Road-Based Surveys for Estimating Wild Turkey Density in the Texas Rolling Plains

Abstract: Line-transect-based distance sampling has been used to estimate density of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys during autumn (Aug-Nov) and winter (Dec-Mar) 2003-2005 at study sites in the Texas Rolling Plains, USA, to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks using logistic regression models. Our modeling effort suggested that distance to a flock and flock size played important roles in flock detectability. We also conducted surveys from roads for wild turkeys during November 2004-January 2006. The detection probability of decoy flocks was similar to wild turkey flocks during winter (decoy flock, 69.3 ± 6.2% [x̄ ± 95% CI]; wild turkey flock, 62.2 ± 18.3%) and autumn (decoy flock, 44.1 ± 5.1%; wild turkey flock, 44.7 ± 25.6%), which suggested that using decoys was appropriate for evaluating detectability of wild turkey flocks from roads. We conducted computer simulations to evaluate the performance of line-transect-based distance sampling and examined the power to detect trends in population change. Simulations suggested that population density may be underestimated by 12% during inter and 29% during autumn. Such bias occurred because of incomplete detectability of flocks near roads. Winter surveys tended to have less bias, lower relative variability, and greater power than did autumn surveys. During winter surveys, power was sufficient (≥0.80) to detect a 10-25% change in population density in 8-12 years using ≥100 16-km transects or ≥80 32-km transects. We concluded line-transect-based distance sampling from roads is an efficient, effective, and inexpensive technique for monitoring Rio Grande wild turkey populations across large scales.     

Wild turkey (<Emphasis Type="Italic">Meleagris gallopavo</Emphasis>) detectability from helicopters and ramifications for estimating abundance

Aerial surveys have been used to estimate abundance for several wild bird species but its application for wild turkey (Meleagris gallopavo) populations has been limited. We surveyed Rio Grande wild turkey (M. gallopavo intermedia) populations during March 2006 using an R44 helicopter. We used flocks with radio-tagged birds to estimate flock detectability. We also used simulations to evaluate accuracy and precision and examine power to detect trends in population change. We observed that wild turkey flock detectability was 94.7% (74.0–99.9%; 95% CI). Our simulations suggested helicopter surveys would underestimate abundance by about 5.6% (4.6% CV). Surveying 980 to 1,960 km² (requiring 27 to 55 h of flight time) can provide sufficient power (≥0.80) to detect a 10 to 25% change in abundance over a 4- to 5-year period.     

Encounter Rates From Road-Based Surveys of Rio Grande Wild Turkeys in Texas

ABSTRACT Traditional index-based techniques have indicated declines in Rio Grande wild turkey (Meleagris gallopavo intermedia; hereafter, wild turkey) populations across much of Texas, USA. However, population indices can be unreliable. Research has indicated that road-based surveys may be an efficacious technique for monitoring wild turkey populations on an ecoregion level. Therefore, our goal was to evaluate applicability of road-based distance sampling in the Cross Timbers, Edwards Plateau, Rolling Plains, and South Texas ecoregions of Texas. We conducted road-based surveys in each ecoregion during December 2007—March 2008 to estimate wild turkey flock encounter rates and to determine survey effort (i.e., km of roads) required to obtain adequate sample sizes for distance sampling in each ecoregion. With simulations using inflatable turkey decoys, we also evaluated effects of distance to a flock, flock size, and vegetative cover on turkey flock detectability. Encounter rates of wild turkey flocks from road-based surveys varied from 0.1 (95% CI = 0.0–0.6) to 2.2 (95% CI = 0.8–6.0) flocks/100 km surveyed. Encounter rates from surveys restricted to riparian communities (i.e., areas ≤1 km from a river or stream) varied from 0.2 (95% CI = 0.1–0.6) to 2.9 (95% CI = 1.5–6.7) flocks/100 km surveyed. Flock detection probabilities from field simulations ranged from 22.5% (95% CI = 16.3–29.8%) to 25.0% (95% CI = 13.6–39.6%). Flock detection probabilities were lower than expected in all 4 ecoregions, which resulted in low encounter rates. Estimated survey effort required to obtain adequate sample sizes for distance sampling ranged from 2,765 km (95% CI = 2,597–2,956 km) in the Edwards Plateau to 37,153 km (95% CI = 12,861–107,329 km) in South Texas. When we restricted road-based surveys to riparian communities, estimated survey effort ranged from 2,222 km (95% CI = 2,092–2,370 km) in the Edwards Plateau to 22,222 km (95% CI = 19,782–25,349 km) in South Texas.     

