Occupancy and detectability of Snowy Plovers in western Utah: an application to a low density population

Occupancy modeling can be used to identify habitat characteristics associated with species occurrence. Additionally, occupancy sampling can provide measures of detection probability, increasing confidence in monitoring efforts. Little is known about the distribution and habitat preferences of a small population of Snowy Plovers (Charadrius nivosus) in western Utah. We conducted a study to estimate occupancy and detection probability of Snowy Plovers in western Utah during 2011 and 2012. We made repeated visits to randomly selected survey plots during the breeding period, sampling 84 64‐ha plots in 2011 and 100 64‐ha plots in 2012 and recording the number of adults and habitat characteristics in each plot. We then modeled the relationship between detection, occupancy, and covariates that included distance to water, distance to roads, land cover types, and characteristics of the vegetation. We also included covariates for observer, Julian date, temperature, cloud cover, and wind speed when modeling detection probability. Detection probability was high (0.74, 95% CI = 0.57–0.86) and positively influenced by temperature. Occupancy of 64‐ha plots was low (0.27, 95% CI = 0.18–0.39) and did not vary by year. Occupancy of Snowy Plovers was negatively associated with distance to water (β = ?0.62 ± 0.31, 95% CI = ?1.23 to ?0.01) and percent shrub cover (β = ?0.28 ± 0.02, 95% CI = ?0.58 to ?0.01). Land cover types also influenced plot occupancy. Management actions that conserve shallow water and adjacent habitats or minimize disturbance in these areas are likely to have conservation benefits for Snowy Plovers where water is scarce. Because our detection probabilities were high, investigators involved in future monitoring efforts can achieve reasonable precision with limited revisits to sample plots.     

Occupancy patterns of an apex avian predator across a forest landscape

Apex predators are integral parts of every ecosystem, having top‐down roles in food web maintenance. Understanding the environmental and habitat characteristics associated with predator occurrence is paramount to conservation efforts. However, detecting top order predators can be difficult due to small population sizes and cryptic behaviour. The endangered Tasmanian masked owl (Tyto novaehollandiae castanops) is a nocturnal predator with a distribution understood to be associated with high mature forest cover at broad scales. With the aim to gather monitoring data to inform future conservation effort, we trialled an occupancy survey design to model masked owl occurrence across ~800 km² in the Tasmanian Southern Forests. We conducted 662 visits to assess masked owl occupancy at 160 sites during July–September 2018. Masked owl site occupancy was 12%, and estimated detectability was 0.26 (±0.06 SE). Cumulative detection probability of masked owls over four visits was 0.7. Occupancy modelling suggested owls were more likely to be detected when mean prey count was higher. However, low detection rates hindered the development of confident occupancy predictions. To inform effective conservation of the endangered Tasmanian masked owl, there is a need to develop novel survey techniques that better account for the ecology of this rare, wide‐ranging and cryptic predator. We discuss the potential to combine novel census approaches that exploit different aspects of masked owl ecology to obtain more robust and detailed data.     

A Comparison of Methods for Estimating Northern Bobwhite Covey Detection Probabilities

Abstract: We compared the time-of-detection and logistic regression methods of estimating probability of detection for northern bobwhite (Colinus virginianus) coveys. Both methods are unusual in that they allow estimation of the total probability of detection (i.e., the product of the probability that a covey is available for detection [i.e., that a covey vocalizes] and detection given availability). The logistic regression method produced an average detection probability of 0.596 (SE = 0.020) and the time-of-detection method produced a detection probability estimate of 0.540 (SE = 0.086), and the 2 estimates were not significantly different. This is the first evaluation of the time-of-detection method with empirical field data. Although the time-of-detection and logistic regression method each have advantages, both can be used under appropriate conditions to improve estimates of bobwhite abundance by allowing for the estimation of detection probabilities. Improved estimates of bobwhite abundance will allow land managers to make more informed management decisions.     

