Optimizing Survey Designs for Complex Habitat: Evaluating Seasonal Variation of Alligator Abundance Estimates Derived From Nightlight Surveys in South Carolina

Poster presented at the 23rd Working Meeting of the IUCN Crocodile Specialist Group in Lake Charles, LA, May 2014, and at the Annual Conference of the Wildlife Society (TWS) in Pittsburgh, PA, October 2014. At TWS, the poster was awarded 1st place in the PhD category for the Student Research in Progress Poster Session.

ABSTRACT:

Nightlight surveys are a commonly used, cost-effective monitoring method to acquire crocodilian abundance, occupancy, and size class distribution data. Monitoring data can be directly applied to infer population trends and inform management decisions. However, reliability of nightlight survey-derived abundance estimates are heavily influenced by survey design components, including season, number of replicate surveys, and replicate time interval. In the United States, five states in the American alligator’s (Alligator mississippiensis) eastern distribution have established nightlight-survey based monitoring programs in the last decade. However, new programs are frequently modeled after existing programs in other regions with different alligator habitat, with little to no empirical evaluation to determine if the proposed survey designs are appropriate for areas beyond their original use or if an alternative design may increase demographic estimation precision. A “one-size-fits-all” approach to monitoring program design is risky, as it can produce imprecise or deficient data and ultimately, wasted time and resources. Here, we describe an on-going study in South Carolina aimed at identifying the optimal nightlight survey design that maximizes precision of size-class specific abundance and detection probability estimates, in order to minimize uncertainty associated with harvest decisions. From 2014-2016 we will conduct two replicate nightlight surveys within the breeding, nesting, and post-nesting periods (6 surveys/route/year; N = 6 routes), in several major habitat types. Our main objective is to quantify levels of demographic uncertainty associated with varying combinations of survey design components and identify a design that is tailored to South Carolina’s habitat, management needs, and resources.