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Atmospheric water vapor is not only a key element of the global hydrological cycle but also the most abundant greenhouse gas. The phase transition and transportation of water vapor are essential for maintaining global energy balance and regulating hydrological processes. However, due to insufficient meteorological observational data, climate research in Africa faces significant limitations despite its substantial contribution to changes in global precipitable water vapor (PWV). In this study, we used MODIS near-infrared (NIR) PWV products and Berkeley temperature data to depict the spatial–temporal variability in PWV across Africa from 2001 to 2020. The results reveal a significant increasing trend in PWV over Africa, with an increase of 0.0158 cm/year. Nearly 99.96% of Africa shows an increase in PWV, with 88.95% of these areas experiencing statistically significant changes, particularly in central regions of Africa. The increase in PWV is more pronounced in high-value months compared to low-value months. The equatorial region of the Congo Basin exhibits higher PWV, which gradually decreases as latitude increases. Despite significant warming (0.0162 °C/year) in Africa, there is no consistent positive correlation between temperature and water vapor. A positive relationship between PWV and temperature is observed in western Africa, while a negative relationship is noted in eastern and southern Africa on an annual scale. Additionally, an increasing trend in precipitation (4.6669 mm/year) is observed, with a significant positive correlation between PWV and precipitation across most of Africa, although this relationship varies by month. These findings provide valuable insights into the comprehension of the hydrothermal variation in Africa amidst climate warming. [ABSTRACT FROM AUTHOR]

To address the limitations of existing public transit passenger flow prediction methods, which often rely on predefined graph structures for spatial modeling, inadequately consider fluctuations in passenger flow caused by changes in traffic conditions, and fail to capture short-term dynamic spatial dependencies, this paper proposed an adaptively balanced staticdynamic joint network (ASDNet) model. Firstly, the model used a temporal convolution network to capture the temporal correlation of sequences. Secondly, it employed graph convolution to capture the overall spatial information between sites, and then incorporated a dynamic graph isomorphic network to capture the hidden dynamic dependencies between dynamic graphs of neighboring time slots. Finally, it introduced an adaptively balanced mechanism to adjust the information transfer between static-dynamic joint networks. The model tested a real bus dataset derived from Guangzhou city. The results demonstrate that the model reduces the MAE, RMSE, and MAPE prediction error metric by an average of 12.2%, 9.9%, and 15%, respectively, and improves the R2 accuracy metric by an average of 6.3% compared to several benchmark models. These results indicate that the model can effectively capture the spatiotemporal variation law of passenger flow data and provide technical reference for bus operation management. [ABSTRACT FROM AUTHOR]

In order to master the influence of the East Route of South-to-North Water Diversion Project to the regional terrestrial water storage in Shandong, based on GRACE gravity satellite data from January 2010 to December 2017, combined with the data set of major hydrological factors (precipitation and evapotranspiration) in the same period, the changes of terrestrial water storage and major hydrological factors in the study area were studied by time period and region, and by the operating time of the South-to-North Water Diversion Project as the boundary. The influence of the South-to-North Water Diversion Project to the change of terrestrial water storage in Shandong Province was calculated based on the water transfer data of the South-to-North Water Diversion Project. The results show that the spatial distribution of terrestrial water storage in the study area decreases from east to west over the years. The seasonal characteristics show that the terrestrial water storage is abundant in summer and autumn, but less in spring and winter. The results show that the terrestrial water storage decay rate is 1.45 cm/a and -0.36 cm/a before and after the operation of the South-to-North Water Diversion Project respectively. It is found that the South-to-North Water Diversion Project has a good positive impact on the central and southern parts of western Shandong Province and the southern parts of central Shandong Province. In summary, the South-to-North Water Diversion Project has alleviated the decline trend of 56.9% of terrestrial water storage in Shandong Province, and has a positive effect on water resources conditions and terrestrial water storage enrichment in the study area during the study period. [ABSTRACT FROM AUTHOR]

Soil pH is crucial for the quality of the farmland and crop growth. The objective of this study is to analyze the spatial and temporal variations of farmland soil pH in Xinjiang (XJ), and to provide a scientific basis for soil improvement and agricultural production optimization. Based on soil pH data from XJ farmland in two periods, 2008~2010 and 2019~2021, geostatistical methods and kriging spatial interpolation techniques were employed to analyze the spatiotemporal changes in soil pH and to investigate the relationship between relevant influencing factors and pH over more than a decade. The results indicate that the spatiotemporal distribution of soil pH in XJ farmlands is uneven. Between 2019 and 2021, the average soil pH was 8.11, generally being on the higher side, with a coefficient of variation (CV) of 3.85%, indicating minimal spatial variability. In the farmland soil of Southern Xinjiang (S-XJ), the average pH value was 8.17, significantly higher than that of Northern Xinjiang (N-XJ), which was 8.10, demonstrating a spatial pattern of "higher in the south, lower in the north". Over the past decade, soil pH in XJ has significantly increased from 8.11 to 8.13, with a 0.05 unit increase in the north and a 0.01 unit increase in the south (p < 0.05). Regionally, Altay saw the largest increase of 0.22 units, while Bortala Mongol Autonomous Prefecture (Bortala) experienced the most significant decrease, dropping by 0.59 units. Furthermore, this study found that factors such as topography, nutrients, and irrigation methods all have certain influences on the spatial distribution of soil pH in XJ farmland, while variations in climate factors and fertilization levels may affect its long-term temporal changes. These research findings will provide new insights for adjusting and updating agricultural management measures related to soil pH regulation in XJ. [ABSTRACT FROM AUTHOR]

Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region's socio-economic framework. [ABSTRACT FROM AUTHOR]

Investigating the spatial-temporal evolution of land use and its driving forces provides a scientific basis for policy formulation, land-use structure adjustment, and ecological civilization development. Using the Google Earth Engine (GEE) platform, this study analyzed remote sensing images from 2000, 2010, and 2020 to derive basic land-use data for Putian City and its five districts and counties. These data were then systematically analyzed using methodologies such as Single Land-use Dynamics and Geo-informatic Tupu to reveal the characteristics of land-use transitions (LUTs), and the spatial-temporal evolution pattern over the past two decades in Putian City, China. Subsequently, socioeconomic conditions and macro policies were identified as driving factors to further explore the mechanisms behind land-use evolution in the study area through canonical correspondence analysis (CCA). The findings revealed that: (1) The predominant land-use structure in Putian City consisted mainly of cultivated land and forest land, with other land types interspersed within them, while built-up land exhibited continual outward expansion. (2) Various regions within Putian City exhibited varying degrees of abandoned farmland, ultimately transforming into wasteland (grassland) with weed growth, presenting significant challenges for ensuring food security and mitigating the conversion of cultivated land to non-agricultural and non-grain uses. (3) Specific macro-economic development objectives during distinct periods, particularly urban expansion and the growth of the secondary industry resulting from municipal and county mergers, emerged as pivotal factors driving the spatial and temporal evolution of land use and influenced the differential distribution pattern across Putian City. Consequently, this study suggests bolstering scientific planning and implementing effective regulations concerning land use, and it advocates for the efficient utilization of space-time resources pertaining to cultivated land, integrating them with agriculture, culture, and tourism endeavors. Such measures are proposed to ensure the harmonized and sustainable development of the regional ecological economy. [ABSTRACT FROM AUTHOR]

