Arid
DOI10.1111/jvs.12686
Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions
Pollock, Laura J.1; Kelly, Luke T.2; Thomas, Freya M.3; Soe, Paing3,4; Morris, William K.3; White, Matt5; Vesk, Peter A.3
通讯作者Pollock, Laura J.
来源期刊JOURNAL OF VEGETATION SCIENCE
ISSN1100-9233
EISSN1654-1103
出版年2018
卷号29期号:6页码:967-977
英文摘要

Questions Relationships between species, their functional traits and environmental gradients can now be more fully understood with trait-based multi-species distribution models (trait-SDMs). However, general patterns are yet to emerge from founding studies using these models, which are mostly case studies at a single scale. Here, we address the generality of trait-environment relations by asking whether these relationships hold for different sampling schemes, environmental variables and species sets. Methods We focus on the drought and fire-resistant "mallee" eucalypts of a semi-arid region of southeast Australia, which are likely to face new climates and disturbance regimes under global change. We use hierarchical regression modelling to test how trait-environment relationships change for two data sets representing an extensively collected, multipurpose data set and an intensively collected data set stratified along environmental gradients. Results Three functional traits (specific leaf area, maximum height and seed mass) explained a substantial portion of the occurrence of species along soil, water and climatic gradients, with the relationship between seed mass and soil type robust across all tests. Other trait-environment relationships changed depending on study design and species set, with soil and substrate variables more important relative to climate (precipitation) for the intensively sampled survey. Remotely sensed variables were good surrogates for some field-based measures (soil type), but not others (land form: dune or swale). In particular, airborne soil radiometric data show promise as a spatially continuous substitute for soil texture. Conclusions Trait-SDMs are a powerful tool for quantifying ecological interactions, but generalizations will only be possible when sample design, scale and environmental variables are carefully considered. We show that important ecological relationships can be diluted or missed entirely in broad scale trait-environment studies that rely on remotely sensed climate variables alone. Relationships that are robust to differences in study design, growth form and ecosystem (e.g., heavier seeds on sandy soil) are the most likely to reveal general ecological processes.


英文关键词Australia Eucalyptus hierarchical multi-species model leaf-height-seed scheme mallee semi-arid ecosystem
类型Article
语种英语
国家France ; Australia ; Myanmar
收录类别SCI-E
WOS记录号WOS:000454200200002
WOS关键词SPECIES DISTRIBUTION MODELS ; GLOBAL PATTERNS ; CLIMATE-CHANGE ; VEGETATION ; CONSERVATION ; PREDICTION ; EUCALYPTS ; RESPONSES ; ECOLOGY ; SIZE
WOS类目Plant Sciences ; Ecology ; Forestry
WOS研究方向Plant Sciences ; Environmental Sciences & Ecology ; Forestry
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/211407
作者单位1.Univ Grenoble Alpes, CNRS, Lab Ecol Alpine LECA, Grenoble, France;
2.Univ Melbourne, Sch Ecosyst & Forest Sci, Melbourne, Vic, Australia;
3.Univ Melbourne, Sch BioSci, ARC Ctr Excellence Environm Decis, Melbourne, Vic, Australia;
4.World Wildlife Fund Myanmar, Dawei, Myanmar;
5.Arthur Rylah Inst Environm Res, Dept Environm Land Water & Planning, Heidelberg, Vic, Australia
推荐引用方式
GB/T 7714
Pollock, Laura J.,Kelly, Luke T.,Thomas, Freya M.,et al. Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions[J],2018,29(6):967-977.
APA Pollock, Laura J..,Kelly, Luke T..,Thomas, Freya M..,Soe, Paing.,Morris, William K..,...&Vesk, Peter A..(2018).Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions.JOURNAL OF VEGETATION SCIENCE,29(6),967-977.
MLA Pollock, Laura J.,et al."Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions".JOURNAL OF VEGETATION SCIENCE 29.6(2018):967-977.
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