## 3 Results and Discussion
### Models of GPP in PJ Woodlands Had the Lowest Error at the Disturbed Site
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Site** & **Sensor** & **Model** & **R2 adj** & \(\Delta\)**AICc** & **ReLLL** & **Weights** \\ \hline \multirow{6}{*}{Control} & Landsat & NDVI\({}_{\text{LS}}\) & 0.902 & 0 & 1 & 0.997 \\  & Landsat & NDVI\({}_{\text{LSW}}\) & 0.75 & 12.159 & 0.002 & 0.002 \\  & RapidEye & NDVI\({}_{\text{IRE}}\) & 0.813 & 14.072 & 0.001 & 0.001 \\  & RapidEye & NDVI\({}_{\text{REW}}\) & 0.056 & 29.427 & 0 & 0 \\  & RapidEye & NDRE & 0.024 & 29.86 & 0 & 0 \\  & RapidEye & NDRE\({}_{\text{W}}\) & 0.135 & 33.983 & 0 & 0 \\ \hline \multirow{6}{*}{Girdle} & Landsat & NDVI\({}_{\text{LS}}\) & 0.391 & 18.428 & 0 & 0 \\  & Landsat & NDVI\({}_{\text{LSW}}\) & 0.439 & 17.684 & 0 & 0 \\ \cline{1-1}  & RapidEye & NDVI\({}_{\text{IRE}}\) & 0.238 & 41.847 & 0 & 0 \\ \cline{1-1}  & RapidEye & NDVI\({}_{\text{REW}}\) & 0.392 & 39.812 & 0 & 0 \\ \cline{1-1}  & RapidEye & NDRE & 0.921 & 0 & 1 & 1 \\ \cline{1-1}  & RapidEye & NDRE\({}_{\text{W}}\) & 0.361 & 18.851 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Model performance statistics for only year 2009 of the experiment. See Table 1 for a description of model names. R2 adj is the adjusted R2, AAICc is the difference in model AICc (Akaike information criterion) relative to the lowest scoring model, ReLL is the relative log likelihood, or how likely it is that each model is actually the best, and Weights is a list of the AICc weights for each model. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Site** & **Sensor** & **Model** & \(\mathbf{R^{2}_{adj}}\) & \(\Delta\)**AICc** & **ReLLL** & **Weights** \\ \hline \multirow{6}{*}{Control} & Landsat & NDVI\({}_{\mathrm{LS}}\) & 0.401 & 0.836 & 0.658 & 0.352 \\  & Landsat & NDVI\({}_{\mathrm{LSW}}\) & 0.394 & 3.518 & 0.172 & 0.092 \\  & RapidEye & NDVI\({}_{\mathrm{IRE}}\) & 0.373 & 0 & 1 & 0.534 \\  & RapidEye & NDVI\({}_{\mathrm{REW}}\) & 0.231 & 7.608 & 0.022 & 0.012 \\  & RapidEye & NDRE & \(-\)0.013 & 12.934 & 0.002 & 0.001 \\  & RapidEye & NDRE\({}_{\mathrm{W}}\) & 0.218 & 8.042 & 0.018 & 0.01 \\ \hline \multirow{6}{*}{Girdle} & Landsat & NDVI\({}_{\mathrm{LS}}\) & 0.167 & 10.991 & 0.004 & 0.004 \\  & Landsat & NDVI\({}_{\mathrm{LSW}}\) & 0.497 & 0 & 1 & 0.899 \\ \cline{1-1}  & RapidEye & NDVI\({}_{\mathrm{IRE}}\) & 0.14 & 13.979 & 0.001 & 0.001 \\ \cline{1-1}  & RapidEye & NDVI\({}_{\mathrm{REW}}\) & 0.302 & 8.552 & 0.014 & 0.012 \\ \cline{1-1}  & RapidEye & NDRE & 0.136 & 11.945 & 0.003 & 0.002 \\ \cline{1-1}  & RapidEye & NDRE\({}_{\mathrm{W}}\) & 0.45 & 4.803 & 0.091 & 0.081 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Model performance statistics for all years of data. See Table 1 for a description of model names. \(\mathrm{R^{2}_{adj}}\) is the adjusted \(\mathrm{R^{2}}\), \(\Delta\)AICc is the difference in model AICc relative to the lowest scoring model, ReLLL is the relative log likelihood, or how likely it is that each model is actually the best, and Weights is a list of the AICc weights for each model. Figure 2: One to one plots of tower derived (measured) and predicted (modeled) gross primary productivity for the control (C, black) and girdled (G, grey) sites for all years of the study. See Table 1 for a description of model names.