Estimated Occupancy Probabilities Research Articles

Response of dholes to prey availability and human disturbance in space and time in Southern India

Understanding spatial and temporal behavior of large carnivores is critical to developing conservation strategies that mitigate the limiting factors of prey availability and human disturbance. Dholes (Cuon alpinus) are endangered, pack-living canids persisting in tropical forests of Asia, yet significant knowledge gaps remain about their basic ecology. We estimated spatial occurrence and temporal activity of dholes relative to prey availability, anthropogenic disturbance, and landscape features using camera traps in two protected areas in Southern India. Estimated detection probability of dholes was 0.14 (95 % CI: 0.11, 0.18), while estimated occupancy probability was 0.33 (95 % CI: 0.26, 0.40). Prey availability was the strongest driver of spatial occurrence of dholes, followed by multiple measures of human disturbance. Dholes responded to human activity and human infrastructure differently in space and time, which appeared to free them to overlap with their primary prey. Dholes avoided roads spatially, avoided livestock in space and time, and avoided human activity temporally. Dholes exhibited high temporal overlap with chital, barking deer, and wild pig activity, which are likely important prey. We recommend regulating livestock presence within protected areas and limiting new road development within habitat occupied by endangered species. A proposed reservoir project to create drinking water and electricity would inundate important forested habitat for dholes along the River Cauvery where occupancy was high. This removal of habitat would significantly impact dhole presence in this landscape. Our findings advance understanding of behavioral responses by an understudied, endangered large carnivore to its primary limiting factors: prey and human disturbance.

What can occupancy models gain from time-to-detection data?

The time taken to detect a species during site occupancy surveys contains information about the observation process. Accounting for the observation process leads to better inference about site occupancy. We explore the gain in efficiency that can be obtained from time-to-detection (TTD) data and show that this model type has a significant benefit for estimating the parameters related to detection intensity. However, for estimating occupancy probability parameters, the efficiency improvement is generally very minor. To explore whether TTD data could add valuable information when detection intensities vary between sites and surveys, we developed a mixed exponential TTD occupancy model. This new model can simultaneously estimate the detection intensity and aggregation parameters when the number of detectable individuals at the site follows a negative binomial distribution. We found that this model provided a much better description of the occupancy patterns than conventional detection/nondetection methods among 63 bird species data from the Karoo region of South Africa. Ignoring the heterogeneity of detection intensity in the TTD model generally yielded a negative bias in the estimated occupancy probability. Using simulations, we briefly explore study design trade offs between numbers of sites and surveys for different occupancy modeling strategies.

What happened to the house mouse: Modelling the occupancy of Mus musculus in an argentine city considering its urban growth

This work aimed to estimate occupancy probabilities of Mus musculus (house mouse) as a function of environmental (NDVI and distance to water bodies) and anthropogenic (proportion of paved streets, distances to illegal dumpsites and railways) variables and to explore the differences in occupancy according to temporal changes of urban growth. We used occupancy models to obtain predictive maps of M. musculus distribution in habitats with open spatial arrangements of the city of Río Cuarto in periods 2001-2003 and 2020, which was validated on the ground. The obtained map for the first period showed that the highest occupancy probabilities agreed with paved areas following a gradient to the outskirt of the city, where the lowest occupancy values coincided with those areas without any buildings and with high values of vegetation cover. The obtained map for 2020 conditional on the actual presence of an open spatial arrangement habitat, showed that the house mouse expanded its distribution range in the city, with low-medium probability values in zones where it was absent in the previous period. Data obtained from field validation would support the reliability of our predictive map. This work reinforces the importance of integrating spatial analysis, environmental and anthropogenic variables and occupancy data in an urban area. Mus musculus expanded its range of distribution in the city accompanying the increase in urbanization that Río Cuarto has experienced in the last 20 years. Considering the importance of M. musculus as an indicator of environmental degradation in urban areas, local authorities have now a spatially explicit tool to prioritize resources to detect vacant lots located in those areas predicted as mediumhigh occupancy probabilities and direct control policies on them.

