Separating Components of the Detection Process With Combined Methods: An Example With Northern Bobwhite

Abstract: There are various methods of estimating detection probabilities for avian point counts. Distance and multiple-observer methods require the sometimes unlikely assumption that all birds in the population are available (i.e., sing or are visible) during a count, but the time-of-detection method allows for the possibility that some birds are unavailable during the count. We combined the dependent double-observer method with the time-of-detection method and obtained field-based estimates of the components of detection probability for northern bobwhite (Colinus virginianus). Our approach was a special case of Pollock's robust capture-recapture design where the probability that a bird does not sing is analogous to the probability that an animal is a temporary emigrant. Top models indicated that observers' detection probabilities were similar (0.78–0.84) if bobwhite were available, but bobwhite only had an approximately 0.61 probability of being available during a 2.5-minute sampling interval. Additionally, observers' detection probabilities increased substantially after the initial encounter with an individual bobwhite (analogous to a trap-happy response on the part of the observer). A simulated data set revealed that the combined method was precise when availability and detection given availability were substantially lower. Combined methods approaches can provide critical information for researchers and land managers to make decisions regarding survey length and personnel requirements for point-count-based surveys.     

An Evaluation of Survey Methods for Estimating Northern Bobwhite Abundance in Southern Texas

Abstract: Distance sampling has been identified as a reliable and well-suited method for estimating northern bobwhite (Colinus virginianus) density. However, distance sampling using walked transects requires intense sampling to obtain precise estimates, thus making the technique impractical for large acreages. Researchers have addressed this limitation by either resorting to the use of indices (e.g., morning covey-call surveys) or incorporating the use of aerial surveys with distance sampling. Both approaches remain relatively untested. Our objectives were to 1) compare density estimates among morning covey-call surveys, helicopter transects, and walked transects; 2) test a critical assumption of distance sampling pertinent to helicopter surveys (i.e., all objects on line are detected); and 3) evaluate the underlying premise of morning covey-call surveys (i.e., that the no. of calling coveys correlates with bobwhite density). Our study was conducted on 3 study sites in Brooks County, Texas, USA, during October to December, 2001 to 2005. Comparisons between walked transects and morning covey-call surveys involved the entire 5-year data set, whereas helicopter transects involved only the latter 2 years. Density estimates obtained from helicopter transects were similar to walked transect estimates for both years. We documented a detection probability on the helicopter transect line of 70 ± 10.2% (% ± SE; n = 20 coveys). Morning covey-call surveys yielded similar density estimates to walked transect estimates during only 2 of 5 years, when walked transect estimates were the least accurate and precise. We detected a positive relationship (R² = 0.51; 95% CI for slope: 29.5–53.1; n = 63 observations) between covey density and number of coveys heard calling. We conclude that helicopter transects appear to be a viable alternative to walked transects for estimating density of bobwhites. Morning covey-call surveys appear to be a poor method to estimate absolute abundance and to depict general population trajectories.     

Comparison of Methods for Estimating Bird Abundance and Trends From Historical Count Data

Abstract: The use of bird counts as indices has come under increasing scrutiny because assumptions concerning detection probabilities may not be met, but there also seems to be some resistance to use of model-based approaches to estimating abundance. We used data from the United States Forest Service, Southern Region bird monitoring program to compare several common approaches for estimating annual abundance or indices and population trends from point-count data. We compared indices of abundance estimated as annual means of counts and from a mixed-Poisson model to abundance estimates from a count-removal model with 3 time intervals and a distance model with 3 distance bands. We compared trend estimates calculated from an autoregressive, exponential model fit to annual abundance estimates from the above methods and also by estimating trend directly by treating year as a continuous covariate in the mixed-Poisson model. We produced estimates for 6 forest songbirds based on an average of 621 and 459 points in 2 physiographic areas from 1997 to 2004. There was strong evidence that detection probabilities varied among species and years. Nevertheless, there was good overall agreement across trend estimates from the 5 methods for 9 of 12 comparisons. In 3 of 12 comparisons, however, patterns in detection probabilities potentially confounded interpretation of uncorrected counts. Estimates of detection probabilities differed greatly between removal and distance models, likely because the methods estimated different components of detection probability and the data collection was not optimally designed for either method. Given that detection probabilities often vary among species, years, and observers investigators should address detection probability in their surveys, whether it be by estimation of probability of detection and abundance, estimation of effects of key covariates when modeling count as an index of abundance, or through design-based methods to standardize these effects.     

