Department of Biology, Duke University, Durham, North Carolina, USA.
Environmental Studies Program, University of Colorado, Boulder, Colorado, USA.
Ecol Lett. 2024 Mar;27(3):e14417. doi: 10.1111/ele.14417.
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.
生命表响应实验 (LTRE) 将种群增长率在环境之间的差异分解为每个基础人口率的单独贡献。然而，大多数 LTRE 分析都假设人口率与环境驱动因素之间的关系是线性和独立的，当这些假设被违反时，这可能会导致准确性降低。我们将回归 LTRE 扩展到包含非线性（二阶）项，并比较了这两种方法在三个先前发表的人口数据集上的准确性。我们表明，二阶方法在所有三个案例研究中都等于或优于线性方法，即使所有基础生命率函数都是线性的。对驱动因素变化的非线性生命率响应对种群增长率响应的贡献最大，但生活史变化也做出了实质性的贡献。我们的结果表明，从线性到二阶 LTRE 分析的转变可以提高我们对种群对环境变化的反应的理解。
