Individual tree and stand-level carbon and nutrient contents across one rotation of loblolly pine plantations on a reclaimed surface mine

While reclaimed loblolly pine (Pinus taeda L.) plantations in east Texas, USA have demonstrated similar aboveground productivity levels relative to unmined forests, there is interest in assessing carbon (C) and nutrients in aboveground components of reclaimed trees. Numerous studies have previously documented aboveground biomass, C, and nutrient contents in loblolly pine plantations; however, similar data have not been collected on mined lands. We investigated C, N, P, K, Ca, and Mg aboveground contents for first-rotation loblolly pine growing on reclaimed mined lands in the Gulf Coastal Plain over a 32-year chronosequence and correlated elemental rates to stand age, stem growth, and similar data for unmined lands. At the individual tree level, we evaluated elemental contents in aboveground biomass components using tree size, age, and site index as predictor variables. At the stand-level, we then scaled individual tree C and nutrients and fit a model to determine the sensitivity of aboveground elemental contents to stand age and site index. Our data suggest that aboveground C and nutrients in loblolly pine on mined lands exceed or follow similar trends to data for unmined pine plantations derived from the literature. Diameter and height were the best predictors of individual tree stem C and nutrient contents (R ≥ 0.9473 and 0.9280, respectively) followed by stand age (R ≥ 0.8660). Foliage produced weaker relationships across all predictor variables compared to stem, though still significant (P ≤ 0.05). The model for estimating stand-level C and nutrients using stand age provided a good fit, indicating that contents aggrade over time predictably. Results of this study show successful modelling of reclaimed loblolly pine aboveground C and nutrients, and suggest elemental cycling is comparable to unmined lands, thus providing applicability of our model to related systems

The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project

Background The voluntary carbon market is a new and growing market that is increasingly important to consider in managing forestland. Monitoring, reporting, and verifying carbon stocks and fluxes at a project level is the single largest direct cost of a forest carbon offset project. There are now many methods for estimating forest stocks with high accuracy that use both Airborne Laser Scanning (ALS) and high-resolution optical remote sensing data. However, many of these methods are not appropriate for use under existing carbon offset standards and most have not been field tested. Results This paper presents a pixel-based forest stratification method that uses both ALS and optical remote sensing data to optimally partition the variability across an ~10,000 ha forest ownership in Mendocino County, CA, USA. This new stratification approach improved the accuracy of the forest inventory, reduced the cost of field-based inventory, and provides a powerful tool for future management planning. This approach also details a method of determining the optimum pixel size to best partition a forest. Conclusions The use of ALS and optical remote sensing data can help reduce the cost of field inventory and can help to locate areas that need the most intensive inventory effort. This pixel-based stratification method may provide a cost-effective approach to reducing inventory costs over larger areas when the remote sensing data acquisition costs can be kept low on a per acre basis

Fluid Intelligence and Psychosocial Outcome: From Logical Problem Solving to Social Adaptation

While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized.Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher.Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts

Racism as a determinant of health: a systematic review and meta-analysis

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants.<br /