Using time‐of‐detection to evaluate detectability assumptions in temporally replicated aural count indices: an example with Ring‐necked Pheasants

ABSTRACT The validity of treating counts as indices to abundance is based on the assumption that the expected detection probability, E(p), is constant over time or comparison groups or, more realistically, that variation in p is small relative to variation in population size that investigators seek to detect. Unfortunately, reliable estimates of E(p) and var(p) are lacking for most index methods. As a case study, we applied the time‐of‐detection method to temporally replicated (within season) aural counts of crowing male Ring‐necked Pheasants (Phasianus colchicus) at 18 sites in southern Minnesota in 2007 to evaluate the detectability assumptions. More specifically, we used the time‐of‐detection method to estimate E(p) and var(p), and then used these estimates in a Monte Carlo simulation to evaluate bias‐variance tradeoffs associated with adjusting count indices for imperfect detection. The estimated mean detection probability in our case study was 0.533 (SE = 0.030) and estimated spatial variation in E(p) was 0.081 (95% CI: 0.057–0.126). On average, both adjusted (for) and unadjusted counts of crowing males qualitatively described the simulated relationship between pheasant abundance and grassland abundance, but the bias‐variance tradeoff was smaller for adjusted counts (MSE = 0.003 vs. 0.045, respectively). Our case study supports the general recommendation to use, whenever feasible, formal population‐estimation procedures (e.g., mark‐recapture, distance sampling, double sampling) to account for imperfect detection. However, we caution that interpreting estimates of absolute abundance can be complicated, even if formal estimation methods are used. For example, the time‐of‐detection method was useful for evaluating detectability assumptions in our case study and the method could be used to adjust aural count indices for imperfect detection. Conversely, using the time‐of‐detection method to estimate absolute abundances in our case study was problematic because the biological populations and sampling coverage could not be clearly delineated. These estimation and inference challenges may also be important in other avian surveys that involve mobile species (whose home ranges may overlap several sampling sites), temporally replicated counts, and inexact sampling coverage.     

Behavior of Walk-Hunters and Pointing Dogs During Northern Bobwhite Hunts

Abstract: Data on the behavior of walk-hunters and pointing dogs aids in understanding and managing quail harvest. We collected Global Positioning System track logs and recorded behaviors of hunters and dogs on northern bobwhite (Colinus virginianus) hunts in Oklahoma (n = 43), Texas (n = 43), and Missouri (n = 7), USA, during the 2005–2006 and 2006–2007 hunting seasons. Hunter velocity averaged 0.8 ± 0.03 (SE) m/second both seasons (n = 85) and pooled (95% CL overlap) velocity of bird dogs was 2.5 ± 0.07 (SE) m/second (n = 154). Hunters spent 60.5 ± 2.4% (SE) of their time walking in 2005–2006 (n = 45) versus 75.2 ± 3.5% (SE) in 2006–2007 (n = 48); respective figures for ranging by dogs were 50.2 ± 2.2% (n = 57) versus 82.0 ± 1.3% (SE; n = 97). Mean duration of a hunt declined from 82.3 ± 8.16 (SE) minutes (n = 45) to 50.2 ± 5.1 (SE) minutes (n = 48) between seasons. Variation in bobwhite abundance was the primary cause of seasonal variation in hunter and dog behaviors because covey-associated activities declined as quail abundance declined. With our results and those of previous workers, managers have first-generation estimates of all variables in hunter-covey interface models for managing bobwhite harvest on discrete areas.     

