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The temporal and spatial distributionfeatures of precipitation based on corrected TMPA data in northwest arid area of China

The temporal and spatial distributionfeatures of precipitati...

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IGU2013 International Conference on Water Sustainability in Arid Regions(第十届国际地理大会——水资源可持续发展论坛)

作者： Yanfen Yang Yi Luo Chansheng He University of Chinese Academy of Sciences BeijingChina100049 Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences11ADatun RoadChaoyang DistrictBeijingChina100101 Lanzhou UniversitySouth Tianshui RoadLanzhouChina730000 Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences11ADatun RoadChaoyang DistrictBeijingChina100101

The northwest arid region of China has an extensive coverage of land and *** and its distribution are critically complicated by the atmospheric circulation and the *** observed precipitation data is quite scare due to...

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Community Structure and Diversity Distribution Pattern of Sandy Plants in the Middle and Upper Reaches of the Yarlung Zangbo River

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Journal of Resources and Ecology 2021年第1期12卷 11-21页

作者： LI Chao XU Wenli LI Qingkang WANG Jingsheng Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China School of Environment and Natural Resources Renmin University of ChinaBeijing 100872China

The Yarlung Zangbo River Basin is an important populated area in Tibet, and its plant community structure and diversity pattern have attracted the attention of many scholars. In this paper, the distribution pattern of plant diversity and the environmental factors impacting it in the middle and upper reaches of the Yarlung Zangbo River are revealed and discussed through sample surveys and climate and habitat data. The results show that the plant communities in the study area can be divided into seven types according to the dominant species: Artemisia minor + Stipa purpurea, Artemisia wellbyi + Festuca ovina, Potentilla fruticosa + Orinus thoroldii, Trikeraia hookeri + Artemisia frigida, Kobresia pygmaea, Sophora moorcroftiana + Artemisia hedinii, and Sophora moorcroftiana + Pennisetum centrasiaticum. Plant diversity decreases with decreasing longitude, increasing latitude, and increasing altitude;and the diversity distribution pattern in the study area has distinct zonal characteristics. Water and heat are the main factors which affect the distribution of vegetation types. The explanation rates of water and heat for the plant diversity distribution pattern were 19.3% and 5.7%, respectively, while the spatial variation explained by these two factors together was 60.8%. Therefore, the coupling effect is obvious.

关键词： Yarlung Zangbo River community structure diversity pattern

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Spatial variations and mechanisms for the stability of terrestrial carbon sink in China

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Science China Earth Sciences 2023年第2期66卷 227-236页

作者： Kai WANG Shilong PIAO Yue HE Yongwen LIU Honglin HE College of Urban and Environmental Sciences Peking UniversityBeijing100871China State Key Laboratory of Tibetan Plateau Earth System Resources and Environment(TPESRE)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing100101China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China National Ecosystem Science Data Center Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing100190China

Understanding the stability of terrestrial carbon sinks(S-TCS)contributes to more accurate prediction of the terrestrial carbon sink(TCS)in the context of future global change and helps inform climate change mitigation ***,focusing on China,we analyzed the spatial distribution and driving mechanisms for the S-TCS,quantified by the interannual variability of the TCS,using three independent approaches(atmospheric inversions,ecosystem carbon cycle models,and machine learning models based on flux tower observations).We found that the interannual variability of the TCS in China is relatively small compared with the conterminous United States and geographic Europe,indicating a generally stable TCS in ***,the S-TCS is lower in the North China Plain,Northeast China Plain,and western Yunnan-Guizhou Plateau than in other regions,with varying underlying *** interannual variations in precipitation and high TCS sensitivities to precipitation fluctuations explain the low S-TCS in the North China Plain and Northeast China Plain,while high TCS sensitivities to temperature variations drive the low S-TCS in the western Yunnan-Guizhou *** findings highlight the importance of considering local contexts for stabilizing and enhancing China’s TCS in a changing environment.

