DEBBIES. A database to compare life history strategies across ectotherms.

Demographic models are used to explore how survival, growth and reproduction rates structure variation in life history traits (e.g., longevity, generation time, age at maturity) and strategies (pace of life and reproductive strategy) across species. This study presents the DEBBIES dataset that contains estimates of eight life history traits (length at birth, puberty and maximum length, maximum reproduction rate, fraction energy allocated to respiration versus reproduction, von Bertalanffy growth rate, juvenile and adult mortality rate) for 185 ectotherm species. The dataset can be used to parameterise dynamic energy budget integral projection models (DEB-IPMs) to calculate key demographic quantities like population growth rate and demographic resilience, but also link to conservation status, biogeographical characteristics, and evolutionary biology. Our technical validation shows a satisfactory agreement between observed and predicted longevity, generation time, age at maturity across all species. Compared to existing datasets, DEBBIES accommodates (i) easy cross-taxonomical comparisons because all DEB-IPMs have the same structure, (ii) many data-deficient species because no long-term individual data are required, and (iii) population forecasts to novel conditions because DEB-IPMs include a mechanistic description of the tradeoff between growth and reproduction. This dataset has the potential for biologists to unlock general predictions on ectotherm population responses from only a few key life history traits.

种群统计学模型可用于探究不同物种种群的存活、生长与繁殖速率如何塑造生活史性状（如寿命、世代时间、成熟年龄）及生活史策略（生活节奏与繁殖策略）的变异。本研究发布的DEBBIES数据集（DEBBIES dataset）涵盖了185种变温动物的8项生活史性状估算值，具体包括出生体长、性成熟体长、最大体长、最大繁殖速率、呼吸与繁殖的能量分配比例、冯·贝塔朗菲生长速率（von Bertalanffy growth rate）、幼体死亡率与成体死亡率。该数据集可用于为动态能量预算积分投影模型（dynamic energy budget integral projection models，DEB-IPMs）拟合参数，以计算种群增长速率、种群恢复力等核心种群统计指标，同时可与物种保护现状、生物地理特征及进化生物学研究相结合。本研究的技术验证结果显示，所有物种的观测值与预测值在寿命、世代时间、成熟年龄上均表现出良好的一致性。相较于现有数据集，DEBBIES具备三大优势：其一，所有DEB-IPMs结构统一，便于开展跨分类群比较；其二，无需长期个体观测数据，可覆盖大量数据匮乏物种；其三，DEB-IPMs包含生长与繁殖权衡的机制性描述，能够对新型环境下的种群进行预测。该数据集能够帮助生物学家仅通过少数关键生活史性状，即可获取变温动物种群响应的普适性预测结果。