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Survey and analysis design for wood turtle population monitoring
Author(s) -
Brown Donald J.,
Cochrane Madaline M.,
Moen Ron A.
Publication year - 2017
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.1002/jwmg.21249
Subject(s) - transect , abundance (ecology) , population , wildlife , survey methodology , geography , range (aeronautics) , turtle (robot) , environmental science , aerial survey , habitat , sampling (signal processing) , ecology , statistics , biology , cartography , demography , mathematics , materials science , filter (signal processing) , sociology , computer science , composite material , computer vision
ABSTRACT 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 conservation concern for federal and state agencies because of population declines across the species’ range. We developed and tested a survey and analysis design to assist agencies in the Upper Midwest, USA, with establishment of long‐term monitoring programs for wood turtle populations. In spring of 2016, 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; we also 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. Mean abundance estimates were similar when surveying 2 transects (i.e., the river‐land interface to ∼25 m inland) or 4 transects (i.e., the river‐land interface to ∼55 m inland), but decreasing the survey distance from river reduced the precision of estimates. 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 we surveyed 2 or 4 transects, 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. © 2017 The Wildlife Society.