ABUNDANCE OF SOUTHERN CALIFORNIA COASTAL BOTTLENOSE DOLPHINS ESTIMATED FROM TANDEM AERIAL SURVEYS

We describe a tandem aerial survey method for bottlenose dolphins ( Tursiops truncatus ) that uses two aircraft and independent observer teams to conduct consecutive surveys of the same coastal strip one hour apart. Alternatively, one aircraft with one observer team surveys the same coastal strip twice over several hours. Using mark-recapture analysis, we corrected survey counts for visibility bias resulting from missing dolphin groups at the surface and submerged groups. Dolphin groups were considered "recaptured" when we determined that both observer teams had detected the same group. This tandem method is highly useful for estimating abundance (and visibility bias) for species where population closure may be assumed between flights. We assumed population closure between flights and matched groups using geographic location, group size, and expected travel rates. We derive a new variance estimator of population size which incorporates group-size variability commonly encounteted in cetacean surveys. From six tandem surveys conducted from 1991 to 1994, we estimated the abundance of southern California coastal bottlenose dolphins to be between 78 (95% CI 60-102) and 271 (240-306) animals, with an average of 140 (128-154). Variability in abundance estimates is likely due to seasonal and interannual movement of animals along the California and Baja California coast. Abundance estimates from tandem surveys averaged 53% higher than dolphin counts obtained from individual survey flights, demonstrating the importance of correcting for visibility bias.     

Roadway mortality of barn owls in Idaho,USA

We examined the temporal, spatial, and demographic factors that influenced roadway mortality of barn owls (Tyto alba) along a 248-km stretch of Interstate 84 in southern Idaho using systematic road surveys. Counts of dead animals from surveys can be underestimated because of sampling biases; therefore, we also conducted experiments to assess the effects of search and removal bias on the estimates of roadway mortality of owls. We conducted surveys every 2 weeks over a 2-year period and detected 812 dead barn owls (unadjusted mortality rate of 1.64 owls/km/yr). After adjusting this estimate for search and removal bias, we documented mortality rates of up to 5.99 owls/km/year. Owl mortality was not random in relation to sex, age class, or location along the highway. Females and juveniles, which represent individuals more likely to disperse long distances, were killed more frequently than males and adults. During the nonbreeding season, owls were killed more often near agricultural lands than in shrub-steppe, but this pattern was not apparent during the breeding season. Owls were also killed more often on portions of the roadway closer to the Snake River canyon, perhaps because of the availability of nest and roost sites. Mortality rates differed markedly between the 2 years of study, which could have been related to variability in weather and its subsequent effect on owl productivity. Our data suggest that barn owls in this region may not persist under this level of mortality without significant immigration or management. Thus, roadway management to reduce or prevent owl use of roadways, reduce rodent populations near major roads, alert motorists to the presence of owls, or otherwise reduce the chances that vehicles and owls collide would improve barn owl survival and population persistence. © 2012 The Wildlife Society.     

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies.     

Effects of survey methods on burrowing owl behaviors

Monitoring wildlife populations often involves intensive survey efforts to attain reliable estimates of population size. Such efforts can increase disturbance to animals, alter detection, and bias population estimates. Burrowing owls (Athene cunicularia) are declining across western North America, and information on the relative effects of potential survey methods on owl behaviors is needed. We designed a field experiment to compare burrowing owl flight distances, times displaced, and probabilities of being displaced between 4 potential population survey methods (single walking surveyor, single vehicle stop, single vehicle stop with 2 surveyors, and double vehicle stop with 2 surveyors), and an experimental control in the agricultural matrix of Imperial Valley, California. Between 25 April and 1 May 2008, we randomly applied survey methods to 395 adult male owls during daylight hours (0700 hours through 1900 hours). All survey methods increased odds of displacing owls from perches. Survey methods with observers outside the vehicle were 3 times more likely to displace an owl than a single vehicle stop where observers remained inside the vehicle. Owls were displaced farther distances by all survey methods compared to control trials, but distances and time displaced did not differ among survey methods. We recommend that surveys for counting owls during the breeding season in agroecystems like the Imperial Valley where high densities of owls nest primarily along the borders of fields be conducted using single vehicle stops with or without 2 surveyors, depending on conditions for locating owls from roads. © 2011 The Wildlife Society.     

