摘要：
Maritime transportation plays a crucial role in global trade and economic development. However, this industry is exposed to various risks (e.g., natural disasters), which can cause significant economic and environmental damage. This study aims to develop a spatial risk assessment approach for maritime transportation using machine learning and geospatial big data to identify potential risks in China's maritime transportation industry. The proposed approach first produces risk maps that reveal significant variability in maritime transportation risks across different regions of China. Then, factor importance analysis identifies wave height, rainfall, and sea surface temperature as the most influential factors affecting navigational safety. Finally, capability indicators are employed to analyze the matching relationship between coastal search and rescue resources and maritime transportation risks. Our study provides valuable references for enhancing maritime emergency response capabilities and protecting marine ecological environments.
期刊：
Journal of Soils and Sediments,2024年24(1):1-16 ISSN：1439-0108
通讯作者：
Liu, Muxing;Yi, J
作者机构：
[Yi, Jun; Lu, Shiguo; Liu, Muxing; Zhang, Hailin; Liu, MX; Wang, Weijie] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Yi, Jun; Lu, Shiguo; Liu, Muxing; Zhang, Hailin; Liu, MX; Wang, Weijie] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Wan, Jinhong] Inst Water Resources & Hydropower Res, Beijing 100048, Peoples R China.
通讯机构：
[Yi, J ; Liu, MX] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
Soil infiltration response;Forest conversion;Hillslope hydrology;Humid area
摘要：
PurposeUnderstanding the characteristics of soil infiltration response to rainfall is critical for soil water transport processes and hydrologic modeling. However, little is known about how they vary with forest conversion at different temporal stages (< 20 years) below the rooting zone. Therefore, this study aims to investigate soil infiltration response patterns in different subtropical forest conversion hillslopes, including mature original forest (thick root), young secondary forest (middle root), and very young secondary grassland (fine root), and analyzed the effects of environmental factors on the dynamics of soil infiltration.Materials and methodsSeveral metrics were evaluated to characterize and quantify the nature of these responses by estimating changes in the soil water content, the response time difference between two adjacent soil depths, and infiltration velocities for 1144 infiltration events at 6 locations on the three hillslopes.Results and discussionSoil infiltration responses were similar on both forestland hillslopes, yet significantly different from those on the grassland hillslope. The preferential flow was more evident in the profile of thick-rooted vegetation, and the velocity of the wetting front was faster in the profiles of middle- and fine-rooted vegetation. Topography and root characteristics interact to influence soil infiltration response at the hillslope scale.ConclusionsConversion from thick-rooted forests into fine-rooted grasslands altered the rainfall-related soil infiltration dynamics below the rooting zone. In particular, the occurrence of preferential flow and infiltration rates varied, which helps enhance our understanding of ecohydrological processes in the context of changing land use and hydroclimatic conditions.
摘要：
Revegetation is effective in improving soil quality in ecologically fragile areas. However, little is known about the impact of diverse phytomanagement strategies of tailings on soil quality and ecological security in erosion-prone areas. We investigated the water stability, soil aggregate nutrients, and the risk of heavy metal contamination of abandoned tailings under phytomanagement and in adjacent bare land on the Loess Plateau. The results showed that phytomanagement significantly enhanced soil aggregate stability, as demonstrated by higher contents of soil organic carbon (SOC), glomalin-related soil protein (GRSP), aromatic-C, and alkene-C in macro-aggregates. The pollution load index (PLI) and ecological risk index (RI) of soil heavy metals were lower in shrub/herbaceous mixed forests than in natural grasslands and planted forests. The risk of heavy metal contamination was higher in macro-aggregates (>0.25 mm) than in micro-aggregates (<0.25 mm) and was significantly and positively correlated with the SOC and GRSP contents of the aggregates. Our study demonstrates that soil aggregate quality is closely related to the fate of heavy metals. Diversified tailing revegetation measures can improve soil quality and ensure ecological security.
期刊：
Science of The Total Environment,2024年906:167663 ISSN：0048-9697
通讯作者：
Yin, GF
作者机构：
[Yin, Gaofei; Yin, GF; Xie, Jiangliu; Ma, Dujuan; Chen, Rui] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 610031, Peoples R China.;[Zhao, Wei] Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China.;[Xie, Qiaoyun] Univ Western Australia, Sch Engn, Perth, WA 6009, Australia.;[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Lin, Shangrong; Yuan, Wenping] Sun Yat Sen Univ, Guangdong Prov Data Ctr Terr & Marine Ecosyst Carb, Sch Atmospher Sci, Zhuhai 519000, Peoples R China.
通讯机构：
[Yin, GF ] S;Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 610031, Peoples R China.
