Efficient thinning regimes for Eucalyptus fastigata: Multi-objective stand-level optimisation using the island model genetic algorithm

A stand-level optimisation problem formulated to determine a set of efficient thinning regimes satisfying two objectives, i.e. value production for sawlog harvesting and volume production for a pulpwood market, was demonstrated for a Eucalyptus fastigata trial in Kaingaroa Forest, New Zealand. Genetic algorithms were used to estimate the set of efficient thinning regimes (i.e. regimes that occur when it is not possible to increase the achievement of one objective without reducing another) known as a Pareto frontier. Each thinning regime specified a unique combination of initial planting density; frequency, timing and intensity of thinning; final crop number; and rotation length. Specifications for the “best” regime in the Pareto set (i.e. the one that satisfied a balanced trade-off between value and volume production) were similar to those recommended through professional judgment based on pooled long-term field observations from different eucalypt species grown throughout New Zealand. The advantage of Pareto optimality was the ability of not only identifying a unique thinning regime, but equally efficient regimes each providing a different combination of value and volume production. Research on this approach has the potential of being applied to other forest sites, providing there is sufficient re-measurement data to reflect stand growth dynamics.     

Exploring a new perspective of sustainable development drive through environmental Phillips curve in the case of the BRICST countries

Environmental Science and Pollution Research - Considering that the rigor of economic activities has widely been linked with the turbulent nature of the increasing global atmospheric and...     

Globalization and environmental problems in developing countries

Environmental Science and Pollution Research -     

Convergence of per capita carbon dioxide emissions among developing countries: evidence from stochastic and club convergence tests

Environmental Science and Pollution Research - This exploratory study extends the literature on the convergence of per capita carbon dioxide emissions in analyzing stochastic and club convergence...     

Predicting Respiratory Morbidity from Pulmonary Function Tests: A Reanalysis of Ozone Chamber Studies

Some consequences of acute exposure to ozone are best measured In studies of human respiratory responses in controlled exposure chambers. These studies typically examine relationships between exposures to alternative pollutant concentrations and Indicators of lung function as measured by spirometry, such as forced expiratory volume In one second, FEV₁ However, the association of respiratory morbidity with these changes In lung function is not well established. To gain a better understanding of the relationship between ozonerelated changes in pulmonary function and respiratory symptoms, data from several clinical studies have been reanalyzed. Logistic regression models were used to determine the quantitative relationship between changes in FEV₁ and the probability of a mild or moderate lower respiratory symptom. Models were developed that corrected for repeated sampling of individuals and both population-averaged and subject-specific effects were determined. The results indicate the existence of a strong and consistent quantitative relationship between changes in lung function and the probability of a respiratory symptom. Specifically, a 10 percent reduction in FEV₁ is associated with a 15 percentage point increase In the probability of a mild, moderate or severe lower respiratory symptom and a 6 percentage point increase in the probability of a moderate or severe lower respiratory symptom.