RESUMO
Objective: Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and non-school time. Methods: We conducted a retrospective analysis of CGM metrics in children 7-12 years (n=217, diabetes duration 3.5±2.5 years, hemoglobin A1c 7.5±0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school. Results: Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school. Conclusion: Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines.
Assuntos
Diabetes Mellitus Tipo 1 , Humanos , Criança , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hemoglobinas Glicadas , Glicemia/análise , Automonitorização da Glicemia , Estudos RetrospectivosRESUMO
Tree size shapes forest carbon dynamics and determines how trees interact with their environment, including a changing climate. Here, we conduct the first global analysis of among-site differences in how aboveground biomass stocks and fluxes are distributed with tree size. We analyzed repeat tree censuses from 25 large-scale (4-52 ha) forest plots spanning a broad climatic range over five continents to characterize how aboveground biomass, woody productivity, and woody mortality vary with tree diameter. We examined how the median, dispersion, and skewness of these size-related distributions vary with mean annual temperature and precipitation. In warmer forests, aboveground biomass, woody productivity, and woody mortality were more broadly distributed with respect to tree size. In warmer and wetter forests, aboveground biomass and woody productivity were more right skewed, with a long tail towards large trees. Small trees (1-10 cm diameter) contributed more to productivity and mortality than to biomass, highlighting the importance of including these trees in analyses of forest dynamics. Our findings provide an improved characterization of climate-driven forest differences in the size structure of aboveground biomass and dynamics of that biomass, as well as refined benchmarks for capturing climate influences in vegetation demographic models.
Assuntos
Carbono , Clima Tropical , Biomassa , Temperatura , MadeiraRESUMO
The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.
Assuntos
Mudança Climática , Clima Tropical , Biomassa , Demografia , EcossistemaRESUMO
Historical forest conditions are often used to inform contemporary management goals because historical forests are considered to be resilient to ecological disturbances. The General Land Office (GLO) surveys of the late 19th and early 20th centuries provide regionally quasi-contiguous data sets of historical forests across much of the Western United States. Multiple methods exist for estimating tree density from point-based sampling such as the GLO surveys, including distance-based and area-based approaches. Area-based approaches have been applied in California mixed-conifer forests but their estimates have not been validated. To assess the accuracy and precision of plotless density estimators with potential for application to GLO data in this region, we imposed a GLO sampling scheme on six mapped forest stands of known densities (159-784 trees/ha) in the Sierra Nevada in California, USA, and Baja California Norte, Mexico. We compared three distance-based plotless density estimators (Cottam, Pollard, and Morisita) as well as two Voronoi area (VA) estimators, the Delincé and mean harmonic Voronoi density (MHVD), to the true densities. We simulated sampling schemes of increasing intensity to assess sampling error. The relative error (RE) of density estimates for the GLO sampling scheme ranged from 0.36 to 4.78. The least biased estimate of tree density in every stand was obtained with the Morisita estimator and the most biased was obtained with the MHVD estimator. The MHVD estimates of tree density were 1.2-3.8 times larger than the true densities and performed best in stands subject to fire exclusion for 100 yr. The Delincé approach obtained accurate estimates of density, implying that the Voronoi approach is theoretically sound but that its application in the MHVD was flawed. The misapplication was attributed to two causes: (1) the use of a crown scaling factor that does not correct for the number of trees sampled and (2) the persistent underestimate of the true VA due to a weak relationship between tree size and VA. The magnitude of differences between true densities and MHVD estimates suggest caution in using results based on the MHVD to inform management and restoration practices in the conifer forests of the American West.