1. 福建农林大学 林学院,福建,福州,350002
2. 福建农林大学 资源与环境学院,福建,福州,350002
3. 福建农林大学 交通与土木工程学院,福建,福州,350002
纸质出版:2023
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吴玲鑫, 林以恒, 李键, 等. 基于“源—汇”原理的森林空间格局变化研究——以福建省为例[J]. 水土保持通报, 2023,43(4):238-247.
Wu Lingxin, Lin Yiheng, Li Jian, et al. Changes in Forest Spatial Patterns Based on Source-sink Principle—A Case Study in Fujian Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(4): 238-247.
吴玲鑫, 林以恒, 李键, 等. 基于“源—汇”原理的森林空间格局变化研究——以福建省为例[J]. 水土保持通报, 2023,43(4):238-247. DOI: 10.13961/j.cnki.stbctb.20230508.007.
Wu Lingxin, Lin Yiheng, Li Jian, et al. Changes in Forest Spatial Patterns Based on Source-sink Principle—A Case Study in Fujian Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(4): 238-247. DOI: 10.13961/j.cnki.stbctb.20230508.007.
[目的] 借助“源—汇”景观原理,明晰区域性的森林覆盖时空变化特征所蕴含的内在机制,为森林资源保护提供决策依据。[方法] 利用福建省2010和2020年的土地利用/覆盖变化(LUCC)、数字高程模型(DEM)和道路交通数据集,将对森林丧失起到促进或阻止/延缓作用的景观分别视为“源”景观和“汇”景观,综合高程、坡度和距离3个景观空间要素计算得到综合景观空间负荷对比指数(LCI'),从省、市2种尺度对福建省森林丧失空间格局变化进行系统分析。[结果] 省域尺度下,2010和2020年LCI'分别为0.117和0.152,“源”景观对森林丧失贡献较大,且景观空间要素的作用表现为:距离>坡度>高程;市域尺度下的LCI'计算结果存在差异,南平、三明、龙岩,LCI'相对较小(<0),福州、莆田、厦门、泉州、漳州地区的LCI'较大(>0);与2010年相比,2020年福建省各市LCI'均有小幅上升,其中福州市增长幅度最大(0.070),相对其他城市的森林丧失变化情况更为剧烈。[结论] 近10 a来,福建省各区域存在不同程度的森林丧失,LCI'能够将景观格局与过程相结合,在一定程度上有效地反映2010—2020年福建省森林空间格局变化情况。
[Objective] The mechanism underlying the spatial and temporal variation characteristics of regional forest cover was studied by using the source-sink landscape principle in order to provide a basis for decision-making regarding forest resource conservation. [Methods] We collected datasets of land use/cover change (LUCC)
digital elevation model (DEM)
and road traffic in Fujian Province for 2010 and 2020
and identified landscapes (i.e.
source landscapes and sink landscapes) that either promoted or prevented/delayed forest loss. The comprehensive location-weighted landscape contrast index (LCI') was calculated by integrating three landscape spatial elements (elevation
slope
and distance). The spatial pattern change of forest loss in Fujian Province was systematically determined at the provincial and city scales. [Results] At the provincial scale
LCI' was 0.117 and 0.152 in 2010 and 2020
respectively. The source landscape contributed more to forest loss
and the most influential of the spatial elements of the landscape was distance
followed by slope and elevation. There were differences in calculated LCI' at the city scale
with relatively small LCI' in Nanping
Sanming
and Longyan (<0) and large LCI' in Fuzhou
Putian
Xiamen
Quanzhou
and Zhangzhou (>0). The LCI' of all cities in Fujian Province in 2020 had increased slightly since 2010
with Fuzhou having the largest increase (0.070) and a more dramatic forest loss relative to other cities. [Conclusion] There have been different degrees of forest loss in various regions of Fujian Province during the last decade. The LCI' combined the landscape pattern with process
and effectively reflected changes in forest spatial patterns in Fujian Province from 2010 to 2020.
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