已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Root functional traits are important predictors for plant resource acquisition strategies in subtropical forests

生物 植物生态学 营养物 比叶面积 亚热带 下层林 桉树 草本植物 植物 农学 生态学 光合作用 天蓬 医学 传统医学 草药
作者
Guangcan Yu,Yufang Wang,Andi Li,Senhao Wang,Jing Chen,Jiangming Mo,Mianhai Zheng
出处
期刊:Ecological Applications [Wiley]
卷期号:35 (1): e3082-e3082 被引量:8
标识
DOI:10.1002/eap.3082
摘要

Abstract Intercorrelated aboveground traits associated with costs and plant growth have been widely used to predict vegetation in response to environmental changes. However, whether underground traits exhibit consistent responses remains unclear, particularly in N‐rich subtropical forests. Responses of foliar and root morphological and physiological traits of tree and herb species after 8‐year N, P, and combined N and P treatments (50 kg N, P, N and P ha −1 year −1 ) were examined in leguminous Acacia auriculiformis ( AA ) and nonleguminous Eucalyptus urophylla ( EU ) forests in southern China. N addition did not significantly impact all leaf and root traits except root N concentration per root length. Root traits responded to P addition more than leaf traits in trees; however, both traits responded similarly to P addition in herbs. Tree species deviated from the expected leaf economics spectrum; however, all species aligned with the root economics spectrum. The P and combined N and P treatments significantly altered the position of principal components analysis of root functional traits for herb species compared to the control. However, these changes did not reflect a classic shift in nutrient acquisition strategy within the root economics spectrum. As leguminous species experienced greater P limitation, AA responded more to P addition than EU ; their understories indicated no significant differences. This study reveals how plant aboveground and underground traits adapt to nutrient‐rich environments. These findings highlight the importance of incorporating plant underground traits, which show significant and specific responses to nutrient additions, into Earth system models for accurately predicting plant responses to global change.
最长约 10秒,即可获得该文献文件

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
精神是块骨头完成签到,获得积分10
1秒前
欣宇发布了新的文献求助10
2秒前
2秒前
研友_ndDjBn发布了新的文献求助20
3秒前
11发布了新的文献求助10
3秒前
4秒前
5秒前
5秒前
LJ发布了新的文献求助10
6秒前
ChenJc发布了新的文献求助20
6秒前
7秒前
hhhjy发布了新的文献求助10
7秒前
8秒前
木子完成签到,获得积分10
9秒前
9秒前
ZMF发布了新的文献求助10
9秒前
27完成签到,获得积分10
10秒前
杨德帅发布了新的文献求助10
10秒前
自觉的星星完成签到,获得积分20
11秒前
壮观复天完成签到 ,获得积分10
11秒前
13秒前
14秒前
whoknowsname发布了新的文献求助10
15秒前
科研通AI6.2应助CapO采纳,获得10
16秒前
小马甲应助科研通管家采纳,获得10
17秒前
XX应助科研通管家采纳,获得10
17秒前
思源应助科研通管家采纳,获得10
17秒前
YIYI应助科研通管家采纳,获得10
17秒前
17秒前
XX应助科研通管家采纳,获得10
17秒前
XX应助科研通管家采纳,获得10
18秒前
Nole应助科研通管家采纳,获得10
18秒前
18秒前
杨德帅发布了新的文献求助10
18秒前
20秒前
20秒前
结实大白完成签到,获得积分10
21秒前
852应助LJ采纳,获得10
21秒前
cyy关闭了cyy文献求助
21秒前
24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
Rosenblum, Global Change Biology 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Physiologic specialization in Peronospora manshurica 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 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7777672
求助须知:如何正确求助?哪些是违规求助? 9318513
关于积分的说明 20364691
捐赠科研通 7364587
什么是DOI,文献DOI怎么找? 3318990
关于科研通互助平台的介绍 2466628
邀请新用户注册赠送积分活动 2334211