Errors in aerial survey count data: Identifying pitfalls and solutions

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double‐observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.     

The Effects of Predation Risk, Food Abundance, and Population Size on Group Size of Brown-Headed Cowbirds (Molothrus ater)

Social and ecological conditions can influence flock formation (e.g. number of flocks, flock size, etc.) depending on the degree of social attraction of a species. We studied group formation in brown‐headed cowbirds (Molothrus ater) over short time periods (30 min) in two semi‐natural experiments conducted under controlled conditions. First, we determined the shape of the relationship between intake rate and flock size by manipulating group size in a single enclosure. Second, we assessed the role of population size, food abundance, and predation risk, and their interactions, in flock size formation in a system of four enclosures (two with and two without food) connected to a central refuge patch. In the first experiment, we found that pecking rates peaked at intermediate flock sizes (three to six individuals), which was influenced by greater availability of foraging time and more aggressive interactions in large groups. In the second experiment, flock sizes in the patches with food increased with population size likely due to the benefits of patch exploitation in groups. Flock size decreased after predator attack probably because refuge availability reduced perceived predation risk more than flocking in larger groups. Food abundance had minor effects, varying flock sizes between the two patches with food, under high food availability conditions when population size was high, probably due to social cohesion effects. Our results suggest that: (1) this species has an inverted‐U food intake–group size relationship with a range of intake‐maximizing flock sizes rather than a single peak, (2) the presence of a near refuge modifies the expected benefits of group patch exploitation under high predation risk, and (3) an increase in population size would more likely be translated into rapid increases in the size of the flocks rather than in more new flocks.     

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)     

Modeling the flocking propensity of passerine birds in two Neotropical habitats

We examined the importance of mixed-species flock abundance, individual bird home range size, foraging height, and foraging patch characteristics in predicting the propensity for five Neotropical passerine bird species (Slaty Antwren, Myrmotherula schisticolor; Golden-crowned Warbler, Basileuterus culicivorus; Slate-throated Redstart, Myioborus miniatus; Wilson’s Warbler, Wilsonia pusilla; and Black-and-white Warbler, Mniotilta varia) to forage within flocks, rather than solitarily. We used study plots in primary mid-elevation forest and in shade coffee fields in western Panama. We expected that all species would spend as much time as possible flocking, but that the social and environmental factors listed above would limit compatibility between flock movements and individual bird movements, explaining variability in flocking propensity both within and among species. Flocking propensity was well predicted by home range size and flock abundance together, for four of the five species. While flock abundance was uniform across plots, home range sizes varied among species and plots, so that home range size appeared to be the principle factor limiting flocking propensity. Estimates of flock abundance were still required, however, for calculating flocking propensity values. Foraging height and patch characteristics slightly improved predictive ability for the remaining species, M. miniatus. In general, individual birds tended to join flocks whenever one was available inside their home range, regardless of a flock’s specific location within the home range. Flocking propensities of individual species were lower in shade coffee fields than in forests, and probably vary across landscapes with variations in habitat. This variability affects the stability and species composition of flocks, and may affect survival rates of individual species. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Statistical power of replicated helicopter surveys in southern African conservation areas

