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煤矿井田区地表沉陷对植被景观的影响——以山西省晋城市东大煤矿为例
引用本文:全占军,程宏,于云江,邹学勇.煤矿井田区地表沉陷对植被景观的影响——以山西省晋城市东大煤矿为例[J].植物生态学报,2006,30(3):414-420.
作者姓名:全占军  程宏  于云江  邹学勇
作者单位:北京师范大学中国沙漠研究中心,北京 100875
北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875
中国环境科学研究院,北京 100022
基金项目:中国科学院资助项目;科技部社会公益研究项目
摘    要:借助地表沉陷预测模型,预测了地表沉陷状况,依据地表沉陷对景观的破坏程度划分出重度影响区和轻度影响区;在遥感及地理信息系统技术的支持下,把植被景观现状与地表沉陷影响区叠加,通过沉陷前后景观格局的变化分析,对山西省晋城市东大煤矿的生态影响进行了探索性评价研究。结果表明:1) 重度影响区地表会出现盆型、马鞍型和波浪型等塌陷或裂缝,土壤侵蚀的作用将导致土壤养分空间格局发生明显变化。塌陷或裂缝周围生境恶化,成为养分流失源,植被恢复困难;养分汇处土壤水、肥条件优越,植被演替迅速,适当的人为干扰可以加快区域生态环境的恢复步伐。2) 地表沉陷后,植被景观破碎及隔离程度严重,原有的稳定态景观格局被打破,随着地形、土壤的空间变化,植被开始新一轮发展演替。由于原先占绝对优势的退化植被类型白羊草(Bothriochloa ischemum)-百里香(Thymus mongolicus)型优势度下降,同时,大部分次优势景观的内部生态功能受影响不大,这对景观整体的生物多样性以及次优势景观类型的演替是有益的,但是,重度影响区对斑块的隔离呈直线性,这对物种迁移的障碍是明显的。因此,重视井田区的封育与引种工作,科学规划、合理布局,在此基础上,引导植被演替沿着白羊草-百里香型—白羊草-黄背草(Themeda japonica)型—灌木丛—阔叶林的方向发展是可行的。

关 键 词:地表沉陷  景观  最大斑块指数  景观形状指数  凝结度指数  
收稿时间:2005-08-16
修稿时间:2005-12-20

ASSESSMENT OF SUBSIDENCE IMPACT ON VEGETATION LANDSCAPE IN COAL MINING AREA-A CASE STUDY OF DONGDA MINE IN JINCHENG CITY, SHANXI PROVINCE
QUAN Zhan-Jun,CHENG Hong,YU Yun-Jiang,ZOU Xue-Yong.ASSESSMENT OF SUBSIDENCE IMPACT ON VEGETATION LANDSCAPE IN COAL MINING AREA-A CASE STUDY OF DONGDA MINE IN JINCHENG CITY, SHANXI PROVINCE[J].Acta Phytoecologica Sinica,2006,30(3):414-420.
Authors:QUAN Zhan-Jun  CHENG Hong  YU Yun-Jiang  ZOU Xue-Yong
Affiliation:Center for China Desert Research, Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China, Beijing Normal University, Beijing 100875, China
Chinese Academy of Environmental Sciences, Beijing 100022, China
Abstract:Ground subsidence and its effects on environment have been the core content of ecological and environmental assessment in coal mining area. Although there are researches on these topics, the results and methods show some uncertainties and few involves forecast analysis.  This paper forecasts the status of ground subsidence using ground subsidence forecasting mathematical model and classifies the heavy or slight influencing areas based on the degree of destructions of landscape. Based on remote sensing (RS) and geographical information system (GIS), this paper overlays the existing state map of the vegetation landscape and the map of the influenced areas. The influence of mining on environment is analyzed by comparison of the landscape patterns before and after ground subsidence in Dongda Mine of Jincheng, Shanxi Province. The results showed that:  1) in heavy influencing areas, there are some collapse or crack structure such as basin, saddle and wave etc. Soil erosion leads to obvious change in spatial distribution of soil nutrients. The environment near the collapse or crack areas  worsens and becomes the source of nutrient loss. It is very difficult for the vegetation to recover in these areas. In  nutrient_rich areas, the vegetation succession performs rapidly. Proper artificial disturbance can accelerate the recovery paces of the regional environment. 2) After the ground subsidence, the vegetation landscape is broken up and isolated severely. With the changes of landform and soil in space, the vegetation begins to perform a new round of succession. Because the degraded vegetation type, Bothrichloa ischaemum_Thymus mongolicus community, will decrease, and the internal ecological function of the sub_dominance landscape is not quite affected, it is helpful to biodiversity and sub_dominance landscape succession. However, there is a linear relationship between the isolation of heavy influencing areas and the resulting patches, the obstacle for species to move from one patch to another in heavy influencing areas is obvious. Therefore, we should place more emphases on environmental conservation in coal mining area. On this basis, it is feasible to guide vegetation succession along the  direction of Bothrichloa ischaemum_Thymus mongolicuscommunity-Bothrichl oaischaemum_Themeda japonica community-bush-broad_leaved forest.
Keywords:Ground subsidence  RS  GIS  Landscape  Largest patch index  Landscape shape index  Patch cohesion index
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