Captive breeding and reintroduction of the endangered masked bobwhite

Efforts to restore the endangered masked bobwhite (Colinus virginianus ridgwayi) to its former range have required 1) habitat acquisition, restoration, and preservation; 2) captive propagation; and 3) reintroduction of captive-bred stock. In its role to recover the masked bobwhite, the Patuxent Wildlife Research Center (U.S. Fish and Wildlife Service) has refined captive breeding techniques; provided captive-produced stock for release; conducted field research on the distribution, limiting factors, and habitat characteristics of this species; and developed release methods. Techniques for the husbandry and captive management, breeding, artificial incubation and hatching of eggs, and rearing of young of the masked bobwhite have been developed. Successful reintroduction techniques for the masked bobwhite have included prerelease conditioning and/or cross-fostering of captive-reared masked bobwhite chicks to a wild-caught, related, vasectomized bobwhite species and their release to the wild as family units. In addition, the establishment by the U.S. Fish and Wildlife Service of the Buenos Aires National Wildlife Refuge in 1985 has further enhanced the potential for establishing a self-sustaining population of the masked bobwhite in the U.S. Through continued releases and active management of habitat, therefore, it is believed that the masked bobwhite can become permanently established at the refuge to ensure its continued survival in the wild.     

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.     

Nonconsumptive effects of hunting on a nontarget game bird

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Automated auditory detection of a rare,secretive marsh bird with infrequent and acoustically indistinct vocalizations

Autonomous recording units (ARUs) provide a non-invasive and efficient method for acoustic detection of elusive species across large temporal and spatial scales. However, species with indistinct vocalization structures can be a considerable challenge for automated signal recognizers. We investigated the performance of ARUs and signal recognizers in identifying the broadband, short-syllable, pulsed calls of a secretive, threatened marsh bird, the King Rail Rallus elegans. Other sympatric species in the same habitat also have repetitive calls within the same frequency range that can be difficult to distinguish. Following serial ARU deployments at specified sites in known breeding habitat, we conducted standardized callback surveys and nest searches to provide an independent measure of breeder density. To analyse recordings, we developed a signal recognizer based on user-input training files to detect two common call types, kek and grunt. Detections that remained following manual review of recognizer output revealed a previously undescribed seasonal decline and crepuscular diel pattern in calling rate. The rate of the grunt call also predicted density. These patterns emerged despite the recognizer's low precision and high false-positive rate, which were largely due to misclassification of other species' calls, although ambient noise and effective detection radius also limited the detectability of King Rail calls. We demonstrate that with informed ARU scheduling, improved ability to manipulate user-specified parameters within signal detection software, and attention to quality control, even the simplest call structures can be located consistently in a diverse acoustic landscape. Our behavioural findings will inform improvements to auditory surveys and to management of King Rails across their range.     

Increased yolk testosterone facilitates prenatal perceptual learning in Northern bobwhite quail (Colinus virginianus)

Prenatal learning plays an important role in the ontogeny of behavior and birds provide a useful model to explore whether and how prenatal exposure to hormones of maternal origin can influence prenatal learning and the development of behavior. In this study we assessed if prenatal exposure to yolk testosterone can influence auditory learning in embryos of Northern bobwhite quail (Colinus virginianus). We experimentally enhanced testosterone concentrations in bobwhite quail eggs prior to incubation. The embryos from these T-treated eggs as well as control embryos that had received the vehicle-only or were non-treated were exposed to an individual bobwhite hen's maternal call for 120 min over the course of the day prior to hatching. All chicks were tested at 24 h following hatching for their auditory preference between the familiar bobwhite maternal call versus an unfamiliar bobwhite maternal call. T-treated chicks spent significantly more time in proximity to the familiar call compared to the unfamiliar call and also showed shorter latencies to approach the familiar call than control birds. Increased emotional reactivity, i.e. propensity to express fear responses, was also found in T-treated chicks. Baseline heart rates recorded in a second group of T-treated embryos and control embryos did not differ, which suggests no effect of yolk testosterone on baseline arousal level. To our knowledge this is the first demonstration of the influence of prenatal exposure to testosterone on auditory learning.     

