Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well ...Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well understood. This study aimed to enhance comprehension of this critical issue by integrating the run theory for drought identification, Mann-Kendall trend analysis, and partial correlation attribution methods to analyze global drought dynamics in 1901–2018. Methodological innovations include:(1) a standardized drought severity metric enabling cross-typology comparisons;and (2) quantitative separation of precipitation and temperature impacts. Key findings reveal that socioeconomic drought severity exceeded meteorological, agricultural, and hydrological droughts by 350.48%, 47.80%, and 14.40%, respectively. Temporal analysis of Standardized Precipitation Evapotranspiration Index (SPEI) trends demonstrated intensification gradients:SPEI24 (-0.09slope/100 yr)> SPEI01 (-0.088/100 yr)> SPEI06 (-0.087/100 yr)> SPEI12 (-0.086/100 yr). Climate drivers exhibited distinct patterns, with precipitation showing stronger partial correlations across all drought types (meteorological:0.78;agricultural:0.76;hydrological:0.60;socioeconomic:0.39) compared to temperature (meteorological:-0.45;agricultural:-0.38;hydrological:-0.27;socioeconomic:-0.18). These results quantitatively establish a hierarchical climate response gradient among drought types. The framework advances drought typology theory through three original contributions:(1)systematic quantification of cross-typology drought severity disparities;(2) precipitation-temperature influence partitioning across drought types;and (3) identification of socioeconomic drought as the most climate-decoupled yet fastest-intensifying type. This study refined drought typological theories and provides a methodological foundation for climate-resilient drought management planning.展开更多
Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high qual...Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high quality observations are not available with sufficient frequency.However,existing models are vulnerable to spatial heterogeneity and land cover changes,which are frequent in human-dominated regions.To obtain quality time series of satellite images in a human-dominated region,this study developed the Modified Flexible Spatial-temporal Data Fusion(MFSDAF)approach based on the Flexible Spatial-temporal Data Fusion(FSDAF)model by using the enhanced linear regression(ELR).Multiple experiments of various land cover change scenarios were conducted based on both actual and simulated satellite images,respectively.The proposed MFSDAF model was validated by using the correlation coefficient(r),relative root mean square error(RRMSE),and structural similarity(SSIM),and was then compared with the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM)and FSDAF models.Results show that in the presence of significant land cover change,MFSDAF showed a maximum increase in r,RRMSE,and SSIM of 0.0313,0.0109 and 0.049,respectively,compared to FSDAF,while ESTARFM performed best with less temporal difference of in the input images.In conditions of stable landscape changes,the three performance statistics indicated a small advantage of MFSDAF over FSDAF,but were 0.0286,0.0102,0.0317 higher than for ESTARFM,respectively.MFSDAF showed greater accuracy of capturing subtle changes and created high-precision images from both actual and simulated satellite images.展开更多
China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is...China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is critical.This paper researches China’s most forested province,Fujian Province,as the study area.We proposed a grid-based approach to assess the regional carbon footprint in accordance with the Intergovernmental Panel on Climate Change’s(IPCC)carbon emission guidelines.Our method of assessment also introduced carbon emission indicators with our improved and published Net Primary Production(NPP)based on process simulation.The carbon footprint in Fujian Province from 2005-2017 was calculated and examined from a spatiotemporal perspective.Ecological indicators were used in the sustainability assessment.The research draws the following conclusions:1)the carbon footprint in the eastern regions of Fujian Province was higher due to rapid economic development;2)that of the western regions was lower;3)an uptrend in the carbon footprint of Fujian Province was observed.All five ecological indicators based on carbon emissions and economic and social data showed an ecologically unsustainable trend over 13 years in the research area due to unsustainable economic development.Therefore,it is urgent to balance the relationship between economic development and environmental protection.Our research provides scientific references for achieving ecological civilization and sustainability in a similar region.展开更多
