Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field, Measurements, and Experiments (COMPASS-FME)
Abstract
Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field, Measurements, and Experiments (COMPASS-FME) is a multi-institutional pilot project to understand coastal terrestrial-aquatic interfaces (TAI) and inform their representation in multiscale, hierarchical models. We focus on the causes, mechanisms, and consequences of the shift between aerobic and anaerobic conditions related to the interacting water-soil-microbe-vegetation system; these gaseous, aqueous, and particulate fluxes and transformations must be mechanistically resolved to enable coupling between land, wetland, and open-water systems in our target models. Several data syntheses and model analyses have informed site selection, experimental designs, and sampling priorities. We have an array of sites and manipulative experiments in the Chesapeake Bay and Lake Erie regions to learn how ecosystem controls on these complex processes emerge along differing gradients in topography, soil saturation, ionic strength, redox state, and nutrient availability. These measurements are translated into model couplings that link biogeochemistry, microbial processes, and hydrology with land models. Vegetation measurements and model simulations indicate greater water stress and reduced physiological function in dying trees at the transition zones. Geophysical data incorporated into hydrological model (ATS) simulations suggest that surface soil solute concentration is more sensitive to tidal level change closer to the shoreline. A storm surge experiment (TEMPEST) informs representation of salinity stress responses in vegetation and soil gas fluxes in TAIs. In addition to measurements and experiments at our core sites, community-based sampling (EXCHANGE consortium) captures the range of characteristics that need to be represented across these landscapes. Machine learning techniques were used with publicly available data layers to develop functional zonation maps of Lake Erie's coastal landscapes that provide a pathway to translate findings from 1- and 2-D to larger spatiotemporal scales. These early results show that our measurements and experiments are successfully capturing ecosystem processes and mechanisms that promise to inform and challenge a new generation of fully coupled models relevant to TAIs.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMGC46D..11B