There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficien...There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.展开更多
Understanding the impact of meteorological and topographical factors on snow cover fraction(SCF)is crucial for water resource management in the Qilian Mountains(QLM),China.However,there is still a lack of adequate qua...Understanding the impact of meteorological and topographical factors on snow cover fraction(SCF)is crucial for water resource management in the Qilian Mountains(QLM),China.However,there is still a lack of adequate quantitative analysis of the impact of these factors.This study investigated the spatiotemporal characteristics and trends of SCF in the QLM based on the cloud-removed Moderate Resolution Imaging Spectroradiometer(MODIS)SCF dataset during 2000-2021 and conducted a quantitative analysis of the drivers using a histogram-based gradient boosting regression tree(HGBRT)model.The results indicated that the monthly distribution of SCF exhibited a bimodal pattern.The SCF showed a pattern of higher values in the western regions and lower values in the eastern regions.Overall,the SCF showed a decreasing trend during 2000-2021.The decrease in SCF occurred at higher elevations,while an increase was observed at lower elevations.At the annual scale,the SCF showed a downward trend in the western regions affected by westerly(52.84%of the QLM).However,the opposite trend was observed in the eastern regions affected by monsoon(45.73%of the QLM).The SCF displayed broadly similar spatial patterns in autumn and winter,with a significant decrease in the western regions and a slight increase in the central and eastern regions.The effect of spring SCF on spring surface runoff was more pronounced than that of winter SCF.Furthermore,compared with meteorological factors,a variation of 46.53%in spring surface runoff can be attributed to changes in spring SCF.At the annual scale,temperature and relative humidity were the most important drivers of SCF change.An increase in temperature exceeding 0.04°C/a was observed to result in a decline in SCF,with a maximum decrease of 0.22%/a.An increase in relative humidity of more than 0.02%/a stabilized the rise in SCF(about 0.06%/a).The impacts of slope and aspect were found to be minimal.At the seasonal scale,the primary factors impacting SCF change varied.In spring,precipitation and wind speed emerged as the primary drivers.In autumn,precipitation and temperature were identified as the primary drivers.In winter,relative humidity and precipitation were the most important drivers.In contrast to the other seasons,slope exerted the strongest influence on SCF change in summer.This study facilitates a detailed quantitative description of SCF change in the QLM,enhancing the effectiveness of watershed water resource management and ecological conservation efforts in this region.展开更多
Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the fron...Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has not been achieved due to the limitations of traditional scientometrics methods.The present synthesis of information employed BERTopic,an advanced natural language processing tool,to analyze the extensive ecological literature on grassland degradation.We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject.Our analysis identified key topics in the global grassland degradation research domain,including the effects of grassland degradation on ecosystem functions,grassland ecological restoration and biodiversity conservation,erosion processes and hydrological models in grasslands,and others.The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature.Compared to traditional scientometrics analysis,BERTopic provides a more comprehensive perspective on the research areas,revealing not only popular topics but also emerging research areas that traditional methods may overlook,although scientometrics offers more specificity and detail.Therefore,we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas.This study represents an emerging application of BERTopic algorithms in ecological research,particularly in the critical research focused on global grassland degradation.It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion.Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems,and it marks an important stride towards more sophisticated,data-driven analysis in ecology.展开更多
为探究青藏高原碳储量的估算方法及其驱动要素,本研究基于生态系统服务和权衡综合评估(Integratedvaluation of ecosystem service and tradeoffs,InVEST)模型,利用实测数据估算青藏高原碳储量,结合气候和土壤因子建立结构方程模型,分...为探究青藏高原碳储量的估算方法及其驱动要素,本研究基于生态系统服务和权衡综合评估(Integratedvaluation of ecosystem service and tradeoffs,InVEST)模型,利用实测数据估算青藏高原碳储量,结合气候和土壤因子建立结构方程模型,分析碳储量主要驱动因素。结果表明:青藏高原碳密度整体呈东南高、西北低的空间格局;进一步探究不同植被类型碳储量特征发现,高寒嵩草、杂草类草甸的碳储量最高,达1.97×10^(11)Mg;敏感性分析表明,地上碳密度对总碳密度的变化最为敏感,斜率为44.73;就驱动要素而言,发现降水、pH值、阳离子交换、有机质、全氮和速效氮是青藏高原碳密度的重要驱动因子。研究结果可为高寒生态系统碳平衡提供参考,也可为区域生态系统碳库管理和人类活动调控提供科学依据。展开更多