A review of burrow counting as an alternative to other typical methods of assessment of Norway lobster populations

The diurnal and seasonal regulation of the complex burrowing behavior of Nephrops norvegicus complicates population assessment for this species. Population assessment is traditionally carried out by Virtual Population Analysis (Length Cohort Analysis; LCA) and swept area density estimations from catch data. However, burrow counting from visual surveys has also acquired increasing importance in recent years as an alternative and apparently efficient method. All these approaches produced non-equivalent assessment results in the literature, and therefore, a comparison and critical discussion of these methods is warranted. In this review, we pursued this goal by using already published and unpublished fishery data for a commercially exploited western Mediterranean shelf (60–100 m) population as an example. The cross-assessment was carried out by LCA, the swept area method and burrow counting in different seasons (spring-summer and autumn–winter) to highlight biases in abundance estimations in relation to Nephrops behavior. We also used novel trawl density data for other fish and decapod species in the area because the burrowing behavior of these species may deeply bias Nephrops abundance in visual surveys. LCA provided intermediate assessment values when compared to the swept area and photographic estimates, which over- and underestimated the abundance, respectively. We reviewed the problems related to the peculiar burrowing behavior of the species that generate assessment estimations of such different magnitude.     

Marine copepod diversity patterns and the metabolic theory of ecology

The ongoing climate change has improved our understanding of how climate affects the reproduction of animals. However, the interaction between food availability and climate on breeding has rarely been examined. While it has been shown that breeding of boreal birds of prey is first and foremost determined by prey abundance, little information exists on how climatic conditions influence this relationship. We studied the joint effects of main prey abundance and ambient weather on timing of breeding and reproductive success of two smaller (pygmy owl Glaucidium passerinum and Tengmalm’s owl Aegolius funereus) and two larger (tawny owl Strix aluco and Ural owl Strix uralensis) avian predator species using long-term nation-wide datasets during 1973–2004. We found no temporal trend either in vole abundance or in hatching date and brood size of any studied owl species. In the larger species, increasing late winter or early spring temperature advanced breeding at least as much as did high autumn abundance of prey (voles). Furthermore, increasing snow depth delayed breeding of the largest species (Ural owl), presumably by reducing the availability of voles. Brood size was strongly determined by spring vole abundance in all four owl species. These results show that climate directly affects the breeding performance of vole-eating boreal avian predators much more than previously thought. According to earlier studies, small-sized species should advance their breeding more than larger species in response to increasing temperature. However, we found an opposite pattern, with larger species being more sensitive to temperature. We argue that this pattern is caused by a difference in the breeding tactics of larger mostly capital breeding and smaller mostly income breeding owl species.     

Factors Affecting Detection of Burrowing Owl Nests During Standardized Surveys

Abstract: Identifying causes of declines and evaluating effects of management practices on persistence of local populations of burrowing owls (Athene cunicularia) requires accurate estimates of abundance and population trends. Moreover, regulatory agencies in the United States and Canada typically require surveys to detect nest burrows prior to approving developments or other activities in areas that are potentially suitable for nesting burrowing owls. In general, guidelines on timing of surveys have been lacking and surveys have been conducted at different times of day and in different stages of the nesting cycle. We used logistic regression to evaluate 7 factors that could potentially affect probability of a surveyor detecting a burrowing owl nest. We conducted 1,444 detection trials at 323 burrowing owl nests within 3 study areas in Washington and Wyoming, USA, between February and August 2000–2002. Detection probability was highest during the nestling period and increased with ambient temperature. The other 5 factors that we examined (i.e., study area, time of day, timing within the breeding season, wind speed, % cloud cover) interacted with another factor to influence detection probability. Use of call-broadcast surveys increased detection probability, even during daylight hours when we detected >95% of owls visually. Optimal timing of surveys will vary due to differences in breeding phenology and differences in nesting behavior across populations. Nevertheless, we recommend ≥3 surveys per year: one that coincides with the laying and incubation period, another that coincides with the early nestling period, and a third that coincides with the late nestling period. In northern latitudes, surveys can be conducted throughout the day. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):688–696; 2008)     

