Increasing fire and the decline of fire adapted black spruce in the boreal forest.

Intensifying wildfire activity and climate change can drive rapid forest compositional shifts. In boreal North America, black spruce shapes forest flammability and depends on fire for regeneration. This relationship has helped black spruce maintain its dominance through much of the Holocene. However, with climate change and more frequent and severe fires, shifts away from black spruce dominance to broadleaf or pine species are emerging, with implications for ecosystem functions including carbon sequestration, water and energy fluxes, and wildlife habitat. Here, we predict that such reductions in black spruce after fire may already be widespread given current trends in climate and fire. To test this, we synthesize data from 1,538 field sites across boreal North America to evaluate compositional changes in tree species following 58 recent fires (1989 to 2014). While black spruce was resilient following most fires (62%), loss of resilience was common, and spruce regeneration failed completely in 18% of 1,140 black spruce sites. In contrast, postfire regeneration never failed in forests dominated by jack pine, which also possesses an aerial seed bank, or broad-leaved trees. More complete combustion of the soil organic layer, which often occurs in better-drained landscape positions and in dryer duff, promoted compositional changes throughout boreal North America. Forests in western North America, however, were more vulnerable to change due to greater long-term climate moisture deficits. While we find considerable remaining resilience in black spruce forests, predicted increases in climate moisture deficits and fire activity will erode this resilience, pushing the system toward a tipping point that has not been crossed in several thousand years.

Latent trajectory models for spatio-temporal dynamics in Alaskan ecosystems.

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a Bayesian hierarchical model to quantify the impact of climate change on the structural transformation of ecosystems using remotely sensed imagery. We used latent trajectory processes to model dynamic state probabilities that evolve annually, from which we derived transition probabilities between ecotypes. Our latent trajectory model accommodates temporal irregularity in survey intervals and uses spatio-temporally heterogeneous climate drivers to infer rates of land cover transitions. We characterized multi-scale spatial correlation induced by plot and subplot arrangements in our study system. We also developed a Pólya-Gamma sampling strategy to improve computation. Our model facilitates inference on the response of ecosystems to shifts in the climate and can be used to predict future land cover transitions under various climate scenarios.

Tree and shrub expansion at treeline drive contrasting responses in a subarctic passerine community.

Inferences about the mechanisms of distributional change are often made from simple assessments of variation in the geographical positions of populations. However, direct assessments of species' responses to local habitat change may be necessary for proper understanding of the drivers of distributional dynamics. Amplified climate warming is inducing cascading impacts in boreal-tundra regions including the expansion of conifers and deciduous shrubs (shrubs). In Denali National Park (Denali), Alaska, passerine birds are exhibiting rapid upslope shifts in distribution but the relative roles of conifer and shrub (woody vegetation) expansion in driving these shifts are unknown. Without directly assessing passerine-vegetation dynamics, the assumption has been that the observed upslope shifts are indicative of shrub-adapted passerines tracking the upslope expansion of shrubs. Here, we jointly investigate the processes of conifer and shrub expansion and their relationship to changes in passerine abundance in Denali. We used a remotely sensed vegetation cover timeseries (1985-2020) to assess the topographic and edaphic correlates of conifer and shrub expansion. We then assessed the impacts of changes in shrub and conifer cover on the relative abundance of 12 passerine species (1995-2020). Shrub and conifer colonization rates were highest at intermediate elevations near treeline. However, forest- and shrub-adapted passerines differed in terms of the location in which their response was concentrated relative to treeline. The population growth rates of forest-adapted passerines exhibited stronger effects of woody vegetation expansion at sites that were initially above treeline (IAT). In contrast, the population growth rates of shrub-adapted passerines exhibited the negative effects of conifer expansion together with the positive effects of shrub expansion at initially below treeline sites. However, they showed a weak response to woody vegetation expansion at sites that were IAT. Below treeline conifer infilling appears to be pushing the elevational distributions of shrub-adapted passerines upslope rather than these species following the pull of modest shrub expansion above treeline, as previously assumed. Overall, our findings illustrate the need for explicitly accommodating heterogeneity in habitat change at small spatial scales to properly view the distributional response, particularly when habitat change is concentrated at ecotones.

