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SSRN 2024年

作者： Mengdi, Fu Chunfei, Hou Jun, Wang Yuanyuan, Zhang Jiade, Bai Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection Chinese Research Academy of Environmental Sciences 8 Anwai Dayangfang Chaoyang District Beijing100012 China Center for Biodiversity and Nature Reserve Chinese Academy of Environmental Planning Beijing100041 China Beijing Biodiversity Conservation Research Center Beijing100076 China Beijing Milu Ecological Research Center Beijing100076 China

China's coastal wetlands provide important breeding, migratory stopover and wintering areas for birds in the East Asian-Australasian flyway, and the Bohai Rim wetlands are one of the most important distribution areas for waterbirds. Seventeen coastal wetlands around the Bohai Sea were selected to investigate the diversity of waterbirds, clarify the community composition and its temporal and spatial changes, and analyze the main factors influencing waterbird diversity in different types of coastal wetlands. The results showed that 133 species of waterbirds, representing 18 families from 8 orders, were observed, mainly in the families Scolopacidae, Charadriidae and Laridae. From 2018 to 2023, the species, abundance and diversity of waterbirds fluctuated and increased, while the evenness showed a fluctuating and decreasing trend. PM2.5 and the construction of protected areas were the key factors influencing waterbird diversity, and vegetation cover, macroinvertebrates biodiversity index, population density and temperature were the main factors influencing waterbird diversity. PM2.5 was the most important factor influencing waterbird diversity in estuarine wetlands, followed by population density. Population density and vegetation cover were the most important factors influencing waterbird diversity in island wetlands, followed by the establishment of nature reserves. Population density was the most important factor influencing waterbird diversity in tidal wetlands, followed by the establishment of nature reserves. PM2.5 was the most important factor influencing waterbird diversity in shallow sea wetlands, followed by eutrophication. The results of this study are intended to provide a basis for scientific decision-making and precise policy implementation for the conservation of wetland bird diversity. © 2024, The Authors. All rights reserved.

关键词： Wetlands

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Plasticity Response Of Desert Shrubs To Extreme Drought Events At Different Phenophases Under the Context of Climate Change

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SSRN 2024年

作者： Wang, Chunyuan Yu, Minghan Ding, Guodong Quan, Zhanjun State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China State Key Laboratory of Environmental Protection for Regional Eco-Process and Function Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China Institute of Ecology Chinese Research Academy of Environmental Sciences Beijing100012 China Yanchi Research Station School of Soil and Water Conservation Beijing Forestry University Beijing100083 China Key Laboratory of State Forestry Administration on Soil and Water Conservation Beijing Forestry University Beijing100083 China

Desert ecosystems are expected to suffer from extreme drought events with unprecedented frequency and magnitude amidst the current situation of severe droughts and erratic seasonal rainfall induced by global climate change. Against this background, it is essential to elucidate the differences in the plasticity response of typical desert vegetation to extreme drought events at different phenophases for predicting the response of desert ecosystems to climate change. Taking the typical subshrub Artemisia ordosica community in the Mu Us Desert as the research object, this study simulated the extreme drought events via controlling rainfall at the sample plot scale, setting up three extreme drought treatment gradients in phenophases. This paper aimed to investigate the differences in the impacts of extreme drought events at different phenophases on the phenotypic characteristics and functional traits of A. ordosica, as well as the trade-off response mechanism of its twig number and length, and nutrient reproduction allocation to extreme drought events. Results showed that (1) Phenotypic characteristics of A. ordosica decreased significantly under extreme drought events at each phenophase, while the number and length of twigs declined, thereby lowering the accumulation of ANPP;the impacts of the extreme drought events on ANPP accumulation of A. ordosica at each phenophase were as follows: flowering and fruiting stage > sprouting stage > vegetative growth stage. (2) The number and length of twigs of the current year showed a significant positive correlation under extreme drought conditions. (3) A. ordosica would adapt to extreme drought via increasing the proportion of reproductive growth and decreasing the proportion of vegetative growth during both sprouting and vegetative growth stages. This study has demonstrated the varying impacts on phenotypic characteristics and functional traits of A. ordosica by extreme drought at each phenophase, and A. ordosica possesses a plast

关键词： Drought

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Nitrogen Addition Enhances Tree Radial Growth But Weakens its Recovery from Drought Impact in a Temperate Forest in Northern China

