# Coupled Spatiotemporal Characterization of Monsoon Cloud Cover and Vegetation Phenology
## 4 Discussion
### Implications for Jabal Dhofar  
Results from the example study area illustrate the type of information to be expected from the spatiotemporal analysis approach. In Dhofar, the location of the temporal endmembers in geographic space is consistent with expectations given local expertise and field observations of spatial variability in the relative strength of the monsoon. The clustering of individual wadi subsystems into relatively compact, curvilinear manifolds within the temporal feature space is highly suggestive that consistent differences in climate and phenology exist among many wadis. The observation that wadis which are adjacent in geographic space are represented by manifolds which are adjacent in the temporal feature space suggests gradual spatial gradients in both monsoon strength and phenological intensity across the study area. These gradients are predominantly oriented east-to-west in both Jabal Al Qara and Jabal Al Qamar, although with opposite polarity. Within-wadi variability can largely be explained by topographic gradients in slope and elevation. This agreement between spatial patterns of endmember affinity and known features of the physical geography of Jabal Dhofar provides strong evidence that the spatiotemporal patterns that are identified from the feature space are biogeophysically meaningful. Despite the lack of any observed historical trends in the MODIS time series, our field observations confirm extensive overgrazing throughout the study area in the form of physical damage to native trees and shrubs, the nearly complete absence of ungrazed grasses, and the spatial extent of invasive plant species indicative of ecological succession. However, we see no evidence that this degradation is consistently captured in the MODIS record as degradation found by [44]. In our view, the absence of any appreciable trend in the either the anniversary time series or the full, near-daily 17-year calendarplots that are shown in Figure 8 provides stronger evidence than can be obtained from analysis of MODIS composite time series, particularly because of the potential for the introduction of artifacts by the compositing process [52]. Importantly, we do not interpret our results as contradicting claims of overgrazing itself. Rather, we observe that the effects of overgrazing are apparently masked by concurrent senescence of post-monsoon vegetation, interannual variability of phenology related to variability in the timing and extent of the monsoon, and the inability of multispectral sensors to discriminate between the plant species. The limitations of hectometer satellite imaging in terms of pixel footprint, terrain correction, BRDF compensation, and subpixel cloud cover are substantial, especially in areas like Dhofar with substantial relief and a relatively small geographic extent. While we cannot state with certainty, we suggest that the discrepancy between our results and those of [44] may be partially explained by some or all of the following factors: 1) aliasing of interannual phenological variability by the 16-day MODIS compositing process, 2) inaccuracies introduced by the presumption of sinusoidal basis functions, and 3) noise that is present in pixel-level time series, which is partially reduced by using the spatial mean of all pixels in the endmember regions. In addition, further analysis using 30 m Landsat imagery over a longer baseline (1985-2017) revealed relatively few isolated areas with detectable loss of forest cover [40]. It is further important to note that the presence or absence of historical trends does not necessarily have straightforward implications for the future behavior of a complex system. This is especially noteworthy in a case like Dhofar, where degradation is observed in the field, but is not captured by the limited spatial, spectral, and temporal resolution of the multispectral satellite archive. In addition, in many landscapes, the relationship between cloud cover and vegetation may not be stationary. Non-stationarities in climate-vegetation coupling can be abrupt or gradual.