关键词： Terrestrial carbon sink Stability Interannual variability China Carbon neutrality

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SPATIALIZATION OF STATION MEASURED NET ecosystem EXCHANGE USING ARTIFICIAL NEURAL network

SPATIALIZATION OF STATION MEASURED NET ECOSYSTEM EXCHANGE US...

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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： RUN-HE SHI XU-DONG ZHU HUI-FANG ZHANG Key Laboratory of Geographic Information Science for Ministry of Education East China Normal Univer Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Science and Na Key Laboratory of Geographic Information Science for Ministry of Education East China Normal Univer

Net ecosystem exchange (NEE) is a critical ecological parameter indicating the exchange of carbon dioxide between vegetation and atmosphere, which is widely used in the field of carbon cycle researches. It is common measurement by flux tower based on eddy covariance technique can only represent local status, however regional NEE is much more important. This paper introduces a spatialization method of NEE based on artificial neural network (ANN). 14 input nodes are selected purposefully including meteorological variables, ecological variables, land cover variables and seasonal variables. A feed-forward back propagation neural network is trained by 92 measured samples. Validation results show that ANN is a satisfactory method for the spatialization of NEE-like ecological parameters.

关键词： Spatialization net ecosystem ezchange artificial neural network

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High-altitude tree growth responses to climate change across the Hindu Kush Himalaya

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Journal of Plant Ecology 2021年第5期14卷 829-842页

作者： Lili Zheng Narayan Prasad Gaire Peili Shi Lhasa Plateau Ecosystem Research Station Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China CAS Key Laboratory of Tropical Forest Ecology Xishuanghanna Tropical Botanical GardenChinese Academy of SciencesMenglunMenglaYunnan 666303China Central Department of Environmental Science Tribhuvan UniversityKirtipurKathniantluNepal

Aims Rapid warming at high altitudes may lead to a higher sensitivity in tree growth to *** key factors constraining tree radial growth and to what extent regional tree growth has suffered from climatic changes are *** Tree-ring width data were collected from 73 sites across the Hindu Kush Himalaya(HKH),including three dominant genera(Abies,Juniperus and Picea)at high altitudes over 3000 *** time warping was introduced to develop subregional chronologies by considering the synchrony of annual tree growth among different *** quantified the contribution of the climate variables,and analyzed the spatiotemporal variation of the growth–climate *** Findings The site chronologies were grouped into three clusters,corresponding to the three distinct bioclimatic zones,*** western HKH,central-eastern HKH and southeastern Tibetan Plateau(TP).Tree growth was positively correlated to winter and spring precipitation in the drier western HKH,and to winter temperature and spring precipitation in the humid southeastern *** growth was markedly constrained by the minimum temperature,especially in winter,with its importance increasing from the west toward the *** shown by moving correlation analysis,the signal of winter temperature in tree growth was weakened in the western and central-eastern HKH,while it was enhanced in the southeastern TP following rapid warming since the *** results highlight that continuous warming may cause forest recession due to warming-induced moisture deficit in the western HKH,but forest expansion in the southeastern TP.

关键词： tree ring high-altitude forests key climate factors tree growth-climate relationships growth trends climate sensitivity

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Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China

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Forest ecosystems 2023年第2期10卷 141-152页

作者： Shuai Wang Bol Roland Kabindra Adhikari Qianlai Zhuang Xinxin Jin Chunlan Han Fengkui Qian College of Land and Environment Shenyang Agricultural UniversityShenyang110866China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchCASBeijing100101China Institute of Bio-and Geosciences Agrosphere(IBG-3)Forschungszentrum Jülich GmbHWilhelm-Johnen-Straße52428JülichGermany School of Natural Sciences Environment Centre WalesBangor UniversityBangorLL572UWUK USDA-ARS GrasslandSoil and Water Research LaboratoryTempleTX76502USA Department of Earth Atmosphericand Planetary SciencesPurdue UniversityWest LafayetteIN47907USA

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 *** 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 ***,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 *** selected80%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 *** found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,*** maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in *** annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both *** 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 *** study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks *** 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 ***,our approach is likely to be useful in forestry management and ecologic