Genetic basis of growth reaction to drought stress differs in contrasting high-latitude treeline ecotones of a widespread conifer.

Climate change is increasing the frequency and intensity of drought events in many boreal forests. Trees are sessile organisms with a long generation time, which makes them vulnerable to fast climate change and hinders fast adaptations. Therefore, it is important to know how forests cope with drought stress and to explore the genetic basis of these reactions. We investigated three natural populations of white spruce (Picea glauca) in Alaska, located at one drought-limited and two cold-limited treelines with a paired plot design of one forest and one treeline plot. We obtained individual increment cores from 458 trees and climate data to assess dendrophenotypes, in particular the growth reaction to drought stress. To explore the genetic basis of these dendrophenotypes, we genotyped the individual trees at 3000 single nucleotide polymorphisms in candidate genes and performed genotype-phenotype association analysis using linear mixed models and Bayesian sparse linear mixed models. Growth reaction to drought stress differed in contrasting treeline populations. Therefore, the populations are likely to be unevenly affected by climate change. We identified 40 genes associated with dendrophenotypic traits that differed among the treeline populations. Most genes were identified in the drought-limited site, indicating comparatively strong selection pressure of drought-tolerant phenotypes. Contrasting patterns of drought-associated genes among sampled sites and in comparison to Canadian populations in a previous study suggest that drought adaptation acts on a local scale. Our results highlight genes that are associated with wood traits which in turn are critical for the establishment and persistence of future forests under climate change.

Multivariate Bayesian clustering using covariate-informed components with application to boreal vegetation sensitivity.

Climate change is impacting both the distribution and abundance of vegetation, especially in far northern latitudes. The effects of climate change are different for every plant assemblage and vary heterogeneously in both space and time. Small changes in climate could result in large vegetation responses in sensitive assemblages but weak responses in robust assemblages. But, patterns and mechanisms of sensitivity and robustness are not yet well understood, largely due to a lack of long-term measurements of climate and vegetation. Fortunately, observations are sometimes available across a broad spatial extent. We develop a novel statistical model for a multivariate response based on unknown cluster-specific effects and covariances, where cluster labels correspond to sensitivity and robustness. Our approach utilizes a prototype model for cluster membership that offers flexibility while enforcing smoothness in cluster probabilities across sites with similar characteristics. We demonstrate our approach with an application to vegetation abundance in Alaska, USA, in which we leverage the broad spatial extent of the study area as a proxy for unrecorded historical observations. In the context of the application, our approach yields interpretable site-level cluster labels associated with assemblage-level sensitivity and robustness without requiring strong a priori assumptions about the drivers of climate sensitivity.

Evaluating multiple historical climate products in ecological models under current and projected temperatures.

Gridded historical climate products (GHCPs) are employed with increasing frequency when modeling ecological phenomena across large scales and predicting ecological responses to projected climate changes. Concurrently, there is an increasing acknowledgement of the need to account for uncertainty when employing climate projections from ensembles of global circulation models (GCMs) and emissions scenarios. Despite the growing usage and documented differences among GHCPs, uncertainty characterization has primarily focused on GCM and emissions scenario choice, while the consequences of using a single GHCP to make predictions over space and time have received less attention. Here we employ average July temperature data from observations and seven GHCPs to model plant canopy cover and tree basal area across central Alaska, USA. We first compare the fit of, and support for, models employing observed temperatures, GHCP temperatures, and GHCP temperatures with an elevation adjustment, finding (1) greater support for, and better fit using, elevation-adjusted vs. raw temperature models and (2) overall similar fits of elevation-adjusted models employing temperatures from observations or GHCPs. Focusing on basal area, we next compare predictions generated by elevation-adjusted models employing GHCP data under current conditions and a warming scenario of current temperatures plus 2°C, finding good agreement among GHCPs though with between-GHCP differences and variation primarily at middle elevations (~1,000 m). These differences were amplified under the warming scenario. Finally, using pooled indices of prediction variation and difference across GHCP models, we identify characteristics of areas most likely to exhibit prediction uncertainty under current and warming conditions. Despite (1) overall good performance of GHCP data relative to observations in models and (2) positive correlation among model predictions, variation in predictions across models, particularly in mid-elevation areas where the position of treeline may be changing, suggests researchers should exercise caution if selecting a single GHCP for use in models. We recommend the use of multiple GHCPs to provide additional uncertainty information beyond standard estimated prediction intervals, particularly when model predictions are employed in conservation planning.

