| 摘要: |
| ：园林绿化树种在城市景观中发挥着重要作用，是减
轻气候变化负面影响的有力工具。以中国重要林业树种木兰属
植物为例，基于物种分布和气候的大数据集构建了物种分布模
型。结果表明：1)我国木兰属植物在气候适宜性方面存在显
著的种间差异，且在水分-热量条件的权衡限制下占据着特定
的气候生态位；2)在54种木兰中筛选出潜在的耐旱型木兰14
种、耐热型木兰10种、耐寒型木兰6种；3)以华北地区3个代
表性城市沈阳、北京、西安为例进行了树种与城市之间的气候
适宜性匹配，证明水分条件是制约木兰属植物在我国暖温带及
中温带地区分布的关键因素，并筛选确定了一系列具有推广种
植潜力的木兰种。采用的数据分析方法为不同气候条件下的城
市绿化树种选择提供了理论指导，可用于我国木本植物区系
的快速筛选，在植物引种和迁地保护等方面具有长远的应用
前景。 |
| 关键词: 风景园林 城市绿化 树种选择 气候适宜性 大
数据分析 木兰属 |
| DOI：10.19775/j.cla.2024.07.0071 |
| 投稿时间：2023-03-17修订日期：2023-06-15 |
| 基金项目:西南大学创新研究2035先导计划 |
|
| Climate S u i t a b i l i t y Matching for UrbanLandscaping Tree Species Based on the Analysisof Big Data |
| XU Jie,GOU Minxin,CHEN Xinping,ZHOU Jianhua |
| Abstract: |
| Tree species plays an important role in urban landscape
construction and it is a powerful tool for mitigating the impacts
of climate change. Taking Magnolia genus as an example, species
distribution models were constructed based on the large datasets
on species distribution and climate. The results showed as follows:
1) 54 Magnolia species had significant interspecific differences in
climate suitability and occupied specific climate niches under the
tradeoff between moisture and heat conditions; 2) Fourteen, ten and
six species with potential drought, heat and cold tolerance were
predicted of 54 Magnolia species, respectively; 3) Taking three
representative cities in North China, Shenyang, Beijing and Xi'an,
as examples, climate suitability matching between tree species and
cities was carried out. It is proved that water condition was the key
factor limiting the distribution of Magnolia in warm and middle
temperate zones of China. Meanwhile, a series of Magnolia species
with the potential of spreading planting were identified. The data
analysis method used in this study provides theoretical guidance
for the selection of urban landscaping tree species under different
climate conditions, which can be applied to the rapid screening of
woody flora in China and has a long-term application prospect in
plant introduction and ex situ protection. |
| Key words: landscape architecture urban landscaping tree species
selection climatic suitability big data analytics Magnolia |
