Stephen J. DeMaso

Survival and cause-specific mortality of northern bobwhites in western Oklahoma

Abstract We present descriptive data on survival and cause-specific mortality of northern bobwhites (Colinus virginianus) in western Oklahoma, USA, during 1991–2002. We captured and radiomarked 2,647 bobwhites (286 adult [ad] M, 1,064 juvenile [juv] M, 185 ad F, and 1,049 juv F) to obtain estimates. We estimated that annual survival (Nov–Oct) averaged 0.068 ± 0.018 (SE) and ranged between 0.018 ± 0.048 and 0.211 ± 0.038. We pooled data over the study period and found that sex–age classes survived at similar rates. We estimated average annual isolated rates of bobwhite mortality (rates in the absence of other causes) to be 0.63 ± 0.027 from raptor predation, 0.45 ± 0.021 from mammal predation, and 0.45 ± 0.043 from harvest. Under the additive theorem of probability, the isolated rates translated to an average annual mortality rate of 0.88 ± 0.017. The bobwhite population had variable and sometimes low survival in November–February inclusive. Low monthly survival (<0.5, n = 7) during winter was due primarily to harvest (0.57 ± 0.099 losses/known-fate individual) and raptor predation (0.25 ± 0.051 losses/known-fate individual). We discuss evidence indicating that radiotransmitters handicapped bobwhites and resulted in survival estimates biased low and to uncertainty in interpretation of cause-specific mortality.

Northern bobwhite (Colinus virginianus) abundance in relation to yearly weather and long-term climate patterns

Abstract We used a multilayered, backpropagation neural network to investigate the relative effects of yearly weather and long-term climate patterns on the abundance of northern bobwhites (Colinus virginianus: hereafter, bobwhite) in Oklahoma, USA. Bobwhite populations have been declining for several decades across the United States, and predicted global climate change might accelerate the rate of decline. We were interested in whether bobwhite abundance was more responsive to yearly precipitation and temperature, or to annual deviations from long-term mean climate patterns. We used roadside count data collected over a 6 year period (1991–1997) by the Oklahoma Department of Wildlife Conservation as a measure of bobwhite abundance. We standardized quail counts among counties by calculating the standard normal deviate for each county. Weather data were obtained from weather stations closest to the roadside-count route. We had 280 training cases and 68 test-validation cases. Two data sets were constructed: one using yearly weather data (actual rainfall and temperature) and the second using annual deviations from long-term mean values. We conducted simulation analyses to determine the nature of the relationship between each dependent variable and the standardized bobwhite counts. A neural network with eight neurons was most efficient for the yearly weather data, accounting for 25% of the variation in the training data. The adjusted sum-of-squares for this model was 2.42. A four-neuron network was selected for the deviation-from-normal data set, accounting for 23% of the variation in the training data. The adjusted sum-of-squares for the deviation model was 1.44, indicating it performed better than the model for yearly weather patterns. Deviation from long-term mean July and August temperatures combined contributed 31.5% to the climate networks predictions, and deviations from mean winter, spring, and summer precipitation combined contributed 42.8% to the networks predictions. As July temperature increased over the long-term mean, the number of bobwhites counted increased over the route mean, but the relationship decelerated at high July temperatures. Predicted increases in bobwhites counted were highest when August temperatures were below the mean and decreased rapidly for all temperatures greater than the mean. Predicted bobwhite counts increased asymptotically as winter rain increased over the long-term mean, but were greatest at mean spring-rainfall amounts and at below average amounts of summer rainfall. We conclude that the absolute changes in yearly weather pattern predicted by some global change models will not have as great an impact on bobwhite abundance as will the magnitude of the deviations of these values from the climate bobwhites are adapted to in this portion of their range.

Survival of northern bobwhite chicks in Western Oklahoma

We estimated survival for chicks within 59 northern bobwhite (Colinus virginianus) broods using a modification of the Mayfield method that allows for brood mixing and intrabrood dependence. Broods were monitored during 1992-94 on the Packsaddle wildlife Management Area in western Oklahoma. Daily survival rates (DSR) were calculated for chicks reared by both female and male parents, chicks from hatching to 20 days old, chicks from 21 to 39 days old, chicks from hatching to 39 days old, by year, and pooled over years. Survival rates of brood mates were dependent on each other (P < 0.0001); therefore, the entire brood was the appropriate sampling unit for estimating variation associated with chick survival. Daily survival rate estimates for chicks in broods raised by females and males did not differ. Daily survival rates of chicks ≤20 days old were not significantly less than DSRs of chicks ≥21 days old. No differences were observed among years for DSR of chicks pooled over sexes ≤20 days old or chicks ≥21 days old (P = 0.9997). Chick DSR pooled over the entire brood-rearing period (x = 39 days, SE = 4.1 days) did not differ among years for either sex or pooled over sexes. Survival estimates pooled over sex and years for chicks from hatching to 20 days old and from 21 to 39 days old were 37.9 and 96.8%. The estimate of chick survival pooled over sex and years from hatching to 39 days was 36.7%.

