Spring Dispersal of Northern Bobwhites in Southwestern Ohio

Northern bobwhites (Colinus virginianus) historically occurred throughout Ohio but their core range has contracted to 18 southwestern counties. The Ohio Division of Wildlife has used trapping and transplanting to reintroduce wild bobwhites to unoccupied habitats within the species’ historic range. Bobwhite dispersal information is necessary to understand population dynamics and the species’ capacity to recolonize unoccupied habitats. Bobwhites were captured and radiomarked on 4 private-land study sites in southwestern Ohio. Radio-marked bobwhites (n 1⁄4 66) were tracked by homing or triangulation during spring 2010 and 2011 to ascertain dispersal distances between winter and breeding ranges. The spring dispersal period was defined by break-up of coveys and subsequent occupation of breeding season home ranges. The dispersal period, defined by non-affiliation with coveys, long directional daily movements, and observed breeding activity, varied among individuals and ranged from 2 April to 26 May. Dispersal distances were measured as the net Euclidean distance between locations recorded at the beginning and end of the dispersal period. Dispersers were defined as birds that moved . 23 the diameter of the mean home-range size (26.1 ha) observed during October-March 2010 and 2011. Movements of 1–2 home-range diameters were classified as home range shifts. Non-dispersing bobwhites traveled , 1 home-range diameter. Mean movement for all birds was 1.54 km. Twenty-eight (42.4%) radio-marked bobwhites were non-dispersers, 15 (22.7%) shifted home ranges, and 23 (34.8%) dispersed. Non-dispersers moved a mean of 0.31 km (range 1⁄4 0.03–0.56 km), home range shifts averaged 0.78 km (range 1⁄4 0.60–0.99 km), and dispersers traveled a mean distance of 3.6 km (range 1⁄4 1.18–11.5 km). Dispersal distance was lowest for adult females and increased in order for adult males, juvenile females, and juvenile males. Dispersal distance decreased as the proportion of early successional wooded habitat within winter home ranges increased. Sex, age, and dispersal distance did not affect survival. Our results suggest Ohio bobwhites are capable of expanding their range into historically-populated areas

Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species

Temporal and Spatial Assessment of Usable Space and Cover Type Interspersion for Northern Bobwhites on Private Farmlands in Southwestern Ohio

Contemporary landscape change driven by socio-economic forces and advances in agricultural technology do not favor northern bobwhites (Colinus virginianus) in the Midwestern United States. The challenge of bobwhite conservation is to provide sufficient quantities of habitat with optimal configurations in proportions that satisfy needs throughout the year on private-owned working lands. We radio-tracked 58 coveys and 98 individual birds throughout the year in 2009-10 and 2010-11 on privately owned farmland in southwestern Ohio. We investigated temporal changes in usable space from use-availability data. Estimated proportions of usable space based on analyses of habitat selection across four study sites were 0.06-0.12 during the non-breeding season compared to 0.10-10.30 during the breeding season. We also modeled probabilities that radio-marked coveys or individual birds used points within individual cover types as a function of distance to other cover types. Locations of radio-marked coveys and individual birds within focal cover types were closer to other cover types compared to random points during breeding (mean = 44 m) and non-breeding (mean = 58 m) seasons. Probability of use within focal cover types declined with distance to other cover types, typically falling below 50% when distances exceeded 9-242 m. Locations of radio-marked coveys were concentrated near edges within used cover types, while locations of individual birds were more dispersed during the breeding season. Estimated proportions of usable space based on distances between locations of radio-marked bobwhites and nearest cover types were higher (0.30-0.53) than estimates based on habitat selection ratios, and were similar between non-breeding and breeding seasons. Potentially usable sites were not fully occupied in either season, but there was no relationship between crude covey densities and proportions of usable space estimated from habitat selection analyses during the breeding and non-breeding seasons across study sites and years (r2 \u3c 0.166, P \u3e 0.316). With distance to cover type estimates of usable space (years combined), two study sites with the highest proportions of usable space (0.43-0.53) also had the largest crude covey densities (0.0065-0.153 coveys/ha) compared to the other two sites with lower proportions of usable space (0.30-0.32) and smaller covey densities (0.004 – 0.006 coveys/ha). Habitat enhancement should focus on providing protective cover near food for coveys during the non-breeding season and protective cover near nesting and brood-rearing habitat during the breeding season. Conserving Midwestern bobwhite populations requires innovative practices that can be implemented on private lands as economic incentives change for farm operators. Improving protective cover along habitat edges can increase usable space by improving cover type juxtaposition (e.g. food near cover) while minimizing impact on farming practices

Demographic Analysis of a Declining Northern Bobwhite Population in Southwestern Ohio

