Effects of the fundamental axes of variation in structural diversity on the forest canopy temperature in an urban area

Jia Jia; Lei Wang; Yunlong Yao; Zhiwei Ye; Yalin Zhai; Jiyuan Fang; Zhongwei Jing; Ruonan Li; Mingchen Yao

doi:10.1016/j.scitotenv.2023.166201

Effects of the fundamental axes of variation in structural diversity on the forest canopy temperature in an urban area

Sci Total Environ. 2023 Dec 10:903:166201. doi: 10.1016/j.scitotenv.2023.166201. Epub 2023 Aug 9.

Authors

Jia Jia¹, Lei Wang², Yunlong Yao³, Zhiwei Ye⁴, Yalin Zhai¹, Jiyuan Fang¹, Zhongwei Jing¹, Ruonan Li¹, Mingchen Yao¹

Affiliations

¹ College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China; Key Lab for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province, Harbin 150040, China.
² College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China; Key Lab for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province, Harbin 150040, China. Electronic address: wanglei@nefu.edu.cn.
³ College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China; Key Lab for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province, Harbin 150040, China. Electronic address: yaoyunlong@nefu.edu.cn.
⁴ Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA.

PMID: 37567290
DOI: 10.1016/j.scitotenv.2023.166201

Abstract

The spatial distribution and heterogeneity of forest canopy elements reveal the fundamental dimensions of plant structure variations. Forests characterized by greater structural complexity and diversity intercept solar radiation more effectively, directly influencing the thermal environment and energy balance of the canopy. However, the axes of variation in the distribution and heterogeneity of the canopy remain largely unknown, which limits our understanding of how structural diversity responds to canopy temperature variability. Here, we derived a set of structural diversity metrics from a dataset of canopy structure measurements obtained using unmanned aerial vehicle-light detection and ranging across major forest communities in an urban area in 2021 and 2022. We also explored the key axes of structural diversity variability and tested their predictive power for canopy temperature. The results showed that: (1) most of the variability within structural diversity (83.6 % and 81.8 %) was captured by the three key axes in 2021 and 2022. The first axis was primarily driven by structural heterogeneity, representing the heterogeneity of vegetation distribution within the canopy. The second axis was primarily influenced by the interaction between height and cover/openness, indicating the vertical structure and horizontal distribution pattern of the canopy. The third axis represented the horizontal coverage and density of the canopy. (2) In both 2021 and 2022, the second axis was identified as the most influential predictor of canopy temperature, as evidenced by R² values of 0.46 and 0.28, respectively. The model incorporating all three axes of structural diversity achieved the highest accuracy in predicting the canopy temperature for 2021 (R² = 0.68, AIC = 81.35, ΔAIC = 0, and RMSE = 0.89). Prior research on canopy temperature prediction has overlooked the true potential of principal component axes derived from structural diversity. The findings present a novel approach for selecting structural diversity indicators for future investigation.

Keywords: Canopy structure and temperature; Light detection and ranging (LiDAR); Principal component axes (PCs); Unmanned aerial vehicle (UAV); Urban forest; Vegetation index.