Relative Selection Strength: Quantifying effect size in habitat- and step-selection inference.

ECOLOGY AND EVOLUTION(2017)

引用 109|浏览7
暂无评分
摘要
Habitat-selection analysis lacks an appropriate measure of the ecological significance of the statistical estimatesa practical interpretation of the magnitude of the selection coefficients. There is a need for a standard approach that allows relating the strength of selection to a change in habitat conditions across space, a quantification of the estimated effect size that can be compared both within and across studies. We offer a solution, based on the epidemiological risk ratio, which we term the relative selection strength (RSS). For a used-available design with an exponential selection function, the RSS provides an appropriate interpretation of the magnitude of the estimated selection coefficients, conditional on all other covariates being fixed. This is similar to the interpretation of the regression coefficients in any multivariable regression analysis. Although technically correct, the conditional interpretation may be inappropriate when attempting to predict habitat use across a given landscape. Hence, we also provide a simple graphical tool that communicates both the conditional and average effect of the change in one covariate. The average-effect plot answers the question: What is the average change in the space use probability as we change the covariate of interest, while averaging over possible values of other covariates? We illustrate an application of the average-effect plot for the average effect of distance to road on space use for elk (Cervus elaphus) during the hunting season. We provide a list of potentially useful RSS expressions and discuss the utility of the RSS in the context of common ecological applications.
更多
查看译文
关键词
SSA,log odds,logistic regression,odds ratio,resource selection function,HSA,step selection function
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要