关键词：
Climatic limitations;Light use efficiency model;Plant photosynthesis;Tibetan plateau
摘要：
Plant photosynthesis plays an essential role in regulating the global carbon cycle. Therefore, it is essential to understand the limitations imposed by climate on plant photosynthesis to comprehend the impacts of climate change on land carbon dynamics. In this study, taking gross primary productivity as a direct representation of photosynthesis, we employed a light use efficiency model (i.e., the revised EC-LUE) and factorial analysis method to quantify the spatiotemporal variation of temperature- and water-limitations on plant photosynthesis over the Tibetan Plateau (TP) grasslands during growing season (May to October) in 1983-2018. Results revealed a clear spatiotemporal pattern of the temperature- and water-limitations: temperature is the primary climatic limiting factor in the eastern TP, while water is the primary climatic limiting factor in the western TP; the water- and temperature-limitations prevail in summer and spring/autumn, respectively. The water- and temperature-limitations intensified and alleviated, respectively, during 1983 through 2018. There also was a widespread shift from temperature-limitation to water-limitation in the TP, particularly in midsummer (August). Our findings demonstrated the shifting relative importance of climatic limitations on plant photosynthesis under changing climate, which is crucial for predicting future terrestrial carbon cycle dynamics.
期刊：
Journal of Soils and Sediments,2024年24(2):829-846 ISSN：1439-0108
通讯作者：
Tian, P
作者机构：
[Ping, Yaodong; Tian, Pei; Guo, Yahui; Tian, P] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Luo, Li] Northwest Agr & Forestry Univ, Coll Water Resources & Architectural Engn, Yangling 712100, Peoples R China.;[Zhu, Zhanliang; Gong, Yuwei] Beijing Normal Univ, Coll Water Sci, Beijing 100091, Peoples R China.;[Cui, Yongsheng] Fujian Agr & Forestry Univ, Forestry Coll, Fuzhou 350002, Peoples R China.;[Chen, Lin] Univ Calif Riverside, Dept Environm Sci, Riverside, CA 92521 USA.
通讯机构：
[Tian, P ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
关键词：
Soil erosion sensitivity;RUSLE;Deep learning-LSTM model;Geographic detector;Hilly areas of Hubei Province
摘要：
Purpose Hilly areas are highly susceptible to soil erosion. This study aims to discover the drivers of soil erosion, identify soil erosion-sensitive areas, and predict future soil erosion in typical hilly areas of Hubei Province, China, using combined RUSLE and LSTM models.Materials and methods In this study, soil erosion in hilly areas of Hubei Province from 2000 to 2020 was quantitatively analyzed using the revised universal soil loss equation (RUSLE), and the soil erosion sensitivity evaluation system was constructed, a geographic detector was employed to identify the main drivers of soil erosion sensitivity, and using the long short-term memory neural network model (LSTM) to predict soil erosion in 2025.Results and discussions The results showed that most areas were dominated by slight and moderate erosion. Slope and vegetation coverage were identified as the core elements influencing the space heterogeneity of soil erosion. Soil erosion sensitivity was mainly composed of moderate sensitivity, accounting for more than 70% of the total area. The strong and extreme sensitivity demonstrated a downward trend with the continued implementation of slope management and forest rehabilitation from slope agriculture, whereas the sensitivity was still higher in the northwest and southwest Hubei Province. Regions with severe soil erosion had high sensitivity, and the spatial distribution of the two is strongly coherent. Areas with surface relief > 300 m and vegetation cover < 30% had the highest sensitivity and should be highly valued. The percentage of moderate and higher soil erosion area in 2025 was 3.77% lower than in 2020, but severe erosion still exists in the northwest and southwest Hubei Province.Conclusions Soil erosion sensitivity in the western part of the study area was the highest, followed by the southeast, and the overall erosion sensitivity was gradually decreasing during the studied period. In the future, soil erosion intensity will show a downward trend, whereas the deployment of soil and water conservation measures in soil erosion-sensitive areas should still be strengthened. The results are helpful for accurate soil erosion control and prediction in the hilly areas of Hubei Province, China.
