Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1002/ecs2.2145 |
Plant community change in three Mongolian steppe ecosystems 1994-2013: applications to state-and-transition models | |
Jamiyansharav, Khishigbayar1; Fernandez-Gimenez, Maria E.1; Angerer, Jay P.2; Yadamsuren, Baasandorj3; Dash, Zumberelmaa4 | |
通讯作者 | Jamiyansharav, Khishigbayar |
来源期刊 | ECOSPHERE
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ISSN | 2150-8925 |
出版年 | 2018 |
卷号 | 9期号:3 |
英文摘要 | Interacting effects of climate change and livestock grazing on semi-arid grassland ecosystems have not been well studied, especially on a long-term basis. This paper analyzes changes in plant community composition in relation to grazing intensity and climate change based on repeated monitoring along long-term grazing intensity gradients in three Mongolian ecological zones over 20 yr. We synthesized our findings into state-and-transition models of vegetation change, contributing to our understanding of ecological dynamics in relation to management and environmental change, and to the development of tools for resilience-based rangeland management. In the mountain steppe (MS), community composition was driven largely by climate, and transitions from one community to another were associated with climate change or combined climate and grazing effects. The MS experienced the largest number of long-term transitions (14 of 15 plots) over 20 yr. In the steppe (ST), grazing intensity was the strongest influence on community composition, but transitions between communities from the early 1990s to 2013 were most strongly correlated with climate change. Ten of the 15 ST plots transitioned to other communities over 20 yr. Community composition in the desert steppe (DS) was unrelated to either grazing intensity or climate change and only six of 15 plots transitioned permanently over 20 yr. The MS appears most vulnerable to climate-induced community change, as others have suggested. Some degraded ST communities are resilient to climate change, while ST communities on drier sites are vulnerable to grazing-induced community changes. Our findings illustrate the utility of state-and-transition models as a means to synthesize and depict plant community dynamics in relation to climate and management factors. These models identify communities that may be growing rarer or more common under the combined effects of climate change and grazing, and highlight species and communities that may be useful conservation targets or indicators of climate- or grazing-induced change. |
英文关键词 | classification classification and regression tree climate change livestock grazing Mongolia ordination rangeland resilience-based management semi-arid grassland |
类型 | Article |
语种 | 英语 |
国家 | USA ; Mongolia |
收录类别 | SCI-E |
WOS记录号 | WOS:000428071900019 |
WOS关键词 | CLIMATE-CHANGE ; INNER-MONGOLIA ; WATER SOURCES ; VEGETATION ; GRADIENTS ; THRESHOLDS ; GRASSLAND ; RANGELANDS ; PRECIPITATION ; COLONIZATION |
WOS类目 | Ecology |
WOS研究方向 | Environmental Sciences & Ecology |
来源机构 | Colorado State University |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/208836 |
作者单位 | 1.Colorado State Univ, Warner Coll Nat Resources, Ft Collins, CO 80523 USA; 2.Texas A&M Agrilife Res, Blackland Res & Extens Ctr, Temple, TX 76502 USA; 3.Mongolian Acad Sci, Inst Geog & Geoecol, POB 81, Ulaanbaatar 211238, Mongolia; 4.Mongolian Acad Sci, Inst Bot, Amariin Gudamj 1, Ulaanbaatar 210620, Mongolia |
推荐引用方式 GB/T 7714 | Jamiyansharav, Khishigbayar,Fernandez-Gimenez, Maria E.,Angerer, Jay P.,et al. Plant community change in three Mongolian steppe ecosystems 1994-2013: applications to state-and-transition models[J]. Colorado State University,2018,9(3). |
APA | Jamiyansharav, Khishigbayar,Fernandez-Gimenez, Maria E.,Angerer, Jay P.,Yadamsuren, Baasandorj,&Dash, Zumberelmaa.(2018).Plant community change in three Mongolian steppe ecosystems 1994-2013: applications to state-and-transition models.ECOSPHERE,9(3). |
MLA | Jamiyansharav, Khishigbayar,et al."Plant community change in three Mongolian steppe ecosystems 1994-2013: applications to state-and-transition models".ECOSPHERE 9.3(2018). |
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