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Ecological Assessment of Wisconsin - Lake Michigan

doi: 10.25923/b9my-ex29 Ecological Assessment of -

Editors Charles Menza Matthew S. Kendall

May 2019

NOAA TECHNICAL MEMORANDUM NOS NCCOS 257

NOAA NCCOS Marine Spatial Ecology Division Citations Full report citation: Menza, C., and M.S. Kendall (eds). 2019 . Ecological Assessment of Wisconsin - . NOAA NOS National Centers for Coastal Ocean Science, Marine Spatial cE ology Division. NOAA Technical Memorandum NOS NCCOS 257. Silver Spring, MD. 106 pp. doi: 10.25923/b9my-ex29

Chapter citation: example for Chapter 2 Menza, C., M.S. Kendall, W. Sautter, A. Mabrouk, and S.D. Hile. 2019. Chapter 2: Lakebed Geomorphology, Substrates, and . pp. 5-30. In: C. Menza and M.S. Kendall (eds.), Ecological Assessment of Wisconsin-Lake Michigan. NOAA NOS National Centers for Coastal Ocean Science, Marine Spatial cE ology Division. NOAA Technical Memorandum NOS NCCOS 257. Silver Spring, MD. 106 pp. doi: 10.25923/b9my-ex29

Acknowledgments This report was funded by NOAA’s National Centers for Coastal Ocean Science (NCCOS), and received many in-kind contributions, including staff time and scientific equipment, from the NOAA Great Environmental Laboratory (GLERL) and NOAA National Marine Sanctuary.

This report was made possible through the cooperation and participation of many federal, state, and non- governmental partners. In particular, we’d like to thank Russ Green (NOAA Office of National Marine Sanctuaries; ONMS) and Ellen Brody (ONMS) for project development, planning and coordination; Tamara Thomsen (Wisconsin Historical Society; WHS), Caitlin Zant (WHS), and John Broihahn (WHS) for helping prioritize survey sites and contributing maritime heritage expertise; David Mickelson (University of Wisconsin; UW), Lucas Zoet (UW), Elmo Rawling (UW), Steven Brown ( State Geological Survey; ISGS), and Ethan Theuerkauf (ISGS) for sharing geological expertise; Mark Rowe (GLERL), and David “Bo” Bunnell (U.S. Geological Survey; USGS) for sharing their mussel and fish data sets; Brandon Krumwiede (NOAA Office for Coastal Management; OCM) and Mark Finkbeiner (OCM) for support using the Coastal and Marine Ecological Classification Standard. We’d also like to thank Chris Jeffery (NOAA NCCOS and CSS, Inc.), Annie Jacob (NCCOS and CSS, Inc.), Russ Green (ONMS), John Janssen (UW), Steven Pothoven (GLERL), Jia Wang (GLERL), Ed Rutherford (GLERL), Titus Seilhemer (Wisconsin Grant), David “Bo” Bunnell (USGS), and Kevin McMahon (NCCOS) for providing reviews and subject matter expertise; and Sarah Hile (NCCOS, CSS, Inc.) for review and preparation of this report for publication.

Some of the ecological data characterizing the lakebed in this report was acquired by fieldwork requiring support from many people. We’d like to thank Dennis Donohue (GLERL) for coordinating the deployment of the RV and 26’ SeaArk; Travis Smith (GLERL), our captain, for straight survey lines and keeping us safe; Brent Johnston, Beau Braymer, and John Bright for installing field equipment and ensuring successful data acquisition; Mark Amend (Kongsberg, Inc.) and Hans VanSumeren for technical support in the field; Rachel Husted (formerly with CSS, Inc.) for collecting and processing field data; Jay Lazar for instructions on how to collect and process sidescan data; the Thunder Bay National Marine Sanctuary for lending their Klein 3000 sidescan sonar system; Kongsberg, LLC and Mark Amend for lending an EM2040c multibeam kit; and the Sheboygan Harbor Centre Marina, the Wisconsin Maritime Museum and Manitowoc Marina for berthing.

Some of the chapter authors and people acknowledged for supporting this report were CSS, Inc. employees supported under NOAA contract Nos. EA133C-14-NC-1384 and EA133C-17-BA-0062. Front and back cover images are provided by NOAA except front image of , provided by Andrew Muir (Great Lakes Fishery Commission).

Mention of trade names or commercial products does not constitute endorsement or recommendation for their use by the government. https://doi.org/10.25923/b9my-ex29

Ecological Assessment of Wisconsin-Lake Michigan

Prepared by: Biogeography Branch Marine Spatial Ecology Division (MSE) National Centers for Coastal Ocean Science (NCCOS) NOAA National Ocean Science (NOS) Silver Spring, MD USA

May 2019

EDITORS Charles Menza Matthew S. Kendall

NOAA Technical Memorandum NOS NCCOS 257

United States Department National Oceanic and National of Commerce Atmospheric Administration Ocean Service

Wilbur L. Ross, Jr. Neil A. Jacobs, PhD Nicole LeBoeuf Secretary Under Secretary Assistant Administrator, Acting

About This Report

For over 30 years, the National Centers for Coastal Ocean Science has compiled and assessed coastal ecological information to develop effective conservation and management tools for many of the nation’s special places. The impetus of this report when it was conceived in 2015 was to provide ecological information that would support the designation and management of the proposed Wisconsin-Lake Michigan National Marine Sanctuary.

During the completion of this report, the future of the proposed sanctuary designation became uncertain. However, the report was finished for several reasons. Funding to complete the report had already been allocated and much of the report had already been written. Perhaps most importantly, although this report was designed for sanctuary managers, we understood it would also benefit other planners and policy makers, including the Wisconsin Historical Society, Wisconsin Department of Natural Resources, U.S. Army Corps of Engineers, and U.S. Environmental Protection Agency. In addition, it serves as an instrument for engaging local communities, research partners and resource managers in a common, accessible, and scientifically sound body of knowledge.

This report characterizes lakebed features, , lake ice, invasive mussels, and fishes offshore of Wisconsin in western Lake Michigan. It is organized into separate chapters for each of these ecological components, and addresses the status and trends of these components over the past 10 to 20 years.

This report was part of a broader three year project to support the Office of National Marine Sanctuaries in Lake Michigan. The project also developed several complementary datasets and tools including: new classified lakebed GIS data; new bathymetry, backscatter and sonar imagery; lakebed mapping priorities compiled from a group of Lake Michigan experts; and online tools to explore new lakebed maps and imagery, as well as, existing ecological datasets collected by other agencies and organizations.

