Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second‐order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second‐order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second‐order LTRE analyses could improve our understanding of population responses to changing environments.

中文翻译：

---

非线性生命表响应实验分析：分解非线性和非加性人口增长对环境驱动因素变化的响应

生命表响应实验 (LTRE) 将环境之间人口增长率的差异分解为每个基础人口增长率的单独贡献。然而，大多数 LTRE 分析做出了不切实际的假设，即人口比率和环境驱动因素之间的关系是线性且独立的，当违反这些假设时，可能会导致准确性下降。我们扩展了回归 LTRE 以纳入非线性（二阶）项，并比较了这两种方法对于之前发布的三个人口数据集的准确性。我们表明，对于所有三个案例研究，二阶方法等于或优于线性方法，即使所有潜在的生命率函数都是线性的。对驱动因素变化的非线性生命率反应对人口增长率反应贡献最大，但生活史变化也做出了重大贡献。我们的结果表明，从线性 LTRE 分析转向二阶 LTRE 分析可以提高我们对人口对不断变化的环境的反应的理解。