## 3 Results and Discussion
### Implications for Regional Remote Sensing Based Estimations of GPP in PJ Woodlands  
The results of our case study suggest that remote sensing driven, simple linear models of GPP have the potential to accurately describe patterns in regional carbon uptake, using locally measured PAR and air temperature as covariates. In this study, we chose to use Landsat ETM+ data, given its ease of access via the WELD portal. The highly heterogeneous composition of PJ woodlands, and the small scale of our manipulation experiment (200 m \(\times\) 200 m), precluded the use of MODIS sized pixels (\(\geqslant\)250 m \(\times\) 250 m), and given the heterogeneous patterns of mortality and subsequent recovery typical of disturbed PJ woodlands (e.g., [9; 22; 27]), Landsat scale or finer resolution (\(\leqslant\)30 m) products are of the appropriate spatial scale to resolve the patchy, heterogeneous patterns of mortality  
Figure 5: 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 RapidEye acquisition angles \(<\)7 degrees off nadir. See Table 1 for a description of model names.  
typical in disturbed PJ woodlands. In spite of the sensor view angle complications described in Section 3.3, limiting image acquisition angle variability impacted model performance in some cases, suggesting that increased spatial resolution data may have a role in constraining GPP predictions in these heterogeneous woodlands in the future, yet we were unable to fully test the hypothesis due to inadequate sample sizes when considering the variation in sensor view angle.  
The inclusion of the red-edge leveraging NDRE from RapidEye only improved model performance during periods of significant stress, such as during the selective mortality of pinon pine that we imposed on the girdled site in Fall 2009, or during periods of severe drought such as in 2011 (see Section 3.2). Given the imminent transition in climate projected for the southwestern US, and the already evident impacts on pinon mortality regionally, GPP prediction efforts in PJ woodlands should benefit from the incorporation of NDRE during mortality. Given recent launch of Sentinel-2, which can leverage the red-edge and infrared wavebands required to compute NDRE and NDWI respectively, the potential to incorporate NDRE into near-future regional models of GPP as a consequence of pinon mortality may significantly constrain the current uncertainty in estimating PJ woodland ecosystem function. Further, while NDWI did not significantly contribute to model performance in this study, the measured productivity of semi-arid plant canopies is strongly a function of available water, which ultimately affects the coupling between canopy VI and GPP (e.g., (2011)), and consequently the predictive power of VI driven models of GPP in these regions. Previous work has shown NDWI to correlate reasonably well with foliar water content, and water potential in pinon pine, but not juniper (2011), suggesting further that the inclusion of these VI to empirical modeling attempts should be perhaps constrained to pinon dominated pixels, requiring higher resolution imagery. Remotely sensed regional estimates of surface soil water content from the soon to launch Soil Moisture Active Passive sensor (SMAP), may provide an alternative to constrain the inter-annual variability in the VI \(\sim\) GPP relationship in semi-arid PJ woodlands.