Soil media CO\u3csub\u3e2\u3c/sub\u3e and N\u3csub\u3e2\u3c/sub\u3eO fluxes dynamics from sand-based roadside bioretention systems

Green stormwater infrastructure such as bioretention is commonly implemented in urban areas for stormwater quality improvements. Although bioretention systems\u27 soil media and vegetation have the potential to increase carbon (C) and nitrogen (N) storage for climate change mitigation, this storage potential has not been rigorously studied, and any analysis of it must consider the question of whether bioretention emits greenhouse gases to the atmosphere. We monitored eight roadside bioretention cells for CO2-C and N2O-N fluxes during two growing seasons (May through October) in Vermont, USA. C and N stocks in the soil media layers, microbes, and aboveground vegetation were also quantified to determine the overall C and N balance. Our bioretention cells contained three different treatments: plant species mix (high diversity versus low diversity), soil media (presence or absence of P-sorbent filter layer), and hydrologic (enhanced rainfall and runoff in some cells). CO2-C and N2O-N fluxes from all cells averaged 194 mg m-2 h-1 (range: 37 to 374 mg m-2 h-1) and 10 μg m-2 h-1 (range: -1100 to 330 μg m-2 h-1), respectively. There were no treatment-induced changes on gas fluxes. CO2-C fluxes were highly significantly correlated with soil temperature (R2 = 0.68, p \u3c 0.0001), while N2O-N fluxes were weakly correlated with temperature (R2 = 0.017, p = 0.04). Bioretention soil media contained the largest pool of total C and N (17122 g and 1236 g, respectively) when compared with vegetation and microbial pools. Microbial biomass C made up 14% (1936 g) of the total soil C in the upper 30 cm media layer. The total C and N sequestered by bioretention plants were 13,020 g and 320 g, respectively. After accounting for C and N losses via gas fluxes, the bioretention appeared to be a net sink for those nutrients. We also compared our bioretention gas fluxes to those from a variety of natural (i.e., grasslands and forests) and artificial (i.e., fertilized and irrigated or engineered) land-use types. We found bioretention fluxes to be in the mid-range among these land-use types, mostly likely due to organic matter (OM) influences on decomposition being similar to processes in natural systems

Estimating Litter Decomposition Rate in Single-Pool Models Using Nonlinear Beta Regression

Litter decomposition rate (k) is typically estimated from proportional litter mass loss data using models that assume constant, normally distributed errors. However, such data often show non-normal errors with reduced variance near bounds (0 or 1), potentially leading to biased k estimates. We compared the performance of nonlinear regression using the beta distribution, which is well-suited to bounded data and this type of heteroscedasticity, to standard nonlinear regression (normal errors) on simulated and real litter decomposition data. Although the beta model often provided better fits to the simulated data (based on the corrected Akaike Information Criterion, AICc), standard nonlinear regression was robust to violation of homoscedasticity and gave equally or more accurate k estimates as nonlinear beta regression. Our simulation results also suggest that k estimates will be most accurate when study length captures mid to late stage decomposition (50-80% mass loss) and the number of measurements through time is ≥5. Regression method and data transformation choices had the smallest impact on k estimates during mid and late stage decomposition. Estimates of k were more variable among methods and generally less accurate during early and end stage decomposition. With real data, neither model was predominately best; in most cases the models were indistinguishable based on AICc, and gave similar k estimates. However, when decomposition rates were high, normal and beta model k estimates often diverged substantially. Therefore, we recommend a pragmatic approach where both models are compared and the best is selected for a given data set. Alternatively, both models may be used via model averaging to develop weighted parameter estimates. We provide code to perform nonlinear beta regression with freely available software. © 2012 Laliberté et al

Interactive Effects of Time, CO\u3csub\u3e2\u3c/sub\u3e, N, and Diversity on Total Belowground Carbon Allocation and Ecosystem Carbon Storage in a Grassland Community

