Imperfect detection impacts the performance of species distribution models

Abstract

Aim: Species often remain undetected at sites where they are present. However, the impact of imperfect detection on species distribution models (SDMs) is not fully appreciated. In this paper we evaluate the influence of imperfect detection on the calibration and discrimination capacity of SDMs. We compare the performance of three types of SDMs: (1) a technique based on presence-absence data, (2) a technique based on presence-background data, and (3) a technique based on detection/non-detection data that accounts for imperfect detection. Innovation: We use simulations to evaluate the impacts of imperfect detection in SDMs. This allows us to assess model performance with respect to the true ob..