Measuring individual-level resource specialization
Measuring individual-level resource specialization
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DOI：
10.2307/3072028
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发表时间：
2002-10-01
期刊：
影响因子：
4.8
通讯作者：
Svanbäck, R
中科院分区：
文献类型：
--
作者：
Bolnick, DI;Yang, LH;Svanbäck, R
许多表面上泛化的物种实际上是由个别专家组成的，他们使用种群资源分布的一小部分。生态位变异通常是通过检验个体从共同的资源分布中获得的零假设来建立的。这种方法鼓励了一种发表偏见，其中负面结果很少被报道，并掩盖了个体专业化程度的差异，限制了我们对利基差异的原因或结果进行比较研究的能力。为了便于对个体专业化程度的研究，本文概述了资源利用的种群内变异的四个量化指标。传统上，这种差异是通过将种群的总生态位宽度划分为个体内和个体之间、性别或表型成分来衡量的。我们提出了两种量化个体与其群体之间平均资源重叠的方法，并讨论了这四种方法的优缺点。所有指数的效用取决于经验数据的质量。如果以粗粒度的方式衡量资源，个人可能会错误地显得泛化。或者，专业化可能被横断面抽样方案高估了，在横断面抽样方案中，饮食变化可以反映一个零散的环境。同位素比率、寄生虫或饮食形态相关性可以补充横断面数据，以建立个体专门化的时间一致性。
Many apparently generalized species are in fact composed of individual specialists that use a small subset of the population's resource distribution. Niche variation is usually established by testing the null hypothesis that individuals draw from a common resource distribution. This approach encourages a publication bias in which negative results are rarely reported, and obscures variation in the degree of individual specialization, limiting our ability to carry out comparative studies of the causes or consequences of niche variation. To facilitate studies of the degree of individual specialization, this paper outlines four quantitative indices of intrapopulation variation in resource use. Traditionally, such variation has been measured by partitioning the population's total niche width into within- and between-individual, sex, or phenotype components. We suggest two alternative measures that quantify the mean resource overlap between an individual and its population, and we discuss the advantages and disadvantages of all four measures. The utility of all indices depends on the quality of the empirical data. If resources are measured in a coarse-grained manner, individuals may falsely appear generalized. Alternatively, specialization may be overestimated by cross-sectional sampling schemes where diet variation can reflect a patchy environment. Isotope ratios, parasites, or diet-morphology correlations can complement cross-sectional data to establish temporal consistency of individual specialization.