The growth, reproductive properties and the variations in total lipids and fatty acids in the gonads and muscle tissue of the mantis shrimp Squilla mantis （Crustacea： Stomatopoda） caught from the gulf of Gabes in T...The growth, reproductive properties and the variations in total lipids and fatty acids in the gonads and muscle tissue of the mantis shrimp Squilla mantis （Crustacea： Stomatopoda） caught from the gulf of Gabes in Tunisia were studied by sampling carried out between Jan. 2005 and Dec. 2006 to elucidate the importance of these components during sexual maturation. A total of 16,569 specimens were examined. The sex of this species was determined macroscopically and the proportion of females （47.07%） was significantly lower than that of males （52.93%） with a ratio of 1 ：l. 12 （male^female）. The mean total lengths （TL） of the male and female individuals were 142.02 ~： 22.76 mm and 141.45 ＋ 24.37 mm, respectively. Length-weight （TL-W） relationship was estimated as W = 7 ~ l06 TL3 o644 for females and W = 4 ~ 10＂6 TL320o7 for males, being altometrically positive for both sexes. The reproductive season, evaluated from the gonado-somatic index （GS1）, extended from Dec. to July, with a peak in Feb.. The smallest mature female was 93 mm total length. Fifty percent of the females were mature at 147.19 mm total length. The levels of lipid displayed pronounced seasonal fluctuations with the highest value in Feb. and the lowest value in Oct.. Major fatty acids in both gonads and muscle tissue （female and male） were C 14：0, C 16：0, C 18：0, C 18： I n-9, C 18：2n-6, C 18：3n-3, C20：4n-6, C20：5n-3 and C22：6n-3. Significant increases in the levels of saturated and poly-unsaturated fatty acids were observed in gonads. The levels of n-3 poly-unsaturated fatty acids （PUFA）, particularly C20：5n-3, decreased in gonads as ovarian development proceeded. Docosahexaenoic acid （DHA）, linoleic acid （LA） and eicosapentaenoic acid （EPA） were the most abundant polyunsaturated fatty acids （PUFAs） in the muscle tissue for both male and female. The highest percentages for EPA and DHA were found in winter and summer season for Squilla mantis in the Gulf of Gabes. The n-3/n-6 ratio fatty acids ratio in Squilla mantis can be significantly influenced by spawning and season. It was conchtded that the mantis shrimp is a healthy item in the human diet during the winter and summer period when balanced n-3/n-6 ratios and EPA and DHA levels are considered.展开更多
Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of ...Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of plate tectonics theory(Trümpy, 2001). With the progress in various studies, the concept of Tethys has evolved from a Mesozoic ocean into three long-term evolving oceans:Proto-Tethys, Paleo-Tethys, and Neo-Tethys (Figure 1), and their life cycles cover the entire Phanerozoic era (Wu et al., 2020).展开更多
Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction...Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction of the historical Tibetan Plateau biomes is not possible due to the lack of quantitative methods that enable appropriate classification of alpine biomes based on proxy data such as fossil pollen records.In this study,a pollen-based biome classification model was developed by applying a random forest algorithm(a supervised machine learning method)based on modern pollen assemblages on and around the Tibetan Plateau,and its robustness was assessed by comparing its results with the predictions of the biomisation method.The results indicated that modern biome distributions reconstructed using the random forest model based on modern pollen data generally concurred with the observed zonal vegetation.The random forest model had a significantly higher accuracy than the biomisation method,indicating the former is a more suitable tool for reconstructing alpine biome changes on the Tibetan Plateau.The random forest model was then applied to reconstruct the Tibetan Plateau biome changes from 22 ka BP to the present based on 51 fossil pollen records.The reconstructed biome distribution changes on the Tibetan Plateau generally corresponded to global climate changes and Asian monsoon variations.In the Last Glacial Maximum,the Tibetan Plateau was mainly desert with subtropical forests distributed in the southeast.During the last deglaciation,the alpine steppe began expanding and gradually became zonal vegetation in the central and eastern regions.Alpine meadow occupied the eastern and southeastern areas of the Tibetan Plateau since the early Holocene,and the forest-meadow-steppe-desert pattern running southeast to northwest on the Tibetan Plateau was established afterwards.In the mid-Holocene,subtropical forests extended north,which reflected the“optimum”condition.During the late Holocene,alpine meadows and alpine steppes expanded south.展开更多
Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through a...Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through accelerating the fermentation of large quantities of long-accumulated soil organic carbon to CH4 by microorganisms particularly methanogens [3]. However, the ultimate CH4 budget in peatlands under the global warming scenario is also determined by changes in the CH4 oxidation activity of the methanotrophs [4]. Thus, identifications of active methanogens and methanotrophs, as well as their metabolic potentials in peatlands, are essential for understanding the overall peatland feedback to global warming.展开更多
基金supported by the Ecological Conservation and High-Quality Development of the Yellow River Basin Program,China(2022-YRUC-010102)the Second Tibetan Plateau Scientific Expedition and Research Program,China(20190ZKK0405)the Basic Research Fund Project of Innovation Team of Novel Forage Germplasm and Sustainable Utilization of Grassland Resources,China(BR22-12-07)。
文摘There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.
