Yeqiong Shi, Xiulong Gao, Chunling Lang, Chuanwen Luo
{"title":"A method for determining the spatial pattern of forest trees based on the uniformity theory","authors":"Yeqiong Shi, Xiulong Gao, Chunling Lang, Chuanwen Luo","doi":"10.1007/s11676-024-01773-z","DOIUrl":null,"url":null,"abstract":"<p>The spatial pattern of trees is an important feature of forests, and different spatial patterns of trees exhibit different ecological stability. Research has confirmed that natural forests with random patterns have higher biodiversity and stronger resistance to unstable factors such as pests and diseases. Even if they are disturbed or destroyed by unstable factors such as pests and diseases, they can still recover and rescue themselves; while artificial forests with uniform and clustered patterns have lower biodiversity and are susceptible to unstable factors such as pests and diseases. And once pests and diseases occur, it’s more difficult for them to recover. In order to promote the healthy and stable development of the forestry industry and protect the diversity of the biological environment, it is necessary to protect the random pattern of natural forests from being destroyed in the process of forest management, while effectively transforming the spatial pattern of artificial forests into a random pattern. Therefore, in order to ensure the convenient and accurate determination of the type of forest spatial pattern, research on methods for determining forest spatial pattern has become particularly important. Based on the theory of uniformity, this study proposes definitions and related theories of included exclusive sphere, included exclusive body, included random pattern, and included uniformity. Under the guidance of the definition of inclusion uniformity and related theories, and by using mathematical method, it is proved that the uniformity of inclusion (<i>CL</i>) is asymptotically subject to the Eq. 18, Therefore, the relationship between the included uniformity (<i>CL</i>) and the number of trees in the sample plot was established, and the corresponding relationship formula was obtained, and then the determination of the spatial pattern type of trees was completed by using the corresponding relationship formula. Through rigorous reasoning and case verification, the determination method of forest spatial pattern is effective.</p>","PeriodicalId":15830,"journal":{"name":"Journal of Forestry Research","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forestry Research","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s11676-024-01773-z","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0
Abstract
The spatial pattern of trees is an important feature of forests, and different spatial patterns of trees exhibit different ecological stability. Research has confirmed that natural forests with random patterns have higher biodiversity and stronger resistance to unstable factors such as pests and diseases. Even if they are disturbed or destroyed by unstable factors such as pests and diseases, they can still recover and rescue themselves; while artificial forests with uniform and clustered patterns have lower biodiversity and are susceptible to unstable factors such as pests and diseases. And once pests and diseases occur, it’s more difficult for them to recover. In order to promote the healthy and stable development of the forestry industry and protect the diversity of the biological environment, it is necessary to protect the random pattern of natural forests from being destroyed in the process of forest management, while effectively transforming the spatial pattern of artificial forests into a random pattern. Therefore, in order to ensure the convenient and accurate determination of the type of forest spatial pattern, research on methods for determining forest spatial pattern has become particularly important. Based on the theory of uniformity, this study proposes definitions and related theories of included exclusive sphere, included exclusive body, included random pattern, and included uniformity. Under the guidance of the definition of inclusion uniformity and related theories, and by using mathematical method, it is proved that the uniformity of inclusion (CL) is asymptotically subject to the Eq. 18, Therefore, the relationship between the included uniformity (CL) and the number of trees in the sample plot was established, and the corresponding relationship formula was obtained, and then the determination of the spatial pattern type of trees was completed by using the corresponding relationship formula. Through rigorous reasoning and case verification, the determination method of forest spatial pattern is effective.
期刊介绍:
The Journal of Forestry Research (JFR), founded in 1990, is a peer-reviewed quarterly journal in English. JFR has rapidly emerged as an international journal published by Northeast Forestry University and Ecological Society of China in collaboration with Springer Verlag. The journal publishes scientific articles related to forestry for a broad range of international scientists, forest managers and practitioners.The scope of the journal covers the following five thematic categories and 20 subjects:
Basic Science of Forestry,
Forest biometrics,
Forest soils,
Forest hydrology,
Tree physiology,
Forest biomass, carbon, and bioenergy,
Forest biotechnology and molecular biology,
Forest Ecology,
Forest ecology,
Forest ecological services,
Restoration ecology,
Forest adaptation to climate change,
Wildlife ecology and management,
Silviculture and Forest Management,
Forest genetics and tree breeding,
Silviculture,
Forest RS, GIS, and modeling,
Forest management,
Forest Protection,
Forest entomology and pathology,
Forest fire,
Forest resources conservation,
Forest health monitoring and assessment,
Wood Science and Technology,
Wood Science and Technology.