In this study, the spatial and temporal characteristics of rainfall and the risk of meteorological drought based on precipitation data observed in 22 meteorological stations over the period 1961 to 2020 in Shanxi province were analyzed. Four precipitation indices and modified Mann–Kendall test were used to analyze the patterns and trends of precipitation. Furthermore, the risk analysis for drought duration and severity of meteorological drought were analyzed with entropy copula. Results showed that the precipitation distribution is irregular and precipitation in central northern parts of Shanxi is more concentrated than that in southern Shanxi. The annual and seasonal precipitation concentration showed no significant change in most stations, while the daily precipitation concentration decreased in a few areas. Results also disclose that the number of droughts (which SPI3 values are less than 0) ranged from 61 to 80 during 1961–2020 and Shanxi tends to dry. The most severe drought event with the longest duration (27 months) and the largest severity (29.7) occurred at station 53,775. The entropy copula is suitable for drought frequency analysis and return period calculation and results indicate that the middle and northern parts of Shanxi are at high risk of drought according to the entropy copula calculated joint return period. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an important river in the western part of Jilin Province, the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province. Within the watershed, it governs the Momoge Wetland, the Xianghai Wetland, and the Danjiang Wetland in Jilin Province. The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space, and the intensification of land salinization. Zhenlai County and Da'an City in the Nenjiang River Basin have sufficient surface water resources, with surface water as the drinking water source. Baicheng City and Tongyu County have scarce surface water resources, and both use groundwater as their domestic water source. The main polluted section in the basin is the Xianghai Reservoir, and the annual water quality evaluation is Class V. However, the water quality of the Tao'er River, the main stream of the Nenjiang River, is significantly better than that of the Xianghai Reservoir. In order to better study the water environmental pollution situation in the Nenjiang River basin, monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality. This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development, agricultural pattern transformation, and the promotion of water ecological civilization construction. [ABSTRACT FROM AUTHOR]

The taillight shiner, Notropis maculatus (Hay in Proc United States Natl Museum 3:488-515, 1881), primarily occurs in the southeastern United States, with rare occurrences in Illinois, where it is state listed as endangered. The first observation in Illinois was in 1987 and the species was last seen in the state in 1988. However, the taillight shiner was recently rediscovered in Buttonland Swamp within the Cache River watershed in September 2020 during fish community surveys. A total of 311 taillight shiners were captured from September 2020 to October 2022 within Buttonland Swamp using electrofishing, mini fyke nets, and light traps from the fish community surveys. Habitat associations were assessed using repeated measures mixed models and a conditional inference tree was developed to assess the probability of taillight shiner occurrence in electrofishing samples based on habitat variables and dissolved oxygen. We also assessed differences in taillight shiner length among years and seasons. Emergent vegetation was particularly important in predicting the occurrence of taillight shiners in samples, with dissolved oxygen and silt/clay also being important. Taillight shiner length distributions were similar among years and significantly different among seasons. Spawning occurred in spring, while post-spawn mortality occurred between June and August. This study provides important information regarding habitat associations, probability of occurrence in samples, recruitment, and timing of post-spawn mortality of taillight shiners in Illinois, which could inform future sampling efforts in Illinois and adjacent states. This rediscovery indicates that the taillight shiner is still present in Illinois and further search efforts to assess the species' status in Illinois are needed. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Green Plastic Cover (GPC) has been widely used in construction sites of China as the main measure for dust suppression. As a unique land cover in China, GPC could be viewed as a sign for evaluating the intensity of urban construction. Therefore, time series GPC maps could provide a new perspective to understand the pattern of urban development, including both urban expansion and urban shrinkage. The objective of this study is to present a novel framework for detection of urban development patterns based on high resolution GPC maps generated from Google Earth Engine (GEE) cloud platform. Specifically, we first generated the GPC maps of 137 districts and counties in Shandong Province of China from 2018 to 2022 by combining time series spectral features and textural features derived from Sentinel-1 and Sentinel-2 images provided by GEE cloud platform. Afterwards, we designed a GPC-based urban development vigor index (GPC-UDVI) to evaluate the vitality of each city, which offers a novel perspective to identify shrinking cities. Experimental results demonstrated that the average overall accuracy of GPC maps is 89.696 %, which is accurate enough for the following analysis. Besides, the proposed GPC-UDVI exhibits a consistent trend with statistical data and could reveal urban development patterns with a high performance. Above all, dynamic monitoring of urban GPC through remote sensing is significant for understanding urban expansion modes and aiding in urban reconstruction management.

Atmospheric water vapor is not only a key element of the global hydrological cycle but also the most abundant greenhouse gas. The phase transition and transportation of water vapor are essential for maintaining global energy balance and regulating hydrological processes. However, due to insufficient meteorological observational data, climate research in Africa faces significant limitations despite its substantial contribution to changes in global precipitable water vapor (PWV). In this study, we used MODIS near-infrared (NIR) PWV products and Berkeley temperature data to depict the spatial–temporal variability in PWV across Africa from 2001 to 2020. The results reveal a significant increasing trend in PWV over Africa, with an increase of 0.0158 cm/year. Nearly 99.96% of Africa shows an increase in PWV, with 88.95% of these areas experiencing statistically significant changes, particularly in central regions of Africa. The increase in PWV is more pronounced in high-value months compared to low-value months. The equatorial region of the Congo Basin exhibits higher PWV, which gradually decreases as latitude increases. Despite significant warming (0.0162 °C/year) in Africa, there is no consistent positive correlation between temperature and water vapor. A positive relationship between PWV and temperature is observed in western Africa, while a negative relationship is noted in eastern and southern Africa on an annual scale. Additionally, an increasing trend in precipitation (4.6669 mm/year) is observed, with a significant positive correlation between PWV and precipitation across most of Africa, although this relationship varies by month. These findings provide valuable insights into the comprehension of the hydrothermal variation in Africa amidst climate warming.

