The rhizosphere, distinct from bulk soil, is defined as the volume of soil around living roots and influenced by root activities. We investigated protease, invertase, cellulase, urease, and acid phosphatase activities...The rhizosphere, distinct from bulk soil, is defined as the volume of soil around living roots and influenced by root activities. We investigated protease, invertase, cellulase, urease, and acid phosphatase activities in rhizosphere and bulk soils of six Nothotsuga longibracteata forest communities within Tianbaoyan National Nature Reserve, including N. longibracteata + either Phyllostachys pubescens, Schima superba, Rhododendron simiarum, Cunninghamia lanceolata, or Cyclobalanopsis glauca, and N. longibracteata pure forest. Rhizosphere soils possessed higher protease, invertase, cellulase, urease, and acid phosphatase activities than bulk soils. The highest invertase, urease, and acid phosphatase activities were observed in rhizosphere samples of N. longibracteata + S. superba. Protease was highest in the N. longibracteata + R. simiarum rhizosphere, while cellulase was highest in the pure N. longibracteata forest rhizosphere. All samples exhibited obvious rhizosphere effects on enzyme activities with a significant linear correlation between acid phosphatase and cellulase activities (p 〈 0.05) in rhizosphere soils and between protease and acid phosphatase activities (p 〈 0.05) in bulk soils. A principal component analysis, correlating 13 soil chemical properties indices relevant to enzyme activities, showed that protease, invertase, acid phosphatase, total N, and cellulase were the most important variables impacting rhizosphere soil quality.展开更多
We investigated the spatial distribution (horizontal and vertical concentrations) of copper (Cu), lead (Pb), zinc (Zn), and cadmium (Cd) in five wetland types (mudflat, aquaculture wetland, water area, farm...We investigated the spatial distribution (horizontal and vertical concentrations) of copper (Cu), lead (Pb), zinc (Zn), and cadmium (Cd) in five wetland types (mudflat, aquaculture wetland, water area, farmland wetland and mangrove) from three areas (Ningde, Fuding, and Xiapu), China. Cu concentrations in five wetland types descended in the order: farm wetland, mudflat, aquaculture, water area and mangrove. Pb concentrations decreased in the order: aquaculture, mangrove, farm wetland, mudflat, and water area. Zn content decreased in the order: farm wetland, water area, aquaculture, mudflat and mangrove, and Cd content decreased as follows: mangrove, aquacul- ture, water area, rnudflat, and farm wetland. Comparison of the concentrations of the same heavy metals in different areas showed that the highest Cu (63.75 mg kg-1) and Zn (152.32mgkg-1) concentrations occurred in Ningdecoastal wetlands; Pb (110.58 mg kg-1) and Cd (2.81 mg kg-1) contents were highest in Fuding wetlands, and the average contents of all heavy metals were very low in Xiapu wetlands. Examination of the vertical distribution showed that the Cu content was high in all mudflat layers; Pb and Cd concentrations were highest in aquaculture and mangrove wetlands, respectively, and Zn content was highest in farm wetlands. The spatial distribution of Cu and Zn contents for different areas decreased as follows: Ningde 〉 Fuding 〉 Xiapu, for Pb and Cd were most concentrated in Fuding coastal wetlands. Concentrations of Zn and Cu were highly correlated, while Zn and Cu were not significantly correlated with Pb.展开更多
Background:Forest is the largest biomass carbon(C)pool in China,taking up a substantial amount of atmospheric carbon dioxide.Although it is well understood that planted forests(PFs)act as a large C sink,the contributi...Background:Forest is the largest biomass carbon(C)pool in China,taking up a substantial amount of atmospheric carbon dioxide.Although it is well understood that planted forests(PFs)act as a large C sink,the contribution of human management to C storage enhancement remains obscure.Moreover,existing projections of forest C dynamics suffer from spatially inconsistent age and type information or neglected human management impacts.In this study,using developed PF age and type maps and data collected from 1371 forest plantation sites in China,we simulated biomass C stock change and quantified management impacts for the time period 2010-2050.Results:Results show that future forest biomass C increment might have been overestimated by 32.5%-107.5% in former studies.We also found that age-related growth will be by far