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SSRN 2023年

作者： Cao, Jing Liu, Hongyan Zhao, Bo Li, Zongshan Liang, Boyi Song, Zhaopeng Shi, Liang Wu, Lu Wang, Qiuming Zhu, Yanpeng Li, Shuang State Key Laboratory of Environmental Criteria and Risk Assessment State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China College of Urban and Environmental Science MOE Laboratory for Earth Surface Processes Peking University Beijing100871 China Lhasa Plateau Ecosystem Research Station Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Science Chinese Academy of Sciences Beijing China College of Forestry Beijing Key Laboratory of Precise Forestry Institute of GIS RS & GPS Beijing Forestry University Beijing100083 China China Meteorological Administration Training Center Beijing100081 China

Forest growth in most parts of northern China is currently limited by drought and low nitrogen availability. The extreme drought events have increasingly threatened multiple ecosystem services provided by forests. Whether nitrogen addition will have a detrimental/beneficial moderation effect on forest resistance and recovery to extreme droughts was remained unclear. Here, Pinus tabulaeformis is the research object in this study, which is the main artificial forest species in northern China. We investigate the role of climate and nitrogen addition in driving multi-year tree growth with a combination of an 8 year nitrogen addition experiment and 184 tree ring series. An extreme drought event occurred during the experiment, providing an opportunity for us to explore the effects of drought and nitrogen addition on tree resistance and recovery. We found that nitrogen addition is beneficial for increasing the resistance of young trees, but has no effect on old trees. The recovery of trees weakens significantly with increasing nitrogen addition, and the reduction in fine root biomass caused by multiyear nitrogen addition is a key influencing factor of limited recovery after extreme drought. Our study implies that the combined effect of increasing drought and nitrogen deposition might increase the risk of pine forest mortality in northern China. © 2023, The Authors. All rights reserved.

关键词： Recovery

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An online spatio-temporal sudden pollution simulation system for the Songhua River, China

An online spatio-temporal sudden pollution simulation system...

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IEEE International Conference of Online Analysis and Computing Science (ICOACS)

作者： Gula Tang Bao Xiang Zhaoliang Li Yunqiang Zhu Chinese Academy of Sciences Institute of Geographical Sciences and Natural Resources Research Beijing China ICube (UMR 7357) CNRS Strasbourg France University of Chinese Academy of Sciences Beijing China Chinese Research Academy of Environmental Sciences State Environment Protection key Laboratory of RegionalEco-process and Function Assessment Beijing China

ISBN: (纸本)9781467377560

The Songhua River Pollution Control Project is one of the most significant water-related environmental pollution control schemes in Northeastern China. This paper details the requirements, architecture, and main components of an online river sudden pollution simulation system (RSPSS) for scientific planning and decision making for a complicated natural river network. On the basis of a service-oriented method and spatiotemporal simulation technology, the following components are developed: multi-platform, multi-level, dynamic, and flexible data services; task services that can be used by other online ArcGIS Server Silverlight Projects; and integrated third-party hydrodynamic and water quality models, which can simulate complex river networks under natural hydrological and climatic conditions online. With the RSPSS, spatial and non-spatial datasets and functions are seamlessly integrated from distributed sources by standard services. Thus, this system can support effective cross-regional and cross-departmental decisions. A study of a real-world implementation of the suggested system involving the historical sudden pollution of the Songhua River based on the RSPSS is also presented.

关键词： Decision support systems Water pollution

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Comparison of denoising multi-algorithms for the MODIS NDVI time-series signal

Comparison of denoising multi-algorithms for the MODIS NDVI ...

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Congress on Image and Signal processing, CISP

作者： GuLa Tang Bao Xiang ShouZhen Liang GuangWen Ma JunQin Wang State Key Laboratory of Resources and Environmental Information Systems Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China LSIIT CNRS UdS Illkirch France Chinese Academy of Sciences Beijing China State Environment Protection key Laboratory of Regional Eco-process and Function Assessment Chinese Research Academy of Environmental Sciences Beijing China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China China National Environmental Monitoring Centre Beijing China Sichuan Provincial Water Conservancy Research Institute Chengdu China

ISBN: (纸本)9781467309653

Cloud clutter is the most important noise in NDVI time series data signal; hence to remove the cloud noise is prerequisite for the normal use of NDVI data. In this paper, the MODIS NDVI data of Second Songhua River Basin and Songhua River Trunk Stream Basin is adopted as the experimental region, to conduct a comparative analysis of noise reduction effect for the HANTS algorithm, the Moving Average method and the Asymmetric Gaussian function fitting method. The results show that the HANTS algorithm and the Asymmetric Gaussian function fitting method can effectively remove the noise, while the denoising effect of the Moving Average method is inferior. In general, the HANTS algorithm can provide the best denoising effect, but the algorithm is more difficult in setting parameters.

