Modeling stream fish distributions using interval‐censored detection times

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy‐detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time‐to‐detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time‐to‐first detection conditional on occupancy in relation to local factors, using modified interval‐censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time‐to‐detection model provided unbiased parameter estimates despite interval‐censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P‐values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval‐censored time‐to‐detection model provides a practical solution to model occupancy‐detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.     

Comparative use of active searches and artificial refuges to detect amphibians in terrestrial environments

Artificial refuges (cover boards) are commonly used to survey and monitor herpetofauna in many parts of the world. Despite the extensive use of artificial refuges in mesic environments, their effectiveness for detecting amphibians in temperate zones has rarely been examined. We compared amphibian detection probabilities between two survey methods; active searches of natural habitat and artificial refuges of three different types (corrugated steel, roofing tiles and timber railway sleepers). Our study area included five bioregions encompassing a 1180‐km latitudinal gradient across a modified, temperate eucalypt woodland vegetation community in south‐eastern Australia. We deployed 14 778 artificial refuges in terrestrial environments, within patches of remnant vegetation, and collected presence and abundance data on herpetofauna between 1999 and 2017. We used Bayesian logistic regression to identify the most effective survey method for detecting frog species across all bioregions. We modelled frog detections by fitting survey method, time since refuge deployment and rainfall prior to each survey. We detected 3970 individuals from 18 frog species. Overall, we found active searches and timber substrates most effective for detecting a broad range of species, although detection rates were driven by the numerically abundant spotted marsh frog Limnodynastes tasmaniensis. Timber refuges were effective for detecting several burrowing species, whereas active searches were effective at detecting habitat generalists. Quadratic effects of rainfall prior to survey as opposed to linear effects of time since artificial refuge placement was important in explaining frog detection rates in some bioregions. Active searches, timber railway sleepers and sheets of corrugated steel provide complimentary survey methods for detecting amphibians, although detection rates are influenced by rainfall patterns. Artificial refuges provide a time‐effective and standardized method for studying amphibians in their non‐breeding terrestrial environment and should be incorporated into future surveys and biodiversity monitoring programmes.     

Optimizing occupancy surveys by maximizing detection probability: application to amphibian monitoring in the Mediterranean region

• Setting up effective conservation strategies requires the precise determination of the targeted species’ distribution area and, if possible, its local abundance. However, detection issues make these objectives complex for most vertebrates. The detection probability is usually <1 and is highly dependent on species phenology and other environmental variables. The aim of this study was to define an optimized survey protocol for the Mediterranean amphibian community, that is, to determine the most favorable periods and the most effective sampling techniques for detecting all species present on a site in a minimum number of field sessions and a minimum amount of prospecting effort. We visited 49 ponds located in the Languedoc region of southern France on four occasions between February and June 2011. Amphibians were detected using three methods: nighttime call count, nighttime visual encounter, and daytime netting. The detection nondetection data obtained was then modeled using site‐occupancy models. The detection probability of amphibians sharply differed between species, the survey method used and the date of the survey. These three covariates also interacted. Thus, a minimum of three visits spread over the breeding season, using a combination of all three survey methods, is needed to reach a 95% detection level for all species in the Mediterranean region. Synthesis and applications: detection nondetection surveys combined to site occupancy modeling approach are powerful methods that can be used to estimate the detection probability and to determine the prospecting effort necessary to assert that a species is absent from a site.

     

Spatially explicit estimation of occupancy,detection probability and survey effort needed to inform conservation planning

Aim It is increasingly recognized the importance of accounting for imperfect detection in species distribution modelling and conservation planning. However, the integration of detectability into a spatially explicit frame has received little attention. We aim (1) to show how to develop distribution maps of both detection probability and survey effort required to reliably determine a species presence/absence and (2) to increase awareness of the spatial variation of detection error inherent in studies of species occurrence. Location North‐western Spain. Methods  We registered the presence/absence of the endangered Egyptian vulture (Neophron percnopterus) in 213 surveys performed in 40 of 104 territories once known to be occupied. We model simultaneously both detection probability and occurrence, using site occupancy modelling. With the resulting regression equations, we developed distribution maps of both detection probability and required sampling effort throughout the area. Results Of the studied territories, 72.5% were detected as occupied, but after accounting for imperfect detection, the proportion of sites truly occupied was 79%. Detectability decreased in territories with higher topographical irregularity and increased with both the time of day of the survey and the progress of the season. Spatial distribution of detectability showed a mainly north–south gradient following the distribution of slope in the area. The likelihood of occupancy increased with rockier, less forested surface and less topographical irregularity within the territory. A minimum of five surveys, on average, are needed to assess, with 95% probability, the occupancy status of a site, ranging from ≤ 3 to > 24 visits/territory depending on survey‐ and site‐specific features. Main conclusions Accounting for detectability and its sources of variation allows us to elaborate distribution maps of detectability‐based survey effort. These maps are useful tools to reliably assess (e.g. with 95% probability) occupancy status throughout a landscape and provide guidance for species conservation planning.     

