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Leveraging the Landsat Archive to Track Understory Evergreen Shrub Expansions in the Coweeta Basin, North Carolina

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Date

2022-06-28

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Publisher

Virginia Tech

Abstract

Invasive species introductions, namely the chestnut blight fungus (Cryphonectria parasitica) and hemlock woolly adelgid (Adelges tsugae), have permanently altered the overstory canopy of Appalachian forests by causing the dramatic die-offs of two ecologically significant tree species, American chestnut (Castanea dentata) and eastern hemlock (Tsuga canadensis). These canopy dominants once had significant roles in regulating understory communities. The loss of these trees, along with fire suppression, has driven two common evergreen shrubs, rosebay rhododendron (Rhododendron maximum) and mountain laurel (Kalmia latifolia), to expand and proliferate in areas where they were once restricted. These two common shrubs are recognized agents of change in Appalachian forests because of their abilities to modify soil seed banks, regulate light, and alter the local soil chemistry. This study documented evergreen shrub expansion across the Coweeta Creek basin over the past 36 years analyzing changes in winter greenness using harmonized multi-decadal archives of Landsat imagery. We found the greatest change in winter greenness in relatively dry areas: higher elevations (1275–1300 m), steeper slopes (33°–35°), southward aspects, and far from streams (600–800 m). Historical field data collected in three unmanaged watersheds at Coweeta showed a simultaneous decrease in T. canadensis and increase in R. maximum. We also documented the decline of a xerophytic canopy tree species, pitch pine (Pinus rigida), and an associate understory shrub, K. latifolia. Our analysis of the influence of terrain variables on evergreen shrub expansion allowed us to determine which of the two species was expanding in various locations with reasonable certainty. This study provides spatially explicit data on the expansion of two evergreen shrub species at the Coweeta Hydrologic Laboratory that could be used to pinpoint areas for future management interventions.

Description

Keywords

Remote sensing, Landsat, Biogeography, Rhododendron, Mountain laurel

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