Heavy Lake-Effect Snowfall Changes and Mechanisms for the Laurentian Great Lakes Region

Heavy lake-effect snowfall (HLES) events are snowfall events enhanced by interactions between lakes and overlying cold air. Significant snowfall rates and accumulations caused during such events disrupt socioeconomic activities and sometimes lead to lethal consequences. The aim of this study is to assess projected changes to HLES by the end of the century (2079–2100) using a regional climate model for the first time with 3D representation for the Laurentian Great Lakes. When compared to observations over the 1989–2010 period, the model is able to realistically reproduce key mechanisms and characteristics of HLES events, thus increasing confidence in future projections. Projected changes to the frequency and amount of HLES suggest decreasing patterns, during the onset, active and decline phases of HLES. Despite reduced lake ice cover that will allow enhanced lake–atmosphere interactions favouring HLES, the warmer temperatures and associated increase in liquid to solid precipitation ratio along with reduced cold air outbreaks contribute to reduced HLES in the future climate. Analysis of the correlation patterns for current and future climates further supports the weaker impact of lake ice fraction on HLES in future climates. Albeit the decreases in HLES frequency and intensity and projected increases in extreme snowfall events (resulting from all mechanisms) raise concerns for impacts on the transportation, infrastructure and hydropower sectors in the region.

How Many Ciscoes are Needed for Stocking in the Laurentian Great Lakes?

Historically, Cisco Coregonus artedi and deepwater ciscoes Coregonus spp. were the most abundant and ecologically important fish species in the Laurentian Great Lakes, but anthropogenic influences caused nearly all populations to collapse by the 1970s. Fishery managers have begun exploring the feasibility of restoring populations throughout the basin, but questions regarding hatchery propagation and stocking remain. We used historical and contemporary stock-recruit parameters previously estimated for Ciscoes in Wisconsin waters of Lake Superior, with estimates of age-1 Cisco rearing habitat (broadly defined as total ha ≤ 80 m depth) and natural mortality, to estimate how many fry (5.5 months post-hatch), fall fingerling (7.5 months post-hatch), and age-1 (at least 12 months post-hatch) hatchery-reared Ciscoes are needed for stocking in the Great Lakes to mimic recruitment rates in Lake Superior, a lake that has undergone some recovery. Estimated stocking densities suggested that basin-wide stocking would require at least 0.641-billion fry, 0.469-billion fall fingerlings, or 0.343-billion age-1 fish for a simultaneous restoration effort targeting historically important Cisco spawning and rearing areas in Lakes Huron, Michigan, Erie, Ontario, and Saint Clair. Numbers required for basin-wide stocking were considerably greater than current or planned coregonine production capacity, thus simultaneous stocking in the Great Lakes is likely not feasible. Provided current habitat conditions do not preclude Cisco restoration, managers could maximize the effectiveness of available production capacity by concentrating stocking efforts in historically important spawning and rearing areas, similar to the current stocking effort in Saginaw Bay, Lake Huron. Other historically important Cisco spawning and rearing areas within each lake (listed in no particular order) include: (1) Thunder Bay in Lake Huron, (2) Green Bay in Lake Michigan, (3) the islands near Sandusky, Ohio, in western Lake Erie, and (4) the area near Hamilton, Ontario, and Bay of Quinte in Lake Ontario. Our study focused entirely on Ciscoes but may provide a framework for describing future stocking needs for deepwater ciscoes.

A multilevel dataset of microplastic abundance in the world’s upper ocean and the Laurentian Great Lakes

A total of 8218 pelagic microplastic samples from the world’s oceans were synthesized to create a dataset composed of raw, calibrated, processed, and gridded data which are made available to the public. The raw microplastic abundance data were obtained by different research projects using surface net tows or continuous seawater intake. Fibrous microplastics were removed from the calibrated dataset. Microplastic abundance which fluctuates due to vertical mixing under different oceanic conditions was standardized. An optimum interpolation method was used to create the gridded data; in total, there were 24.4 trillion pieces (8.2 × 104 ~ 57.8 × 104 tons) of microplastics in the world’s upper oceans.