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
刚刚
刚刚
刚刚
科研通AI6.1应助毛毛采纳,获得10
1秒前
追寻紫安发布了新的文献求助10
1秒前
泡泡完成签到 ,获得积分10
1秒前
2秒前
完美世界应助Bellis采纳,获得10
2秒前
李健应助mask采纳,获得10
2秒前
2秒前
ran完成签到 ,获得积分10
3秒前
3秒前
3秒前
bkagyin应助科研小达人采纳,获得10
3秒前
斯文败类应助企鹅采纳,获得10
4秒前
独特友安发布了新的文献求助10
4秒前
huyuan发布了新的文献求助10
5秒前
6秒前
HZZ发布了新的文献求助10
6秒前
6秒前
7秒前
GentleFade发布了新的文献求助10
7秒前
上官若男应助狂野书易采纳,获得30
7秒前
8秒前
CHOSENONE发布了新的文献求助10
8秒前
8秒前
chess完成签到,获得积分10
9秒前
kiki完成签到,获得积分10
10秒前
传奇3应助Jane采纳,获得10
10秒前
桐桐应助稳重一鸣采纳,获得10
10秒前
www完成签到,获得积分10
10秒前
11秒前
斯文败类应助淡淡的从雪采纳,获得10
11秒前
11秒前
张诗远完成签到,获得积分10
11秒前
11秒前
11秒前
11秒前
LI完成签到,获得积分20
12秒前
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Social Work and Social Welfare: An Invitation(7th Edition) 410
Medical Management of Pregnancy Complicated by Diabetes 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6056497
求助须知:如何正确求助?哪些是违规求助? 7889341
关于积分的说明 16290831
捐赠科研通 5201903
什么是DOI,文献DOI怎么找? 2783326
邀请新用户注册赠送积分活动 1766075
关于科研通互助平台的介绍 1646904