Stand basal area and solar radiation amplify white spruce climate sensitivity in interior Alaska: Evidence from carbon isotopes and tree rings.

The negative growth response of North American boreal forest trees to warm summers is well documented and the constraint of competition on tree growth widely reported, but the potential interaction between climate and competition in the boreal forest is not well studied. Because competition may amplify or mute tree climate-growth responses, understanding the role current forest structure plays in tree growth responses to climate is critical in assessing and managing future forest productivity in a warming climate. Using white spruce tree ring and carbon isotope data from a long-term vegetation monitoring program in Denali National Park and Preserve, we investigated the hypotheses that (a) competition and site moisture characteristics mediate white spruce radial growth response to climate and (b) moisture limitation is the mechanism for reduced growth. We further examined the impact of large reproductive events (mast years) on white spruce radial growth and stomatal regulation. We found that competition and site moisture characteristics mediated white spruce climate-growth response. The negative radial growth response to warm and dry early- to mid-summer and dry late summer conditions intensified in high competition stands and in areas receiving high potential solar radiation. Discrimination against 13 C was reduced in warm, dry summers and further diminished on south-facing hillslopes and in high competition stands, but was unaffected by climate in open floodplain stands, supporting the hypothesis that competition for moisture limits growth. Finally, during mast years, we found a shift in current year's carbon resources from radial growth to reproduction, reduced 13 C discrimination, and increased intrinsic water-use efficiency. Our findings highlight the importance of temporally variable and confounded factors, such as forest structure and climate, on the observed climate-growth response of white spruce. Thus, white spruce growth trends and productivity in a warming climate will likely depend on landscape position and current forest structure.

Weather-driven change in primary productivity explains variation in the amplitude of two herbivore population cycles in a boreal system.

Vertebrate populations throughout the circumpolar north often exhibit cyclic dynamics, and predation is generally considered to be a primary driver of these cycles in a variety of herbivore species. However, weather and climate play a role in entraining cycles over broad landscapes and may alter cyclic dynamics, although the mechanism by which these processes operate is uncertain. Experimental and observational work has suggested that weather influences primary productivity over multi-year time periods, suggesting a pathway through which weather and climate may influence cyclic herbivore dynamics. Using long-term monitoring data, we investigated the relationships among multi-year weather conditions, measures of primary productivity, and the abundance of two cyclic herbivore species: snowshoe hare and northern red-backed vole. We found that precipitation (rain and snow) and growing season temperatures were strongly associated with variation in primary productivity over multi-year time horizons. In turn, fourfold variation in the amplitude of both the hare and vole cycles observed in our study area corresponded to long-term changes in primary productivity. The congruence of our results for these two species suggests a general mechanism by which weather and climate might influence cyclic herbivore population dynamics. Our findings also suggested that the association between climate warming and the disappearance of cycles might be initiated by changes in primary productivity. This work provides an explanation for observed influences of weather and climate on primary productivity and population cycles and will help our collective understanding of how future climate warming may influence these ecological phenomena in the future.

Safety and effectiveness of long-term treatment with diazepam auto-injector administered by caregivers in an outpatient setting for the treatment of acute repetitive seizures.