Optimizing detection of the bobwhite reproduction call using passive acoustic monitoring

Northern bobwhite (Colinus virginianus) populations have declined across much of their range. In response to these declines, wildlife biologists and managers have increased survey efforts and tried to optimize detection and capitalize on technological advances to improve population estimates and cost-effectiveness. Our objective was to determine how environmental conditions influence detection of the reproduction call, or whistle, of masked bobwhite (C. v. ridgwayi), an endangered subspecies of northern bobwhite, using autonomous recording units (ARUs). We estimated the call intensity of the masked bobwhite reproduction call as 112 ± 0.5 decibels (mean ± SE) at 10 cm. We then broadcasted 16,284 calls during 17 trials to compare manual and automated call detection in recordings collected with ARUs. We used these data to model detectability of a bobwhite reproduction call, for when the bird is present and available, as a function of distance and weather conditions using generalized linear mixed models with trial as a random effect. Regardless of detection type, one model structure was competitive and suggested detection probability was a function of distance, wind speed, and wind direction. Detectability decreased with increased distance and wind speed and was influenced by wind direction. We demonstrate the use of our results to predict the probability of detecting a reproduction call during ARU-based monitoring efforts. By understanding the effects of environmental factors on the detection of a bobwhite reproductive call, bobwhite surveys can be improved.     

ESTIMATED POPULATION SIZE OF THE CALIFORNIA GRAY WHALE

Abstract: The 1987-1988 counts of gray whales passing Monterey are reanalyzed to provide a revised population size estimate. The double count data are modeled using iterative logistic regression to allow for the effects of various covariates on probability of detection, and a correction factor is introduced for night rate of travel. The revised absolute population size estimate is 20,869 animals, with CV = 4.37% and 95% confidence interval (19,200, 22,700). In addition the series of relative population size estimates from 1967-1968 to 1987-1988 is scaled to pass through this estimate and modeled to provide variance estimates from interannual variation in population size estimates. This method yields an alternative population size estimate for 1987-1988 of 21,296 animals, with CV = 6.05% and 95% confidence interval (18,900, 24,000). The average annual rate of increase between 1967-1968 and 1987-1988 was estimated to be 3.29% with standard error 0.44%.     

Addressing Temporal Variability in Bird Calling with Design and Estimation: A Northern Bobwhite Example

Imprecise or biased density estimates can lead to inadequate conservation action, overexploitation of game species, or lost recreational opportunities. Common approaches to estimating density of avian populations often either ignore the probability that an individual is present within the sampling area but is not available to be sampled (e.g., not vocalizing), or do not consider covariates that could influence availability. Additionally, management decisions made at the management unit scale are often informed by inadequate monitoring practices, such as limited sampling intensity. In such cases, management agencies calculate density by applying correction factors (e.g., detection probabilities estimated using empirical data from a different study system) to count data, rather than estimating a detection function directly using statistical models. We conducted a simulation study using northern bobwhite (Colinus virginianus; bobwhite) as a model species to quantify the consequences of mis-specifying avian point count models on bias and precision of density estimates. We compared bias and precision of estimates from a fully specified distance-sampling model that estimates availability and detection to 4 different mis-specified approaches, including 2 approaches to calculating density using correction factors. Using correction factors to calculate density produced estimates with low bias but relatively lower precision compared to the fully specified model (CV of density estimates at 35 sites over 5 years: fully specified = 10%, correction factors = 25% and 30%). Although the mean precision and bias of the fully specified model improved with more data (70 sites over 5 years, CV = 9%; 35 sites over 10 years, CV = 9%), precision of correction factors did not (70 sites over 5 years, CV = 22% and 27%; 35 sites over 10 years, CV = 24% and 29%). The fully specified model captured the underlying temporal variation in detection and availability. Increasing sampling duration from 5 to 10 years improved modeled estimates of growth rate, even for mis-specified models, but not derived growth rates using pre-determined detection functions. We demonstrated that conducting point counts 3 times/year at a feasible number of sites can produce relatively unbiased estimates of bobwhite density. Pre-determined detection functions can be fortuitously unbiased for certain years, but they are not a reliable method for determining density or identifying trends in density over time. © 2020 The Wildlife Society.     

