Using AHP and Time Series Model to Make a Better Forest Harvest Plan

Abstract

Nowadays, climate change is the biggest threat to the sustainable development of our society. How to deal with greenhouse gas emissions is an essential prerequisite to solve this problem. Forest carbon sequestration is an important method to offset the release of carbon dioxide. So the balance between the value of forest products and the value of allowing trees to continue growing is closely related to the amount of carbon storage. Therefore, we are expected to find an optimal management strategy that is suitable for all the forests with different factors such as economic benefits, locations and residents’ satisfaction, so as to improve forest carbon sequestration as much as possible. Three models are established: Model I: Maximum the Carbon Sequestration; Model II: Score System via Analytic Hierarchy Process (AHP) and Entropy-Weight Method; Model III: Time Series Analysis Model and Comparison. For Model I, we aim at maximizing the carbon sequestration of a forest and collect a series of biological parameters throughout the America. We start with describing the relationship between forest growing stock and carbon sequestration via the conversion ratio. Afterwards, we introduce the S-size Logistic curve to fit the growing stock volume and set different harvest and plant rate to observe the change of growing stock volume so that find an optimal harvest or plant rate to maximize the carbon sequestration amount. The transition point is found as 4% for harvest rate and also 4% for plant rate. We note that although the values of these two parameters are identical, it would arouse a significant difference because they are completely different process for a forest. For Model II, we take citizen attitude and timber value into consideration besides carbon sequestration. With the existing data in Model I and the data of new factors from literatures, we construct a score system of different strategies through analytic hierarchy process and entropy method. As a result, the optimal harvest rate decreases although timber value is included, because the local citizens interviewed in the literature showed a high-level anti-harvest attitude, which is consistent with the output of our model. For Model III, we establish a time series of carbon sequestration (or growing stock, they can be interconverted without difficulty). After recognizing the specific type (ARIMA type) of this time series by solving difference equation, the data in the subsequent years can be predicted. Then, we make the varication of the autocorrelation coefficient and partial autocorrelation coefficient (ACF and PACF) the ensure that the result is reliable and dose make sense. The models constructed in this paper make full use of the data obtained from website and literatures to describe and visualize the results. They are validated by sensitivity analysis and can be widely applied to evaluate the different situations. At the end, we provide a two-page newspaper for the authorities and local residents. According to the output in this paper, we finally draw a conclusion that an appropriate harvest rate is advantageous for both forest and society, and this phenomenon is called tending felling or reproduction felling, which is widely applied in managing forest.