Evolvement of Spatio-Temporal Pattern and Driving Forces Analysis of Ancient Trees Based on the Geographically Weighted Regression Model in Guangzhou and Foshan, China

常绿 地理 空间分布 点模式分析 植被(病理学) 亚热带 共同空间格局 空间异质性 中国 分布(数学) 生态学 自然地理学 林业 生物 考古 遥感 数学 医学 数学分析 病理
作者
Zhenzhou Xu,Qing Xu,Kai‐Yan Liu,Yan Liu,Jiaheng Du,Kexin Yi,Xiaokang Zhou,Wei Lin,Hui Li
出处
期刊:Forests [Multidisciplinary Digital Publishing Institute]
卷期号:15 (8): 1353-1353
标识
DOI:10.3390/f15081353
摘要

Ancient trees play an important ecosystem service role in high-density cities, revealing the zonal distribution characteristics of vegetation under climate influence. The ancient trees in Guangzhou and Foshan in 2018 and 2023 were taken as study objects to explore the evolution of their spatio-temporal patterns and to analyze the spatial differentiation characteristics of their driving factors using the geographical weighted regression (GWR) model. The results showed the following: (1) The ancient trees in Guangzhou and Foshan were composed of typical subtropical evergreen broad-leaved forest communities, mainly represented by broad-leaved species of evergreen dicotyledonous plants. The dominant species mainly included Litchi chinensis, Ficus microcarpa, Canarium pimela, Ficus virens, and Dimocarpus longan. However, there was a significant difference between Guangzhou and Foshan. (2) The number of ancient trees in Guangzhou showed negative growth, while Foshan saw a significant increase. However, species diversity in both areas increased, with the highest diversity in the northeast, higher diversity in the south-central part, and lower diversity in the western and northwestern parts. (3) The maximum kernel density of ancient trees in Guangzhou and Foshan differed 22-fold, indicating a spatial distribution pattern of multiple clusters. (4) The GWR model effectively explained the driving factors of the heterogeneity of the spatial distribution of ancient trees. The results showed that artificial disturbance was the most important factor affecting the spatial distribution of ancient trees in high-density urban agglomerations in the same vegetation zone. The study clarified the characteristics of the spatial distribution and species diversity of ancient trees in the region, revealed the driving factors for the evolution of the spatial pattern of ancient trees in highly urbanized areas, and provided guidelines for policies and measures for enhancing biodiversity and conserving germplasm resources in the region.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
二马三乡完成签到 ,获得积分10
2秒前
3秒前
木野狐发布了新的文献求助10
6秒前
喂喂完成签到 ,获得积分10
8秒前
9秒前
干净问筠完成签到,获得积分10
10秒前
kang发布了新的文献求助10
11秒前
12秒前
12秒前
荷子完成签到,获得积分20
14秒前
14秒前
14秒前
14秒前
16秒前
17秒前
ReBorn发布了新的文献求助10
17秒前
裴仰纳完成签到 ,获得积分10
18秒前
傲娇蓝血发布了新的文献求助30
18秒前
18秒前
撒西不理给撒西不理的求助进行了留言
19秒前
路灯下的小伙完成签到,获得积分10
19秒前
zym999999发布了新的文献求助10
22秒前
Jrssion发布了新的文献求助10
22秒前
夏惋清完成签到 ,获得积分0
23秒前
量子星尘发布了新的文献求助10
24秒前
ClaudiaCY发布了新的文献求助150
24秒前
kang完成签到,获得积分20
26秒前
天才臭屁星完成签到 ,获得积分10
27秒前
Ava应助粱涵易采纳,获得10
27秒前
Jasper应助Literaturecome采纳,获得10
28秒前
sci发布了新的文献求助10
28秒前
卜大大发布了新的文献求助10
29秒前
冷万天关注了科研通微信公众号
29秒前
seal发布了新的文献求助10
30秒前
31秒前
33秒前
念之完成签到 ,获得积分10
35秒前
37秒前
Ljc发布了新的文献求助10
38秒前
拼搏的宇完成签到,获得积分10
39秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 588
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3958068
求助须知:如何正确求助?哪些是违规求助? 3504219
关于积分的说明 11117555
捐赠科研通 3235582
什么是DOI,文献DOI怎么找? 1788351
邀请新用户注册赠送积分活动 871204
科研通“疑难数据库(出版商)”最低求助积分说明 802511