Re-imagining the Future of Forest Management -- An Age-Dependent Approach towards Harvesting

Abstract

Facing the drastic climate changes, current strategies for enhancing carbon dioxide stocks need to be thoroughly honed. To address the problem, we first built a carbon sequestration growth model driven by growth rate dependency (GRDM). We abstracted the carbon cycling system into the process of photosynthesis, the humidity fluctuation, and the original storage of carbon in the trees. In the photosynthesis model, we considered various factors, including transition rate of absorption and organic matter production. We also designed an Economic Return Evaluation Model (EREM) to estimate the optimal distribution of trees in the forest based on the utility function. Maximizing the utility brought by the amount of carbon storage, we derived the equation for profit optimization with the constraints of total economic expenses allowed. To assess its performance, we took an object-oriented approach, simulated an ideal forest by placing instances of trees and plotted a time-dependent forest composition graph. After proper normalization of climate and economic data, we also make predictions for 169 worldwide forest-covered countries. Our model further suggests high sensitivity and robustness with a similar trend of overall utility when environmental aridity or proportion of harvested woods are varied. Finally, we apply the model to Georgia temperate deciduous forest, and we evaluate the carbon storage ability to adjust the Red Spruce based on available biological literature research. We recognize that while the model is preliminary in its failure to identify a diverse array of variables, it has encapsulated key features of idealized forests.