期刊
ACTA OECOLOGICA-INTERNATIONAL JOURNAL OF ECOLOGY
卷 35, 期 3, 页码 400-408出版社
ELSEVIER
DOI: 10.1016/j.actao.2009.01.010
关键词
Andropogon gerardii; Climate variability; Leaf gas exchange; RaMPs; Sensitivity; Sorghastrum nutans
类别
资金
- DOE-PER [DE-FG02-04ER63892]
- USDA NRI Managed Ecosystems Program
- Direct For Biological Sciences
- Division Of Environmental Biology [GRANTS:13874398, 0823341] Funding Source: National Science Foundation
Ecosystem responses to climate change will largely be driven by responses of the dominant species. However, if co-dominant species have traits that lead them to differential responses, then predicting how ecosystem structure and function will be altered is more challenging. We assessed differences in response to climate change factors for the two dominant C-4 grass species in tallgrass prairie, Andropogon gerardii and Sorghastrum nutans, by measuring changes in a suite of plant ecophysiological traits in response to experimentally elevated air temperatures and increased precipitation variability over two growing seasons. Maximum photosynthetic rates, stomatal conductance, water-use efficiency, chlorophyll fluorescence, and leaf water potential varied with leaf and canopy temperature as well as with volumetric soil water content (0-15 cm). Both species had similar responses to imposed changes in temperature and water availability, but when differences occurred. responses by A. gerardii were more closely linked with changes in air temperature whereas S. nutans was more sensitive to changes in water availability. Moreover, S. nutans was more responsive overall than A. gerardii to climate alterations. These results indicate both grass species are responsive to forecast changes in temperature and precipitation, but their differential sensitivity to temperature and water availability Suggest that future population and community structure may vary based on the magnitude and scope of an altered climate. (C) 2009 Elsevier Masson SAS. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据