摘要：
Located in the northwestern edge of the modern Asian summer monsoon (ASM), the northeastern Tibetan Plateau (NETP) is sensitive to changes of the ASM climate. However, variations of climate and vegetation during the Holocene remain unclear in this marginal region of the monsoon climate. Here we present a Holocene highresolution pollen record from Lake Gahai in the NETP since 11.4 (+/- 0.3) ka BP to reconstruct regional vegetation history. A quantitative reconstruction of precipitation is also tried using fossil pollen assemblages. Results suggested that before 10.2 (+/- 0.4) ka BP in the early Holocene, the vegetation cover was low and the climate was arid. A relatively wet climate indicated by high A/C ratio values occurred between 10.2 (+/- 0.4) and 7.4 (+/- 0.2) ka BP. After 7.4 (+/- 0.2) ka BP, the A/C ratio decreased, indicating that the climate was getting drier. The overall environment of the basin has become similar to modern conditions since 5.4 (+/- 0.1) ka BP. The reconstructed precipitation is not comparable with the tree-ring-based reconstruction from the Delingha region, although the reconstruction processes passed significance tests statistically. In addition to abundant surface pollen data and gradually improved quantitative reconstruction techniques, other factors such as the environmental settings and vegetation dynamics also affect the reliability of the pollen-based quantitative reconstruction of regional precipitation. Therefore, the applicability of pollen data for quantitative precipitation reconstruction in arid regions should be assessed and the results should be treated cautiously.
期刊：
GEOPHYSICAL RESEARCH LETTERS,2024年51(4) ISSN：0094-8276
通讯作者：
Yin, GF
作者机构：
[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.;[Yin, Gaofei; Yin, GF; Yang, Yajie] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.;[Xie, Qiaoyun] Univ Western Australia, Sch Engn, Perth, WA, Australia.;[Xu, Baodong] Huazhong Agr Univ, Macro Agr Res Inst, Coll Resource & Environm, Wuhan, Peoples R China.;[Verger, Aleixandre] CSIC UV GV, CIDE, Valencia, Spain.
通讯机构：
[Yin, GF ] S;Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.
摘要：
Abstract Remote sensing detection of autumn phenology is challenging and highly uncertain, as exemplified by the observed divergence in autumn phenology extracted from different proxies. Here, we compared the autumn phenology derived from Solar‐Induced chlorophyll Fluorescence (SIF), Chlorophyll/Carotenoid Index (CCI), Enhanced Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) over deciduous forest sites. We observed a clear temporal sequence in the derived autumn phenology from various proxies: SIF < CCI < EVI < NDVI. Comparison with field measurements supported that SIF, EVI, and NDVI can successfully capture the attenuation of photosynthetic activity, leaf coloration, and leaf fall, respectively. The sequence among the autumn phenology derived from those proxies was also consistent with their responses to climate cues, where SIF had the highest partial correlation coefficient to solar radiation in autumn, followed by CCI, EVI, and NDVI, while NDVI was more correlated with temperature, followed by EVI, CCI, and SIF.
摘要：
The global trend of vegetation "greening" in the context of ecological restoration necessitates an urgent assessment of ecosystem services. As essential components of ecosystem services, the hydraulic functions of soil in infiltrating and retaining water following vegetation restoration remain unclear, especially in subtropical mountainous and hilly areas with complex topographies. From 2018 to 2021, soil moisture data collected at five-minute intervals were monitored for three restoration strategies in a hilly catchment of China's Three Gorges Reservoir area. The restoration strategies included planted forest (PF) and natural restoration (naturally regenerated forest, NF; deforested pasture, DP). The soil moisture response to rainfall under these strategies was evaluated using several metrics, including the time difference between peak rainfall intensity and peak soil moisture response (T-p2p), cumulative infiltration, and occurrence frequency of preferential flow (PRF). The results showed that the average soil moisture content (SMC) of PF was significantly (p < 0.05) lower than that of NF and DP in both dry and wet seasons, regardless of upslope or downslope location. However, the topographic position affected the difference in average SMC between DP and NF. At the downslope location, the average SMC of DP (0.39 cm(3) cm(-3)) was significantly higher than that of NF (0.33 cm(3) cm(-3)). Conversely, at the upslope location, the average SMC of DP (0.27 cm(3) cm(-3)) was lower than that of NF (0.30 cm(3) cm(-3)). These findings suggested that PF had a lower amount of soil water storage than NF and DP, which was supported by the lowest cumulative infiltration in PF during storm events. The response of soil moisture to storms in PF (T-p2p = 3.1 h) was slower than that in NF (T-p2p = 1.9 h) and DP (T-p2p = 2.5 h). This was consistent with the lower occurrence frequency of preferential flow in PF (PRF = 19.2 %) than NF (PRF = 39.2 %) and DP (PRF = 32.9 %). Therefore, longer response time and less preferential flow indicated that the PF had a relatively poor soil moisture responsiveness to storm events. Accordingly, this study highlights the insufficiency of afforestation in soil water infiltration and retention compared to natural restoration, meriting consideration when assessing soil hydraulic functions in vegetation restoration areas.