For more information on how to obtain this report or complementary datasets and tools, please visit the National Centers of Coastal Ocean Science website (https://coastalscience.noaa.gov/), or contact:

Charles Menza, Principal Investigator Biogeography Branch, Marine Spatial Ecology Division National Centers for Coastal Ocean Science NOAA National Ocean Service [email protected] Phone: 240.533.0372 or

John D. Christensen, Chief Biogeography Branch, Marine Spatial Ecology Division National Centers for Coastal Ocean Science NOAA National Ocean Service Phone: 240.533.0378

Table of Contents Executive Summary...... i Chapter 1 Introduction...... 1 Charles Menza 1.1 Introduction...... 1 1.2 Report’s Objective...... 3 1.3 References ...... 3 Chapter 2 Lakebed Geomorphology, Substrates and Habitats ...... 5 Charles Menza, Matthew S. Kendall, Will Sautter, Ayman Mabrouk, and Sarah D. Hile 2.1 Introduction...... 5 2.2 Data and Methods...... 6 2.2.1 Literature Review...... 6 2.2.2 Multibeam and Sidescan Sonar Surveys...... 7 2.2.3 Lidar Bathymetry Interpretation...... 9 2.2.4 Lakebed Classification ...... 9 2.2.5 Lakebed Maps...... 12 2.2.6 Digital Lakebed Maps...... 14 2.3 Current Conditions and Trends...... 16 2.3.1 Geomorphology...... 16 2.3.2 Substrate...... 19 2.3.3 Invasive Mussels...... 20 2.3.4 Macroalgae...... 22 2.3.5 Human Disturbance...... 23 2.3.6 Biotope...... 24 2.4 Discussion...... 25 2.4.1 Rocky Substrate ...... 26 2.4.2 No Bedrock Detected ...... 26 2.4.3 Suspected Dredge Deposits...... 27 2.4.4 New Interpretations of Lidar Data ...... 27 2.4.5 Lakebed Maps Support Submerged Cultural Resource Management...... 27 2.5 References ...... 28 Chapter 3 Water Quality...... 31 Charles Menza, Dan S. Dorfman, Ayman Mabrouk, Varis Ransibrahmanakul 3.1 Introduction...... 31 3.2 Data and Methods...... 32 3.3 Current Conditions and Trends...... 34 3.3.1 Temperature ...... 34 3.3.2 Upwelling ...... 37 3.3.3 Turbidity ...... 37 3.3.4 Phosphorus and Nitrogen ...... 40 3.3.5 Chlorophyll a...... 40 3.3.6 Dissolved Oxygen ...... 42 3.3.7 Fecal Contamination, Escherichia coliform (E. Coli)...... 43 3.4 Discussion ...... 44 3.5 References ...... 47 Table of Contents Chapter 4 Lake Ice...... 53 Christopher Clement 4.1 Introduction...... 53 4.2 Data and Methods...... 54 4.3 Current Conditions and Trends...... 55 4.3.1 Ice Season Temporal Characteristics...... 55 4.3.2 Ice Concentration and Spatial Coverage ...... 59 4.4 Discussion...... 60 4.5 References ...... 61 Chapter 5 Invasive Mussels...... 63 Simon Pittman, Charles Menza, Ashley Elgin 5.1 Introduction...... 63 5.2 Data and Methods...... 64 5.3 Current Conditions and Trends ...... 66 5.4 Discussion...... 70 5.5 References ...... 73 Chapter 6 Fish ...... 81 David Moe Nelson, Larry Claflin 6.1 Introduction...... 81 6.2 Data and Information Sources...... 84 6.3 Current Conditions and Trends by Species...... 85 6.3.1 Lake Trout...... 85 6.3.2 Chinook and ...... 87 6.3.3 Steelhead/, Brown Trout, and ...... 87 6.3.4 ...... 88 6.3.5 Bloater...... 89 6.3.6 ...... 91 6.3.7 Sculpins...... 92 6.3.8 Ninespine Stickleback ...... 93 6.3.9 Rainbow ...... 94 6.3.10 ...... 95 6.3.11 ...... 95 6.3.12 ...... 97 6.3.13 Lake ...... 97 6.3.14 Sea ...... 97 6.4 Discussion...... 98 6.5 References ...... 98 6.6 Appendix A...... 104

Executive Summary Executive Summary

Wreck of the steamer Vernon within the survey area. Credit: Tamara Thomsen, Wisconsin Historical Society

This report is an assessment of key physical, chemical, and biological attributes that influence the natural and cultural resources offshore of Wisconsin in western Lake Michigan. It is a synthesis of existing scientific literature and a collection of new ecological data that organizes and substantially expands the body of ecological knowledge within the study area. It was conceived to support the designation and management of the proposed Wisconsin-Lake Michigan National Marine Sanctuary, but it is also an instrument for engaging communities, research partners and resource managers in a common, accessible, and scientifically sound body of knowledge.

This report characterizes the current conditions and trends of lakebed features, water quality, lake ice, invasive mussels, and the fish community. These ecological components are strongly linked to the preservation and conservation of submerged cultural resources, as well as access to and public perception of those resources. Equally important, the characterization of these ecological resources will serve a much broader purpose in the overall conservation of Lake Michigan.

Chapter 1 provides a brief overview of the proposed Wisconsin-Lake Michigan National Marine Sanctuary. It also connects this ecological assessment to the proposed sanctuary’s goals of protecting and interpreting a nationally significant collection of underwater cultural resources, and enhancing and facilitating broader lake conservation efforts.

Although this report compiles many existing datasets, it also draws heavily upon a new lakebed survey completed off Manitowoc, Wisconsin. Chapter 2 describes the recent lakebed survey and provides new data describing geomorphological features, substrates, biological distributions and human impacts within the study area. The surveys revealed broad coverage of rocky substrate, a rarity in the Great Lakes, understudied glacial features formed during the , and the widespread impacts of invasive mussels and human disturbance on the lakebed. These data are critical to managing fish which prefer spawning on rocky substrate (e.g., lake trout and yellow perch), support the preservation and protection of submerged cultural resources, and impart new information showing the location and impacts of human activities on the lakebed.

Ecological Assessment of Wisconsin - Lake Michigan i Executive Summary

Chapter 3 focuses on a core set of chemical, physical, and biological parameters that are commonly used as indicators of water quality and which broadly characterize the status and trends of ecological health needed to support aquatic life, and safe access to lake resources. Overall, the study area is considered to have relatively good water quality, however recent changes in nearshore regions have been more equivocal. There is a dichotomy in productivity between nearshore and offshore regions created by a nearshore nutrient shunt linked to invasive mussels. The mussels and associated shunt have led to increases of macroalgae like Cladophora nearshore and concurrently the decline of offshore, particularly the spring bloom. One of the most striking findings from this assessment is how different the study area is from the broader lake when considering water temperature. The study area is positioned within the most active region of upwelling in Lake Michigan, and it also shows no signs of warming, which contrasts with Lake Michigan as a whole.