Resistance is futile: effects of landscape features on gene flow of the northern bobwhite

Habitat for the northern bobwhite (Colinus virginianus) has declined and changed drastically in spatial structure throughout the last century. Undoubtedly such changes have impacted bobwhite and may have altered their ability to access available habitat. We investigated whether landscape resistance, geographic distance, or interstate highway barriers were related to dispersal and gene flow of bobwhite in central and southern Illinois. Landscape resistance was determined from two empirically informed models depicting habitat suitability for bobwhite. During 2007–2008, hunters submitted bobwhite tissue samples from which we amplified 11 microsatellites. The relationship between individual genetic distances and spatial variables was analyzed with Mantel tests and causal modeling was used to verify the spatial variables influencing gene flow. Genetic distance was correlated with geographic distance but showed no relationship with interstate highway barriers. Habitat suitability did not enhance gene flow, and was inversely related in some partial Mantel tests. We suggest that bobwhite dispersal from suitable habitat patches may be less frequent than from suboptimal habitats. Bobwhite may be able to access suitable habitat across gaps of unsuitable habitat but distance limits their dispersal. Because available habitat for bobwhites may have a greater likelihood of being colonized when closer to occupied habitat, we suggest that lands closer to occupied habitat should be targeted for conservation or habitat improvement efforts.     

Three-dimensional analysis of aphid landing behaviour in the laboratory and field

The final second of the landing approach of black bean aphids, Aphis fabae, was analysed in three dimensions using video techniques. A yellow landing platform was placed upwind or downwind from aphids aggregating under a ceiling light in a laboratory wind tunnel with 10, 20, 30, 40 or 50 cm s^–1 wind speeds, and up-tunnel or down-tunnel in still air. As individual aphids flew to the platform, body orientation (assessed by direct observation) was predominantly into-wind whether the initial flight direction to the landing platform was upwind or downwind. A greater proportion showed into-wind body orientation as wind speed increased. Flight track parameters which differed significantly between wind speeds were the track length, linear start to finish distance, linearity index, horizontal ground speed, speed vertical to the ground, vertical turning rate, and horizontal turning rate. The position of the landing platform was important for track length, linear start to finish distance, horizontal ground speed, three-dimensional turning rate, horizontal turning rate, vertical turning rate, and sinuosity. As wind speed increased above 30 cm s^–1 the ground speed became more consistent and indicated considerable variation in air speed to adjust for ground speed. For the majority of aphids there was a strong preference (88%) for into-wind landings with initial upwind directed flight, while for downwind flights a significant number (55%) of insects reversed initial flight direction and landed into-wind. Field recorded landings showed that 66% of aphids landed into-wind and there was a mean bearing to the wind of 71 ± 42°, a similar finding to wind-tunnel studies.     

Aspects of northern bobwhite ecology on south Florida US pastureland

During 2004 and 2005, we monitored breeding season survival, home range, habitat use, density, and reproduction of northern bobwhite (Colinus virginianus) in the peninsular region of Florida, USA. We radio-tagged 81 birds across a 20-km² cattle ranch consisting predominately of rotationally grazed pastureland. Birds were radio-tracked three to five times per week until mortality or the transition to nonbreeding season. We found no difference in home range size among the sexes, ages, or their interaction. Mean home range size pooled for years, sexes, and age class was 56.28 ha (±7.87 SE). Home ranges of bobwhites were not distributed among habitats randomly (second order: Λ?=?0.10; 7, 35 df; P?=?0.002). In addition, bobwhites did not use the habitats within their home range at random (third order: Λ?=?0.14, 5, 35 df; P?=?0.02). Estimated seasonal survival was 0.28 (±0.12 SE) and was best explained by the time-dependent model. Reproductive metrics indicated adequate reproduction and values consistent with the bobwhite literature. Bobwhite density (birds per hectare) in 2004 was 0.52 (±0.54 95 % confidence interval [CI]) and 0.75 (±0.51 95 % CI) for 2005. These results suggest that pastureland landscapes managed with rotational grazing can support bobwhite populations, albeit at low densities. More conservation attention should be directed towards improving these systems for bobwhite restoration.     

Quail and rain in semiarid rangelands: Does management matter?

