Science Advances
Supplementary Materials
This PDF file includes:
- Supplementary Materials and Methods
- fig. S1. Fine-resolution (5 m) spatial predictions of temperature metrics at the
HJA based on BRT models.
- fig. S2. Partial dependence plots showing the relationship between selected microtopographic
variables and microclimate.
- fig. S3. Partial dependence plots showing the relationship between selected vegetation
structure variables and microclimate.
- fig. S4. Key interactions identified from BRT models testing the effects of elevation,
microtopography, and vegetation structure on microclimate.
- fig. S5. RI of variables measured at 25- and 250-m scales for each temperature metric
in both years.
- fig. S6. Comparison of observed microclimate data by year.
- fig. S7. Comparison of predicted microclimate metrics by year.
- fig. S8. Photo of the HOBO temperature sensor in the field.
- table S1. BRT model settings (learning rate, number of trees), performance diagnostics
(deviance, deviance SE, CV corr, CV SE), and tests for spatial autocorrelation in
the BRT model residuals (Moran’s I and P).
- table S2. Pearson’s correlation coefficients (r) and associated P values for both observed and predicted values between years.
- table S3. Results from a PCA of all vegetation structure predictor variables.
- table S4. Summary statistics and t tests showing differences in LiDAR metrics between mature plantations and mature/old-growth
forests.
- table S5. Results from Welch two-sample t tests comparing measures of biomass and canopy cover for plantation sites and mature/old-growth
forest sites.
- table S6. Temperature metrics used in our study and associated summary statistics.
- table S7. Predictor variables used to predict patterns in microclimate metrics.
- References (59–65)
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