OBJECTIVE: Part 1 of this phase III study was a randomized, double-blind, parallel-group, placebo-controlled, multicenter study of caregiver administered diazepam auto-injector (AI) in subjects with acute repetitive seizures (ARS) and demonstrated that diazepam AI was well-tolerated and significantly more effective than placebo AI in delaying the time to next seizure or rescue. Part 2 of this study, presented herein, was an open-label continuation to assess the long-term safety and effectiveness of diazepam AI for the treatment of ARS. METHODS: Of the 234 subjects randomized in part 1, 161 continued into part 2 and were provided open-label diazepam AI. Effectiveness measures were time to next seizure or rescue, number of subsequent rescues by type (rescue medication, emergency room visit, or other medical care), and number of subsequent seizures during the 12-h follow-up period. Safety data (adverse events and respirations <8/min) were also collected. RESULTS: During the open-label part 2 study, 129 subjects were administered a total of 1,380 diazepam AI treatments (median 4.5; range 1-118), of which 1,071 (77.6%) were effective with no subsequent seizure or rescue during the 12-h follow-up period. Median number of subsequent seizures experienced by subjects was one (range 0-20). Of the 1,380 administrations, 79 (5.7%) required use of rescue medication, 18 (1.3%) required a visit to an emergency room, and 6 (0.4%) required other rescue medical care. In most (75%) of subjects with treatment-emergent adverse events (TEAEs), TEAEs were mild or moderate in severity. Commonly reported treatment-related TEAEs were injection-site pain (10.9%), injection-site hemorrhage (7%), and injection-site bruising (6.3%). Although three subjects met the predefined respiratory rate threshold, none were considered clinically significant or reported as AEs. SIGNIFICANCE: Long-term treatment with diazepam AI administered by trained caregivers in an outpatient setting to treat ARS is a safe and effective option. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Climate sensitivity of reproduction in a mast-seeding boreal conifer across its distributional range from lowland to treeline forests.

Mast-seeding conifers such as Picea glauca exhibit synchronous production of large seed crops over wide areas, suggesting climate factors as possible triggers for episodic high seed production. Rapidly changing climatic conditions may thus alter the tempo and spatial pattern of masting of dominant species with potentially far-reaching ecological consequences. Understanding the future reproductive dynamics of ecosystems including boreal forests, which may be dominated by mast-seeding species, requires identifying the specific cues that drive variation in reproductive output across landscape gradients and among years. Here we used annual data collected at three sites spanning an elevation gradient in interior Alaska, USA between 1986 and 2011 to produce the first quantitative models for climate controls over both seedfall and seed viability in P. glauca, a dominant boreal conifer. We identified positive associations between seedfall and increased summer precipitation and decreased summer warmth in all years except for the year prior to seedfall. Seed viability showed a contrasting response, with positive correlations to summer warmth in all years analyzed except for one, and an especially positive response to warm and wet conditions in the seedfall year. Finally, we found substantial reductions in reproductive potential of P. glauca at high elevation due to significantly reduced seed viability there. Our results indicate that major variation in the reproductive potential of this species may occur in different landscape positions in response to warming, with decreasing reproductive success in areas prone to drought stress contrasted with increasing success in higher elevation areas currently limited by cool summer temperatures.

A double-blind, randomized, placebo-controlled trial of a diazepam auto-injector administered by caregivers to patients with epilepsy who require intermittent intervention for acute repetitive seizures.

PURPOSE: A diazepam auto­injector (AI) has been developed for intramuscular administration to treat acute repetitive seizures (ARS). The objective of this study was to evaluate the efficacy and safety of the diazepam AI when administered by caregivers to control an episode of ARS (ClinicalTrials.gov identifier NCT00319501). METHODS: In this phase III, randomized, double­blind, parallel­group, placebo­controlled, multicenter study, subjects with epilepsy on a stable antiepileptic drug regimen who required intermittent medical intervention to control ARS were randomized 1:1 to the placebo AI or the diazepam AI group. Subjects were stratified according to age (2­5, 6­11, ≥12 years). Dose (5, 10, 15, or 20 mg) was based on age and weight. A single dose of study medication was dispensed to be administered by caregivers in an outpatient setting when required. The primary end point was time to next seizure or rescue from 15 min to 12 h postdose. Secondary end points included rescue medication use, number of seizures postdose, caregiver and physician treatment assessments, and safety measures. KEY FINDINGS: Of 234 subjects randomized, 81/110 in the placebo AI group and 82/124 in the diazepam AI group were included in the intent­to­treat analysis. Baseline characteristics were similar for both groups. Time to next seizure or rescue was significantly longer in the diazepam AI group compared with the placebo AI group, with a hazard ratio of 0.55 (95% confidence interval [CI] 0.34­0.88; p = 0.012) for diazepam AI versus placebo AI, adjusted for age group. The 25th percentile for time to the next seizure or rescue was 1.18 h (95% CI 0.38­2.03) for placebo AI and 2.70 h (95% CI 0.48­11.42) for diazepam AI; the median was 5.9 h for placebo AI and was inestimable for diazepam AI due to the low number of events experienced by subjects in that group. The proportion of subjects using rescue medication postdose was 30% (24/81) placebo AI versus 17% (14/82) diazepam AI (p = 0.066). An event (seizure or rescue) occurred in 55.6% of subjects in the placebo AI group and 35.4% in the diazepam AI group. The number of seizures experienced during the 12­h postdose period was significantly lower for diazepam AI (median 0.0) compared with placebo AI (median 1.0; p = 0.010). Treatment­emergent adverse events (TEAEs) were reported in 44% (35/79) of subjects in the placebo AI group and 42% (34/81) in the diazepam AI group. The most common TEAEs reported were injection site pain (15% placebo AI, 17% diazepam AI) and injection site hemorrhage (6% placebo AI, 5% diazepam AI). SIGNIFICANCE: The diazepam AI was significantly more effective than placebo AI at delaying the next seizure or rescue. Secondary efficacy end points were generally supportive of the primary outcome. Diazepam AI administered by trained caregivers was effective for the treatment of ARS and was well tolerated, with a safety profile similar to placebo.

