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Reproductive individuality of clonal fish raised in identical environments and its link to early-life behavioral individuality

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DataCite Commons2023-10-07 更新2024-08-18 收录
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https://figshare.com/articles/dataset/Reproductive_individuality_of_clonal_fish_raised_in_identical_environments_and_its_link_to_early-life_behavioral_individuality/23971599
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资源简介:
Genetic and environmental differences are by far the most studied drivers underlying phenotypic variation. However, a growing number of studies finds among-individual variation that is unexplained by genetic or apparent environmental differences. Up to now, it remains an open question whether such seemingly stochastic variation has fitness consequences. To address this question, we performed a tightly controlled long-term life-history experiment with naturally clonal fish (Poecilia formosa) separated directly after birth into near-identical environments. Maintaining highly standardized conditions for 280 days, we first recorded individuals for 10 hours per day over the first 28 days of their lives, characterizing early-life behavioral profiles (activity and feeding behavior). We then measured the complete reproductive profiles of these individuals over an average of 4.5 successive broods per individual, quantifying in total 2522 offspring from 152 broods. Standard lengths of focal individuals were measured once a week. We estimated the growth coefficient (K), maximum predicted (i.e., asymptotic) size (Linf), and predicted size at parturition for each focal individual by fitting individual von Bertalanffy growth curves.

迄今为止,遗传与环境差异是表型变异(phenotypic variation)背后被研究得最为深入的驱动因素。然而,越来越多的研究发现,个体间存在无法由遗传差异或显性环境差异解释的变异。时至今日,这类看似随机的变异是否会对适合度(fitness)产生影响,仍是一个悬而未决的科学问题。为解答这一问题,我们以天然克隆鱼类亚马逊花鳉(Poecilia formosa)为实验对象,开展了严格受控的长期生活史实验:将幼鱼在出生后立即分离至近乎一致的养殖环境中。在维持高度标准化的实验条件长达280天的周期内,我们首先在幼鱼出生后的前28天内,每日对个体进行10小时的行为记录,以此刻画其早期生活史行为特征(包括活动与摄食行为)。随后,我们对这些个体连续多胎的完整繁殖特征进行了测量,平均每只个体记录了4.5胎,累计统计了来自152胎的2522尾后代。我们每周测量一次目标个体的标准体长,并通过拟合单条个体的冯·贝塔朗菲生长曲线(von Bertalanffy growth curves),估算了每只目标个体的生长系数(K)、理论最大(即渐近)体长(Linf)以及产仔时的预测体长。
提供机构:
figshare
创建时间:
2023-10-07
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