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil pH is crucial for the quality of the farmland and crop growth. The objective of this study is to analyze the spatial and temporal variations of farmland soil pH in Xinjiang (XJ), and to provide a scientific basis for soil improvement and agricultural production optimization. Based on soil pH data from XJ farmland in two periods, 2008~2010 and 2019~2021, geostatistical methods and kriging spatial interpolation techniques were employed to analyze the spatiotemporal changes in soil pH and to investigate the relationship between relevant influencing factors and pH over more than a decade. The results indicate that the spatiotemporal distribution of soil pH in XJ farmlands is uneven. Between 2019 and 2021, the average soil pH was 8.11, generally being on the higher side, with a coefficient of variation (CV) of 3.85%, indicating minimal spatial variability. In the farmland soil of Southern Xinjiang (S-XJ), the average pH value was 8.17, significantly higher than that of Northern Xinjiang (N-XJ), which was 8.10, demonstrating a spatial pattern of “higher in the south, lower in the north”. Over the past decade, soil pH in XJ has significantly increased from 8.11 to 8.13, with a 0.05 unit increase in the north and a 0.01 unit increase in the south (p < 0.05). Regionally, Altay saw the largest increase of 0.22 units, while Bortala Mongol Autonomous Prefecture (Bortala) experienced the most significant decrease, dropping by 0.59 units. Furthermore, this study found that factors such as topography, nutrients, and irrigation methods all have certain influences on the spatial distribution of soil pH in XJ farmland, while variations in climate factors and fertilization levels may affect its long-term temporal changes. These research findings will provide new insights for adjusting and updating agricultural management measures related to soil pH regulation in XJ.

Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region’s socio-economic framework.

The relationships among ecosystem services (ESs) and their spatiotemporal dynamics plays an essential role in ESs management. However, it is difficult to characterize the spatial composition of ecosystem services bundles (ESB), clarify the complex relationships and their driving forces. This study estimated 6 specific ESs of Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) based on related models, using conjunction operations identified ESB, finally explored the trade-offs and synergies between ESs within each ESB, and furtherly suggested different management zones in terms of ESB types. The results indicated the values of all six key ESs have improved from 2000 to 2015, and shown a decreasing trend from the southeast to the northwest accompanied by expansion trend of the high value region. Additionally, ESB dominated by sand-fixing service were primarily distributed in the southwest and showed a trend of continuous and significant expansion from southwest to northeast during 2000–2015. And, wind speed, soil types, slope, vegetation types and population density are the main driving factors of ESB changes. What’s more, trade-offs and synergies among ESs appears the characteristics of spatial heterogeneity, especially between sand-fixing service and Net primary productivity, which presenting synergistic promotion relationship in bundles 1 and 2, while significant trade-offs in bundles 3 and 4. Finally, we divided BTSSCP into three zones—key improvement zone, ecological conservation zone, and integrated optimization zone based on ESB as per the regional sand-fixing capacity, enhancement potential and the relationship between ESs, and proposed specific suggestions for management in various ESB, which are beneficial to regional sustainable development and appropriate management.

This study delves into the temporal–spatial variations and influencing factors of interprovincial ecological efficiency in China, aiming to provide vital guidance for sustainable development and ecological equilibrium. Employing the super-efficiency SBM model, we compute ecological efficiency indices for 31 Chinese provinces from 2005 to 2021. Furthermore, utilizing Geodetectors, we conduct an in-depth analysis of the impact of key dimensions—economic factors, efficiency elements, environmental governance, pollution determinants, input factors, and natural components—consisting of 30 specific indicators of ecological efficiency. The findings unveil several significant insights. Firstly, interprovincial ecological efficiency in China has experienced undulating declines since 2005. Additionally, notable spatial agglomeration exists, with economically developed regions demonstrating elevated ecological efficiency, while less-developed areas exhibit lower levels. Moreover, among the influencing factors, (1) economic aspects hold a dominant role, where optimizing industrial structure and enhancing resource utilization efficiency can partially alleviate environmental pressure; (2) efficiency elements exhibit a progressive enhancement trend; (3) the impacts of environmental governance and pollution factors manifest complex dynamics, necessitating continuous policy support and comprehensive remediation; (4) despite the relatively weaker influence of natural components, vigilance remains imperative due to intensifying climate change and natural disasters; and (5) while input factors exert limited effects on ecological efficiency, their significance in resource allocation and sustainable development persists. [ABSTRACT FROM AUTHOR]

Variations in precipitation have a great influence on human society and the natural environment. Existing studies have provided substantial information regarding variations in the magnitude, frequency, and intensity of precipitation. However, little is known about how the start and end dates of precipitation change, which could offer crucial insights for related studies in agriculture, hydrology, and other related disciplines. Here, we present an analysis of variations in the start date, end date, and frequency of different precipitation intensities, using a widely used gauge-satellite-reanalysis-based merging product, during the latest period, 1980–2022, across China. The results show that the spatial–temporal variations in the start date, end date, and frequency of different precipitation intensities were complex among regions. For example, in northeast and northwest China, light precipitation (LP) started earlier and increased in frequency during the study period. In the Tibetan Plateau, precipitation at different intensities levels started earlier, heavy precipitation (HP) and violent precipitation ended earlier, and the frequency of LP and moderate precipitation increased significantly. The start date of HP shifted earlier in Southeast China (−0.28 days/year). Our findings could be helpful in providing a comprehensive understanding of precipitation changes under global warming and highlight the need to pay close attention to these precipitation changes in the future. [ABSTRACT FROM AUTHOR]

The impact of extreme climate change on terrestrial ecosystems continues to intensify. This study was conducted to understand extreme climate–vegetation interactions under exacerbated frequency, severity, and duration of extreme climatic events. The Inner Mongolian Plateau (IMP) was selected due to its sensitive natural location, which is particularly vulnerable to climate change. Based on the Normalized Difference Vegetation Index (NDVI) and daily meteorological station data from 1982 to 2020, changes in the patterns of vegetation and extreme climate in the three ecological zones (forest, steppe, and desert steppe) of the IMP were identified. Furthermore, the effects of extreme climate on vegetation were quantified using correlation analysis and a geographical detector. The results showed that the annual NDVI of 95.1%, 50.6%, and 19.5% of the area increased significantly in the forest, steppe, and desert steppe, respectively. The Tx90p (warm days) and Tn90p (warm nights) increased significantly at the rate of 0.21 and 0.235 day·yr−1, respectively, while the Tx10p (cold days) and Tn10p (cold nights) showed a significantly decreasing trend at the rate of −0.105 and −0.117 day·yr−1. An extreme warming phenomenon was observed in all extreme temperature indices on the IMP. The results of both the correlation analysis and factor detector indicated that extreme temperature intensity and frequency greatly affected forest vegetation. In contrast, extreme precipitation intensity and frequency were relatively more important to the vegetation of the desert steppe. The lag in NDVI response to extreme temperature intensity was not less than three months in the IMP; however, extreme precipitation intensity exhibited a two-month time lag in the NDVI. This study can improve our understanding of extreme climate–vegetation interactions, provide theoretical support for disaster mitigation, and aid in understanding the ecological environment of the IMP. [ABSTRACT FROM AUTHOR]

