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For models predicting fAPAR, we excluded MinT instead of elevation because Elevation showed a stronger correlation with fAPAR.
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To quantify whether predictors identified as important in above multiple-predictor models improved the conditional R2 of MWD based models (see Fig. 4 for details), we directly added MinT to the models predicting LAI and FCover from MWD and we added Ele_Min and Slope to the MWD based model predicting fAPAR.
The spatial autocorrelation term did not play a significant part in the models predicting LAI and fAPAR, but had a negative effect in the model predicting FCover (Table 2).
Models predicting PRs utilized binomial regression.
By Monday, we'll know which of the models predicting Irma's path is correct.
A second part is based on economic models, predicting future lost GDP through 2018.
Other models predict no effects.
Models predict trends in climate, not particular events.
The problem is that things may not be less dramatic than the models predict.
Models predict the trend will continue.
Previous models predicted too many gas giants.
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