关键词： Vegetation mapping Fitting Clouds Time series analysis Noise Noise reduction MODIS

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Diversity characteristic and pollution load of non-point source total nitrogen and total phosphorus in Songhua River Basin

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2011年第SUPPL.2期27卷 163-169页

作者： Ma, Guangwen Wang, Yeyao Xiang, Bao Wang, Jinsheng Wang, Taiming Hu, Yu College of Water Sciences Beijing Normal University Beijing 100875 China Chinese Research Academy of Environmental Sciences Beijing 100012 China China National Environmental Monitoring Centre Beijing 100012 China State Environment Protection Key Laboratory of Regional Eco-Process and Function Assessment Beijing 100012 China

In order to study the diversity characteristic and pollution load of non-point source pollution of nitrogen and phosphorus in the Songhua River, and provide a reference for the water environment management, based on remote sensing (RS) and geographic information system (GIS) technique, using the data of digital elevation model (DEM), county statistics and land use in Songhua River Basin in 2008, the space simulation and load estimation of non-point source pollution in the Songhua River Basin was conducted by export coefficient model (ECM), and the diversity of the non-point source pollution characteristics in the basin was analyzed. The results showed that the non-point source total nitrogen (TN) load was 112.99×104 t and total phosphorus (TP) load was 4.05×104 t in the Songhua River Basin in 2008 respectively. Nenjiang River sub-basin was the maximum load of TN and TP which was 52.80×104 t and 1.79×104 t respectively, accounting for 46.09% and 44.14% of the total TN and TP. The maximum load intensity of TN and TP was the second Songhua River sub-basin which was 2.96 t/(km2·a) and 0.11 t/(km2·a) respectively. From the perspective of non-point sources, 95.92×104 t of TN loads and 3.40×104 t of TP loads were caused by anthropogenic activities, accounting for 83.90% and 83.94% of the total TN and TP respectively. Anthropogenic factor is the key of non-point source TN and TP of the Songhua River, natural causes should not be ignored as well. The results can provide reference for water environment management and overall understanding the non-point source pollution of the Songhua River.

关键词： Geographic information systems

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Model bias in calculating factor importance of climate on vegetation growth

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Global and Planetary Change 2023年第1期228卷

作者： Liang, Boyi Liu, Hongyan Wang, Shaopeng Cressey, Elizabeth L. Dahlsjö, Cecilia A.L. Xu, Chongyang Wang, Jia Wang, Zong Liu, Feng Feng, Siwen Shi, Liang Dai, Jingyu Cao, Jing Li, Fufu Quine, Timothy A. College of Forestry Precision Forestry Key Laboratory of Beijing Beijing Forestry University Beijing100083 China College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface Processes Peking University Beijing100871 China Geography College of Life and Environmental Sciences University of Exeter ExeterEX4 4RJ United Kingdom School of Geography and the Environment University of Oxford OxfordOX1 3QY United Kingdom Faculty of Agriculture Food and Environment The Hebrew University of Jerusalem Rehovot7610001 Israel Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China National Ecosystem Science Data Center Beijing100101 China State Key Laboratory of Environmental Criteria and Risk Assessment State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China

Machine learning is increasingly used to study vegetation growth, however, more often than not, predicting and simulating functions are prioritized over quantitative estimates of the drivers of vegetation growth such as climate. In this paper, we, for the first time, systematically investigate the model bias in calculating factor importance of climate on vegetation growth, especially when various kinds of machine learning models are considered. We undertake two case studies to simulate research in remote sensing and ground-based scenarios from which the difference in quantitative relationships between climate and vegetation is evaluated across multiple models. We found that model complexity increased the determination coefficient (R2) but reduced the absolute importance of the preselected independent variables. As the fitting accuracy increases, the absolute factor importance of dominant factor and all the other influencing factors decreases simultaneously, and factor importance calculated by different models tended to be more normally distributed across the study region. The reduction in factor importance was accompanied by the increased effect of model selection;e.g. the model that was used to estimate vegetation growth played a larger role in producing the factor importance (shown by variance analysis, remote sensing scenario, F-statistic = 555.2;ground based scenario, F-statistic = 30.8) than the climate variables (variance analysis, remote sensing scenario, F = 460.8;ground based scenario, F = 28.8). Critically, for those machine learning models with highest fitting accuracy, the resultant factor importance of climate factors had smaller difference with that of random factor. In contrast, the relative factor influence among the selected climate factor is more robust and reliable (in variation analysis, model was detected no significant impact on the resultant factor importance). For 5 of 8 models, the dominant factor (temperature) has relative influence over 0.