the largest contributor to PF biomass C increment from 2010 to 2050(1.23±0.002 Pg C,1 Pg=10^(15) g=1 billion metric tons),followed by the impact of human management(0.57±0.02 Pg C),while the contribution of climate is slight(0.087±0.04 Pg C).Besides,an additional 0.24±0.07 Pg C can be stored if current PFs are all managed by 2050,resulting in a total increase of 2.13±0.05 Pg C.Conclusions:Forest management and age-related growth dominate the biomass C change in PFs,while the effect of climatic factors on the accumulation is minor.To achieve the ambitious goal of forest C stock enhancement by 3.5 Pg from 2020 to 2050,we advocate to improve the management of existing forests and reduce the requests for more lands for forest expansion,which helps mitigate potential conflicts with agricultural sectors.Our results highlight that appropriate planning and management are required for sustaining and enhancing biomass C sequestration in China’s PF.展开更多
The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of sh...The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of shelterforest remediation planning and sustainable management. In this study, a protection efficiency index (PEI) model was established using the projection pursuit method to assess the protective quality of the coastal shelter forest at the coastal section scale of Dongshan Island, China. Three criteria were used, including forest stand structure, forest belt structure, and windbreak effect; each criterion further comprised multiple factors. Based on survey data of 31 plots in the coastal shelter forest of Dongshan Island, we calculated PEI values using a projection of a pursuit model. The result showed 64.5 % of the PEIs fell at or below the middle level, which can indicate the status of the coastal shelterbelt is unsatisfactory. To further explore whether the different bays and land use types create significant differences in PEIs and evaluation indices, we used an ANOVA to test the influence of various bays and forms of land use on coastal shelterbelts. The results showed that PEI and most of the indices differed significantly by bay; mean tree height, mean DBH, mean crown width, stand density, vegetation coverage, and wind velocity reduction differed significantly by land use. Therefore, relevant measures for different locations, bays and surrounding land use can be proposed to improve the existing conditions of the coastal shelterbelt. The results of this study provide a theoretical and technical framework for future changes and sustainable management of coastal shelterbelt on Dongshan Island.展开更多
The exotic saltmarsh cordgrass,Spartina alterniflora(Loisel)Peterson&Saarela,is one of the important causes for the extensive destruction of mangroves in China due to its invasive nature.The species has rapidly sp...The exotic saltmarsh cordgrass,Spartina alterniflora(Loisel)Peterson&Saarela,is one of the important causes for the extensive destruction of mangroves in China due to its invasive nature.The species has rapidly spread wildly across coastal wetlands,challenging resource managers for control of its further spread.An investigation of S.alterniflora invasion and associated ecological risk is urgent in China's coastal wetlands.In this study,an ecological risk invasive index system was developed based on the Driving Force-Pressure-State-Impact-Response framework.Predictions were made of'warning degrees':zero warning and light,moderate,strong,and extreme warning,by developing a back propagation(BP)artificial neural network model for coastal wetlands in eastern Fujian Province.Our results suggest that S.alterniflora mainly has invaded Kandelia candel beaches and farmlands with clustered distributions.An early warning indicator system assessed the ecological risk of the invasion and showed a ladder-like distribution from high to low extending from the urban area in the central inland region with changes spread to adjacent areas.Areas of light warning and extreme warning accounted for43%and 7%,respectively,suggesting the BP neural network model is reliable prediction of the ecological risk of S.alterniflora invasion.The model predicts that distribution pattern of this invasive species will change little in the next 10 years.However,the invaded patches will become relatively more concentrated without warning predicted.We suggest that human factors such as land use activities may partially determine changes in warning degree.Our results emphasize that an early warning system for S.alterniflora invasion in China's eastern coastal wetlands is significant,and comprehensive control measures are needed,particularly for K.candel beach.展开更多
