Document Details

The overall goal of the Georgia Coastal Ecosystems (GCE) Long-Term Ecological Research program is to understand estuarine and intertidal ecosystems and how they respond to long-term change. Since the program began in 2000 the Principal Investigator (PI) team has established a robust program of long-term field observations, experiments, remote sensing, and modeling to understand wetland ecosystem functioning. The PIs will build on this in GCE-V, but with an overlay of new efforts focused on variability. The GCE-V project has 5 programmatic areas that map onto objectives (obj). Obj. 1 is to characterize spatial and temporal patterns in mean and variability of drivers and responses. This will be done by measuring external drivers (e.g., sea level), marsh and estuarine conditions, the wetland biophysical template, and modeling. Obj 2 is to evaluate linkages between external drivers and ecological responses, and determine whether assessing the variability of abiotic drivers improves explanatory power for predicting those responses. This will be done by analyzing long-term data and conducting field campaigns in areas with different salinity standard deviations and time-varying inundation, and complementary mechanistic experiments exploring effects of driver variability (e.g., salinity). Obj. 3 is to assess disturbances and their effects on patterns of variability in ecological responses. This will be done by tracking response to and recovery from natural disturbances in the field and in ongoing experimental manipulations. Obj. 4 is to evaluate how ecological properties change across abiotic gradients, and determine whether variability increases near habitat transitions. This will be done using remote sensing, sampling across gradients of salinity and inundation, and establishing new long-term monitoring sites in forested areas to track upland marsh migration. Obj. 5 is to determine the mechanisms by which coastal wetlands respond to changing drivers and assess whether variability informs this understanding. This will be done by conducting univariate and multivariate analyses relating key ecosystem variables (e.g., net ecosystem exchange, plant biomass) to drivers (salinity, inundation, temperature), using remote sensing to investigate spatial and temporal patterns in the mean and variability of marsh productivity and their relationship to variability in climate drivers, and synthesizing results to describe net daytime production and above- and below-ground C stocks and how they might change in response to future conditions.

Merryl Alber, Deepak Mishra, Craig Osenberg, Steve Pennings, Adam Sapp and Amanda Spivak. 2025. GCE V renewal proposal, submitted to NSF in March 2024 (text only version). Georgia Coastal Ecosystems LTER File Archive, University of Georgia, Athens, Georgia. (https://gce-lter.marsci.uga.edu/public/app/resource_details.asp?id=1087&version=1)