Factors affecting detection probability of burrowing owls in southwest agroecosystem environments

Estimating range-wide population trends of western burrowing owls (Athene cunicularia) requires standardized survey protocols that correct for detection bias in environments that support large owl populations. High concentrations of owls exist in irrigated agroecosystems within the southwest United States, yet little is known about the factors that affect detection bias during owl surveys in these systems. I used closed-population capture-recapture models to evaluate 4 factors that could affect the probability of a surveyor detecting an owl activity center (i.e., nest burrow) during visual surveys where owls are the focal object and analyzed the relationship (linear or curvilinear) between specific factors and detection probability. I recorded 1,199 detections of owls from 132 capture-recapture surveys within 12 sites of the Imperial Valley agroecosystem in California, USA between 16 April and 20 May 2006. I also conducted 96 time budget surveys throughout the day and used mixed linear models to evaluate the effect of each factor on probability of an owl activity center being available for detection (i.e., ≥1 owls above ground) during surveys. Model selection results indicated that detection probability was influenced by ambient air temperature interacting with wind speed. Detection probability followed a curvilinear relationship that resembled bell-shaped curve along a temperature gradient, with the maximum detection probability shifting as a function of wind speed. At low temperatures, detection probability declined with increased wind speed, but this relationship was reversed at high temperatures, producing a 3-dimensional pattern in detection probability characterized by a saddle-shaped hyperbolic paraboloid response surface. The probability of an activity center being available for detection declined curvilinearly with increased temperature and explained 51% of the variation in detection probability. Given the broad range of detection probabilities, correcting visual survey counts for detection bias is necessary for comparing population estimates among regions and through time. Survey designs intended to estimate abundance of owls in southwest agroecosystems should incorporate methods to estimate and correct for variation in detection probability that include measurements of ambient temperature and wind speed for use as covariates. © 2011 The Wildlife Society.     

Minimizing polymerase biases in metabarcoding

DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or “barcode,” from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.     

Estimation and Correction of Visibility Bias in Aerial Surveys of Wintering Ducks

Abstract: Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1–100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36–42%, and associated standard errors increased 38–55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):808–813; 2008)     

Bayesian estimation of group sizes for a coastal cetacean using aerial survey data

Many small cetacean, sirenian, and pinniped species aggregate in groups of large or variable size. Accurate estimation of group sizes is essential for estimating the abundance and distribution of these species, but is challenging as individuals are highly mobile and only partially visible. We developed a Bayesian approach for estimating group sizes using wide‐angle aerial photographic or video imagery. Our approach accounts for both availability and perception bias, including a new method (analogous to distance sampling) for estimating perception bias due to small image size in wide‐angle images. We demonstrate our approach through an application to aerial survey data for an endangered population of beluga whales (Delphinapterus leucas) in Cook Inlet, Alaska. Our results strengthen understanding of variation in group size estimates and allow for probabilistic statements about the size of detected groups. Aerial surveys are a standard tool for estimating the abundance and distribution of various marine mammal species. The role of aerial photographic and video data in wildlife assessment is expected to increase substantially with the widespread uptake of unmanned aerial vehicle technology. Key aspects of our approach are relevant to group size estimation for a broad range of marine mammal, seabird, other waterfowl, and terrestrial ungulate species.     

