|Table of Contents|

Change Characteristics of Multi-scenario Landscape Pattern and Spatio-temporal Evolution of Carbon Stock in Suiling County,Heilongjiang Province

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2024年2
Page:
68-78
Research Field:
Publishing date:

Info

Title:
Change Characteristics of Multi-scenario Landscape Pattern and Spatio-temporal Evolution of Carbon Stock in Suiling County,Heilongjiang Province
Author(s):
YU Xiaobo1ZHOU Yuxin1PU Yifan2LU Yi1
(1.School of Landscape Architecture,Northeast Forestry University,Harbin,Heilongjiang 150040;2.School of Integrated Circuit Science and Engineering,University of Electronic Science and Technology of China,Chengdu,Sichuan 611731)
Keywords:
county planningmulti-scenarioslandscape patternspatio-temporal evolution of carbon stock
PACS:
F 301.2
DOI:
10.11937/bfyy.20232296
Abstract:
Based on the land use data of Suiling county in 2000,2010 and 2020 changes in carbon stock in Suiling county from 1990 to 2018 were calculated using the InVEST model,and changes in landscape pattern and carbon stock of Suiling county under three scenarios were simulated using the FLUS model and the Fragstats model.Taken together,these all provide suggestions for the green and low-carbon development of Suiling county.The results showed that,1) Suiling county mainly benefited from the protection of forest resources during the period from 2000 to 2010,with increased landscape fragmentation,decreased spreading degree and increased carbon stock (1.076×105 t in total).While Suiling county showed intensified landscape fragmentation,increased landscape heterogeneity,and decreased carbon stock (0.609×105 t in total) during the period from 2010 to 2020.2) Landscape heterogeneity increased in all three scenarios,while ecological protection scenarios changed slightly compared with other two scenarios.Carbon stock in natural development scenarios and farmland protection scenarios showed a downward trend,with a value of 18.051×106 t and 18.059×106 t,respectively.Ecological protection scenarios showed increased carbon stock of 18.116×106 t,which was 6.08×104 t higher than that of natural development scenarios.In conclusion,by analyzing the characteristics of land landscape pattern changes in different scenarios in Suiling county,the changes of carbon storage were calculated.Among them,the ecological protection scenario was more conducive to urban development.We should follow the low-carbon urban development model,take the living environment as the guide,rationally organize the division of land resources,and promote the construction of ecological green urban areas.

References:

1]国家发展改革委.《大小兴安岭林区生态保护与经济转型规划(2021—2035年)》[EB/OL].(2021-5-24) [2022-05-13].https://www.ndrc.gov.cn/xxgk/zcfb/ghwb/202105/t20210524_1280602_ext.html.[2]2021年国务院政府工作报告.(2021-03-05)[2022-05-22].https://www.gov.cn/guowuyuan/2021zfgzbg.ht m/ivk_sa=1024320u.[3]工业和信息化部.《“十四五”工业绿色发展规划》(工信部规[2021].178号)[EB/OL].(2021-11-15)[2023-05-05].http://www.gov.cn/zhengc e/zhengceku/2021-12/03/content_5655701.htm.[4]黑龙江省人民政府.《黑龙江省“十四五”节能减排综合工作实施方案》([黑政发2022].11号)[EB/OL].(2022-04-01)[2023-05-05].https://www.hlj.gov.cn/hlj/c108376/202203/c00_31185987.shtml.[5]周爽,刘邵权,彭立.成都市景观格局与生态系统服务的关联效应[J].山地学报,2021,39(2):262-274.[6]赵敬.太岳山典型山地景观格局特征及碳储量空间分布研究[D].北京:北京林业大学,2016.[7]吕海亮.城市植被与土壤碳储量时空变化规律研究:以哈尔滨市为例[D].哈尔滨:中国科学院大学(中国科学院东北地理与农业生态研究所),2017.[8]陈丽萍.基于Landsat数据的森林碳储量与土壤侵蚀功能研究[D].北京:北京林业大学,2019.[9]CHU X,ZHAN J,LI Z,et al.Assessment on forest carbon sequestration in the Three-North Shelterbelt program region,China[J].Journal of Cleaner Production,2019,215:382-389.[10]尚二萍,张红旗.1980s—2010s年新疆伊犁河谷草地碳存储动态评估[J].资源科学,2016,38(7):1229-1238.[11]王永吉,崔玲,程岭,等.黑龙江省山区半山区分区系统[J].国土与自然资源研究,2000(2):24-26.[12]高周冰,王晓瑞,隋雪艳,等.基于FLUS和InVEST模型的南京市生境质量多情景预测[J].农业资源与环境学报,2022,39(5):1001-1013.[13]黄宝华,周利霞,张兴国.烟台市土地利用变化模拟及陆地碳储量变化预测分析[J].国土资源科技管理,2023,40(2):58-67.[14]LI H,SONG W.Pattern of spatial evolution of rural settlements in the Jizhou District of China during 1962—2030[J].Applied Geography,2020,122:102247.[15]王保盛,廖江福,祝薇,等.基于历史情景的FLUS模型邻域权重设置:以闽三角城市群2030年土地利用模拟为例[J].生态学报,2019,39(12):4284-4298.[16]韩晋榕.基于InVEST模型的城市扩张对碳储量的影响分析[D].长春:东北师范大学,2013.[17]奚小环,杨忠芳,崔玉军,等.东北平原土壤有机碳分布与变化趋势研究[J].地学前缘,2010,17(3):213-221.[18]郭树平.黑龙江省碳储量及碳汇潜力分析[J].森林工程,2011,27(3):9-11,16.[19]李慧颖.基于遥感和InVEST模型的辽宁省退耕还林工程生态效应评估[D].长春:吉林大学,2019.[20]陈光水,杨玉盛,刘乐中,等.森林地下碳分配(TBCA)研究进展[J].亚热带资源与环境学报,2007,2(1):34-42.

Memo

Memo:
-
Last Update: 2024-02-08