Plant community feedbacks and long-term ecosystem responses to multi-factored global change

生态系统 全球变化 植物群落 期限(时间) 生态学 生物 种间竞争 群落结构 生产力 环境资源管理 气候变化 环境科学 生态演替 经济 物理 量子力学 宏观经济学
作者
J. Adam Langley,Bruce A. Hungate
出处
期刊:Aob Plants [Oxford University Press]
卷期号:6: plu035-plu035 被引量:47
标识
DOI:10.1093/aobpla/plu035
摘要

While short-term plant responses to global change are driven by physiological mechanisms, which are represented relatively well by models, long-term ecosystem responses to global change may be determined by shifts in plant community structure resulting from other ecological phenomena such as interspecific interactions, which are represented poorly by models. In single-factor scenarios, plant communities often adjust to increase ecosystem response to that factor. For instance, some early global change experiments showed that elevated CO2 favours plants that respond strongly to elevated CO2, generally amplifying the response of ecosystem productivity to elevated CO2, a positive community feedback. However, most ecosystems are subject to multiple drivers of change, which can complicate the community feedback effect in ways that are more difficult to generalize. Recent studies have shown that (i) shifts in plant community structure cannot be reliably predicted from short-term plant physiological response to global change and (ii) that the ecosystem response to multi-factored change is commonly less than the sum of its parts. Here, we survey results from long-term field manipulations to examine the role community shifts may play in explaining these common findings. We use a simple model to examine the potential importance of community shifts in governing ecosystem response. Empirical evidence and the model demonstrate that with multi-factored change, the ecosystem response depends on community feedbacks, and that the magnitude of ecosystem response will depend on the relationship between plant response to one factor and plant response to another factor. Tradeoffs in the ability of plants to respond positively to, or to tolerate, different global change drivers may underlie generalizable patterns of covariance in responses to different drivers of change across plant taxa. Mechanistic understanding of these patterns will help predict the community feedbacks that determine long-term ecosystem responses.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
avalanche发布了新的文献求助10
刚刚
科研通AI6.3应助twinkle采纳,获得10
刚刚
刚刚
SZY发布了新的文献求助10
1秒前
李爱国应助刻苦的断天采纳,获得10
1秒前
WEILAI完成签到,获得积分10
1秒前
高大的千秋完成签到,获得积分10
1秒前
命运的X号发布了新的文献求助10
1秒前
田様应助zyyin采纳,获得10
1秒前
海阔光明完成签到,获得积分10
3秒前
3秒前
安啦关注了科研通微信公众号
3秒前
yuliang发布了新的文献求助10
3秒前
3秒前
4秒前
小二郎应助JraInYIu采纳,获得10
4秒前
甜美静白发布了新的文献求助10
4秒前
英姑应助Wing采纳,获得10
5秒前
gdj发布了新的文献求助30
6秒前
6秒前
核桃发布了新的文献求助10
6秒前
yuuta完成签到,获得积分10
6秒前
Jasmine完成签到 ,获得积分10
7秒前
7秒前
Ava应助老迟到的馒头采纳,获得10
7秒前
NexusExplorer应助阿谭采纳,获得10
8秒前
8秒前
小七完成签到,获得积分10
8秒前
丘比特应助子忧采纳,获得10
8秒前
9秒前
打打应助佛山婆婆采纳,获得10
9秒前
333发布了新的文献求助10
9秒前
9秒前
标致的雅香完成签到,获得积分10
9秒前
苗硕恒发布了新的文献求助10
9秒前
JamesPei应助老迟到的馒头采纳,获得10
9秒前
tjlovef完成签到 ,获得积分0
10秒前
Bill发布了新的文献求助10
10秒前
10秒前
10秒前
高分求助中
Cronologia da história de Macau 5000
Matrix Methods in Data Mining and Pattern Recognition 510
C语言程序设计(微课版) 500
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Forensic Science An Introduction to Scientific and Investigative Techniques 6th Edition 400
Reaction of 3-Methylenedihydro-(3H)furan-2-one with Diazoalkanes. Syntheses and Crystal Structures of Spiranic Cyclopropyl Compounds 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7094605
求助须知:如何正确求助?哪些是违规求助? 8751265
关于积分的说明 18509553
捐赠科研通 6647411
什么是DOI,文献DOI怎么找? 3137289
关于科研通互助平台的介绍 2245250
邀请新用户注册赠送积分活动 2112028