Both the resource environmental carrying capacity (RECC) and supply-side reform are crucial for achieving sustainable national developments. However, current research on RECC lacks consideration of the supply-side industrial structures and factors, and the relationship between RECC and supply-side reform remains unrevealed. In order to measure the RECC in China at the provincial level from 2005 to 2019, this study constructs an evaluation index based on industrial structure. It utilizes the TOPSIS model coupled with the supply-demand balance method and environmental capacity method while gathering and summarizing the indicators related to natural resource support, socio-economic support, and environmental factor accommodation. The analysis of evolutionary characteristics and spatial heterogeneity is carried out by statistical and spatial econometric methods, and the impact of the supply-side reform policy on RECC is examined using a bidirectional fixed-effect model. The findings indicate the following: (1) China's RECC demonstrates a clear upward trend, with higher values in the west and lower values in the east. The average annual growth rate from 2016 to 2019 (18.12%) is nearly three times that of the period from 2005 to 2010 (6.28%), indicating a significant acceleration in the increase in RECC post-supply-side reform. (2) The spatial agglomeration of RECC and its sub-system support is observed, as the allocation of nature resources and markets promotes the convergence of regional differences and enhances the spatial convergence of the RECC. (3) The implementation of supply-side reform policies has a positive impact on RECC, with industrial upgrading playing a particularly significant role. This study provides a new idea and method for the selection of evaluation indicators, quantitatively assessing province-level RECC and understanding the potential effects of national supply-side policies on RECC. [ABSTRACT FROM AUTHOR]

Guangzhou and Shenzhen are two core cities in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). It is increasingly important to regulate water quality in urban development. The Forel–Ule Index (FUI) can be obtained by optical data and is an important indicator. Therefore, we used Sentinel-2 to calculate the FUI of 41 lakes and reservoirs in Guangzhou and Shenzhen from January to December in 2016–2021, and analyzed their spatio-temporal variations, including spatial distributions, seasonal variations, and inter-annual variations. We also performed a correlation analysis of driving factors. In Guangzhou, the FUI was low in the north and west, and high in the south and east. In Shenzhen, the FUI was high in the west and low in the east. Moreover, 68% of the lakes and reservoirs in Guangzhou exhibited seasonal variations, with a low FUI in summer and autumn, and high levels in spring and winter. Shenzhen had the lowest FUI in autumn. Furthermore, 36% of the lakes and reservoirs in Guangzhou exhibited increasing inter-annual variations, whereas Shenzhen exhibited stable and decreasing inter-annual variations. Among the 41 lakes and reservoirs analyzed herein, the FUI of 10 water areas were positively correlated with precipitation, while the FUI of 31 water areas were negatively correlated with precipitation. Increased precipitation leads to an increase in external pollutants and sediment, as well as the resuspension of substances in the water, resulting in more turbid water. Therefore, an increase in precipitation is positively correlated with the FUI, whereas a decrease in precipitation is negatively correlated with the FUI. These findings can be used to design suitable management policies to maintain and control the local water quality. [ABSTRACT FROM AUTHOR]

As China’s largest cross-regional urban agglomerations, the middle reaches of the Yangtze River urban agglomerations (MRYRUA) possess both significant societal carbon source volume and ecological carbon sequestration capacity. Nevertheless, with the uncontrolled expansion of urban energy consumption activities and the industry migration from eastern coastal regions to inland cities, the carbon budget pattern of territorial space is increasingly unbalanced in the MRYRUA. To achieve low-carbon regulation, this study utilized land use and energy consumption data from 31 cities within the MRYRUA to establish a “carbon source-carbon sink” quantification and spatiotemporal exploration model, revealing the spatial-temporal variation of carbon budgets from 2005 to 2020. Furthermore, we developed a carbon balance indicator analysis system by employing the carbon offset rate (COR), carbon productivity (CP), Gini coefficient, ecological support coefficient (ESC), economic contribution coefficient (ECC), and functional zoning was performed. Finally, using the GM (1,1) model, we derived the carbon budget pattern for 2050 and explored the differentiated regulatory mechanisms under the carbon balance perspective. The results indicated that: (1) The MRYRUA’s territorial carbon budgets have increased annually, displaying a spatial distribution pattern with the highest values in the central region, followed by the northwest, and the lowest in the southeast near water bodies. The spatiotemporal differentiation effects manifest as an east–west axial development trend, with spatiotemporal clustering effects demonstrating a propensity for outward dispersion from the northern hot spot radiation core. (2) The MRYRUA’s COR has consistently remained below 10% and decreased annually, while the CP has shown a yearly increase at an accelerating rate. The ESC and ECC exhibit evident spatial heterogeneity among cities. In response to the carbon emission economic benefits and carbon sequestration ecological carrying capacity reflected by carbon balance indicators, each city was classified into low-carbon economic zones, carbon intensity control zones, carbon sink functional zones, and high-carbon optimization zones. (3) From 2020 to 2050, the polarization trend of the carbon budget pattern continues to intensify. Subsequently, we have established a differentiated territorial spatial carbon balance regulatory mechanism. This mechanism strengthens the leading role of low-carbon economic zones in the green low-carbon transition, moderately retains the carbon sink functional zones in the southeast with solid carbon fixation capabilities, and promotes the transition of the northern carbon intensity control zones and high-carbon optimization zones to low-carbon economic zones. The research findings provide a scientific basis for formulating territorial spatial planning policies from a carbon neutrality perspective.

Evapotranspiration (ET) is a vital variable in the water and energy cycles and significantly influenced by changing environmental conditions. However, in the data-lacking agro-pastoral ecotone in northern China (APENC) that has undergone warming and wetting climate trend and implemented a series of ecological restoration projects (ERP), the effects of climate change and vegetation greening on the magnitude, drivers, and mechanism of ET variations are not fully understood yet. In this study, we evaluated nine commonly used ET products to determine the most applicable one in the APENC based on the in-situ observations and water balance method. Subsequently, the ET variation was examined and the contribution of each factor to the ET change from 1982 to 2017 was quantified. Results show that the Global Land Evaporation Amsterdam Model (GLEAM) performed best and meets the accuracy requirements for research in the APENC. Based on the GLEAM data, our analysis reveals a notable increase in ET at a rate of 1.11 mm/y (p