Diurnal temperature range as a key predictor of plants' elevation ranges globally.

A prominent hypothesis in ecology is that larger species ranges are found in more variable climates because species develop broader environmental tolerances, predicting a positive range size-temperature variability relationship. However, this overlooks the extreme temperatures that variable climates impose on species, with upper or lower thermal limits more likely to be exceeded. Accordingly, we propose the 'temperature range squeeze' hypothesis, predicting a negative range size-temperature variability relationship. We test these contrasting predictions by relating 88,000 elevation range sizes of vascular plants in 44 mountains to short- and long-term temperature variation. Consistent with our hypothesis, we find that species' range size is negatively correlated with diurnal temperature range. Accurate predictions of short-term temperature variation will become increasingly important for extinction risk assessment in the future.

A model to identify patients at risk for prescription opioid abuse, dependence, and misuse.

OBJECTIVE: The objective of this study was to use administrative claims data to identify and analyze patient characteristics and behavior associated with diagnosed opioid abuse. DESIGN: Patients, aged 12-64 years, with at least one prescription opioid claim during 2007-2009 (n = 821,916) were selected from a de-identified administrative claims database of privately insured members (n = 8,316,665). Patients were divided into two mutually exclusive groups: those diagnosed with opioid abuse during 1999-2009 (n = 6,380) and those without a diagnosis for opioid abuse (n = 815,536). A logistic regression model was developed to estimate the association between an opioid abuse diagnosis and patient characteristics, including patient demographics, prescription drug use and filling behavior, comorbidities, medical resource use, and family member characteristics. Sensitivity analyses were conducted on the model's predictive power. RESULTS: In addition to demographic factors associated with abuse (e.g., male gender), the following were identified as "key characteristics" (i.e., odds ratio [OR] > 2): prior opioid prescriptions (OR = 2.23 for 1-5 prior Rxs; OR = 6.85 for 6+ prior Rxs); at least one prior prescription of buprenorphine (OR = 51.75) or methadone (OR = 2.97); at least one diagnosis of non-opioid drug abuse (OR = 9.89), mental illness (OR = 2.45), or hepatitis (OR = 2.36); and having a family member diagnosed with opioid abuse (OR = 3.01). CONCLUSIONS: Using medical as well as drug claims data, it is feasible to develop models that could assist payers in identifying patients who exhibit characteristics associated with increased risk for opioid abuse. These models incorporate medical information beyond that available to prescription drug monitoring programs that are reliant on drug claims data and can be an important tool to identify potentially inappropriate opioid use.

Experience of switching from a daily to a less frequent administration of injection treatments.