Chapter 4 focuses on the characteristics of ice cover in the study area. Lake ice is important to understand, because it impacts coastal and lake economics through its effects on navigation, hydropower generation, lake levels, flooding, recreational opportunities, and damage to shore structures. The waters of the study area are subject to a regular yearly cycle of winter freezing and spring melting, which is quite variable from year to year. Time series and summaries are provided for first ice, last ice, length of ice season, number of ice days, percent spatial cover and maximum ice cover.

Chapter 5 characterizes spatial and temporal patterns of invasive zebra (Dreissena polymorpha) and quagga (Dreissena rostriformis bugensis) mussels in the study area and highlights some of the known ecological consequences. Both species are filter-feeding biofoulers that have fundamentally transformed the physical, chemical, and biological components of Lake Michigan’s ecosystem and are considered a threat to underwater maritime heritage. This chapter documents the spatial and temporal patterns of the mussel invasion and the shift from zebra to quagga mussels in the study area. The patterns are significant since attached mussels and associated Cladophora blooms cover and obscure structures, and mussel colonization can accelerate corrosion and breakage of maritime artifacts.

Chapter 6 provides a baseline description of the fish and fisheries of the study area, and describes their role in the region’s ecological context. The area supports a diverse set of fish species and fish habitats; however, it is clear the fish community and habitats have dramatically changed in the past century. Impacts from non-native species, fluctuating nutrient loads, changing food webs, new contaminants, fisheries, and other ecological factors have resulted in widely different impacts to abundance across species. Some species have been extirpated, some have increased, but most have persisted at substantially lower abundances. The chapter ends with a series of questions coastal managers will need to answer, and highlights the uncertainty for the fish community in the study area.

Many of the assessed physical, chemical, and biological attributes, particularly indicators of water quality, invasive mussels and fishes, reveal that the study area and the broader are in an era of protracted, widespread environmental change. The most powerful catalyst of this change has been the invasion of various non-indigenous species, including zebra and quagga mussels. These invasions have significantly shifted the foundation of the study area’s , distorted nutrient cycles, and widely impacted water quality. These changes are ongoing and the ultimate end point of the ecosystem is uncertain, particularly given the uncertain impacts of accelerated climate change.

ii Ecological Assessment of Wisconsin - Lake Michigan Chapter 1 Introduction Charles Menza1

Port Washington lighthouse, Wisconsin. Credit: NOAA NOS/ONMS

1.1 INTRODUCTION This assessment focuses on western Lake Michigan along Wisconsin’s coast and more specifically the area proposed as the Wisconsin – Lake Michigan National Marine Sanctuary (NOAA ONMS 2016, Figure 1.1). The proposed sanctuary encompasses over 2,500 km2 (1,000 mi2) of waters and bottom lands adjacent to Manitowoc, Sheboygan, and Ozaukee Counties, and lies alongside the shoreline communities of Port Washington, Sheboygan, Manitowoc, and Two Rivers among others. An alternative, larger sanctuary boundary option (Alternative B Figure 1.1) identified in the proposed sanctuary’s Draft Environmental Impact Statement (NOAA ONMS 2016) includes an additional area off Kewaunee County, which is also included in our report. The proposed sanctuary boundaries provide a convenient focus; however, since species, habitats and datasets do not align neatly with man-made administrative boundaries, this assessment includes information presented at broader scales for ecological context as advocated by NOAA’s biogeographic assessment framework approach (Caldow et al. 2015).

The proposed sanctuary would protect and interpret a nationally significant collection of underwater cultural resources, including 37 known and numerous other historic maritime-related features (Meverden and Thomsen 2008, NOAA ONMS 2016). In addition, archival research indicates approximately 80 other shipwrecks are likely within the boundaries of the proposed sanctuary (Meverden and Thomsen 2008, NOAA ONMS 2016). The sanctuary would also enhance and facilitate broader conservation efforts, as well as heritage tourism within the many communities that have embraced their centuries-long maritime relationship with Lake Michigan, the Great Lakes region, and the nation.

Undeniably, the study area has a recognized trove of submerged cultural resources (Meverden and Thomsen 2008, Jensen and Hartmeyer 2014, NOAA ONMS 2016), but the study area is ecologically exceptional as well. Unlike most of the Great Lakes, the study area possesses substantial surficial rocky substrate (Janssen et al. 2005) and high rates of upwelling (Plattner et al. 2006). These rare attributes are key physical factors supporting

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch. Silver Spring, MD

Ecological Assessment of Wisconsin - Lake Michigan 1 Introduction Chapter 1 Chapter

Figure 1.1. Map of the study area boundary. Boundaries from ONMS (2016).

2 Ecological Assessment of Wisconsin - Lake Michigan Introduction critical fish nursery and spawning habitats (Goodyear et al. 1982), and high lake productivity (Fitzsimons et al. 2002). In addition, the area historically supported the greatest concentrations of Diporeia, a shrimp-like crustacean which was once one of the most important organisms in the Great Lakes food-web, and has been a hotspot for invasive mussels in Lake Michigan (Nalepa et al. 2014).

There is a rich history of ecological research relevant to the study area conducted by the Great Lakes Environmental Research Laboratory, the Wisconsin Historical Society, the University of Wisconsin, the University of Michigan, the Wisconsin Department of Natural Resources, and the US Army Corps of Engineers. Their research provides information on the broad-scale ecology (Edsall and Munawar 2005, Janssen et al. 2005, Nalepa et al. 2009), geology (Lineback et al. 1974, Wickham et al. 1978), pressures (EPA 2008, Smith et al. 2015, ECCC and EPA 2017), management (Pearsall et al. 2012) and submerged cultural resources (Meverden and Thomsen 2008, Jensen and Hartmeyer 2014) in the study area. Separately, individual studies achieve 1 Chapter many different, often uncoordinated objectives. Taken together, studies tell a more holistic story.

1.2 REPORT’S OBJECTIVE The objective of this ecological assessment is to synthesize both existing and new ecological data that will facilitate protection and interpretation of underwater cultural resources, and enhance and facilitate broader lake conservation efforts and heritage tourism within the study area. Accordingly, this report characterizes lakebed features (Chapter 2), water quality (Chapter 3), lake ice (Chapter 4), invasive mussels (Chapter 5), and the fish community (Chapter 6) – all of which are strongly linked to the preservation and conservation of submerged cultural resources, as well as access to and public perception of those resources. Equally important, the characterization of these ecological resources will serve the broader conservation of Lake Michigan.