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a sensitive climate change indicator, global multi‐depth soil moisture (SM) has undergone great variation due to warming trends during the past decades. Here, we investigate the evolutionary pattern of SM and then carry out an attribution analysis from climate and human perspectives. The results reveal an unbalanced surface and rootzone variation trend during 1980–2020. The surface soil had approximately equal proportions of drying and wetting. Nonetheless, the percentage of the wetting region is significantly higher than that of the drying region for rootzone soil. The significantly drying region is mainly distributed in habitable areas, while the remarkably wetting region is usually located in the harsh climate and tropical humid zones. According to the attribution analysis using the Feature Importance Index of the Random Forest model, Pearson correlation coefficient, Maximum information coefficient, Spearman rank correlation coefficient, and Granger causality with 99% statistical significance, both climatic and human factors presented significant impacts on SM. Specifically, air temperature and evaporation are thought to be the primary climatic factors affecting the seasonal and long‐term variability of SM, respectively. Irrigation water withdrawal is regarded as the dominant driving force of SM variation among six human water withdrawals, and domestic and electricity water withdrawals play indispensable roles in SM fluctuation. Additionally, SM also provides profound feedbacks on climatic factors and human water withdrawals. The global spatial‐temporal SM variation along with warming temperatures could seriously risk food security and sustainable development, which needs to be addressed. Key Points: Drying regions are distributed in habitable areas, while wetting regions are located in the harsh climate and tropical humid zonesAir temperature and evaporation are thought to be the primary climatic factors affecting the seasonal and long‐term variability of soil moisture (SM)Irrigation water withdrawal is regarded as the dominant driving force of SM variation among the six human water withdrawals [ABSTRACT FROM AUTHOR]

The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas. In this paper, based on 320 groups of soil and groundwater samples collected at the same time, geostatistical analysis and multiple regression analysis were comprehensively used to conduct the evaluation of nitrogen contents in both groundwater and soil. From May to August, as the nitrification of groundwater is dominant, the average concentration of nitrate nitrogen is 34.80 mg/L; The variation of soil ammonia nitrogen and nitrate nitrogen is moderate from May to July, and the variation coefficient decreased sharply and then increased in August. There is a high correlation between the nitrate nitrogen in groundwater and soil in July, and there is a high correlation between the nitrate nitrogen in groundwater and ammonium nitrogen in soil in August and nitrate nitrogen in soil in July. From May to August, the area of low groundwater nitrate nitrogen in 0–5 mg/L and 5–10 mg/L decreased from 10.97% to 0, and the proportion of high-value area (greater than 70 mg/L) increased from 21.19% to 27.29%. Nitrate nitrogen is the main factor affecting the quality of groundwater. The correlation analysis of nitrate nitrogen in groundwater, nitrate nitrogen in soil and ammonium nitrogen shows that they have a certain period of delay. The areas with high concentration of nitrate in groundwater are mainly concentrated in the western part of the study area, which has a high consistency with the high value areas of soil nitrate distribution from July to August, and a high difference with the spatial position of soil ammonia nitrogen distribution in August.

Due to global climate change and the intensification of human activities, the ecological function of Wuliangsu Lake Basin has been seriously degraded. Obtaining accurate spatial–temporal dynamics of regional ecological environment quality is essential for the evaluation of ecological management and restoration effects. This study assessed the trend changes and drivers of the Remote Sensing Ecological Index (RSEI) in the Wuliangsu Lake Basin from 2000−2020. Firstly, the trend analysis method and hurst index were used to analyze the temporal and spatial variation of RSEI. Then the main factors of RSEI variation were analyzed using meteorological data, integrated nighttime lighting data, and population density data. Overall, the RSEI shows an increasing trend from the west to the east with a rate of 0.0034 year−1 over the last 21 years. The area change of RSEI was 54.22%, 63.80% and 52.43% for 2000−2006, 2007−2013 and 2014−2020, respectively, which indicates that most areas have a stable ecological environment. However, the overall Future Improvement Trend (FIT) area of RSEI is 42.21%, mainly in Dengkou area, Urad Qianqi and central area. This indicates that the RSEI remains stable locally and shows an overall improving trend. The results of the correlation analysis showed that the areas influenced by meteorological and human factors were highly coincident, mainly in Dengkou and northern Linhe areas and Urad Qianqi. Considering the lagging effect of ecological engineering, the sustainable development status of RSEI in the western and eastern regions will maintain an improving trend in the future. Our study confirms the complex relationship between RSEI and meteorological and human activities, which is crucial for the scientific management of watershed ecosystems under the influence of anthropogenic factors.

To determine the spatial–temporal variations and the factors leading to vegetation recovery in the loess hilly and gully region of China, this study analyzed a two-decade trend in the variation of vegetation cover based on normalized difference vegetation index (NDVI) data from 1998 to 2019 using the Sen + MK test and Hurst index and determined the driving factors using the Geodetector model. The vegetation index in the area was high in the southeast and low in the northwest, with an overall increasing rate of 0.0108/year. The areas with significant improvement in vegetation cover accounted for 95.14%, and the areas with persistent change accounted for 37.36%. Annual precipitation is the most crucial factor driving the NDVI change, and potential evapotranspiration, relative humidity, elevation, land use type, and vegetation type can also explain local variations. The effect of compound factors is significantly greater than that of a single factor. The most effective factors are annual precipitation, potential evapotranspiration, relative humidity and elevation, which varied between 559.4–698.6 mm, 530.6–744.6 mm, 59%–62%, and 2006–2717 m, respectively. The land use, vegetation, and soil types suitable for healthy vegetation growth are forest, coniferous forest, and eluvial soil. [ABSTRACT FROM AUTHOR]

The drivers and spatial distribution trends for net primary productivity (NPP) in Ningxia were studied to determine the priority vegetation restoration areas. NPP data from MOD17 A3 were used to determine the future NPP trends through slope trend analysis and the Hurst index. Spatial drivers were defined by a geographic detector and correlation analysis. Results indicate that NPP positively fluctuated from 2000 to 2020 with an average range between 119.98 and 249.66 gC/m2a, and a multi-year average of 190.15 gC/m2a. The spatial distribution has more obvious divergent characteristics, showing distribution characteristics of low in the central and northern sides and high in the southern and northern middle. Superimposed on the analysis of slope and Hurst indices, the future vegetation NPP in Ningxia will show four scenarios of continuous increase, continuous decrease, change from increase to decrease and change from decrease to increase, accounting for 22.35%, 1.36%, 71.42% and 2.86% of the area of the region, respectively. Driving factor influence can be divided into dominant factors and important factors. The interaction between the two factors is positive, and the maximum q value under the interaction of precipitation and temperature is 0.687. NPP is mainly driven by climatic factors in 50.92% of the area and is mainly distributed in the central, western and southern parts of Ningxia. The non-climatic-factor-driven areas can be used as priority vegetation restoration areas, which accounting for 47.08%, are mainly concentrated in the northern Yellow River irrigation area, the desert steppe in the central and eastern parts, and a small part in the southern Liupan Mountains. [ABSTRACT FROM AUTHOR]