Hunting and water scarcity affect habitat occupancy by peccaries (Tayassu pecari and Pecari tajacu) in Calakmul, Mexico

Abstract The white-lipped peccary (WLP; Tayassu pecari) and the collared peccary (CP; Pecari tajacu) are social ungulates of huge ecological and economic importance. We determined the habitat occupancy for peccaries in a rural community bordering the Calakmul Biosphere Reserve in Campeche, Mexico. Twenty-eight stratified sampling points were randomly placed in the study area during a rainy and a dry season, where the presence of both peccary species was measured in relation to three ecological variables (habitat type, presence of natural predators, and water availability) and one anthropogenic variable (hunting). Ten sampling points were established with camera traps (total days/camera traps = 2268), and 18 sampling points were plots of 20 m2 to detect feces and/or footprints. To assess the relationship between both species’ presence and the selected variables, models of habitat occupancy were constructed using a binary matrix of detection/non-detection using the PRESENCE program. For WLP and CP, the respective estimated occupancy probabilities were 30 and 40% in the rainy season and 88 and 44% in the dry season. Our results suggest that occupancy by WLP is affected by habitat type and predators in the rainy season and by water availability and hunting in the dry season. Conversely, for CP, occupancy is affected by water availability and hunting in the rainy season, and by habitat type and predators in the dry season. Thus, hunting negatively affects the way that WLP occupy specific habitats, such as floodplain forest and medium sub-deciduous forest, particularly during periods of water scarcity when the species is more vulnerable to hunting.

Sparse Tensor-Based Multiscale Representation for Point Cloud Geometry Compression.

This study develops a unified Point Cloud Geometry (PCG) compression method through the processing of multiscale sparse tensor-based voxelized PCG. We call this compression method SparsePCGC. The proposed SparsePCGC is a low complexity solution because it only performs the convolutions on sparsely-distributed Most-Probable Positively-Occupied Voxels (MP-POV). The multiscale representation also allows us to compress scale-wise MP-POVs by exploiting cross-scale and same-scale correlations extensively and flexibly. The overall compression efficiency highly depends on the accuracy of estimated occupancy probability for each MP-POV. Thus, we first design the Sparse Convolution-based Neural Network (SparseCNN) which stacks sparse convolutions and voxel sampling to best characterize and embed spatial correlations. We then develop the SparseCNN-based Occupancy Probability Approximation (SOPA) model to estimate the occupancy probability either in a single-stage manner only using the cross-scale correlation, or in a multi-stage manner by exploiting stage-wise correlation among same-scale neighbors. Besides, we also suggest the SparseCNN based Local Neighborhood Embedding (SLNE) to aggregate local variations as spatial priors in feature attribute to improve the SOPA. Our unified approach not only shows state-of-the-art performance in both lossless and lossy compression modes across a variety of datasets including the dense object PCGs (8iVFB, Owlii, MUVB) and sparse LiDAR PCGs (KITTI, Ford) when compared with standardized MPEG G-PCC and other prevalent learning-based schemes, but also has low complexity which is attractive to practical applications.

Coffee plantations, hurricanes and avian resiliency: insights from occupancy, and local colonization and extinction rates in Puerto Rico

