Beaver-driven peatland ecotone dynamics: Impoundment detection using Lidar and geomorphon analysis

Background/Question/Methods Beaver (Castor spp.) are renowned for their role as ecosystem engineers. Their ponds and vegetation consumption can greatly alter local hydrology and ratios of meadow to woodland. Beaver also actively buffer their environments against drought and wildfire susceptibility, and can influence important climate parameters like carbon retention and methanogenesis. Beaver impoundments tend to follow a multiyear cycle of construction, maintenance, degradation, and fallow. Flooding is the primary agent of destruction. This investigation focused on remotely detecting beaver impacts on the boreal peatland ecotones enmeshing Cranberry Glades Botanical Area, a National Natural Landmark in mountainous West Virginia adjacent to Cranberry Wilderness, and contained entirely by Monongahela National Forest. The Glades are perched at ~1000 m elevation and occupy ~300 ha. Literature suggests that beaver activity may have had an important role in the formation and maintenance of peatland conditions at Cranberry Glades. Aerial Lidar/photography were analyzed in tandem in order to identify and reconstruct shifting hydrological patterns associated with beaver dams and ponds. We rasterized aerial Lidar data from Nov/Dec 2018 for the entire Glades at 1-meter resolution, including a bare-earth Digital Terrain Model (RMSE vertical accuracy ~10cm) and a canopy height model sufficient to discern between trees, shrubs, and near-surface. We developed a novel method of geomorphon analysis to detect ponds and dams by exploiting their occupancy of the incised stream channels typical of these wetlands. Aerial color-infrared and RGB photography, gathered during a variety of seasons, enabled complementary identification of beaver-related infrastructure by visual inspection. Results/Conclusions Geomorphon DTM analysis successfully revealed low ridges closely bracketing inter-glade stream channels featuring free-flowing water, manifesting as a ridge/valley/ridge cross-channel sequence. This signal is conspicuously absent along stretches flooded by beaver ponds; an abrupt transition between the two states also occurs at dams. A survey using these methods counted 13 ponds in Winter 2013-14 and 17 ponds in Summer 2016. This multi-year interval worked well, allowing time for widespread changes in beaver infrastructure while conserving utility of reference imagery. Future work will include analysis of the most recent beaver activity, refinement of classification workflows, generation of more accurate physical models using drone-acquired Lidar, and more complete incorporation of historical imagery. Much remains to be understood about the full role of beaver in this rare and imperiled ‘Arctic island’ of the southern High Alleghenies.