基金funded by the Key Research and Development Project for Ecological Civilization Construction in Gansu Province(24YFFA010)the Gansu Province Major Science and Technology Project(22ZD6FA005)+2 种基金the Natural Science Foundation of Gansu Province(24JRRA091)the Shanxi Province Basic Research Program(Free Exploration Category)Youth Project(202403021212316)the Science and Technology Innovation Program for Universities in Shanxi Province(2024L327)。
文摘Understanding the impact of meteorological and topographical factors on snow cover fraction(SCF)is crucial for water resource management in the Qilian Mountains(QLM),China.However,there is still a lack of adequate quantitative analysis of the impact of these factors.This study investigated the spatiotemporal characteristics and trends of SCF in the QLM based on the cloud-removed Moderate Resolution Imaging Spectroradiometer(MODIS)SCF dataset during 2000-2021 and conducted a quantitative analysis of the drivers using a histogram-based gradient boosting regression tree(HGBRT)model.The results indicated that the monthly distribution of SCF exhibited a bimodal pattern.The SCF showed a pattern of higher values in the western regions and lower values in the eastern regions.Overall,the SCF showed a decreasing trend during 2000-2021.The decrease in SCF occurred at higher elevations,while an increase was observed at lower elevations.At the annual scale,the SCF showed a downward trend in the western regions affected by westerly(52.84%of the QLM).However,the opposite trend was observed in the eastern regions affected by monsoon(45.73%of the QLM).The SCF displayed broadly similar spatial patterns in autumn and winter,with a significant decrease in the western regions and a slight increase in the central and eastern regions.The effect of spring SCF on spring surface runoff was more pronounced than that of winter SCF.Furthermore,compared with meteorological factors,a variation of 46.53%in spring surface runoff can be attributed to changes in spring SCF.At the annual scale,temperature and relative humidity were the most important drivers of SCF change.An increase in temperature exceeding 0.04°C/a was observed to result in a decline in SCF,with a maximum decrease of 0.22%/a.An increase in relative humidity of more than 0.02%/a stabilized the rise in SCF(about 0.06%/a).The impacts of slope and aspect were found to be minimal.At the seasonal scale,the primary factors impacting SCF change varied.In spring,precipitation and wind speed emerged as the primary drivers.In autumn,precipitation and temperature were identified as the primary drivers.In winter,relative humidity and precipitation were the most important drivers.In contrast to the other seasons,slope exerted the strongest influence on SCF change in summer.This study facilitates a detailed quantitative description of SCF change in the QLM,enhancing the effectiveness of watershed water resource management and ecological conservation efforts in this region.
基金financially supported by the First-Class Curriculum Program at the School of Economics and Management,University of the Chinese Academy of Sciencesthe National Natural Science Foundation of China(42041005)the National Social Science Foundation of China(23BTQ054)。
文摘Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has not been achieved due to the limitations of traditional scientometrics methods.The present synthesis of information employed BERTopic,an advanced natural language processing tool,to analyze the extensive ecological literature on grassland degradation.We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject.Our analysis identified key topics in the global grassland degradation research domain,including the effects of grassland degradation on ecosystem functions,grassland ecological restoration and biodiversity conservation,erosion processes and hydrological models in grasslands,and others.The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature.Compared to traditional scientometrics analysis,BERTopic provides a more comprehensive perspective on the research areas,revealing not only popular topics but also emerging research areas that traditional methods may overlook,although scientometrics offers more specificity and detail.Therefore,we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas.This study represents an emerging application of BERTopic algorithms in ecological research,particularly in the critical research focused on global grassland degradation.It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion.Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems,and it marks an important stride towards more sophisticated,data-driven analysis in ecology.