BACKGROUND: Daily injections of recombinant human growth hormone are the standard of care to treat growth failure due to pediatric growth hormone deficiency (GHD). While effective, daily injections are burdensome and can compromise adherence. In recent years, novel injection treatments requiring less frequent administration for growth hormone deficiency (GHD) have been developed. A targeted, pragmatic literature review was conducted to summarize and document the patient experience of moving from daily to less frequent injections, with a specific focus on changing from daily to weekly injection treatments in pediatric GHD (pGHD). OBJECTIVE: Explore and describe the patient experience when switching from a daily to a less frequent injection schedule for GHD. METHODS: Targeted literature searches were conducted to identify literature describing the patient experience of moving from a daily to weekly injection in GHD. Supplementary searches were conducted to identify literature describing the patient experience of moving from daily to less frequent injection regimens in other medical conditions. RESULTS: Across searches, 1,691 abstracts were reviewed and 13 articles were included in the final analysis. These publications reported that patients moving to less frequent injections across a variety of conditions, including GHD, experienced increased convenience and satisfaction, higher adherence rates, fewer adverse events, and improved quality of life. Less frequent injections were also reported to be at least as efficacious as daily treatments. CONCLUSIONS: Less frequent injections in GHD and as other conditions are less burdensome, positively benefit patients, and result in improved adherence that may lead to improved clinical outcomes. Clinicians may consider weekly regimens as an effective alternative for patients, in particular in pGHD, especially when missed injections can negatively impact treatment outcomes. More research is needed to better understand the real-world benefits of injectable therapies that require less frequent administration (e.g., weekly versus daily).

Efficacy and Safety of Weekly Somatrogon vs Daily Somatropin in Children With Growth Hormone Deficiency: A Phase 3 Study.

CONTEXT: Somatrogon is a long-acting recombinant human growth hormone (rhGH) in development for once-weekly treatment of children with growth hormone deficiency (GHD). OBJECTIVE: We aimed to compare the efficacy and safety of once-weekly somatrogon with once-daily somatropin in prepubertal children with GHD. METHODS: In this 12-month, open-label, randomized, active-controlled, parallel-group, phase 3 study, participants were randomized 1:1 to receive once-weekly somatrogon (0.66 mg/kg/week) or once-daily somatropin (0.24 mg/kg/week) for 12 months. A total of 228 prepubertal children (boys aged 3-11 years, girls aged 3-10 years) with GHD, impaired height and height velocity (HV), and no prior rhGH treatment were randomized and 224 received ≥1 dose of study treatment (somatrogon: 109; somatropin: 115). The primary endpoint was annualized HV at month 12. RESULTS: HV at month 12 was 10.10 cm/year for somatrogon-treated subjects and 9.78 cm/year for somatropin-treated subjects, with a treatment difference (somatrogon-somatropin) of 0.33 (95% CI: -0.24, 0.89). The lower bound of the 2-sided 95% CI was higher than the prespecified noninferiority margin (-1.8 cm/year), demonstrating noninferiority of once-weekly somatrogon vs daily somatropin. HV at month 6 and change in height standard deviation score at months 6 and 12 were similar between both treatment groups. Both treatments were well tolerated, with a similar percentage of subjects experiencing mild to moderate treatment-emergent adverse events in both groups (somatrogon: 78.9%, somatropin: 79.1%). CONCLUSION: The efficacy of once-weekly somatrogon was noninferior to once-daily somatropin, with similar safety and tolerability profiles. (ClinicalTrials.gov no. NCT02968004).

The abuse potential of Remoxy(®), an extended-release formulation of oxycodone, compared with immediate- and extended-release oxycodone.

