Nonlinear relationships between vital rates and state variables in demographic models.
Nonlinear relationships between vital rates and state variables in demographic models.
复制标题
人口模型中生命率和状态变量之间的非线性关系。
DOI：
10.1890/10-1184.1
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发表时间：
2011
期刊：
影响因子：
4.8
通讯作者：
J. Ehrlén
中科院分区：
文献类型：
--
作者：
J. Dahlgren;María B. García;J. Ehrlén
为了准确地估计人口动态和生存能力，结构化人口模型考虑了与个人状态相关的人口参数的个人差异。在广泛使用的矩阵模型中，这种差异被合并到离散状态类别中，而积分投影模型(IPMS)使用连续的状态变量来避免人工类别。在综合方案管理系统中，有时也在矩阵模型中，参数化是基于回归，而回归并不总是对人口统计参数和状态变量之间的非线性关系进行建模。我们强调了检验非线性的重要性，并建议使用受限三次样条法，以便在回归和人口统计模型中考虑各种关系。结果表明，活力率与种群大小和年龄的关系是非线性的，参数化方法对预测的种群增长率X有较大影响(线性IPM为0.95；非线性IPMS为1.00；矩阵模型为0.96)。我们的结果表明，约束三次样条模型比线性或多项式模型更可靠。由于生命率和状态变量之间的关系即使是微弱的非线性也会对模型预测产生很大影响，因此我们建议，当不能假设线性时，应该考虑使用限制三次回归样条法来对种群动态模型进行参数化。
To accurately estimate population dynamics and viability, structured population models account for among-individual differences in demographic parameters that are related to individual state. In the widely used matrix models, such differences are incorporated in terms of discrete state categories, whereas integral projection models (IPMs) use continuous state variables to avoid artificial classes. In IPMs, and sometimes also in matrix models, parameterization is based on regressions that do not always model nonlinear relationships between demographic parameters and state variables. We stress the importance of testing for nonlinearity and propose using restricted cubic splines in order to allow for a wide variety of relationships in regressions and demographic models. For the plant Borderea pyrenaica, we found that vital rate relationships with size and age were nonlinear and that the parameterization method had large effects on predicted population growth rates, X (linear IPM, 0.95; nonlinear IPMs, 1.00; matrix model, 0.96). Our results suggest that restricted cubic spline models are more reliable than linear or polynomial models. Because even weak nonlinearity in relationships between vital rates and state variables can have large effects on model predictions, we suggest that restricted cubic regression splines should be considered for parameterizing models of population dynamics whenever linearity cannot be assumed.