Research Priorities to Incorporate Terrestrial-Aquatic Interfaces in Earth System Models. Workshop Report, September 7-9, 2016
The terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system, developed from a near balance between terrestrial and aquatic conditions and forming unique processes and community assemblages. Furthermore, TAIs are known to play a critical role in carbon biogeochemical cycling and have the potential to provide major feedbacks to the Earth system (e.g., methane production). However, there is a lack of basic data and multiscale models to adequately describe how a changing climate can influence the key processes (also an unknown) related to Earth system–relevant feedbacks in these unique, ubiquitous ecosystems. In general, Earth system models (ESMs) have excluded TAI ecosystem processes, thus creating tremendous uncertainty as to how TAIs will influence climate feedbacks across a range of scales, spanning from local to global. For example, ESMs represent wetlands very simplistically at best (e.g., the Accelerated Climate Modeling for Energy project) and include only a static fraction of dry land or open water, entirely lacking key processes in these hybrid areas and critical climate and biological feedbacks between land and water. This new area of research, therefore, must integrate a variety of important research topics—plants, soil, hydrology, reactive transport, microbiology, genomics, and modeling—into a systems-level understanding that can be extended to improve predictive modeling capabilities. The goal of the September 2016 Research Priorities to Incorporate Terrestrial-Aquatic Interfaces in Earth System Models Workshop was to engage the scientific community in an open discussion about critical scientific gaps. These gaps and research topics demand immediate field investigations to gather data for representing these important, yet understudied and underrepresented, ecosystems in ESMs. Workshop results will inform the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) as it plans and prepares for future research efforts that address the TAI gap through model-informed and model-inspired field studies. The resulting data will enable iterative refinement of high-resolution, next-generation ESMs. Specifically, the workshop (1) summarized past and current field, process, and modeling TAI research; (2) identified critical sensitivities and uncertainties in the systems; (3) identified key processes, traits, existing data, and environmental variables needed to adequately characterize these systems; and (4) discussed idealized strategies that couple models and experiments to advance the state of the science in TAI modeling, including potential experiments that would test and improve land model fidelity.