1.3 REFERENCES Caldow, C., M.E. Monaco, S.J. Pittman, M.S. Kendall, T.L. Goedeke, C. Menza, B.P. Kinlan, and B. Costa. 2015. Biogeographic Assessments: A framework for information synthesis in marine spatial planning. Marine Policy 51: 423-432. doi: https://doi.org/10.1016/j.marpol.2014.07.023

ECCC and EPA. 2017. State of the Great Lakes 2017 Technical Report. Cat. No. En161-3/1E-PDF. EPA 905-R- 17-001. Environment and Climate Change and the U.S. Environmental Protection Agency. 552 pp. Online: https://binational.net/wp-content/uploads/2017/09/SOGL_2017_Technical_Report-EN.pdf (Accessed 30 April 2019)

Edsall, T., and M. Munawar (eds.). 2005. State of Lake Michigan: Ecology, Health, and Management. Michigan State University Press. 639 pp.

EPA. 2008. Lake Michigan lakewide management plan (LaMP) 2008 Status Report. 233 pp. Online: https:// www.epa.gov/sites/production/files/2015-11/documents/lake-michigan-lamp-2008-233pp.pdf (Accessed 22 April 2019)

Fitzsimons, J.D., D.L. Perkins, and C.C. Kruger. 2002. Sculpins and in lake trout spawning areas in Lake : estimates of abundance and egg predation on lake trout eggs. Journal of Great Lakes Research 28: 421-436. doi: https://doi.org/10.1016/S0380-1330(02)70595-9

Goodyear, C.S., T.A. Edsall, K.M. Ormsby-Dempsey, G.D. Moss, and P.E Polanski. 1982. Atlas of the spawning and nursery areas of Great Lakes fishes. Volume IV: Lake Michigan. U.S. Fish and Wildlife Service. FWS/OBS- 82/52. 211 pp.

Ecological Assessment of Wisconsin - Lake Michigan 3 Introduction

Janssen, J., M.B. Berg, and S.J. Lozano. 2005. Submerged terra incognita: Lake Michigan’s abundant but unknown rocky zones. pp. 113-139. In: T. Edsall and M. Munawar (eds.), State of Lake Michigan: Ecology, Health, and Management. Michigan State University Press. 639 pp.

Jensen, J.O. and P. Hartmeyer. 2014. A Cultural Landscape Approach (CLA) Overview and Sourcebook for Wisconsin’s Mid-Lake Michigan Maritime Heritage Trail Region. Prepared for NOAA Office of National Marine Sanctuaries. 95 pp.

Lineback, J.A., D.L. Gross, and R.P. Meyer. 1974. Glacial Tills under Lake Michigan. University of Wisconsin Geophysical and Polar Research Center Contribution 311. Environmental Geology Notes 69. 62 pp.

Chapter 1 Chapter Meverden, K.N. and T.L. Thomsen. 2008 Wisconsin’s Historic Shipwrecks: An Overview and Analysis of Locations for a State/Federal Partnership with the National Marine Sanctuary Program. Wisconsin State Archaeology Maritime Preservation Program Technical Report Series #08-003. 129 pp.

Nalepa, T.F., D.L. Fanslow, and G.A Lang. 2009. Transformation of the offshore benthic community in Lake Michigan: recent shift from the native amphipod Diporeia spp. to the invasive mussel Dreissena rostriformis bugenis. Freshwater Biology 54: 466-479. doi: https://doi.org/10.1111/j.1365-2427.2008.02123.x

Nalepa, T.F., D.L. Fanslow, G.A. Lang, K. Mabrey, and M. Rowe. 2014. Lake-wide benthic surveys in Lake Michigan in 1994-95, 2000, 2005, and 2010: Abundances of the amphipod Diporeia spp. and abundances and biomass of the mussels Dreissena polymorpha and Dreissena rostriformis bugensis. NOAA Technical Memorandum GLERL-164. NOAA Great Lakes Environmental Research Laboratory. Ann Arbor, MI. 21 pp.

NOAA ONMS. 2016. Wisconsin - Lake Michigan National Marine Sanctuary Designation Draft Environmental Impact Statement. NOAA Office of National Marine Sanctuaries. Silver Spring, MD. 125 pp.

Pearsall, D., P. Carton de Grammont, C. Cavalieri, P. Doran, L. Elbing, D. Ewert, K. Hall, M. Herbert, M. Khoury, S. Mysorekar, S. Neville, J. Paskus, and A. Sasson. 2012. Michigami: Great Water. Strategies to Conserve the of Lake Michigan. Technical Report. A joint publication of The Nature Conservancy and Michigan Natural Features Inventory. 309 pp. with Appendices. doi: https://doi.org/10.13140/RG.2.2.13422.61764

Plattner, S., D.M. Mason, G.A. Leshkevich, D.J. Schwab, and E.S. Rutherford. 2006. Classifying and Forecasting Coastal Upwellings in Lake Michigan Using Satellite Derived Temperature Images and Buoy Data. Journal of Great Lakes Research 32: 63-76. doi: 10.3394/0380-1330(2006)32[63:CAFCUI]2.0.CO;2

Smith S.D., P.B. McIntyre, B.S. Halpern, R.M. Cooke, Marino A.L., G.L. Boyer, A. Buchsbaum, G.A. Burton Jr., L.M. Campbell, J.J. Ciborowski, and P.J. Doran. 2015. Rating impacts in a multi-stressor world: a quantitative assessment of 50 stressors affecting the Great Lakes. Ecological Applications 25(3): 717-728. doi: https://doi. org/10.1890/14-0366.1

Wickham J.T. D.L. Gross, J.A Lineback, and R.L. Thomas. 1978. Late Quaternary Sediments of Lake Michigan. Environmental Geology Notes No. 84. Illinois State Geological Survey, Urbana, IL.

4 Ecological Assessment of Wisconsin - Lake Michigan Chapter 2 Lakebed Geomorphology, Substrates and Habitats

Charles Menza1 Matthew S. Kendall1, Will Sautter1,2, Ayman Mabrouk1,2, and Sarah D. Hile1,2

Algae and mussels on cobble substrate, Lake Michigan. Credit: NOAA NOS/NCCOS

2.1 INTRODUCTION This chapter characterizes lakebed geomorphological features, substrates and habitats within the Wisconsin - Lake Michigan study area. These lakebed characteristics are valuable to understanding the distribution of natural and cultural resources, managing important fishes, identifying hazards to navigation, and supporting other aspects of commerce and recreation. Lakebed characteristics are also useful in recognizing factors which impact degradation, preservation and conservation of underwater cultural resources, such as the many shipwrecks in the study area (NOAA ONMS 2016).

There are numerous surveys of the study area which impart information on lakebed geomorphology, substrates and habitats, but surveys are scattered and meant to achieve many different and uncoordinated objectives. For example, in situ observations were used to characterize fish , echograms were used to plot stratigraphic units, satellite imagery were used to map nuisance algae, and bathymetric soundings were used to update nautical charts. Taken together they offer general information broadly, and detailed, but discordant information at specific sites. They also leave broad data gaps, particularly on hard bottom substrates and in deeper water.