A Double-Observer Method to Estimate Detection Rate During Aerial Waterfowl Surveys

Abstract We evaluated double-observer methods for aerial surveys as a means to adjust counts of waterfowl for incomplete detection. We conducted our study in eastern Canada and the northeast United States utilizing 3 aerial-survey crews flying 3 different types of fixed-wing aircraft. We reconciled counts of front- and rear-seat observers immediately following an observation by the rear-seat observer (i.e., on-the-fly reconciliation). We evaluated 6 a priori models containing a combination of several factors thought to influence detection probability including observer, seat position, aircraft type, and group size. We analyzed data for American black ducks (Anas rubripes) and mallards (A. platyrhynchos), which are among the most abundant duck species in this region. The best-supported model for both black ducks and mallards included observer effects. Sample sizes of black ducks were sufficient to estimate observer-specific detection rates for each crew. Estimated detection rates for black ducks were 0.62 (SE = 0.10), 0.63 (SE = 0.06), and 0.74 (SE = 0.07) for pilot-observers, 0.61 (SE = 0.08), 0.62 (SE = 0.06), and 0.81 (SE = 0.07) for other front-seat observers, and 0.43 (SE = 0.05), 0.58 (SE = 0.06), and 0.73 (SE = 0.04) for rear-seat observers. For mallards, sample sizes were adequate to generate stable maximum-likelihood estimates of observer-specific detection rates for only one aerial crew. Estimated observer-specific detection rates for that crew were 0.84 (SE = 0.04) for the pilot-observer, 0.74 (SE = 0.05) for the other front-seat observer, and 0.47 (SE = 0.03) for the rear-seat observer. Estimated observer detection rates were confounded by the position of the seat occupied by an observer, because observers did not switch seats, and by land-cover because vegetation and landform varied among crew areas. Double-observer methods with on-the-fly reconciliation, although not without challenges, offer one viable option to account for detection bias in aerial waterfowl surveys where birds are distributed at low density in remote areas that are inaccessible by ground crews. Double-observer methods, however, estimate only detection rate of animals that are potentially observable given the survey method applied. Auxiliary data and methods must be considered to estimate overall detection rate.     

Multi-region response to conservation buffers targeted for northern bobwhite

We coordinated a large-scale evaluation of northern bobwhite (Colinus virginianus) population response to establishment of 9-m to 37-m linear patches (buffers) of native herbaceous vegetation along row-crop field margins as part of the Conservation Reserve Program practice Habitat Buffers for Upland Birds (CP33). We compared northern bobwhite covey densities on 1,088 paired row-crop fields with and without native herbaceous buffers in 13 states during autumn, 2006–2008. We used a 2-stage random effects modeling approach that incorporates the effective area as an offset in generalized linear mixed models to assess regional relationships among autumn bobwhite covey densities and covariates of field type (i.e., fields with vs. without native herbaceous buffers), ecological region, year, survey week, and contracted vegetative cover (i.e., planting native grasses and forbs vs. establishing through natural regeneration). Covey density was correlated with year and interaction effects of field type and ecological region. The year effect suggested annual variation in covey densities, whereas the field type by ecological region interaction suggested covey response to buffers was dependent on spatial location, likely reflecting differences in buffer establishment, succession, and characteristics of the surrounding landscape among regions. Mean fitted covey density on fields across all survey sites was 0.047 (±0.008 bootstrap standard error [BSE]) and 0.031 coveys/ha (±0.003 BSE) on row-crop fields with and without herbaceous buffers, respectively. Covey density was greater on fields with buffers relative to matched, comparison fields without buffers in the Mississippi Alluvial Valley (241%; P < 0.001) and both the eastern (123%; P < 0.001) and western (60%; P = 0.01) portions of the Southeastern Coastal Plain region. Covey density was an order of magnitude greater in the central Texas region compared to other regions, but exhibited a small response to native herbaceous buffers, as did density of coveys in the Eastern Tallgrass Prairie and Central Hardwoods regions. Disproportionate response to buffers in the Mississippi Alluvial Valley and Southeastern Coastal Plain suggests native herbaceous habitats might be limiting during autumn in these regions, whereas lack of response in the Eastern Tallgrass Prairie, Central Hardwoods, and central Texas regions suggests that herbaceous habitat either was not limiting or buffers failed to provide adequate requirements for bobwhites during autumn. Selection of other habitats to meet security and thermoregulatory needs might have resulted in lack of response in these regions. Native herbaceous cover provided by buffers can provide critical habitat in row-crop agricultural systems in some regions, and can contribute to regional population recovery objectives of the Northern Bobwhite Conservation Initiative (NBCI). However, range-wide NBCI recovery objectives will best be met through multiple conservation practices in row-crop agricultural systems. © 2013 The Wildlife Society.     

