Spatiotemporal pattern of vegetation water use efficiency between 2003 and 2017 and its coupling relationship with artificial carbon sequestration in the karst region of Southwestern China DOI Creative Commons
Lei Wang, Xiuqin Wu,

Jianbin Guo

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 154, P. 110566 - 110566

Published: July 1, 2023

After extensive ecological restoration in the karst region of Southwestern China, a potential zone for achieving "carbon neutrality" has emerged, despite facing water scarcity. We analyzed dynamics use efficiency (WUE) and its correlations with soil moisture (SM) leaf area index (LAI) from 2003 to 2017 using PML-V2 data multiple datasets SM LAI. Advantageous areas artificial carbon sequestration (CS) were also identified. Key findings are as follows: (1) Temporally, WUE exhibited fluctuating growth at an annual rate 0.01 gCmm−1H2O (P < 0.05). The advantage CS accounted 15.96%, over 31.74% regions needing management intervention. (2) Monthly was highest peak forest plain (PFP) landform (2.88 gCmm−1H2O), while PFP experiencing decrease −0.0021 gCmm−1H2O. (3) forests followed by shrubs (2.49 farmland (2.32 gCmm−1H2O) grassland (1.93 showing increase (0.02). (4) both positive (14.26%∼26.02%) negative (14.19%∼30.98%) correlations. In areas, decreased drought stress (DSI) increased all vegetation types. Clear DSI threshold observed (0.29 0.42) (0.19 0.30). However, values less pronounced. There transitional point impact on WUE, which faster types when exceeded 0.53. (5) LAI (27.09%∼30.25%) (23.37%∼34.57%) 1.85 based MODIS data, 2.71 GLASS 2.59 GEOV2 had 1.69, 2.66, 2.23, respectively. While displayed 0.79, 0.70, 0.72, minimum 3.14 4.05 grassland, it 1.04, 1.97, 1.76 This study helps us identify enhancing CS. It assists making informed decisions regarding implementation initiatives considering limiting factor adjustment measures utilizing reference standard.

Language: Английский

A 1 km daily soil moisture dataset over China using in situ measurement and machine learning DOI Creative Commons
Qingliang Li, Gaosong Shi, Wei Shangguan

et al.

Earth system science data, Journal Year: 2022, Volume and Issue: 14(12), P. 5267 - 5286

Published: Nov. 30, 2022

Abstract. High-quality gridded soil moisture products are essential for many Earth system science applications, while the recent reanalysis and remote sensing data often available at coarse resolution only surface soil. Here, we present a 1 km long-term dataset of derived through machine learning trained by in situ measurements 1789 stations over China, named SMCI1.0 (Soil Moisture China data, version 1.0). Random forest is used as robust approach to predict using ERA5-Land time series, leaf area index, land cover type, topography properties predictors. provides 10-layer with 10 cm intervals up 100 deep daily period 2000–2020. Using benchmark, two independent experiments were conducted evaluate estimation accuracy SMCI1.0: year-to-year (ubRMSE ranges from 0.041 0.052 R 0.883 0.919) station-to-station 0.045 0.051 0.866 0.893). generally has advantages other products, including ERA5-Land, SMAP-L4, SoMo.ml. However, high errors located North Monsoon Region. Overall, highly accurate estimations both ensure applicability study spatial–temporal patterns. As based on it can be useful complement existing model-based satellite-based datasets various hydrological, meteorological, ecological analyses models. The DOI link http://dx.doi.org/10.11888/Terre.tpdc.272415 (Shangguan et al., 2022).

Language: Английский

Citations

117
Evaluation of ecosystem resilience to drought based on drought intensity and recovery time DOI
Yao Ying, Bojie Fu, Yanxu Liu

et al.

Agricultural and Forest Meteorology, Journal Year: 2022, Volume and Issue: 314, P. 108809 - 108809

Published: Jan. 8, 2022

Language: Английский

Citations

89
Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth’s Third Pole DOI Creative Commons
Yuyang Wang, Jingfeng Xiao, Yaoming Ma

et al.