Insights on impacts and resiliency of avian species with respect to hurricanes in the Caribbean have largely focused on responses measured in protected habitats. We assessed avian responses in non-protected habitat, specifically shade-restored coffee plantations, because their structural complexity retains many attributes of secondary forests, and may contribute to landscape scale species resiliency. We tallied species richness and estimated occupancy probability of 12 resident avian species, after adjusting for imperfect detection, to assess the impact of hurricane Maria (20 September 2017). For five of those species, we also estimated local colonization and extinction probabilities to assess their prospect of rebounding (resiliency) in the context of two stages of shade restoration. We used survey data collected March-June 2015–2017 (pre-hurricane) and 2018 (post-hurricane) in 58 coffee farms and satellite imagery to assess vegetation structure. Restored farms were grouped into two categories based on time-since-restoration: newly-restored and fully-restored. We predicted that mean percent forest cover in fully-restored farms (~30–40%) would revert to levels in newly-restored farms (<15%), with concomitant changes in occupancy by avian species. As predicted, mean percent forest cover (16.17±4.27%) in fully-restored farms post-hurricane reverted to pre-hurricane levels in newly-restored farms (15.00±5.61%). The loss represented 30–38% relative to the pre-hurricane cover levels. Detections of focal species dropped an average of 41% post-hurricane, with associated reductions in occupancy for 9/11 species. Occupancy of the Puerto Rican Bullfinch and Puerto Rican Spindalis reverted to levels detected in newly-restored plantations prior to the hurricane as predicted. Prospects of rebounding were more likely for species with invariant or increases in colonization probability (e.g., Yellow-faced Grassquit, Northern Mockingbird, Puerto Rican Spindalis). Rebounding for frugivores like the Puerto Rican Bullfinch would be protracted given that colonization rates dropped from 0.56±0.12 (pre-hurricane) to 0.04±0.2 (post-hurricane), regardless of restoration stage. Our work showed that the avian community associated with restored coffee farms exhibited a high degree of ecological resistance as the similarity in species composition before and after the hurricane was 81%, and all 12 focal species continued to occupy farms under both restoration stages. The prospect of the focal species to rebound (resiliency) was species-specific, and in some cases, mediated by their affinity to a particular farm restoration stage. The strength of hurricanes is projected to intensify with global warming. Pockets of undamaged or partially damaged shade-grown or fully-restored coffee plantations may contribute to species resiliency by increasing landscape level habitat redundancy, and facilitate habitat shifts to secure food resources or harbor source populations to colonize recovering, hurricane-damaged habitat tracts.

Guest or pest? Spatio-temporal occurrence and effects on soil and vegetation of the wild boar on Elba island

Where allochthonous large mammals, such as the wild boars, occur in high density, human-wildlife conflicts may arise. Thus, assessing their spatio-temporal patterns is paramount to their management. We studied the wild boars on Elba island, Italy, where they have been introduced and are perceived as pests to address their occurrence and impact of foraging on natural habitat. We surveyed the western island with three camera trapping surveys within one year. We found that the species' estimated occupancy probability was higher in summer-autumn (0.75 ± 0.14) and winter-early spring (0.70 ± 0.10) than in spring–summer (0.53 ± 0.15), whereas detection probability did not vary. Occupancy was significantly associated with lower elevation and woodland cover. Lower site use of wild boars during spring–summer might reflect lower food availability in this season and/or boars’ movements towards landfarms outside the sampled area. Detectability increased with proximity to roads during spring–summer and decreased with humans’ relative abundance in other periods. Boars were mainly nocturnal, with decreasing overlap with human activity when human presence was higher in the park. Soil degradation caused by wild boars was higher in pine plantations, which is the cover with a lower conservation interest. The spatio-temporal activity of wild boars on the island appears driven by seasonal preferences for food-rich cover and avoidance of human disturbance. The lowered site use in months with lower resources could partially reflect increased proximity to settled and farmed areas, which may trigger crop-raiding and the negative perception by residents.

Viewpoints Planning for Active 3-D Reconstruction of Profiled Blades Using Estimated Occupancy Probabilities (EOP)

