Data Sheet 1_Life history traits influence method-specific detection of native and invasive amphibians.pdf

IntroductionEfficient and effective monitoring is essential for informing conservation efforts and determining where to focus management actions. Newly arriving invasive and declining native taxa are often the focus of conservation programs, but these species are inherently difficult to monitor and detect. A key challenge to effective monitoring is when a species is present at a location but goes undetected, creating uncertainty about whether the species is truly absent or present but unobserved. Estimating detection improves the efficacy of monitoring methods and accurately informs conservation efforts.
MethodsIn this study, we applied occupancy modeling to estimate method-specific detection probabilities for two focal amphibian species: the native northern leopard frog (Lithobates pipiens) and invasive American bullfrog (Lithobates catesbeianus). We evaluated three monitoring techniques: automated acoustic recorders, eDNA, and visual encounter surveys at 38 breeding sites in Colorado’s South Platte River Basin, USA, an area where northern leopard frogs are declining, and bullfrogs are expanding. We investigated how local environmental conditions (temperature and pH) and survey-specific choices (survey date, number of observers, search time, and liters of filtered water) influenced detection probabilities for each species and method.
ResultsOur results showed that northern leopard frog detection probability increased slightly with longer visual search times and eDNA detection probability was highest in neutral pH conditions. Acoustic detection of northern leopard frog breeding calls peaked in early spring. For bullfrogs, eDNA detection improved with liters of filtered water and both eDNA and visual detection increased with water temperature. Bullfrog breeding call detection was highest in mid to late summer.
DiscussionNorthern leopard frog and bullfrog distinct life history traits related to breeding habitat preferences, behaviors, and seasonal emergence explained differences in their detection probabilities.