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29th Annual Meeting and Symposium of the
Desert Tortoise Council, February 20-23, 2004
Abstracts
STUDENT PAPER
Can Modeling of Tortoise Activity Be Used to Improve Species Monitoring?
1Kenneth E. Nussear, 1C. Richard Tracy, 2Richard
Inman, 2Jill S. Heaton and 3Philip A. Medica
1Biological Resource Research Center, University of Nevada,
Reno NV.
2Redlands Institute, University of Redlands, Redlands CA.
3U. S. Fish and Wildlife Service, Las Vegas, NV
Desert tortoises are currently the focus of a large, multi-state monitoring program that uses distance sampling to estimate population densities from line-transects. A critical assumption of this technique is that all animals on or near transects are observed. Because desert tortoises spend large proportions of the year in burrows, this assumption is frequently violated. Therefore, the density calculation requires a correction factor to account for the proportion of animals active and available to be counted (Go) to account for the under-sampled proportion of the population. Estimating Go is currently accomplished by monitoring a small number of animals (N = 6-12), which are scored for behavior several times daily during the transect-sampling period. Collecting these data is very costly, and lacks precision due to the small sample sizes currently monitored. To explore the influence of environmental variables on tortoise activity, we are modeling the link between biophysical attributes of the environment and the proportions of tortoise that are active. These models are based upon empirical observations of ~120 tortoises monitored over a three-year period. The model inputs include: environmental temperatures, operative temperatures, rainfall, solar radiation, among others. We employ a fusion of biophysical and neural network modeling to allow for, and benefit from, the complex interactions existing among the environmental variables included in the model. We present an initial model that identifies influential environmental variables affecting activity, and explore the repeatability of tortoise activity among days with similar environmental conditions. Our data show that activity may not be a highly repeatable behavior, which will make modeling efforts difficult. We are conducting further research to refine our ability to predict tortoise activity.
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