关键词： Machine learning

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Genome assembly of autotetraploid Actinidia arguta highlights adaptive evolution and enables dissection of important economic traits

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Plant Communications 2024年第6期5卷 173-192页

作者： Xue-Mei Lu Xiao-Fen Yu Guo-Qiang Li Ming-Hao Qu Huan Wang Chuang Liu Yu-Ping Man Xiao-Han Jiang Mu-Zi Li Jian Wang Qi-Qi Chen Rui Lei Cheng-Cheng Zhao Yun-Qiu Zhou Zheng-Wang Jiang Zuo-Zhou Li Shang Zheng Chang Dong Bai-Lin Wang Yan-Xiang Sun Hui-Qin Zhang Jie-Wei Li Quan-Hui Mo Ying Zhang Xin Lou Hai-Xu Peng Ya-Ting Yi He-Xin Wang Xiu-Jun Zhang Yi-Bo Wang Dan Wang Li Li Qiong Zhang Wen-Xia Wang Yongbo Liu Lei Gao Jin-Hu Wu Yan-Chang Wang CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture Wuhan Botanical GardenChinese Academy of SciencesWuhanHubeiChina Key Laboratory of Western China’s Environmental Systems(Ministry of Education) College of Earth and Environmental SciencesLanzhou UniversityLanzhouGansuChina College of Life Sciences University of Chinese Academy of SciencesBeijingChina Wuhan Frasergen Bioinformatics Co. LtdWuhanHubeiChina Institute of Soil and Fertilizer Anhui Academy of Agricultural SciencesHefeiChina College of Agricultural Sciences Xichang UniversityXichangSichuanChina Department of Horticulture Heilongjiang Academy of Agricultural SciencesHarbinHeilongjiangChina College of Life Sciences Langfang Normal UniversityLangfangHebeiChina Institute of Horticulture Zhejiang Academy of Agricultural SciencesHangzhouZhejiangChina Guangxi Institute of Botany Chinese Academy of SciencesGuilinGuangxiChina Xi’an Botanical Garden of Shaanxi Province Institute of Botany of Shaanxi ProvinceXi’anShaanxiChina Institute of Modern Agricultural Research Dalian UniversityDalianLiaoningChina Bioinformatics Center College of Plant Science and TechnologyBeijing University of AgricultureBeijingChina College of Agriculture Eastern Liaoning UniversityDandongLiaoningChina Dalian Institute of Chemical Physics Chinese Academy of SciencesDalianLiaoningChina State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment Chinese Research Academy of Environmental SciencesBeijingChina Hubei Hongshan Laboratory WuhanHubeiChina The New Zealand Institute for Plant and Food Research Limited AucklandNew Zealand

Actinidia arguta,the most widely distributed Actinidia species and the second cultivated species in the genus,can be distinguished from the currently cultivated Actinidia chinensis on the basis of its small and smooth fruit,rapid softening,and excellent cold *** evolution of tetraploid Actinidia species and the genetic basis of their important agronomic traits are still ***,we generated a chromosome-scale genome assembly of an autotetraploid male *** *** genome assembly was 2.77 Gb in length with a contig N50 of 9.97 Mb and was anchored onto 116 *** and clustering of 101 geographically representative accessions showed that they could be divided into two geographic groups,Southern and Northern,which first diverged 12.9 million years *** underwent two prominent expansions and one demographic bottleneck from the midPleistocene climate transition to the late *** genomics studies using paleoclimate data enabled us to discern the evolution of the species’adaptation to different historical *** genes(AaCEL1,AaPME1,and AaDOF1)related to flesh softening were identified by multi-omics analysis,and their ability to accelerate flesh softening was verified through transient expression assays.A set of genes that characteristically regulate sexual dimorphism located on the sex chromosome(Chr3)or autosomal chromosomes showed biased expression during stamen or carpel *** chromosome-level assembly of the autotetraploid *** genome and the genes related to important agronomic traits will facilitate future functional genomics research and improvement of ***.

