Date of Award

12-1-2025

Degree Name

Master of Science

Department

Forestry

First Advisor

Pease, Brent

Second Advisor

Cove, Michael

Abstract

This study employed a telemetry-based framework, using radio-collared Virginia opossums (Didelphis virginiana), to quantify survival patterns and estimate detection probabilities of python predation events. Between April 2022 and January 2025, 135 adult opossums were monitored using VHF collars across protected habitats within Key Largo. Annual survival was estimated using a staggered-entry Kaplan-Meier model, producing an annual survival rate of 0.17 (SE = 0.089) for females, and male survival was estimated at 0.04 (SE = 0.032) at 10 months since no male lived 10 months after collaring. Cause-specific monthly survival analyses indicated python predation peaked during the late summer months of July through September, when temperatures were at their annual highest. No python predation events were recorded from January through April, corresponding to lower temperatures and the python breeding season. Bootstrap simulations (n = 1000 per 5% increment) demonstrated that opossum survival estimates stabilize around 35% sample coverage or 48 collars, and produce RMSE values of 0.022, indicating that 135 collars is likely representative of the population. A python-specific detection model revealed a 95% detection probability with 8–10 collars, whereas a theoretical model, assuming independent mortality risk, required 37 collars to reach equivalent power. The empirical model consistently exceeded theoretical expectations, likely reflecting temporal clustering in predation risk. These findings support the integration of radio-collared prey into invasive predator monitoring protocols, providing a scalable, cost-effective approach for early detection and removal of invasive predators. Moreover, this method may be broadly transferable to similar habitats and comparable cryptic predators, offering strategic benefits in wildlife management and conservation monitoring.

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