## 1 Introduction
Chlorophyll a + b strongly absorb in the red portion of the visible spectrum, resulting in saturation of the red band at low Chlorophyll a + b, and reducing its potential to track initial chlorophyll loss at the onset of stress. However, the red-edge has been shown to have a more linear response to a wide range of chlorophyll concentrations, increasing its potential as a stress indicator in vegetated systems over conventional red-NIR combinations [29; 30; 31; 26; 32]. Given the increasing availability of the red-edge waveband in commercial (e.g., RapidEye, WorldView-2, WorldView-3) sensors, and freely available data (Sentinel-2, launched June 2015), testing the potential of the red-edge waveband to improve modeled estimates of GPP in semi-arid ecosystems is becoming a feasible task. Here, we test the ability of spectral VI's other than NDVI to model GPP in semi-arid ecosystems. We focus particularly on pinon-juniper woodlands for several reasons. First, because it is the largest biome in the Southwestern US, covering 18 million ha in New Mexico, Arizona, Colorado and Utah. Second, the changes in climate in this region have triggered a significant amount of mortality in this biome [10; 33], and thus, quantifying the extent of this disturbance on productivity throughout the region is crucial to understanding how this extensive mortality has impacted both current and future carbon dynamics. Finally, we take advantage of an existing experimental manipulation in a Pinon-Juniper woodland in central New Mexico that was girdled in 2009 to simulate the widespread pinon mortality observed throughout the region. The advantage of using this experimental manipulation is that since the girdling in 2009, changes in ecosystem productivity triggered by this mortality have been continuously monitored using eddy covariance, and compared to similar measurements in a nearby intact PJ woodland that serves as a control. Recent research [34] conducted in our experimental manipulation suggested that the red-edge employing normalized difference red-edge index (NDRE) [35] was more sensitive than NDVI to the observed initial decrease in leaf chlorophyll concentration triggered by pinon girdling in this PJ woodland, adding evidence to its potential as a stress monitoring component in GPP modeling efforts. The NDRE was determined to be more sensitive to changes in greenup of the low LAI herbaceous vegetation following mortality in this same system [22]. Based on these findings, the goal of this study was to test three specific hypotheses. The first hypothesis being that the observed variability in NDRE will allow more accurate estimation of GPP in both the disturbed and undisturbed PJ woodland in this experimental manipulation. Secondly, due to the inherent dependence of productivity on water availability in this biome, adding the normalized difference wetness index (NDWI), a VI that is sensitive to changes in foliar water content, will significantly improve the model fit by constraining the model error during the dry season. Finally, given the low vegetation cover and highly heterogeneous nature of PJ woodlands, that VIs generated from higher spatial resolution (5 m) data will provide more accurate estimates of GPP relative to traditional, moderate resolution (30 m) remote sensing data.