关键词： kiwiberry dioecism adaptive evolution paleoclimate GEA rapid softening

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The 2nd International Conference on Water Resource and environment (WRE 2016) Shanghai, China. 23-26 July 2016 Abstracts

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BMC ecoLOGY 2016年第SUPPL 2期16卷 71-71页

作者： [Anonymous] Key Laboratory of Forest Ecology and Management Institute of Applied Ecology Chinese Academy of Sciences 72 Wenhua Road Shenhe District Shenyang 110016 People’s Republic of China State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University) Chengdu 610500 Sichuan China School of Geoscience and Technology Southwest Petroleum University Chengdu 610500 Sichuan China Technology Center Sichuan Coal Industry Group Limited Liability Company Chengdu 610091 Sichuan China School of Civil Engineering and Architecture Southwest Petroleum University Chengdu 610500 Sichuan China Hainan Academy of Ocean and Fisheries Sciences Haihou 570100 China Third Institute of Oceanography State Oceanic Administration Xiamen 361005 China College of Forestry and Landscape Architecture South China Agricultural University Guangzhou 510642 China Inner Mongolia University for Nationalities Tongliao 028043 Inner Mongolia China Marine College Shandong University Weihai 264209 China Institute of Ecology and Biodiversity Shandong University Jinan 250100 China Cold and Arid Regions Environmental and Engineering Research Institute Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions Chinese Academy of Sciences Lanzhou 730000 China College of Life Science Guangxi Normal University Guilin 541004 Guangxi China Key Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University) Ministry of Education Guilin 541004 China Tianjin Research Institute for Water Transport Engineering Key Laboratory of Engineering Sediment Ministry of Transport Tanggu Tianjin 300456 China State Key Laboratory of Ecological Water Conservancy in the Northwest Arid Area Xi’an University of Technology Xi’an 710048 China Research Institute of Complex Engineering and Management Tongji University Shanghai 200092 China China Three Gorges Corporation Beijing 100038 China Ji’nan City Construction Investment Group Corpor

01 The eco-toxicological effects of cadmium stress on five ornamental plants Zhouli Liu, Wei Chen, Xingyuan He, Shuai Yu, Weihang Ding 02 Study on the formation and release mechanisms of hydrogen sulfide in Longtan coal mine Jianjun Liu, Yuliang Wu, Kaixiang Fan 03 Coral bleaching in the North Reef of China’s Xisha Islands in 2014 Yuanchao Li, Xinqing Zheng, Shiquan Chen, Haiqun Xie 04 Soil chemical characteristics in a Cunninghamia lanceolata stand suffering from ice-snow damage Jie Li, Zhuomin Wang, Li Xue 05 Diversity of understory vegetation was under a Cunninghamia lanceolata stand suffering from ice-snow damage Zhiyang Lie, Weilong Huang, Tongtong Zhou, Li Xue 06 The effect of water, nitrogen and harvesting time on yield and biomass allocation of Helianthus tuberosus L. Kai Gao, Tiexia Zhu 07 The vertical variation of microbial communities in the sediment of sea cucumber pond Weiteng Mao, Pei Yu, Xinfang Lv, Yunchun Li 08 Indicating significances of alpine plant functional groups to environmental change Peixi Su, Rui Shi 09 Research on the daily CH4 fluxes of soil in summer mangrove community at Yingluogang of Guangxi, China Yong Jiang, Xingbin Chen, Shichu liang 10 Beach protection structures in middle and lower reaches of Yangtze River Junfeng Xu 11 Social responsibility management of large dam project with owner as core: an empirical case in China Jiwei Zhu, Zhao Zhai, Linan Zhou, Yun Le, Li Cao 12 The ecological function value assessment analysis of urban waterfront Jiwei Zhu, Ping Lu, Zhiqian Huang, Bei Zhou 13 Mechanism of diurnal osmotic potential changes and adjustment of three Caragana species in different habitats of the Inner Mongolia Plateau Zhirong Zheng, Shihai Lv, Chaoyang Feng 14 Biodiversity of phytoplankton and environmental influences analysis of Longfeng Wetland, China Nan Song, Yan Liu, Xinxin Lu, Yawen Fan 15 The effect of human activities on culturable soil microbes from Yaoquan Mountain in Wudalianchi, China Jianfei Guan, Jihua Wang, Xu

关键词： Coral Bleaching Caragana Species Zoige Plateau Degraded Meadow Beach protection

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Correction to: Full‑scale genetic pattern and environmental association of Actinidia chinensis populations across ten mountain systems in China, and its significance for conservation

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Tree Genetics & Genomes 2023年第1期20卷 1-1页

作者： Lu, Xue‑Mei Wang, Yan‑Chang Liu, Chuang Liao, Li Liu, Yongbo Zhang, Jian‑Wen Zhong, Cai‑Hong Li, Zuo‑Zhou Wuhan Botanical Garden Chinese Academy of Sciences Wuhan China Institute of Soil and Fertilizer Anhui Academy of Agricultural Sciences Hefei China State Environmental Protection Key Laboratory of Regional Eco‑process and Function Assessment Chinese Research Academy of Environmental Sciences Beijing China Xinjiang Bayingoleng Mongolian Autonomous Prefecture Academy of Agricultural Sciences Korla China

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