Ecosystem resistance and resilience describes the capacity for an ecosystem to withstand and recover from environmental disturbance. The fraction of vegetative cover, non-vegetative cover, and bare soil all directly impact ecosystem stability. This novel study quantifies the stability of vegetation cover of an urban ecosystem, focusing on Los Angeles (L.A.), California. The climate gradient from the coast to inland and frequent regional drought and temperature extremes make L.A. a unique location to study vegetative response to variations in climate. We hypothesize that stability of urban vegetation cover is increased by 1) less variability in local microclimate conditions and 2) increasing species richness. We used remotely sensed imagery for June to August, 2000 to 2016, to calculate stability of vegetation cover. NDVI anomaly, temperature anomaly, and a drought index were incorporated into a regression model, which normalizes for vegetation anomalies. An anomaly is defined as the detrended annual difference from the long-term average. NDVI anomaly was calculated from Landsat imagery by detrending the time series. We determined the drought anomaly by calculating the Standardized Precipitation Evapotranspiration Index (SPEI). The temperature anomaly was calculated from Landsat imagery.
Results/Conclusions
The mean of the NDVI anomaly was positive from 2013-2016 and negative all other years, with an average across all years of -0.022. As well, the standard deviation of the NDVI anomaly increased slightly from 2013-2016 over previous years. Spatially, the NDVI anomaly was strongly negative in the San Fernando Valley and in downtown L.A. from 2007-2013. During this same period the NDVI anomaly was positive in more natural areas. Surprisingly, it was during the height of the drought beginning in 2011 that NDVI anomaly values were most strongly positive. As well, the NDVI anomaly was slightly higher along the coast than further inland for the time series on average. How these NDVI data as well as the other covariates from the regression model have contributed to vegetative stability over time remains to be investigated. The results from this study will inform urban planners and citizens about how to increase the resilience and resistance of urban vegetation to climate stress and to maintain the delivery of ecosystem services even in suboptimal conditions. To increase understanding of localized drivers of urban ecological stability, future studies should consider higher spatial resolution imagery data and intra-city comparisons.