Abstract
Hyperspectral remote sensing can be a powerful tool for detecting invasive species and their impact across large spatial scales. However, remote sensing studies of invasives rarely occur across multiple seasons, although the properties of invasives often change seasonally. This may limit the detection of invasives using remote sensing through time. We evaluated the ability of hyperspectral measurements to quantify the coverage of a plant invader and its impact on senesced plant coverage and canopy equivalent water thickness (EWT) across seasons. A portable spectroradiometer was used to collect data in a field experiment where uninvaded plant communities were experimentally invaded by cogongrass, a non-native perennial grass, or maintained as an uninvaded reference. Vegetation canopy characteristics, including senesced plant material, the ratio of live to senesced plants, and canopy EWT varied across the seasons and showed different temporal patterns between the invaded and reference plots. Partial least square regression (PLSR) models based on a single season had a limited predictive ability for data from a different season. Models trained with data from multiple seasons successfully predicted invasive plant coverage and vegetation characteristics across multiple seasons and years. Our results suggest that if seasonal variation is accounted for, the hyperspectral measurement of invaders and their effects on uninvaded vegetation may be scaled up to quantify effects at landscape scales using airborne imaging spectrometers.
Highlights
Invasions of non-native plants into terrestrial ecosystems can alter vegetation structure, plant and animal biodiversity, fire regimes, and ecosystem processes, such as nutrient and water cycling [1,2,3,4]
The contribution of spectral regions to the Partial least square regression (PLSR) calibration models is revealed by the PLSR regression coefficients, which represent the magnitude and direction that each wavelength has on PLSR factors (Figure 4)
The regression coefficients of both the live-to-dead ratio and canopy equivalent water thickness (EWT) were largest around 1240 nm, which is an important wavelength in the normalized difference water index (NDWI), but in opposite directions
Summary
Invasions of non-native plants into terrestrial ecosystems can alter vegetation structure, plant and animal biodiversity, fire regimes, and ecosystem processes, such as nutrient and water cycling [1,2,3,4]. Hyperspectral remote sensing can be useful for invasive plant detection [12] because its high spectral resolution can discriminate among plant functional groups and plant species [13]. Hyperspectral measurements can simultaneously detect multiple plant chemical or structural traits that may be unique to the invasive plant [14] or occur as a result of invader impacts [10]. The invasive iceplant (Carpobrotus edulis) and jubata grass (Cortaderia jubata) in coastal California were identified via hyperspectral images based on their higher leaf water content than native vegetation [15]. Other studies have used spectral differences to identify senescent vegetation and quantify the canopy water content associated with invasive species [18,19]
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