In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by ...In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.展开更多
Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while r...Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.展开更多
The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric ...The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.展开更多
Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional pr...Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional processes,and underlying mechanisms of global natural vegetation,particularly in the case of ongoing climate warming.In this study,we visualize the spatio-temporal pattern and inter-transition procedure of global PNV,analyse the shifting distances and directions of global PNV under the influence of climatic disturbance,and explore the mechanisms of global PNV in response to temperature and precipitation fluctuations.To achieve this,we utilize meteorological data,mainly temperature and precipitation,from six phases:the Last Inter-Glacial(LIG),the Last Glacial Maximum(LGM),the Mid Holocene(MH),the Present Day(PD),2030(20212040)and 2090(2081–2100),and employ a widely-accepted comprehensive and sequential classification sy–stem(CSCS)for global PNV classification.We find that the spatial patterns of five PNV groups(forest,shrubland,savanna,grassland and tundra)generally align with their respective ecotopes,although their distributions have shifted due to fluctuating temperature and precipitation.Notably,we observe an unexpected transition between tundra and savanna despite their geographical distance.The shifts in distance and direction of five PNV groups are mainly driven by temperature and precipitation,although there is heterogeneity among these shifts for each group.Indeed,the heterogeneity observed among different global PNV groups suggests that they may possess varying capacities to adjust to and withstand the impacts of changing climate.The spatio-temporal distributions,mutual transitions and shift tendencies of global PNV and its underlying mechanism in face of changing climate,as revealed in this study,can significantly contribute to the development of strategies for mitigating warming and promoting re-vegetation in degraded regions worldwide.展开更多
The aim of this work is to inventory and study the lignicolous parasitic macrofungi of the Tin plant formation. The mycological outings from July to September 2018 and 2019, collected forty-four (44) basidiomes throug...The aim of this work is to inventory and study the lignicolous parasitic macrofungi of the Tin plant formation. The mycological outings from July to September 2018 and 2019, collected forty-four (44) basidiomes through a random sampling device over an area of 40,000 m2 including 1000 m long by 40 m2 wide. The standard methods and techniques used in mycology for taxonomic studies were used to describe and classify the carpophores collected in three families: Hymenochaetaceae, Ganodermataceae and Polyporaceae, into eight genera: Onnia (4.55%), Amauroderma (4.55%), Ganoderma (20.45%), Phellinus (52.27%), Inonotus (4.55%), Phellinopsis (6.82%), Grammothele (2.27%) and Trametes (4.55%). The genera Phellinus and Ganoderma were the most abundant. Finally, eight species were identified: Inonotus cf. ochroporus, Inonotus cf. pachyphloeus, Phellinus cf. cryptarum, Phellinus cf. hartigii, Phellinus cf. hippophaecola;Phellinus cf. robustus, Phellinus cf. igniarius, et Amauroderma cf. fasciculatum. Seven fungal species belong to the family Hymenochaetaceae and only the species Amauroderma cf. fasciculatum is a Ganodermataceae. However, all these fungal species are shown to be parasites of trunks and/or branches of the following woody: Parkia biglobosa (50%), Anogeissus leiocarpus (25%), Annona senegalensis (12.5%) and Mangifera indica (12.5%). Authors attest that the presence of phytoparasitic polypores in a plant formation is an indicator of aging hence the urgency to put in place the appropriate measures to safeguard and restore Tin’s plant formation.展开更多
Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aime...Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.展开更多
The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetatio...The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.展开更多
