A toolkit modeling approach for sustainable forest management planning: Achieving balance between science and local needs

To assist forest managers in balancing an increasing diversity of resource objectives, we developed a toolkit modeling approach for sustainable forest management (SFM). The approach inserts a meta-modeling strategy into a collaborative modeling framework grounded in adaptive management philosophy that facilitates participation among stakeholders, decision makers, and local domain experts in the meta-model building process. The modeling team works iteratively with each of these groups to define osential questions, identify data resources, and then determine whether available tools can be applied or adapted, or whether new tools can be rapidly created to fit the need. The desired goal of the process is a linked series of domain-specific models (tools) that balances generalized "top-down" models (i.e., scientific models developed without input from the local system) with case-specific customized "bottom-up" models that are driven primarily by local needs. Information flow between models is organized according to vertical (i.e., between scale) and horizontal (i.e., within scale) dimensions. We illustrate our approach within a 2.1 million hectare forest planning district in central Labrador, a forested landscape where social hnd ecological values receive a higher priority than economic values. However, the focus of this paper is on the process of how SFM modeling tools and concepts can be rapidly assembled and applied in new locations, balancing efficient transfer of science with adaptation to local needs. We use the Labrador case study to illustrate strengths and challenges uniquely associated with a meta-modeling approach to integrated modeling as it fits within the broader collaborative modeling framework. Principle advantages of the approach include the scientific rigor introduced by peer-reviewed models, combined with the adaptability of meta-modeling. A key challenge is the limited transparency of scientific models to different participatory groups. This challenge can be overcome by frequent and substantive two-way communication among different groups at appropriate times in the model-building process, combined with strong leadership that includes strategic choices when assembling the modeling team. The toolkit approach holds promise for extending beyond case studies, without compromising the bottom-up flow of needs and information, to inform SFM planning using the best available science

Stillbirth and loss: family practices and display

This paper explores how parents respond to their memories of their stillborn child over the years following their loss. When people die after living for several years or more, their family and friends have the residual traces of a life lived as a basis for an identity that may be remembered over a sustained period of time. For the parent of a stillborn child there is no such basis and the claim for a continuing social identity for their son or daughter is precarious. Drawing on interviews with the parents of 22 stillborn children, this paper explores the identity work performed by parents concerned to create a lasting and meaningful identity for their child and to include him or her in their families after death. The paper draws on Finch's (2007) concept of family display and Walter's (1999) thesis that links continue to exist between the living and the dead over a continued period. The paper argues that evidence from the experience of stillbirth suggests that there is scope for development for both theoretical frameworks

Oral antibiotic prescribing patterns for treatment of pulmonary exacerbations in two large pediatric CF centers

Introduction: Oral antibiotics are frequently prescribed for outpatient pulmonary exacerbations (PEx) in children with cystic fibrosis (CF). This study aimed to characterize oral antibiotic use for PEx and treatment outcomes at two large US CF centers. Methods: Retrospective, descriptive study of oral antibiotic prescribing practices among children with CF ages 6–17 years over 1 year. The care setting for antibiotic initiation (clinic or phone encounter) was determined and outcomes were compared. Results: A total of 763 oral antibiotic courses were prescribed to 312 patients aged 6–17 years (77% of 403 eligible patients) with a median of two courses per year (range: 1–10). Fifty‐eight percent of prescriptions were provided over the phone. Penicillin was the most commonly prescribed antibiotic class (36% of prescriptions) but differences in antibiotic class prescriptions were noted between the two centers. Hospitalizations occurred within 3 months following 19% of oral antibiotic courses. Forced expiratory volume in 1 s (FEV1) recovered to within 90% of prior baseline within 6 months in 87% of encounters; the mean (SD) % recovery was 99.6% (12.1%) of baseline. Outcomes did not differ between phone and clinic prescriptions. Conclusions: Phone prescriptions, commonly excluded in studies of PEx, made up more than half of all oral antibiotic courses. Heterogeneity in prescribing patterns was observed between the two centers. Most patients had improvement in FEV1 returning to near their prior baseline, but hospitalizations occurred in one‐fifth following oral antibiotic treatment. Efforts to optimize PEx treatment must consider care that occurs over the phone; this is particularly important as the use of telemedicine increases.This work was supported by the Cystic Fibrosis Foundation (SANDERS18A1, HOPPE16A0)

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

[Comment] Redefine statistical significance

The lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on “statistically significant” findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (e.g., multiple testing, P-hacking, publication bias, and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: Statistical standards of evidence for claiming discoveries in many fields of science are simply too low. Associating “statistically significant” findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems. For fields where the threshold for defining statistical significance is P<0.05, we propose a change to P<0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called “significant” but do not meet the new threshold should instead be called “suggestive.” While statisticians have known the relative weakness of using P≈0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new (1, 2), a critical mass of researchers now endorse this change. We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (e.g., genomics and high-energy physics research; see Potential Objections below). We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P-values. However, changing the P-value threshold is simple and might quickly achieve broad acceptance