Table 3.

Model summaries from hierarchical models estimating effects of tree canopy cover on maximum and minimum air temperature anomalies (°C) during summer 2022, using field-collected and remote-sensed assessments of canopy cover, with cloud cover data from nearby weather stations, and including an interaction term. Models also included intercept-only random effects of date and location (utility pole number).

Predictor	Field-based canopy cover (%)						Remote-sensed canopy cover (%)
	Estimate		95%CI		p		Estimates		95%CI		p
Maximum air temperature (°C)
Intercept	0.719		0.562 to 0.876		< 0.001		0.683		0.532 to 0.833		< 0.001
Canopy cover	− 0.006		− 0.009 to − 0.003		< 0.001		− 0.010		− 0.015 to − 0.005		< 0.001
Cloud cover	0.002		− 0.001 to 0.004		0.13		0.002		− 0.000 to 0.005		0.093
Canopy × cloud	< 0.001		− 0.000 to 0.000		0.333		< 0.001		− 0.000 to 0.000		0.818
Random effects
σ2	0.35						0.35
τ00 Date	0.16						0.16
τ00 Pole_No	0.06						0.06
ICC	0.39						0.38
NDate	92						92
NPole_No	50						50
Observations	3506						3506
Marginal R2/conditional R2	0.036/0.408						0.047/0.411
Minimum air temperature (°C)
Intercept	1.638		1.430 to 1.847		< 0.001		1.573		1.371 to 1.775		< 0.001
Canopy cover	− 0.009		− 0.013 to − 0.004		< 0.001		− 0.012		− 0.020 to − 0.004		0.002
Cloud cover	− 0.011		− 0.014 to − 0.007		< 0.001		− 0.01		− 0.013 to − 0.007		< 0.001
Canopy × cloud	< 0.001		0.000 to 0.000		< 0.001		< 0.001		0.000 to 0.000		< 0.001
Random effects
σ2	0.17						0.17
τ00 Date	0.27						0.27
τ00 Pole_No	0.14						0.15
ICC	0.7						0.7
NDate	9						92
NPole_No	50						50
Observations	3506						3506
Marginal R2/conditional R2	0.177/0.756						0.170/0.755

p-values < 0.05 are in bold.