Current Research

What will PIE marshes look like in the future?

The system as we know it today is facing a number of challenges stemming from the external drivers of sea level rise, human activities, and climate change.

For PIE, those challenges are:

  • Accelerated rates of sea level rise, currently 4mm y-1 compared to the 100 year average of 2.8 mm y-1
  • Sediment starvation,
    from the damming of rivers and streams in the watershed by humans as
    well as by beavers, whose populations are now protected and flourishing
  • Species immigration and emigration, with sea surface temperatures in the Gulf of Maine having risen at 3 times the global average over the last 30 years

We anticipate large changes in the geomorphology of the marsh and estuary over the next century and beyond, with the current predominantly high-elevation marsh, dominated by Spartina patens, changing to a lower elevation, more frequently flooded marsh dominated by Spartina alterniflora (depicted right).

Our current research will examine the effects of the external drivers on the mechanisms of geomorphic change, and the impacts they will have on ecosystem structure and function. We will examine the connections and feedbacks between the external drivers and internal responses, as well as interactions among the internal processes. We have organized our thinking by focusing on specific components within the overall conceptual model, highlighted below, as well as the processes and interactions most relevant to them.

 

Marsh-Estuary Geomorphology

We expect changes in the configuration of the marsh-estuary to include

  • increase in the ratio of low marsh to high marsh
  • increase in tidal creek length and marsh edge
  • changes in the number and sizes of ponds
  • decrease in the area of the marsh compared to the estuary

Resulting from

  • decreased sediment delivery from the watershed
  • changes in primary production and decomposition
  • changes in species and food web dynamics, including potential increases in creekbank bioturbation

Biogeochemistry and Primary Production

We anticipate a changing biogeochemical regime in the marsh, with the direction of change uncertain and variable due to complex interactions and feedbacks.

We expect to see changes in

  • salinity regime experienced by the marsh
  • primary production of marsh grasses
  • porewater chemistry and nutrient dynamics
  • carbon storage and export

Driven by

  • increases in water and nutrient fluxes from the watershed
  • increased porewater drainage from marsh edges and the creation of biogeochemical "hot spots"
  • increase in grazing as access to the marsh platform increases with rising sea level

Consumer Dynamics and Food Webs

Warming temperatures and rising sea level are expected to lead to changes in PIE food webs.

We anticipate changes in

  • species distribution across the system
  • abundances of some species
  • range expansions by southern species
  • alternate food web structures
  • increased energy flow to marine pathways

Resulting from

  • changing salinity regimes with sea-level rise and as freshwater flow from the watershed changes
  • restructuring of habitats and resourse access as the shape of the marsh changes
  • changes in organic matter production
  • species immigration and emigration

Models
PIE researchers use a number of complementary or linked descriptive, predictive, and theoretical models to integrate and synthesize their research.

WATERSHED

Framework for Aquatic  Modeling in the Earth System (FrAMES)

Modified Universal Soil Loss Equation (MUSLE)

GEOMORPHOLOGY and HYDRODYNAMICS

Delft University of Technolgy hydrodynamic model linked to Simulation WAves Nearshore model (Delft/SWAN)

Land-use Change analysis (LA Analysis)

Hydrodynamic model linked to Marsh Equilibrium Model (Hydro-MEM)

BIOGEOCHEMISTRY

Maximum Entropy Production with Darwinian solution (MEP-Darwin)

Maximum Entropy Production with receding horizon Optimal Control solution (MEP-OC)

CONSUMER DYNAMICS and FOOD WEBS

Structured Equation Modeling (SEM)

Bayesian approaches to model species interaction strengths (Food Web Topology)

Combining stable isotope reverse modeling with community module approach to evaluate changes in species niche space (Isotope Modeling)