Colorado mountains
From Long-Term Data to Understanding: Toward a Predictive Ecology
2015 LTER ASM Estes Park, CO - August 30 - September 2, 2015

Virginia Coast Long-Term Ecological Research: Drivers, Dynamics and Consequences of Non-linear Change in Coastal Barrier Systems

Printer-friendly versionPrinter-friendly version

Poster Number: 
Presenter/Primary Author: 
Karen McGlathery
John Porter
Patricia Wiberg
Matthew Reidenbach
(and others)

The Virginia Coast Reserve (VCR) is a heterogeneous landscape with mainland watersheds, tidal marshes, mudflats, shallow coastal bays, and barrier islands. Transitions between ecosystems can be abrupt with threshold responses to external drivers.  Our central hypothesis is that ecosystem changes on the coastal barrier landscape in response to long-term drivers are primarily the result of complex non-linear dynamics based on the existence of alternative stable states and threshold responses. Our research is organized around three synthetic themes:  (1) Mechanisms of long-term change; (2) Ecosystem connectivity; and (3) Interacting drivers, scales and feedbacks.

We ask the questions related to these themes: (1) What are the mechanisms of non-linear state change in coastal barrier landscapes in response to environmental drivers? Are there specific thresholds for ecosystem state change and leading indicators of proximity to that threshold? (2) To what extent does connectivity of adjacent ecosystems via fluxes of sediment and organisms affect responses to environmental change? Is there evidence of subsidies between adjacent habitats that influence key ecosystem processes, services and states? (3) How will ecosystem resilience, state dynamics, and the delivery of ecosystem services vary in response to the multiple drivers of climate and land use change?

Data from our observations, experiments and analyses of remote-sensing imagery are linked with quantitative models to understand dynamics of ecosystem state transitions under current conditions, to test these dynamics by hindcasting past conditions, and to explore future scenarios of long-term change.