摘要：
Inorganic fertilizers are widely used to provide crops with significant amounts of nitrogen (N) and phosphorus (P), but can exacerbate soil carbon (C) limitation and acidification. Crop residues with distinct ecological stoichiometry from inorganic fertilizers can help balance soil ecological stoichiometry and thus increase soil organic matter accumulation. The combined use of inorganic fertilizers and crop residues is expected to alleviate the metabolic limitations of organisms and enhance soil C, N, and P sequestration, hence increasing grain yields. However, the effects of this practice on soil C, N, and P stocks and grain yield remain unclear. In this study, we conducted a meta-analysis of 806 paired data to investigate the impact of crop residue return combined with inorganic fertilizer on soil and grain yield across different land uses (paddy, upland, paddy-upland rotation) and soil profiles (0–60 cm). Our findings indicate that crop residue return significantly enhances soil C (8–13%) stocks across all soil layers, particularly in the topsoil (0–20 cm). Soil N (9%) and P (5%) stocks also increase significantly in the topsoil. In uplands, crop residue return can mitigate soil acidification and increase grain yield (by 7%). Moreover, the soil C and N stocks increase depending on the initial soil pH, C and N levels, and C:N ratio. In contrast, the soil P stock increase depends on rainfall, while the grain yield increase is closely linked to the soil texture and fertilizer rate. Our study highlights that crop residue return can increase topsoil C, N, and P stocks, which can benefit crop growth and environmental mitigation efforts. Furthermore, this practice can increase C stocks in deeper soil horizons (below 20 cm), providing a long-term solution to mitigate climate change.
作者机构：
Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan 430079, China;College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China;Author to whom correspondence should be addressed.;[Liu, Jingyi; He, Nan; Wang, Li; Zuo, Qian; Li, Qing] Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan 430079, China<&wdkj&>College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China;[Zhou, Yong] Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan 430079, China<&wdkj&>College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
通讯机构：
[Yong Zhou] K;Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan 430079, China<&wdkj&>College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
Land use/cover change (LUCC) accompanied by climate change and human activities will have unpredictable impacts on watershed ecosystems. However, the extent to which these land use changes affect the spatial and temporal distribution of ecosystem services (ESs) in different regions remains unclear. The impact of LUCC on ESs in the Qingjiang Watershed (QJW), an ecologically sensitive area, and LUCC’s role in future ESs under different land use scenarios are crucial to promoting ecological conservation and land use management. This paper assessed water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) using the InVEST model, and their responses to LUCC in the QJW from 1990 to 2018 using the geodetector and multiscale geographically weighted regression. We predicted land use patterns using the Logistic–CA–Markov model and their effects on ESs in 2034 under business as usual (BAU), ecological land protection (ELP), arable land protection (ALP) and ecological economic construction (EEC) scenarios. From 1990 to 2018, the area of cropland and woodland decreased by 28.3 and 138.17 km2, respectively, while the built-up land increased by 96.65 km2. The WY increased by 18.92%, while the SC, CS and HQ decreased by 26.94%, 1.05% and 0.4%, respectively. The increase in the arable land area led to a increase in WY, and the decrease in forest land and the increase in construction land led to a decrease in SC, CS and HQ. In addition to being influenced by land use patterns, WY and SC were influenced mainly by meteorological and topographical factors, respectively. In 2034, there was an obvious spatial growth conflict between cropland and construction land, especially in the area centered on Lichuan, Enshi and Yidu counties. Under four scenarios, WY and SC were ranked ALP > BAU > EEC > ELP, while CS and HQ were ranked ELP > EEC > BAU > ALP. Considering the sustainable eco-socio-economic development of the QJW, the EEC scenario can be chosen as a future development plan. These results can indicate how to rationally improve the supply of watershed ESs through land resource allocation, promoting sustainable regional development in mountainous watershed areas.
