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鸟类出生扩散距离的生态形态学预测因素

Ecomorphological predictors of natal dispersal distances in birds.

作者信息

Dawideit Britta A, Phillimore Albert B, Laube Irina, Leisler Bernd, Böhning-Gaese Katrin

机构信息

Institut für Zoologie, Abteilung V, Johannes Gutenberg-Universität, Mainz, Mainz, Germany.

出版信息

J Anim Ecol. 2009 Mar;78(2):388-95. doi: 10.1111/j.1365-2656.2008.01504.x. Epub 2008 Nov 24.

Abstract
  1. Dispersal is one of the key ecological parameters but it is very difficult to quantify directly. As a consequence, empirical studies often ignore dispersal or use indirect measures. 2. Ringing data have previously been used to estimate the natal dispersal distances of 47 British passerine bird species. This provides an excellent opportunity to examine the potential of various indirect measures to predict natal dispersal distances in British birds. 3. We use a phylogenetic comparative framework and single- and multipredictor models including ecomorphological, behavioural or ecological traits to predict natal dispersal distance. 4. A multipredictor model that includes Kipp's distance (a measure of wing tip length), bill depth and tail graduation explains 45% of the interspecific variation in natal dispersal distance. These morphological characters all relate to aerodynamics with stronger flyers dispersing further. 5. However, an index of migration is a strong (but less informative) correlate of dispersal distance and Kipp's distance and bill depth are strong correlates of migration. Thus, we cannot disentangle whether these ecomorphological traits influence dispersal distance directly or whether the relationship between ecomorphology and dispersal is mediated through migratory behaviour. 6. Notwithstanding uncertainties regarding the causal links between dispersal distance and wing morphology, we suggest that two ecomorphological traits, Kipp's distance and bill depth, may provide a useful surrogate.
摘要
  1. 扩散是关键的生态参数之一,但直接量化非常困难。因此,实证研究常常忽略扩散或采用间接测量方法。2. 环志数据此前已被用于估算47种英国雀形目鸟类的出生地扩散距离。这为检验各种间接测量方法预测英国鸟类出生地扩散距离的潜力提供了绝佳机会。3. 我们使用系统发育比较框架以及包括生态形态学、行为或生态特征的单预测变量和多预测变量模型来预测出生地扩散距离。4. 一个包含基普氏距离(一种翼尖长度的测量方法)、喙深度和尾羽渐变的多预测变量模型解释了种间出生地扩散距离变化的45%。这些形态特征均与空气动力学相关,飞行能力更强的鸟类扩散得更远。5. 然而,迁徙指数是扩散距离的一个强相关因素(但信息较少),基普氏距离和喙深度是迁徙的强相关因素。因此,我们无法厘清这些生态形态特征是直接影响扩散距离,还是生态形态与扩散之间的关系是通过迁徙行为介导的。6. 尽管扩散距离与翼形态之间的因果联系存在不确定性,但我们认为基普氏距离和喙深度这两个生态形态特征可能提供一个有用的替代指标。

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