Understanding the ecology of large ungulates in southern Africa requires accurate and precise measures of population size. Recovery or exploitation of ungulates in reserves is currently instigated when population size changes exceed 15% per annum, but monitoring is usually undertaken with single counts from helicopters, for which precision and the power to detect change are untested. In essence, power being the strength of a monitoring result in showing change over time. Retrospective power analysis is a useful technique to investigate the variability of single‐count aerial surveys. Using replicated helicopter‐based counts of southern African ungulates and post hoc analysis, we investigated the power of currently used single‐count surveys across five common ungulate species and 11 wildlife reserves. We expected high variability in count data and set α = 0.1 and 0.2 (α being the type I error rate), and asked two questions: ‘How much does power vary in replicated aerial counts of southern African wildlife across reserves and species?’ and ‘Can current single‐count aerial surveys detect population changes in response to management actions or are the statistical errors intractable?’ Single counts were mostly unreliable; only one of 42 had sufficient power to detect meaningful changes in population size or their trends at α = 0.1, and only three had sufficient power at α = 0.2. Power varied widely according to species (e.g. warthog, median power at α = 0.1; 0.12–0.37: blue wildebeest, median power at α = 0.1; 0.23–0.74), and, within species, between replicates and reserves. Our retrospective calculations demonstrated insensitivity and ineffectiveness in most currently applied single counts from helicopters. Consequently, it is impossible to interpret the effects of ungulate conservation actions on many southern African reserves. Retrospective power analyses enables determination of which previous aerial surveys were useful for population assessment and adaptive management, and which should be discarded. We recommend that prospective power analyses are undertaken to determine future helicopter survey sample size and replication requirements, especially in small reserves.     

Estimation of Detection Probability in Manatee Aerial Surveys at a Winter Aggregation Site

Abstract: Estimating components of detection probability is crucial to improving the design of aerial surveys for wildlife populations, and this is especially true for species of marine mammals that are threatened or endangered. To evaluate the probability that Florida manatees (Trichechus manatus latirostris) will be detected by observers during aerial surveys, we conducted 6 series of survey flights, during mornings and afternoons on 14-16 consecutive days over the Tampa Electric Company's (TECO) Big Bend power plant discharge canal in Tampa Bay, Florida, USA (winter 2000 through 2003). Our objective was to understand how our ability to detect manatees at a winter aggregation site affects aerial survey counts, so that we may improve techniques for estimating manatee population size. We estimated the probability that manatees would be present at the warm-water discharge of the plant during winter cold fronts and estimated the overall detection probability of manatees present at the plant and the 2 components that make up the probability of detection (the probability of being available and the probability of being detected given they are available). We used telemetry tags and marker flags (n = 15) to facilitate capture-recapture analyses. The probability that marked manatees would be at the plant varied from 48% to 68% across flight series and was inversely related to the ambient water temperature. Based on sightings of marked animals, estimates of the overall probability of detecting a manatee ranged from 45% to 69% across flight series (x̄ = 58%, n = 6). The probability that a manatee would be available to an observer ranged from 73% to 94% across flight series (x̄ = 83%) but was constant among years (83%, 81%, and 78%; x̄ = 81%). The probability that an available manatee would be detected by an aerial observer was variable across flight series (55-95%) and years (73%, 86%, and 66%, x̄ = 73%). Independent estimates of the probability that a manatee would be available to the observer on one pass were obtained from time-depth data loggers and ranged from 5% to 33% (x̄ = 19%, SE = 3.7%), and the probability that a manatee would be available during ≥1 of 10 passes ranged from 41% to 98% (x̄ = 88%, 95% confidence bounds 0.71-0.95). We adjusted survey counts using measures of detectability. Although corrected counts presented here are site-specific, adjusting counts based on detection probability will greatly improve reliability of population estimates from all aerial surveys. Special sampling to estimate components of detection probability should be built into all aerial surveys to ensure that reliable and unbiased information on species abundance is used to evaluate wildlife populations.     

Age-specific differences in the winter foraging strategies of rooks Corvus frugilegus

Summary Foraging efficiency and intraspecific competition were compared between wild adult and immature rooks Corvus frugilegus with respect to flock size. Behavioural time budgets, and observations of prey selection and prey energetic values revealed that adult rooks in large flocks (> 50 individuals) consumed smaller, less profitable prey, but allocated more time to feeding and fed at a faster rate and with greater success than adults in small flocks. By contrast, immature rooks in flocks of more than 30 individuals allocated proportionally less time to feeding, fed at a lower rate and fed with no increase in success rate than when foraging in smaller flocks. Agonistic encounters and the avoidance of adults by immature rooks appeared responsible for such inefficient foraging. Hence immature rooks showed a preference for smaller flocks (< 50 individuals) with low adult: immature ratios while adults preferred larger flocks (> 50 individuals). We discuss the possible influence of competitive disadvantages on immature rook distribution, flock composition and post-natal dispersal.     