摘要：
Approximately 1 billion people worldwide currently inhabit slum areas. The UN Sustainable Development Goal (SDG 11.1) underscores the imperative of upgrading all slums by 2030 to ensure adequate housing for everyone. Geo-locations of slums help local governments with upgrading slums and alleviating urban poverty. Remote sensing (RS) technology, with its excellent Earth observation capabilities, can play an important role in slum mapping. Deep learning (DL)-based RS information extraction methods have attracted a lot of attention. Currently, DL-based slum mapping studies typically uses three optical bands to adapt to existing models, neglecting essential geo-scientific information, such as spectral and textural characteristics, which are beneficial for slum mapping. Inspired by the geoscience-aware DL paradigm, we propose the Geoscience-Aware Network for slum mapping (GASlumNet), aiming to improve slum mapping accuracies via incorporating the DL model with geoscientific prior knowledge. GASlumNet employs a two-stream architecture, combining ConvNeXt and UNet. One stream concentrates on optical feature representation, while the other emphasizes geo-scientific features. Further, the feature-level and decision-level fusion mechanisms are applied to optimize deep features and enhance model performance. We used Jilin-1 Spectrum 01 and Sentinel-2 images to perform experiments in Mumbai, India. The results demonstrate that GASlumNet achieves higher slum mapping accuracy than the comparison models, with an intersection over union (IoU) of 58.41%. Specifically, GASlumNet improves the IoU by 4.60 similar to 5.97% over the baseline models, i.e., UNet and ConvNeXt-UNet, which exclusively utilize optical bands. Furthermore, GASlumNet enhances the IoU by 10.97% compared to FuseNet, a model that combines optical bands and geo-scientific features. Our method presents a new technical solution to achieve accurate slum mapping, offering potential benefits for regional and global slum mapping and upgrading initiatives.
关键词：
biochar;coastal saline soils;polyacrylamide;soil microstructure;water and salt transport
摘要：
Increasing scientific knowledge on the improvement of coastal saline soils is critical for spatially expanding coastal development. Biochar and polyacrylamide (PAM) are popular soil amendments, however, it remains unclear how they affect water and salt transport by regulating soil microstructure characteristics. In this study, we conducted a five-year rice barrel trial and investigated the changes in the aggregates and microstructure of saline soils after adding biochar with three different application rates (B1 = 0%, B2 = 2%, and B3 = 5%, mass ratio) and PAM with three different application rates (P1 = 0%, P2 = 0.4 parts per thousand, and P3 = 1.0 parts per thousand, mass ratio), and simulated the water and salt transport. Results showed that at B1 and B2 treatments, soil mu-CT porosity in 2020 increased by 89.8% and 208.0%, respectively, with respect to that in 2016. The development of soil mesopore structure was promoted at B2 treatments, whereas the P2 and P3 treatments promoted the development of the soil macrostructure. Compared with those of the blank control, soil internal mean water flow rate increased by 22.2% at B2 treatments and 69.2% at P2 treatments, respectively. However, their increases were less pronounced at B3 treatments and the water flow rate decreased by 50.5% at P3 treatments. It might be reasonably attributed to the reason that porous biochar helped the formation of soil pore structure while an excessive amount of biochar blocked soil pores. Furthermore, PAM amendment helped to form soil aggregates while an excessive amount of viscous PAM might block soil pores or form a viscous layer. The time corresponding to the maximum salt concentration was negatively correlated with soil mu-CT porosity (R2 = 0.27) and pore connectivity density (R2 = 0.29). Our findings indicate that appropriate amounts of biochar and PAM can help improve saline soil structure in coastal areas, improve their hydraulic properties, and alleviate salt stress.
期刊：
Global Change Biology,2024年30(1):e17027- ISSN：1354-1013
通讯作者：
Fang, LC
作者机构：
[Fang, Linchuan; Ma, Dengke; Jin, Xiaolian; Fang, LC; Ju, Wenliang; Guo, Liang] Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess Pl, Minist Water Resources, Yangling 712100, Peoples R China.;[Ju, Wenliang] Tsinghua Univ, Sch Environm, Beijing, Peoples R China.;[Fang, Linchuan] Wuhan Univ Technol, Key Lab Green Utilizat Crit Nonmet Mineral Resourc, Minist Educ, Wuhan, Peoples R China.;[Shen, Guoting; Blagodatskaya, Evgenia] UFZ Helmholtz Ctr Environm Res, Dept Soil Ecol, Halle, Saale, Germany.;[Delgado-Baquerizo, Manuel; Zhou, Guiyao] Inst Recursos Nat & Agrobiol Sevilla IRNAS, Lab Biodivers & Funcionamiento Ecosistem, CSIC, Seville, Spain.
