Riparian sign surveys near bridge crossings are commonly used to detect the presence of river otters. However, the efficacy of using such surveys for determining river otter presence has not been evaluated relative to habitat conditions. We conducted surveys to detect latrines (locations where scats are deposited in riparian areas) from reintroduced populations of river otters at 26 bridge-suites in northern Pennsylvania. A bridge-suite consisted of a bridge site, a random site and a selected site (i.e., high quality site based on several habitat variables), <2.5 km upstream or downstream from the bridge. Sites consisted of both shorelines along a 200-m section of stream or river. Site quality was determined by applying a modified Pattern Recognition model (PATREC) previously developed to provide a probabilistic assessment for predicting the occurrence of river otter latrines based on the presence or absence of certain riparian and riverine habitat features. Sites were surveyed in fall 2003 and spring 2004. Latrines were detected at 19 (73.1%) of the 26 bridge-suites. Of these 19 bridge-suites, 17 (65.3%) were positive for latrines in spring, 15 (57.7%) in the fall and 13 (50.0%) in both seasons. Among the 78 survey sites (i.e., 3 sites per bridge-suite), 32 (41.0%) were positive for latrines [21 sites (26.9%) in spring and 22 sites (28.2%) sites in fall]. Repeated measures logistic regression was used to assess the influence of the covariates season (spring or fall), type of site (i.e., site type: bridge, random or selected) and quality of site (site score) on the probability of detecting latrines. Two models were useful in describing the occurrence of a positive site (i.e., a site with ≥1 latrine), and both included site type as a variable. The odds of a selected site being positive ranged from 7.8 to 9.3 times the odds of random or bridge sites being positive. We concluded that monitoring the presence of river otters based on searching for latrines at bridge or random sites was considerably less effective than by using the a priori selection of surveys areas based on riparian habitat features.
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