Rainfall is a strong driver of quail populations on southwestern rangelands and can account for a large portion (~70–95%) of the variability in regional quail production and abundance. Landowners have attempted to moderate these boom-and-bust fluctuations via management; however, presently it is unknown whether management can increase or stabilize quail populations in semiarid environments or whether rainfall remains as influential at small spatial extents. Our objectives were to evaluate the efficacy of management at mitigating the effects of rainfall on northern bobwhite (Colinus virginianus) populations on semiarid rangelands and to quantify the influence of rainfall on bobwhite density at smaller spatial extents. We conducted a study to evaluate these objectives during 2014–2020 in the Rio Grande Plains (n = 11 sites; 1,100‒6,500 ha) and Rolling Plains (n = 4 sites; 1,900‒4,000 ha) of Texas, USA. We estimated bobwhite density during late autumn (Dec‒Jan) on all sites using helicopter surveys within a distance-sampling framework. We also obtained site-level seasonal rainfall (Apr‒Aug) and quantified management intensity via landowner surveys and a scoring rubric to categorize sites into 3 classes (low, medium, and high management intensity). Bobwhite populations during this study experienced a boom-bust cycle in both the Rio Grande Plains and Rolling Plains, with mean bobwhite density fluctuating considerably (0.57‒2.96 bobwhites/ha and 0.02‒2.88 bobwhites/ha, respectively). In the Rio Grande Plains, mean bobwhite density significantly increased from low to high management intensity in 2015 (1.12 ± 0.17 bobwhites/ha vs. 2.87 ± 0.39 bobwhites/ha, respectively), 2016 (1.06 ± 0.20 bobwhites/ha vs. 2.96 ± 0.36 bobwhites/ha, respectively), 2017 (0.73 ± 0.16 bobwhites/ha vs. 1.91 ± 0.32 bobwhites/ha, respectively), and 2019 (0.42 ± 0.14 bobwhites/ha vs. 1.01 ± 0.26 bobwhites/ha, respectively; P < 0.05). In addition, rainfall at the site level accounted for a low amount of the variation in bobwhite density (r² = 0.09; P < 0.01). Similarly, in the Rolling Plains, mean bobwhite density significantly increased from low to high management intensity in 2015 (1.30 ± 0.27 bobwhites/ha vs. 2.20 ± 0.29 bobwhites/ha, respectively) and 2016 (1.26 ± 0.26 bobwhites/ha vs. 2.88 ± 0.34 bobwhites/ha, respectively; P < 0.05). Rainfall at the site level also accounted for a low amount of the variation in bobwhite density (r² < 0.02; P = 0.82). Our findings suggest that management can increase bobwhite density beyond that of less-managed properties but does not completely eliminate inter-annual fluctuations in semiarid environments. In addition, rainfall appears to exert less of an influence on bobwhite density at a site level (e.g., 2,000 ha) than has been documented at a regional level (e.g., ≥8 million ha).     

The effect of soundscape composition on bird vocalization classification in a citizen science biodiversity monitoring project

There is a need for monitoring biodiversity at multiple spatial and temporal scales to aid conservation efforts. Autonomous recording units (ARUs) can provide cost-effective, long-term and systematic species monitoring data for sound-producing wildlife, including birds, amphibians, insects and mammals over large areas. Modern deep learning can efficiently automate the detection of species occurrences in these sound data with high accuracy. Further, citizen science can be leveraged to scale up the deployment of ARUs and collect reference vocalizations needed for training and validating deep learning models. In this study we develop a convolutional neural network (CNN) acoustic classification pipeline for detecting 54 bird species in Sonoma County, California USA, with sound and reference vocalization data collected by citizen scientists within the Soundscapes to Landscapes project (www.soundscapes2landscapes.org). We trained three ImageNet-based CNN architectures (MobileNetv2, ResNet50v2, ResNet100v2), which function as a Mixture of Experts (MoE), to evaluate the usefulness of several methods to enhance model accuracy. Specifically, we: 1) quantify accuracy with fully-labeled 1-min soundscapes for an assessment of real-world conditions; 2) assess the effect on precision and recall of additional pre-training with an external sound archive (xeno-canto) prior to fine-tuning with vocalization data from our study domain; and, 3) assess how detections and errors are influenced by the presence of coincident biotic and non-biotic sounds (i.e., soundscape components). In evaluating accuracy with soundscape data (n = 37 species) across CNN probability thresholds and models, we found acoustic pre-training followed by fine-tuning improved average precision by 10.3% relative to no pre-training, although there was a small average 0.8% reduction in recall. In selecting an optimal CNN architecture for each species based on maximum F(β = 0.5), we found our MoE approach had total precision of 84.5% and average species precision of 85.1%. Our data exhibit multiple issues arising from applying citizen science and acoustic monitoring at the county scale, including deployment of ARUs with relatively low fidelity and recordings with background noise and overlapping vocalizations. In particular, human noise was significantly associated with more incorrect species detections (false positives, decreased precision), while physical interference (e.g., recorder hit by a branch) and geophony (e.g., wind) was associated with the classifier missing detections (false negatives, decreased recall). Our process surmounted these obstacles, and our final predictions allowed us to demonstrate how deep learning applied to acoustic data from low-cost ARUs paired with citizen science can provide valuable bird diversity data for monitoring and conservation efforts.     