通讯机构：
[Fang, LC ] C;Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess Pl, Minist Water Resources, Yangling 712100, Peoples R China.
关键词：
carbon sequestration;grasslands;grazing exclusion;microbial communities and functions;nitrogen and phosphorus accumulation;soil aggregates
摘要：
We linked the soil microscale‐associated microbiomes with the carbon sequestration and biogeochemical cycling of livestock excluded grasslands for up to 36 years. Long‐term grazing exclusion reduced microbial diversity, community stability, and microbial functional genes associated with carbon sequestration and nutrient cycling. Moreover, we emphasize that the interaction between grazing exclusion and longevity as well as the structure of soil aggregates have substantial impacts the grassland biogeochemical cycles and global climate change in which the soil microbiome is involved. Abstract Grazing exclusion alters grassland soil aggregation, microbiome composition, and biogeochemical processes. However, the long‐term effects of grazing exclusion on the microbial communities and nutrient dynamics within soil aggregates remain unclear. We conducted a 36‐year exclusion experiment to investigate how grazing exclusion affects the soil microbial community and the associated soil functions within soil aggregates in a semiarid grassland. Long‐term (36 years) grazing exclusion induced a shift in microbial communities, especially in the <2 mm aggregates, from high to low diversity compared to the grazing control. The reduced microbial diversity was accompanied by instability of fungal communities, extended distribution of fungal pathogens to >2 mm aggregates, and reduced carbon (C) sequestration potential thus revealing a negative impact of long‐term GE. In contrast, 11–26 years of grazing exclusion greatly increased C sequestration and promoted nutrient cycling in soil aggregates and associated microbial functional genes. Moreover, the environmental characteristics of microhabitats (e.g., soil pH) altered the soil microbiome and strongly contributed to C sequestration. Our findings reveal new evidence from soil microbiology for optimizing grazing exclusion duration to maintain multiple belowground ecosystem functions, providing promising suggestions for climate‐smart and resource‐efficient grasslands.
摘要：
Over the past decade, China has experienced a decline in atmospheric reactive nitrogen (Nr) emissions. Given that China's subtropical region is a significant nitrogen (N) deposition hotspot, it is essential to accurately quantify the ten-year variations in dry and wet N depositions in the context of reductions in atmospheric Nr emissions. Here, we evaluated the spatiotemporal variation in N deposition on forest, paddy field and tea field ecosystems in a typical subtropical agricultural catchment from 2011 to 2020. Our findings indicated a significant decrease in total N deposition in both the tea field ecosystem (41.5-30.5kgNha(-1)) and the forest ecosystem (40.8-25.7kgNha(-1)) (P<0.05), but no significant change in the paddy field ecosystem (29.3-32.9kgNha(-1)). Specifically, dry N deposition exhibited significant declines except in the paddy field ecosystem, whereas wet N deposition had no significant change. The reduction in total oxidized and reduced N depositions in forest and tea field ecosystems is attributed to the decrease in NO(x) and NH(3) emissions. Additionally, The ratio of NH(x) deposition to total N deposition all exceeded 0.5 in three ecosystems and the NH(x)/NO(y) ratio had an increasing trend (P<0.05) in the paddy field, indicating that reactive N emissions from agricultural sources were the primary contributor to overall N deposition. Our study emphasizes that despite the decreasing trend in N deposition, it still exceeds the critical loads of natural ecosystems and requires stringent N emissions control, particularly from agricultural sources, in the future.
期刊：
GEOPHYSICAL RESEARCH LETTERS,2024年51(5):e2023GL107316- ISSN：0094-8276
通讯作者：
Yin, GF
作者机构：
[Yin, Gaofei; Yin, GF; Wang, Changjing; Ma, Dujuan; Xie, Jiangliu; Chen, Rui; Wu, Xiaodan] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.;[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan, Peoples R China.;[Xie, Qiaoyun] Univ Western Australia, Sch Engn, Perth, WA, Australia.
通讯机构：
[Yin, GF ] S;Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu, Peoples R China.
关键词：
microclimate;phenology;aspects;climate
摘要：
Vegetation growth is influenced by the microclimate driven by aspects, as evident in the asymmetric vegetation greenness on polar-facing slopes (PFS) and equatorial-facing slopes (EFS). However, it remains uncertain whether aspects influence vegetation phenology. To address this question, we defined the aspect-induced phenological differences between PFS and EFS from 2019 to 2022 within each 3 × 3 km2 grid, using average phenological metrics extracted from Sentinel-2 data. We found that the start of the growing season (SOS) occurs earlier on EFS in cold and humid regions, but in arid areas, PFS has an earlier SOS. The end of the growing season (EOS) consistently occurred later on EFS due to radiation limitations in autumn phenology. Employing the space-for-time approach, the observed distribution of phenological differences within the climate space could potentially indicate the phenological trends of different slope orientations in the future. Our study provides valuable insights into topographic regulation on vegetation phenology.
