Allison Myers-Pigg, Stephanie C. Pennington, Khadijah K Homolka, Allison M Lewis, Opal Otenburg, Kaizad F Patel, Peter Regier, Madison Bowe, Maxium I Boyanov, Nathan A Conroy, Donnie Day, Cooper G Norris, Edward J. O'Loughlin , Jesse Alan Roebuck Jr., Lucie Stetten, Vanessa Bailey, Kenneth M. Kemner , Nicholas Ward, EXCHANGE Consortium

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can enable a mechanistic understanding of coastal ecosystem control points and examine how geographically transferable this knowledge is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium– a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each site, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments. The data described herein aims to characterize the baseline distribution and chemical forms of carbon, nutrients, iron redox and mineralogy across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. This first campaign measures surface water quality parameters (e.g., conductivity, pH, ORP, alkalinity, and total suspended solids); bulk geochemical parameters on water, soil, and sediment samples (e.g., carbon, nutrient, and ionic concentration and composition); physicochemical parameters of sediment and soil (soil pH, conductivity, bulk density, water retention); and the rate of O2 consumption in inundated sediment and soil samples. Future campaigns will focus on building off these baseline datasets to enable a mechanistic understanding of coastal ecosystem biogeochemical control points.