Putting space into trait ecology: Trait, environment and biodiversity relationships at multiple spatial scales

特质 生物多样性 生态学 种内竞争 生物 种间竞争 空间生态学 空间分析 空间变异性 地理 统计 数学 遥感 计算机科学 程序设计语言
作者
Shekhar R. Biswas,Dong He,Jialin Li,Li Gong,Prity L. Biswas,Ziqing Zhuo,Mingshan Xu,Xiaodong Yang,En‐Rong Yan
出处
期刊:Journal of Ecology [Wiley]
卷期号:112 (3): 613-628 被引量:4
标识
DOI:10.1111/1365-2745.14257
摘要

Abstract Ecological processes such as environmental filtering and biotic interactions that shape species' traits and community diversity often vary with geographic distance, potentially generating spatial structures in trait variation, covariation and biodiversity data. Understanding spatial structures of trait, environment and biodiversity, or the spatial link between those factors, is fundamental to identifying spatially explicit assembly processes or biodiversity distributions in spatially heterogeneous landscapes but remains unclear. To address the issue, we gathered individual‐level leaf and diameter traits data paired with environmental data from a 4.8 ha subtropical Chinese forest and divided the forest into 25, 100, 400 and 1936 m 2 grids representing contrasting spatial grains. Using Moran's correlograms, we quantified the spatial structures of trait variation and covariation, environmental conditions and biodiversity. We assessed the links between those variables using path analyses. Most variables were spatially positively autocorrelated. However, trait mean was more autocorrelated than trait variation or covariation, and intraspecific trait variation was more autocorrelated than interspecific variation. Autocorrelations in those community properties were generally weak at the large grain. Path analyses indicated positive associations between interspecific trait variation and species diversity at a very small to medium scale and a positive association between intraspecific variation and small‐scale functional diversity. Trait covariation constrained biodiversity, and multi‐trait means were negatively linked to very small‐ to medium‐scale species diversity but positively to medium‐ and large‐scale functional diversity. Patterns regarding multi‐trait community structure–environment–biodiversity associations were generally held for individual traits. However, depending on the trait, spatial scale and plant ontogenic stage, the pattern's strength changed, or occasionally, their sign reversed. We attribute spatial patterns in multi‐trait mean and covariation to scale‐dependent variation in environmental heterogeneity and trait variation to scale‐dependent competition. Synthesis . Our study provides novel insights into spatial and scale‐dependent variability in functional community structure, environment and biodiversity, and their relationships. Our results demonstrate the usefulness of spatial trait analyses in identifying scale‐dependent assembly processes or finding the importance of processes to biodiversity distributions in spatially heterogeneous landscapes. A spatially explicit perspective is thus helpful for the progress of trait ecology.

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
慕青应助ZZB采纳,获得10
1秒前
1秒前
1秒前
汉堡大王发布了新的文献求助10
1秒前
大模型应助李李李李李采纳,获得10
1秒前
2秒前
科研同人发布了新的文献求助10
2秒前
无辜的夏兰完成签到,获得积分10
2秒前
2秒前
EMC应助SSY采纳,获得10
3秒前
正直凌文发布了新的文献求助10
3秒前
小样本完成签到,获得积分20
3秒前
TY完成签到,获得积分10
3秒前
3秒前
zxy发布了新的文献求助10
3秒前
是ok耶完成签到,获得积分10
4秒前
简单酒窝完成签到,获得积分20
4秒前
4秒前
Jasper应助悦耳的乐松采纳,获得10
4秒前
joey发布了新的文献求助10
4秒前
慕青应助刻苦念桃采纳,获得10
4秒前
xiaolin发布了新的文献求助10
5秒前
梧桐树完成签到,获得积分10
5秒前
Fen3i完成签到,获得积分10
5秒前
充电宝应助Kenny采纳,获得10
5秒前
5秒前
6秒前
wuzihao完成签到,获得积分10
6秒前
顾矜应助小文采纳,获得10
6秒前
勇者义彦完成签到,获得积分10
6秒前
6秒前
顶顶顶发布了新的文献求助10
6秒前
温婉的紫霜完成签到,获得积分10
7秒前
7秒前
7秒前
星辰大海应助脸像大饼采纳,获得10
7秒前
7秒前
xxxx发布了新的文献求助10
7秒前
7秒前
ai zs完成签到,获得积分10
7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
Kinesiophobia : a new view of chronic pain behavior 3000
Les Mantodea de guyane 2500
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 2000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Clinical Electromyography 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5946024
求助须知:如何正确求助?哪些是违规求助? 7102416
关于积分的说明 15902108
捐赠科研通 5078254
什么是DOI,文献DOI怎么找? 2730732
邀请新用户注册赠送积分活动 1690748
关于科研通互助平台的介绍 1614718