@article{mcclintock_bailey_pollock_simons_2010, title={Experimental Investigation of Observation Error in Anuran Call Surveys}, volume={74}, ISSN={["1937-2817"]}, DOI={10.2193/2009-321}, abstractNote={ABSTRACT Occupancy models that account for imperfect detection are often used to monitor anuran and songbird species occurrence. However, presence—absence data arising from auditory detections may be more prone to observation error (e.g., false‐positive detections) than are sampling approaches utilizing physical captures or sightings of individuals. We conducted realistic, replicated field experiments using a remote broadcasting system to simulate simple anuran call surveys and to investigate potential factors affecting observation error in these studies. Distance, time, ambient noise, and observer abilities were the most important factors explaining false‐negative detections. Distance and observer ability were the best overall predictors of false‐positive errors, but ambient noise and competing species also affected error rates for some species. False‐positive errors made up 5% of all positive detections, with individual observers exhibiting false‐positive rates between 0.5% and 14%. Previous research suggests false‐positive errors of these magnitudes would induce substantial positive biases in standard estimators of species occurrence, and we recommend practices to mitigate for false positives when developing occupancy monitoring protocols that rely on auditory detections. These recommendations include additional observer training, limiting the number of target species, and establishing distance and ambient noise thresholds during surveys.}, number={8}, journal={JOURNAL OF WILDLIFE MANAGEMENT}, author={Mcclintock, Brett T. and Bailey, Larissa L. and Pollock, Kenneth H. and Simons, Theodore R.}, year={2010}, month={Nov}, pages={1882–1893} }
 @article{mcclintock_bailey_pollock_simons_2010, title={Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections}, volume={91}, ISSN={["0012-9658"]}, DOI={10.1890/09-1287.1}, abstractNote={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.}, number={8}, journal={ECOLOGY}, author={McClintock, Brett T. and Bailey, Larissa L. and Pollock, Kenneth H. and Simons, Theodore R.}, year={2010}, month={Aug}, pages={2446–2454} }
 @article{talancy_bailey_sauer_cook_gilbert_2006, title={Estimating site occupancy and detection probability parameters for meso- and large mammals in a coastal ecosystem}, volume={70}, ISSN={["1937-2817"]}, DOI={10.2193/0022-541X(2006)70[1625:ESOADP]2.0.CO;2}, abstractNote={Abstract Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.}, number={6}, journal={JOURNAL OF WILDLIFE MANAGEMENT}, author={Talancy, Neil W. and Bailey, Larissa L. and Sauer, John R. and Cook, Robert and Gilbert, Andrew T.}, year={2006}, month={Dec}, pages={1625–1633} }
 @article{conn_arthur_bailey_singleton_2006, title={Estimating the abundance of mouse populations of known size: Promises and pitfalls of new methods}, volume={16}, ISSN={["1939-5582"]}, DOI={10.1890/1051-0761(2006)016[0829:ETAOMP]2.0.CO;2}, abstractNote={Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark-recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark-recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark-recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates.}, number={2}, journal={ECOLOGICAL APPLICATIONS}, author={Conn, PB and Arthur, AD and Bailey, LL and Singleton, GR}, year={2006}, month={Apr}, pages={829–837} }
 @article{bailey_sauer_nichols_geissler_2005, title={General constraints on sampling wildlife on FIA plots}, journal={Proceedings of the fourth annual Forest Inventory and Analysis Symposium : meeting jointly with the Southern Forest Mensurationists : New Orleans, Louisiana, November 19-21, 2002}, publisher={Saint Paul, MN : North Central Forest Experiment Station, USDA Forest Service}, author={Bailey, L. L. and Sauer, J. R. and Nichols, J. D. and Geissler, P. H.}, year={2005} }
 @article{mackenzie_nichols_sutton_kawanishi_bailey_2005, title={Improving inferences in popoulation studies of rare species that are detected imperfectly}, volume={86}, number={5}, journal={Ecology (Brooklyn, New York, N.Y.)}, author={Mackenzie, D. I. and Nichols, J. D. and Sutton, N. and Kawanishi, K. and Bailey, L. L.}, year={2005}, pages={1101–1113} }
 @article{mackenzie_bailey_2004, title={Assessing the fit of site-occupancy models}, volume={9}, ISSN={["1537-2693"]}, DOI={10.1198/108571104X3361}, abstractNote={Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question “how accurately does the fitted model represent the data?” The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.}, number={3}, journal={JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS}, author={MacKenzie, DI and Bailey, LL}, year={2004}, month={Sep}, pages={300–318} }
