Scenario modeling for spatial-temporal change detection of carbon storage and sequestration in a forested landscape in Northern Iran

Abstract

The present study was conducted, based on scenario modeling approach, in the Do-hezar and Se-hezar forested landscape in the Mazandaran Province in Northern Iran in order to detect spatial-temporal changes of carbon storage and sequestration in four different carbon pools, i.e., aboveground and belowground biomasses, dead organic matter, and organic soils. For this purpose, firstly, the changing trend of land use/land cover (LULC) was detected by analyzing and comparing remotely sensed data of the landscape during the period of 1984-2016. Then, the impacts of future LULC changes on carbon storage and sequestration were predicted and valued using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model under two future plausible scenarios of business as usual (BAU) and balanced development (BD). According to the results of BAU scenario, continuation of the current trend will lead to a significant reduction in the carbon sequestration and a huge amount of social cost due to the loss of carbon stored in the landscape and its release to the atmosphere. The BD scenario which refers to the principled and under control development of human settlements simultaneously with forest conservational and restoration activities, could potentially reverse the downtrend of carbon sequestration service and avoid future socioeconomic costs, hence add to the economic value of the forest landscape in terms of providing a better sink for carbon storage. The results of this research can facilitate the quantitative and accurate assessment of carbon storage and sequestration relying on more precise biophysical and economic data as well as provide insight for effective land-use planning.

Assessing the effects of the Green for Grain Program on ecosystem carbon storage service by linking the InVEST and FLUS models: A case study of Zichang county in hilly and gully region of Loess Plateau

“…根据许泉等 [38] 、解宪丽等 [39] 相关研究，分别获得了全国水平耕地、林地和草地的地 上碳密度；根据解宪丽等 [39] 研究确定了全国水平耕地、林地和草地的地下碳密度；根据 李克让 [40] 、马钦彦等 [41] 研究，确定了全国水平耕地、草地和林地的土壤碳密度；根据揣 小伟等 [42] 研究得到江苏省水域、城乡工矿建设用地的地上碳密度和土壤碳密度，地下碳密 度均默认为 0。然后，通过参考朱文博等 [43] 和全国气象数据网上提供的数据，获得全国、 江苏省和子长县多年均温分别为9 ℃、15.7 ℃、9.64 ℃，降水量分别为628 mm、1040.4 mm、 479 mm。最后采用陈光水等 [44] 、Giardina 等 [45] 、Alam 等 [46] 研究中的关于生物量碳密度和 [47] 在研究中指出，当前中 国的碳排放社会成本应该确定为 24 美元/t；2017-2037 年的碳汇经济价值市场贴现率根据 亚洲发展银行在对项目进行评估时采用 10%~12%的贴现率 [37] ，本文最终将贴现率确定为 10%；碳排放社会成本年际变化率通过参考前人的研究 [48] 将其设置为不变，即为 0。 (3) In the future, it is assumed that the GFGP will continue to be implemented in the county, and its ecosystem carbon storage services will be further improved. In addition, certain carbon sink economic value will be obtained.…”

The Spatiotemporal Evolution and Prediction of Carbon Storage in the Yellow River Basin Based on the Major Function-Oriented Zone Planning

“…The InVEST model is the most common method for model simulation, with the advantages of simple operation, easy parameter acquisition, and visual representation, and it can accurately reflect carbon storage variations at multiple scales [16,17]. Zarandian et al [18] assessed the impact of LUCC on carbon storage and sequestration using the InVEST model in the Mazandaran Province of Northern Iran. Lahiji et al [19] investigated how different land use policies contribute to changes in carbon storage in a mixed agriculture-forest landscape.…”

Exploring ecosystem carbon storage change and scenario simulation in the Qiantang River source region of China

“…The research showed that the social cost of carbon emissions in China was approximately 24 $/t with an interannual rate of change in the social cost of carbon emissions of 0. 55 , 56 Based on the Asian Development Bank's assessment of the discount rate for the carbon storage market, the economic value market discount rate was determined to be 11% in this study. 44…”