Development and assessment of predictive spatial models for a rare Tennessee anuran: Barking treefrog (Hyla gratiosa)

In Tennessee, the Barking Treefrog (Hyla gratiosa) is listed as both rare and vulnerable, and more field data is needed to elucidate its distribution. Predictive modeling using the program MaxEnt provided results for models that guided field sampling to potential presence locations. From April-August 2017, 126 sites (63 historical; 63 predicted) were visited monthly and sampled for frog calls according to a standardized protocol. Field results revealed H. gratiosa’s auditory presence at 23 out of 63 historic sites and at nine out of 63 predicted sites. While other predictive models were also generated, MaxEnt was demonstrated to be most precise in predicting presence likelihood. Weighted regression analysis showed that shrub/scrub and woody wetland coverages were the most positively associated with presence. The results suggest that H. gratiosa is not as relatively abundant as some frog species throughout ecologically relevant landscapes in Tennessee.

Grantor dc:publisher

University of Tennessee at Chattanooga

Author dc:creator

• Hunt, Nyssa R.

Contributors dc:contributor

• Wilson, Thomas P.
• Aborn, David A.; Carroll, Andrew
• College of Arts and Sciences

• Hylidae -- Tennessee
• Frogs
• Barking treefrog

Licence

• https://rightsstatements.org/page/InC/1.0/?language=en

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/564

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-1722