Permafrost in Northeast China is undergoing extensive and rapid degradation,and it is of great importance to understand the dynamics of vegetation response to permafrost degradation during different periods in this re...Permafrost in Northeast China is undergoing extensive and rapid degradation,and it is of great importance to understand the dynamics of vegetation response to permafrost degradation during different periods in this region.Based on the meteorological station data and MODIS land surface temperature data,we mapped the distribution of permafrost using the surface frost number(SFN)model to analyze the permafrost degradation processes in Northeast China from 1981 to 2020.We investigated the spatiotemporal variation characteristics of vegetation and its response to permafrost degradation during different periods from 1982 to 2020 using the normalized difference vegetation index(NDVI).We further discussed the dominant factors influencing the vegetation dynamics in the permafrost degradation processes.Results indicated that the permafrost area in Northeast China decreased significantly by 1.01×10^(5) km^(2) in the past 40 a.The permafrost stability continued to weaken,with large areas of stable permafrost(SP)converted to semi-stable permafrost(SSP)and unstable permafrost(UP)after 2000.From 1982 to 2020,NDVI exhibited a significant decreasing trend in the seasonal frost(SF)region,while it exhibited an increasing trend in the permafrost region.NDVI in the UP and SSP regions changed from a significant increasing trend before 2000 to a nonsignificant decreasing trend after 2000.In 78.63%of the permafrost region,there was a negative correlation between the SFN and NDVI from 1982 to 2020.In the SP and SSP regions,the correlation between the SFN and NDVI was predominantly negative,while in the UP region,it was predominantly positive.Temperature was the dominant factor influencing the NDVI variations in the permafrost region from 1982 to 2020,and the impact of precipitation on NDVI variations increased after 2000.The findings elucidate the complex dynamics of vegetation in the permafrost region of Northeast China and provide deeper insights into the response mechanisms of vegetation in cold regions to permafrost degradation induced by climate change.展开更多
基金Supported by the National Natural Science Foundation of China(No.40675071)~~
文摘In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.
基金supported by the National Natural Science Foundation of China(42271360 and 42271399)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(CAST)(2020QNRC001)the Fundamental Research Funds for the Central Universities,China(2662021JC013,CCNU22QN018)。
文摘Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.
基金This research was supported by the Ningxia Hui Autonomous Region Key Research and Development Plan(2022BEG03052).
文摘The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.
基金funded by the National Natural Science Foundation of China(grants No.30960264,31160475 and 42071258)Open Research Fund of TPESER(grant No.TPESER202208)+2 种基金Special Fund for Basic Scientific Research of Central Colleges,Chang’an University,China(grant No.300102353501)Natural Science Foundation of Gansu Province,China(grant No.22JR5RA857)Higher Education Novel Foundation of Gansu Province,China(grant No.2021B-130)。
文摘Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional processes,and underlying mechanisms of global natural vegetation,particularly in the case of ongoing climate warming.In this study,we visualize the spatio-temporal pattern and inter-transition procedure of global PNV,analyse the shifting distances and directions of global PNV under the influence of climatic disturbance,and explore the mechanisms of global PNV in response to temperature and precipitation fluctuations.To achieve this,we utilize meteorological data,mainly temperature and precipitation,from six phases:the Last Inter-Glacial(LIG),the Last Glacial Maximum(LGM),the Mid Holocene(MH),the Present Day(PD),2030(20212040)and 2090(2081–2100),and employ a widely-accepted comprehensive and sequential classification sy–stem(CSCS)for global PNV classification.We find that the spatial patterns of five PNV groups(forest,shrubland,savanna,grassland and tundra)generally align with their respective ecotopes,although their distributions have shifted due to fluctuating temperature and precipitation.Notably,we observe an unexpected transition between tundra and savanna despite their geographical distance.The shifts in distance and direction of five PNV groups are mainly driven by temperature and precipitation,although there is heterogeneity among these shifts for each group.Indeed,the heterogeneity observed among different global PNV groups suggests that they may possess varying capacities to adjust to and withstand the impacts of changing climate.The spatio-temporal distributions,mutual transitions and shift tendencies of global PNV and its underlying mechanism in face of changing climate,as revealed in this study,can significantly contribute to the development of strategies for mitigating warming and promoting re-vegetation in degraded regions worldwide.
