Remote Sensing of Invasive Annual Grasses

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One of the major ecological consequences of increasing global connectivity is the introduction, establishment, and spread of non-native species into new ecosystems. The rate and extent of biological invasions continues to increase globally, often at considerable environmental and economic costs. Once established, non-native species can transform ecosystems, complicating land management decision-making and impeding ecological restoration. These issues are magnified in drylands where increasing climate variability may be expected. Given the inherent challenges of managing ecosystems and invasive species in a rapidly changing world, information on the geographic distributions of invasive plants, their rates of spread, and the factors contributing to successful invasion are critical for informed management and decision-making.

A growing demand for energy has led to a surge in development in the Western United States, and the clearing of native vegetation for access roads and pads presents new opportunities for invasive plants to take hold and spread. Exotic plant species present major management challenges in areas where energy developments create new openings for invasion and invasions can persist long after the sites have been abandoned. Once established, exotic annuals like red brome (Bromus rubens) and cheatgrass (Bromus tectorum) and can spread to adjacent areas, rapidly alter community composition and increasing wildfire risk. “Early season” invasives green up earlier than native vegetation, producing a distinct “pulse” of greenness in the early spring. This pulse can be exploited to identify the location of these annuals by using the difference between a spring satellite image with peak cheatgrass greenness and an early summer image where cheatgrass is senescent. Using these approaches, we developed Landsat time series to analyze trends and patterns of early season invasive grasses around disturbed wind turbine sites as well as mapping invasive trends across the entire Mojave Desert of southern California.


A diagram of sampling approach for remote measurement of invasives around wind turbines.

(Public domain.)





Figure 1.2.1. Sampling approach for remote measurements of invasives around wind turbines.







Graphic of invasives increases after wind turbine construction

(Public domain.)







Figure 1.2.2Invasives index values before and after turbine construction compared to surrounding control areas (top). Green indicates turbines with higher index values in the period after construction, and yellow indicates no change or lower invasive index values after construction. 5-year average Early Season Invasives index values for 1989–1993 (middle) and 2014–2018 (bottom) illustrating trends across the larger landscape. Green values indicate persistent yearly high NDVI values over each period (greater than 0.2).









A photo of desert grassland in southern New Mexico

 Figure 1.2.3. Desert grassland in southern New Mexico.

(Credit: Miguel Villarreal, USGS. Public domain.)

We use remote sensing to map and monitor introduced species in desert grasslands of southern Arizona and New Mexico, including Lehmann Lovegrass (Eragrostis lehmanniana) and Boer Lovegrass (E. curvula var. conferta = E. chloromelas), both native to South Africa. Fire is the primary natural disturbance in desert grasslands, and its removal from the landscape in the past contributed to widespread changes in vegetation structure, composition, and function.  Desert grasslands are also sensitive to drought and overgrazing, which can also influence species cover and composition. Landsat indices were developed to differentiate between these invasive grasses, native grasses and annual species, and used to examine cover changes after prescribed fires (Villarreal et al. 2016).

Illustration of potential state changes related to drought, fire and grazing

Figure 1.2.4 Illustration of potential state changes related to drought, fire and grazing. Native grassland sites (1) can transition (A) to non-native dominated (2) when the fire regime is altered and grazing occurs. Re-introduction of fire (B) can help restore native grasses and reduce woody plant cover (3), especially with optimal timing and amount of precipitation (C, 1). Alternatively, non-native (2) sites may transition (D) to annualized/bare states (4) during drought periods.

(Public domain.)


A photo of a field crew measuring density of grasses

(Credit: Miguel Villarreal, USGS. Public domain.)




Figure 1.2.5. Field crew measuring cover of Lehmann Lovegrass (Eragrostis lehmanniana) and Boer Lovegrass (E. curvula var. conferta = E. chloromelas) in a desert grassland of southern Arizona.








Future work: Multi-date spectral information can be used to identify and exploit different phenological phases of non-native and native species. Red brome and cheatgrass, for example, “green up” earlier than native vegetation, producing a distinct pulse of greenness in the early spring. This pulse can be exploited to identify the location of cheatgrass by using a difference between the spring image with peak cheatgrass greenness and an early summer image, where cheatgrass is senescent. We are using this approach to map invasive plant species associated with high fire risk in the Mojave and Sonoran Desert regions. Up-to-date maps showing areas invaded by non-native invasive weeds can help land mangers through early detection of new invasions and identifying areas with high fire risk. With the increasing risk to public lands posed by the spread of invasive annual grasses across the Southwest, new maps and technologies are needed that can better inform where and when weed control or fuels management is needed across DOI managed lands.


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