摘要：
Fractional vegetation cover (FVC) has a significant role in indicating changes in ecosystems and is useful for simulating growth processes and modeling land surfaces. The fine-resolution FVC products represent detailed vegetation cover information within fine grids. However, the long revisit cycle of satellites with fine-resolution sensors and cloud contamination has resulted in poor spatial and temporal continuity. In this study, we propose to derive a spatially and temporally continuous FVC dataset by comparing multiple methods, including the data-fusion method (STARFM), curve-fitting reconstruction (S-G filtering), and deep learning prediction (Bi-LSTM). By combining Landsat and Sentinel-2 data, the integrated FVC was used to construct the initial input of fine-resolution FVC with gaps. The results showed that the FVC of gaps were estimated and time-series FVC was reconstructed. The Bi-LSTM method was the most effective and achieved the highest accuracy (R-2 = 0.857), followed by the data-fusion method (R-2 = 0.709) and curve-fitting method (R-2 = 0.705), and the optimal time step was 3. The inclusion of relevant variables in the Bi-LSTM model, including LAI, albedo, and FAPAR derived from coarse-resolution products, further reduced the RMSE from 5.022 to 2.797. By applying the optimized Bi-LSTM model to Hubei Province, a time series 30 m FVC dataset was generated, characterized by a spatial and temporal continuity. In terms of the major vegetation types in Hubei (e.g., evergreen and deciduous forests, grass, and cropland), the seasonal trends as well as the spatial details were captured by the reconstructed 30 m FVC. It was concluded that the proposed method was applicable to reconstruct the time-series FVC over a large spatial scale, and the produced fine-resolution dataset can support the data needed by many Earth system science studies.
期刊：
Science of The Total Environment,2023年892:164735 ISSN：0048-9697
通讯作者：
Li, J
作者机构：
[Liu, Qinhuo; Gu, Chenpeng; Dong, Yadong; Zhao, Jing; Li, Jing; Liu, Chang; Mumtaz, Faisal] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.;[Liu, Qinhuo; Gu, Chenpeng; Dong, Yadong; Zhao, Jing; Li, Jing; Liu, Chang; Mumtaz, Faisal] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.;[Gao, Jixi] Minist Ecol & Environm Peoples Republ China, Satellite Applicat Ctr Ecol & Environm, Beijing 100094, Peoples R China.;[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
通讯机构：
[Li, J ] C;Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
关键词：
Leaf area index;Eurasian Steppe (EAS);ENSO;Vegetation change
摘要：
As the most influential atmospheric oscillation on Earth, the El Niño/Southern Oscillation (ENSO) can significantly change the surface climate of the tropics and subtropics and affect the high latitudes of northern hemisphere areas through atmospheric teleconnection. The North Atlantic Oscillation (NAO) is the dominant pattern of low-frequency variability in the Northern Hemisphere. As the dominant oscillations in the Northern Hemisphere, the ENSO and NAO have been affecting the giant grassland belt in the world, the Eurasian Steppe (EAS), in recent decades. In this study, the spatio-temporal anomaly patterns of grassland growth in the EAS and their correlations with the ENSO and NAO were investigated using four long-term leaf area index (LAI) and one normalized difference vegetation index (NDVI) remote sensing products from 1982 to 2018. The driving forces of meteorological factors under the ENSO and NAO were analyzed. The results showed that grassland in the EAS has been turning green over the past 36years. Warm ENSO events or positive NAO events accompanied by increased temperature and slightly more precipitation promoted grassland growth, and cold ENSO events or negative NAO events with cooling effects over the whole EAS and uneven precipitation decreased deteriorated the EAS grassland. During the combination of warm ENSO and positive NAO events, a more severe warming effect caused more significant grassland greening. Moreover, the co-occurrence of positive NAO with cold ENSO or warm ENSO with negative NAO kept the characteristic of the decreased temperature and rainfall in cold ENSO or negative NAO events, and deteriorate the grassland more severely.