This chapter summarizes existing information on geomorphology, substrates and habitats and identifies data gaps in the study area. We sought to strategically expand on the existing body of knowledge by conducting new multibeam and sidescan surveys, and interpreting existing lidar (Light Detection and Ranging) surveys for the first time in the study area. The survey and interpretations were executed in a large data gap, and provide new information on glacial features, cobble habitats, hard clay deposits, and invasive mussel beds among many other lakebed attributes.

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch. Silver Spring, MD 2 CSS, Inc. Fairfax, VA

Ecological Assessment of Wisconsin - Lake Michigan 5 Lakebed 2.2 DATA AND METHODS 2.2.1 Literature Review We conducted a literature review to identify all sources of lakebed geomorphology, substrate and habitat information in the study area prior to 2019 (Table 2.1). Janssen et al. (2005) provide a good summary of data collections prior to 2005. These and more recent collections are included in Table 2.1. Previous studies established useful lakebed survey approaches, provided an inventory of known lakebed features, and identified spatial and thematic data gaps.

Most lakebed information in the study area is derived from bathymetry and therefore is tightly linkedto bathymetric data density and spatial coverage (Table 2.1). Prior to our 2017 multibeam and sidescan survey, relatively high-density bathymetry (at least 1 sounding per 2m ) was collected only within a couple of kilometers from shore using lidar. These lidar surveys provide high-density bathymetry with sufficient detail to characterize fine and moderate scale (1 m to 1 km) lakebed features and the potential to model substrate composition. The remainder of the study area (approximately 90% of the lakebed) comprises relatively low-density bathymetric data ( approximately 1 to 100 soundings per km2) with gaps as large as 200 km2 without any bathymetry data at all. Low-density bathymetry comes from surveys by NOAA National Ocean Service (NOS) prior to 1950 using single beam echosounders, and more recent community-sourced bathymetry. These lower density

Chapter 2 Chapter Table 2.1. A summary of lakebed surveys within the study area prior to 2019. Survey type Data Type Surveyors Spatial coverage Temporal coverage Soundings from single- Low-density, NOAA’s Office of Coastal Widespread, with gaps before 1950 beam echosounders bathymetric soundings Survey (OCS) as large as 200 km2 , cruising, and Aggregated offshore of Aggregated low-density Community-sourced communities (C-MAP Sheboygan, Manitowoc, unknown, presumed bathymetry using bathymetry Genesis and Social Map Kewaunee and Port 2000 to the present various systems charts) Washington Piston cores, gravity Great Lakes Biolimnology Widespread and Stratigraphic surveys cores, and subbottom Laboratory, Canada Centre systematic, core density 1975 echograms for Inland Waters approx. 1 per 100 km2 Lidar (Light Detection and High-density swath US Army Corps of Engineers Entire nearshore out to 2008, 2012, planned Ranging) topography/ topography/bathymetry (USACE) 10 m depth for 2019 bathymetry High-density swath NOAA's National Centers Isolated to offshore Mid-depth sonar surveys bathymetry and for Coastal Ocean Science of Manitowoc and 2017, 2018 sidescan (NCCOS) Sheboygan, WI Shoreline material USACE shoreline Shoreline descriptors Entire shoreline 2012 classes descriptors Submerged aquatic Nearshore, satellite- Michigan Tech (Shuchman Entire shoreline out to vegetation and sand 2008-2011 based assessments et al. 2013) 10 m depth predictions Two Rivers, Manitowoc, University of Wisconsin (J. Harbor surveys Sidescan Sheboygan, and Port 2018 Janssen, pers. comm.) Washington harbors Selected Fucciolo 1993, Edsall et al. Clay Banks reef (off Sidescan, in situ surveys 1985 characterizations 1995a, 1995b Kewaunee county) Goodyear et al. 1982, before 1982, Historical fish spawning General descriptive Various littoral and Coberly and Horrall 1980, except for Janssen's and nursery surveys characterizations offshore reefs Janssen et al. 2005 observations Powers and Robertson Offshore station/transect Grab samples and video 1968 and Karatayev et al. 10 offshore stations 2000-2018 characterizations transects 2018

6 Ecological Assessment of Wisconsin - Lake Michigan Lakebed bathymetry datasets provide lakebed information restricted to only broad spatial scales (>1 km), but given their comprehensive spatial coverage they have been used to update nautical charts, improve navigation, and interpolate continuous bathymetry (NGDC 1996) and geomorphology (GLAHF 2018) surfaces. Another source of broad spatial scale lakebed information are a series of piston cores, gravity cores, and subbottom echograms collected by Wickham et al. (1978). These data mapped the thicknesses of several glaciolacustrine and lacustrine stratigraphic units throughout the study area at very broad spatial scales (>1 km).

Detailed information on the composition of lakebed substrate is extremely limited in the study area. Lakebed composition has been characterized along the shoreline, inside harbors, and on a handful of reefs and offshore stations T( able 2.1). These data are scattered throughout the study area to achieve various objectives, although most data were collected to assess fish habitats and monitor benthic fauna. The different surveys use different substrate classification systems, but several have been compiled to interpolate consistent broad-scale substrate types throughout Lake Michigan (GLAHF 2018; Riseng et al. 2018).

Taken together, observations and models show the study area’s lakebed consists of lacustrine clays, glacial deposits, bedrock, and anthropogenic debris These are organized into a diverse set of geomorphological features, such as rocky reefs, cobble fields, clay outcrops and flat unconsolidated sediment (e.g., Janssen et al.

2005, see Section 2.3). 2 Chapter

In addition to physical lakebed attributes 10 10 0 10 20 30 km (e.g., geomorphology, stratigraphy), ¯ 30 0 100 10 20 mi many of the surveys listed in Table 2.1 Algoma 44°36'N also collected biological information to 200 map important fishes (Coberly and Horrall 1980, Goodyear et al. 1982, Fucciolo Kewaunee 1993, Edsall et al. 1995a, 1995b, Janssen 44°24'N et al. 2005), invasive mussels (Karatayev 100 and Burlakova 2017) and nuisance algae Two (Shuchman et al. 2013). These biological Rivers 44°12'N 200 datasets, as well as invasive mussel (Rowe et al. 2015) and Cladophora (University Manitowoc of Wisconsin 2019) distribution models 44°N characterize a range of benthic habitats in the study area. 100 Lakebed maps 43°48'N Phase I - Maps completed 2.2.2 Multibeam and Sidescan Sonar Sheboygan Phase II - Maps being processed Surveys Contours (m) Proposed Sanctuary Boundaries To address data gaps in the existing body Alternative A (preferred) 43°36'N of lakebed knowledge, we surveyed Alternative B the lakebed off Manitowoc, Wisconsin Port Lake in 2017 with multibeam and sidescan Superior Washington 43°24'N sonars, and interpreted existing adjacent Study Area Lake coastal lidar data (Figure 2.1). The area off Grafton Huron Lake

10 30 Manitowoc was selected with guidance Mequon 100 Ontario Lake 43°12'N from NOAA’s Office of National Marine Michigan Sanctuaries (ONMS), the Wisconsin Historical Society (WHS), Wisconsin 88°W 87°48'W 87°36'W 87°24'W 87°12'W 87°W Figure 2.1 Location of lakebed surveys and mapped areas off Manitowoc, WI (Phase Sea Grant and Wisconsin Coastal Zone I) and Sheboygan, WI (Phase II).