Predicting if ecosystems will mitigate or exacerbate rising CO2 requires understanding how elevated CO2 will interact with coincident changes in diversity and nitrogen (N) availability to affect ecosystem carbon (C) storage. Yet achieving such understanding has been hampered by the difficulty of quantifying belowground C pools and fluxes. Thus, we used mass balance calculations to quantify the effects of diversity, CO2, and N on both the total amount of C allocated belowground by plants (total belowground C allocation, TBCA) and ecosystem C storage in a periodically burned, 8-year Minnesota grassland biodiversity, CO2, and N experiment (BioCON). Annual TBCA increased in response to elevated CO2, enriched N, and increasing diversity. TBCA was positively related to standing root biomass. After removing the influence of root biomass, the effect of elevated CO2 remained positive, suggesting additional drivers of TBCA apart from those that maintain high root biomass. Removing root biomass effects resulted in the effects of N and diversity becoming neutral or negative (depending on year), suggesting that the positive effects of diversity and N on TBCA were related to treatmentdriven differences in root biomass. Greater litter production in high diversity, elevated CO2, and enhanced N treatments increased annual ecosystem C loss in fire years and C gain in non-fire years, resulting in overall neutral C storage rates. Our results suggest that frequently burned grasslands are unlikely to exhibit enhanced C sequestration with increasing atmospheric CO2 levels or N deposition

Health systems integration: state of the evidence

Introduction: Integrated health systems are considered a solution to the challenge of maintaining the accessibility and integrity of healthcare in numerous jurisdictions worldwide. However, decision makers in a Canadian health region indicated they were challenged to find evidence-based information to assist with the planning and implementation of integrated healthcare systems. <br><br> Methods: A systematic literature review of peer-reviewed literature from health sciences and business databases, and targeted grey literature sources. <br><br> Results: Despite the large number of articles discussing integration, significant gaps in the research literature exist. There was a lack of high quality, empirical studies providing evidence on how health systems can improve service delivery and population health. No universal definition or concept of integration was found and multiple integration models from both the healthcare and business literature were proposed in the literature. The review also revealed a lack of standardized, validated tools that have been systematically used to evaluate integration outcomes. This makes measuring and comparing the impact of integration on system, provider and patient level challenging. <br><br> Discussion and conclusion: Healthcare is likely too complex for a one-size-fits-all integration solution. It is important for decision makers and planners to choose a set of complementary models, structures and processes to create an integrated health system that fits the needs of the population across the continuum of care. However, in order to have evidence available, decision makers and planners should include evaluation for accountability purposes and to ensure a better understanding of the effectiveness and impact of health systems integration

Simulation of the effects of photodecay on long-term litter decay using DayCent

Recent studies have found that solar ultraviolet (UV) radiation significantly shifts the mass loss and nitrogen dynamics of plant litter decomposition in semi-arid and arid ecosystems. In this study, we examined the role of photodegradation in litter decomposition by using the DayCent-UV biogeochemical model. DayCent-UV incorporated the following mechanisms related to UV radiation: (1) direct photolysis, (2) facilitation of microbial decomposition via production of labile materials, and (3) microbial inhibition effects. We also allowed maximum photodecay rate of the structural litter pool to vary with litter\u27s initial lignin fraction in the model. We calibrated DayCent-UV with observed ecosystem variables (e.g., volumetric soil water content, live biomass, actual evapotranspiration, and net ecosystem exchange), and validated the optimized model with Long-Term Intersite Decomposition Experiment (LIDET) observations of remaining carbon and nitrogen at three semi-arid sites in Western United States. DayCent-UV better simulated the observed linear carbon loss patterns and the persistent net nitrogen mineralization in the 10-year LIDET experiment at the three sites than the model without UV decomposition. In the DayCent-UV equilibrium model runs, UV decomposition increased aboveground and belowground plant production, surface net nitrogen mineralization, and surface litter nitrogen pool, but decreased surface litter carbon, soil net nitrogen mineralization, and mineral soil carbon and nitrogen. In addition, UV decomposition had minimal impacts on trace gas emissions and biotic decomposition rates. The model results suggest that the most important ecological impact of photodecay of surface litter in dry grasslands is to increase N mineralization from the surface litter (25%), and decay rates of the surface litter (15%) and decrease the organic soil carbon and nitrogen (5%)

