Survey and Analysis Design for Wood Turtle Abundance Monitoring Programs
The Lakes States Fire Science March Webinar welcomes Donald Brown, School of Natural Resources, West Virginia University, Northern Research Station, US Forest Service. He will present Survey and Analysis Design for Wood Turtle Abundance Monitoring Programs as the March webinar.
Population monitoring is a fundamental component of wildlife management, and is necessary to track site- and regional-level status and recovery of species of conservation concern. The wood turtle (Glyptemys insculpta) is a species of high conservation concern for federal and state agencies due to population declines across the species’ range. We developed and tested a survey and analysis design to assist agencies in the Upper Midwest with establishment of long-term monitoring programs for wood turtle populations. We conducted 8 replicate population surveys at 8 candidate long-term monitoring sites in northeastern Minnesota, USA. Using field survey data and simulation models, we assessed the influence of distance from river surveyed, number of survey replications, and number of sites on abundance estimates, as well as delineated important survey covariates and compared demographic estimates based on distance from river surveyed. We estimated site-level abundances and compared survey designs using a multinomial N-mixture model that included a removal sampling observation process. We found that mean abundance estimates were similar when surveying 2 transects (i.e., the river-land interface to ca. 25 m inland) or 4 transects (i.e., the river-land interface to ca. 55 m inland), but reducing survey distance from river reduced the mean precision of estimates by ca. 60%. We found that mean abundance estimates were similar with ≥6 replications. Air temperature was an important predictor of survey-specific detection probability, with maximum detectability at 19−23 °C. Sex ratio and mean carapace length did not differ based on whether 2 or 4 transects were surveyed, and percentage of individuals by size class was nearly identical between the sampling designs. Simulations indicated that 75% of mean abundance estimates were within ±8% of true abundance when ≥15 sites were surveyed. The wood turtle survey and analysis design we developed and tested was effective for estimating abundance of wood turtle populations in northeastern Minnesota, and we encourage its use as a template for wood turtle monitoring programs in the Upper Midwest.