Site occupancy dynamics of northern spotted owls in managed interior Douglas fir forests,California, USA, 1995–2009

Northern spotted owls (Strix occidentalis caurina) have received intense research and management interest since their listing as a threatened species by the United States Fish and Wildlife Service in 1990. For example, public and private forest managers in the Pacific Northwest, USA, conduct surveys to determine presence or absence of spotted owls prior to timber harvest operations. However, although recently developed statistical methods have been applied to presence–absence data collected during research surveys, the effectiveness of operational surveys for detecting spotted owls and evaluating site occupancy dynamics is not known. We used spotted owl survey data collected from 1995 to 2009 on a study area in interior northern California, USA, to evaluate competing occupancy models from Program PRESENCE using Akaike's Information Criterion (AIC). During 1,282 individual surveys, we recorded 480 spotted owl detections (37.4%) and 13 barred owl (1.0%) detections. Average per visit detection probability (85% CL) for single and paired spotted owls was 0.93 (0.90–0.96) for informed daytime, stand-based searches and 0.47 (0.43–0.51) for nighttime, station-based surveys (estimated from the best model); the average per visit detection probability from the null model was 0.67 (0.64–0.70). Average pair-only detection probabilities were 0.86 (0.81–0.90) for informed daytime, stand-based searches and 0.23 (0.18–0.29) for nighttime, station-based surveys; the average per visit detection probability from the null model was 0.63 (0.58–0.68). Site occupancy for any owl declined from 0.81 (0.59–0.93) in 1995 to 0.50 (0.39–0.60) in 2009; pair occupancy declined from 0.75 (0.56–0.87) to 0.46 (0.31–0.61). Our results suggest that a combination of 1 informed stand and 2 station-based operational surveys can support determinations of spotted owl site status (either a single or a pair) at desired levels of confidence. However, our information was collected in an area where barred owls were rarely detected. Surveys conducted in areas that support well-established barred owl populations are likely to be less effective for determining presence or absence of spotted owls and may require more surveys and/or different survey methods to determine site status with confidence. © 2012 The Wildlife Society.     

Effect of detection heterogeneity in occupancy‐detection models: an experimental test of time‐to‐first‐detection methods

Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time‐to‐first‐detection (TTD) occupancy models have been proposed as a cost–effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy‐detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala Phascolarctos cinereus populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness‐of‐fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy‐detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness‐of‐fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy‐detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.     

Effectiveness and utility of acoustic recordings for surveying tropical birds

ABSTRACT Although acoustic recordings have recently gained popularity as an alternative to point counts for surveying birds, little is known about the relative performance of the two methods for detecting tropical bird species across multiple vegetation types. During June and July 2008, we collected species detection/nondetection data to compare the performance of a quadraphonic acoustic recording system and point counts for estimating species richness and composition and detection probabilities of 15 rare, moderately common, and common tropical bird species across six structurally distinct vegetation types (coastal dune scrub, mangrove, low‐stature deciduous thorn forest, early and late successional medium‐stature semievergreen forest, and grazed pastures) in the northern Yucatan Peninsula. We selected five rare species endemic to the Yucatan Peninsula and 10 moderately common and common species that also occur in other tropical regions. Species richness and composition did not differ between survey methods in any of the vegetation types. At the population level, however, we found support for an effect of method on detection probability for most species. For 13 species, regardless of their abundance, acoustic recordings yielded detection probabilities as high as or higher than those for point counts across all vegetation types. The remaining two species were better detected by point counts in pastures and coastal scrub, where greater visibility likely improved sightings of these species. However, these species were detected as well as or better by acoustic recordings in forests and mangroves where detections were primarily auditory. In tropical regions where experienced field observers may not be available and funding for field surveys may be limited, acoustic recordings offer a practical solution for determining species richness and composition and the occupancy patterns of most species. However, for some species, a combination of methods will provide the most reliable data. Regardless of the method selected, analyses that account for variation in detection probability among vegetation types will be necessary because most species in our study demonstrated vegetation‐dependent detection probabilities.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.     