N-mixture models for estimating population size from spatially replicated counts

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, I describe a class of models (N-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, N, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for N. Carroll and Lombard (1985, Journal of American Statistical Association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on N that is exploited by the N-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the N-mixture estimator compared to the Caroll and Lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.     

Evaluation of three methods to estimate density and detectability from roadside point counts

Roadside point counts are often used to estimate trends of bird populations. The use of aural counts of birds without adjustment for detection probability, however, can lead to incorrect population trend estimates. We compared precision of estimates of density and detectability of whistling northern bobwhites (Colinus virginianus) using distance sampling, independent double-observer, and removal methods from roadside surveys. Two observers independently recorded each whistling bird heard, distance from the observer, and time of first detection at 362 call-count stops in Ohio. We examined models that included covariates for year and observer effects for each method and distance from observer effects for the double-observer and removal methods using Akaike's Information Criterion (AIC). The best model of detectability from distance sampling included observer and year effects. The best models from the removal and double-observer techniques included observer and distance effects. All 3 methods provided precise estimates of detection probability (CV = 2.4–4.4%) with a range of detectability of 0.44–0.95 for a 6-min survey. Density estimates from double-observer surveys had the lowest coefficient of variation (2005 = 3.2%, 2006 = 1.7%), but the removal method also provided precise estimates of density (2005 CV = 3.4%, 2006 CV = 4.8%), and density estimates from distance sampling were less precise (2005 CV = 9.6%, 2006 CV = 7.9%). Assumptions of distance sampling were violated in our study because probability of detecting bobwhites near the observer was <1 or the roadside survey points were not randomly distributed with respect to the birds. Distances also were not consistently recorded by individual members of observer pairs. Although double-observer surveys provided more precise estimates, we recommend using the removal method to estimate detectability and abundance of bobwhites. The removal method provided precise estimates of density and detection probability and requires half the personnel time as double-observer surveys. Furthermore, the likelihood of meeting model assumptions is higher for the removal survey than with independent double-observers. © 2011 The Wildlife Society.     

Factors Influencing Survival of Radiotagged and Banded Northern Bobwhites in Georgia

Abstract: Numerous studies of behavior and ecology of northern bobwhites (Colinus virginianus) have depended on radiotagging and telemetry for data collection. Excluding the presumably short-term effects of trapping, handling, and attaching radiotransmitters, researchers often assume that little bias is associated with estimating survival and behavioral parameters associated with this technique. However, researchers have not adequately examined these effects on organisms being investigated and have thus assumed demographic information obtained from such methods are valid. In light of this conjecture, it is imperative to evaluate methodological assumptions to ensure research is statistically valid and biologically meaningful. Therefore, we used Burnham's model and program MARK to analyze survival estimates of individually banded and radiotagged bobwhites during an 8-year period (1997–2004) consisting of 6,568 individuals (2,527 radiotagged) via combined analysis of mark—recapture, dead recovery (via harvest), and radiotelemetry data to test the effects of radiotransmitters on bobwhite survival. We also compared band—recapture survival estimates to Kaplan—Meier survival estimates, and we examined the effects of various other factors (e.g., temporal, spatial) on bobwhite survival. Based on Akaike's model selection criterion, the best model including the radiotransmitter covariate (Akaike's Information Criterion adjusted for small sample size bias and overdispersion relative value = 0.72) did not explain more of the variation in survival than models without this effect. Thus, we found the effect of radiotransmitters as negligible. Bobwhite survival varied relative to spatial (e.g., site), temporal (e.g., yr and season), and gender effects. Average annual survival for the 8-year period was 22.76% (1.50 SE) for banded-only and 21.72% (1.49 SE) for radiotagged birds. Survival rate varied annually, ranging from 12.42% (7.51 SE) to 37.16% (8.27 SE), and seasonally, ranging from 23.82% (2.71 SE) to 65.06% (3.23 SE); however, between group (banded-only, radiotagged) survival differences were still inconsequential. We conclude that for our study, radiotelemetry provided reliable survival estimates of an intensively managed bobwhite population, where supplemental food was provided, and this information provided useful data to make practical habitat management decisions. We believe that future radiotelemetry studies would benefit as a whole if researchers conducted similar analyses prior to presenting their results from radiotelemetry data, especially for populations that are more food limited.     

