| In order to successfully achieve the goal of achieving carbon peak in 2030 and carbon neutralization in 2060,and to further understand the carbon sequestration and carbon revenue and expenditure balance of terrestrial ecosystems in mountainous counties,it is particularly important to study how forest land changes affect forest ecosystem carbon storage and explore how mountain counties manage carbon storage and carbon sequestration.In order to better understand the process of forest land change and the driving factors of this change,we choose the Dinamica-EGO model as an important tool for research.Using the land use/cover data of 2010,2015 and 2020,combined with the driving factor data,we simulate and predict the land use/land cover situation of Yuanling County in 2025 and 2030,and explore the main driving forces affecting forest land change in Yuanling County.This paper further coupled with InV EST model,qualitatively and quantitatively studied the distribution and spatio-temporal change of carbon reserves under land use change in 2025,2015 and 2020,and predicted and estimated the forest carbon reserves in 2010,2015 and 2030.The main conclusions are as follows:(1)This study adopts multi-window spatial fuzzy similarity test and Kappa coefficient test to test the accuracy of the simulation results of 2010-2015,2015-2020 and 2010-2020.Multi-window fuzzy similarity test shows that the simulation results of the three periods meet the requirements,and the Kappa coefficient reaches 87.49.Therefore,the calculation of carbon reserves in the following will be based on the results of the 2010-2015 trend simulation.(2)The main driving factor of the transformation from cultivated land to woodland is the distance to the national highway,the main influencing factor of the transformation from woodland to water is the distance to rural road,and the main influencing factor is the distance to the center of town during the transformation of woodland to urban and rural industrial and mining residents,and the main driving factor of the transformation from grassland to woodland is the distance to the main river.(3)The carbon reserves of Yuanling County in 2010,2015 and 2020 are 6237.79 × 104t,6231.14 × 104t and 6235.56 × 104t,respectively,and the forest carbon reserves are 5534.05 × 104t,5532.15 × 104t and 5537.84 × 104t,respectively.It is predicted that the carbon reserves of Yuanling County in 2025 and 2030 are 6216.71× 104t and 6210.13 × 104t respectively.The forest carbon storage is 55 28 × 104t and 5526.05 × 104t respectively.(4)Analysis of carbon stocks in Yuanling County from the time scale shows that the total carbon stocks in Yuanling County remain basically unchanged from 2010 to 2030.At the same time,it is found that the carbon sequestration capacity of forests in Yuanling County is positively correlated with the change in the area of forested land.The lower carbon stocks are mainly distributed in the central part of Yuanling County and the interwoven strip-like area in the middle of Yuanling County and the small scattered nodes near the strip-like area;(2)the analysis of the distribution of carbon stocks in townships shows that the maximum average carbon stock of each township in Yuanling County in 2010 is 114.23 t and the minimum average carbon stock is 87.91 t.The areas with higher carbon stocks in Yuanling County form an "n" shape,surrounding the northern part of Yuanling County.The northern part of Yuanling County is surrounded.The areas with lower carbon stock levels are mainly located in Yuanling Township and Pangu Township,showing the shape of a number "7".In 2015,the number of towns and villages with high carbon stock levels increased by three towns and villages compared with 2010,and the number of towns and villages with medium to high carbon stock levels decreased by two towns and villages compared with 2010.2020 carbon stock levels in Yuanling County returned to the distribution characteristics of 2010,and it was found that the conflicts between forest land and arable land and forest land and urban and rural industrial and mining residential land had a continuous impact on carbon stock.It is expected that the number of townships or forestry farms with high carbon stocks will expand by four in 2025 and 2030.The distribution of carbon storage level in forestry sub-districts in Yuanling County shows that the maximum average carbon storage level in each sub-district in Yuanling County is 125.27t and the minimum average carbon storage level is 64.53t.The sub-districts with high carbon storage level in Yuanling County in 2010 are,in order from north to south,the northern soil and water conservation forest functional area,Qimeijie Forest Park,the northeastern Chinese herbal medicine development functional area,the eastern tea industry development functional area,and the eastern tea industry development functional area.The majority of sub-districts with medium to high carbon stock levels were mainly located in the northwest and south-central part of the county;the sub-districts with high carbon stock levels in Yuanling County in 2015 decreased by one district compared with 2010.2020 saw a slight change in the average level of carbon stock of the sub-districts compared with 2015.It was found that the average carbon stock in the eastern tea development functional area changed round-trip within these 20 years,indicating the persistence of the contradiction between tea industry development and forest land protection in this area. |
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