文摘The aim of this work is to inventory and study the lignicolous parasitic macrofungi of the Tin plant formation. The mycological outings from July to September 2018 and 2019, collected forty-four (44) basidiomes through a random sampling device over an area of 40,000 m2 including 1000 m long by 40 m2 wide. The standard methods and techniques used in mycology for taxonomic studies were used to describe and classify the carpophores collected in three families: Hymenochaetaceae, Ganodermataceae and Polyporaceae, into eight genera: Onnia (4.55%), Amauroderma (4.55%), Ganoderma (20.45%), Phellinus (52.27%), Inonotus (4.55%), Phellinopsis (6.82%), Grammothele (2.27%) and Trametes (4.55%). The genera Phellinus and Ganoderma were the most abundant. Finally, eight species were identified: Inonotus cf. ochroporus, Inonotus cf. pachyphloeus, Phellinus cf. cryptarum, Phellinus cf. hartigii, Phellinus cf. hippophaecola;Phellinus cf. robustus, Phellinus cf. igniarius, et Amauroderma cf. fasciculatum. Seven fungal species belong to the family Hymenochaetaceae and only the species Amauroderma cf. fasciculatum is a Ganodermataceae. However, all these fungal species are shown to be parasites of trunks and/or branches of the following woody: Parkia biglobosa (50%), Anogeissus leiocarpus (25%), Annona senegalensis (12.5%) and Mangifera indica (12.5%). Authors attest that the presence of phytoparasitic polypores in a plant formation is an indicator of aging hence the urgency to put in place the appropriate measures to safeguard and restore Tin’s plant formation.
基金National Natural Science Foundation of China(42230720).
文摘Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.
基金supported by the National Natural Science Foundation of China (42377472, 42174055)the Jiangxi Provincial Social Science "Fourteenth Five-Year Plan" (2024) Fund Project (24GL45)+1 种基金the Research Center of Resource and Environment Economics (20RGL01)the Provincial Finance Project of Jiangxi Academy of Sciences-Young Talent Cultivation Program (2023YSBG50010)
文摘The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.
基金funded by the National Natural Science Foundation of China(41641024)the Science and the Technology Project of Heilongjiang Communications Investment Group(JT-100000-ZC-FW-2021-0182)the Field Scientific Observation and Research Station of the Ministry of Education-Geological Environment System of the Permafrost Area in Northeast China(MEORS-PGSNEC).
文摘Permafrost in Northeast China is undergoing extensive and rapid degradation,and it is of great importance to understand the dynamics of vegetation response to permafrost degradation during different periods in this region.Based on the meteorological station data and MODIS land surface temperature data,we mapped the distribution of permafrost using the surface frost number(SFN)model to analyze the permafrost degradation processes in Northeast China from 1981 to 2020.We investigated the spatiotemporal variation characteristics of vegetation and its response to permafrost degradation during different periods from 1982 to 2020 using the normalized difference vegetation index(NDVI).We further discussed the dominant factors influencing the vegetation dynamics in the permafrost degradation processes.Results indicated that the permafrost area in Northeast China decreased significantly by 1.01×10^(5) km^(2) in the past 40 a.The permafrost stability continued to weaken,with large areas of stable permafrost(SP)converted to semi-stable permafrost(SSP)and unstable permafrost(UP)after 2000.From 1982 to 2020,NDVI exhibited a significant decreasing trend in the seasonal frost(SF)region,while it exhibited an increasing trend in the permafrost region.NDVI in the UP and SSP regions changed from a significant increasing trend before 2000 to a nonsignificant decreasing trend after 2000.In 78.63%of the permafrost region,there was a negative correlation between the SFN and NDVI from 1982 to 2020.In the SP and SSP regions,the correlation between the SFN and NDVI was predominantly negative,while in the UP region,it was predominantly positive.Temperature was the dominant factor influencing the NDVI variations in the permafrost region from 1982 to 2020,and the impact of precipitation on NDVI variations increased after 2000.The findings elucidate the complex dynamics of vegetation in the permafrost region of Northeast China and provide deeper insights into the response mechanisms of vegetation in cold regions to permafrost degradation induced by climate change.
