Combining Data Sources to Understand Drivers of Spotted Salamander (Ambystoma maculatum) Population Abundance
Robust methods for estimating abundance of wetland-breeding amphibian species, such as mark–recapture, are often resource intensive. This limits our ability to study the processes that influence species abundance. Alternatively, more efficient sampling methods, such as indices based on visual encounter surveys (VES) (e.g., egg masses), may be biased by variability in detection probabilities and species biology (e.g., no. of egg masses per female). We combine data sources (i.e., VES and capture–mark–recapture) to provide an efficient technique for monitoring wetland-breeding amphibians. Our study focuses on understanding factors that determine local abundance of Spotted Salamanders, Ambystoma maculatum, in Pennsylvania. We first estimated abundance for a subset of wetlands using single-season, capture–mark–recapture data and then verified egg-mass counts collected from a wider network of wetlands as an unbiased index of abundance. We found a strong correlation between estimated adult abundance and estimated egg-mass abundance with an estimated ratio of one egg mass per adult per breeding effort. We next determined the factors that best explained variation in estimated A. maculatum egg-mass abundance and consequently, adult abundance among sites. Our “best-fit” model included effects for wetland hydroperiod and quadratic effects of mean water temperature. We also report positive, but weak, association with two co-occurring amphibian species, Jefferson Salamanders, A. jeffersonianum and Wood Frogs, Lithobates sylvaticus. We demonstrate how combining sampling approaches can provide efficient abundance estimates in wetland ecosystems. In particular, positive co-occurrence among species indicates shared habitat preferences that may enable us to predict the presence of difficult-to-detect species using only VES.Abstract
Study area location within Pennsylvania and individual wetland sites within the study area. Red triangles indicate wetlands surveyed with CMR and VES, whereas gray circles indicate wetlands surveyed using only the VES method.
Diagram depicting the (A) placement of VIE marks, (B) standardized processing station for photographing all captured Ambystoma maculatum individuals, and a (C) straightened and cropped image as displayed in I3S, the identification software used to identify individuals via unique dorsal spot patterns, as highlighted here, which can then be used to construct individual encounter histories.
Estimated Ambystoma maculatum egg-mass abundance (gray; counts adjusted for 0.69 detection probability) and 95% confidence intervals as well as mean double-observer egg-mass counts for A. jeffersonianum (red) and Lithobates sylvaticus (blue) for all 37 wetlands monitored via VES in 2015.
Relationship between predicted density of Ambystoma maculatum (AMMA) egg masses and (A) mean water temperature (°C), (B) A. jeffersonianum (AJEF) egg-mass density (mean count/m2), and (C) Lithobates sylvaticus (LSYL) egg-mass density (mean count/m2) for wetlands of shorter (blue) and longer (black) hydroperiod. Regression lines show predicted slopes with 95% prediction intervals.
Estimated Ambystoma maculatum egg-mass abundance as a function of estimated adult (A) female and (B) male abundance for our 12 CMR wetlands in 2015. Egg-mass abundances were estimated using an N-mixture model in the R package “unmarked,” whereas sex-specific adult abundances were estimated using Huggins' closed population model in Program MARK. Regression lines show predicted slopes with 95% prediction intervals.
Mean egg-mass counts (not corrected for imperfect detection) for Ambystoma maculatum as a function of estimated (A) female and (B) male abundance for our 12 CMR wetlands in 2015. Regression lines show predicted slopes with 95% prediction intervals.
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