A population model to simulate northern bobwhite population dynamics in southern Texas

Models are important tools that can help managers and researchers understand the population dynamics of a species and how different habitat or population management scenarios impact that species. We used radio-telemetry data from northern bobwhites (Colinus virginianus) in southern Texas from 2000 to 2005 to develop a stochastic simulation model for bobwhite populations. Our model is based on difference equations, with stochastic variables drawn from normal and Weibull distributions. We simulated bobwhite populations to 100 yr and evaluated our model by comparing results with independent estimates of 4 population parameters (spring and fall density, finite rate of increase in the fall population [λ], and winter juv:ad age ratios). Using a quasi-extinction criterion of ≤40 birds (density = ≤0.05 birds/ha), probability of persistence to 100 yr was 88.3% (106 of 120 simulations) for the spring population and 96.7% (116 of 120 simulations) for the fall population. Using a less restrictive quasi-extinction criteria (≤14 birds), probability of persistence was 93.3% (112 of 120 simulations) for the spring population and 98.3% (118 of 120 simulations) for the fall population. Simulated population parameters were similar to independent estimates for 4 of 4 population parameters. Winter age ratios differed between our model ( juv:ad, n = 120, SE = 0.32) and empirical age ratios from harvested bobwhites on our study area ( juv:ad, n = 25, SE = 0.24). However, when we corrected harvest age ratios for bias in juvenile harvest ( juv:ad, n = 25, SE = 0.32) simulated and empirical estimates were similar. Our model appears to be a reliable predictor of bobwhite populations in the southern Texas. Our simulation results indicate that bobwhite hunters and managers can expect excellent bobwhite hunting (fall populations ≥2.2 birds per ha) in about one of 10 yr. © 2011 The Wildlife Society     

Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep

Aerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)-collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.     

Optimal group size and northern bobwhite coveys

Northern bobwhite, Colinus virginianus, form social units, called coveys, during the nonbreeding season (approximately September-April). Because the evolutionary advantage of this behaviour is generally unknown, we used controlled group size manipulations within an aviary to investigate whether group size influences (1) the time that the covey spends feeding, (2) the percentage of the covey that is vigilant, (3) the overall vigilance of the group and (4) the time to predator detection. We found that increasing group size increased the time that coveys spent in an exposed feeding area, reduced individual vigilance, improved group vigilance and decreased the time to detection of a potential predator. Additionally, we used experimental reductions of wild northern bobwhite coveys to test whether groups size influences (1) individual and covey survival, (2) daily movement in maintaining covey size and (3) mass change. We conducted field research on 12 independent 259-ha study areas (6 control plots and 6 treatments, where 60% of the population was removed) in east-central Kansas, U.S.A. between 9 November and 31 January, 1997-2000. We radio-marked 386 radiocollared individuals that comprised 137 groups on the study areas. Covey size did not differ between or within years or treatments (X±SE: 10.98±0.22 individuals). Our results indicate that a stable group size existed between 1 and 22 individuals, with 11 being an optimal group size. Small coveys (1-7 individuals) had lower group persistence and individual survival, and used increased movement to create or join larger groups where survival was higher. Large groups (15-22) had lower individual survival, increased group movement and individual mass loss. Density-dependent feedbacks (e.g. lower survival and increased competition) may have lowered larger coveys to a stable size. Our results suggest the regulation of an optimal covey size of 11 was promoted by high group persistence, low group movement, improved feeding efficiency, improved individual predator detection and improved individual survival. Copyright 2003 Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour.      