There are significant phenological differences between polar-facing slopes and equatorial-facing slopes
Phenological differences vary under different background climatic conditions
Using the space-for-time approach, the phenological differences in climate space suggest future phenological shifts
Equatorial-facing slopes (EFS) receive more solar radiation than polar-facing slopes (PFS), resulting in contrasting microclimate conditions. Specifically, EFS are warmer and drier, while PFS are colder and wetter. These microclimate differences contribute to variations in vegetation greenness between PFS and EFS. Based on this, we hypothesized that the phenology of grassland in the Three Rivers Source Region on the Tibetan Plateau is influenced by aspects. To test this hypothesis, we calculated the phenological differences between PFS and EFS within each 3 × 3 km2 grid using average phenological metrics derived from Sentinel-2. Our findings reveal that, for the start of the growing season (SOS), EFS exhibited an earlier onset in regions with low temperature and high precipitation, whereas for regions with high temperature, the growing season starts earlier on PFS. In contrast, over 70% of the grassland area on EFS experiences a later end of the growing season (EOS) due to radiation being a major limiting factor of autumn phenology. In addition, we utilized the space-for-time approach to project potential future phenological changes on PFS and EFS. Our study enhances comprehension of vegetation ecological management and carbon sequestration in mountainous areas.
作者机构：
[Yu, Lei; Xu, Yueling; Zhou, Xueyan; Lv, Tianqi; Wang, Caiyun; Huang, Fan] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Yu, Lei; Xu, Yueling; Zhou, Xueyan; Lv, Tianqi; Wang, Caiyun; Huang, Fan] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Yu, L ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
摘要：
This study evaluates the effects of a combined rice-crayfish farming model and compares this model with traditional paddy fields. The focus is on soil aggregate characteristics, organic matter content, and also the distribution of soil aggregates. This research was conducted in Qianjiang, Hubei Province. The surface soil samples were collected from two types of arable land: paddy fields (WR) and rice-crayfish fields (CR). We performed an analysis of soil aggregate distribution and organic matter content. Results reveal that the majority of soil aggregates exceed 2 mm in size (>= 74.94%). The integrated rice-crayfish farming model significantly enhances the presence of large soil aggregates. And these parameters such as the average weight diameter (MWD), average geometric diameter (GWD), and agglomerate stability (PAD) also increase. Moreover, it mitigates agglomerate fragmentation (WASR). However, the net increase in total soil organic matter due to the integrated farming model remains modest. Organic matter content within the agglomerates follows an initial increase followed by a decrease. The highest content occurs in the 0.25-0.5 mm grain size (D4). When examining the distribution of soil aggregates and organic matter, it becomes evident that organic matter primarily originates from grain sizes larger than 2 mm (>= 71.92%). Notably, the rice-crayfish paddy field (CR) exhibits a substantially higher contribution compared to the traditional rice paddy field (WR). This study demonstrates several positive outcomes of the integrated rice-crayfish farming model compared to traditional paddy farming. It promotes the development of larger soil aggregates, enhances the structural integrity of soil aggregates, and improves their mechanical and hydrological stability. Additionally, it marginally increases the organic matter content within each component of soil aggregates. Furthermore, integrated modelling increases the impact of larger soil aggregates on soil organic matter. This improves the quality of the soil and as a result, crop yields are increased. The health of the soil is also improved and this contributes positively to food security.
摘要：
The deteriorating urban thermal environment poses a huge impediment to sustainable urban development, which is closely related to the urban morphology under different urban functional zones (UFZs). By integrating remote sensing and geospatial big data, this work aims to reveal the divergent mechanism behind Urban Heat Island (UHI) across UFZs taking insights from 2D/3D urban morphology. The Minimum Spanning Tree (MST) indicator depicting 3D building distribution was introduced and integrated with the classic indicators. Their impacts on UHI were measured by ensemble learning and SHapley Additive exPlanations (SHAP) model. Taking Wuhan as the study area, the eighteen 2D/3D urban morphology indicators affecting UHI in different locations and UFZs were extensively examined and compared. The results reveal that: 1) The impact of 2D/3D urban morphology indicators on UHI significantly varies across different UFZs, with dominance in transportation zones exhibiting opposite polarity compared to the other types; 2) positive impacts have a decreasing trend from the urban center to the edge, while negative impacts exhibit opposite trend; 3) XGBoost outperforms other classic methods in interpreting the impact of urban morphology on UHI for all UFZ types. The findings improving knowledge of UHI across UFZs will provide a practical guide for urban planning.
