAVE建立三维数值波浪水槽,并结合沟槽系统模型,对规则波在沟槽系统岸礁上波生流及波浪演变特性进行数值模拟研究。同时研究了不同波浪要素(入射波高、波浪周期)及水深影响,系统分析了平均流场、环流强度以及消能率在沟槽系统岸礁上的变化规律。研究结果表明:沟槽系统显著改变了波浪流场的分布,且与波浪共同作用,形成了拉格朗日环流,进一步增强了波浪的能量耗散,进而有效减弱了波浪对沿岸地区的侵蚀,保护了沿岸地貌的稳定性。展开更多
随着海洋工程建设的快速推进和极端天气事件频发,海岸带滑坡的风险显著增加。然而,现有关于滑坡易发性区划的研究多集中于内陆山地滑坡,对海岸带滑坡灾害的易发性评价尚缺乏系统研究。以福建省海岸带为研究区,通过收集海岸带滑坡历史数...随着海洋工程建设的快速推进和极端天气事件频发,海岸带滑坡的风险显著增加。然而,现有关于滑坡易发性区划的研究多集中于内陆山地滑坡,对海岸带滑坡灾害的易发性评价尚缺乏系统研究。以福建省海岸带为研究区,通过收集海岸带滑坡历史数据,利用信息增益比法和皮尔森相关系数法构建适用于海岸带滑坡的易发性评价指标体系。以粒子群优化支持向量机(PSO-SVM)和随机森林(RF)为基学习器,构建Stacking异质集成学习模型,开展福建省海岸带滑坡的易发性评价和区划研究,探讨不同训练集与测试集划分比例对异质集成模型预测精度的影响。结果表明:Stacking异质集成学习模型在训练-测试集比例为70∶30时表现最佳,其准确度、精确度、召回率、F1分数值分别为0.869,0.842,0.909,0.874,其中准确度、精确度与F1分数较其他模型提升了最高0.198,0.227和0.140,其受试者工作特征(ROC)曲线下方面积(area under the curve,简称AUC)值为0.938,较其他模型提高了0.019~0.216;表明Stacking异质集成模型在海岸带滑坡易发性评价中具有较强的适用性和优越性。展开更多
The Yellow Sea and Bohai Sea are among the global shelf seas susceptible to typhoons every year.Using observations and high-resolution numerical simulations,the current study investigates the dramatic changes in tempe...The Yellow Sea and Bohai Sea are among the global shelf seas susceptible to typhoons every year.Using observations and high-resolution numerical simulations,the current study investigates the dramatic changes in temperature and ocean heat content(OHC)of the Yellow Sea and Bohai Sea caused by Super Typhoon Maysak in early September 2020,which is representative of northwardortheastward-bypassing typhoons with centers just to the east of the study area.Temperature shows spatially coherent cooling in the upper mixed layer but warming in the subsurface layer in the majority of the offshore waters,due to wind-enhanced vertical mixing.In lower layers from the thermocline to sea bottom,temperature experiences significant warming in northeastern coastal waters of the Shandong Peninsula and in regions just off the Subei Shoal,but significant cooling in western coastal waters of the Korean Peninsula and southern coastal waters of the Shandong Peninsula.Significant temperature warming/cooling in lower layers is caused by coastal downwelling/upwelling.The total OHC of the study area decreases rapidly during Typhoon Maysak(2020)’s passage,which is generated comparably by latent heat loss at the sea surface and southward heat advection out of the study area at the southern boundary.Reduced shortwave radiation contributes positively but secondarily to the decreasing OHC during the first day.A numerical experiment suggests that Typhoon Maysak(2020)-induced OHC decline could have greatly affected the regional climate evolution in the following seasons.More studies are needed to fully understand the impacts of typhoons on regional climate changes in shelf seas at different time scales.展开更多
Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature...Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature forecasting model based on ConvLSTM for the northern SCS and,in conjunction with the ocean forecasting system LICOM Forecast System(LFS),constructed a hybrid Fusion model using Wasserstein-Distance optimization.The ability of these three models to forecast key MHW metrics with a 10-day lead was assessed during the summer of 2022 in the SCS.Overall,the Fusion model takes advantage of LFS and ConvLSTM,providing superior forecasts for both the duration and intensity of MHWs in the southern SCS.LFS(ConvLSTM)overestimates(underestimates)the duration of MHWs and all models exhibit limitations in forecasting the intensity of MHWs in part of the SCS.The Fusion model's superior forecast skill for MHWs may be attributable to its more realistic representation of the upper-ocean thermal structure with shallower mixed-layer depths during MHWs.This study highlights that combining the deep learning technique with a dynamical model can improve MHW forecasting and has certain physical interpretability.展开更多
