Vegetation analysis and mapping in evolving ice-wedge-polygon terrain Prudhoe Bay Region, Alaska

Abstract

The Arctic is warming at an accelerating pace, and within the past few decades, ice-rich regions of the Arctic have undergone systemic changes. The subsidence of ground over degraded ice wedges has created new drainage networks and ponds within previously perpetually inundated areas, fundamentally altering ice-wedge-polygon landscape dynamics. Understanding the nature and distribution of these changes is crucial to determining potential impacts on climate, wildlife, and human society. We focus on an accessible and data-rich region within Prudhoe Bay. Although the changes caused by this shift in moisture regime are multi-faceted, we use vegetation as an easily measured proxy for multiple factors. Within this thesis, we delineate and describe the post-regime-shift vegetation at the study site along with corresponding environmental data. Following vegetation description, we map this vegetation at a very fine spatial scale (<1-m) using an automated approach suitable for efficient spatial and temporal repetition. Our results show that vegetation is strongly influenced by soil moisture, and consequently microrelief, making it a suitable indicator of inundation or drainage following permafrost subsidence. Moreover, novel vegetation types have been identified in both newly inundated and newly drained areas. Mapping results show that distribution of vegetation types is strongly influenced by surficial geology, and consequently ice richness. Older surfaces with thicker ice wedges have a higher cover of dry and moist vegetation types on drained polygon centers in addition to transitional aquatic vegetation within thermokarst ponds. Younger surfaces with thinner or absent ice wedges remain inundated, and have a higher cover of wet vegetation in addition to shallow, sparsely-vegetated lakes and ponds. We recommend further vegetation sampling at the study site to support development of a pan-Arctic vegetation classification, and additionally to better understand vegetation dynamics in enriched areas within close proximity to oil field infrastructure. We also recommend temporal repetition of the mapping approach in order to identify continued landscape changes over time.