Air density plays an important role in assessing wind resource. Air density significantly fluctuates both spatially and temporally. But literature typically used standard air density or local annual average air density to assess wind resource. The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China. The air density at 100 m height is accurately calculated by using air temperature, pressure, and humidity. The spatial-temporal variation features of air density are firstly analyzed. Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density, standard air density ρst, and local annual average air density ρsite, respectively. Using ρst overestimates the annual wind energy production (AEP) in 93.6% of the study area. Humidity significantly affects AEP in central and southern China areas. In more than 75% of the study area, the winter to summer differences in AEP are underestimated, but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated. Using ρsite significantly reduces the estimation error in AEP. But AEP is still overestimated (0–8.6%) in summer and underestimated (0–11.2%) in winter. Except for southwest China, it is hard to reduce the estimation errors of winter to summer differences in AEP by using ρsite. Using ρsite distinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power, but these estimation errors cannot be ignored as well. The impacts of air density on assessing wind resource are almost independent of the wind turbine types. [ABSTRACT FROM AUTHOR]

Copyright of Mountain Research (10082786) is the property of Mountain Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The results of scientific analysis of the temporal and spatial evolution characteristics and influencing factors of grain production efficiency have far-reaching implications for optimizing agricultural resource allocation efficiency and promoting grain production quality and efficiency. Based on the statistical data of 134 counties ( districts) in Shandong Province, we performed data envelopment analysis to measure the comprehensive efficiency ( TE), pure technical efficiency ( PTE), and scale efficiency ( SE) of grain production in Shandong Province. Our aim was to examine the characteristics of their temporal and spatial variations. Therefore, we used the Tobit panel regression model to explore the factors influencing grain production efficiency. The results showed that, from 2000 to 2019, the overall grain production levels of TE, PTE, and SE in Shandong Province were high, with mean values of 0.963, 0.996, and 0.967, respectively. All indicators showed a fluctuating upward trend, with notable periodic characteristics, especially after 2002. The regional spatial differentiation in grain production efficiency in Shandong Province was remarkable, with TE and PTE showing a pattern of decreasing distribution from the western to eastern regions, and SE showing a trend of gradual concentration from contiguous high-value regions to the western region. TE, PTE, and SE showed significant positive spatial correlation, the agglomeration effect was relatively notable in the western region, whereas the spatial randomness was stronger in the eastern coastal areas. The results of our analysis of influencing factors showed that the levels of economic development, natural conditions, production conditions, resource endowment and policy system impacted the TE, PTE, and SE, but the direction and degree of influence differed. Among the factors considered, per capita disposable income, multiple cropping index, effective irrigation rate, and agricultural planting structure effectively improved grain production efficiency. Our findings indicate that in the future, although the layout of grain production should be scientifically planned, emphasis should be placed on improving the efficiency of grain production by raising farmer income level, improving agricultural infrastructure, and optimizing the structure of agricultural cultivation. [ABSTRACT FROM AUTHOR]

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Timely and rapidly mapping impervious surface area (ISA) and monitoring its spatial-temporal change pattern can deepen our understanding of the urban process. However, the complex spectral variability and spatial heterogeneity of ISA caused by the increased spatial resolution poses a great challenge to accurate ISA dynamics monitoring. This research selected Jinan City as a case study to boost ISA mapping performance through integrating the dual-attention CBAM module, SE module and focal loss function into the Deeplabv3+ model using Sentinel-2 data, and subsequently examining ISA spatial-temporal evolution using the generated annual time-series ISA data from 2017 to 2021. The experimental results demonstrated that (a) the improved Deeplabv3+ model achieved satisfactory accuracy in ISA mapping, with Precision, Recall, IoU and F1 values reaching 82.24%, 92.38%, 77.01% and 0.87, respectively. (b) In a comparison with traditional classification methods and other state-of-the-art deep learning semantic segmentation models, the proposed method performed well, qualitatively and quantitatively. (c) The time-series analysis on ISA distribution revealed that the ISA expansion in Jinan City had significant directionality from northeast to southwest from 2017 to 2021, with the number of patches as well as the degree of connectivity and aggregation increasing while the degree of fragmentation and the complexity of shape decreased. Overall, the proposed method shows great potential in generating reliable times-series ISA data and can be better served for fine urban research. [ABSTRACT FROM AUTHOR]

Reasonable ecological function zoning is conducive to balancing ecological security and social development. Previous studies of evaluation for urban ecosystem services (ESs) have great progress. However, there is a lack of integrating ES stable hotspots into urban planning and refined management. In this research, we are interested in how hotspot identification can help promote ecological refined management. To achieve this, Chengdu-Chongqing urban agglomeration (CY) was chosen as a case study. First, we employed coefficient of variation and linear regression to analyze ESs temporal and spatial evolution trend from 2000 to 2017. Then, the stable ES hotspots were identified in the time dimension, and the results were superimposed on the dominant function zoning map obtained by a self-organizing feature map (SOFM). Finally, the refined zoning results were obtained, and we added corresponding control measures and policy guidance. The results showed the following: (1) from 2000 to 2017, water conservation (WR) and biodiversity conservation (Sbio) in the study area fluctuated greatly and showed a significant improvement trend on the whole; soil erosion protection (Spro), carbon sequestration and oxygen production (CSOP) showed a degradation trend in a few areas; (2) the area with at least one kind of ES stable hotspot accounted for 35.22% in the study area, and only 0.8% covered the four kinds of ES hotspots; and (3) the two-level zoning system of CY-refined management was designed. Eighteen cells have been designed within five main functional zones: urban agglomeration zone, modern agricultural development zone, ecological farming zone, ecological transition zone, and core ecological protection zone. Overall, the research based on natural ecological zoning management can provide a decision-making basis for urban planning, policy making, and sustainable development. [ABSTRACT FROM AUTHOR]

Recently, there has been an increase in the occurrence of extreme high-temperature events across the China–Pakistan Economic Corridor (CPEC). Regional spatiotemporal identification and evaluation of extreme high temperatures are essential for accurate forecasting of future climate changes. When such events generate a meteorological hazard, it is important to understand their temporal and spatial features, return period, and identification criteria. Accurately identifying extreme events can help assess risk and predict their spatial–temporal variation. While past studies have focused on individual sites, extreme heat events generally manifest as spatially and temporally continuous regional events. In this study, we propose an objective identification technique based on gridded data and spatiotemporal continuity to reveal the spatiotemporal characteristics of intensity, frequency, and duration events of extreme heat events in the CPEC from May to October between 1961 and 2015. Furthermore, we estimate the return period of extreme heat in the study region using the generalized Pareto distribution (GPD). Our findings indicate that the historical extreme temperature events (intensity, frequency, and duration) in the CPEC have significantly increased. Areas with a high incidence of extreme heat events are concentrated in eastern Balochistan, northern Sindh, and southeastern Punjab. These findings suggest that disaster prevention and mitigation plans should be targeted towards areas with a high frequency of extreme heat events in the CPEC, allowing policy makers to better prepare for and respond to future events. [ABSTRACT FROM AUTHOR]