云南省纳帕海自然保护区越冬黑颈鹤的集群特征

2004年10月-2005年5月,在云南纳帕海自然保护区采用定点扫描法对越冬黑颈鹤(Grus nigricollis)的集群类犁和集群大小进行了观察.结果表明黑颈鹤夜间集群夜栖,形成较大的夜栖群,平均群体大小为67.9只(16-157,n=17):按照有无灰鹤加入,又将其分为同种集群和混种集群两种类型,其中同种集群的黑颈鹤数量占整个越冬种群的65.3%.在白昼,黑颈鹤以家庭鹤、集群鹤及特殊群体3种类型活动,家庭鹤和集群鹤的平均大小分别为2.7只(2-4,n=145)和16.1只(3-65,n=1017).黑颈鹤的集群大小并不稳定,在日内和月份间均有明显变化(P=0.000＜0.05).存越冬期,最大集群形成于12月,其次为11月和1月;在日内,早上8时集群最大,随后减小并保持相对稳定,18时黑颈鹤开始向夜栖地靠拢,使得集群再次开始增大.随后观察中还发现,黑颈鹤的家庭解体过程开始于3月底,当幼鹤被成鹤驱逐离群后,逐渐加入集群鹤活动,从而使得家庭鹤和集群鹤的大小和组成发生改变.黑颈鹤的集群大小和组成受自身状况、种内关系、天气、食物等多种因素的共同影响,随时间和季节变动而发生变化,是对自身、种群和环境条件变化的综合反映.     

To See or Not to See: Investigating Detectability of Ganges River Dolphins Using a Combined Visual-Acoustic Survey

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring.     

Age bias in the bag of pink-footed geese <Emphasis Type="Italic">Anser brachyrhynchus</Emphasis>: influence of flocking behaviour on vulnerability

In pink-footed goose (Anser brachyrhynchus) wintering in Denmark, The Netherlands and Belgium, the proportion of juveniles in the hunting bag is consistently higher than that observed in the autumn population. Such juvenile bias in the bag is usually ascribed to young geese lacking experience with hunting or disruption of juveniles from families. An alternative explanation may be that flocking behaviour of families make juveniles more vulnerable. Observations of morning flights of pink-footed geese to the feeding grounds from two of the major autumn-staging areas showed that geese were distributed in many small flocks (median flock size = 9). This was not significantly different from the flock size distribution shot at by hunters (median = 8), suggesting that hunters targeted goose flock size in proportion to the general probability of encounter. The rate at which hunters downed geese was independent of flock size. The ratio between juveniles and adults in flocks decreased with flock size and flocks of <60 individuals primarily comprised family groups. The likelihood of being shot at was 2.4 times higher for juveniles and 3.4 times higher for older birds in small flocks (<10 individuals) compared to larger flocks. The observations suggest that both juveniles as well as successful adult breeding birds were more vulnerable than non-breeding/failed breeding birds as a result of flocking behaviour.     

Comparison and Assessment of Aerial and Ground Estimates of Waterbird Colonies

Abstract: Aerial surveys are often used to quantify sizes of waterbird colonies; however, these surveys would benefit from a better understanding of associated biases. We compared estimates of breeding pairs of waterbirds, in colonies across southern Louisiana, USA, made from the ground, fixed-wing aircraft, and a helicopter. We used a marked-subsample method for ground-counting colonies to obtain estimates of error and visibility bias. We made comparisons over 2 sampling periods: 1) surveys conducted on the same colonies using all 3 methods during 3–11 May 2005 and 2) an expanded fixed-wing and ground-survey comparison conducted over 4 periods (May and Jun, 2004–2005). Estimates from fixed-wing aircraft were approximately 65% higher than those from ground counts for overall estimated number of breeding pairs and for both dark and white-plumaged species. The coefficient of determination between estimates based on ground and fixed-wing aircraft was ≤0.40 for most species, and based on the assumption that estimates from the ground were closer to the true count, fixed-wing aerial surveys appeared to overestimate numbers of nesting birds of some species; this bias often increased with the size of the colony. Unlike estimates from fixed-wing aircraft, numbers of nesting pairs made from ground and helicopter surveys were very similar for all species we observed. Ground counts by one observer resulted in underestimated number of breeding pairs by 20% on average. The marked-subsample method provided an estimate of the number of missed nests as well as an estimate of precision. These estimates represent a major advantage of marked-subsample ground counts over aerial methods; however, ground counts are difficult in large or remote colonies. Helicopter surveys and ground counts provide less biased, more precise estimates of breeding pairs than do surveys made from fixed-wing aircraft. We recommend managers employ ground counts using double observers for surveying waterbird colonies when feasible. Fixed-wing aerial surveys may be suitable to determine colony activity and composition of common waterbird species. The most appropriate combination of survey approaches will be based on the need for precise and unbiased estimates, balanced with financial and logistical constraints. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):697–706; 2008)     

