2023 CSDMS meeting-108

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GenVeg: development of an individual-based plant population dynamics model for Landlab


Emily Russ, (she/her),US Army Engineer Research and Development Center Vicksburg Mississippi, United States. Emily.R.Russ@usace.army.mil
Candice Piercy, US Army Engineer Research and Development Center Vicksburg Mississippi, United States. Candice.D.Piercy@usace.army.mil
Carra Carrillo, US Army Engineer Research and Development Center Vicksburg Mississippi, United States. Carra.C.Carrillo@usace.army.mil
Todd Swannack, US Army Engineer Research and Development Center Vicksburg Mississippi, United States. Todd.M.Swannack@usace.army.mil



As a foundation of many ecological systems, vegetation is often a central component of ecological models used for forecasting and management. Many models are narrowly constrained by the system, species, and/or processes of interest and lack the ability to simulate specific management actions. This specificity limits their applicability to new, nonstationary, or actively-managed systems. The objective of this work is to create a Landlab component that combines an individual-based model design with grid-based model components to describe vegetation dynamics within and between grid cells. GenVeg is process-based, incorporating polymorphic plant-scale processes such as photosynthesis, dispersal, and seasonal allocation of biomass resources. Plant taxonomic principles are used to adapt the model methods based on the species (or representative species) of interest. Feedbacks between plants, plant communities, and the local physical environment utilize existing Landlab components and grid geometry to represent vegetation dynamics across the landscape. GenVeg is designed to be applied at a scale on the order of 10s to 1000s of meters over years to decades, which are scales relevant to ecosystem management and engineering planning. While the component is still under development, we will demonstrate its use within a dune environment utilizing coastal water levels and soil moisture to drive vegetation distribution across an idealized foredune system.