The exchange of carbon dioxide (CO2) flux between rivers and the atmosphere is an important part of the global carbon cycle. Reservoir development and environmental changes gradually transform rivers into river-reservoir systems. However, the current estimates of CO2 exchange flux at the water–air interface in river-reservoir systems, especially in ecologically fragile regions, are still largely uncertain. In this study, the CO2 partial pressure (ρCO2) and exchange flux (FCO2) from river-reservoir systems in the upper reaches of the Yellow River (YeUR) were investigated using the CO2SYS system and a boundary layer approach. The spatiotemporal dynamics and driving factors of the partial pressure of ρCO2 and FCO2 were revealed. Our results demonstrated that, driven by the freeze–thaw cycle of the permafrost active layer and the development of cascade reservoirs, the average ρCO2 in the two water periods was higher in the cascade reservoir section (CR) than in the source region section (SR) and higher in the flood period than in the dry period. Driven by water temperature stratification and light conditions, the ρCO2 of each reservoir in the CR exhibited seasonal variations along with water depth. The environmental factors TN, TP, T, DO, and DOC were the main influencing factors of ρCO2 distribution and could be used as predictors of ρCO2 in the dry period (R2 = 0.40 P < 0.01). In the dry period, the FCO2 in the SR was − 112.91 ± 165.94 mmol/(m2·d), which was a sink of CO2, and the FCO2 in the CR was 131.02 ± 156.77 mmol/(m2·d), which was a source of CO2. In the flood period, the FCO2 in the SR was 686.54 ± 624.33 mmol/(m2·d), and the FCO2 in the CR was 466.10 ± 366.67 mmol/(m2·d). Both the SR and the CR were sinks of CO2. Our results contribute to the understanding of CO2 exchange in river-reservoir systems and carbon cycle processes. [ABSTRACT FROM AUTHOR]

The maintenance of coral reef services depends largely on the conservation of the ichthyofauna and to develop strategies aimed at its conservation, data on its condition and threats are required. This work aimed to describe reef fish associations in the San Felipe Keys National Park (NPSFK and explore the influence of fishing and habitat on community attributes. Between 2013 and 2015, nine reef sites (15-25 m) were studied with stereo-video (535 transects of 50 m x 2 m) and 47 792 individuals were counted. The ichthyofauna was characterized by a high number of species, high density of small species and accumulated biomass in top predators and macrocarnivores (inverted trophic pyramid due to snapper aggregations). About 60% of the variation of the ichthyofauna was explained by the turbidity and heterogeneity of the bottom. The density (90 indiv./100m2), size (14.2 cm) and average biomass (12 kg/100m2) of the NPSFK's ichthyofauna were similar to that of other protected reefs. However, the negative effect of fishing was observed in the decrease of indicators of abundance and size at the level of functional groups and families of interest for fishing in the eastern area of the NPSFK (greater fishing pressure) in relation to the western area. In addition, the biomass (15 g/m2) of herbivores in the NPSFK and that of snappers and groupers (12 g/m2) in the eastern area was assessed as poor. The information provided can help decision-making for the best use of coral reef resources in the NPSFK. [ABSTRACT FROM AUTHOR]

Populations of the same plant species living in different locations but flowering at different times may vary in pollinator availability and floral traits. However, the spatial and temporal links between floral traits and pollination are rarely included in single studies. In this study, three populations of an alpine lousewort, Pedicularis rhinanthoides Schrenk subsp. tibetica (Bonati) Tsoong, were surveyed to detect the variations in floral traits and pollinator activity. We hypothesized that floral divergence was spatio-temporally correlated with pollen limitation (PL) in relation to pollinators. Sampled plants from each population were divided into three groups, according to flowering stage: early, peak, and late. Pollen-supplementation experiments and investigations into pollinators, reproductive success, and floral traits were conducted on the plants from the different flowering stages and across the populations. Our results showed that the extent of PL varies across populations and among flowering stages. Populations in which more pollinators were recorded displayed a lower extent of PL. Furthermore, the temporal differences in PL showed a similar pattern for the three populations; the plants from the peak flowering stage suffered slighter PL than those from the other two stages. Nevertheless, some of the floral traits displayed similar spatial and temporal patterns to the PL, while the others only varied among the populations spatially. The results indicated that the performance of floral traits in a particular spatial–temporal situation shows they are well adapted to the corresponding pollination environment, which might help plants to optimize their reproductive fitness under different abiotic factors. [ABSTRACT FROM AUTHOR]

Forest soil carbon is a major carbon pool of terrestrial ecosystems, and accurate estimation of soil organic carbon (SOC) stocks in forest ecosystems is rather challenging. This study compared the prediction performance of three empirical model approaches namely, regression kriging (RK), multiple stepwise regression (MSR), random forest (RF), and boosted regression trees (BRT) to predict SOC stocks in Northeast China for 1990 and 2015. Furthermore, the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified. A total of 82 (in 1990) and 157 (in 2015) topsoil (0-20 cm) samples with 12 environmental factors (soil property, climate, topography and biology) were selected for model construction. Randomly selected 80% of the soil sample data were used to train the models and the other 20% data for model verification using mean absolute error, root mean square error, coefficient of determination and Lin's consistency correlation coefficient indices. We found BRT model as the best prediction model and it could explain 67% and 60% spatial variation of SOC stocks, in 1990, and 2015, respectively. Predicted maps of all models in both periods showed similar spatial distribution characteristics, with the lower SOC in northeast and higher SOC in southwest. Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods. SOC stocks were mainly stored under Cambosols, Gleyosols and Isohumosols, accounting for 95.6% (1990) and 95.9% (2015). Overall, SOC stocks increased by 471 Tg C during the past 25 years. Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories. The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks. Overall, our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale. [ABSTRACT FROM AUTHOR]

This study investigated the spatial-temporal variation and trend of the Internet user percentage (IUP) at the country level in the world from 1996 to 2017. Several methods were applied including kernel density estimation, global autocorrelations, sigma-convergence detection, and hierarchical clustering. The results demonstrated that the spatial distribution of IUP at the country level showed significant positive autocorrelations indicating clustered spatial patterns rather than dispersed or random distributions. In addition, the temporal variation of the distribution disparity of IUP showed a decreasing trend at the country level during the study period. Further, sigma convergence of IUP during this period was detected according to the coefficient of variation. Last, the similarity of the IUP variation at the country level presented the spatial clustering feature with spatially contiguous countries in the world. In sum, the finding in this study indicated that Internet penetration may show the promotion of the balanced development trend over time in the world and the spatial characteristics of Internet development should be considered in the future policy globally. [ABSTRACT FROM AUTHOR]