Scaling Occupancy Estimates up to Abundance for Wolves

Management of wildlife populations often requires reliable estimates of population size or distribution. Estimating abundance can be logistically difficult, and occupancy models have been used as a less expensive proxy for abundance estimation. Another alternative is to use independent estimates of home-range size and mean group size to directly scale occupancy estimates up to abundance. We used simulations to explore when scaling occupancy up to abundance is reliable, and as an example we applied an occupancy approach to estimate abundance of wolves (Canis lupus) from roadside snow-tracking surveys in northern Wisconsin, USA, in 2016 and 2018. Estimates of wolf abundance were plausible and compared favorably with independent estimates produced by territory mapping, and snow-tracking data requirements were lower than for territory mapping. Simulation results suggested that reasonable abundance estimates could be obtained under some conditions but also that severe positive bias could result under other conditions, especially when populations were small and dispersed, home range size was small, and areal sampling units were large. Positive bias in abundance estimates occurs because of closure assumption violations when tracks from a single wolf or pack are detected in >1 sample unit, and the sum of the sample unit areas where tracks were detected exceed the sum of the home range areas. Bias was minimized when sampling units were small relative to home range size or when sampling units were route segments that approximate point sample units, and when home ranges were highly aggregated. We conclude that, although caution is warranted when scaling occupancy estimates up to abundance, scaled occupancy models can provide feasible and reliable estimates of abundance, assuming home range size and mean group size are accurately known or estimated, sampling units are appropriately chosen, and covariates that aggregate home ranges can be used to accurately predict occupancy probability. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.     

Experimental evaluation of a new ground-based survey method for estimating the density and abundance of nesting Adélie penguins <Emphasis Type="Italic">Pygoscelis adeliae</Emphasis>

A new ground-based technique for estimating the density of nesting Adélie penguins (Pygoscelis adeliae) within occupied habitat is described and evaluated using an experimental approach with model penguins. In this set-up, an operator takes photos with a camera mounted on a 3-m pole at pre-determined sampling locations within habitat occupied by nesting penguins, and the actual boundaries of the plot in which penguin density is estimated are added post-survey. Density estimates are calculated by overlaying slope-specific templates delineating plot boundaries and distances of known dimensions onto the digital photos to allow a distance-sampling analysis to correct for any negative bias in counts arising from a proportion of penguins being obscured. Experimental assessment of biases in density estimates because of misclassification error was <2% when compared to true density, indicating that this survey method is effective at accurately estimating penguin density and, therefore, abundance.     

Humpback whale abundance in the North Pacific estimated by photographic capture‐recapture with bias correction from simulation studies

We estimated the abundance of humpback whales in the North Pacific by capture‐recapture methods using over 18,000 fluke identification photographs collected in 2004–2006. Our best estimate of abundance was 21,808 (CV = 0.04). We estimated the biases in this value using a simulation model. Births and deaths, which violate the assumption of a closed population, resulted in a bias of +5.2%, exclusion of calves in samples resulted in a bias of ?10.5%, failure to achieve random geographic sampling resulted in a bias of ?0.4%, and missed matches resulted in a bias of +9.3%. Known sex‐biased sampling favoring males in breeding areas did not add significant bias if both sexes are proportionately sampled in the feeding areas. Our best estimate of abundance was 21,063 after accounting for a net bias of +3.5%. This estimate is likely to be lower than the true abundance due to two additional sources of bias: individual heterogeneity in the probability of being sampled (unquantified) and the likely existence of an unknown and unsampled breeding area (?8.7%). Results confirm that the overall humpback whale population in the North Pacific has continued to increase and is now greater than some prior estimates of prewhaling abundance.     

Prey colour biases in jumping spiders (Habronattus brunneus) differ across populations

