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Analysis of vertical differentiation of vegetation in Taishan World Heritage site based on cloud model.
Wang, Zhe; Han, Fang; Li, Chuanrong; Shen, Weixing; Yang, Zhijun; Li, Kun; Yao, Qi.
Affiliation
  • Wang Z; School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo, 255000, People's Republic of China.
  • Han F; School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo, 255000, People's Republic of China. hanf@lreis.ac.cn.
  • Li C; Mountain Tai Forest Ecosystem Research Station of State Forestry Administration/Key Laboratory of State Forestry Administration for Silviculture of the Lower Yellow River, Tai'an, 271018, People's Republic of China.
  • Shen W; Research Center for Forest Carbon Neutrality Engineering of Shandong Higher Education Institutions/Key Laboratory of Ecological Protection and Security Control of the Lower Yellow River of Shandong Higher Education Institutions, Tai'an, 271018, People's Republic of China.
  • Yang Z; Mount Taishan Scenic Area Management Committee, Tai'an, 271000, People's Republic of China.
  • Li K; Shandong Provincial Institute of Land and Space Planning, Jinan, 250013, People's Republic of China.
  • Yao Q; Mountain Tai Forest Ecosystem Research Station of State Forestry Administration/Key Laboratory of State Forestry Administration for Silviculture of the Lower Yellow River, Tai'an, 271018, People's Republic of China.
Sci Rep ; 14(1): 10948, 2024 05 13.
Article in En | MEDLINE | ID: mdl-38740964
ABSTRACT
While the forests on Mount Taishan are predominantly man-made, there is a notable vertical variation in vegetation. This study employs the method of cloud model, quantifying uncertainty (fuzziness and randomness) of things. Utilizing digital elevation model (DEM) and vegetation distribution data, we constructed elevation cloud models for Mount Taishan's deciduous broad-leaved, temperate coniferous, and mixed coniferous-broadleaved forests. Using three numerical features of the cloud model-Expectation (EX), Entropy (EN), and Hyper-entropy (HE)-we quantitatively analyzed the macro regularity and local heterogeneity of Mount Taishan's forests vertical distribution from the perspective of uncertainty theory. The results indicate (1) The EX of the core zone elevation of deciduous broad-leaved forest is 716.65 m, temperate coniferous forest is 1053.51 m, and mixed coniferous-broadleaved forest is 1384.09 m. The variation range of the core zone distribution height is smaller in the mixed coniferous-broadleaved forest (EN 53.74 m) compared to deciduous broad-leaved forest (EN 99.63 m) and temperate coniferous forest (EN 121.70 m). (2) The fuzziness and randomness of the distribution height of the lower extension zones of deciduous broad-leaved forest and temperate coniferous forest (EN 75.15 m, 184.56 m; HE 24.09 m, 63.54 m) are greater than those of the upper extension zones (EN 44.75 m, 42.49 m; HE 14.48 m, 13.23 m). (3) The distribution fuzziness and randomness within temperate coniferous forests exceed those of deciduous broad-leaved forests. Within the core zones, the uncertainty regarding the vertical distribution of vegetation across different aspects remains consistent, which retains the characteristic of man-made forests. However, in transition areas, there is significant disparity, reflecting the adaptive relationship between vegetation and its environment to some extent. In the upper and lower extension zones of deciduous broad-leaved forests, the EX values for the vertical distribution height of mixed coniferous and broad-leaved forests differ significantly from those of deciduous broad-leaved forests (the difference is 22.82-39.15 m), yet closely resemble those of temperate coniferous forests (the difference is 4.79-7.94 m). This suggests a trend wherein deciduous broad-leaved tree species exhibit a proclivity to encroach upon coniferous forest habitats. The elevation cloud model of vertical vegetation zones provides a novel perspective and method for the detailed analysis of Mount Taishan's vegetation vertical differentiation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Forests Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Forests Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2024 Document type: Article