Relative abundance of bobwhites in relation to weather and land use

Weather and land use are important factors influencing the population dynamics of northern bobwhites (Colinus virginianus) in Texas and elsewhere. Using an artificial neural network, we studied the effects of these factors on an index of bobwhite abundance (hereafter, index) in 6 ecoregions in Texas. We used roadside-count data collected by the Texas Parks and Wildlife Department (TPWD) during 1978-1997. Weather variables were June, July, and August mean maximum temperatures, and winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and fall (Sep-Nov) rainfall. We also included the proportion of county area in cultivation, the number of livestock per hectare of noncultivated land, and the previous years bobwhite count in the analyses. The data were partitioned into training and validation data sets prior to analyses. The neural model explained 65% of the variation in the training data (n = 72) and 61% of the variation in the validation data (n = 17). The most important variables contributing to network predictions were July temperature, fall rainfall, cattle density, and the previous years bob-white count. State-level simulation results indicated that the bobwhite index decreased with increasing June temperature and livestock density. The bobwhite index increased with July and August temperature, fall rainfall, and the previous years bobwhite count. Bobwhite abundance increased with the proportion of county area in cultivation up to approximately 20% cultivation and then declined. Winter, spring, and summer rainfall had little effect on the bobwhite index. Although many relationships appeared approximately linear or were decelerating, proportion of county area in cultivation and livestock density on noncultivated land showed strongly curvilinear responses. Therefore, cultivation up to approximately 20% of county area was beneficial, but the benefits disappeared as cultivation increased beyond this level. Further, at low livestock densities, between 0.15 and 0.40 head/ha, small increases in head/ha resulted in a decrease in the bobwhite index of 156.4%/head/ha. The results also indicated that a potential bias might exist in the survey protocol resulting in artificially inflated counts under some weather conditions.

Fitness Costs and Benefits Associated with Dispersal in Northern Bobwhites (Colinus virginianus)

Abstract Movements and dispersal distances are fundamental aspects of ecology and evolutionary biology. Northern bobwhites (Colinus virginianus) generally are considered the least mobile of all gallinaceous species, but dispersal events of bobwhites (commonly referred to as “shuffling”) are well known. Although dispersal may be a key component in regulating population densities and inbreeding avoidance, few studies have attempted to explain relationships between dispersal, mortality and nest success in northern bobwhites. To examine these relationships, we monitored 957 radio-marked bobwhite from 1991 to 1996. Mean dispersal distance did not differ between sexes (P = 0.699). Mean dispersal distances of adults (2821 m) were shorter than those of juveniles (3411 m; P = 0.042). We found no sex- or age-related differences in survival rates among dispersers and non-dispersers. Despite associated risks with increased movement activity in unfamiliar areas, survival rate was 1.5-times greater for dispersers (Ŝ = 0.72) than non-dispersers (Ŝ = 0.50). Further, we found no relationships between nest success and dispersal distance, suggesting that dispersal distance had little influence on reproductive output of bobwhites. Thus, dispersers may play a key role in bobwhite population dynamics whereby declining populations escape extinction through recruitment from productive populations.

Land cover and bobwhite abundance on Oklahoma farms and ranches

To test prevailing paradigrns of habitat management for northern bobwhites (Colinus virginianus), we analyzed relations between the abundance of these birds, land-cover classes, and landscape metrics on Oklahoma farms and ranches (200-ha areas; n = 78) during 1998-1999. Based on replicated call-count indices, bobwhites declined (-0.03 to -0.07 males/ha; 95% confidence level here and below) with the quantity of an area in mature woodland, and increased (0.02 to 0.05 males/ha) with the quantity of brushy prairie or early successional woodland. We observed highest populations in the absence of cropland agriculture. Bobwhites declined as Shannon diversity of cover types (-6.0 to -0.01 males/Shannon unit), patch richness (-0.08 to -0.02 males/patch), and the density of woody edge (-0.027 to -0.003 males/m/ha) increased. Bobwhites responded more strongly to the composition of land-cover classes on areas than to the configuration of these classes in areas. Our results did not support the patchwork agriculture model of bobwhite abundance or the principle of edge. Results were consistent with a hypothesis that predicts bobwhite abundance is a nondecreasing function of usable space in time.

