Functional traits explain variation in plant life history strategies
Functional traits explain variation in plant life history strategies
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DOI：
10.1073/pnas.1315179111
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发表时间：
2014-01-14
影响因子：
11.1
通讯作者：
Franco, Miguel
中科院分区：
文献类型：
--
作者：
Adler, Peter B.;Salguero-Gomez, Roberto;Franco, Miguel
生态学家寻求对物种丰度在空间和时间上的巨大变化的一般解释。一个越来越流行的解决方案是预测物种的分布，动态，并根据容易测量的解剖和形态特征对环境变化的反应。基于性状的方法假设简单的功能性状影响适应性和生活史进化，但缺乏对这一假设的严格检验，因为它们需要代表不同生活史的许多物种的完整生命周期的定量信息。在这里，我们将全球性状数据库与222个物种的经验矩阵种群模型联系起来，并报告了功能性状与植物生活史之间的密切关系。具有大种子、长寿叶或茂密木材的物种具有缓慢的生活史，具有平均适合度（即，种群增长率）更强烈的影响生存比生长或繁殖力，与快速生活史物种与小种子，短寿命的叶子，或软木。与基于整个生命周期的人口对健身的贡献的测量相反，专注于原始人口比率的分析可能会低估性状和平均健身之间的关联强度。我们的研究结果有助于建立植物生活史进化的生理基础，并显示了基于性状的方法在种群动态中的潜力。
Ecologists seek general explanations for the dramatic variation in species abundances in space and time. An increasingly popular solution is to predict species distributions, dynamics, and responses to environmental change based on easily measured anatomical and morphological traits. Trait-based approaches assume that simple functional traits influence fitness and life history evolution, but rigorous tests of this assumption are lacking, because they require quantitative information about the full lifecycles of many species representing different life histories. Here, we link a global traits database with empirical matrix population models for 222 species and report strong relationships between functional traits and plant life histories. Species with large seeds, long-lived leaves, or dense wood have slow life histories, with mean fitness (i.e., population growth rates) more strongly influenced by survival than by growth or fecundity, compared with fast life history species with small seeds, short-lived leaves, or soft wood. In contrast to measures of demographic contributions to fitness based on whole lifecycles, analyses focused on raw demographic rates may underestimate the strength of association between traits and mean fitness. Our results help establish the physiological basis for plant life history evolution and show the potential for trait-based approaches in population dynamics.