 @article{bailey_simons_pollock_2004, title={Comparing population size estimators for plethodontid salamanders}, volume={38}, ISSN={["1937-2418"]}, DOI={10.1670/194-03A}, abstractNote={Abstract Despite concern over amphibian declines, few studies estimate absolute abundances because of logistic and economic constraints and previously poor estimator performance. Two estimation approaches recommended for amphibian studies are mark-recapture and depletion (or removal) sampling. We compared abundance estimation via various mark-recapture and depletion methods, using data from a three-year study of terrestrial salamanders in Great Smoky Mountains National Park. Our results indicate that short-term closed-population, robust design, and depletion methods estimate surface population of salamanders (i.e., those near the surface and available for capture during a given sampling occasion). In longer duration studies, temporary emigration violates assumptions of both open- and closed-population mark-recapture estimation models. However, if the temporary emigration is completely random, these models should yield unbiased estimates of the total population (superpopulation) of salamanders in the sampled area. We recommend using Pollock's robust design in mark-recapture studies because of its flexibility to incorporate variation in capture probabilities and to estimate temporary emigration probabilities.}, number={3}, journal={JOURNAL OF HERPETOLOGY}, author={Bailey, LL and Simons, TR and Pollock, KH}, year={2004}, month={Sep}, pages={370–380} }
 @article{bailey_simons_pollock_2004, title={Estimating site occupancy and species detection probability parameters for terrestrial salamanders}, volume={14}, ISSN={["1051-0761"]}, DOI={10.1890/03-5012}, abstractNote={Recent, worldwide amphibian declines have highlighted a need for more extensive and rigorous monitoring programs to document species occurrence and detect population change. Abundance estimation methods, such as mark–recapture, are often expensive and impractical for large‐scale or long‐term amphibian monitoring. We apply a new method to estimate proportion of area occupied using detection/nondetection data from a terrestrial salamander system in Great Smoky Mountains National Park. Estimated species‐specific detection probabilities were all <1 and varied among seven species and four sampling methods. Time (i.e., sampling occasion) and four large‐scale habitat characteristics (previous disturbance history, vegetation type, elevation, and stream presence) were important covariates in estimates of both proportion of area occupied and detection probability. All sampling methods were consistent in their ability to identify important covariates for each salamander species. We believe proportion of area occupied represents a useful state variable for large‐scale monitoring programs. However, our results emphasize the importance of estimating detection and occupancy probabilities rather than using an unadjusted proportion of sites where species are observed where actual occupancy probabilities are confounded with detection probabilities. Estimated detection probabilities accommodate variations in sampling effort; thus comparisons of occupancy probabilities are possible among studies with different sampling protocols.}, number={3}, journal={ECOLOGICAL APPLICATIONS}, author={Bailey, LL and Simons, TR and Pollock, KH}, year={2004}, month={Jun}, pages={692–702} }
 @article{bailey_kendall_church_wilbur_2004, title={Estimating survival and breeding probability for pond-breeding amphibians: A modified robust design}, volume={85}, ISSN={["1939-9170"]}, DOI={10.1890/03-0539}, abstractNote={Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture–recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark–recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary)...}, number={9}, journal={ECOLOGY}, author={Bailey, LL and Kendall, WL and Church, DR and Wilbur, HM}, year={2004}, month={Sep}, pages={2456–2466} }
 @article{mackenzie_bailey_nichols_2004, title={Investigating species co-occurrence patterns when species are detected imperfectly}, volume={73}, ISSN={["1365-2656"]}, DOI={10.1111/j.0021-8790.2004.00828.x}, abstractNote={Summary}, number={3}, journal={JOURNAL OF ANIMAL ECOLOGY}, author={MacKenzie, DI and Bailey, LL and Nichols, JD}, year={2004}, month={May}, pages={546–555} }
 @article{pollock_nichols_simons_farnsworth_bailey_sauer_2002, title={Large scale wildlife monitoring studies: statistical methods for design and analysis}, volume={13}, ISSN={["1099-095X"]}, DOI={10.1002/env.514}, abstractNote={Abstract}, number={2}, journal={ENVIRONMETRICS}, author={Pollock, KH and Nichols, JD and Simons, TR and Farnsworth, GL and Bailey, LL and Sauer, JR}, year={2002}, month={Mar}, pages={105–119} }