Developing the Concept of Estimating Bobwhite Density With Pointing Dogs

Abstract: Currently available methods of estimating northern bobwhite (Colinus virginianus) abundance are often expensive and time-consuming; therefore, additional research is necessary to develop new tools. Using Global Positioning System (GPS) and Geographic Information System technologies and distance-sampling theory, we developed a method of estimating bobwhite density during hunts with pointing dogs. Data collection occurred during the 2005–2006 and 2006–2007 hunting seasons in western Oklahoma and northern Texas, USA. We estimated effective strip width (ESW) of a bird dog's path using distance-sampling theory and point-to-flush distances. For coveys >7 birds (n = 58), estimated ESW was 13.2 m (95% CI = 11.1–15.6 m). Area searched by one dog was its GPS path buffered by ESW. For ≥2 dogs, area searched was the union of the areas of individual dogs; taking the union eliminated between- or among-dog redundancy in searched areas. A point estimate of density was number of birds flushed on a hunt divided by searched area. During the 2005–2006 hunting season, bobwhite density averaged 1.4 birds/ha (60.28 SE; n = 33). Average density declined to 0.2 birds/ha (60.07 SE) during 2006–2007 (n = 46). Estimating bobwhite density with pointing dogs needs further testing and development, but the technique may prove useful in research and management.     

Quick methods for evaluating survival of age-characterizable long-lived territorial birds

Survival is a key life-history trait in animals. However, most methods of survival estimation require substantial human and economic investment in the long term, particularly in species occurring in low densities, the case of most endangered species. An alternative to traditional recapture (CR) methods is estimation of adult survival based indirectly on either age ratios (AGR) or turnover rates (TOR) in territorial species. These 2 methods are applicable to bird species in which recruited individuals enter into the breeding population whilst still exhibiting the external traits that distinguish those animals from experienced adults. The main advantages of these methods are that survival can be easily estimated for all monitored individuals after just 1 or 2 breeding seasons and that disturbance to the species is minimized. The main constraints of indirect methods are that the assumptions are more restrictive than in CR methods, and survival estimates, although comparable between sites and years, may be biased. We used data from a long-term monitoring survey of 2 populations of the endangered Bonelli's eagle (Aquila fasciata), one in Catalonia (NE Spain) and the other in Provence and Languedoc-Roussillon (SE France). We evaluated survival estimates using the AGR and TOR methods and compared them with CR methods and provide suitable corrections for refining survival estimates based on indirect methods. In Catalonia (2002–2008), survival was estimated at 0.84 by CR methods (SE = 0.047; n = 25 radio tagged eagles), at 0.86 by the corrected AGR method (SE = 0.011; n = 558 bird * year), and at 0.86 by the corrected TOR method (SE = 0.022; n = 547 bird * year). In France (1999–2008), survival was estimated at 0.88 by CR methods (SE = 0.040; n = 45 darvic banded eagles), at 0.87 by the corrected AGR method (SE = 0.015; n = 443 bird * year), and at 0.87 by the corrected TOR method (SE = 0.015; n = 438 bird * year). All analyses suggest that females survive better than males and that individuals from the French population survive better than individuals from the Catalan population. We conclude that indirect methods, which should not be regarded as a substitute of CR methods, will allow wildlife managers and researchers to estimate accurately adult survival in a territorial species over a short period of time and to monitor survival across populations over large geographic ranges and over time. © 2011 The Wildlife Society.     

Raising the bar for the next generation of biological atlases: using existing data to inform the design and implementation of atlas monitoring

Selecting a sampling design to monitor multiple species across a broad geographical region can be a daunting task and often involves tradeoffs between limited resources and the accurate estimation of population abundance and occurrence. Since the 1950s, biological atlases have been implemented in various regions to document the occurrence of plant and animal species. As next‐generation atlases repeat original surveys, investigators often seek to raise the rigour of atlases by incorporating species abundances. We present a repeatable framework that incorporates existing monitoring data, hierarchical modelling and sampling simulations to augment existing atlas occurrence and breeding status maps with a secondary sampling of species abundances. Using existing information on three bird species with varying abundance and detectability, we evaluated several sampling scenarios for the 2nd Wisconsin Breeding Bird Atlas. In general, we found that most sampling schemes produced accurate mean statewide abundance estimates for species with medium to high abundance and detection probability, but estimates varied significantly for species with low abundance and low detection probability. Our approach provided a statewide point‐count sampling design that: provided precise and unbiased abundance estimates for species of varied prevalence and detectability; ensured suitable spatial coverage across the state and its habitats; and reduced spending on total survey costs. Our framework could benefit investigators conducting atlases and other broad‐scale avian surveys that seek to add systematic, multi‐species sampling for estimating density and abundance across broad geographical regions.