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Wind farms increase land surface temperature and reduce vegetation productivity in the inner mongolia

Geography and Sustainability 2024年第3期5卷 319-328页

作者： Luyao Liu Pengtao Liu Jiawei Yu Gang Feng Qing Zhang Jens-Christian Svenning Ministry of Education Key Laboratory of Ecology and Resource Use of the mongolian Plateau School of Ecology and EnvironmentInner Mongolia UniversityHohhot 010021China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China inner mongolia autonomous region ecological and agricultural meteorological centre Hohhot 010051China e Collaborative Innovation Center for Grassland ecological Security(Jointly Supported by the Ministry of Education of China and inner mongolia autonomous region) Hohhot 010021China Center for ecological Dynamics in a Novel Biosphere(ECONOVO) Department of BiologyAarhus UniversityNy Munkegade 114Aarhus C DK-8000Denmark Center for Biodiversity Dynamics in a Changing World(BIOCHANGE) Department of BiologyAarhus UniversityNy Munkegade 114Aarhus C DK-8000Denmark

Wind power has been developing rapidly as a key measure to mitigate human-driven global *** under-standing of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still *** this study,we combined remote sensing and on-site investigations to identify wind farm locations in inner mongolia and performed landscape pattern analyses using *** explored the impacts of wind farms on land surface temperature(LST)and vegetation net primary productivity(NPP)between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm *** results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in ***,wind farms are mainly clustered in three aggregation areas in the ***,wind farms increased nighttime LST,with a mean value of 0.23℃,but had minor impacts on the daytime ***,wind farms caused a decline in NPP,especially over forest areas,with an average reduction of 12.37 GC/m^(2).Given the impact of wind farms on LST and NPP,we suggest that the development of wind farms should fully consider their direct and potential *** study provides scientific guidance on the spatial pattern of future wind farms.

关键词： Wind farm Landscape pattern LST NPP inner mongolia

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Spatiotemporal variations in ecological quality of Otindag Sandy Land based on a new modified remote sensing ecological index

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Journal of Arid Land 2023年第8期15卷 920-939页

作者： ZHAO Xiaohan HAN Dianchen LU Qi LI Yunpeng ZHANG Fangmin Collaborative Innovation Center on Forecast and Evaluation of meteorological Disasters/Jiangsu Key Laboratory of agricultural Meteorology Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Desertification Chinese Academy of ForestryBeijing 100091China Ecology and agricultural Meteorology Center of inner mongolia autonomous region Hohhot 010051China

Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this *** on principal component analysis and path analysis,we first generated a modified remote sensing ecological index(MRSEI)coupled with satellite and ground observational data during 2001–2020 that integrated four local indicators(greenness,wetness,and heatness that reflect vegetation status,water,and heat conditions,respectively,as well as soil erosion).Then,we assessed the ecological quality in Otindag Sandy Land during 2001–2020 based on the MRSEI at different time scales(i.e.,the whole year,growing season,and non-growing season).MRSEI generally increased with an upward rate of 0.006/a during 2001–2020,with clear seasonal and spatial *** quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern *** with ecological degradation expanded to 18.64%of the total area in the non-growing *** area with the worst grade of MRSEI shrunk by 15.83%of the total area from 2001 to 2020,while the area with the best grade of MRSEI increased by 9.77%of the total *** temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing *** implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological *** results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.

关键词： ecological quality modified remote sensing ecological index principal component analysis path analysis Otindag Sandy Land dryland ecosystem

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Evaluation of the Adaptability of Six Sets of Precipitation Data in inner mongolia

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meteorological and Environmental Research 2021年第5期12卷 21-30,34页

作者： Yan HUANG Haiqing SONG Xiaolong SUN Shiyun LIU Ulanqab meteorological Bureau Ulanqab 012000China ecological and agricultural Meteorology Center of inner mongolia autonomous region Hohhot 010051China

Based on daily precipitation data of 119 weather stations over inner mongolia in 2018,the adaptability of six sets of precipitation data( GLDAS2.1,ITPCAS,CLDAS2.0,CMPAS2.0 ERA5 and CMPAS2.1) in inner mongolia was evaluated and analyzed by using Pearson correlation coefficient( R),mean deviation( Bias) and root mean square error( RMSE).The results indicate that the six sets of precipitation data could well reflect the spatial and temporal variation of precipitation over inner *** a ten-day scale,the mean deviation of CMPAS2.1 had a smaller variation,which slightly underestimated precipitation;the mean deviation of CLDAS2.0 had a smaller variation in the eastern region;the mean deviation of both ITPCAS and CMPAS2.0 was more stable in the central region than in the eastern and western regions;the mean deviation of GLDAS2.1 and ERA5 had a relatively larger variation,and ERA5 overestimated precipitation to a certain extent;the root mean square error of CMPAS2.1 had the smallest variation,whereas that of ERA5 was relatively *** monthly scale was similar to the ten-day *** correlation coefficient of the six sets of precipitation data in the central region was better than that in the east and west,and the mean deviation and root mean square error were relatively larger in areas with more complex mountain *** to statistical indicators,CMPAS2.1 performed better in inner mongolia than other five sets of data.

关键词： Precipitation data inner mongolia Evaluation

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The Effect of ecological Factors on the Indexes of Yield Property Equation and Quantitative Analysis

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agricultural Sciences in China 2010年第4期9卷 536-548页

作者： HOU Yu-hong DONG Shu-ting HOU Guo-feng CHEN Chuan-yong DONG Zhi-qiang ZHAO Ming College of Agronomy Shandong Agricultural University Tai'an 271018 P.R.China Institute of Crop Science Chinese Academy of Agricultural Sciences Beijing 100081 P.R. China Soil Fertilizer Station of inner mongolia autonomous region Hohhot 010011 P.R.China

The mechanism of action of ecological factors affecting crop growth and development was complicated. In order to study the relationships between ecological factors and the indexes of yield property equation and determine the main ecological factors affecting yield, using 3-yr field experimental results for different yielding spring maize （Zea mays L.） populations and the relative meteorological observation data in Huadian of Jilin Province in China, and analyzing on the base of the yield property equation （MLAI × D × MNAR × HI = EN × GN × GW）, the main ecological factors were screened, and further mechanisms of action affecting yield were analyzed. Stepwise regression analysis showed that yield was affected mainly by effective accumulated temperature, daily mean minimum temperature, daily mean maximum temperature in July, the ratios of growth days, and the sunshine hour before and after silking. In yield property equation, four indexes of MLAI, growth days, ear number and grain number （total grain number） affected principally yield, the ecological factors affecting predominantly yield were effective accumulated temperature, daily mean temperature, daily mean minimum temperature, daily mean maximum temperature in July, the ratios of growth days, rainfall, accumulated temperature, and sunshine hours before and after silking. Combined with the two analytical methods, it could be deduced that the temperature and the allocated ratios before and after silking of ecological factors were the key factors to achieve high yield. Therefore, appropriate sowing data should be adjusted to achieve the suitable temperature indexes during the whole growth stage and the rational allocated ratios of ecological factors before and after silking.

关键词： spring maize ecological factors three combination structure yield property equation

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