Responsiveness of the Eating Disorders Quality of Life Scale (EDQLS) in a longitudinal multi-site sample

<p>Abstract</p> <p>Background</p> <p>In eating disorders (EDs), treatment outcome measurement has traditionally focused on symptom reduction rather than functioning or quality of life (QoL). The Eating Disorders Quality of Life Scale (EDQLS) was recently developed to allow for measurement of broader outcomes. We examined responsiveness of the EDQLS in a longitudinal multi-site study.</p> <p>Methods</p> <p>The EDQLS and comparator generic QoL scales were collected in person at baseline, and 3 and 6 months from 130 participants (mean age 25.6 years; range 14-60) in 12 treatment programs in four Canadian provinces. Total score differences across the time points and responsiveness were examined using both anchor- and distribution-based methods.</p> <p>Results</p> <p>98 (75%) and 85 (65%) responses were received at 3 and 6 months respectively. No statistically significant differences were found between the baseline sample and those lost to follow-up on any measured characteristic. Mean EDQLS total scores increased from 110 (SD = 24) to 124.5 (SD = 29) at 3 months and 129 (SD = 28) at 6 months, and the difference by time was tested using a general linear model (GLM) to account for repeated measurement (p < .001). Responsiveness was good overall (Cohen's d = .61 and .80), and confirmed using anchor methods across 5 levels of self-reported improvement in health status (p < .001). Effect sizes across time were moderate or large for for all age groups. Internal consistency (Chronbach's alpha=.96) held across measurement points and patterns of responsiveness held across subscales. EDQLS responsiveness exceeded that of the Quality of Life Inventory, the Short Form-12 (mental and physical subscales) and was similar to the 16-dimension quality of life scale.</p> <p>Conclusions</p> <p>The EDQLS is responsive to change in geographically diverse and clinically heterogeneous programs over a relatively short time period in adolescents and adults. It shows promise as an outcome measure for both research and clinical practice.</p

Land Use and Season Influence Event-Scale Nitrate and Soluble Reactive Phosphorus Exports and Export Stoichiometry from Headwater Catchments

Catchment nutrient export, especially during high flow events, can influence ecological processes in receiving waters by altering nitrogen (N) and phosphorus (P) concentrations and relative amounts (stoichiometry). Event-scale N and P export dynamics may be significantly altered by land use/land cover (LULC) and season. Consequently, to manage water resources, it is important to understand how LULC and season interact to influence event N and P export. In situ, high-frequency spectrophotometers allowed us to continuously and concurrently monitor nitrate (NO3−) and soluble reactive P (SRP) concentrations and therefore examine event-scale NO3− and SRP export dynamics. Here we analyzed event NO3− and SRP concentration-discharge hysteresis patterns and yields for \u3e400 events to evaluate how LULC and seasonality influence event NO3− and SRP export dynamics in three low-order watersheds with different primary LULCs (agricultural, forested, and urban). Differences among event NO3− and SRP hysteresis patterns suggest these nutrients have different source areas and dominant transport pathways that were impacted by both LULC and seasonality. Unexpectedly, we observed similar seasonal patterns in event NO3−:SRP stoichiometry among LULCs, with the most N-enriched events occurring in spring, and event stoichiometry approaching Redfield N:P ratios in the fall. However, seasonal stoichiometry patterns were driven by unique seasonal NO3− and SRP export patterns at each site. Overall these findings suggest LULC and seasonality interact to alter the timing and magnitude of event NO3− and SRP exports, leading to seasonal patterns in event NO3− to SRP stoichiometry that may influence ecological processes, such as productivity, in receiving waters