COS 20-5
A simple temperature model predicts the timeing of Green Treefrog (Hyla cinerea) breeding

Tuesday, August 11, 2015: 9:20 AM
318, Baltimore Convention Center
Jacoby Carter, National Wetlands Research Center, US Geological Survey, Lafayette, LA
Darren Johnson, Five Rivers Services LLC, Lafayette, LA
Vinodh K Chellamuthu, Mathematics, University of Louisiana at Lafayette, Lafayette, LA

We monitored Green Treefrogs (GTF, Hyla cinerea) in two adjacent pond complexes in Lafayette, Louisiana over the course of five years. The two pond complexes functioned as a metapopulation, that is, they were close enough that frogs occasionally, but rarely, moved between them. The monitoring involved once weekly mark/recapture, noting calling activity, temperature, wind speed and time since last significant precipitation. Monitoring began in February before breeding began and ended in October after breeding had ceased for the year. We noted when tadpoles metamorphosed to frogs and left the ponds. We wanted to predict when breeding began based on environmental variables (temperature, wind speed and precipitation) in order to incorporate climate driven GTF phenology into a temperature sensitive model of chytridiomycosis. Data from a nearby weather station was used to estimate daily temperatures our sites on non-sampling days. We ran a stepwise logistic regression analysis with a 0.05 alpha acceptance criteria, with frog calls (index 2 or higher) as the categorical response variable and temperature, wind speed and precipitation for parameters.


We had 199 observations with two levels (call index of 0 or 1 vs. call index of 2 or 3). The best model to predict calling (and by implication breeding) was a function of temperature at the time of observation and previous three-week’s average temperature. This model had a correct classification rate of 75.9% at 27°C. Time since last precipitation and wind speed were not significant. These results can be used to model the breeding phenology of GTF under different climate change scenarios.