Departure of migrating European robins, Erithacus rubecula, from a stopover site in relation to wind and rain

Migratory birds replenishing their fuel stores have to decide when to leave their stopover site for the next flight bout. We studied whether the decision to leave a stopover site depends on wind and rain conditions. From capture-recapture data of 1153 European robins collected during three autumns at a stopover site in Switzerland, we estimated the daily emigration probability with a newly developed multistate capture-recapture model that accounts for the occurrence of transients. We tested whether the variation in the daily emigration probabilities can be explained by wind speed, wind direction (both on the ground and 300 m above ground) or rain. Variation in emigration probability was largely explained by variation in wind at 300 m and rain. The emigration probability was highest (0.5) during nights with no or weak (<1.5 m/s) winds at 300 m and no rain, intermediate (0.15-0.2) on nights without rain and with medium wind (>1.5 m/s), and on nights with weak winds (<1.5 m/s) and rain; and almost zero during nights with rain and strong winds at 300 m. Wind direction at 300 m and wind conditions (speed and direction) on the ground had no influence on departure decision. We suggest that birds may consider cues other than wind speed at ground level to predict wind speed at higher altitudes, and that they consider wind direction only when aloft by selecting an optimal flight altitude. Wind speed aloft and rain appeared to be significant factors that synchronize bird migration spatially and temporally.     

The dispersal and deposition of hydrochorous plant seeds in drainage ditches

1. Surface water is an important dispersal vector for wetland plant species. However, most previous studies on hydrochory (i.e. water dispersal) have focused on ecosystems with relatively rapid water flow. Therefore, there is a need to study such dispersal in slow‐flowing or stagnant waterbodies, such as drainage ditches, which might act as dispersal corridors between habitat patches. 2. To gain insight into the mechanisms by which seeds are transported in drainage ditches, the effect of the velocity of wind and water on the rate of transport of floating seeds of three wetland species (Carex pseudocyperus L., Iris pseudacorus L. and Sparganium erectum L.) was investigated. Furthermore, in release and retrace experiments with painted C. pseudocyperus seeds, a number of factors potentially determining the probability of seed deposition were investigated. 3. Net wind speed was found to be the main factor determining the rate at which seeds are transported in drainage ditches. No relation between water flow at middepth in the ditches and seed transport was found. Wind speed and flow at the water surface were positively related. The effect of wind speed on the rate of transport of floating seeds was greater for S. erectum seeds, because a greater ratio of their volume protrudes from the water, than for C. pseudocyperus and I. pseudacorus seeds. 4. The principal factors that determine seed deposition were aquatic plant cover, ditch slope and indentations in the ditch bank. Seeds changed direction if the wind direction changed, or if there was a bend in the ditch. The final pattern of deposition was related to mean net wind speed. Mean transport distance after 2 days varied between 34 and 451 m. 5. Unlike in rivers, seed transport in ditches was determined by wind speed and direction, enabling multidirectional seed dispersal. We conclude that in slow‐flowing waters, wind is a more important driver for hydrochorous seed transport than the flow of water. This sheds a new light on hydrochory and has important consequences for the management of otherwise fragmented wetland remnants.     

