DOI: 10.5061/dryad.2z34tmpz7
title: Integrating forest inventory and LiDAR observations to uncover the role of plant traits on cooling and humidifying effects in urban areas

description: 1. Outdoor heat stress possesses significant health risks, contributing to
 thousands of premature deaths each summer. Urban greening has been widely
 recognized as a potential solution to mitigate this heat threat. However,
 the optimal way to maximize cooling effects from urban forest—specifically
 through the influences of plant leaf traits and canopy structure on local
 climate (temperature and humidity)—remains underexplored. 2. To address
 this issue, we combined traditional forest inventory methods with advanced
 LiDAR observations to assess 3,883 individual trees and 77 plant species
 in the urban forests of Shanghai during the summer of 2021. For all trees,
 we analyzed six leaf traits: nitrogen content, phosphorus content,
 potassium content, leaf area, specific leaf area, and leaf dry matter
 content. Additionally, three canopy structural characteristics—mean
 foliage height, foliage height diversity, and canopy coverage—were
 investigated. Near-surface air temperature and relative humidity within
 and outside the forests were measured repeatedly using a state-of-the-art
 mobile monitoring system during four time intervals: 07:00 – 10:00, 11:00
 – 14:00, 16:00 – 19:00, and 21:00 – 24:00. 3. Our findings revealed that
 leaf stoichiometric traits significantly contribute to the variation in
 cooling effects, with their relative importance being twice as high as
 that of canopy structure during morning and afternoon periods.
 Specifically, nitrogen (N) and phosphorus (P) in leaves positively
 influenced cooling and humidification, whereas potassium (K) had a
 negative impact. 4. Synthesis and applications. To enhance the summer
 cooling potential of urban forests, we recommend incorporating tree
 species with high leaf N, leaf P, and low leaf K in urban park designs,
 rather than solely expanding canopy coverage. This study highlights the
 importance of considering plant traits in future urban green design,
 planning, and management for combating heat effectively.
description: # Integrating forest inventory and LiDAR observations to uncover the role
 of plant traits on cooling and humidifying effects in urban areas Dataset
 DOI: [10.5061/dryad.2z34tmpz7](10.5061/dryad.2z34tmpz7) ## Description of
 the data and file structure **Study Area & Design** This dataset was
 collected in **Shanghai, China** (subtropical monsoon climate) during
 summer 2021 to investigate the cooling and humidifying effects of urban
 forests. Six parks (44.5 ± 23.7 ha, &gt;80% vegetation cover) and adjacent
 reference areas (impervious surfaces) were selected. Air temperature (AT)
 and relative humidity (RH) were measured via mobile transects at four time
 periods (morning to nighttime), with 1,334 data points across 34 plots
 (30×30 m). **LiDAR & Field Measurements** * **3D Forest Structure**:
 Integrated aerial (UAV) and terrestrial (hand-held) LiDAR data
 (6,000–7,000 pts/m²) were used to reconstruct canopy architecture (e.g.,
 leaf area index, crown area) and segment 3,883 individual trees. * **Leaf
 Traits**: For 77 woody species, morphological (leaf area, SLA, LDMC) and
 stoichiometric traits (N, P, K content) were measured from 9,570 leaves.
 Community-weighted means (CWM) were calculated using LiDAR-derived leaf
 areas and biomass. **Key Variables** * **Microclimate Effects**: Cooling
 (ΔAT) and humidification (ΔAH) metrics, relative to reference areas. *
 **Canopy Structure**: Coverage, mean foliage height (MFH), and foliage
 height diversity (FHD). * **Leaf Traits**: Community-weighted means (CWM)
 values for LA (leaf areas), SLA (specific leaf area), LDMC (leaf dry
 matter content), N (leaf nitrogen content), P (leaf phosphorus content),
 and K ( leaf potassium content). **Statistical Analysis**\ Linear
 mixed-effects models (LMMs) assessed the influence of leaf traits and
 canopy structure on ΔAT/ΔAH, with park/ride as random effects. Variance
 decomposition quantified trait contributions. ### Files and variables ####
 File: Data\_Analysis\_Linear\_mixed-effects\_models.R
 **Description:** Codes of linear mixed-effects model (LMMs). LMMs were
 used to examine the effects of leaf traits on cooling and humidifying
 effects. #### File: Figure3\_BoxPlots.R **Description:** Codes for box
 plots in Figure 3. We used one-way repeated-measures ANOVA and
 Tukey's post hoc test to examine the significance of cooling and
 humidifying differences at four time periods. #### File:
 Figure4\_ForestPlots.R **Description:** Codes for forest plots in Figure
 3. The model outputs of Lmms. The forest plots will display parameter
 estimation of community-level leaf traits and canopy structural features
 for air temperature reduction and absolute humidity increase during the
 hours 07:00–10:00, 11:00–14:00, 16:00–19:00, and 21:00–24:00. #### File:
 Figure5\_RelativeContribution.R **Description:** Codes for relative
 contribution plots in Figure 3. The relative contribution of
