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|Title: ||Estimating Detection Probabilities for Terrestrial Salamanders in Great Smoky Mountains National Park|
|Authors: ||Bailey, Larissa|
|Advisors: ||Dr. Kenneth H. Pollock, Committee Member|
Dr. John R. Godwin, Committee Member
Dr. Nick M. Haddad, Committee Member
Dr. Theodore R. Simons, Committee Chair
|Keywords: ||Great Smoky Mountains National Park|
|Issue Date: ||2-Aug-2002|
|Abstract: ||Recent worldwide amphibian declines have highlighted a need for more extensive, rigorous monitoring programs. Investigators must make decisions about which state variable to monitor based on the monitoring program's scientific or management objectives, while considering economic and logistical constraints. Two sources of variation; spatial variation and variation in detection probability constrain the inferences drawn from these monitoring programs. Our research focused on estimating detection probabilities for three state variables commonly used in terrestrial salamander monitoring programs: population size, proportion of area occupied, and species richness.
Approximately 10% of the world's salamander species are found in the southern Appalachian region and they are a high priority taxon in Great Smoky Mountains National Park (GSMNP). We used Pollock's robust design in a 3-year capture-recapture study at 15-20 replicated sites in a single watershed in GSMNP. We used competing models to estimate detection probability parameters for plethodon salamanders, determine the importance of temporary emigration (i.e. the probability of being absent from the sample area), and explored temporal and behavioral effects on conditional capture probabilities. Models that included random temporary emigration were chosen four times more often than models with no temporary emigration. Models that contained behavioral effects in capture probabilities were preferred over models with only time effects, but there was evidence that behavioral and time effects together influenced capture probabilities.
We used the 'best' robust design model to test a priori hypothesis about spatial and temporal variation in salamander detection probability parameters. We explored the effects of 3 large-scale habitat characteristics (disturbance history, elevation, vegetation type) and found vegetation type and elevation were significant covariates in temporary emigration, conditional capture probability, and surface population size estimates. All detection probability parameters increased over the 3-year study, but estimates of surface and superpopulation (total population) did not change.
We estimated the proportion of area occupied (PAO) and species detection probability for 7 salamander species using other sites within the same watershed. We tested whether the type of sampling method, the number of sites sampled, or the number of sampling occasions per site affected PAO parameter estimates. We also investigated a priori hypotheses about temporal and spatial variations in PAO parameter estimates associated with four large-scale habitat characteristics (covariates). Both PAO and species detection probability estimates varied among species, sampling method, and year. In general, the accuracy and precision of PAO and detection probability estimates were better using natural cover transects rather than coverboard transects. Reducing the number of sampling occasions or the number of sites sampled reduced PAO precision. Average species-specific detection probabilities showed consistent patterns over our 3-year study (no species x year interaction), but within year detection patterns varied among species. PAO methods were capable of revealing differences in species' distribution types (clumped or widespread) as well as potentially important species-specific habitat covariates.
Finally, we explored the effectiveness of estimating species richness using two methods, but neither method performed well, primarily because there are not enough different species at each site to allow meaningful comparisons across time or space.
This study represents the largest mark-recapture study on terrestrial salamanders and is the first to estimate a suite of potential state variables and related detection probabilities. We found strong evidence that detection probabilities change over time, space, and among species. Therefore, we discourage using unadjusted count data to make inferences about the status of amphibian systems without estimating or eliminating differences in detection probabilities.|
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