Ecology, 91(8), 2010, pp. 2446–2454 Ó 2010 by the Ecological Society of America Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections BRETT T. MCCLINTOCK, 1,5 LARISSA L. BAILEY, 2 KENNETH H. POLLOCK, 3 AND THEODORE R. SIMONS 4 1 U.S. Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, Maryland 20708 USA 2 Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado 80523 USA 3 Biology, Biomathematics, and Statistics, Campus Box 7617, North Carolina State University, Raleigh, North Carolina 27695 USA 4 U.S. Geological Survey North Carolina Cooperative Fish and Wildlife Research Unit, Department of Biology, Campus Box 7617, North Carolina State University, Raleigh, North Carolina 27695 USA Abstract. The recent surge in the development and application of species occurrence models has been associated with an acknowledgment among ecologists that species are detected imperfectly due to observation error. Standard models now allow unbiased estimation of occupancy probability when false negative detections occur, but this is conditional on no false positive detections and sufficient incorporation of explanatory variables for the false negative detection process. These assumptions are likely reasonable in many circumstances, but there is mounting evidence that false positive errors and detection probability heterogeneity may be much more prevalent in studies relying on auditory cues for species detection (e.g., songbird or calling amphibian surveys). We used field survey data from a simulated calling anuran system of known occupancy state to investigate the biases induced by these errors in dynamic models of species occurrence. Despite the participation of expert observers in simplified field conditions, both false positive errors and site detection probability heterogeneity were extensive for most species in the survey. We found that even low levels of false positive errors, constituting as little as 1% of all detections, can cause severe overestimation of site occupancy, colonization, and local extinction probabilities. Further, unmodeled detection probability heterogeneity induced substantial underestimation of occupancy and overestimation of colonization and local extinction probabilities. Completely spurious relationships between species occurrence and explanatory variables were also found. Such misleading inferences would likely have deleterious implications for conservation and management programs. We contend that all forms of observation error, including false positive errors and heterogeneous detection probabilities, must be incorporated into the estimation framework to facilitate reliable inferences about occupancy and its associated vital rate parameters. Key words: auditory detection; colonization; detection probability; false negative; false positive; imperfect detection; local extinction; measurement error; monitoring; observation error; site occupancy; species occurrence. INTRODUCTION The use of site occupancy models for inferring patterns and dynamics of species occurrence has surged in recent years (e.g., Wintle et al. 2005, Mazerolle et al. 2007). Many of the recently developed occupancy probability models acknowledge that species are detect- ed imperfectly as a result of observation error. One form of observation error, arising when a species is present but fails to be detected (i.e., false negative error), has been a primary focus of these models (e.g., MacKenzie et al. 2002, 2003). This focus is justifiable because such errors are generally unavoidable, regardless of sampling design efforts. Receiving considerably less attention is another form of observation error that arises when a species is incorrectly detected as present when it is in fact absent (i.e., false positive error), and it remains standard practice to assume false positive errors are of little concern (but see Royle and Link 2006). The models of MacKenzie et al. (2002, 2003) facilitate unbiased estimation of occupancy probability conditional on there being no false positives and on the sufficient incorporation of explanatory variables for the false negative detection process. To help satisfy the latter condition, variables related to environmental conditions or observer abilities can be identified a priori and measured. However, other factors related to detection that are more difficult to assess, such as site-variable abundance (Royle and Nichols 2003), can result in detection probability heterogeneity between sites that induces bias in standard occupancy estimators. When detections rely on auditory cues (e.g., avian or amphibian vocalizations), another form of heterogeneity can arise due to site-variable calling distances (i.e., the distance Manuscript received 16 July 2009; revised 2 November 2009; accepted 9 November 2009. Corresponding Editor: J. R. Sauer. 5 E-mail: brett.mcclintock@gmail.com 2446