 community-level leaf traits and canopy structural features for explaining
 reduction in air temperature and increase in absolute humidity by LMM
 models. #### File: Graphic\_Abstract.R **Description:** Codes for graphic
 abstract. It will combine the forest plots and relative contribution plots
 with good visulization. #### File: Imp\_LMM\_Trait\_Structure.top.AH5.csv
 **Description:** Data of LMMs outputs. The relative contribution of
 community-level leaf traits and canopy structural features for explaining
 increase in relative humidity during the hours 07:00–10:00, 11:00–14:00,
 16:00–19:00, and 21:00–24:00 by LMM models . ##### Variables * Importance:
 The relative contribution of community-level leaf traits and canopy
 structural features for explaining (a) reduction in air temperature and
 (b) increase in absolute humidity by LMM models. (%) * Trait:
 Community-level leaf traits and canopy structure. For leaf traits, the
 Leaf_N_eco, Leaf_P_eco, Leaf_K_eco, LA_eco, SLA_eco, and LDMC_eco
 represent the leaf nitrogen content, leaf phosphorus content, leaf
 potassium content, leaf areas, specific leaf area and leaf dry matter
 content at the community level. For canopy structural features, the Zmean,
 Evenness, and Cover indicate mean foliage height, foliage height
 diversity, and canopy coverage of the whole plot, respectively. * Time:
 Four time periods during a day. Morning, Noon, Afternoon, and Night are
 during hours 07:00 – 10:00, 11:00 – 14:00, 16:00 – 19:00 and 21:00 –
 24:00, respectively. #### File:
 35Plots\_LAIEco-traits\_Structure\_Cooling2.csv **Description:** Data used
 for LMMs modeling. It included cooling effects, humidifying effects,
 canopy structure, and leaf traits. ##### Variables * Point_ID: Points ID
 based on the mobile monitoring system * Plot_ID: Field plot ID * Park_ID:
 Park ID * Route_ID: Route ID based on the mobile monitoring system *
 Time_Period: Four time periods during a day. Morning, Noon, Afternoon, and
 Night are during hours 07:00 – 10:00, 11:00 – 14:00, 16:00 – 19:00 and
 21:00 – 24:00, respectively * Time: Exact time of the recording *
 Longitude: Longitude of the recording point * Latitude: Latitude of the
 recording point * Temp_Ano: Air temperature reduction (℃) *
 Hum_Ano: Relative humidity increase (%) * Leaf_K_eco: Leaf potassium
 content (%) * Leaf_N_eco: Leaf nitrogen content (%) * Leaf_P_eco: Leaf
 phosphorus content (%) * LDMC_eco: Leaf dry matter content (g/g) * LA_eco:
 Leaf areas (cm2) * SLA_eco: Specific leaf area (cm2/g) * Cover: Canopy
 coverage (%) * Zmean: Mean foliage height (m) * Evenness: Foliage height
 diversity #### File: Imp\_LMM\_Trait\_Structure.top.Tem6.csv
 **Description:** Data of LMMs outputs. The relative contribution of
 community-level leaf traits and canopy structural features for explaining
 reduction in air temperature during the hours 07:00–10:00, 11:00–14:00,
 16:00–19:00, and 21:00–24:00 by LMM models . ##### Variables * Importance:
 The relative contribution of community-level leaf traits and canopy
 structural features for explaining (a) reduction in air temperature and
 (b) increase in absolute humidity by LMM models. (%) * Trait:
 Community-level leaf traits and canopy structure. For leaf traits, the
 Leaf_N_eco, Leaf_P_eco, Leaf_K_eco, LA_eco, SLA_eco, and LDM_eco represent
 the leaf nitrogen content, leaf phosphorus content, leaf potassium
 content, leaf areas, specific leaf area and leaf dry matter content at the
 community level. For canopy structural features, the Zmean, Evenness, and
 Cover indicate mean foliage height, foliage height diversity, and canopy
 coverage of the whole plot, respectively. * Time: Four time periods during
 a day. Morning, Noon, Afternoon, and Night are during hours 07:00 – 10:00,
 11:00 – 14:00, 16:00 – 19:00 and 21:00 – 24:00, respectively. #### File:
 Relationship-ForestPlot6\_AT.csv **Description:** Data of LMMs outputs for
 air temperature reduction. It was used for forest plots. ##### Variables *
 Time: Four time periods during a day. Morning, Noon, Afternoon, and Night
 are during hours 07:00 – 10:00, 11:00 – 14:00, 16:00 – 19:00 and 21:00 –
 24:00, respectively. * Factors: Community-level leaf traits and canopy
 structure. For leaf traits, the Leaf N, Leaf P, Leaf K, LA, SLA, and LDMC
 represent the leaf nitrogen content, leaf phosphorus content, leaf
 potassium content, leaf areas, specific leaf area and leaf dry matter
 content at the community level. For canopy structural features, the Zmean,
 Evenness, and Cover indicate mean foliage height, foliage height
 diversity, and canopy coverage of the whole plot, respectively. *
 Estimate: Estimates from the model * SE: Sdandard errors of the estimate *
 xmin: min value of the estimate * xmax: max value of the estimate * t: t
 value from the model * p: p value from the model #### File:
 Relationship-ForestPlot6\_AH.csv **Description:** Data of LMMs outputs for
 air humidity reduction. It was used for forest plots. ##### Variables *
 Same as for Relationship-ForestPlot6_AT.csv ## Code/software  R version
 4.1.2 was used for all data analyses.