Matthew Holden

Accurately detecting population trends in ecology

Accurately estimating trends in population abundance is critical for developing ecological theory, performing environmental assessments, and advising natural resource management. While the error and power of statistical methods for detecting population declines and recoveries are well-studied, they rarely consider the issues of density dependence. If population size time series data occurs in an area where the species is abundant, density dependence may cause the over-prediction of a population decline. In this project, we will calculate the probability of misestimating population growth rates above or below a specified threshold. We will then use the analysis in two applied contexts (1) the probability of falsely predicting a threatened species is declining or recovering and (2) the use of linear population models for predicting species occurrence spatially. In the latter case, we will derive simple rules of thumb for the critical population abundance, in relation to carrying capacity, after which density dependence interferes with accurate predictions of persistence. The critical abundance can be used as a guideline for when it may be appropriate to use linear population process models to predict species occurrence in a density-dependent world. The outcomes of the project can inform conservation planning from reserve design to invasive and threatened species management