Background:Shifts in forest phenological events serve as strong indicators of climate change.However,the sensitivity of phenology events to climate change in relation to forest origins has received limited attention.M...Background:Shifts in forest phenological events serve as strong indicators of climate change.However,the sensitivity of phenology events to climate change in relation to forest origins has received limited attention.Moreover,it is unknown whether forest phenology changes with the proximity to forest edge.Methods:This study examined the green-up dates,dormancy dates,time-integrated NDVI(LiNDVI,a measure of vegetation productivity in growing season),and their sensitivities to climatic factors along the gradients of distance(i.e.proximity)to forest edge(0–2 km)in China's natural forests(NF)and planted forests(PF).For the analysis,field-surveyed data were integrated with Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI from 2000 to 2022.Results:Our results reveal that PF had earlier green-up dates,later dormancy dates,and higher LiNDVI than NF.However,green-up sensitivities to temperature were higher at the edges of NF,whereas no such pattern was observed in PF.Conversely,the sensitivity of dormancy dates remains relatively stable from the inner to the edge of both NF and PF,except for a quadratic change in dormancy date sensitivity to precipitation found in NF.Additionally,we found that the green-up sensitivity to temperature increased with decreasing proximity to edge in NF evergreen forests,while it showed the opposite trend in PF evergreen forests.Furthermore,we observed that the precipitation impact on green-up dates shifts from postponing to advancing from the inner to the edge of NF,whereas precipitation dominantly postpones PF's green-up dates regardless of the proximity to edge.The LiNDVI exhibits higher sensitivity to precipitation at the edge areas,a phenomenon observed in NF but not in PF.Conclusions:These results suggest that the responses of forests to climate change vary with the distance to the edge.With increasing edge forests,which results from fragmentation caused by global changes,we anticipate that desynchronized phenological events along the distance to the edge could alter biogeochemical cycles and reshape ecosystem services such as energy flows,pollination duration,and the tourism industry.Therefore,we advocate for further investigations of edge effects to improve ecosystem modelling,enhance forest stability,and promote sustainable tourism.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.31370624)the Specialized Research Fund for the Doctoral Program of Higher Education(Grant No.20103515110005)+3 种基金the National Science Foundation of Fujian,China(Grant No.2011J01071)Young Teacher Project of Fujian Province(Grant No.JA13118JK2013016)the National College Students’Innovation and Entrepreneurship Training Program(Grant No.111zc3009)
文摘The rhizosphere, distinct from bulk soil, is defined as the volume of soil around living roots and influenced by root activities. We investigated protease, invertase, cellulase, urease, and acid phosphatase activities in rhizosphere and bulk soils of six Nothotsuga longibracteata forest communities within Tianbaoyan National Nature Reserve, including N. longibracteata + either Phyllostachys pubescens, Schima superba, Rhododendron simiarum, Cunninghamia lanceolata, or Cyclobalanopsis glauca, and N. longibracteata pure forest. Rhizosphere soils possessed higher protease, invertase, cellulase, urease, and acid phosphatase activities than bulk soils. The highest invertase, urease, and acid phosphatase activities were observed in rhizosphere samples of N. longibracteata + S. superba. Protease was highest in the N. longibracteata + R. simiarum rhizosphere, while cellulase was highest in the pure N. longibracteata forest rhizosphere. All samples exhibited obvious rhizosphere effects on enzyme activities with a significant linear correlation between acid phosphatase and cellulase activities (p 〈 0.05) in rhizosphere soils and between protease and acid phosphatase activities (p 〈 0.05) in bulk soils. A principal component analysis, correlating 13 soil chemical properties indices relevant to enzyme activities, showed that protease, invertase, acid phosphatase, total N, and cellulase were the most important variables impacting rhizosphere soil quality.