Ecological Assessment of Wisconsin - Lake Michigan 7 Lakebed

Management Program. The area includes important reefs and submerged cultural resources (Goodyear et al. 1982, Coberly and Horrall 1980, NOAA ONMS 2016) but very little lakebed information. Previous lakebed information in the area were limited to nautical charts developed from bathymetric soundings collected prior 1950, broad-scale substrate maps derived from extrapolating shoreline material offshore (GLAHF 2018) and anecdotal observations (Janssen et al. 2005).

A second phase of surveying was completed off Sheboygan, Wisconsin in 2018. Data and maps for this second phase are still being processed and expected to be completed in late 2019 (Figure 2.1). The Sheboygan survey location was chosen based on a spatial mapping prioritization by Kendall et al. (2018). This chapter focuses only on the Manitowoc area (Phase I).

The 2017 Manitowoc survey was conducted by NOAA’s National Centers for Coastal Ocean Science (NCCOS), in collaboration with the Great Lakes Environmental Research Laboratory (GLERL) and ONMS (OCS survey W00440). The survey provided 100% sidescan coverage and “skunk stripe” (i.e., partial) multibeam coverage across 53.9 km2 (23 mi2). The survey was positioned off Manitowoc in water depths from 5 to 34 m (15 to 111 ft), and was immediately offshore of lidar data collected by the US Army Corps of Engineers (USACE) in 2012 (Figure 2.2). Chapter 2 Chapter 0 1 2 3 Kilometers ¯ Two 10 m 0 0.75 1.5 Miles Rivers

44°8'

10 m

30 m 44°6' Manitowoc

44°4'

10 m

Contours (m) 44°2' Interpreted imagery Sidescan LiDAR 30 m

-87°40' -87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.2. Map of uninterpreted imagery used to classify the lakebed off Manitowoc, Wisconsin. Lidar data were collected in 2012 by the USACE National Coastal Mapping Program. Sidescan data were collected in 2017 by NCCOS, GLERL and ONMS, and is part of OCS survey W00440.

8 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

Sidescan and multibeam data were collected off the 50 foot R/VStorm (R5002; operated by GLERL) from June 3-13, 2017. The lakebed was ensonified using a towed Klein 3000 sidescan sonar system (100 kHz and 500 kHz) and a Kongsberg EM 2040C multibeam echosounder (200 kHz to 400 kHz). These instruments were loaned for the survey by the Thunder Bay National Marine Sanctuary and by Kongsberg, Underwater Technology, Inc., respectively. Survey outputs were mosaicked images of sidescan backscatter (0.25 x 0.25 m resolution), multibeam backscatter (1 x 1 m) and multibeam bathymetry (1 x 1 m). Derived surfaces of bathymetric slope (1 x 1 m) and variance (1 x 1 m) were also developed to support lakebed classifications. Detailed survey acquisition and data processing methods used to develop backscatter and bathymetry surfaces, including spatial positioning, temperature-dependent corrections for the speed of sound in water and spatial calibrations, are provided in the Office of Coastal Survey (OCS) Descriptive Summary Report W00440. These data have been submitted to the Pacific Hydrographic Branch and National Centers for Environmental Information (NCEI) for archival and public dissemination. All data is expected to be available in late 2019 at https://www.nodc.noaa. gov/access/. A subsequent mission from August 20-29, 2017 and off a 26 foot SeaArk (R2604; operated by GLERL) was used to groundtruth sonar observations and test the accuracy of derived lakebed maps with in situ imagery from drop cameras.

2.2.3 Lidar Bathymetry Interpretation Coastal lidar surveys along the entire Lake Michigan shoreline were completed by the Joint Airborne Lidar Chapter 2 Chapter Bathymetry Technical Center of Expertise (JALBTCX) in 2012. These data supersede lidar collected by JALBTCX in roughly the same area in 2008. We used a 29 km2 (11.2 mi2) subset of the coastal lidar survey adjacent to the 2017 Manitowoc sonar survey to interpret the lakebed. A JALBTCX collection followed the coastline and extended from onshore to a depth of approximately 10 m (33 ft). The RIEGL VQ-480 airborne lidar system was used for acquisition of underwater elevation data and data were provided through the NOAA Data Access Viewer (https://coast.noaa.gov/dataviewer). Survey data acquisition methods and processing steps for spatially-explicit point clouds are detailed in metadata for the dataset at the NOAA Data Access Viewer. We post-processed LAS (LASer) File Format point clouds to derive 1 x 1 m resolution surfaces of lakebed elevation using Global Mapper (v. 18) and the Lidar Module, and then derived bathymetric slope (1 x 1 m) and bathymetric variance (1 x 1 m) using a 3 m x 3 m kernel in ArcGIS (ESRI, v. 10.5). A narrow band along shore extending 100 to 400 m off the shoreline was not classified because of widespread lidar data gaps and hazardous ground validation (GV) environments.

2.2.4 Lakebed Classification Sonar backscatter and bathymetry were classified based upon the principle that relative changes in depth, and the intensity of backscatter are affected by lakebed characteristics, including sediment grain size, bottom roughness, geomorphology, and benthic organisms (particularly hard-shelled mussels). We used this principle to classify lakebed features on the basis of geomorphology, substrate composition, benthic biology and anthropogenic disturbance. Each of these four components is adopted from the Coastal and Marine Ecological Classification Standard (CMECS; FGDC 2012) and is a stand-alone construct that can be interpreted on its own or in combination with other components. Within each component the lakebed is classified into distinct units based on major geomorphic, structural, material or biological characteristics of the lakebed. Table 2.2 defines the classified components and all corresponding lakebed units.

