Feasibility of implementing an integrated long-term database to advance ecosystem-based management in the Laurentian Great Lakes basin.

The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.

Seasonal overturn and stratification changes drive deep-water warming in one of Earth's largest lakes.

Most of Earth's fresh surface water is consolidated in just a few of its largest lakes, and because of their unique response to environmental conditions, lakes have been identified as climate change sentinels. While the response of lake surface water temperatures to climate change is well documented from satellite and summer in situ measurements, our understanding of how water temperatures in large lakes are responding at depth is limited, as few large lakes have detailed long-term subsurface observations. We present an analysis of three decades of high frequency (3-hourly and hourly) subsurface water temperature data from Lake Michigan. This unique data set reveals that deep water temperatures are rising in the winter and provides precise measurements of the timing of fall overturn, the point of minimum temperature, and the duration of the winter cooling period. Relationships from the data show a shortened winter season results in higher subsurface temperatures and earlier onset of summer stratification. Shifts in the thermal regimes of large lakes will have profound impacts on the ecosystems of the world's surface freshwater.

A consistent Great Lakes ice cover digital data set for winters 1973-2019.

Ice formation and loss in the Laurentian Great Lakes has a strong impact on regional climate, weather, economy and ecology in North America. To record the ice changes during the winter season, Great Lakes ice cover data has been collected and maintained since 1973 by Canadian Ice Service, U.S. National Ice Center, and National Oceanic and Atmospheric Administration's Great Lakes Environmental Research Laboratory. Throughout this long history, technology has improved and the needs of users have evolved, so Great Lakes ice cover datasets have been upgraded several times in both spatial and temporal resolutions. In order to make those long-term data consistent and accessible, we reprocessed the Great Lakes ice cover database to generate daily gridded data (1.8 km resolution) using a re-project method with Nearest Neighbor Search for spatial interpolation, and linear interpolation with categorization for temporal interpolation. This report elucidates data history, generation procedures, and file structure in order to improve access and usability of Great Lakes ice cover data.

Effective fetch and relative exposure index maps for the Laurentian Great Lakes.

Wind exposure is a key physical driver of coastal systems in aquatic environments influencing circulation and wave dynamics. A measure of wind exposure is fetch, the distance over which wind can travel across open water. In large lake systems, such as the Laurentian Great Lakes, estimating fetch has proven to be difficult due to their vast size and complex topobathymetry. Here we describe the development of two spatially discrete indicators of exposure to provide a more accurate indicator of the influence of wind exposure in the nearshore of the Laurentian Great Lakes. We summarized wind data from offshore buoys and used existing tools to calculate effective fetch and a relative exposure index (effective fetch scaled by mean wind speed) at a 30-m grid cell resolution. We validated these models by comparing our exposure maps to the U.S. Army Corps of Engineers Wave Information Studies models and found general agreement. These exposure maps are available for public download for the years 2004-2014.