基金supported by the National Natural Science Foundation of China(Grant No.31370624)Key Financing Project of Fujian Provincial Department of Science and Technology(2009N0009)
文摘We investigated the spatial distribution (horizontal and vertical concentrations) of copper (Cu), lead (Pb), zinc (Zn), and cadmium (Cd) in five wetland types (mudflat, aquaculture wetland, water area, farmland wetland and mangrove) from three areas (Ningde, Fuding, and Xiapu), China. Cu concentrations in five wetland types descended in the order: farm wetland, mudflat, aquaculture, water area and mangrove. Pb concentrations decreased in the order: aquaculture, mangrove, farm wetland, mudflat, and water area. Zn content decreased in the order: farm wetland, water area, aquaculture, mudflat and mangrove, and Cd content decreased as follows: mangrove, aquacul- ture, water area, rnudflat, and farm wetland. Comparison of the concentrations of the same heavy metals in different areas showed that the highest Cu (63.75 mg kg-1) and Zn (152.32mgkg-1) concentrations occurred in Ningdecoastal wetlands; Pb (110.58 mg kg-1) and Cd (2.81 mg kg-1) contents were highest in Fuding wetlands, and the average contents of all heavy metals were very low in Xiapu wetlands. Examination of the vertical distribution showed that the Cu content was high in all mudflat layers; Pb and Cd concentrations were highest in aquaculture and mangrove wetlands, respectively, and Zn content was highest in farm wetlands. The spatial distribution of Cu and Zn contents for different areas decreased as follows: Ningde 〉 Fuding 〉 Xiapu, for Pb and Cd were most concentrated in Fuding coastal wetlands. Concentrations of Zn and Cu were highly correlated, while Zn and Cu were not significantly correlated with Pb.
文摘Background:Forest is the largest biomass carbon(C)pool in China,taking up a substantial amount of atmospheric carbon dioxide.Although it is well understood that planted forests(PFs)act as a large C sink,the contribution of human management to C storage enhancement remains obscure.Moreover,existing projections of forest C dynamics suffer from spatially inconsistent age and type information or neglected human management impacts.In this study,using developed PF age and type maps and data collected from 1371 forest plantation sites in China,we simulated biomass C stock change and quantified management impacts for the time period 2010-2050.Results:Results show that future forest biomass C increment might have been overestimated by 32.5%-107.5% in former studies.We also found that age-related growth will be by far the largest contributor to PF biomass C increment from 2010 to 2050(1.23±0.002 Pg C,1 Pg=10^(15) g=1 billion metric tons),followed by the impact of human management(0.57±0.02 Pg C),while the contribution of climate is slight(0.087±0.04 Pg C).Besides,an additional 0.24±0.07 Pg C can be stored if current PFs are all managed by 2050,resulting in a total increase of 2.13±0.05 Pg C.Conclusions:Forest management and age-related growth dominate the biomass C change in PFs,while the effect of climatic factors on the accumulation is minor.To achieve the ambitious goal of forest C stock enhancement by 3.5 Pg from 2020 to 2050,we advocate to improve the management of existing forests and reduce the requests for more lands for forest expansion,which helps mitigate potential conflicts with agricultural sectors.Our results highlight that appropriate planning and management are required for sustaining and enhancing biomass C sequestration in China’s PF.
基金supported by the National Natural Science Foundation of China(Nos.31200365,31370624,and30870435)the Youth Science Fund of the Forestry College of Fujian Agriculture and Forestry University(No.6112C039V)
文摘The coastal shelter forest in China is under threat of destruction and degradation because of the impact of human activities. Protection efficiency assessment of the coastal shelterbelt is an important component of shelterforest remediation planning and sustainable management. In this study, a protection efficiency index (PEI) model was established using the projection pursuit method to assess the protective quality of the coastal shelter forest at the coastal section scale of Dongshan Island, China. Three criteria were used, including forest stand structure, forest belt structure, and windbreak effect; each criterion further comprised multiple factors. Based on survey data of 31 plots in the coastal shelter forest of Dongshan Island, we calculated PEI values using a projection of a pursuit model. The result showed 64.5 % of the PEIs fell at or below the middle level, which can indicate the status of the coastal shelterbelt is unsatisfactory. To further explore whether the different bays and land use types create significant differences in PEIs and evaluation indices, we used an ANOVA to test the influence of various bays and forms of land use on coastal shelterbelts. The results showed that PEI and most of the indices differed significantly by bay; mean tree height, mean DBH, mean crown width, stand density, vegetation coverage, and wind velocity reduction differed significantly by land use. Therefore, relevant measures for different locations, bays and surrounding land use can be proposed to improve the existing conditions of the coastal shelterbelt. The results of this study provide a theoretical and technical framework for future changes and sustainable management of coastal shelterbelt on Dongshan Island.