文摘为探究青藏高原碳储量的估算方法及其驱动要素,本研究基于生态系统服务和权衡综合评估(Integratedvaluation of ecosystem service and tradeoffs,InVEST)模型,利用实测数据估算青藏高原碳储量,结合气候和土壤因子建立结构方程模型,分析碳储量主要驱动因素。结果表明:青藏高原碳密度整体呈东南高、西北低的空间格局;进一步探究不同植被类型碳储量特征发现,高寒嵩草、杂草类草甸的碳储量最高,达1.97×10^(11)Mg;敏感性分析表明,地上碳密度对总碳密度的变化最为敏感,斜率为44.73;就驱动要素而言,发现降水、pH值、阳离子交换、有机质、全氮和速效氮是青藏高原碳密度的重要驱动因子。研究结果可为高寒生态系统碳平衡提供参考,也可为区域生态系统碳库管理和人类活动调控提供科学依据。
文摘The growth, reproductive properties and the variations in total lipids and fatty acids in the gonads and muscle tissue of the mantis shrimp Squilla mantis （Crustacea： Stomatopoda） caught from the gulf of Gabes in Tunisia were studied by sampling carried out between Jan. 2005 and Dec. 2006 to elucidate the importance of these components during sexual maturation. A total of 16,569 specimens were examined. The sex of this species was determined macroscopically and the proportion of females （47.07%） was significantly lower than that of males （52.93%） with a ratio of 1 ：l. 12 （male^female）. The mean total lengths （TL） of the male and female individuals were 142.02 ~： 22.76 mm and 141.45 ＋ 24.37 mm, respectively. Length-weight （TL-W） relationship was estimated as W = 7 ~ l06 TL3 o644 for females and W = 4 ~ 10＂6 TL320o7 for males, being altometrically positive for both sexes. The reproductive season, evaluated from the gonado-somatic index （GS1）, extended from Dec. to July, with a peak in Feb.. The smallest mature female was 93 mm total length. Fifty percent of the females were mature at 147.19 mm total length. The levels of lipid displayed pronounced seasonal fluctuations with the highest value in Feb. and the lowest value in Oct.. Major fatty acids in both gonads and muscle tissue （female and male） were C 14：0, C 16：0, C 18：0, C 18： I n-9, C 18：2n-6, C 18：3n-3, C20：4n-6, C20：5n-3 and C22：6n-3. Significant increases in the levels of saturated and poly-unsaturated fatty acids were observed in gonads. The levels of n-3 poly-unsaturated fatty acids （PUFA）, particularly C20：5n-3, decreased in gonads as ovarian development proceeded. Docosahexaenoic acid （DHA）, linoleic acid （LA） and eicosapentaenoic acid （EPA） were the most abundant polyunsaturated fatty acids （PUFAs） in the muscle tissue for both male and female. The highest percentages for EPA and DHA were found in winter and summer season for Squilla mantis in the Gulf of Gabes. The n-3/n-6 ratio fatty acids ratio in Squilla mantis can be significantly influenced by spawning and season. It was conchtded that the mantis shrimp is a healthy item in the human diet during the winter and summer period when balanced n-3/n-6 ratios and EPA and DHA levels are considered.
文摘Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of plate tectonics theory(Trümpy, 2001). With the progress in various studies, the concept of Tethys has evolved from a Mesozoic ocean into three long-term evolving oceans:Proto-Tethys, Paleo-Tethys, and Neo-Tethys (Figure 1), and their life cycles cover the entire Phanerozoic era (Wu et al., 2020).
基金supported by the National Natural Science Foundation of China(Grant No.41690113)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA20070101)the National Natural Science Foundation of China(Grant Nos.42071114,41977395,and 41671202)。
文摘Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction of the historical Tibetan Plateau biomes is not possible due to the lack of quantitative methods that enable appropriate classification of alpine biomes based on proxy data such as fossil pollen records.In this study,a pollen-based biome classification model was developed by applying a random forest algorithm(a supervised machine learning method)based on modern pollen assemblages on and around the Tibetan Plateau,and its robustness was assessed by comparing its results with the predictions of the biomisation method.The results indicated that modern biome distributions reconstructed using the random forest model based on modern pollen data generally concurred with the observed zonal vegetation.The random forest model had a significantly higher accuracy than the biomisation method,indicating the former is a more suitable tool for reconstructing alpine biome changes on the Tibetan Plateau.The random forest model was then applied to reconstruct the Tibetan Plateau biome changes from 22 ka BP to the present based on 51 fossil pollen records.The reconstructed biome distribution changes on the Tibetan Plateau generally corresponded to global climate changes and Asian monsoon variations.In the Last Glacial Maximum,the Tibetan Plateau was mainly desert with subtropical forests distributed in the southeast.During the last deglaciation,the alpine steppe began expanding and gradually became zonal vegetation in the central and eastern regions.Alpine meadow occupied the eastern and southeastern areas of the Tibetan Plateau since the early Holocene,and the forest-meadow-steppe-desert pattern running southeast to northwest on the Tibetan Plateau was established afterwards.In the mid-Holocene,subtropical forests extended north,which reflected the“optimum”condition.During the late Holocene,alpine meadows and alpine steppes expanded south.
基金supported by the Strategic Priority Research Program A of the Chinese Academy of Sciences (CAS) (XDA20050104)the Joint CAS-MPG Research Project (HZXM20225001MI)+2 种基金the National Natural Science Foundation of China (42041005)the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (2019QZKK0304)the Fundamental Research Funds for the Central Universities。
文摘Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through accelerating the fermentation of large quantities of long-accumulated soil organic carbon to CH4 by microorganisms particularly methanogens [3]. However, the ultimate CH4 budget in peatlands under the global warming scenario is also determined by changes in the CH4 oxidation activity of the methanotrophs [4]. Thus, identifications of active methanogens and methanotrophs, as well as their metabolic potentials in peatlands, are essential for understanding the overall peatland feedback to global warming.