We further classified the lakebed using distinct combinations of lakebed units across different components, and which aligned with previous Lake Michigan classification systems (e.g., Edsall et al. 1995a, Waples et al. 2005, Creque et al. 2010) to derive map units classifying dominant substrates, biotopes and mussel coverage. Spatial patchiness was defined for these derived units as: none or minimal (0-4%), scattered (5-29%), patchy (30-79%), or continuous (80-100%), and align with thresholds applied to substrate classes in CMECS. Across substrate units, we used standard sediment grain size definitions provided by Wentworth (1922; Table 2.3) and grain size mixtures used by Folk (1954). Figure 2.3 provides images showing differences among geoforms and dominant substrates.

Ecological Assessment of Wisconsin - Lake Michigan 9 Lakebed

Table 2.2. List of components and units used to classify the lakebed off Manitowoc, Wisconsin. Biological and Geomorphological Substrate Composition Derived Map Classes Anthropogenic Geoform Substrate Origin Mussel coverage Dominant substrate Flat Geologic substrate Continuous (80-100%) Continuous (80-100%) hard clay Coarse gravel field Anthropogenic substrate Patchy (30-79%) Patchy (30-79%) hard clay Glacial-lacustrine deposit Unknown Scattered (5-29%) Scattered (5-29%) hard clay Sediment wave field None or minimal (0-4%) Continuous (80-100%) cobbles Dredge deposit Substrate Class Unknown Patchy (30-79%) cobbles Ridge Unconsolidated mineral substrate Scattered (5-29%) cobbles Pipeline area Anthropogenic rock Human disturbance Continuous (80-100%) pebbles Unknown Unknown Filled Patchy (30-79%) pebbles Scarred Scattered (5-29%) pebbles Substrate Sublass Trawled Continuous (80-100%) fine sediment Coarse unconsolidated substrate None Unknown Fine unconsolidated substrate Anthropogenic rock Biotope Unknown Hard clay Chapter 2 Chapter Cobbley mussel bed Substrate Group Fine sediment with mussel beds Gravel Fine sediment without mussel beds Gravel mixes Fine sediment with waves Gravelly Mud (silt and clay) Other fine unconsolidated substrate Unknown

Table 2.3. Sediment grain size descriptors. Descriptor Grain Size (mm) Class Sizes (phi) Boulder 256 to < 4,096 -8 to < -12 Cobble 64 to < 256 -6 to < -8 Pebble 4 to < 64 -1 to < -6 Granule 2 to < 4 -1 to < -2 Gravel 2 to < 4,096 -1 to < -1 Fine sediment <2 > -1 Sand 0.0625 to < 2 4 to < -1 Mud < 0.0625 > 4 Silt 0.004 to < 0.0625 > 4 to 8 Clay < 0.004 > 8

10 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

A

B Chapter 2 Chapter

C

Figure 2.3. In situ images of the lakebed showing classified (A) geoforms, (B) dominant substrates, (C) and mussel coverages. Dominant substrates (B) are organized as a matrix defined by substrate from left to right, and spatial coverage top to bottom. Photo credit: NOAA NOS/ NCCOS.

Ecological Assessment of Wisconsin - Lake Michigan 11 Lakebed

2.2.5 Lakebed Maps Homogenous lakebed features were delineated by drawing boundaries around contiguous areas with similar values and similar spatial patterns of remotely-sensed backscatter, bathymetry, slope, and bathymetric variance. Boundaries were drawn and digitized on screen with a computer mouse at a spatial scale of 1:2000, a stream tolerance of 1 m (minimum distance between vertices on a line), and a minimum mapping unit (MMU) of 400 m2. These digitization parameters were chosen to balance the level of spatial granularity with the amount of time needed for map development. All digitization was performed in ArcGIS (ESRI, v. 10.5).

To classify digitized lakebed features, we collected groundtruth data at 166 sites and relate in situ lakebed information with remotely-sensed patterns of backscatter, bathymetry, slope, and bathymetric variance. For instance, we used in situ measurements to define areas with uniformly low backscatter and low bathymetric variance as continuous fine sediment, and areas with relatively high backscatter and moderate bathymetric variance as continuous cobbles. GV sites were positioned purposefully in features across a range of depths and geographic regions, and along bathymetry and backscatter gradients (Figure 2.4) to acquire a wide range of remotely-sensed patterns and to define map class thresholds.

Chapter 2 Chapter 0 1 2 3 Kilometers ¯ Two 10 m 0 0.75 1.5 Miles Rivers ! ! ! ! ! !!! ! ! ! ! 44°8' !! ! ! ! !!!! !! ! ! ! ! ! !!!!!! 10 m ! ! ! ! ! ! !! ! !!!!!!!!!! !! ! ! !! ! !! ! ! ! ! !! ! ! !! ! ! ! ! ! !! !! ! ! ! ! ! !! ! ! !! ! ! 30 m ! !! ! ! ! 44°6' ! ! !!! !! !!! ! ! ! ! !!!! ! !! ! !! ! ! ! ! ! ! ! ! !! ! !! ! !!! ! !! Manitowoc ! ! ! ! !! !! ! ! ! !! ! ! !! !! ! ! !!! !!! ! ! ! !!! ! !! ! !! ! ! ! ! !!!! !! !! ! !!!!!!!! ! !!!!!! ! !! ! !!!!! ! ! ! ! ! ! !!! !! ! ! 44°4' ! ! ! ! ! ! ! 10 m !!! !! !!!!! ! !!!! ! ! In situ data ! 44°2' ! ! !!! ! ! Ground validation sites ! ! ! !! Accuracy assesment sites 30 m Lakebed map extent

-87°40' -87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.4. Map of 2017 in situ ground validation and accuracy assessment sites for the classified lakebed map.

12 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

In situ data consisted of underwater videos collected at each site with a Seaviewer 6000HD underwater camera. The camera was deployed from the R2604, a 26 foot SeaArk operated by GLERL, with the boat’s position recorded every 1 second (time unit, not geographic unit) using a Trimble GeoXH geographic positioning system. At each site, 1-2 minutes of underwater video were collected. A 30 second subset of the video was selected to represent each site. Typically, the selected video sample started when the lakebed first came into view in the video, but occasionally was delayed if the first few seconds of the lakebed were dramatically different from the remainder of the video. Thirty seconds of video were chosen as the duration of the sample to standardize interpretation effort among sites and align the spatial scale inof situ interpretations to the minimum mapping unit of classified maps. Each video sample represented a 5 to 20 m long lakebed transect depending on camera drift speed. If necessary, the full site video was divided into two or more separate non-overlapping samples to represent two or more dissimilar lakebed habitats. The geographic position of each video sample was determined by the average boat position during the duration of the sample. We estimated camera drift from the boat was typically less than 5 m, and did not exceed 10 m.