Detection probability in aerial surveys of feral horses

Observation bias pervades data collected during aerial surveys of large animals, and although some sources can be mitigated with informed planning, others must be addressed using valid sampling techniques that carefully model detection probability. Nonetheless, aerial surveys are frequently employed to count large mammals without applying such methods to account for heterogeneity in visibility of animal groups on the landscape. This often leaves managers and interest groups at odds over decisions that are not adequately informed. I analyzed detection of feral horse (Equus caballus) groups by dual independent observers from 24 fixed-wing and 16 helicopter flights using mixed-effect logistic regression models to investigate potential sources of observation bias. I accounted for observer skill, population location, and aircraft type in the model structure and analyzed the effects of group size, sun effect (position related to observer), vegetation type, topography, cloud cover, percent snow cover, and observer fatigue on detection of horse groups. The most important model-averaged effects for both fixed-wing and helicopter surveys included group size (fixed-wing: odds ratio = 0.891, 95% CI = 0.850–0.935; helicopter: odds ratio = 0.640, 95% CI = 0.587–0.698) and sun effect (fixed-wing: odds ratio = 0.632, 95% CI = 0.350–1.141; helicopter: odds ratio = 0.194, 95% CI = 0.080–0.470). Observer fatigue was also an important effect in the best model for helicopter surveys, with detection probability declining after 3 hr of survey time (odds ratio = 0.278, 95% CI = 0.144–0.537). Biases arising from sun effect and observer fatigue can be mitigated by pre-flight survey design. Other sources of bias, such as those arising from group size, topography, and vegetation can only be addressed by employing valid sampling techniques such as double sampling, mark–resight (batch-marked animals), mark–recapture (uniquely marked and identifiable animals), sightability bias correction models, and line transect distance sampling; however, some of these techniques may still only partially correct for negative observation biases. © 2011 The Wildlife Society.     

Evaluating monitoring methods to guide adaptive management of a threatened amphibian (Litoria aurea)

Prompt detection of declines in abundance or distribution of populations is critical when managing threatened species that have high population turnover. Population monitoring programs provide the tools necessary to identify and detect decreases in abundance that will threaten the persistence of key populations and should occur in an adaptive management framework which designs monitoring to maximize detection and minimize effort. We monitored a population of Litoria aurea at Sydney Olympic Park over 5 years using mark–recapture, capture encounter, noncapture encounter, auditory, tadpole trapping, and dip‐net surveys. The methods differed in the cost, time, and ability to detect changes in the population. Only capture encounter surveys were able to simultaneously detect a decline in the occupancy, relative abundance, and recruitment of frogs during the surveys. The relative abundance of L. aurea during encounter surveys correlated with the population size obtained from mark–recapture surveys, and the methods were therefore useful for detecting a change in the population. Tadpole trapping and auditory surveys did not predict overall abundance and were therefore not useful in detecting declines. Monitoring regimes should determine optimal survey times to identify periods where populations have the highest detectability. Once this has been achieved, capture encounter surveys provide a cost‐effective method of effectively monitoring trends in occupancy, changes in relative abundance, and detecting recruitment in populations.     

Factors causing variation in flock size: Decision making to join a foraging flock

In order to clarify the temporal variation of flock size, we examined factors that cause the temporal variation of foraging flock size in a wintering population of the Yellow-throated bunting (Emberiza elegans). We conducted field observations to examine whether the flock size varies greatly and whether non-random associations between individuals exist. We confirmed that flock size varied greatly and some individuals showed non-random associations with other flock members. Then, we carried out computer simulations that assume stochastic risky situation, the condition of hunger level and non-random associations between individuals. In the simulation, the condition of hunger level caused the variation of flock size. However, the distribution of flock size differed from observed ones. When the condition of non-random association was added to the simulation, the variation of flock size became large and the distribution of flock size was similar to that of the observed one. In wintering flocks of Yellow-throated bunting, each individual attempts to forage in an optimal flock size. However, if they are extremely starved, it is suggested that they adopt a conditional strategy to join a flock independently of the flock size to acquire the energy necessary for survival. Simultaneously, they may decide to forage under the effect of non-random association between individuals.     

