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Management boundaries are often delimited by political and social factors, whereas animal movements are affected by ecological and geophysical constraints. Thus, understanding connectivity among distinct management units is of considerable importance, particularly for harvested species, where quotas set in ignorance of connectivity may fail to meet management goals.We constructed an individual‐based model (IBM) to better understand wild turkey movements at large scales, benefiting from multiple data sources that are often available for harvested species.We built an IBM from spring seasonal movements of wild turkey, using data from ringed, radio‐, and GPS‐marked turkeys captured in Maine, USA. Our IBM accommodated variation in individual turkey response to landscape connectivity metrics and identified emergent migratory connectivity dynamics among harvest management regions.We calculated a low degree of connectivity among wildlife management districts (WMD) which, in combination with the substantial number of boundary crossings observed, indicated a more diffuse distribution of turkeys among WMDs.Synthesis and applications: Estimates of turkeys moving between districts provided a clear delineation of where immigration was strongest, identifying which WMDs should be managed as singular population units. This approach has widespread utility for any species or system where harvest management decisions are made at finer spatial scales than the movement dynamics affecting population processes. [ABSTRACT FROM AUTHOR]

Context. Stress or injury resulting from capture and marking of animals is a potential cause of mortality following release. Multiple methods have been developed to identify sources of postcapture mortality, but these are most often applied following completion of field work to identify an appropriate censor window for other analyses. Aims. Following unacceptable levels of post-capture mortality (13 of 53) in radio-marked individuals in the first year of a larger wild turkey research project in Maine, USA, we assessed post-capture survival as data became available to inform proactive changes to capture protocols, with the goals of improving animal welfare and data quality. Methods. We evaluated potential sources of post-capture mortality related to the capture and marking process, individual characteristics of the turkey, and local weather conditions. We then used results from the preliminary analysis to inform adaptive changes to capture protocols in subsequent years and confirmed the effectiveness of these changes through a final analysis. Key results. We found that greater handling time was positively correlated with increased postcapture survival, possibly in response to releasing turkeys in larger groupsto facilitate regrouping. We also found that transmitter style impacted post-capture survival, such that female turkeys fitted with backpack-style transmitters experienced a survivalrate of 0.787 (0.677–0.861 95%CI), compared with 0.903 (0.538–0.976 95% CI) for those fitted with a necklace transmitter, although adjustments to the fit of backpack transmitters appeared to help mitigate such issues. Conclusions. Following informed adjustments to our capture protocols, we observed a dramatic increase in post-capture survival such that no mortalities were experienced in the first 30 days post capture in the final year of our study (n= 65).Although our estimated censor window wassimilarto otherstudies(~10 days), differencesin effects of external stressors further the need for adaptive capture protocols because local stressors and risks may vary according to climate and ecosystem characteristics such as predator communities and habitat type. Implications.We recommend that when possible, investigators continuously assess their protocols throughout the capture process and adapt accordingly to limit negative repercussions of capture and handling to wildlife. [ABSTRACT FROM AUTHOR]

For wide‐ranging species in temperate environments, populations at high‐latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high‐latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state‐specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries. [ABSTRACT FROM AUTHOR]

Background: Sustainable Childhood Obesity Prevention Through Community Engagement is an initiative that engages stakeholders across multiple sectors to promote the Live-5-2-1-0 message (5 vegetables and fruits, 2 hours at most of recreational screen time, 1 hour of physical activity, 0 sugar-sweetened beverages each day) and implement action to support healthy behaviors. As part of this initiative, an intervention using the Live 5-2- 1-0 Toolkit for family physicians (FPs) was piloted in two communities. This study aimed to identify barriers and aids to toolkit implementation, and to determine whether the toolkit improves physicians' capacity to promote healthy childhood behaviors. Methods: FPs completed preintervention and postintervention surveys and participated in semistructured interviews after implementation of the Live 5-2-1-0 Toolkit intervention. Implementation occurred sequentially in two communities and involved a total of 21 FPs in six primary care clinics. Descriptive statistics were used for quantitative data, and content analysis was used for qualitative data. Results: Of the 21 participating FPs, 14 completed the preintervention and the postintervention surveys (67%) and 7 completed the preintervention survey only (33%). FPs reported increased knowledge of medical evaluation of pediatric patients with obesity (from 14% preintervention to 36% postintervention), behavioral goal setting (from 36% to 93%), and motivational interviewing (from 57% to 79%). FPs' perceived efficacy in addressing the subject of weight improved (from 43% preintervention to 93% postintervention). Increases were also observed in routinely addressing nutrition (from 43% preintervention to 79% postintervention), physical activity (from 50% to 79%), screen time (from 14% to 64%), and sugar-sweetened beverage consumption (from 29% to 71%). As a result of toolkit implementation, 71% of FPs felt their patients were more aware of long-term complications related to lifestyle, 64% felt patients were more willing to set behavioral goals with providers, and 50% felt patients were more able to selfmanage issues related to lifestyle. The predominant barrier to implementation was lack of staff/clinic capacity to measure BMI; the most noted aid to implementation was access to ready-to-use Live 5-2-1-0 resources. Conclusions: The Live 5-2-1-0 Toolkit facilitated health promotion to pediatric patients in the primary care setting. Increasing routine BMI measurement in primary care remains challenging due to clinical capacity issues. Results of this pilot study will be used to refine the toolkit prior to wider dissemination across British Columbia. [ABSTRACT FROM AUTHOR]

I thought I was lucky to work with good mentors in my previous two clinical placements but, somehow, I never gained much from them. In my current clinical placement in [...]