Optimising camera trap surveys for the Carpentarian Pseudantechinus (Pseudantechinus mimulus) in northwest Queensland

The Carpentarian Pseudantechinus (Pseudantechinus mimulus) is a poorly studied dasyurid marsupial that inhabits rocky outcrops in the Mount Isa Inlier bioregion in Queensland and the Gulf Coastal and Gulf Fall and Uplands bioregions in the Northern Territory. It is readily detected by passive infrared triggered camera traps (‘camera traps’). Camera trap data can be used to develop detection probability estimates from which activity patterns can be inferred, but no effort has previously been made to determine changes in the detectability of P. mimulus throughout the year. We undertook a 13-month baited camera trap survey across nine sampling periods at 60 locations of known historic presence or nearby suitable habitat to assess the change in detection rates and detection probabilities of P. mimulus across a year. Detection probabilities were calculated from camera trap data within a single-species, multi-season occupancy framework to determine optimal survey timing. Detection probability data were used to calculate the likelihood of false absences to determine optimal survey duration. We recorded 2493 detections of P. mimulus over 10 966 camera days. Detection probability ranged from 0.009 to 0.179 and was significantly higher from April to October than from November to March. The likelihood of false absences varied by sampling period and desired level of confidence. We find that camera trap surveys for P. mimulus are best conducted from April to October, but optimal survey duration is dependent upon the time of year and desired level of confidence that an observed absence from a given site reflects a true absence at that site. Attaining a minimum of 80% confidence of absence requires as few as 9 days of survey effort in May to 16 days of survey effort in October.     

Detection probabilities of two introduced frogs in Hawaii: implications for assessing non-native species distributions

Two nonnative Caribbean frogs, the Puerto Rican coqui and the Cuban greenhouse frog, recently invaded Hawaii. Because of its louder breeding call, management efforts have focused on the coqui, while little has been done to address the more cryptic greenhouse frog, even though it may be as widespread and have similar ecological impacts. The goal of this research was to determine the distribution and detection probability of both species on the island of Hawaii. We conducted a breeding call presence/absence survey at 446 sites every 2 km along major road networks. We re-surveyed 125 sites twice to determine detection and occupancy probabilities. Greenhouse frog detection probabilities (0.24, 0.29, 0.48, for each of the three visits, respectively) were lower than coqui detection probabilities (0.58, 0.73, 0.50, respectively) and increased with visits while those of the coqui did not. Greenhouse frog detection probabilities were lower in the presence of coquis for the first two surveys (0.12, 0.14) than in sites with greenhouse frogs alone (0.41), while greenhouse frogs had no effect on the detection of coquis. Site occupancy estimates for the greenhouse and coqui frog were 0.35 and 0.31, respectively, suggesting the species are similarly widespread. Results suggest multiple visits to sites are required to detect the greenhouse frog. Furthermore, results suggest that accounting for detectability is essential when determining the extent of invasion of cryptic species.     

Using bioacoustics to enhance the efficiency of spotted owl surveys and facilitate forest restoration

The California spotted owl (Strix occidentalis occidentalis) is an older-forest associated species that resides at the center of forest management planning in the Sierra Nevada and Southern California, USA, which are experiencing increasingly large and severe wildfires and drought-related tree mortality. We leveraged advances in passive acoustic survey technologies to develop an acoustically assisted survey design that could increase the efficiency and effectiveness of project-level surveys for spotted owls, allowing surveys to be completed in a single year instead of in multiple years. We deployed an array of autonomous recording units (ARUs) across a landscape and identified spotted owl vocalizations in the resulting audio using BirdNET. We then evaluated spatio-temporal patterns in spotted owl vocalizations near occupied territories and the ability of a crew naïve to the location of occupied territories to locate spotted owls based on patterns of acoustic detections. After only 3 weeks of acoustic surveys, ≥1 ARU within 750 m of all 17 occupied territories obtained spotted owl detections across ≥2 nights. When active surveys using broadcast calling were conducted near ARUs with spotted owl detections by surveyors naïve to territory occupancy status and locations, surveyors located owls in 93% to 100% of occupied territories with ≤3 surveys. To further improve the efficiency of spotted owl surveys, we developed a statistical model to identify and prioritize areas across the Sierra Nevada for different survey methods (active only, acoustically assisted, no surveys) based on the expected probability of occupancy predicted from remotely sensed measurements of tree height and historical occupancy. Depending on managers' tolerance for false negatives, this model could help identify large areas that might not benefit from surveys based on low expected occupancy probabilities and areas where acoustically assisted surveys might enhance survey effectiveness and efficiency. Collectively, these findings can help managers streamline the survey process and thus increase the pace of forest restoration while minimizing potential near-term adverse effects on California spotted owls.     