Reconstructing 3-D models of blades plays an increasingly important role in manufacturing. However, the scanning equipment cannot acquire a complete model of a blade with one scanning due to its discontinuous and complex spatial surface. How to plan the viewpoints in presence of the thin walled and free-form properties of blades is a challenging task. In this article, we propose a novel viewpoint planning algorithm using estimated occupancy probabilities. Existing viewpoint planning methods do not consider the enough overlaps, which are important for data registration. We predict surface overlaps using an estimated OctoMap. OctoMap is an efficient probabilistic framework for 3-D occupancy grid mapping. However, the occupancy probabilities of occluded voxels in the original OctoMap remain unknown, which makes it impossible to calculate the overlap of candidate viewpoints. Hence, a recursive Bayesian filter is designed to estimate occupancy probabilities of occluded voxels. With more specific occupancy probabilities, the overlap of a viewpoint is predicted by the ray tracing technology. Experiments on four different profiled blades synthetic datasets show that our algorithm outperforms existing methods in terms of controlling overlap rate. The efficiency of our method is confirmed by real world experiments with low registration failure frequency in reconstruction.

Influence of lure choice and survey duration on scent stations for carnivore surveys

AbstractNoninvasive, camera‐based, scent station surveys have become a common approach to estimate population parameters for mammalian carnivores. Many carnivores are particularly sensitive to olfactory cues; and, as such, the quality and quantity of odor attractant used during surveys can significantly affect the accuracy and precision of the survey. Additionally, survey length is also an important consideration because many mammalian predators are highly mobile and elusive in nature. Using scent station surveys in autumn 2013 and 2014 on the Savannah River Site, Aiken, South Carolina, USA, we tested the effects of 5 lures: fatty acid, fish oil, synthetic fermented egg, beaver castor, and skunk essence on visitation rates, visitation probability, and latency to visitation of multiple predator species. We also estimated occupancy probability for 2 carnivore species using different survey lengths to determine the effect of survey period on the precision of occupancy estimates. We found that skunk essence had greater visitation probability and visits than other lures evaluated. Species‐specific bait‐preference models revealed that raccoons (Procyon lotor) were more likely to visit skunk essence, and coyotes (Canis latrans) were less likely to visit fish oil as compared with fatty acid. Latency to visitation ranged from 104.7 to 112.1 hours and did not vary among scents. Longer survey durations resulted in more precise estimates of occupancy and detection probability. Our results suggest a wide range of scents commonly used for carnivore capture may perform as well as, or better than, fatty acid for noninvasive carnivore surveys. Further, study designs should carefully consider the duration of scent‐station surveys depending on the level of precision desired in estimates of occupancy and detection probability. © 2019 The Wildlife Society.

Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques

The American marten Martes americana is a species of conservation concern in the northeastern United States due to widespread declines from over-harvesting and habitat loss. Little information exists on current marten distribution and how landscape characteristics shape patterns of occupancy across the region, which could help develop effective recovery strategies. The rarity of marten and lack of historical distribution records are also problematic for region-wide conservation planning. Expert opinion can provide a source of information for estimating species–landscape relationships and is especially useful when empirical data are sparse. We created a survey to elicit expert opinion and build a model that describes marten occupancy in the northeastern United States as a function of landscape conditions. We elicited opinions from 18 marten experts that included wildlife managers, trappers and researchers. Each expert estimated occupancy probability at 30 sites in their geographic region of expertise. We, then, fit the response data with a set of 58 models that incorporated the effects of covariates related to forest characteristics, climate, anthropogenic impacts and competition at two spatial scales (1.5 and 5 km radii), and used model selection techniques to determine the best model in the set. Three top models had strong empirical support, which we model averaged based on AIC weights. The final model included effects of five covariates at the 5-km scale: percent canopy cover (positive), percent spruce-fir land cover (positive), winter temperature (negative), elevation (positive) and road density (negative). A receiver operating characteristic curve indicated that the model performed well based on recent occurrence records. We mapped distribution across the region and used circuit theory to estimate movement corridors between isolated core populations. The results demonstrate the effectiveness of expert-opinion data at modeling occupancy for rare species and provide tools for planning marten recovery in the northeastern United States.