摘要：
Semantic change detection (SCD) holds a critical place in remote sensing image interpretation, as it aims to locate changing regions and identify their associated land cover classes. Presently, post-classification techniques stand as the predominant strategy for SCD due to their simplicity and efficacy. However, these methods often overlook the intricate relationships between alterations in land cover. In this paper, we argue that comprehending the interplay of changes within land cover maps holds the key to enhancing SCD's performance. With this insight, a Temporal-Transform Module (TTM) is designed to capture change relationships across temporal dimensions. TTM selectively aggregates features across all temporal images, enhancing the unique features of each temporal image at distinct pixels. Moreover, we build a Temporal-Transform Network (TTNet) for SCD, comprising two semantic segmentation branches and a binary change detection branch. TTM is embedded into the decoder of each semantic segmentation branch, thus enabling TTNet to obtain better land cover classification results. Experimental results on the SECOND dataset show that TTNet achieves enhanced performance when compared to other benchmark methods in the SCD task. In particular, TTNet elevates mIoU accuracy by a minimum of 1.5% in the SCD task and 3.1% in the semantic segmentation task.
期刊：
Critical Reviews in Environmental Science and Technology,2023年53(20):1795-1816 ISSN：1064-3389
通讯作者：
Linchuan Fang
作者机构：
[He, Haoran; Fang, Linchuan; Chao, Herong; Zeng, Yi; Chen, Li; Zhang, Zhiqin] Northwest A&F Univ, Coll Nat Resources & Environm, Yangling, Peoples R China.;[He, Haoran; Duan, Chengjiao; Fang, Linchuan; Chao, Herong; Zeng, Yi; Chen, Li; Zhang, Zhiqin] Inst Soil & Water Conservat CAS & MWR, State Key Lab soil Eros & Dryland Farming Loess Pl, Yangling, Peoples R China.;[Wang, Fayuan] Qingdao Univ Sci & Technol, Coll Environm & Safety Engn, Qingdao, Peoples R China.;[Hu, Weifang] Guangdong Acad Agr Sci, Inst Agr Resources & Environm, Guangzhou, Peoples R China.;[Liu, Ji] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.
通讯机构：
[Linchuan Fang] C;College of Natural Resources and Environment, Northwest A&F University, Yangling, China<&wdkj&>State Key Laboratory of soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation CAS and MWR, Yangling, China
关键词：
Arbuscular mycorrhizal fungi;bioaccumulation;crop growth;Jörg Rinklebe and Lena Q. Ma;meta-analysis;physiological activities;potentially toxic elements
摘要：
Soil pollution from potentially toxic elements (PTEs) is a serious environmental issue worldwide that affects agricultural safety and human health. Arbuscular mycorrhizal fungi (AMF), as ecosystem engineers, can alleviate PTE toxicity in crop plants. However, the comprehensive effects of AMF on crop performance in PTE-contaminated soils have not yet been recognized globally. Here, a meta-analysis of 153 studies with 3213 individual observations was conducted to evaluate the effects of AMF on the growth and PTE accumulation of five staple crops (wheat, rice, maize, soybean, and sorghum) in contaminated soils. Our results demonstrated that AMF had strong positive effects on the shoot and root biomass. This is because AMF can effectively alleviate oxidative damage induced by PTEs by stimulating photosynthesis, promoting nutrition, and activating non-enzymatic and enzymatic defense systems in crop plants. AMF also decreased shoot PTE accumulation by 23.6% and increased root PTE accumulation by 0.8%, demonstrating that AMF effectively inhibited the PTE transfer and uptake by crop shoot. Meanwhile, AMF-mediated effects on shoot PTE accumulation were weaker in soils with pH > 7.5. Overall, this global survey has essential implications on the ability of AMF to enhance crop performance in PTE-contaminated soils and provides insights into the guidelines for safe agricultural production worldwide.