关键词： Soil organic carbon stocks Forest ecosystem Spatial-temporal variation Carbon sink Digital soil mapping

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Whole-Fertility Rice Growth Monitoring Based on C-Band Sar Data at the Phenological Scale Using Crop Growth Curve

SSRN

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SSRN 2023年

作者： Liu, Yu Wang, Bo Sheng, Qinghong Li, Jun Zhao, Hong Wang, Shuwei Liu, Xiaoli He, Honglin College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing211106 China Changshu National Agro-Ecosystem Observation and Research Station Institute of Soil Science Chinese Academy of Sciences Nanjing210008 China Yingtan National Agro-Ecosystem Observation and Research Station Institute of Soil Science Chinese Academy of Sciences Nanjing210008 China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

Rice plant height is a comprehensive reflection of rice itself, as well as soil, hydrology, meteorology, and other factors, and is an important indicator for monitoring rice growth. Synthetic Aperture Radar (SAR) has become one of the important means for monitoring rice growth due to its sensitivity to vegetation changes. This paper proposes a dynamic monitoring method for rice plant height based on crop growth law, effectively combining crop growth law with plant height models, developing a Dual Polarization SAR crop growth (DPSCG) model, and using unsupervised domain adaptive (DA) method to improve the generalization ability of growth monitoring. The experimental results show that the DPSCG model proposed in this study considers the correlation of crop growth changes in the time dimension and the difference in crop growth at different phenological stages and can be effectively applied to the entire growth period of rice. © 2023, The Authors. All rights reserved.

关键词： Synthetic aperture radar

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Significant Difference between Temporal and Spatial Scales Regarding the Response of Soil Respiration to Temperature and Precipitation in China's Terrestrial ecosystems

SSRN

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SSRN 2023年

作者： Zhao, Wei Yang, Meng Yu, Guirui Chen, Zhi Wang, Qiufeng Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100049 China

In the context of increasing CO2 concentrations and climate warming, there are large uncertainties regarding the regulatory mechanisms of soil respiration and its accurate assessment. As an area sensitive to global climate change, China covers a broad range of longitudes, latitudes, and altitudes, and it is of great significance to study the spatial and temporal patterns of soil respiration and its environmental response in China's terrestrial ecosystems to clarify the mechanisms of regional and global carbon balance processes and their assessment. Based on the expanded annual soil respiration dataset from 1993 to 2020, we re-evaluated soil respiration in China's terrestrial ecosystems and its responses to environmental factors. The mean annual soil respiration in China's terrestrial ecosystems was 777.90 ± 489.43 g C m-2 yr-1, with soil respiration in wetlands being higher than that of the forest, grassland, shrubland, cropland, and desert. Soil respiration showed a significant upward trend between 1993 and 2020, which was mainly caused by a significant increase in soil respiration in grasslands due to increasing precipitation. In addition, we found differences in the environmental factors influencing the interannual and spatial variability of soil respiration. MAP dominated the interannual variability of soil respiration in China, whereas MAT and MAP jointly controlled the spatial variability of soil respiration in China. The response sensitivity of soil respiration to interannual climate variability was significantly higher than its response sensitivity to spatial variability, possibly one of the reasons for the relatively low accuracy of the present statistical models, which do not distinguish between temporal and spatial responses. More studies are needed to quantify the response of soil respiration to environmental changes at temporal and spatial scales and to construct soil respiration models considering two-dimensional responses in time and space. © 2023, Th

关键词： Climate change

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Strong Inhibiting Effect of Daytime Warming But Weak Promoting Effect of Nighttime Warming on Carbon Use Efficiency in Northern Hemisphere

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SSRN 2023年

作者： Sun, Yihan Zhang, Yangjian Zheng, Zhoutao Zhao, Guang Zhu, Yixuan Gao, Jie Zhang, Yu Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100190 China

