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Large-Scale Spatial Patterns of Grassland Community Properties in the Inner Mongolia Autonomous Region, China

文献类型：期刊论文

作者Qiao, YuXin2,4; Zhu, HuaZhong2,5; Li, Yuzhe3; Shao, Xiaomin4; Zhong, HuaPing3; Shi, Hua6; Wu, ZhaoWen1,2
刊名RANGELAND ECOLOGY & MANAGEMENT
出版日期2020-07-01
卷号73期号:4页码:560-568
关键词grassland community properties multifactor comprehensive model regression analysis spatial interpolation spatial pattern
ISSN号1550-7424
DOI10.1016/j.rama.2020.02.003
通讯作者Zhong, HuaPing(zhonghp@igsnrr.ac.cn)
英文摘要Mapping large-scale spatial patterns of grassland community properties in the Inner Mongolia Autonomous Region of China and learning how they are affected by environmental factors are vital to understand grassland changes in response to climate change and human activity. We collected data on six grassland community properties across 198 sample plots in the Inner Mongolia Autonomous Region: height, coverage, aboveground biomass (AGB), belowground biomass (BGB), soil bulk density (SBD), and species number (SN). We then analyzed the relationship between these and a range of environmental factors, including elevation, mean annual temperature (MAT), mean annual precipitation (MAP), >= 10 C annual accumulated temperature, humidity index, and normalized difference vegetation index (NDVI), using correlation and regression analysis. On the basis of the regression equation, we undertook a multifactor model using ArcGIS, in which different weights were assigned to each factor according to the degree of fitness between the estimated results and measured data. We then mapped the spatial distribution of grassland community properties in Inner Mongolia. We found a significant correlation between all of the grassland community properties and environmental factors measured (P < 0.01). In terms of spatial patterns, SN, height, coverage, AGB, and BGB were positively correlated with the transition from desert grassland to meadow grassland. The community properties model provided good results, with average accuracies of 53.05-90.21% and R-2 values of 0.40-0.68 (P < 0.01) across the six grassland community properties. The multifactor comprehensive model provides significant correlation between the predicted results and measured data. Therefore, this could be used as a basis for future studies on Inner Mongolia grasslands and to understand temporal and spatial changes of grassland in response to human activity and climate change. (C) 2020 The Society for Range Management. Published by Elsevier Inc. All rights reserved.
WOS关键词NET PRIMARY PRODUCTIVITY ; ABOVEGROUND BIOMASS ; CARBON STOCKS ; RESPONSES ; VEGETATION ; DIVERSITY
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000547491400012
出版者SOC RANGE MANAGEMENT
源URL[http://ir.igsnrr.ac.cn/handle/311030/158396]  
专题中国科学院地理科学与资源研究所
通讯作者Zhong, HuaPing
作者单位1.Chinese Acad Sci, State Key Lab Systemat & Evolutionary Bot, Inst Bot, Beijing 100093, Peoples R China
2.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Tibet Agr & Anim Husb Coll, Tibet 850400, Peoples R China
5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
6.US Geol Survey, InuTeq, Earth Resources Observat & Sci Ctr, Sioux Falls, SD 57198 USA
推荐引用方式
GB/T 7714		 Qiao, YuXin,Zhu, HuaZhong,Li, Yuzhe,et al. Large-Scale Spatial Patterns of Grassland Community Properties in the Inner Mongolia Autonomous Region, China[J]. RANGELAND ECOLOGY & MANAGEMENT,2020,73(4):560-568.
APA Qiao, YuXin.,Zhu, HuaZhong.,Li, Yuzhe.,Shao, Xiaomin.,Zhong, HuaPing.,...&Wu, ZhaoWen.(2020).Large-Scale Spatial Patterns of Grassland Community Properties in the Inner Mongolia Autonomous Region, China.RANGELAND ECOLOGY & MANAGEMENT,73(4),560-568.
MLA Qiao, YuXin,et al."Large-Scale Spatial Patterns of Grassland Community Properties in the Inner Mongolia Autonomous Region, China".RANGELAND ECOLOGY & MANAGEMENT 73.4(2020):560-568.

入库方式： OAI收割

来源：地理科学与资源研究所

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