基金funded by Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University (72202200205)Fujian Province Natural Science (2022J01575)Science and Technology Innovation Project of Fujian Agriculture and Forestry University (KFA20036A)。
文摘The exotic saltmarsh cordgrass,Spartina alterniflora(Loisel)Peterson&Saarela,is one of the important causes for the extensive destruction of mangroves in China due to its invasive nature.The species has rapidly spread wildly across coastal wetlands,challenging resource managers for control of its further spread.An investigation of S.alterniflora invasion and associated ecological risk is urgent in China's coastal wetlands.In this study,an ecological risk invasive index system was developed based on the Driving Force-Pressure-State-Impact-Response framework.Predictions were made of'warning degrees':zero warning and light,moderate,strong,and extreme warning,by developing a back propagation(BP)artificial neural network model for coastal wetlands in eastern Fujian Province.Our results suggest that S.alterniflora mainly has invaded Kandelia candel beaches and farmlands with clustered distributions.An early warning indicator system assessed the ecological risk of the invasion and showed a ladder-like distribution from high to low extending from the urban area in the central inland region with changes spread to adjacent areas.Areas of light warning and extreme warning accounted for43%and 7%,respectively,suggesting the BP neural network model is reliable prediction of the ecological risk of S.alterniflora invasion.The model predicts that distribution pattern of this invasive species will change little in the next 10 years.However,the invaded patches will become relatively more concentrated without warning predicted.We suggest that human factors such as land use activities may partially determine changes in warning degree.Our results emphasize that an early warning system for S.alterniflora invasion in China's eastern coastal wetlands is significant,and comprehensive control measures are needed,particularly for K.candel beach.
基金supported by National Science Foundation of China(Nos.32001166,32371663)the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University,China(No.72202200205).
文摘Background:Shifts in forest phenological events serve as strong indicators of climate change.However,the sensitivity of phenology events to climate change in relation to forest origins has received limited attention.Moreover,it is unknown whether forest phenology changes with the proximity to forest edge.Methods:This study examined the green-up dates,dormancy dates,time-integrated NDVI(LiNDVI,a measure of vegetation productivity in growing season),and their sensitivities to climatic factors along the gradients of distance(i.e.proximity)to forest edge(0–2 km)in China's natural forests(NF)and planted forests(PF).For the analysis,field-surveyed data were integrated with Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI from 2000 to 2022.Results:Our results reveal that PF had earlier green-up dates,later dormancy dates,and higher LiNDVI than NF.However,green-up sensitivities to temperature were higher at the edges of NF,whereas no such pattern was observed in PF.Conversely,the sensitivity of dormancy dates remains relatively stable from the inner to the edge of both NF and PF,except for a quadratic change in dormancy date sensitivity to precipitation found in NF.Additionally,we found that the green-up sensitivity to temperature increased with decreasing proximity to edge in NF evergreen forests,while it showed the opposite trend in PF evergreen forests.Furthermore,we observed that the precipitation impact on green-up dates shifts from postponing to advancing from the inner to the edge of NF,whereas precipitation dominantly postpones PF's green-up dates regardless of the proximity to edge.The LiNDVI exhibits higher sensitivity to precipitation at the edge areas,a phenomenon observed in NF but not in PF.Conclusions:These results suggest that the responses of forests to climate change vary with the distance to the edge.With increasing edge forests,which results from fragmentation caused by global changes,we anticipate that desynchronized phenological events along the distance to the edge could alter biogeochemical cycles and reshape ecosystem services such as energy flows,pollination duration,and the tourism industry.Therefore,we advocate for further investigations of edge effects to improve ecosystem modelling,enhance forest stability,and promote sustainable tourism.