Data from: Interacting effects of unobserved heterogeneity and individual stochasticity in the life-history of the Southern fulmar

1.Individuals are heterogeneous in many ways. Some of these differences are incorporated as individual states (e.g., age, size, breeding status) in population models. However, substantial amounts of heterogeneity may remain unaccounted for, due to unmeasurable genetic, maternal, or environmental factors.

2.Such unobserved heterogeneity (UH) affects the behavior of heterogeneous cohorts via intra-cohort selection and contributes to inter-individual variance in demographic outcomes such as longevity and lifetime reproduction. Variance is also produced by individual stochasticity, due to random events in the life cycle of wild organisms, yet no study thus far has attempted to decompose the variance in demographic outcomes into contributions from unobserved heterogeneity and individual stochasticity for an animal population in the wild.

3.We developed a stage-classified matrix population model for the Southern fulmar breeding on Ile des Pétrels, Antarctica. We applied multi-event, multi-state markrecapture methods to estimate a finite mixture model accounting for UH in all vital rates and Markov chain methods to calculate demographic outcomes. Finally, we partitioned the variance in demographic outcomes into contributions from unobserved heterogeneity and individual stochasticity.

4.We identify three UH groups, differing substantially in longevity, lifetime reproductive output, age at first reproduction, and in the proportion of the life spent in each reproductive state.

14% of individuals at fledging have a delayed but high probability of recruitment and extended reproductive lifespan.

67% of individuals are less likely to reach adulthood, recruit late and skip breeding often but have the highest adult survival rate.

19% of individuals recruit early and attempt to breed often. They are likely to raise their offspring successfully, but experience a relatively short lifespan.

Unobserved heterogeneity only explains a small fraction of the variances in longevity (5.9%), age at first reproduction (3.7%) and lifetime reproduction (22%).

5.UH can affect the entire life cycle, including survival, development, and reproductive rates, with consequences over the lifetime of individuals and impacts on cohort dynamics. The respective role of unobserved heterogeneity versus individual stochasticity varies greatly among demographic outcomes. We discuss the implication of our finding for the gradient of life-history strategies observed among species and argue that individual differences should always be accounted for in demographic studies of wild populations.

1. 种群内个体存在多维度异质性。部分个体差异会被作为个体状态参数纳入种群模型，例如年龄、体型与繁殖状态等。然而，由于无法测量的遗传、母体效应或环境因素，仍有大量异质性未被纳入考量。
2. 这类未观测异质性（Unobserved Heterogeneity, UH）会通过群内选择影响异质性种群群的动态，并导致个体间在寿命、终生繁殖产出等种群统计特征上的方差差异。此外，野生生物生命周期中的随机事件也会通过个体随机性产生方差，但迄今为止尚无研究尝试将野生动物种群的种群统计特征方差分解为未观测异质性与个体随机性的贡献份额。
3. 我们针对南极洲佩特雷尔岛（Ile des Pétrels）上繁殖的南方暴风鹱（Southern fulmar）构建了阶段分类矩阵种群模型（stage-classified matrix population model）。我们采用多事件多状态标记重捕法（multi-event, multi-state mark-recapture methods）估计了涵盖所有生命率未观测异质性的有限混合模型（finite mixture model），并通过马尔可夫链（Markov chain）方法计算种群统计特征。最终，我们将种群统计特征的方差分解为未观测异质性与个体随机性的贡献分量。
4. 我们识别出三类未观测异质性群，它们在寿命、终生繁殖产出、首次繁殖年龄以及各繁殖状态下的生命占比上均存在显著差异。
离巢个体中有14%存在繁殖补充延迟但概率较高的情况，且繁殖寿命更长。
67%的个体较难达到成体阶段，繁殖补充较晚且常跳过繁殖，但拥有最高的成体存活率。
19%的个体较早完成繁殖补充并频繁尝试繁殖，它们成功抚育后代的概率较高，但寿命相对较短。
未观测异质性仅能解释寿命（5.9%）、首次繁殖年龄（3.7%）与终生繁殖产出（22%）的小部分方差。
5. 未观测异质性会影响整个生命周期，包括存活率、发育速率与繁殖速率，进而对个体终生存活与种群群动态产生影响。未观测异质性与个体随机性各自的作用在不同种群统计特征中差异巨大。我们讨论了本研究发现对于不同物种间观测到的生活史策略梯度的意义，并提出在野生种群的种群统计研究中，个体差异始终应当被纳入考量范畴。