DOONIES: A process-based ecogeomorphological functional community model for coastal dune vegetation and landscape dynamics

In ecogeomorphic systems, such as beach-dune habitats, complex couplings exist between geomorphology and ecology. Abiotic conditions influence vegetation growth and distribution while vegetation imposes a geomorphic feedback, impacting topography. Communities affect storm response by impacting pre-storm state, post-storm recovery, and landscape evolution. Despite their importance, beach-dune and other ecogeomorphic land-sea systems are deteriorating with increased anthropogenic modification and amplified natural disaster impact linked to climate change. A structured approach is needed to develop a more comprehensive understanding of coastal vegetation community interactions with the environment as these interactions underpin topographic change, strom response, and restoration and management efforts. Toward this goal, a spatially explicit process-based grid model, the DOONIES Model, encompassing biological, physiological, and geomorphological drivers of landscape change is presented. DOONIES simulates critical biotic and abiotic processes of vegetation growth, abundance, and spatial distribution dynamics impacting topography and storm response. Biological processes and ecogeomorphic responses are tailored to generalizable dune functional-communities with species-specific representatives. Estimates of the balance between photosynthesis and respiration dictate plant growth and morphology spatiotemporally which in turn impact sediment erosion and deposition. Relative sensitivity analyses indicate that the model is fundamentally driven by the photosynthesis formulation, where parameters such as maximum daily photosynthesis (grams of carbohydrate per day) and light intensity impact vegetation growth. These in turn, indirectly impact topographic change in modeled ecogeomorphic links. DOONIES is standalone and with a biological focus making it unique compared to more physical morphodynamic and hydrodynamic models with which this model is designed to couple. The model was evaluated by comparing simulation topography to actual across 6 years at Island Beach State Park, NJ while modeling Hurricane Sandy and daily wind conditions driving sediment input and output events. The predicted results were within the measurement error for the elevation datasets that the simulations were based on. This new model affords dynamic predictions of the response of naturally occurring and planted dune vegetation communities to typical abiotic conditions, as a tool for supporting and exploring restoration decisions.