Science Advances, Journal Year: 2023, Volume and Issue: 9(20)

Published: May 17, 2023

The carbon sequestration capacity of alpine grasslands, composed meadows and steppes, in the Tibetan Plateau has an essential role regulating regional cycle. However, inadequate understanding its spatiotemporal dynamics regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed spatial temporal patterns net ecosystem exchange (NEE) dioxide Plateau. grasslands ranged from 26.39 79.19 Tg C year-1 had increasing rate 1.14 between 1982 2018. While were relatively strong sinks, semiarid arid steppes nearly neutral. Alpine meadow areas experienced increases mainly because temperatures, while steppe weak due precipitation. Carbon on plateau undergone persistent enhancement under a warmer wetter climate.

Language: Английский

Citations

85
A 21-year dataset (2000–2020) of gap-free global daily surface soil moisture at 1-km grid resolution DOI Creative Commons
Chaolei Zheng, Jia Li, Tianjie Zhao

et al.

Scientific Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: March 15, 2023

Abstract Global soil moisture estimates from current satellite missions are suffering inherent discontinuous observations and coarse spatial resolution, which limit applications especially at the fine scale. This study developed a dataset of global gap-free surface (SSM) daily 1-km resolution 2000 to 2020. is achieved based on European Space Agency - Climate Change Initiative (ESA-CCI) SSM combined product 0.25° resolution. Firstly, an operational gap-filling method was fill missing data in ESA-CCI using ERA5 reanalysis dataset. Random Forest algorithm then adopted disaggregate coarse-resolution 1-km, with help International Soil Moisture Network in-situ other optical remote sensing datasets. The generated had good accuracy, high correlation coefficent (0.89) low unbiased Root Mean Square Error (0.045 m 3 /m ) by cross-validation. To best our knowledge, this currently only long-term far.

Language: Английский

Citations

69
A fine-resolution soil moisture dataset for China in 2002–2018 DOI Creative Commons
Xiangjin Meng, Kebiao Mao, Fei Meng

et al.

Earth system science data, Journal Year: 2021, Volume and Issue: 13(7), P. 3239 - 3261

Published: July 7, 2021

Abstract. Soil moisture is an important parameter required for agricultural drought monitoring and climate change models. Passive microwave remote sensing technology has become means to quickly obtain soil across large areas, but the coarse spatial resolution of data imposes great limitations on application these data. We provide a unique dataset (0.05∘, monthly) China from 2002 2018 based reconstruction model-based downscaling techniques using different passive products – including AMSR-E AMSR2 (Advanced Microwave Scanning Radiometer Earth Observing System) JAXA (Japan Aerospace Exploration Agency) Level 3 SMOS-IC (Soil Moisture Ocean Salinity designed by Institut National de la Recherche Agronomique, INRA, Centre d’Etudes Spatiales BIOsphère, CESBIO) calibrated with consistent model in combination ground observation This new fine-resolution high overcomes multisource time matching problem between optical sources eliminates difference sensor errors. The validation analysis indicates that accuracy satisfactory (bias: −0.057, −0.063 −0.027 m3 m−3; unbiased root mean square error (ubRMSE): 0.056, 0.036 0.048; correlation coefficient (R): 0.84, 0.85 0.89 monthly, seasonal annual scales, respectively). was used analyze spatiotemporal patterns water content 2018. In past 17 years, China's shown cyclical fluctuations slight downward trend can be summarized as wet south dry north, increases west decreases east. reconstructed widely significantly improve hydrologic serve input ecological other geophysical are published Zenodo at https://doi.org/10.5281/zenodo.4738556 (Meng et al., 2021a).

Language: Английский

Citations

96
A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019 DOI Creative Commons
Peilin Song, Yongqiang Zhang, Jianping Guo

et al.