基金The Major Science and Technology plan of Hainan Province under contract No.ZDYF2023SHFZ173the Innovative Talent Foundation of Hainan Province under contract No.KJRC2023C39the National Natural Science Foundation of China under contract No.42161144006 or 3511/21。
摘要Coral reefs are critical for marine biodiversity and coastal protection but face severe threats from climate change and human activities.This study conducted seasonal surveys on the composition of biological communities and organic carbon content in the restored,natural,and fragmented reef areas in the northern part of Wuzhizhou Island,while continuously monitoring carbonate system parameters in the restored area.Results showed improvements in substrate complexity and coral coverage,with increased fish and macrobenthos densities,particularly in spring and summer.Fish numbers and large benthic species densities were higher in the restored area than in the fragmented area.Organic carbon content was also higher in the restored areas,indicating ongoing nutrient accumulation.Seasonal fluctuations in carbonate system indicators reflected coral growth and calcification in spring and summer,with positive net ecosystem productivity(NEP)and net ecosystem calcification(NEC).In contrast,winter conditions led to negative NEC and nearzero NEP,indicating decalcification.Furthermore,the study emphasizes the critical roles of the biological carbon pump(BCP)and coral carbonate pump(CCP)in the restoration process.In spring and summer,the increase in species diversity and abundance in the restored area can enhance overall ecological stability,thereby supporting the function of the BCP.The CCP further supports this by regulating carbonate chemistry and enhancing the reef's capacity to adapt to environmental changes.These processes are crucial in fostering the long-term recovery of coral reef ecosystems.
基金Supported by the National Key Research and Development Program of China(No.2021YFC3101104)。
摘要Typhoons can induce significant changes in the upper ocean,increasing sea surface nutrients via mixing,entrainment,and upwelling,which often leads to a substantial phytoplankton bloom in an oligotrophic region of the South China Sea(SCS),subsequently triggers carbon cycling and ecosystem responses,and enhances local marine primary productivity.Using a coupled physical-biogeochemical model,we analyzed the dynamic and ecological responses of the shelf region near the Dongsha Islands in the SCS caused by the fast-moving Typhoon Hagupit,and investigated the underlying mechanisms of sea surface chlorophyll-a increase.Results indicate that after Hagupit,sea surface temperature along the typhoon path rapidly decreased by maximum of 5.2℃,and the chlorophyll a along the typhoon path increased.In the shelf region near the Dongsha Islands,the sea surface chlorophyll a increased from 0.07 mg/m3(weekly average)to 0.14 mg/m3after Hagupit.The maximum increase reached 0.16 mg/m3,occurred 6 days after Hagupit,which is more than twice the average concentration before the typhoon.In contrast,the subsurface chlorophyll a decreased from 0.18 to 0.10 mg/m3.Power spectral analysis of horizontal velocity indicated that Hagupit triggered strong near-inertial waves(NIWs),which had a period of approximately 31.45 h,slightly greater than the local inertial period,and lasted for about one week.Therefore,we believed that while fast-moving typhoons cannot induce strong Ekman pumping velocity(EPV)as slow-moving ones do,they can trigger NIWs.The NIWs enhanced turbulent mixing in the upper 60 m,causing directly a rapid increase in sea surface chlorophyll a and nutrients after the typhoon.Two to three days later,the nitrates uptake by sea surface phytoplankton increased,promoting phytoplankton growth.Therefore,the variability in upper-ocean chlorophyll a induced by fast-moving typhoons involves not only strong dynamic processes but also significant participation of marine biological processes.