Microhabitat Factors Associated with Occupancy of Songbirds in Suburban Forest Fragments in the Eastern United States

Forests in the eastern United States have become fragmented by urban development and agriculture, creating a landscape of remnant forest patches. Many bird species rely on these fragments for breeding habitat, but habitat selection in these patches is not well-understood. Our objective was to examine the effects of forest structure, native plants, and invertebrate biomass on the occupancy of an assemblage of common Eastern songbird species in suburban forest fragments. We collected data at 98 plots in remnant forest patches in Delaware and Maryland. Avian point counts were conducted three times per season between 15 May–7 August 2009–2010. We estimated occupancy probability, while accounting for imperfect detection, for nine common songbird species in order to understand how they are influenced by invertebrate biomass and vegetation characteristics. We ranked competing models using Akaike Information Criteria (AIC). Occupancy of six of our 10 candidate species was affected by forest structure, native plant density, or invertebrate biomass. Species we identified to have occupancy relationships with forest structure variables in suburban forest fragments appear to align well with habitat relationships that have been previously identified for the species in more forested areas. This supports that managing for structural characteristics associated with these species in more heavily forested areas could improve habitat quality for these species in suburban forest fragments as well. Occupancy of only one species we examined was related to native plants, suggesting vegetation structure, rather than composition, was a more important factor in occupancy.

Designing occupancy studies when false‐positive detections occur

Summary Recently, estimators have been developed to estimate occupancy probabilities when false‐positive detections occur during presence–absence surveys. Some of these estimators combine different types of survey data to improve estimates of occupancy. With these estimators, there is a trade‐off between the number of sample units surveyed, and the number and type of surveys at each sample unit. Guidance on efficient design of studies when false positives occur is unavailable. For a range of scenarios, I identified survey designs that minimized the mean square error of the estimate of occupancy. I considered an approach that uses one survey method and two observation states and an approach that uses two survey methods. For each approach, I used numerical methods to identify optimal survey designs when model assumptions were met and parameter values were correctly anticipated, when parameter values were not correctly anticipated and when the assumption of no unmodelled detection heterogeneity was violated. Under the approach with two observation states, false‐positive detections increased the number of recommended surveys, relative to standard occupancy models. If parameter values could not be anticipated, pessimism about detection probabilities avoided poor designs. Detection heterogeneity could require more or fewer repeat surveys, depending on parameter values. If model assumptions were met, the approach with two survey methods was inefficient. However, with poor anticipation of parameter values, with detection heterogeneity or with removal sampling schemes, combining two survey methods could improve estimates of occupancy. Ignoring false positives can yield biased parameter estimates, yet false positives greatly complicate the design of occupancy studies. Specific guidance for major types of false‐positive occupancy models, and for two assumption violations common in field data, can conserve survey resources. This guidance can be used to design efficient monitoring programmes and studies of species occurrence, species distribution or habitat selection, when false positives occur during surveys.

Community occupancy of herpetofauna in roadside ditches in a managed pine landscape

Aquatic habitat types embedded in managed forest can contribute ecological services and suitable conditions for numerous species despite departing from historical baselines. Although prevalent in the Atlantic Coastal Plain, roadside ditches adjacent to pine plantations have had few surveys of vertebrate diversity and little is known about local and landscape level effects of silvicultural activities on species assemblages. Our goal was to investigate richness and occupancy of amphibians and reptiles in an intensively managed forest landscape with a history of silvicultural alterations of aquatic habitat types, including ditching, draining, and periodic maintenance of ditches for optimizing loblolly pine (Pinus taeda) growth. We selected 15 roadside ditches that were maintained 3–17years earlier and were embedded in a matrix of pine plantations in eastern North Carolina, USA. We conducted repeated, visual encounter surveys of roadside ditches during 2012–2013 and detected 25 species of amphibians and reptiles 447 times including five species of statewide conservation concern. We used a Bayesian, hierarchical, community occupancy model with group-specific hyper-parameters to estimate occupancy probabilities and species richness while accounting for imperfect detection. With our model, we examined effects of time since ditch maintenance, amount of nearby mature forest, and amount of adjacent wetlands on species richness and occupancy. We predicted species would respond positively to an intermediate period of time since ditch maintenance and positively to landscape covariates related to mature forest and wetlands. Our model estimated species richness of anurans from 0.9 to 7.4 species/ditch segment, snakes and lizards from 0.8 to 9.0 species/ditch segment, and turtles from 0.9 to 5.1 species/ditch segment. Contrary to our predictions, occupancy of herpetofauna showed no evidence of a relationship to time since ditch maintenance, and landscape metrics only influenced occupancy of one turtle species. Detection probabilities were influenced by season for several anurans, snakes, and lizards, but not turtles. Our results indicate that aquatic habitat types embedded in managed forests that were hydrologically and structurally altered for silviculture can support local occupancy of a relatively diverse herpetofaunal community and that temporal proximity to ditch maintenance had little effect on occupancy or richness.