Earth system science data, Journal Year: 2022, Volume and Issue: 14(6), P. 2613 - 2637

Published: June 8, 2022

Abstract. Surface soil moisture (SSM) is crucial for understanding the hydrological process of our earth surface. The passive microwave (PM) technique has long been primary tool estimating global SSM from view satellites, while coarse resolution (usually >∼10 km) PM observations hampers its applications at finer scales. Although quantitative studies have proposed downscaling satellite PM-based SSM, very few products available to public that meet qualification 1 km and daily revisit cycles under all-weather conditions. In this study, we developed one such product in China with all these characteristics. was generated through AMSR-E/AMSR-2-based (Advance Microwave Scanning Radiometer Earth Observing System successor) 36 km, covering on-orbit times two radiometers during 2003–2019. MODIS optical reflectance data thermal-infrared land surface temperature (LST) had gap-filled cloudy conditions were inputs model so “all-weather” quality achieved SSM. Daily images quasi-complete coverage over country April–September. For other months, national percentage also greatly improved against original a specifically sub-model filling gap between seams neighboring swaths procedure. compares well situ measurements 2000+ meteorological stations, indicated by station averages unbiased root mean square difference (RMSD) ranging 0.052 0.059 vol vol−1. Moreover, evaluation results show outperforms SMAP (Soil Moisture Active Passive) Sentinel (active–passive microwave) combined correlation coefficient 0.55 0.40 latter product. This indicates new great potential be used community, agricultural industry, water resource environment management. download https://doi.org/10.11888/Hydro.tpdc.271762 (Song Zhang, 2021b).

Language: Английский

Citations

53
Automatic detection and classification of land subsidence in deltaic metropolitan areas using distributed scatterer InSAR and Oriented R-CNN DOI
Zherong Wu, Peifeng Ma, Yi Zheng

et al.

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 290, P. 113545 - 113545

Published: March 27, 2023

Language: Английский

Citations

42
The impact of greenspace on air pollution: Empirical evidence from China DOI Creative Commons
Hongshan Ai, Xi Zhang, Zhengqing Zhou

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 146, P. 109881 - 109881

Published: Jan. 9, 2023

Can green vegetation absorb air pollutants and control regional pollution? The existing research has not reached a consistent conclusion on this issue. Using the multi-level data in China, paper provides empirical evidence of causal impact greenspace PM2.5 through abundant fixed effect controls. Besides, applied soil humidity, Normalized Difference Vegetation Index (NDVI) last month, NDVI same month year, prefecture-level city average as instrumental variables, respectively, to test robustness estimation. results show that increased significantly decreases concentration other pollutants. In further analysis, we found decreasing turns significant when exceeds 0.3. addition, there are heterogeneities pollution. Greenspaces more pronounced pollution reduction southern or higher administrative-level cities. This suggests increasing is an economical effective way achieve co-management multiple

Language: Английский

Citations

40
Relationships of stomatal morphology to the environment across plant communities DOI Creative Commons
Congcong Liu, Lawren Sack, Ying Li

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 19, 2023

Abstract The relationship between stomatal traits and environmental drivers across plant communities has important implications for ecosystem carbon water fluxes, but it remained unclear. Here, we measure the morphology of 4492 species-site combinations in 340 vegetation plots China calculate their community-weighted values mean, variance, skewness, kurtosis. We demonstrate a trade-off density size at community level. mean variance are mainly associated with precipitation, while that is temperature, skewness kurtosis less related to climatic soil variables. Beyond climate variables, trait moments also vary seasonality extreme conditions. Our findings extend knowledge trait–environment relationships scale, applications predicting future cycles.

Language: Английский

Citations

36
Annual atrazine residue estimation in Chinese agricultural soils by integrated modeling of machine learning and mechanism-based models DOI
Fengxian Chen, Bin Zhou,

Liqiong Yang

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 472, P. 134539 - 134539

Published: May 4, 2024

Language: Английский

Citations

10