The effect of human disturbance and flock composition on the flight distances of waterfowl species

Flocking bird species tolerate an approaching human up to a certain distance. We measured this distance, i.e., flight distance, to an approaching small boat for 11 waterfowl species. The flight distances correlated positively with flock size and species diversity (Shannon index H′) in species that showed relatively short flight distances when they were in a single-species flock. However, we did not observe such a correlation for single-species flocks that showed relatively long flight distances. Only pochards (Aythya ferina), a species with large individual variation in flight distances, showed a positive correlation between flight distance and flock size in both single- and multispecies flocks. Flight distance seemed to be affected by usage of the water area: flight distances tended to be longer for waterfowl species that use a water area for foraging than for those that use it primarily for resting. Thus, the behavior of actively foraging species may be more affected by human disturbances than that of resting species. Received: March 10, 2001 / Accepted: May 22, 2001     

Detectability of lesser prairie-chicken leks: A comparison of surveys from aircraft

Lesser prairie-chickens (Tympanuchus pallidicinctus) are traditionally monitored by spring road-based lek surveys and counts of males attending leks. Several weaknesses exist with ground-based monitoring methods such as the bias of restricting surveys to roads, unknown probability of lek detection, and man-hours required to survey large tracts of habitat. We evaluated aerial surveys to locate lesser prairie-chicken leks in Texas and New Mexico using a Cessna 172 airplane (C172), R-22 Beta II helicopter (R-22), and R-44 Raven II helicopter (R-44) during spring 2007–2008. We determined lek activity during surveys with remote cameras placed on leks and cross-referenced time on the photo frame to time on our Global Positioning System flight log. From remote cameras we found that 305 leks were available for detection during survey flights. We determined lek detectability was 32.7% (95% CI = 20.3–47.1%) in the C172, 72.3% (64.50–79.14%) in the R-22, and 89.8% (82.0–95.0%) in the R-44. We created 16 a priori logistic regression models incorporating aircraft platform, distance to lek, survey date, lek size, and lek type to explain lek detection from aerial surveys. Our top ranked model included platform, distance, and lek type (model weight; w_i = 0.288). We had four competitive models and model averaged to draw inferences. Model averaging showed that detectability was generally greatest with the R-44, followed by the R-22, and lowest with the C172, with a slight deviation from this ranking at increased distances. Within our transect width, model averaging also suggested that detectability decreased as distance from the transect to the lek increased during helicopter surveys, and detectability increased as distance from the transect to the lek increased during C172 surveys. Furthermore, man-made leks were more likely to be detected than natural leks and large leks were more likely to be detected than medium or small leks. Aerial surveys effectively locate new leks and monitor lek density, and alleviate weaknesses associated with ground-based monitoring. We recommend using the R-44 to conduct lek surveys while flying at an altitude of 15 m at a speed of 60 km/hr on sunny mornings. © 2011 The Wildlife Society.     

Prevalence of Campylobacter spp. in turkey meat from a slaughterhouse and in turkey meat retail products

One hundred and forty-four samples of chilled turkey meat from six flocks, taken directly from the slaughterhouse, and 100 samples of turkey meat retail products were examined. Over one-quarter (29.2%) of the tested samples from the slaughterhouse were Campylobacter positive, showing high variability in the flocks. The lowest percentage of Campylobacter-positive samples was found in flocks I and III (8.3%), whereas, in flock VI, 91.7% of the samples were Campylobacter positive. Turkey meat retail products showed a prevalence of 34% for Campylobacter. Heat-treated meat was negative for Campylobacter. Quantitative studies of the samples taken at the slaughterhouse revealed a mean log range of 1.9-2.5 CFU g(-1)Campylobacter spp. Results from the quantification of retail products gave a mean log value of 2.1 CFU g(-1).