Northern bobwhite (Colinus virginianus) populations continue to decline throughout much of their range, especially in the Midwestern United States. Land use and habitat changes are understood to be the primary cause of decline, and it is unclear how vital rates affect growth of regional populations. We estimated relative abundance and population vital rates of bobwhites on 8 private land sites in southwestern Ohio during 2008–2011. Life stage simulation analyses were used to model the influence of 9 demographic parameters on population growth rates (k). All but one vital rate, chick survival, were modeled with empirical data randomly selected from normal distributions estimated (mean 6 SD) from our study population. The median value of k after 1,000 simulations was 0.248 (inter- quartile range 1⁄4 0.113-0.428). Non-breeding season survival was the dominant vital rate, explaining 50.4% of variation in k, followed by nest success (r2 1⁄4 0.163), and breeding season survival of adults (r2 1⁄4 0.083). Chick survival, egg success, and clutch size individually explained in order 1.4 to 4.6% of variation in k when modeled with survival estimates. Renesting, double-brooding, and male incubation individually explained , 1% of the variation in k. Total fecundity modeled as the sum across individual vital rate components explained 36.9% of variation in k. Non-breeding season survival was the most limiting population vital rate, but age ratios of fall-captured birds and simulated fecundity values indicated partial limitation by recruitment. Population stability (k 1⁄4 1) could be achieved by increasing non-breeding survival from 10.9 to 36.9%. Higher rates of nest success, the second most limiting vital rate, would not stabilize population growth unless survival rates also increased. Bobwhite conservation strategies should emphasize habitat enhancements designed to increase survival rates and useable space during the non-breeding season in Ohio and possibly other Midwestern states

Non-Adherence in Patients on Peritoneal Dialysis: A Systematic Review

Background: It has been increasingly recognized that non-adherence is an important factor that determines the outcome of peritoneal dialysis (PD) therapy. There is therefore a need to establish the levels of non-adherence to different aspects of the PD regimen (dialysis procedures, medications, and dietary/fluid restrictions). Methods: A systematic review of peer-reviewed literature was performed in PubMed, PsycINFO and CINAHL databases using PRISMA guidelines in May 2013. Publications on non-adherence in PD were selected by two reviewers independently according to predefined inclusion and exclusion criteria. Relevant data on patient characteristics, measures, rates and factors associated with non-adherence were extracted. The quality of studies was also evaluated independently by two reviewers according to a revised version of the Effective Public Health Practice Project assessment tool. Results: The search retrieved 204 studies, of which a total of 25 studies met inclusion criteria. Reported rates of nonadherence varied across studies: 2.6 1353% for dialysis exchanges, 3.9 1385% for medication, and 14.4 1367% for diet/fluid restrictions. Methodological differences in measurement and definition of non-adherence underlie the observed variation. Factors associated with non-adherence that showed a degree of consistency were mostly socio-demographical, such as age, employment status, ethnicity, sex, and time period on PD treatment. Conclusion: Non-adherence to different dimensions of the dialysis regimen appears to be prevalent in PD patients. There is a need for further, high-quality research to explore these factors in more detail, with the aim of informing intervention designs to facilitate adherence in this patient populatio

Constraints, Tradeoffs, and Opportunities for Conservation in Contemporary Landscapes

The challenges of achieving conservation goals increase as more people and competing land-uses are present on landscapes. In these landscapes, tradeoffs are inevitable, and people and nature cannot be considered independently. Instead, conservation planning needs to accommodate the complexities, challenges, and synergies within social-ecological systems. Therefore, the overall goal of my research was to develop and apply planning frameworks and tools to improve conservation decision making and bridge implementation gaps in multi-objective landscapes. To achieve this goal, multiple avenues of research were pursued including 1) outlining a conservation framework that considered suites of spatially- and implementation-specific objectives; 2) exploring protected land expansions that achieved social, economic, and ecological objectives; 3) investigating if subdivision improved strategic achievement of conservation goals, and 4) identifying key sources of decision-making uncertainty for a threatened species in the Northeast US. The Northeast US was an ideal landscape to study because the region has an intensive human footprint, even by global standards, but also a strong interest in maintaining its natural resources. To advance conservation efforts in this region, I focused on using methods that were systematic, transparent, and could move us from “knowing what to do” to actual implementation. Using multi-criteria decision methods, I illustrated how expanding the definition of conservation opportunity to include a suite of popular actions that were spatially explicit improved the effectiveness of planning efforts. I used genetic algorithms to iteratively generate and evaluate outcomes for protected land expansions that could navigated tradeoffs between social, economic, and ecological objectives. I applied a broad-scale, systematic subdivision process and demonstrated that socio-economically defined planning units could achieve conservation outcomes and reduce tradeoffs. I also used a value-of-information analysis to identify demographic and management uncertainties with the greatest impact on management and monitoring decisions for the threatened New England cottontail. Achieving contemporary conservation goals requires operating in human modified landscapes and ongoing implementation gaps highlight limitations in our current conservation planning approaches. My research identified frameworks and tools that accommodated landscape complexities and challenges and offered ways to navigate tradeoffs to achieve conservation outcomes

Season detection probability (p*) by season length (0–365 days) and array size (1, 2, 3, 5, 7, 10 cameras; lines) across four species (White-tailed deer, upper left; Raccoon, upper right; Virginia opossum, lower left; Bobcat, lower right), calculated by randomly parsing a yearlong data set with 5,000 Monte Carlo iterations.

<p>Lines represent best fit of nonlinear model in R using the <i>NLS</i> package and grey indicates 95% confidence intervals estimated from R package <i>confint</i>. Only a subset of the total array sizes are displayed to improve visual representation of data.</p