集合(抽象数据类型)
水运
数据集
生物
环境科学
计量经济学
化学
计算机科学
经济
数学
土壤科学
统计
程序设计语言
水流
作者
Xiaoli Fu,Frederick C. Meinzer
出处
期刊:Tree Physiology
[Oxford University Press]
日期:2018-07-26
卷期号:39 (1): 122-134
被引量:146
标识
DOI:10.1093/treephys/tpy087
摘要
Plants operate along a continuum of stringency of regulation of plant water potential from isohydry to anisohydry. However, most metrics and proxies of plant iso/anisohydric behavior have been developed from limited sets of site-specific experiments. Understanding the underlying mechanisms that determine species' operating ranges along this continuum, independent of site and growing conditions, remains challenging. We compiled a global database to assess the global patterns of metrics and proxies of plant iso/anisohydry and then explored some of the underlying functional traits and trade-offs associated with stringency of regulation that determines where species operate along the continuum. Our results showed that arid and semi-arid biomes were associated with greater anisohydry than more mesic biomes, and angiosperms showed marginally greater anisohydry than gymnosperms. Leaf water potential at the turgor loss point (Ψtlp) and wood density were the two most powerful proxies for ranking the degree of plant iso/anisohydry for a wide range of species and biomes. Both of these simple traits can be easily and rapidly determined, and therefore show promise for a priori mapping and understanding of the global distribution pattern of the degree of plant iso/anisohydry. Generally, the most anisohydric species had the most negative values of Ψtlp and highest wood density, greatest resistance to embolism, lowest hydraulic capacitance and lowest leaf-specific hydraulic conductivity of their branches. Wood density in particular appeared to be central to a coordinated series of traits, trade-offs and behaviors along a continuum of iso/anisohydry. Quantification of species' operating ranges along a continuum of iso/anisohydry and identification of associated trade-offs among functional traits may hold promise for mechanistic modeling of species-specific responses to the anticipated more frequent and severe droughts under global climate change scenarios.
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