Predicting eelgrass recovery after implementing restoration actions.
The stressors and bottlenecks for growth of eelgrass seedlings, which were identified during
the REELGRASS project, have been implemented in a combined hydraulic and ecological 3Dmodel
(Rasmussen et al. 2009a). The model includes state variables for nutrients,
phytoplankton, macroalgae, above-ground eelgrass biomass, eelgrass seeds, sediment pools of
C, N, P and inorganic matter, as well as descriptions of wave and current stress, benthic light,
seedling anchoring, stress from macroalgae and seed burial by benthic fauna on survival of
eelgrass seedlings. This well-established ecological model will be improved for use in the
present project with results from WP 2 and WP 3, including effects of increased temperature
and CO2 on eelgrass growth and the effects of hypoxia and sulfide on eelgrass mortality.
The model is extended with a description of below-ground eelgrass biomass. The mass balance
facility of the model system (Rasmussen et al. 2009a,b) provides information on eelgrass
retention of carbon, nitrogen, phosphorus and fine particles based on results from WP 2.
Consequently, this model approach can identify thresholds where the system feedback
mechanisms start responding positively to eelgrass recovery. A series of multi-year simulations
will be done on selected estuaries (lagoons) with different eelgrass die-back history,
restoration schemes and climate scenarios to identify the potential for eelgrass recovery.
The ecosystem services created by recovering eelgrass meadows provide input for cost-benefit
analyses in both monetary and environmental terms (WP 6). Furthermore, new generic
procedures will be applied to generate maps of present and simulated future eelgrass coverage
depending on the applied restoration actions and climate conditions. The generated maps will
be available as thematic layers in GIS and used for subsequent ecological and socioeconomical
analysis. Existing models based on past years data will be available as back-up in
case the forcing and driving data for the NOVAGRASS project period are severely delayed.