Testing the utility of species distribution modelling using Random Forests for a species in decline

Habitat suitability estimates derived from species distribution models (SDMs) are increasingly used to guide management of threatened species. Poorly estimating species’ ranges can lead to underestimation of threatened status, undervaluing of remaining habitat and misdirection of conservation funding. We aimed to evaluate the utility of a SDM, similar to the models used to inform government regulation of habitat in our study region, in estimating the contemporary distribution of a threatened and declining species. We developed a presence‐only SDM for the endangered New Holland Mouse (Pseudomys novaehollandiae) across Victoria, Australia. We conducted extensive camera trap surveys across model‐predicted and expert‐selected areas to generate an independent data set for use in evaluating the model, determining confidence in absence data from non‐detection sites with occupancy and detectability modelling. We assessed the predictive capacity of the model at thresholds based on (1) sum of sensitivity and specificity (SSS), and (2) the lowest presence threshold (LPT; i.e. the lowest non‐zero model‐predicted habitat suitability value at which we detected the species). We detected P. novaehollandiae at 40 of 472 surveyed sites, with strong support for the species’ probable absence from non‐detection sites. Based on our post hoc optimised SSS threshold of the SDM, 25% of our detection sites were falsely predicted as non‐suitable habitat and 75% of sites predicted as suitable habitat did not contain the species at the time of our survey. One occupied site had a model‐predicted suitability value of zero, and at the LPT, 88% of sites predicted as suitable habitat did not contain the species at the time of our survey. Our findings demonstrate that application of generic SDMs in both regulatory and investment contexts should be tempered by considering their limitations and currency. Further, we recommend engaging species experts in the extrapolation and application of SDM outputs.     

Site Occupancy Dynamics of Northern Spotted Owls in the Eastern Cascades,Washington, USA, 1990–2003

Abstract: Northern spotted owls (Strix occidentalis caurina) have received intense research and management interest since their listing as a threatened species by the United States Fish and Wildlife Service in 1990. Several spotted owl (Strix occidentalis) response variables have been examined in various investigations, but recent advances in statistical modeling permit evaluations of temporal and spatial variability in site occupancy, local-extinction, and colonization probabilities while incorporating imperfect detection probabilities. Following recent work by other researchers on site occupancy dynamics of spotted owls in Oregon, USA, we evaluated temporal variability of detection, occupancy, local-extinction, and colonization probabilities for spotted owls, as well as potential influences of barred owl (Strix varia) presence on these parameters. We used spotted owl survey data collected from 1990 to 2003 on a study area in the eastern Cascades Mountains, Washington, USA, to compare competing occupancy models from Program PRESENCE using Akaike's Information Criterion. Detection probabilities for individual spotted owls ranged from 0.54 to 0.80 if barred owls were not detected during the survey season and from 0.19 to 0.71 if barred owls were detected during the survey season. Pair detection probabilities ranged from 0.27 to 0.67 if barred owls were not detected during an individual survey and from 0.09 to 0.36 if barred owls were detected during an individual survey. During the study, site occupancy probabilities for spotted owl pairs declined by approximately 50%. For all spotted owls, both singles and pairs, site occupancy probabilities declined moderately during the study. Barred owl presence was negatively associated with spotted owl detection probabilities, and it had a positive association with local-extinction probabilities for all spotted owls, both singles and pairs. Given that our study area has supported higher densities of barred owls for longer periods than other study areas, our results may provide insight into how barred owls have influenced spotted owl site occupancy dynamics in adjacent British Columbia, Canada, or will influence spotted owl site occupancy dynamics in Oregon and California, USA, in the future.     