Predators often avoid aposematic prey as a result of aversions to particular prey signals (e.g., bright colours and noxious odours). These aversions may be flexible, that is, they can be reinforced or extinguished with experience. As such, we might expect populations to differ in their biases against certain prey characteristics (e.g., colour or pattern) depending on the prey available in the community. Here, we tested whether the jumping spider, Habronattus brunneus(Salticidae), exhibits colour biases against red prey using choice tests with novel (artificially coloured) prey, and then went on to examine how these biases differ across four geographically distinct focal populations. We then conducted preliminary field surveys at each of these four sites to explore differences in habitat type and prey availability. Overall, we found that field‐caught H. brunneusexhibited a bias against the colour red (compared with black) when tested with artificially coloured prey in the laboratory. However, the degree of colour bias varied among our four focal populations (with two populations exhibiting strong biases against red and two showing no colour biases). Preliminary habitat and prey surveys suggest that these populations also differed in both habitat structure (percentage of grass, leaf litter and bare ground) and prey availability across many taxa, suggesting that the spiders from each population may have been exposed to, and had experiences with, different potential prey. We discuss how prey availability may influence colour biases in predators, as well as how predator experience may shape the evolution of prey colour signals.     

Evaluating food availability and nest predation risk as sources of bias in aural bird surveys

ABSTRACT The use of aural surveys to estimate population parameters is widespread in avian studies. Despite efforts to increase the efficacy of this method, the potential for ecological context to bias population estimates remains largely unexplored. For example, food availability and nest predation risk can influence singing activity independent of density and, therefore, may bias aural estimates where these ecological factors vary systematically among habitats or other categories of ecological interest. We used a natural fire event in a mixed‐conifer forest that experienced variation in fire severity (low, intermediate, and high) to determine if aural surveys produce accurate density estimates of Dark‐eyed Juncos ( Junco hyemalis) independent of ecological context. During the first 2‐yr postfire, we censused junco populations in each burn type with intensive spot‐mapping and nest searching, locating 168 nests. Simultaneously, we conducted fixed‐radius point‐count surveys and estimated food availability and nest predation risk in each burn type to test whether ecological context may influence aural detection probability independent of actual density. We found no difference in nesting densities among patches burned at different severity. Arthropod food availability was inversely related to fire severity during the first postfire breeding season, but increased to higher levels across all severities during the second. In both years, aural detections were significantly greater in intermediate severity patches that consistently represented the habitat with the lowest nest predation risk. These results suggest that nest predation risk may significantly bias aural estimates of avian populations. Although traditional aural survey methods such as the Breeding Bird Survey measure habitat attributes, our findings highlight the difficulty in assessing relevant covariates in estimates of avian population. Future research must consider the potential for nest predation and other ecological factors to drive interannual or interhabitat variation in avian population estimates independent of true changes in population size.     

Estimating the complex patterns of survey availability for loggerhead turtles

Successful management strategies are important for conservation and allow accurate surveying and monitoring of populations for presence, abundance, and trend. This becomes challenging for cryptic, low-density species, and for animals that have complicated life histories where not every stage of the life cycle can be surveyed effectively. We used information from animal-borne data loggers to characterize the dive-surfacing behavior of cryptic loggerhead turtles (Caretta caretta) in the northwest Atlantic from 2009–2018. Our data covered a large geographic area off the east coast of North America, and allowed us to present estimates for and variation in 3 metrics that can be used to assess availability bias affecting visual surveys: average dive duration, average surface duration, and the proportion of time at the surface. We used a stochastic partial differential equation approach to construct spatiotemporal regression models for the availability bias metrics. Model predictions showed pronounced individual, spatial, and spatiotemporal (seasonal) variation among the 245 turtles. Overall, we estimated an average dive duration of 14.5 ± 1.36 minutes (SE), an average surface duration of 15.1 ± 2.77 minutes, and an average proportion of time at the surface of 0.50 (95% CI = 0.41–0.59). We made predictions of the 3 availability bias metrics on a 20-km × 20-km grid and further used predictions to explore seasonal variations. Our results contribute new insights into loggerhead turtle behavior and provide information that enables survey counts to be translated into more accurate abundance estimates.     