The role of farm policy in achieving large-scale conservation : Bobwhite and buffers

Abstract The Farm Bill provides a policy vehicle for implementing conservation programs with the potential to alter land use on a large spatial scale. The conservation payments under the Farm Bill dwarf the collective investment of the North American Wetlands Conservation Act, Endangered Species Act, Pittman-Robertson Act, and Conservation and Reinvestment Act. However, the ecological value of past policy has varied by program, practice, region, and wildlife species, resulting in a broad array of wildlife habitat and population effects ranging from positive to negative. We argue the conservation provisions of the Farm Bill can produce more consistent positive wildlife habitat benefits when policy (program statutes, rules, practices, and practice standards) is developed in the context of explicit goals identified as part of large-scale conservation initiatives. For example, initiatives like the North American Waterfowl Management Plan, Partners in Flight, and the Northern Bobwhite Conservation Initiative (NBCI) set science-based goals and objectives to facilitate wildlife species population recovery and sustainability at the landscape scale. We contend that the best ecological and societal cost/benefit ratio is achieved when Farm Bill conservation programs and practices are developed to address these specific habitat goals. We present a case study illustrating how a Conservation Reserve Program option (Conservation Practice 33—Habitat Buffers for Upland Birds) specifically addresses NBCI goals and objectives. We discuss the successes, failures, and lessons learned by NCBI in policy formulation, practice development, programmatic delivery, and evaluation.

Effects of radiotransmitters on body mass, feed consumption, and energy expenditure of northern bobwhites

Abstract Radiotelemetry is commonly used in northern bobwhite (Colinus virginianus) research. An underlying assumption is that radiomarked individuals provide unbiased estimates of population parameters. Our objectives were to evaluate the effects of radiotransmitters on body mass and feed consumption of radiomarked and banded-only pen-raised bobwhites in a controlled environment and to compare daily energy expenditure (kJ/g/day) between treatments in a simulated field setting. We randomly assigned a treatment (i.e., radiomarked or banded-only) to 40 pen-raised bobwhites and placed them in individual cages (51- × 27- × 28-cm) within an environmental chamber. We conducted 2 separate 21-day experiments to simulate summer (35°C daytime high, 23.9°C nighttime low, 15-hour photoperiod) and winter conditions (18.3°C daytime high, 4.4°C nighttime low, 10-hour photoperiod) typical for south Texas. For the field experiment, we evaluated energy expenditure via doubly labeled water for radiomarked (n=5) and banded-only pen-raised bobwhites (n=5) in a flight pen (50- × 30- × 4-m). We documented no difference in change in body mass or feed consumption between radiomarked and banded-only bobwhites during either experiment (P>0.05). We also found no difference in daily energy expenditure between radiomarked (0.839 ± 0.056 kJ/g/day) and banded-only pen-raised bobwhites (0.804 ± 0.014 kJ/g/day; P=0.77).

The relationship of Rio Grande wild turkey distributions to roads

Wildlife Society Bulletin 2005, 33(2):745–748 Peer refereed Distance sampling from roads is a common population estimation technique used for many wildlife species (Brennan and Block 1986, DeYoung and Priebe 1987, Borralho et al. 1996, Dahlheim et al. 2000). A critical assumption of the distance sampling technique is that the distribution of animals is not influenced by the transect, but this assumption may be violated if the transect is a road (Burnham et al. 1980, Buckland et al. 2001, Williams et al. 2001). Attraction of target animals to the transect will result in inflated population estimates, and withdrawal from the transect will bias the estimates low (Verner 1985,Thompson et al. 1998, Buckland et al. 2001). Many authors have suggested line transects should not be positioned along roadways unless individuals are randomly distributed across the landscape (Burnham et al. 1980, Buckland et al. 2001, Williams et al. 2001). Male Rio Grande wild turkeys (Meleagris gallopavo intermedia) likely use roads as display sites in south Texas; thus, population surveys using roads should be conducted outside of the breeding season to reduce the probability of wild turkeys being attracted to roads (DeYoung and Priebe 1987). Eastern wild turkeys (M. g. silvestris) in Virginia used areas >450 m from roads more than expected and areas <150 m from roads in proportion to availability (McDougal et al. 1990). In Arizona, male Merriam’s wild turkeys (M. g. merriami) used areas <200 m from roads less than expected (Rogers et al. 1999). However, none of those studies examined the relationship of roads to wild turkey distributions during specific seasons and time periods. Our objectives were to quantify the association of male and female Rio Grande wild turkeys to roads according to season and time of day, and examine the potential biases of using roads as transects for distance sampling. We conducted this research in order to help develop appropriate protocols for distance sampling of Rio Grande wild turkeys from roads.

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 3 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 winter 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.