摘要沟槽系统(Spur and Groove System)是一种典型的礁前斜坡地貌,由间隔规则、分布平行的长条状沙脊(Spur)和槽谷(Groove)组成。在沟槽系统形成、发展和维持的过程中,存在相对稳定的水动力环境,为研究其水动力特性提供了必要条件。本文基于非静压模型NHWAVE建立三维数值波浪水槽,并结合沟槽系统模型,对规则波在沟槽系统岸礁上波生流及波浪演变特性进行数值模拟研究。同时研究了不同波浪要素(入射波高、波浪周期)及水深影响,系统分析了平均流场、环流强度以及消能率在沟槽系统岸礁上的变化规律。研究结果表明:沟槽系统显著改变了波浪流场的分布,且与波浪共同作用,形成了拉格朗日环流,进一步增强了波浪的能量耗散,进而有效减弱了波浪对沿岸地区的侵蚀,保护了沿岸地貌的稳定性。
摘要随着海洋工程建设的快速推进和极端天气事件频发,海岸带滑坡的风险显著增加。然而,现有关于滑坡易发性区划的研究多集中于内陆山地滑坡,对海岸带滑坡灾害的易发性评价尚缺乏系统研究。以福建省海岸带为研究区,通过收集海岸带滑坡历史数据,利用信息增益比法和皮尔森相关系数法构建适用于海岸带滑坡的易发性评价指标体系。以粒子群优化支持向量机(PSO-SVM)和随机森林(RF)为基学习器,构建Stacking异质集成学习模型,开展福建省海岸带滑坡的易发性评价和区划研究,探讨不同训练集与测试集划分比例对异质集成模型预测精度的影响。结果表明:Stacking异质集成学习模型在训练-测试集比例为70∶30时表现最佳,其准确度、精确度、召回率、F1分数值分别为0.869,0.842,0.909,0.874,其中准确度、精确度与F1分数较其他模型提升了最高0.198,0.227和0.140,其受试者工作特征(ROC)曲线下方面积(area under the curve,简称AUC)值为0.938,较其他模型提高了0.019~0.216;表明Stacking异质集成模型在海岸带滑坡易发性评价中具有较强的适用性和优越性。
基金supported by the National Key Research and Development Program of China(Grant Nos.2022YFF0801400 and 2021YFF0704002)the Shandong Provincial Natural Science Foundation(Grant No.ZR2024LQX002)the National Science Foundation of China(Grant No.42176016).
摘要The Yellow Sea and Bohai Sea are among the global shelf seas susceptible to typhoons every year.Using observations and high-resolution numerical simulations,the current study investigates the dramatic changes in temperature and ocean heat content(OHC)of the Yellow Sea and Bohai Sea caused by Super Typhoon Maysak in early September 2020,which is representative of northwardortheastward-bypassing typhoons with centers just to the east of the study area.Temperature shows spatially coherent cooling in the upper mixed layer but warming in the subsurface layer in the majority of the offshore waters,due to wind-enhanced vertical mixing.In lower layers from the thermocline to sea bottom,temperature experiences significant warming in northeastern coastal waters of the Shandong Peninsula and in regions just off the Subei Shoal,but significant cooling in western coastal waters of the Korean Peninsula and southern coastal waters of the Shandong Peninsula.Significant temperature warming/cooling in lower layers is caused by coastal downwelling/upwelling.The total OHC of the study area decreases rapidly during Typhoon Maysak(2020)’s passage,which is generated comparably by latent heat loss at the sea surface and southward heat advection out of the study area at the southern boundary.Reduced shortwave radiation contributes positively but secondarily to the decreasing OHC during the first day.A numerical experiment suggests that Typhoon Maysak(2020)-induced OHC decline could have greatly affected the regional climate evolution in the following seasons.More studies are needed to fully understand the impacts of typhoons on regional climate changes in shelf seas at different time scales.
基金supported by the National Natural Science Foundation of China [grant numbers 42375168 and 42205035]a Shanghai Science and Technology Commission Project [grant number 23DZ1204704]。
摘要Marine heatwaves(MHWs)in the South China Sea(SCS)significantly impact marine ecosystems and socioeconomic development,yet accurately forecasting MHWs remains a challenge.This study developed an upper-ocean temperature forecasting model based on ConvLSTM for the northern SCS and,in conjunction with the ocean forecasting system LICOM Forecast System(LFS),constructed a hybrid Fusion model using Wasserstein-Distance optimization.The ability of these three models to forecast key MHW metrics with a 10-day lead was assessed during the summer of 2022 in the SCS.Overall,the Fusion model takes advantage of LFS and ConvLSTM,providing superior forecasts for both the duration and intensity of MHWs in the southern SCS.LFS(ConvLSTM)overestimates(underestimates)the duration of MHWs and all models exhibit limitations in forecasting the intensity of MHWs in part of the SCS.The Fusion model's superior forecast skill for MHWs may be attributable to its more realistic representation of the upper-ocean thermal structure with shallower mixed-layer depths during MHWs.This study highlights that combining the deep learning technique with a dynamical model can improve MHW forecasting and has certain physical interpretability.