Percent coverage of surficial boulders, cobbles, pebbles, hash, sand, silt, hard clay, mussels, fleshy macroalgae, turf algae, macrophytes and man-made objects were measured in each video sample. Substrate and biological cover were estimated independently, because we wanted to separate the underlying substrate from overlaid

benthic colonization. The presence of sediment waves, holes, fractures, burrows, and human disturbance were 2 Chapter also recorded. We differentiated hard clay from unconsolidated fine-grained sediment, because we observed major differences in geomorphology and benthic colonization, which we expected to be important to coastal managers and benthic ecologists. In situ measurements were subsequently used to classify each digitized feature according to substrate and mussel coverage classes defined in Table 2.2.

The definition of geoform classes for each feature required a broader spatial perspective. We used in situ measurements, geographic position, and lakebed characteristics from adjacent features to characterize geoforms.

After geoform, substrate, and mussel coverage classes were determined, we assembled consistent combinations of these attributes into dominant substrate and biotope classes. Biotopes were defined as consistently observed combinations of abiotic features and associated species. The biotic group was further differentiated into mussel coverage categories to provide additional information on invasive mussel coverage.

Geoforms and substrate types were classified across all areas with sidescan and lidar coverage. The information to map these classes was readily identifiable in both datasets and there is a seamless transition where these datasets adjoin. In contrast, mussel coverage and biotope classes were only mapped where sidescan backscatter and multibeam data were available. Mussel colonization could not be detected in lidar bathymetry.

The thematic accuracy of classified biotope, dominant substrate and invasive mussel maps were examined using common mapping error statistics (Card 1982, Congalton and Green 1999). These statistics show differences between expected map categories and observations made at 196 accuracy assessment (AA) sites. AA sites are independent from the 166 GV sites.

AA sites were randomly distributed across the survey area and stratified according to an early draft of biotope types (Figure 2.4). Stratification was used to assign sites into rare regions, which would otherwise not be sampled if a simple random design were used. The full permutation of biotope, substrate and mussel classes was not used to stratify points, because more finely resolved substrate and mussel classes were uncertain at the time ofin situ sampling. While stratification improves sample distribution across stratum categories, it has the undesired effect of introducing bias into the error matrix based on the different sizes of the areas mapped in

Ecological Assessment of Wisconsin - Lake Michigan 13 Lakebed

each classification. To remove bias from stratified sampling, we used the area of each mapped category divided by the total mapped area to assess class error proportional to area (Card 1982, Congalton and Green 1999).

Map accuracy was quantified for biotope, Table 2.4. Summary of accuracy assessment (AA) statistics for lakebed map unit. dominant substrate, and mussel coverage Overall Corrected map classes where sidescan data were Map attribute accuracy accuracy Tau available and for dominant substrate where Derived from sidescan/MBES imagery only lidar data were available. The accuracy of geoform classification was not assessed Biotope 94.9% 97.6% 0.94 because more than in situ measurements Dominant substrate 88.8% 96.7% 0.87 were used in its definition. The accuracies Mussel coverage 76.5% 84.4% 0.69 of mapped biotope, dominant substrate, and mussel coverage classes ranged from Derived from lidar imagery very good to fair (Table 2.4). Biotope and Dominant substrate 79.1% 74.6% 0.76 substrate maps developed with sidescan data were best, whereas mussel coverage and substrate maps derived from lidar imagery were considered fair. Tables 2.5-2.8 show measures of overall accuracy and per-class accuracy from the user’s and producer’s point of view. The final step in the map development process was to correct all lakebed map attribute errors Chapter 2 Chapter identified during the AA process. Consequently, the accuracy of the final map product is greater than accuracy statistics specify.

2.2.6 Digital Lakebed Maps The best way to use and explore classified maps is through geographic information system (GIS) software, such as ArcGIS (ArcMap). Classified maps were created as polygon shapefiles providing areal information across a range of spatial scales. These shapefiles are digital products and can be accessed using GIS software that allows users to zoom in and explore target areas in detail. Many features are too small to see in this report’s figures. The shapefiles presented as maps in this chapter will be archived at NOAA NCEI and there will be freely available for viewing and download.

Table 2.5. The confusion matrix for the biotope map developed from sidescan data. AA sites are listed as columns and corresponding mapped habitats as rows. Diagonal cell values denote the number of correctly classified sites. Off-diagonal cell values denote the number of incorrectly classified sites. AA (i) Cobbley Fine Sed, Fine Sed, User's Outcrops Fine Sed n Mussel Bed Mussel Bed SurfWave -j Accuracy (%) Outcrops 17 2 0 0 0 19 89%

Cobbley Mussel Bed 1 34 1 0 1 37 92%

Fine Sed 0 0 27 0 0 27 100%

Fine Sed, Mussel Bed 0 0 0 8 0 8 100% map(j) Fine Sed, SurfWave 0 0 0 0 7 7 100%

ni- 18 36 28 8 8 98 Producer's Accuracy 94% 94% 96% 100% 88% OA = 94.9% (%)

Te = 0.94

14 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

Table 2.6. The confusion matrix for the dominant substrate map developed from sidescan data. AA sites are listed as columns and corresponding mapped habitats, as rows. Diagonal cell values denote the number of correctly classified sites. Off-diagonal cell values denote the number of incorrectly classified sites. AA (i) Patchy Scattered Patchy Scattered Patchy Scattered Continuous User's n Hard Clay Hard Clay Cobble Cobble Pebble Pebble Sediment -j Accuracy (%) Patchy Hard 14 2 1 1 0 0 0 18 78% Clay Scattered 0 1 0 0 0 0 0 1 100% Hard Clay Patchy 0 0 21 1 0 0 0 22 95% Cobble Scattered 1 0 0 11 0 2 1 15 73% Cobble Patchy 0 0 1 0 1 0 1 3 33%

map(j) Pebble Scattered 0 0 0 0 0 4 0 4 100% Pebble Continuous 0 0 0 0 0 0 35 35 100% 2 Chapter Sediment

ni- 15 3 23 13 1 6 37 98 Producer's 93% 33% 91% 85% 100% 67% 95% OA = 88.8% Accuracy (%)

Te = 0.87

Table 2.7. The confusion matrix for the mussel coverage map developed from sidescan data. AA sites are listed as columns and corresponding mapped habitats, as rows. Diagonal cell values denote the number of correctly classified sites. Off-diagonal cell values denote the number of incorrectly classified sites. AA (i) Continuous Patchy Scattered No Mussels n User's Accuracy (%) Mussels Mussels Mussels -j Continuous Mussels 9 2 3 0 14 64%

Patchy Mussels 2 30 7 4 43 70%

Scattered Mussels 0 1 9 2 12 75%

map(j) No Mussels 0 0 2 27 29 93%

ni- 11 33 21 33 98 Producer's Accuracy 82% 91% 43% 82% OA = 76.5% (%)

Te = 0.69

Ecological Assessment of Wisconsin - