Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important …
As global climates shift, coastal systems experience changes that alter function within the tidal zone. However, it remains uncertain how changes in tidal extent and magnitude will alter coastal biogeochemical cycling. We present high‐frequency data …
The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field Measurements and Experiments project aims to understand how interactions among water, soils, sediments, and plants drive carbon and nutrient fluxes and transformations across the coastal interface
This project seeks to quantify how subsurface methane seeps contribute to greenhouse gas emissions from the Puget Sound estuary to the atmosphere.
This project seeks to unravel the sequence of processes and sources of terrestrially-derived organic matter that culminate in the immense carbon dioxide outgassing to the atmosphere from tropical rivers worldwide.
This project explores the mechanisms of a recently discovered phenomenon - the emission of methane and other greenhouse gases from trees. We use a range of field and laboratory techniques to understand, and ultimately predict the magnitude and drivers of tree methane emissions in upland and wetland forests near the coast.
Riverine dissolved organic carbon (DOC) contains charcoal byproducts, termed black carbon (BC). To determine the significance of BC as a sink of atmospheric CO2 and reconcile budgets, the sources and fate of this large, slow-cycling and elusive …