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应用人口模型的参数化和结构的后果:对 Pardini 等人(2009 年)的评论。

Consequences of parameterization and structure of applied demographic models: a comment on Pardini et al. (2009).

出版信息

Ecol Appl. 2011 Mar;21(2):608-13; author reply 614-8. doi: 10.1890/09-1776.1.

Abstract

Correcting the problems in the model of A. petiolata presented in Pardini et al. (2009) changes its dynamics and thus the management recommendations. As with any model, our revised model's-management predictions are conditional on model parameterization. Thus, managers should carefully consider at what spatial scales it is appropriate to infer management recommendations given the data used to build the model (e.g., is a management plan developed from a population in Missouri equally relevant to populations in Georgia, Maine, and Oregon?). In agreement with PDCK's conclusions, we found their A. petiolata study population to exhibit complex dynamics (two-point cycling) at lower efficacies of either rosette or adult management, and stable equilibria at higher management efficacies. This could have important implications for A. petiolata management techniques such as biological control if the biocontrol agents' population dynamics are dependent on A. petiolata density. While the predictions generated in our reanalysis represent an improvement over the original model, they should be tempered by the limited scope of the data used to parameterize the model. Running the model through previously published parameter ranges results in qualitatively different dynamics than those predicted in PDCK. Because of the tremendous spatiotemporal variability in A. petiolata demographic rates and the species' large geographical range, more general management recommendations will only arise from a larger set of demographic data that has greater coverage in space and time. Our revision of the model of Pardini et al. (2009) should therefore be considered as a subset of many possible models of A. petiolata population dynamics.

摘要

纠正 Pardini 等人(2009 年)提出的 A. petiolata 模型中的问题会改变其动态,从而改变管理建议。与任何模型一样,我们修订后的模型的管理预测取决于模型参数化。因此,管理者应该仔细考虑,根据用于构建模型的数据,在什么空间尺度上推断管理建议是合适的(例如,从密苏里州的一个种群中制定的管理计划是否同样适用于佐治亚州、缅因州和俄勒冈州的种群?)。与 PDCK 的结论一致,我们发现他们的 A. petiolata 研究种群在较低的蔷薇或成年管理效率下表现出复杂的动态(两点循环),而在较高的管理效率下则表现出稳定的平衡。如果生物防治剂的种群动态依赖于 A. petiolata 的密度,这可能对 A. petiolata 的管理技术(如生物防治)产生重要影响。虽然我们的重新分析产生的预测比原始模型有所改进,但应考虑到用于参数化模型的数据范围有限。通过以前发表的参数范围运行模型会导致与 PDCK 预测的动态完全不同。由于 A. petiolata 人口动态在空间和时间上存在巨大的时空可变性,以及该物种的广泛地理范围,只有从具有更大空间和时间覆盖范围的更大数据集得出更普遍的管理建议,才能得出更普遍的管理建议。因此,我们对 Pardini 等人(2009 年)模型的修订应被视为许多可能的 A. petiolata 种群动态模型的子集。

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