Accurate forest projections require long‐term wood decay experiments because plant trait effects change through time

气候变化 生态学 天蓬
作者
Brad Oberle,Marissa R. Lee,Jonathan Myers,Oyomoare L. Osazuwa-Peters,Marko J. Spasojevic,Maranda L. Walton,Darcy F. Young,Amy E. Zanne
出处
期刊:Global Change Biology [Wiley]
卷期号:26 (2): 864-875 被引量:18
标识
DOI:10.1111/gcb.14873
摘要

Whether global change will drive changing forests from net carbon (C) sinks to sources relates to how quickly deadwood decomposes. Because complete wood mineralization takes years, most experiments focus on how traits, environments and decomposer communities interact as wood decay begins. Few experiments last long enough to test whether drivers change with decay rates through time, with unknown consequences for scaling short-term results up to long-term forest ecosystem projections. Using a 7 year experiment that captured complete mineralization among 21 temperate tree species, we demonstrate that trait effects fade with advancing decay. However, wood density and vessel diameter, which may influence permeability, control how decay rates change through time. Denser wood loses mass more slowly at first but more quickly with advancing decay, which resolves ambiguity about the after-life consequences of this key plant functional trait by demonstrating that its effect on decay depends on experiment duration and sampling frequency. Only long-term data and a time-varying model yielded accurate predictions of both mass loss in a concurrent experiment and naturally recruited deadwood structure in a 32-year-old forest plot. Given the importance of forests in the carbon cycle, and the pivotal role for wood decay, accurate ecosystem projections are critical and they require experiments that go beyond enumerating potential mechanisms by identifying the temporal scale for their effects.

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
cc发布了新的文献求助10
1秒前
2秒前
深情安青的应助被Dlx采纳,获得10
2秒前
甩看文献发布了新的文献求助10
2秒前
yuansongqian发布了新的文献求助10
3秒前
田様的应助被超帅的剑成采纳,获得10
4秒前
Zhu发布了新的文献求助10
4秒前
5秒前
Rui_Rui的应助被wyl采纳,获得10
5秒前
vanilla发布了新的文献求助50
6秒前
6秒前
吴兰田完成签到,获得积分10
6秒前
聪明火车完成签到,获得积分10
7秒前
科研通AI6.4的应助被Ric采纳,获得10
8秒前
隐形曼青的应助被lzy采纳,获得10
10秒前
尊敬的寄柔完成签到,获得积分10
10秒前
rrrrrr发布了新的文献求助10
10秒前
灵巧的豁完成签到 ,获得积分10
10秒前
phymatstone完成签到,获得积分10
11秒前
Mia717完成签到,获得积分10
11秒前
12秒前
SciGPT的应助被科研小白采纳,获得10
12秒前
赘婿的应助被着急帅采纳,获得10
13秒前
13秒前
14秒前
取名字好难完成签到,获得积分10
15秒前
15秒前
友好的绮晴完成签到,获得积分10
15秒前
16秒前
闪闪的硬币完成签到 ,获得积分10
16秒前
脑洞疼的应助被dengdengdeng采纳,获得10
16秒前
科研通AI6.2的应助被lv采纳,获得10
16秒前
16秒前
17秒前
等待的代容完成签到,获得积分0
17秒前
侯敬远完成签到 ,获得积分10
18秒前
科研通AI6.4的应助被vanilla采纳,获得10
18秒前
18秒前
20秒前
无比璀璨的番茄完成签到,获得积分10
20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
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Les Mots du discours 600
A Consideration on Use of Material Grades for Hull Structural Members Based on Fracture Toughness(Second Report) 500
AI Disclosure in Annual Reports: Evolution, Determinants, and Capital Market Participants’ Perceptions 500
5th World Conference on Detergents: Reinventing the Industry : Opportunities and Challenges 500
Erzählte Gnade 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8110272
求助须知:如何正确求助?哪些是违规求助? 9517616
关于积分的说明 21514099
捐赠科研通 7687497
什么是DOI,文献DOI怎么找? 3411542
关于科研通互助平台的介绍 2538663
邀请新用户注册赠送积分活动 2451463