In the future, sea level rise (SLR) may decrease available habitat for some vertebrate species in coastal Georgia. Urban development could exacerbate habitat loss through both land conversion and fragmentation. While previous studies have shown the potential impact of these distinct stressors on individual species habitat, little work has been done to identify which species or groups of species will be most vulnerable to habitat changes from multiple types of stressors. Our objective was to examine how different change scenarios may affect distinct groups of vertebrate species. We paired outputs from the Sea Level Affecting Marshes Model (SLAMM) and SLEUTH Urban Development Model up to the year 2100 with habitat niche models for vertebrate species in 11 coastal Georgia counties. We examined predicted habitat change for each individual species under scenarios of 1m, 1.5m and 2m SLR as well as decadal scenarios for predicted urban growth.
Results/Conclusions
Results suggest that species reliant on salt marsh, tidal freshwater marsh and ocean beach habitat are likely to be most exposed to changes in habitat from SLR. Species that utilize open pine wood and flat wood forests are likely to be most exposed to changes in habitat from urban development. Species highly ranked for habitat change due to SLR were generally not highly ranked for habitat change due to urban growth. Species ranked highly for habitat change due to SLR were consistent for scenarios at 1m, 1.5m and 2m. Avian species were generally ranked highest for overall habitat change in all scenarios for SLR and urban growth. Potential change in habitat was higher for species affected by urban growth than for species affected by SLR, but species impacted by SLR were generally ranked as higher concern for state and federal conservation status, likely due to a higher number of species relying on beach and salt marsh habitats which are already spatially restricted to coastal zones. Distinguishing between habitat loss from SLR and loss from urban development could help land managers better prioritize conservation resources for multiple species, and provide insight into which populations are most vulnerable.