Modelling broad‐scale wolverine occupancy in a remote boreal region using multi‐year aerial survey data

Aim

We used data from aerial surveys of wolverine tracks collected in seven winters over a 10‐year period (2003–2012) within a 574,287 km² study area to evaluate the broad‐scale pattern of wolverine occurrence across a remote northern boreal forest region, identifying areas of high and low occupancy.

Location

Northern Ontario, Canada.

Taxon

Wolverine (Gulo gulo Linnaeus, 1758).

Methods

We collected wolverine tracks and observations in 100‐km² hexagonal survey units, making a total of 6,664 visits to 3,039 units, visiting each 1–9 times. We used hierarchical Bayesian occupancy modelling to model wolverine occurrence, and included covariates with the potential to affect detection and/or occupancy probability of wolverines.

Results

we detected wolverines on 946 visits, 14.2% of total visits. Probability of detecting a wolverine varied among years and between the two ecozones in the study area. Wolverine occupancy was negatively related to two important covariates, the geographical coordinate Easting and thawing degree‐days. A site occupancy probability map indicated that wolverine occupancy probabilities were highest, and standard error lowest, in the western and northern portions of the study area.

Main conclusions

The occupancy framework enabled us to use observation data from tracks of this elusive, wide‐ranging carnivore over a vast, remote area while explicitly considering detectability and spatial autocorrelation, yielding a map of probable wolverine distribution in northern Ontario that would not be possible using other methods of detection across a large region. With resource development pressures increasing in this globally significant region in the face of a changing climate, it is important to monitor changes in distribution of species like wolverines that have low population growth rates, large spatial requirements and sensitivity to human disturbance. This study demonstrates a relatively cost‐effective and non‐invasive alternative to monitoring based on wolverine harvest records, which have not been available since 2009 in Ontario due to changes in the provincial regulatory regime for this threatened species.     

Effects of point‐count duration on estimated detection probabilities and occupancy of breeding birds

Increasingly, point‐count data are used to estimate occupancy, the probability that a species is present at a given location; occupancy accounts for imperfect detection, the probability that a species is detected given that it is present. To our knowledge, effects of sampling duration on inferences from models of bird occupancy have not been evaluated. Our objective was to determine whether changing count duration from 5 to 8 min affected inferences about the occupancy of birds sampled in the Chesapeake Bay Lowlands (eastern United States) and the central and western Great Basin (western United States) in 2012 and 2013. We examined the proportion of species (two doves, one cuckoo, two swifts, five hummingbirds, 11 woodpeckers, and 122 passerines) for which estimates of detection probability were ≥ 0.3. For species with single‐season detection probabilities ≥ 0.3, we compared occupancy estimates derived from 5‐ and 8‐min counts. We also compared estimates for three species sampled annually for 5 yr in the central Great Basin. Detection probabilities based on both the 5‐ and 8‐min counts were ≥ 0.3 for 40% ± 3% of the species in an ecosystem. Extending the count duration from 5 to 8 min increased the detection probability to ≥ 0.3 for 5% ± 0.5% of the species. We found no difference in occupancy estimates that were based on 5‐ versus 8‐min counts for species sampled over two or five consecutive years. However, for 97% of species sampled over 2 yr, precision of occupancy estimates that were based on 8‐min counts averaged 12% ± 2% higher than those based on 5‐min counts. We suggest that it may be worthwhile to conduct a pilot season to determine the number of locations and surveys needed to achieve detection probabilities that are sufficiently high to estimate occupancy for species of interest.     

Red-Shouldered Hawk Occupancy Surveys in Central Minnesota,USA

ABSTRACT Forest-dwelling raptors are often difficult to detect because many species occur at low density or are secretive. Broadcasting conspecific vocalizations can increase the probability of detecting forest-dwelling raptors and has been shown to be an effective method for locating raptors and assessing their relative abundance. Recent advances in statistical techniques based on presence—absence data use probabilistic arguments to derive probability of detection when it is < 1 and to provide a model and likelihood-based method for estimating proportion of sites occupied. We used these maximum-likelihood models with data from red-shouldered hawk (Buteo lineatus) call-broadcast surveys conducted in central Minnesota, USA, in 1994–1995 and 2004–2005. Our objectives were to obtain estimates of occupancy and detection probability 1) over multiple sampling seasons (yr), 2) incorporating within-season time-specific detection probabilities, 3) with call type and breeding stage included as covariates in models of probability of detection, and 4) with different sampling strategies. We visited individual survey locations 2–9 times per year, and estimates of both probability of detection (range = 0.28-0.54) and site occupancy (range = 0.81-0.97) varied among years. Detection probability was affected by inclusion of a within-season time-specific covariate, call type, and breeding stage. In 2004 and 2005 we used survey results to assess the effect that number of sample locations, double sampling, and discontinued sampling had on parameter estimates. We found that estimates of probability of detection and proportion of sites occupied were similar across different sampling strategies, and we suggest ways to reduce sampling effort in a monitoring program.     