期刊：
Journal of Cleaner Production,2024年434:139854 ISSN：0959-6526
通讯作者：
Gong, J
作者机构：
[Gao, Haoran; Ye, Teng; Gong, Jian] China Univ Geosci, Sch Publ Adm, Wuhan 430074, Peoples R China.;[Gao, Haoran; Ye, Teng; Gong, Jian] Minist Nat Resources, Key Lab Land & Resources Law Evaluat Project, Wuhan 430074, Peoples R China.;[Liu, Jiakang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430074, Peoples R China.
通讯机构：
[Gong, J ] C;China Univ Geosci, Sch Publ Adm, Wuhan 430074, Peoples R China.;Minist Nat Resources, Key Lab Land & Resources Law Evaluat Project, Wuhan 430074, Peoples R China.
关键词：
Ecological functional areas;Comparative analysis;Quantitatively analyze the drivers;Changes of SOC stocks;Carbon sequestration potential
摘要：
Understanding the process of land use/cover changes (LUCC) can provide experience on the enhancement of soil organic carbon (SOC) stocks and carbon sequestration potential for different areas. This study is uniquely to divide different ecological functional areas, and originally combine the machine learning method and soil carbon pool dataset for regional comparative analysis, to compare and quantitatively analyze the drivers of LUCC and the changes in SOC stocks effected by LUCC over 30 years. The results show that topography and climate changes are the main drivers affecting LUCC in four natural areas, while soil factors and population changes do not cause significant effects. The total SOC stocks in Qinghai was increased by 71.18 Tg C and 107.19 Tg C in 0–30 cm and 0–300 cm layers, respectively, and the highest SOC stocks within 0–300 cm were in Pastoral area. Desert and Gobi area had the lowest SOC stocks in both 0–30 cm and 0–300 cm layers. SOC stocks increased in both 0–30 cm and 0–300 cm layers only in Sanjiangyuan Natural Reserve, while the Desert and Gobi area showed a decrease in both over 30 years. This study emphasizes the significant impact of grassland changes on SOC stocks, indicating the importance of considering these changes in land management and ecological protection policies. The initial and original SOC stocks of pre-LUCC may influence the SOC stocks in post-LUCC. The response of SOC stocks changes to LUCC was varies in different areas. The heterogeneity of different ecological functional areas is affected by multiple factors and SOC stocks will become more complex among these areas in the future. These findings contribute to the development of ecological protection policies and the enhancement of regional land management strategies.
摘要：
Accurate monitoring of soil organic carbon (SOC) is critical for sustainable management of soil for improving its quality, function, and carbon sequestration. As a nondestructive, efficient, and low-cost technique, mid-infrared (MIR) spectroscopy has shown a great potential in rapid estimation of SOC, despite limited studies of the global scale. The objective of this work was to use a globally distributed topsoil MIR spectral library with 33,039 samples to predict SOC using different modeling methods. Effects of nine fractional-order derivatives (FODs) on the predicted accuracy of SOC were evaluated using four regression algorithms (i.e., ratio index-based linear regression, RI-LR; partial least squares regression, PLSR; Cubist; convolutional neural network, CNN). Square-root transformation to SOC data was performed to minimize the skewness and non-linearity. Results indicated FOD to capture the subtle spectral details related to SOC, leading to improved predictions that may not be possible by the raw absorbance and common integer-order derivatives. Concerning the RI-LR models, the optimal validation result for SOC was obtained by 0.75-order derivative, with the ratio of performance to inter-quartile distance (RPIQ) of 1.85. Regarding the full-spectrum modeling for SOC, the CNN outperformed PLSR and Cubist models, irrespective of raw absorbance or eight FODs; the best-performing CNN model was achieved by 1.25-order derivative (validation RPIQ = 6.33). It can be concluded that accurate estimation of SOC using large and diverse MIR spectral library at the global scale combined with deep-learning CNN model is feasible. This global-scale database is extremely valuable for us to deal with the shortage of soil data and to monitor the soils at different geographical scales.