OBJECTIVES: Remoxy(®) is a water-insoluble, highly viscous oral formulation of oxycodone extended release (ER) currently in development. The primary objective was to determine the abuse potential of Remoxy under fed conditions relative to oxycodone ER and immediate release (IR) under fasted conditions and compared with placebo (treatment group X). A secondary objective was to evaluate abuse potential under reversed fed/fasted conditions (treatment group Y). DESIGN: Phase I randomized double-blind triple-dummy placebo- and active-controlled 6-way crossover study. Setting. A single US site. PATIENTS. Healthy men and women aged 18-50 years who were nondependent, recreational opioid users. Interventions. Remoxy 40 mg whole and chewed, oxycodone ER 40 mg whole and crushed, oxycodone IR 40 mg crushed, and placebo. OUTCOME MEASURES: The primary endpoint was the drug liking subscale of the drug effects questionnaire assessed by various pharmacodynamic parameters. Secondary endpoints included additional pharmacodynamic measures, chewing duration, and safety measures. RESULTS: In treatment group X, Remoxy whole (fed) and chewed (fed) had a significantly lower abuse potential compared with oxycodone ER (crushed, fasted) and IR (fasted) based on the majority of pharmacodynamic parameters of interest for the primary endpoint (drug liking subscale) as well as secondary endpoints. Treatment group Y showed generally similar results. CONCLUSIONS: The abuse potential of Remoxy when taken whole or chewed was significantly lower than two comparators with known abuse potential, including oxycodone IR and crushed oxycodone ER, under the fed/fasted conditions tested. Remoxy may be associated with a reduced risk potential for abuse.

Societal costs of prescription opioid abuse, dependence, and misuse in the United States.

OBJECTIVES: The objective of this study was to estimate the societal costs of prescription opioid abuse, dependence, and misuse in the United States. METHODS: Costs were grouped into three categories: health care, workplace, and criminal justice. Costs were estimated by 1) quantity method, which multiplies the number of opioid abuse patients by cost per opioid abuse patient; and 2) apportionment method, which begins with overall costs of drug abuse per component and apportions the share associated with prescription opioid abuse based on relative prevalence of prescription opioid to overall drug abuse. Excess health care costs per patient were based on claims data analysis of privately insured and Medicaid beneficiaries. Other data/information were derived from publicly available survey and other secondary sources. RESULTS: Total US societal costs of prescription opioid abuse were estimated at $55.7 billion in 2007 (USD in 2009). Workplace costs accounted for $25.6 billion (46%), health care costs accounted for $25.0 billion (45%), and criminal justice costs accounted for $5.1 billion (9%). Workplace costs were driven by lost earnings from premature death ($11.2 billion) and reduced compensation/lost employment ($7.9 billion). Health care costs consisted primarily of excess medical and prescription costs ($23.7 billion). Criminal justice costs were largely comprised of correctional facility ($2.3 billion) and police costs ($1.5 billion). CONCLUSIONS: The costs of prescription opioid abuse represent a substantial and growing economic burden for the society. The increasing prevalence of abuse suggests an even greater societal burden in the future.

Bridging implementation gaps to connect large ecological datasets and complex models.

Merging robust statistical methods with complex simulation models is a frontier for improving ecological inference and forecasting. However, bringing these tools together is not always straightforward. Matching data with model output, determining starting conditions, and addressing high dimensionality are some of the complexities that arise when attempting to incorporate ecological field data with mechanistic models directly using sophisticated statistical methods. To illustrate these complexities and pragmatic paths forward, we present an analysis using tree-ring basal area reconstructions in Denali National Park (DNPP) to constrain successional trajectories of two spruce species (Picea mariana and Picea glauca) simulated by a forest gap model, University of Virginia Forest Model Enhanced-UVAFME. Through this process, we provide preliminary ecological inference about the long-term competitive dynamics between slow-growing P. mariana and relatively faster-growing P. glauca. Incorporating tree-ring data into UVAFME allowed us to estimate a bias correction for stand age with improved parameter estimates. We found that higher parameter values for P. mariana minimum growth under stress and P. glauca maximum growth rate were key to improving simulations of coexistence, agreeing with recent research that faster-growing P. glauca may outcompete P. mariana under climate change scenarios. The implementation challenges we highlight are a crucial part of the conversation for how to bring models together with data to improve ecological inference and forecasting.

Impacts of pre-fire conifer density and wildfire severity on ecosystem structure and function at the forest-tundra ecotone.