Dealing with detection error in site occupancy surveys: what can we do with a single survey?

Aim Site occupancy probabilities of target species are commonly used in various ecological studies, e.g. to monitor current status and trends in biodiversity. Detection error introduces bias in the estimators of site occupancy. Existing methods for estimating occupancy probability in the presence of detection error use replicate surveys. These methods assume population closure, i.e. the site occupancy status remains constant across surveys, and independence between surveys. We present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or independence. In place of the closure assumption, this method requires covariates that affect detection and occupancy.Methods Penalized maximum-likelihood method was used to estimate the parameters. Estimability of the parameters was checked using data cloning. Parametric boostrapping method was used for computing confidence intervals.Important findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable, situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not met. This method saves significant amounts of time, energy and money in ecological surveys without sacrificing statistical validity. Further, we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.     

Improving geographically extensive acoustic survey designs for modeling species occurrence with imperfect detection and misidentification

Acoustic recording units (ARUs) enable geographically extensive surveys of sensitive and elusive species. However, a hidden cost of using ARU data for modeling species occupancy is that prohibitive amounts of human verification may be required to correct species identifications made from automated software. Bat acoustic studies exemplify this challenge because large volumes of echolocation calls could be recorded and automatically classified to species. The standard occupancy model requires aggregating verified recordings to construct confirmed detection/non‐detection datasets. The multistep data processing workflow is not necessarily transparent nor consistent among studies. We share a workflow diagramming strategy that could provide coherency among practitioners. A false‐positive occupancy model is explored that accounts for misclassification errors and enables potential reduction in the number of confirmed detections. Simulations informed by real data were used to evaluate how much confirmation effort could be reduced without sacrificing site occupancy and detection error estimator bias and precision. We found even under a 50% reduction in total confirmation effort, estimator properties were reasonable for our assumed survey design, species‐specific parameter values, and desired precision. For transferability, a fully documented r package, OCacoustic, for implementing a false‐positive occupancy model is provided. Practitioners can apply OCacoustic to optimize their own study design (required sample sizes, number of visits, and confirmation scenarios) for properly implementing a false‐positive occupancy model with bat or other wildlife acoustic data. Additionally, our work highlights the importance of clearly defining research objectives and data processing strategies at the outset to align the study design with desired statistical inferences.     

Use of environmental DNA to detect Eastern Sand Darter (Ammocrypta pellucida Putnam, 1863) in large Laurentian Great Lakes embayments

A single-species environmental DNA (eDNA) method was developed to sample for a small, benthic rare species, Eastern Sand Darter (Ammocrypta pellucida Putnam, 1863) in two large Lake Ontario embayments. Summer water sampling allowed for: (a) surveys of habitats (Wellers Bay) where traditional fish sampling gear could not be used; and, (b) a comparison between eDNA and seining-based detection probabilities at known occupied habitats (West Lake). In 2018, replicate (n = 3) 1 L water samples were collected from 90 Wellers Bay sites and 71 West Lake sites. A site-occupancy model, a hierarchical logistic regression model, was fitted to determine site occupancy, sample occupancy (presence of Eastern Sand Darter DNA in a water sample) and probability of detection (p) based on replicate quantitative polymerase chain reaction (qPCR) results for each water sample. Eastern Sand Darter was detected at 10 West Lake sites, but not from Wellers Bay. Mean site occupancy was 0.31 (0.12–0.70; 95% CLs), mean sample occupancy was 0.28 (0.09–0.58; 95% CLs), and mean detection probability in a subsample (i.e., successful qPCR amplification) given it was present was 0.40 (0.25–0.55; 95% CLs). While the eDNA method successfully detected Eastern Sand Darter from known occupied areas in West Lake, it was not more effective for assessing local site occupancy than traditional sampling methods, such as the seine.