Asymmetric diurnal warming broadly affects terrestrial ecosystem carbon cycling in the Northern Hemisphere. Vegetation photosynthesis mostly occurs in the daytime and respiration occurs during the whole day. Then the asymmetrical diurnal warming will certainly affect the ratio between net ecosystem productivity (NPP) against gross ecosystem productivity (GPP), i.e. vegetation carbon use efficiency (CUE). However, this kind of study has rarely been reported on a global scale. Using long-term productivity datasets from MODIS and land surface models, we investigated spatiotemporal response patterns of CUE to daytime (Tmax) and nighttime (Tmin) temperature changes across the Northern Hemisphere (>30°N) spanning 2000-2019. Regions exhibiting a positive correlation between Tmax and CUE were extensive throughout the growing season in most northern ecosystems, with a greater magnitude in summer than in spring and autumn. Tmin tended to cause a positive impact on CUE in spring and autumn, while being correlated negatively with summer CUE, resulting in a weak positive relationship between CUE and Tmin. Divergences in the strength and direction of productivity and respiratory responses to diurnal warming lead to spatial and seasonal patterns between CUE and Tmax or Tmin, which is regulated by soil moisture. Our findings provide an in-depth understanding of how the interaction between asymmetric diurnal warming and water limitations regulates the spatiotemporal variations of vegetation product allocation, which is vital for predicting future carbon dynamics under climate warming. © 2023, The Authors. All rights reserved.

关键词： Vegetation

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Spatial variability of water use efficiency in China's terrestrial ecosystems

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GLOBAL AND PLANETARY CHANGE 2015年第Jun.期129卷 37-44页

作者： Zhu, Xian-Jin Yu, Gui-Rui Wang, Qiu-Feng Hu, Zhong-Min Zheng, Han Li, Sheng-Gong Sun, Xiao-Min Zhang, Yi-Ping Yan, Jun-Hua Wang, Hui-Min Zhao, Feng-Hua Zhang, Jun-Hui Shi, Pei-Li Li, Ying-Nian Zhao, Liang Zhang, Fa-Wei Hao, Yan-Bin Chinese Acad Sci Inst Geog Sci & Nat Resources Res Key Lab Ecosyst Network Observat & Modeling Synth Res Ctr Chinese Ecosystem Res Network Beijing 100101 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Xishuangbanna Trop Bot Garden Key Lab Trop Forest Ecol Menglun 666303 Peoples R China Chinese Acad Sci South China Bot Garden Guangzhou 510650 Guangdong Peoples R China Chinese Acad Sci Inst Appl Ecol Shenyang 110016 Peoples R China Chinese Acad Sci Northwest Inst Plateau Biol Xining 810001 Peoples R China

Water use efficiency (WUE) reflects the coupling of carbon and water cycles. Analyzing the spatial variability of WUE can improve our understanding on the interaction between carbon and water cycles at a large scale, which also provides a basis for improving the regional carbon budget assessment. Based on,China's eddy covariance measurements, we examined the spatial variation of China's WUE and its affecting factors. WUE showed a decreasing trend with the increasing altitude, which was the result of ecosystem type distribution resulting from the climatic gradient. After fully considering the vertical variation of WUE, we found that not only mean annual air temperature (MAT), mean annual precipitation (MAP), and mean leaf area index (MLAI) but also mean annual total photosynthesis active radiation (MAR) affected the spatial variation of WUE. With the increasing MAT, MAP, and MLAI, WUE increased significantly but the increasing MAR decreased WUE. The spatial variation of WUE could be directly depicted by MLAI and altitude, the equation including which explained 65% of the spatial variation of WUE. The effects of MAT and MAP on the spatial variation of WUE may be achieved through altering MLAI, while the mechanism underlying the effect of MAR on the spatial variation of WUE was still unclear, which should be the subject of future investigations. This study reveals the vertical variation of WUE and provides a new approach to generate the spatial variation in WUE, which will benefit the regional carbon budget assessment. (C) 2015 Elsevier B.V. All rights reserved.

关键词： eddy covariance water use efficiency terrestrial ecosystems ChinaFLUX spatial pattern altitude leaf area index vertical variation

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