通讯机构：
[Yi, J.] H;Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, China
关键词：
nitrogen balance;nitrogen leaching;nitrogen uptake;nitrogen use efficiency;paddy yield
摘要：
Nitrogen loss from paddy fields contributes to most of the nitrogen pollution load in the Ningxia Yellow River irrigation area, threatening the water quality of the Yellow River. Consequently, optimizing the nitrogen management practices in this area is essential, which can maintain paddy grain productivity and reduce nitrogen loss simultaneously. Five treatments with different nitrogen application rates and nitrogen fertilizer types were set in this study, including conventional urea application with zero nitrogen application rate (CK, 0 kg hm(-2)), nitrogen expert-based fertilization application strategy (NE, 210 kg hm(-2)), optimized nitrogen fertilizer application strategy recommended by local government (OPT, 240 kg hm(-2)), and farmer's experience-based nitrogen fertilizer application strategy (FP, 300 kg hm(-2)), and controlled-release urea application (CRU, 180 kg hm(-2)). The data from one growth season field experiment in 2021 revealed the dynamics of nitrogen concentration, paddy yield and its nitrogen uptake characteristic, and nitrogen balance in the paddy field under different nitrogen application practices. Most nitrogen leaching was observed during the seedling and tillering stages in the form of nitrate nitrogen (NO3-N). Compared with the FP, the CRU and OPT significantly reduced the nitrogen concentrations of total nitrogen (TN), ammonium nitrogen (NH4+-N), and NO3-N in the surface and soil water and reduced the nitrogen leaching at 100 cm soil depth. Meanwhile, the paddy grain yield in CRU (7737 kg hm(-2)) and OPT (7379 kg hm(-2)) was not significantly decreased compared with FP (7918 kg hm(-2)), even though the nitrogen uptake by grain and straw was higher in FP (135 kg hm(-2)) than in other treatments (52.10 similar to 126.40 kg hm(-2)). However, the grain yield in NE (6972 kg hm(-2)) was decreased compared with the FP. The differences in grain yield among these treatments were mainly attributed to the ear number and grain number changes. Also, the highest nitrogen use efficiency (40.14%), apparent nitrogen efficiency (19.53 kg kg(-1)), and nitrogen partial productivity (43.98 kg kg(-1)) were identified in CRU than in other treatments. Considering increased grain yield and reducing nitrogen loss in the paddy field simultaneously, the treatments of CRU (i.e., 180 kg hm(-2) nitrogen application rate with controlled-release urea) and OPT (i.e., 240 kg hm(-2) nitrogen application rate with conventional urea) were recommended for nitrogen fertilizer application in the study area.
作者机构：
[Ma, Li; Ni, Yongxin; Wang, Jianwei; Lv, Xizhi; Zhang, Qiufen] Yellow River Inst Hydraul Res, Henan Key Lab Yellow Basin Ecol Protect & Restorat, Zhengzhou 450003, Peoples R China.;[Zhang, Xin; Qin, TL; Qin, Tianling] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.;[Ni, Yongxin] Hohai Univ, Coll Hydrol & Water Recourses, Nanjing 210098, Peoples R China.;[Nie, Hanjiang] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Nie, Hanjiang] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Qin, TL ] C;China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.
关键词：
distributed hydrological model;water and land resources;evapotranspiration;runoff coefficient;Sihe River Basin
摘要：
Abstract: Conflicts between humans and land use in the process of using water and conflicts between humans and water resources in the process of using land have led to an imbalance between natural ecosystems and socio-economic systems. It is difficult to understand the impact of the processes of water production and consumption on land patches and their ecological effects. A grid-type, basin-distributed hydrological model was established in this study, which was based on land-use units and coupled with groundwater modules to simulate the water production and consumption processes in different units. By combining land use and net primary productivity, the runoff coefficient and the water use efficiency (NPP/ET) of different land units were used as indicators to characterize the interaction between water and land resources. The results showed that the average runoff coefficients of cultivated land, forest land and grassland were 0.7, 0.5 and 0.9, respectively. Moreover, the average runoff coefficients of hills, plains and basins were 0.7, 0.7 and 0.8, respectively. The NPP produced by the average unit, evapotranspiration, in cultivated land, forest land and grassland was 7 (gC/(m2•a))/mm, 0.7 (gC/(m2•a))/mm and 0.2 (gC/(m2•a))/mm, respectively. These results provide quantitative scientific and technological support in favor of the comprehensive ecological management of river basins. Keywords: distributed hydrological model; water and land resources; evapotranspiration; runoff coefficient; Sihe River Basin
