Session Lead: Ryan J. Woodland (University of Maryland Center for Environmental Science/Chesapeake Biological Laboratory)
Co-Lead(s): Victoria Coles
Session Format: Oral presentations
Session Description:
Human activities continue to catalyze change in Chesapeake Bay and coastal ecosystems around the world. These activities and their attendant processes are manifold and can alter the fundamental hydrodynamics, biogeochemistry, and productivity of coastal ecosystems. The ecological consequences associated with these changes are often negative for biota and there is a critical need to understand how natural populations and communities will respond to management decisions and larger, global phenomena. Predicting such ecological change is difficult, with complex interactions among drivers such as climate change, eutrophication, fisheries harvest, and shoreline development (to name only a few) likely to influence coastal systems and their associated ecosystem services in unanticipated ways. Further, models are often not designed to provide guidance on issues relevant to stakeholders. However, statistical and mechanistic modeling approaches continue to develop, increasing the feasibility of addressing relevant processes. For example, large, integrated ecosystem model environments such as the Chesapeake Bay Program’s Phase 6 (and soon Phase 7) models provide high-resolution, spatially and temporally explicit model output that can be used as predictors in ecologically relevant forecast and hindcast simulations.
We argue that a collaborative approach is needed to bring stakeholders, technological and model innovations, and big data together to accelerate progress on environmental challenges. This session provides a forum for scientists, managers, and other professionals collaborating on models and data to present their stakeholder-relevant research. We encourage submission of suitable abstracts on a broad array of subjects in this realm, spanning trophic levels, spatiotemporal scales, and methodologies. Abstracts that emphasize cross-disciplinary approaches, new models that take advantage of emerging cyber solutions, or novel applications that leverage pre-existing models are encouraged. Ecological modeling and forecasting sits at the nexus of many disciplines and the goal of this session is to bring together multi-disciplinary research teams that are working at this interface, as well as managers that are tasked with holistically managing coastal ecosystems for an uncertain future. This session is intended to help foster communication across those communities, share novel ideas and examples of successes (and failures) in ecological forecasting, and develop a network of colleagues working in this space.