关键词：
aridity;biogeography;climate change;deep soil;microbial biodiversity and function;soil depth;water heterogeneity
摘要：
Our results contribute to broader and deeper knowledge of climate change microbiology in deep soil environments under future climate scenarios. We proposes a potential mechanism for the association between climate aridity and deep soil microbes; that is, when the external aridity changes, water evapotranspiration (including plant transpiration and soil water evaporation) is directly and indirectly (e.g., changes in rooting depths and soil texture) affected, and a volumetric soil moisture gradient (related to soil porosity) is formed to primarily drive microorganisms in deep soil. Abstract Microbes inhabiting deep soil layers are known to be different from their counterpart in topsoil yet remain under investigation in terms of their structure, function, and how their diversity is shaped. The microbiome of deep soils (>1 m) is expected to be relatively stable and highly independent from climatic conditions. Much less is known, however, on how these microbial communities vary along climate gradients. Here, we used amplicon sequencing to investigate bacteria, archaea, and fungi along fifteen 18‐m depth profiles at 20–50‐cm intervals across contrasting aridity conditions in semi‐arid forest ecosystems of China's Loess Plateau. Our results showed that bacterial and fungal α diversity and bacterial and archaeal community similarity declined dramatically in topsoil and remained relatively stable in deep soil. Nevertheless, deep soil microbiome still showed the functional potential of N cycling, plant‐derived organic matter degradation, resource exchange, and water coordination. The deep soil microbiome had closer taxa–taxa and bacteria–fungi associations and more influence of dispersal limitation than topsoil microbiome. Geographic distance was more influential in deep soil bacteria and archaea than in topsoil. We further showed that aridity was negatively correlated with deep‐soil archaeal and fungal richness, archaeal community similarity, relative abundance of plant saprotroph, and bacteria–fungi associations, but increased the relative abundance of aerobic ammonia oxidation, manganese oxidation, and arbuscular mycorrhizal in the deep soils. Root depth, complexity, soil volumetric moisture, and clay play bridging roles in the indirect effects of aridity on microbes in deep soils. Our work indicates that, even microbial communities and nutrient cycling in deep soil are susceptible to changes in water availability, with consequences for understanding the sustainability of dryland ecosystems and the whole‐soil in response to aridification. Moreover, we propose that neglecting soil depth may underestimate the role of soil moisture in dryland ecosystems under future climate scenarios.
期刊：
Environmental Science and Pollution Research,2023年30(42):96329-96349 ISSN：0944-1344
通讯作者：
Yu, J
作者机构：
[Li, Yimin; Nie, Yan; Yin, Chen; Zhou, Yong; Yu, Lei] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;[Li, Yimin; Qin, Hong; Nie, Yan; Yin, Chen; Zhou, Yong; Yu, Lei] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Yu, J; Yu, Jing] Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China.
通讯机构：
[Yu, J ] H;Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China.
关键词：
Arable land multifunction;Functional trade-offs;Root mean square deviation method;Ecological compensation;The West Mountain Regions of Hubei Province
摘要：
Tropical deforestation frontiers continue to expand at alarming rates, but their fine-scale temporal patterns (e.g., start timing, patch forming speed, temporal clustering within a year) remain unresolved. Previous deforestation monitoring focus on the annual dynamics or the timely identification of deforestation activities; however, improved methods are needed for accurate mapping of deforestation patches at higher temporal resolution (i.e., sub-monthly) to better reveal their fine-scale temporal dynamics. We propose an optimization method inte-grating the spatial and temporal context information to improve the sub-monthly deforestation mapping from Sentinel-1 (S1) SAR data: (1) a deep learning-based spatial optimization to suppress speckle noises; (2) a Bayesian-based temporal optimization to meaningfully combine deforestations detected in the S1 data streams. The proposed method was comprehensively assessed in three deforestation hotspots in Brazil -Acre, Rondo<SIC>nia and Par ' a, for the whole year of 2019. Results showed: (1) the spatial optimization alone can improve the ac-curacies of deforestation mapping from single-date S1 images for up to 7.3%; (2) the Bayesian-based temporal optimization improved the deforestation mapping accuracies for about 5.9% after three post-deforestation S1 observations (about 18 +/- 3 days after deforestation); (3) combining the spatial and temporal optimizations achieved the highest classification accuracies (overall accuracy of 91.0%, IoU of 89.1%), surpassing the baseline monthly composite method (overall accuracy of 89.3%, IoU of 87.3%) within fewer observation days. Further frontier analysis based on these sub-monthly results showed varying distributions of patch size and forming speed in these three study sites during the wet and dry seasons. The temporal clustering of deforestation also differed among sites during 2019: deforestations in Rondo<SIC>nia were most concentrated during the dry season (CV = 1.1), followed by Par ' a (CV = 0.75), while Acre showed more even temporal distribution in deforestation year-round (CV = 0.57). The proposed method thus can be used for revealing unprecedented temporal details regarding tropical deforestation frontiers, which is critical for evaluating the ecological consequences and formulating scientific conservation strategies.