Avian response to green roofs in urban landscapes in the Midwestern USA

ABSTRACTGreen roofs present an opportunity to provide large areas of vegetation that could serve as bird habitat in urban areas. Point‐count surveys at 12 green‐roof study locations in the midwestern United States were conducted during the bird breeding season in 2010 and 2011. At each green roof location, birds were surveyed on building rooftops and at ground level around (&lt;200 m) each building. Data collection resulted in 771 sampling periods during which 2,973 species detections (1,315 for native songbirds) were recorded. We estimated occupancy probabilities for birds with single‐ and multi‐species occupancy models, which accounted for detection and allowed for community‐level summaries such as species richness. Twenty‐six noninvasive, native bird species were detected on the roofs, and the estimated mean richness of native songbird and woodpecker species for each green roof was 10–21. Most species (approx. 90%) observed on green roofs also were observed in surrounding landscapes, and species richness estimates and species‐specific occupancy probabilities were typically lower for green roofs than for surrounding landscapes. Our results indicate that green roofs may contribute to habitat for a subset of birds already occurring in urbanized landscapes. Although surrounding areas likely provide greater bird habitat than vegetation on green roofs, several native songbird, woodpecker, and waterfowl species use green roofs in urban landscapes; hence, green roofs have potential to contribute to bird habitat in urban areas and may help mitigate negative effects of urbanization on birds. © 2015 The Wildlife Society.

Penalized likelihood methods improve parameter estimates in occupancy models

Summary Occupancy models are employed in species distribution modelling to account for imperfect detection during field surveys. While this approach is popular in the literature, problems can occur when estimating the model parameters. In particular, the maximum likelihood estimates can exhibit bias and large variance for data sets with small sample sizes, which can result in estimated occupancy probabilities near 0 and 1 (‘boundary estimates’). In this paper, we explore strategies for estimating parameters based on maximizing a penalized likelihood. Penalized likelihood methods augment the usual likelihood with a penalty function that encodes information about what parameter values are undesirable. We introduce penalties for occupancy models that have analogues in ridge regression and Bayesian approaches, and we compare them to a penalty developed for occupancy models in prior work. We examine the bias, variance and mean squared error of parameter estimates obtained from each method on synthetic data. Across all of the synthetic data sets, the penalized estimation methods had lower mean squared error than the maximum likelihood estimates. We also provide an example of the application of these methods to point counts of avian species. Penalized likelihood methods show similar improvements when tested using empirical bird point count data. We discuss considerations for choosing among these methods when modelling occupancy. We conclude that penalized methods may be of practical utility for fitting occupancy models with small sample sizes, and we are releasing R code that implements these methods.