An improved multi-scale approach to modeling habitat occupancy of northern bobwhite

Predicting species presence requires knowledge of detection of individuals, scale of model variables, model selection uncertainty, and spatial autocorrelation. Our objective was to incorporate recent modeling advances to predict potential habitat occupancy of northern bobwhite (Colinus virginianus). From 15 May–15 August 2008 and 2009, we conducted repeat-visit surveys at 360 sites within Delaware to sample presence of bobwhite. We randomly selected half the data to model scale-dependent relationships of bobwhite presence with metrics of landscape- and site-scale habitat composition and configuration. The final averaged habitat-occupancy model fit the remainder testing dataset with an area under the receiver operating characteristic curve value of 0.62. At the site scale, bobwhite presence was negatively related to interspersion and juxtaposition of early successional habitat (ESH; grassland and shrubland), ESH to forest edge density, and agriculture to forest edge density, though relative effect sizes were weak to moderate after accounting for model selection uncertainty. At the landscape scale, bobwhite presence was negatively related to patch cohesion of human development within 2.5 km and positively related to patch cohesion of ESH within 2.0 km, with both variables exerting strong effects. Bobwhite presence was also weakly and positively related to percentage of shrubland habitat within 1.0 km of the sampling point. We applied our habitat occupancy model to map the predicted presence of breeding bobwhite within the Delmarva Peninsula, USA. The modeling results and distribution map will provide guidance to State and Federal private land management programs in the Mid-Atlantic to identify where habitat management efforts will be most effective. Our methodology can also serve as a basis for future habitat modeling of bobwhite and other grassland–shrubland species across their range. © 2011 The Wildlife Society.     

Climate alters the movement ecology of a non‐migratory bird

Global climate change is causing increased climate extremes threatening biodiversity and altering ecosystems. Climate is comprised of many variables including air temperature, barometric pressure, solar radiation, wind, relative humidity, and precipitation that interact with each other. As movement connects various aspects of an animal''s life, understanding how climate influences movement at a fine‐temporal scale will be critical to the long‐term conservation of species impacted by climate change. The sedentary nature of non‐migratory species could increase some species risk of extirpation caused by climate change. We used Northern Bobwhite (Colinus virginianus; hereafter bobwhite) as a model to better understand the relationship between climate and the movement ecology of a non‐migratory species at a fine‐temporal scale. We collected movement data on bobwhite from across western Oklahoma during 2019–2020 and paired these data with meteorological data. We analyzed movement in three different ways (probability of movement, hourly distance moved, and sinuosity) using two calculated movement metrics: hourly movement (displacement between two consecutive fixes an hour apart) and sinuosity (a form of tortuosity that determines the amount of curvature of a random search path). We used generalized linear‐mixed models to analyze probability of movement and hourly distance moved, and used linear‐mixed models to analyze sinuosity. The interaction between air temperature and solar radiation affected probability of movement and hourly distance moved. Bobwhite movement increased as air temperature increased beyond 10°C during low solar radiation. During medium and high solar radiation, bobwhite moved farther as air temperature increased until 25–30°C when hourly distance moved plateaued. Bobwhite sinuosity increased as solar radiation increased. Our results show that specific climate variables alter the fine‐scale movement of a non‐migratory species. Understanding the link between climate and movement is important to determining how climate change may impact a species’ space use and fitness now and in the future.     

Factors affecting detection probability of burrowing owls in southwest agroecosystem environments

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

Northern Bobwhites and Postfire Succession

ABSTRACT Our study evaluated the effects of prescribed fire on northern bobwhites (Colinus virginianus) occupying native rangelands in Rolling Plains of Texas, USA, during 2002 and 2003. Prescribed fires were conducted during February of 1996, 1998, and 2000; pastures with no recent treatment history served as controls. We quantified bobwhite densities from line transects using distance sampling. We used a repeated-measures analysis of variance to test for treatment-year differences in bobwhite densities. We measured postfire herbaceous and woody vegetation attributes and evaluated vegetation relationships to bobwhite density using simple linear regression. We found significant between-year differences in fall bobwhite densities (F = 13.05, df = 3, P = 0.036) but no differences among treatments or controls. Fall bobwhite densities were inversely related to visual obstruction (r² = 0.179, df = 15, P = 0.058) and positively associated with increasing heterogeneity of grass cover (r² = 0.416, df = 15, P = 0.004). Our results suggest prescribed fire at large spatial scales may be a neutral practice for managing bobwhite habitat on semiarid rangelands.