Harada Keita, Hayashi Naoki, Kagaya Katsushi
Seto Marine Biological Laboratory, Field Science, Education and Reseach Center, Kyoto University, Wakayama, Japan.
Simulation and Mining Division, NTT DATA Mathematical Systems Inc., Tokyo, Japan.
PeerJ. 2020 May 14;8:e9036. doi: 10.7717/peerj.9036. eCollection 2020.
'Animal personality' is considered to be developed through complex interactions of an individual with its surrounding environment. How can we quantify the 'personality' of an individual? Quantifying intra- and inter-individual variability of behavior, or individual behavioral type, appears to be a prerequisite in the study of animal personality. We propose a statistical method from a predictive point of view to measure the appropriateness of our assumption of 'individual' behavior in repeatedly measured behavioral data from several individuals. For a model case, we studied the sponge crab known to make and carry a 'cap' from a natural sponge for camouflage. Because a cap is most likely to be rebuilt and replaced repeatedly, we hypothesized that each individual crab would grow a unique behavioral type and it would be observed under an experimentally controlled environmental condition. To test the hypothesis, we conducted behavioral experiments and employed a new Bayesian model-based comparison method to examine whether crabs have individual behavioral types in the cap making behavior. Crabs were given behavioral choices by using artificial sponges of three different sizes. We modeled the choice of sponges, size of the trimmed part of a cap, size of the cavity of a cap, and the latency to produce a cap, as random variables in 26 models, including hierarchical models specifying the behavioral types. In addition, we calculated the marginal-level widely applicable information criterion (mWAIC) values for hierarchical models to evaluate and compared them with the non-hierarchical models from the predictive point of view. As a result, the crabs of less than about 9 cm in size were found to make caps from the sponges. The body size explained the behavioral variables namely, choice, trimmed cap characteristics, and cavity size, but not latency. Furthermore, we captured the behavioral type as a probabilistic distribution structure of the behavioral data by comparing WAIC. Our statistical approach is not limited to behavioral data but is also applicable to physiological or morphological data when examining whether some group structure exists behind fluctuating empirical data.
“动物个性”被认为是通过个体与其周围环境的复杂相互作用而形成的。我们如何量化个体的“个性”？量化个体内部和个体之间行为的变异性，即个体行为类型，似乎是动物个性研究的一个先决条件。我们从预测的角度提出一种统计方法，以衡量我们对来自多个个体的重复测量行为数据中“个体”行为假设的合理性。对于一个模型案例，我们研究了一种已知会用天然海绵制作并携带“帽子”用于伪装的寄居蟹。由于帽子很可能会被反复重建和更换，我们假设每只寄居蟹都会形成独特的行为类型，并且在实验控制的环境条件下可以观察到这种行为类型。为了验证这一假设，我们进行了行为实验，并采用了一种基于贝叶斯模型的新比较方法，来检验寄居蟹在制作帽子行为中是否具有个体行为类型。通过使用三种不同大小的人造海绵，为寄居蟹提供行为选择。我们将海绵的选择、帽子修剪部分的大小、帽子的腔体大小以及制作帽子的潜伏期建模为26个模型中的随机变量，包括指定行为类型的层次模型。此外，我们计算了层次模型的边际水平广泛适用信息准则（mWAIC）值，以便从预测的角度对其进行评估并与非层次模型进行比较。结果发现，体型小于约9厘米的寄居蟹会用海绵制作帽子。体型解释了行为变量，即选择、修剪后的帽子特征和腔体大小，但不能解释潜伏期。此外，通过比较WAIC，我们将行为类型捕获为行为数据的概率分布结构。我们的统计方法不仅限于行为数据，在检查波动的经验数据背后是否存在某种群体结构时，也适用于生理或形态数据。