Challenges of DNA-Based Mark-Recapture Studies of American Black Bears

Abstract: We explored whether genetic sampling would be feasible to provide a region-wide population estimate for American black bears (Ursus americanus) in the southern Appalachians, USA. Specifically, we determined whether adequate capture probabilities (p > 0.20) and population estimates with a low coefficient of variation (CV < 20%) could be achieved given typical agency budget and personnel constraints. We extracted DNA from hair collected from baited barbed-wire enclosures sampled over a 10-week period on 2 study areas: a high-density black bear population in a portion of Great Smoky Mountains National Park and a lower density population on National Forest lands in North Carolina, South Carolina, and Georgia. We identified individual bears by their unique genotypes obtained from 9 microsatellite loci. We sampled 129 and 60 different bears in the National Park and National Forest study areas, respectively, and applied closed mark-recapture models to estimate population abundance. Capture probabilities and precision of the population estimates were acceptable only for sampling scenarios for which we pooled weekly sampling periods. We detected capture heterogeneity biases, probably because of inadequate spatial coverage by the hair-trapping grid. The logistical challenges of establishing and checking a sufficiently high density of hair traps make DNA-based estimates of black bears impractical for the southern Appalachian region. Alternatives are to estimate population size for smaller areas, estimate population growth rates or survival using mark-recapture methods, or use independent marking and recapturing techniques to reduce capture heterogeneity.     

Burrowing owls and burrowing mammals: are ecosystem engineers interchangeable as facilitators?

Terrestrial vertebrates exhibit dynamic, positive interactions that form and dissolve under different circumstances, usually with multiple species as participants. Ecosystem engineers are important facilitators of other species because they cause physical changes in the environment that alter resource availability. Although a species can be associated with more than one partner, facilitators may not be interchangeable if they differ in abundance, behavioral characteristics, or interactions with other factors in ways that condition the outcome of the association. We examined interactions between burrowing owls (Athene cunicularia) and two burrowing mammals, hairy armadillos (Chaetophractus villosus) and plains vizcachas (Lagostomus maximus), and determined whether these ecosystem engineers are interchangeable for owls. We examined reproductive success for owls nesting in these mammal burrows, constructed a logistic regression model to identify habitat characteristics associated with owl nests, and examined the engineering activities of the mammals. Data on reproduction and habitat indicate that armadillos and vizcachas are not interchangeable for owls. Thirty-five percent of the nests in vizcacha burrows produced fledglings; no fledglings were produced from nests outside vizcachas colonies, even though owls nest successfully in armadillo burrows in other parts of Argentina. Vizcachas facilitate burrowing owls by construction of burrows and by producing open understory vegetation through herbivory. In contrast, armadillos do not alter vegetation, and their burrows are suitable for nest sites only when they occur in recently burned areas or areas maintained by anthropogenic disturbance. Our habitat model also suggests that fire plays a key role in maintaining owl populations because fire is the only natural process that reduces shrubs to the level required by owls. Current management practices of eradication of vizcachas and fire suppression in shrublands could have strong negative consequences for burrowing owls.     

ICE-BASED CENSUS OF BOWHEAD WHALES MIGRATING PAST POINT BARROW, ALASKA, 1978-1983

Bowhead whale ( Balaena mysticetus ) census data obtained during the northward spring migration are summarized for 1978–1983. Population size estimates are derived from counts made by observers standing on the seaward edge of shorefast ice in the vicinity of Point Barrow, Alaska, from mid-April to early June. The research design utilized two counting stations: South Perch, the primary counting station, and North Perch, used to determine the number of whales missed by South Perch observers. The percentage missed is estimated for each visibility category and used here to correct the census counts. Each season's population estimate is calculated as the sum of the number of trials of several independent multinomial distributions representing different visibility conditions. Corrections are applied for unwatched hours and hours with inferior visibility. A mean estimate of the number of whales passing within view of the census station was computed as 3,674 ± 299. This estimate was based on data collected in 1978, 1981, 1982, and 1983, years with the least apparent biases. Aerial survey data provide estimates of the proportion of whales passing at various distances seaward of the census sites as follows: 0.58 from the ice edge to 2 km, 0.76 to 3 km, and 0.80 to 4 km. Correcting for whales too far offshore to be seen by the ice-based observers results in a population estimate of over 4,200 bowheads.