在考虑天气影响的情况下进行密度依赖性测试。

Testing for density dependence allowing for weather effects.

作者信息

Rothery Peter, Newton Ian, Dale Lois, Wesolowski Tomasz

机构信息

Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire, PE17 2LS, UK Fax: +44 (0) 1487 773 487, , , , , , GB.

Department of Avian Ecology, Wroclaw University, Sienkiewicza 21, 50 335 Wroclaw, Poland, , , , , , PL.

出版信息

Oecologia. 1997 Nov;112(4):518-523. doi: 10.1007/s004420050340.

DOI:10.1007/s004420050340

PMID:28307629

Abstract

A test for density dependence in time-series data allowing for weather effects is presented. The test is based on a discrete time autoregressive model for changes in population density with a covariate for the effects of weather. The distribution of the test statistic on the null hypothesis of density independence is obtained by parametric bootstrapping. A computer simulation exercise is used to demonstrate the gain in statistical power by allowing for weather effects. Application of the method to time-series data on three species of butterflies and two species of songbirds showed stronger evidence of density dependence than two standard tests.

摘要

本文提出了一种用于时间序列数据中密度依赖性检验的方法，该方法考虑了天气影响。该检验基于一个离散时间自回归模型，用于描述种群密度变化，并包含一个用于天气影响的协变量。通过参数自抽样获得了在密度独立性零假设下检验统计量的分布。通过计算机模拟实验证明了考虑天气影响在统计功效方面的提升。将该方法应用于三种蝴蝶和两种鸣禽的时间序列数据，结果表明，与两种标准检验相比，该方法能提供更强的密度依赖性证据。