Assessing hemlock woolly adelgid induced decline and susceptibility using hyperspectral technologies

The ultimate goal of this study was to provide the scientific framework for using narrow band hyperspectral instruments to assess early hemlock decline and susceptibility to the introduced hemlock woolly adelgid (HWA). To this end, spectral data from an ASD FieldSpec Pro was used to develop a 6-term linear regression equation, which predicted a detailed decline rating (0--10) with an R2 of 0.71 and RMSE of 0.591. To scale up this method to a remote sensing platform, NASA\u27s Airborne Visible Infrared Imaging Spectrometer (AVIRIS) was used to create a hemlock abundance map, correctly identifying hemlock dominated pixels (\u3e40% basal area) with 88% accuracy. Reflectance at a chlorophyll sensitive wavelength (683nm), coupled with a water band index (R970/900), was able to predict decline with 85% accuracy. The extreme accuracy at the low (0--4) end of the range indicated that these wavelengths might be used to assess early decline, before visual symptoms are apparent. Because instruments like AVIRIS have the capability to map foliar chemistry, the identification of links between HWA dynamics and foliar chemistry may be used to map relative susceptibility. To this end, we employed a three-tiered approach examining resistant vs. susceptible hemlock species, foliar chemistry vs. colonization success and regional foliar chemistry vs. HWA population levels. We found that HWA resistant hemlock species demonstrated higher concentrations of Ca and P, and lower concentrations of N and K. Regardless of host species, successful colonization of uninfested hemlocks was associated with higher N, and lower Ca and P concentrations. Regionally, higher concentrations of Ca, Mn, N and P were correlated with higher HWA densities. We hypothesize that higher N and K concentrations may have a palatability effect, driving HWA population levels, while higher concentrations of Ca and P may act as deterrents to more severe infestations. These results indicate that by using hyperspectral remote sensing instruments, it is possible to identify the very early stages of hemlock decline and map relative susceptibility to HWA on a landscape scale. Such tools are instrumental in targeting management activities and ultimately controlling the HWA outbreak