Developmental plasticity is critical for plants to adapt to constantly changing environments. Plant root hairs displaydramatic plasticity under different environments and therefore play crucial roles in defense agains...Developmental plasticity is critical for plants to adapt to constantly changing environments. Plant root hairs displaydramatic plasticity under different environments and therefore play crucial roles in defense against environmentalstressors. Here, we report the isolation of an Arabidopsis mutant, salinity over-sensitive mutant 1-1 (som1-1), also exhibitingroot hair developmental defects. Map-based cloning and allelic analyses confirmed that som1-1 is a new mutantallele of SPIRRIG (SPI), which encodes a Beige and Chediak Higashi (BEACH) domain-containing protein. SPI has beenreported to facilitate actin dependent root hair development by temporally and spatially regulating the expressionof BRICK1 (BRK1), a subunit of the SCAR/WAVE actin nucleating promoting complex. Our living cell imaging examinationsrevealed that salt stress induces an altered actin organization in root hair that mimics those in the spi mutant,implying SPI may respond to salt stress induced root hair plasticity by modulating actin cytoskeleton organization.Furthermore, we found BRK1 is also involved in root hair developmental change under salt stress, and overexpressionof BRK1 resulted in root hairs over-sensitive to salt stress as those in spi mutant. Moreover, based on biochemicalanalyses, we found BRK1 is unstable and SPI mediates BRK1 stability. Functional loss of SPI results in the accumulationof steady-state of BRK1.展开更多
基金support from the National Key Research and Development Program of China (2023YFC3006604)the MOE Engineering Research Center of Desertification and Blown-Sand Control (2024-A3-2)
文摘Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well understood. This study aimed to enhance comprehension of this critical issue by integrating the run theory for drought identification, Mann-Kendall trend analysis, and partial correlation attribution methods to analyze global drought dynamics in 1901–2018. Methodological innovations include:(1) a standardized drought severity metric enabling cross-typology comparisons;and (2) quantitative separation of precipitation and temperature impacts. Key findings reveal that socioeconomic drought severity exceeded meteorological, agricultural, and hydrological droughts by 350.48%, 47.80%, and 14.40%, respectively. Temporal analysis of Standardized Precipitation Evapotranspiration Index (SPEI) trends demonstrated intensification gradients:SPEI24 (-0.09slope/100 yr)> SPEI01 (-0.088/100 yr)> SPEI06 (-0.087/100 yr)> SPEI12 (-0.086/100 yr). Climate drivers exhibited distinct patterns, with precipitation showing stronger partial correlations across all drought types (meteorological:0.78;agricultural:0.76;hydrological:0.60;socioeconomic:0.39) compared to temperature (meteorological:-0.45;agricultural:-0.38;hydrological:-0.27;socioeconomic:-0.18). These results quantitatively establish a hierarchical climate response gradient among drought types. The framework advances drought typology theory through three original contributions:(1)systematic quantification of cross-typology drought severity disparities;(2) precipitation-temperature influence partitioning across drought types;and (3) identification of socioeconomic drought as the most climate-decoupled yet fastest-intensifying type. This study refined drought typological theories and provides a methodological foundation for climate-resilient drought management planning.
基金This research received financial support by the National Natural Science Foundation of China(Grant Nos.41601562 and 41761014)the National Key Research and Development Program of China(No.2017YFC1502404)+1 种基金the China Institute of Water Resources and Hydropower Research Team Construction and Talent Development Project(No.JZ0145B752017)the Research Project for Young Teachers of Fujian Province(No.JAT160085).