Wildfire frequency and extent is increasing throughout the boreal forest-tundra ecotone as climate warms. Understanding the impacts of wildfire throughout this ecotone is required to make predictions of the rate and magnitude of changes in boreal-tundra landcover, its future flammability, and associated feedbacks to the global carbon (C) cycle and climate. We studied 48 sites spanning a gradient from tundra to low-density spruce stands that were burned in an extensive 2013 wildfire on the north slope of the Alaska Range in Denali National Park and Preserve, central Alaska. We assessed wildfire severity and C emissions, and determined the impacts of severity on understory vegetation composition, conifer tree recruitment, and active layer thickness (ALT). We also assessed conifer seed rain and used a seeding experiment to determine factors controlling post-fire tree regeneration. We found that an average of 2.18 ± 1.13 Kg C m-2 was emitted from this fire, almost 95% of which came from burning of the organic soil. On average, burn depth of the organic soil was 10.6 ± 4.5 cm and both burn depth and total C combusted increased with pre-fire conifer density. Sites with higher pre-fire conifer density were also located at warmer and drier landscape positions and associated with increased ALT post-fire, greater changes in pre- and post-fire understory vegetation communities, and higher post-fire boreal tree recruitment. Our seed rain observations and seeding experiment indicate that the recruitment potential of conifer trees is limited by seed availability in this forest-tundra ecotone. We conclude that the expected climate-induced forest infilling (i.e. increased density) at the forest-tundra ecotone could increase fire severity, but this infilling is unlikely to occur without increases in the availability of viable seed.

The Prevalence and Cost of Medicare Beneficiaries Diagnosed and At Risk for Opioid Abuse, Dependence, and Poisoning.

BACKGROUND: Reliance on prescription opioids to manage pain has been associated with increases in diversion, overdose, and addiction. Prevalence of misuse and abuse has been shown to be higher among government-insured populations than commercially insured populations. However, the prevalence and costs of misuse/abuse among the Medicare fee-for-service (FFS) population has not been studied. OBJECTIVES: To (a) determine the prevalence and costs of prescription opioid misuse/abuse and (b) evaluate the prevalence and costs associated with those identified as at risk for opioid misuse/abuse in Medicare FFS beneficiaries. METHODS: This retrospective case-control study used Medicare claims data for the calendar years of 2010 and 2011 and included Medicare beneficiaries aged at least 18 years. The index date was the date of first diagnosed misuse/abuse or at risk for abuse and had to occur between July 1, 2010, and June 30, 2011, and beneficiaries had to have at least 6 months continuous eligibility before and after the index date. Matching (1:1) was used for comparing opioid misusers/abusers with nonabuser controls, as well as comparing patients at risk for opioid abuse with controls not at risk for abuse. Controls were matched to cases by gender, age, disability, and geographic region. The index date of the control patient was set equal to the index date of the matched case. RESULTS: Prevalence of misuse/abuse in the Medicare FFS population was 13.1 per 1,000 persons, with the majority among patients receiving Medicare based on disability (76.2%). The prevalence of at risk for misuse/abuse was 117.4 per 1,000 persons. Approximately half of the Medicare FFS patients used an opioid. Overall total annual unadjusted mean costs of health care resources were significantly greater for abusers than for matched controls ($46,194 vs. $21,964; P < 0.0001), with a mean annual excess cost of $24,230. The overall total adjusted 6-month post-index mean costs of health care resources for abusers was significantly greater than that of matched controls ($33,942 vs. $10,754; P < 0.0001), with a mean excess cost of $23,188. CONCLUSIONS: The prevalence of diagnosed abuse among Medicare FFS population (13.1 per 1,000 persons) was higher than other payer groups studied using similar ICD-9-CM codes, and the majority of abuse was among those receiving Medicare based on disability (76.2%). The prevalence of at-risk abuse was 9 times higher than the prevalence of diagnosed abuse. As with other studies, health care resource utilization and costs were significantly greater for diagnosed abuse than matched controls. DISCLOSURES: This study was sponsored by Pfizer. Roland is a Pfizer employee and stockholder and was involved in all aspects of the study as part of a mid-career fellowship in pharmacoeconomics with the University of Utah. Ye and Stevens are employees of University of Utah, and Oderda was an employee of University of Utah, which received financial support from Pfizer in connection with the development of this manuscript. Oderda also reports consulting fees from Pfizer, Trevena, and Pacira, unrelated to this study. The results of this study were presented at the Academy of Managed Care Pharmacy Nexus 2015; October 26-29, 2015; Orlando, FL, and the AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016; April 19-22, 2016; San Francisco, CA.