Mountaintop removal mining reduces stream salamander occupancy and richness in southeastern Kentucky (USA)

Mountaintop removal mining with valley fills (MTR/VF) is a ubiquitous form of land conversion in central Appalachia, USA and threatens the integrity of stream ecosystems. We investigated the effects of MTR/VF on stream salamander occupancy and overall community composition in southeastern Kentucky by conducting area constrained active searches for salamanders within first-order streams located in mature forest (i.e., control streams) and those impacted by MTR/VF. We found high mean species occupancy across 5 species at control streams, ranging from 0.73 (95% CI 0.41 to 0.96) to 0.90 (95% CI 0.77 to 0.98). Occupancy was lower at MTR/VF streams, with mean estimated occupancy probability ranging from 0.23 (95% CI 0.04 to 0.51) to 0.62 (95% CI 0.36 to 0.86). Additionally, the mean species richness for MTR/VF streams was 2.27 (±1.27 SD) whereas richness was 4.67 (±0.65 SD) for control streams. Numerous mechanisms may be responsible for decreased occupancy and species richness at MTR/VF streams, although water chemistry may be particularly important. Indeed, mean specific conductance was 30 times greater, sulfate (SO4) levels were 70 times greater, and concentrations of dissolved ions (Ca, Mg, K, Na) were greater in MTR/VF streams than in control streams. Our results indicate that MTR/VF operations lead to significant decreases in salamander occupancy and species richness.

DETECTION PROBABILITY AND PASTEURELLACEAE SURVEILLANCE IN BIGHORN SHEEP

We investigated the influence of detection probability (i.e., the probability of detecting the disease or organism of interest) on the repeatability of results reported from bacterial culture tests used to demonstrate the presence of species in the Pasteurellaceae family that infect bighorn sheep (Ovis canadensis). We also estimated occupancy probabilities (i.e., the probability an individual bighorn in a herd is infected) for each cultured biovariant and examined the effects of detection probability on the number of samples needed to detect the Pasteurellaceae biovariants from within an individual sheep as well as from within a herd. We collected 5-15 samples from free-ranging bighorns in Colorado, using oropharyngeal swabs or swabs of lungs, and submitted these swabs either immediately or after 2 days for bacterial culture. We saw significant variability in results for repeated samples from each of the sheep, and detection probabilities were ≤ 0.71 for all Pasteurellaceae biovariants cultured. The delayed (≥ 2 days) sample submission reduced both the microbial diversity detected and the detection probability for the biovariants characterized when compared to samples submitted immediately. Oropharyngeal sampling had higher detection probabilities of the individual biovariants than did lung swabs, and there was a difference in the biovariants detected between oropharyngeal and lung sampling. Depending on the biovariant of interest, estimates of occupancy probabilities ranged from 0.37-0.89, and we estimated that three to >30 swab samples were necessary to obtain a 95% confidence of detecting the cultured biovariants if they were present in an individual sheep. We estimated that the optimal sample sizes to detect the observed biovariants within a sheep herd with a 95% confidence ranged from sampling two bighorns twice to sampling 40 individuals once. Detection probability impacts the results reported from bacterial cultures for Pasteurellaceae in bighorn sheep, and confounding effects of the detection process should be addressed to improve the rigor of surveillance.

AMPHIBIAN OCCUPANCY IN FLOOD‐CREATED AND EXISTING WETLANDS OF THE LOWER MISSOURI RIVER ALLUVIAL VALLEY

ABSTRACTDuring the previous century, the wetland area in the lower Missouri River alluvial valley was reduced by 39% because of river channelization and bank stabilization projects. The Great Flood of 1993 reversed the trend of wetland loss by creating 466 new wetlands in the alluvial valley between Kansas City and St. Louis, Missouri. We estimated amphibian occupancy, detection probability and number of species exhibiting evidence of reproduction in eight flood‐created and 16 pre‐flood existing wetlands from 1996 through 1998. We also evaluated whether hydroperiod (the number of days any water was present in a wetland from 20 February through 31 August) and distance to river predicted those values. Detection probabilities for adult amphibian species were relatively constant across years and ranged from 0.013 [Great Plains toad (Anaxyrus cognatus)] to 0.280 [Woodhouse's toad (Anaxyrus woodhousii woodhousii)]. Occupancy of adult amphibians differed across years and was not correlated with habitat features. Estimated occupancy probabilities for amphibian species ranged from 0.126 [Plains spadefoot (Spea bombifrons)] to 0.896 [boreal chorus frog (Pseudacris maculata)]. Almost double the number of amphibian species showed evidence of reproduction in existing wetlands (wetlands created before the Great Flood of 1993) when compared with that in flood‐created wetlands. Similarly, temporary wetlands had nearly double the number of amphibian species showing evidence of reproduction when compared with permanent wetlands. Finally, the highest number of species showed evidence of reproduction in wetlands with spring–summer hydroperiods between 135 and 140 days. All these relationships suggest that the invasion and persistence of predators in wetlands negatively influence amphibian reproduction. If the Missouri River is allowed to reconnect with the alluvial valley, more predators may be introduced into wetlands, leading to reduced amphibian occupancy and reproduction. However, this connection will not likely occur over the entire alluvial valley and, therefore, should not adversely impact amphibians that find refuge in higher‐elevation, non‐connected regions of the alluvial valley. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Basin‐Scale Surveys of Stream‐Associated Amphibians in Intensively Managed Forests

