Integrating carbon and timber objective into forest spatial planning management

In this paper, based on the economic effect, a persuasive model for multi-objective forest management planning, which integrated the carbon stock and spatial configurations of management treatments into traditional timber harvest scheduling model, was developed for the Pangu Forest Farm in Great Xing'an Mountains, northeastern China. And the standard version of simulated annealing was employed. The planning cycle was divided into three 10-years periods. The planning formulations were to maximize the discount net present values (NPV) of timber production and carbon stock, while minimize the NPV of harvesting costs and penalty values. The constraints mainly concern the needs of minimum harvest ages, harvest times, even-flow of harvest volume and adjacency constraints, etc. In addition, the effects of a set of carbon prices were evaluated quantificationally on the results of planning. The simulated results showed that the NPVs of total and three sub-objectives (i.e., timber, carbon and spatial configurations of management treatments), as well as the amount of timber harvested and carbon sequestrated, all presented significant non-linear trends with the increases of carbon price. Compared with the carbon price of 0 CNY/t, the total NPVs increased approximately by 2.06% and 3.91% when the mean (25 CNY/t)and highest(50 CNY/t)carbon prices collected from the market of carbon trading were adopted into the planning model, however the differences of timber production and carbon stock were not significant. We further found that the lowest carbon price that could increase the levels of carbon stock per hectare within the whole planning period should be 1 000 CNY/t if it was evaluated purely from the economic perspective. In addition, the results also showed that the percentages of different management treatments assigned in the optimal plans could be affected significantly by the carbon price, anyway all the solutions meet the even-flow constraints of harvest volume.