Nicieza Alfredo G, Alvarez David
Unidad de Ecología, Departamento de Biología de Organismos y Sistemas, Universidad de Oviedo, 33006, Oviedo, Spain.
Oecologia. 2009 Feb;159(1):27-39. doi: 10.1007/s00442-008-1194-8. Epub 2008 Oct 31.
Compensatory growth (CG) is a key issue in work aiming at a full understanding of the adaptive significance of growth plasticity and its carryover effects on life-history. The number of studies addressing evolutionary explanations for CG has increased rapidly during the last few years, but there has not been a parallel gain in our understanding of the methodological difficulties associated with the analysis of CG. We point out two features of growth that can have serious consequences for detecting CG: (1) size dependence of growth rates, which causes nonlinearity of growth trajectories, and; (2) temporal overlapping of structural growth and replenishment of energy reserves after a period of famine. We show that the currently used methods can be prone to spurious detection of CG (Type I error) under conditions of nonlinear growth, and therefore lead to the accumulation of a significant amount of false "empirical support." True and simulated growth data provided consistent results suggesting that a substantial fraction of the existing evidence for CG may be spurious. A small curvature in the growth trajectory can lead to spurious "detection" of CG when control and manipulated trajectories are compared over the same time interval (the "simultaneous" approach). We present a novel, robust method (the "asynchronous" approach) based on the accurate selection of control trajectories and comparison of control and treatment growth rates at different times. This method enables a reliable test to be performed for compensation under asymptotic growth. While the general results of our simulations do not support the application of conventional methods to the general case of nonlinear growth trajectories under the simultaneous approach, simple methods may prove valid if the experimental design allows for asynchronous comparisons. We advocate an alternative approach to deal with "safe" detection of CG that overcomes the problems associated with the occurrence of nonlinear and asymptotic growth, and provide recommendations for improving CG study designs.
补偿性生长（CG）是旨在全面理解生长可塑性的适应性意义及其对生活史的遗留效应的研究中的一个关键问题。在过去几年中，探讨CG进化解释的研究数量迅速增加，但我们对与CG分析相关的方法学困难的理解并没有相应提高。我们指出了生长的两个特征，它们可能对检测CG产生严重影响：（1）生长速率的大小依赖性，这会导致生长轨迹的非线性；（2）在一段饥荒期后结构生长与能量储备补充的时间重叠。我们表明，在非线性生长条件下，目前使用的方法可能容易出现CG的虚假检测（I型错误），从而导致大量虚假“实证支持”的积累。真实和模拟的生长数据提供了一致的结果，表明现有CG证据的很大一部分可能是虚假的。当在相同时间间隔内比较对照和处理轨迹时（“同步”方法），生长轨迹中的小曲率可能导致CG的虚假“检测”。我们提出了一种基于准确选择对照轨迹并在不同时间比较对照和处理生长速率的新颖、稳健的方法（“异步”方法）。该方法能够在渐近生长下对补偿进行可靠测试。虽然我们模拟的一般结果不支持在同步方法下将传统方法应用于非线性生长轨迹的一般情况，但如果实验设计允许异步比较，简单方法可能被证明是有效的。我们提倡一种替代方法来处理CG的“安全”检测，该方法克服了与非线性和渐近生长出现相关的问题，并为改进CG研究设计提供了建议。