Abstract:Conservation and management of native species on landscapes managed for intensive wood production represents an ongoing challenge to forest managers. Previous research suggests that impacts of forest practices on stream‐associated amphibians (SAA; giant [Dicamptodonspp.], torrent [Rhyacotritonspp.], and plethodontid [Plethodonspp.] salamanders and coastal tailed frogs [Ascaphus truei]) in Oregon and Washington, USA, vary spatially and temporally as a result of biotic and abiotic factors, some of which can be influenced by management treatments. Although individual harvest units can encompass multiple stream reaches and entire second‐order basins, nearly all published research studies used stream reaches of various lengths as sample units. To address this discrepancy between research and operational scales, we sampled first‐, second‐, and third‐order streams in 70 randomly selected third‐order basins in Oregon and Washington in 2007 and 2008 to estimate detection and occupancy parameters for SAA and to develop basin‐level density estimates for different species and genera. We estimated occupancy probabilities of 0.99 (95% CL = 0.96–1.00) for torrent and giant salamanders, 0.93 (95% CL = 0.76–0.92) for Dunn's salamanders (Plethodon dunni), and 0.60 (95% CL = 0.46–0.72) for tailed frogs. Our estimates can be compared with estimates for unmanaged third‐order basins in Oregon and Washington to provide a relative measure of potential impacts of forest management on these taxa. In addition, our estimates provide baseline information with which to assess potential effects of future environmental changes on the 4 genera.

Factors Influencing the Detectability of Forest Owls in Southeastern Alaska

Patch-occupancy models offer a realistic approach to monitoring populations of nocturnal owls. However, because most owls are relatively rare, increasing the probability of detecting an owl at an occupied site will make estimates of occupancy more precise. We investigated the influence of temporal, biological, and environmental factors on rates of detection of forest owls in southeastern Alaska, 2005–2006. Following MacKenzie et al. (2006), we modeled probabilities of detection of the Northern Saw-whet Owl (Aegolius acadicus), Western Screech-Owl (Megascops kennicottii), and Barred Owl (Strix varia). We conducted 479 point counts over 100 days and detected owls 147 times. Sound broadcast increased detections 21–86% over silent surveys. During peak detection (9 April–8 May), probabilities (SE) of detection were 0.39 (0.13) for the Western Screech, 0.44 (0.16) for the Saw-whet, and 0.54 (0.25) for the Barred. For the Barred and Saw-whet, estimated occupancy probabilities (ψ) were constant (i.e., did not vary with covariates), but for the Western Screech, ψ was a function of whether large owls had been detected at a site, with estimated ψ about 66% lower at sites with large owls. For the Western Screech detection probability increased after sunset. For the Barred, the pattern of detection probability was nonlinear in relation to time after sunset, being high near sunset and late at night. For the Saw-whet detection probabilities were most influenced by weather covariates, primarily precipitation and wind. We provide recommendations on allocating survey effort and increasing probabilities of detection of these three owls in southeastern Alaska.