Abstract
Invasive annual grasses are of concern in much of the western United States because they tolerate resource variability and have high reproductive capacity, with propagules that are readily dispersed in disturbed areas like those created and maintained for energy development. Early season invasive grasses “green up” earlier than most native plants, producing a distinct pulse of greenness in the early spring that can be exploited to identify their location using multi-date imagery. To determine if invasive annual grasses increased around energy developments after the construction phase, we calculated an invasives index using Landsat TM and ETM+ imagery for a 34-year time period (1985–2018) and assessed trends for 1755 wind turbines installed between 1988 and 2013 in the southern California desert. The index uses the maximum Normalized Difference Vegetation Index (NDVI) for early season greenness (January-June), and mean NDVI (July–October) for the later dry season. We estimated the relative cover of invasive annuals each year at turbine locations and control sites and tested for changes before and after each turbine was installed. The time series was also mapped across the region and temporal trends were assessed relative to seasonal precipitation. The results showed an increase in early season invasives at turbine sites after installation, but also an increase in many of the surrounding control areas. Maps of the invasive index show a region-wide increase starting around 1998, and much of the increase occurred in areas surrounding wind development sites. These results suggest that invasions around the energy developments occurred within the context of a larger regional invasion, and while the development did not necessarily initiate the invasion, annual grasses were more prevalent around the developments.
Highlights
One of the major ecological consequences of increasing global connectivity is the introduction, establishment, and spread of non-native species into new ecosystems [1]
We investigated early-season invasives (ESI) thresholds values in our study region through comparison with field observations available through CalWeedMapper and environmental assessment surveys performed by Southern California Edison [45]
Studies that leverage precipitation-driven phenology for invasives include Waller et al (2018) who developed a summer annuals index in the Colorado Plateau to map Salsola spp., which greens up in response to summer precipitation and Wallace et al(2016) who developed an index that coupled Normalized Difference Vegetation Index (NDVI) and precipitation data to map presence of invasive buffelgrass (Pennisetum ciliare) in the Sonoran Desert [67]. This application of remote sensing imagery for exotic species detection exploits the relative difference between spring green up and summer senescence annually across the Landsat archive, which provides yearly insights into the amount and distribution of annual grasses on the landscape, and their patterns before and after installation of wind turbines
Summary
One of the major ecological consequences of increasing global connectivity is the introduction, establishment, and spread of non-native species into new ecosystems [1]. The non-native annual grasses red brome (Bromus rubens) and cheatgrass (Bromus tectorum) are a major concern for range management and habitat conservation across the western U.S [32,33], and their spatial and temporal dynamics have been the focus of many recent remote sensing studies [34,35]. (2011) established DESI index thresholds of >0.1 (high probability) and >0.075 (low probability) based on known location of cheatgrass, and these default thresholds have been applied in other studies on the Colorado Plateau [38] where the initial algorithm was developed Because these thresholds are specific to Landsat data collected over the Colorado Plateau, Kokaly suggested user-defined thresholds might prove more effective in other regions [37]. Appendix A contains a time series of ESI collected at the sample locations, plotted with winter precipitation from the same locations
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