Data from: Accurate estimates of age-at-maturity from the growth trajectories of fishes and other ectotherms

Age-at-maturity (AAM) is a key life history trait that provides insight into ecology, evolution, and population dynamics. However, maturity data can be costly to collect or may not be available. Life history theory suggests that growth is biphasic for many organisms, with a change-point in growth occurring at maturity. If so, then it should be possible to use a biphasic growth model to estimate AAM from growth data. To test this prediction, we used the Lester biphasic growth model in a likelihood profiling framework to estimate AAM from length-at-age data. We fit our model to simulated growth trajectories to determine minimum data requirements (in terms of sample size, precision in length-at-age, and the cost to somatic growth of maturity) for accurate AAM estimates. We then applied our method to a large walleye Sander vitreus data set and show that our AAM estimates are in close agreement with conventional estimates when our model fits well. Finally, we highlight the potential of our method by applying it to length-at-age data for a variety of ectotherms. Our method shows promise as a tool for estimating AAM and other life history traits from contemporary and historical samples.

成熟年龄（Age-at-maturity，以下简称AAM）是一项关键的生活史性状，可为生态学、进化生物学及种群动态研究提供重要见解。然而，成熟度数据的采集成本高昂，或根本无法获取。生活史理论指出，多数生物的生长呈现双相模式，在成熟阶段出现生长拐点。若此假设成立，则可借助双相生长模型从生长数据中估算AAM。为验证这一预测，我们采用基于似然剖面框架的莱斯特双相生长模型，从年龄体长数据中估算AAM。我们将模型拟合至模拟生长轨迹，以明确准确估算AAM所需的最小数据阈值（涵盖样本量、年龄体长数据的精度，以及成熟对躯体生长的代价）。随后，我们将该方法应用于大型白斑狗鱼（Sander vitreus）数据集，结果显示，当模型拟合效果良好时，我们得到的AAM估算值与传统估算值高度一致。最后，我们将该方法应用于多种外温动物的年龄体长数据，以此凸显其应用潜力。本方法有望成为从当代及历史样本中估算AAM及其他生活史性状的有效工具。