文摘Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency,contributing to time series research where high quality observations are not available with sufficient frequency.However,existing models are vulnerable to spatial heterogeneity and land cover changes,which are frequent in human-dominated regions.To obtain quality time series of satellite images in a human-dominated region,this study developed the Modified Flexible Spatial-temporal Data Fusion(MFSDAF)approach based on the Flexible Spatial-temporal Data Fusion(FSDAF)model by using the enhanced linear regression(ELR).Multiple experiments of various land cover change scenarios were conducted based on both actual and simulated satellite images,respectively.The proposed MFSDAF model was validated by using the correlation coefficient(r),relative root mean square error(RRMSE),and structural similarity(SSIM),and was then compared with the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM)and FSDAF models.Results show that in the presence of significant land cover change,MFSDAF showed a maximum increase in r,RRMSE,and SSIM of 0.0313,0.0109 and 0.049,respectively,compared to FSDAF,while ESTARFM performed best with less temporal difference of in the input images.In conditions of stable landscape changes,the three performance statistics indicated a small advantage of MFSDAF over FSDAF,but were 0.0286,0.0102,0.0317 higher than for ESTARFM,respectively.MFSDAF showed greater accuracy of capturing subtle changes and created high-precision images from both actual and simulated satellite images.
基金supported by the National Natural Science Foundation of China(Grant No.41601562)sponsored by China Scholarship Council(No.201806655014)+1 种基金the Research Project for Young Teachers of Fujian Province(No.JAT160085)the Scientific Research Foundation of Fuzhou University(No.XRC-1536).
文摘China’s rapid economic development has initiated the deterioration of its ecological environment,posing a threat to the sustainable development of human society.As a result,an assessment of regional sustainability is critical.This paper researches China’s most forested province,Fujian Province,as the study area.We proposed a grid-based approach to assess the regional carbon footprint in accordance with the Intergovernmental Panel on Climate Change’s(IPCC)carbon emission guidelines.Our method of assessment also introduced carbon emission indicators with our improved and published Net Primary Production(NPP)based on process simulation.The carbon footprint in Fujian Province from 2005-2017 was calculated and examined from a spatiotemporal perspective.Ecological indicators were used in the sustainability assessment.The research draws the following conclusions:1)the carbon footprint in the eastern regions of Fujian Province was higher due to rapid economic development;2)that of the western regions was lower;3)an uptrend in the carbon footprint of Fujian Province was observed.All five ecological indicators based on carbon emissions and economic and social data showed an ecologically unsustainable trend over 13 years in the research area due to unsustainable economic development.Therefore,it is urgent to balance the relationship between economic development and environmental protection.Our research provides scientific references for achieving ecological civilization and sustainability in a similar region.
基金supported by the National Natural Science Foundation of China to LA(31470290,32070198)the Chinese Universities Scientific Fund to LA(2452020180)+1 种基金the National Science Foundation grants IOS-1923589 and IOS-2127485 and Department of Energy grant DE-SC0020358 to John Sthe Natural Science Foundation of Shaanxi Province to Jingxia S(2023-JC-YB-158).
文摘Developmental plasticity is critical for plants to adapt to constantly changing environments. Plant root hairs displaydramatic plasticity under different environments and therefore play crucial roles in defense against environmentalstressors. Here, we report the isolation of an Arabidopsis mutant, salinity over-sensitive mutant 1-1 (som1-1), also exhibitingroot hair developmental defects. Map-based cloning and allelic analyses confirmed that som1-1 is a new mutantallele of SPIRRIG (SPI), which encodes a Beige and Chediak Higashi (BEACH) domain-containing protein. SPI has beenreported to facilitate actin dependent root hair development by temporally and spatially regulating the expressionof BRICK1 (BRK1), a subunit of the SCAR/WAVE actin nucleating promoting complex. Our living cell imaging examinationsrevealed that salt stress induces an altered actin organization in root hair that mimics those in the spi mutant,implying SPI may respond to salt stress induced root hair plasticity by modulating actin cytoskeleton organization.Furthermore, we found BRK1 is also involved in root hair developmental change under salt stress, and overexpressionof BRK1 resulted in root hairs over-sensitive to salt stress as those in spi mutant. Moreover, based on biochemicalanalyses, we found BRK1 is unstable and SPI mediates BRK1 stability. Functional loss of SPI results in the accumulationof steady-state of BRK1.
