Integrating eDNA and citizen science observations to model distribution of a temperate freshwater turtle near its northern range limit.

Abstract

To determine species distributions and the factors underlying them, reliable occurrence data are crucial. Assembling such data can be challenging for species with cryptic life histories or that occur at low densities. We developed species-specific eDNA protocols, from sampling through data interpretation, to detect the common musk turtle (Sternotherus odoratus) and tested whether eDNA occurrences change our understanding of the species distribution and the factors that shape its northern range limit. We used Species Distribution Models (SDMs) with full parameter optimization on citizen science observations of S. odoratus in Southern Ontario alone and together with eDNA occurrences. Our eDNA protocol was robust and sensitive. SDMs built from traditional observations and those supplemented with eDNA detections were comparable in prediction accuracy. However, models with eDNA detections suggested that the distribution of S. odoratus in Southern Ontario is underestimated, especially near its northern range limit, and that it is shaped by thermal conditions, hydrology, and elevation. Our study underscores the promise of eDNA for surveying cryptic aquatic organisms in undocumented areas, and how such insights can help us to improve our understanding of species distributions.