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Abstract A beta-logistic generalized linear mixed model was used to study the association of national-level forest cover with selected covariates from a sample of 158 nations over the 1992–2013 period. The model avoided the improper assumption of normally distributed forest cover data and used covariates representing land, economic, and social factors. Agricultural land expansion was the most important factor associated with declines in forest cover. Relationships with other covariates are more nuanced. We found no support for an environmental Kuznets curve; however, a Kuznets-like trajectory with population and education variables was discerned. Population density had a negative marginal effect on forest cover up to 220 people/square kilometer (km2) but changed to positive after this threshold. A turning point for proportion of rural population was found at 22% when the association changed from positive to negative. The threshold for education level was 93% when its association switched from negative to positive. Economic variables inclusive of per capita income and 10-year lagged GDP growth rate had a weak but statistically significant association. In the future, high-income nations are expected to continue moderate growth in forest cover; a few fast-urbanizing developing countries are predicted to keep increasing forest area, but most will be likely to see a decline.

Aircraft noise can disrupt sleep and impair recuperation. The last U.S. investigation into the effects of aircraft noise on sleep dates back more than 20 years. Since then, traffic patterns and the noise levels produced by single aircraft have changed substantially. It is therefore important to acquire current data on sleep disturbance relative to varying degrees of aircraft noise exposure in the U.S. that can be used to check and potentially update the existing noise policy. This manuscript describes the design, procedures, and analytical approaches of the FAA’s National Sleep Study. Seventy-seven U.S. airports with relevant nighttime air traffic from 39 states are included in the sampling frame. Based on simulation-based power calculations, the field study aims to recruit 400 participants from four noise strata and record an electrocardiogram (ECG), body movement, and sound pressure levels in the bedroom for five consecutive nights. The primary outcome of the study is an exposure–response function between the instantaneous, maximum A-weighted sound pressure levels (dBA) of individual aircraft measured in the bedroom and awakening probability inferred from changes in heart rate and body movement. Self-reported sleep disturbance due to aircraft noise is the secondary outcome that will be associated with long-term average noise exposure metrics such as the Day–Night Average Sound Level (DNL) and the Nighttime Equivalent Sound Level (Lnight). The effect of aircraft noise on several other physiological and self-report outcomes will also be investigated. This study will provide key insights into the effects of aircraft noise on objectively and subjectively assessed sleep disturbance.

Increasingly, private landowners are participating in conservation easement programs, but their effects on land management remain to be addressed. Data from the USDA Forest Service National Woodland Owner Survey for the US Northern Region were used to investigate how conservation easement participation is associated with selected past and future forest management practices. Multiple data imputation was used to correct for missing data bias, and propensity score matching was applied to correct for selection bias. Results show that only the adoption of forest management plans, among 17 forest management practices, was significantly and positively correlated with easement participation. Conservation easements legally bind participants to maintain land forested, but there was no evidence of greater association between easement participation and active forest management practices, including timber harvesting. These findings suggest that adoption of conservation easements is a policy tool that can preserve forestland from changing to other uses but may not necessarily be conducive to wider implementation of land practices necessary for long-term protection of forests.

Woody biomass is a renewable energy feedstock with the potential to reduce current use of nonrenewable fossil fuels. We estimated the physical availability of woody biomass for cocombustion at coal-fired electricity plants in the 20-state US northern region. First, we estimated the total amount of woody biomass needed to replace total annual coal-based electricity consumption at the state level to provide a representation of the potential energy footprints associated with using woody biomass for electric energy. If all woody biomass available were used for electric generation it could replace no more than 19% of coal-based electric generation or 11% of total electric energy generation. Second, we examined annual woody biomass increment at the state level in a series of concentric circles around existing coal-fired electricity plants to examine some of the opportunities and limitations associated with using woody biomass for cofiring at those plants to coincide with state-level renewable portfolio standards. On average, an individual coal-fired power electricity plant could theoretically replace 10% of annual coal use if it obtained 30% of the net annual woody biomass increment within a 34-km radius of the plant. In reality, the irregular spatial distribution of coal-fired power plants means potential biomass supply zones overlap and would greatly diminish opportunities for cofiring with biomass, numerous other regulatory, economic, and social considerations notwithstanding. Given that woody biomass use for electricity will be limited to selected locations, use of woody biomass for energy should be complementary with other forest conservation goals.

The development of cointegration theories and the presence of nonstationarity in time series raised serious concerns about possible spurious estimations in forest products models. Based on the results of Hsiao (1997a, 1997b), all the virtues of two-stage least square (2SLS) hold if there are sufficient cointegration relations. Stationary null and nonstationary null unit root tests and monthly seasonal unit root tests were applied to the time series used in this dissertation. Cointegration tests with exogenous variables were performed to justify the 2SLS. A regional error correction model (ECM) with four regional lumber supply and demand equations and a U.S.-Canada supply and demand ECM were estimated. CUSUM tests did not find any structural changes. Both estimated models showed that the imported Canadian lumber and the U.S. lumber are substitutes. The estimated long-run and short-run own-price elasticities for demand and supply are inelastic for all the equations but the short-run supply equation for the West Coast. The long-run lumber supply equations have significant trends: annually -3% for the Inland West and 2% for the other regions. The popular maximum likelihood estimation for the restricted ECM cannot pass the test for the restrictions and is, therefore, not used for the regional structural lumber model. A series of univariate and multi-equation models were used as forecasting models. A combination of univariate model were shown to be the best forecasting models for lumber prices, and a combination of univariate and multi-equation models were shown to be the best forecasting models for lumber quantities. The selected combinations of models were shown to be the best with additional observations. It was also shown that lumber quantities could be forecasted better than lumber prices.

Forests represent a major global C sink, and forest management strategies that maximize carbon storage offer one avenue for mitigating increases in atmospheric carbon dioxide concentrations. Our understanding of relationships between forest management, productivity, carbon storage, and stand age, however, is limited. We established research plots in a chronosequence of thinned and unmanaged red pine stands in northern Minnesota to study patterns of carbon storage, and the major fluxes that influence carbon sequestration. We completed an inventory of all major C pools across a chronosequence of 57 red pine stands ages 9‐306 years on the Chippewa National Forest in the fall of 2009. Results indicate total ecosystem C pools increase as red pine stands age for at least 150 years, and on-site C storage in thinned stands appears similar to unmanaged stands of comparable ages, despite different age-related trends in the live tree and forest floor pools. Thinned stands may have the potential to store more C than unmanaged stands in old age when C removed during harvesting is added into the total ecosystem C pool.