The bottom friction is critical for the dissipation of the global tidal energy. The bottom friction coefficient is traditionally determined using the Manning’s n formulation in tidal models. The Manning’s n coefficient in the Manning’s n formulation is vital for the accurate simulation and prediction of the tide in coastal shallow waters, but it cannot be directly measured and contains large amounts of uncertainties. Based on a two-dimensional multi-constituent tidal model with the adjoint data assimilation, the estimation of the Manning’s n coefficient is investigated by assimilating satellite observations in the Bohai, Yellow and East China Seas with the simulation of four principal tidal constituents M2, S2, K1 and O1. In the twin experiments, the Manning’s n coefficient is assumed to be constant, and it is estimated by assimilating the synthetic observations at the spatial locations of the satellite tracks. Regardless the inclusion of artificial random observational errors associated with synthetic observations, the model performance is improved as evaluated by the independent synthetic observations. The prescribed ‘real’ Manning’s n coefficient is reasonably estimated, indicating that the adjoint data assimilation is an effective method to estimate the Manning’s n coefficient in multi-constituent tidal models. In the practical experiments, the errors between the independent observations at the tidal gauge stations and the corresponding simulated results of the four principal tidal constituents are substantially decreased under both scenarios of the constant and spatially-temporally varying Manning’s n coefficient estimated by assimilating the satellite observations with the adjoint data assimilation. In addition, the estimated spatial and temporal variation trend is robust and not affected by the model settings. The spatially-temporally varying Manning’s n coefficient is negatively correlated with the current speed and shows significant spatial variation in the shallow water areas. This study demonstrates that the Manning’s n coefficient can be reasonably estimated by the adjoint data assimilation, which allows significant improvement in accurate simulation of the ocean tide.

The aboveground biomass (AGB) of withered grass is an important early-warning indicator for grassland fire risk. Most grassland fires occur during the dry-grass season. In order to improve the fire-warning efficiency of withered AGB, it is essential to rapidly acquire the amount of withered-grass biomass. Remote-sensing data has been widely used in monitoring and estimating grassland yields during the growing season. However, applying remote sensing to the estimation of withered grass is still in need of exploration. The aim of this work was to try to establish a remote-sensing estimation model for withered AGB in the dry-grass season. The estimation of aboveground biomass can effectively prevent the occurrence of fire, protect the environment, facilitate local management and reduce economic losses. Our approach was to, first, calculate a dry-grass index based on Sentinel-2 image data and using ENVI, SNAP, and ArcGIS software. Second, a model to estimate the fuel quantity during the dry-grass season was established by regression analysis combined with field-measured data. Finally, the estimation model was used to predict the amount of fuel in different months of the dry-grass season, followed by the fire-defense elements, which were quantified and mapped in the Longzhao Marsh wetlands. It was found that: 1) the two indices were significantly correlated (0.678) with the amount of fuel; 2) the established model could accurately estimate the amount of fuel in the study area during the dry season, and accurate test results demonstrated that the correlation between the estimated results of the best model and the measured values was 0.863, indicating high accuracy; 3) the spatiotemporal variation of withered grass in the study area was obviously different, and the quantities of fuel predicted for the other months were more accurate, which may reflect monthly dynamic changes in actual fuel quantities; and 4) the establishment of a remote-sensing estimation model for fuel quantity in the Longzhao Marsh during the dry-grass season could provide important parameters for fire-risk warning in the western grassland of Jilin Province and Northeast China.

Vegetation coverage is an important indicator for evaluating regional environmental quality. Based on MODIS NDVI and DEM data collected for the upper reaches of the Ganjiang River Basin, China, this study used trend analysis, coefficient of variation, Hurst index, and linear regression to analyze the temporal and spatial evolution of vegetation coverage and its relationship with terrain factors in the basin during the years 2000–2020. The vegetation coverage in the study area showed a fluctuating increasing trend at a rate of 5%/10y, and an increasing trend with increasing elevation. The maximum vegetation coverage was identified in the elevation zone of 750–1,000 m, with an average of 83.54%. Vegetation coverage also showed an increasing trend with increasing slope. The maximum vegetation coverage was up to 82.22% in the slope zone of ≥25°. There were no significant differences among the distributions of vegetation coverage in different aspects because the terrain in the study area is not rugged enough to form barriers against sunlight. The vegetation coverage was relatively stable in the study area, with an average coefficient of variation of 14.8%. Hurst analysis showed that the anti-sustainability effect of vegetation change was stronger than that of sustainability, and weak anti-sustainability was dominant. The effects of human activities mainly concentrated in the areas of low elevation and small slopes less than 2°where cities and towns are located. The findings can provide a scientific basis for the management of regional ecosystems in the future.

Rapid climate warming speeds up the solid-liquid water cycle and reduces the solid water storage in cold regions of the Earth. Snowfall is the most crucial input for the cryosphere. However, the potential snowfall phenology (PSP) variability has not been systematically and comprehensively studied. For this reason, we initially proposed three indicators, i.e., the start of potential snowfall season (SPSS), the end of potential snowfall season (EPSS), and the length of potential snowfall season (LPSS), to describe the characteristics of the PSP, then we explored the spatial-temporal variation of those three PSP indicators past, present, and future across the Chinese Tianshan mountainous region (CTMR) based on the observed daily air temperature from 26 meteorological stations during 1961-2017/2020 combined with 14 models data from CMIP6 (the Phase 6 of the Coupled Model Intercomparison Project) under four different scenarios (SSP126, SSP245, SSP370, and SSP585) during 2021-2100. It proved that the SPSS, EPSS, and LPSS could reproduce features of the PSP well across the study area. In the past and present, the potential snowfall season started on October 29th, ended on March 20th, and lasted for about four months and 23 days across the CTMR on average. The rate of advancing EPSS (-1.6 days/10a) was faster than that of postponing SPSS (1.1 days/10a) during 1961-2017/2020. It also found significant delaying by 2-13 days in the starting time, and advancing for 1-13 days in the ending time, respectively, which reduced 1-27 days for the LPSS. The potential snowfall season started later, ended later, and lasted longer in the north and center than in the south. Similar to the past and present, the SPSS, EPSS, and LPSS will vary under four emission scenarios during 2021-2100. Potential snowfall season will start later, end earlier, and last fewer days under the higher emission scenario. Under the highest emission scenario, SSP585, the starting time will be postponed by 41 days in 2100, while the ending time will be up to 23 days in advance in 2100, implying that it will cut down the length by 63 days (about two months), and the length of the potential snowfall season will only last two and a half months in 2100 under the SSP585 scenario. Spatially, the length of the potential snowfall season in the west and southwest of the CTMR will be compressed by more days because of the more delayed starting time and advanced ending time under all four scenarios. The results indicate that annual total snowfall will decrease, including amount and frequency, then reduce snow cover or mass, which finally feedback to the atmosphere in the form of more rapid warming for the lower reflectivity to solar radiation. Our research provides a new direction to capture the potential snowfall phenology in the alpine region and can be easily expanded to other snow-dominated areas worldwide. [ABSTRACT FROM AUTHOR]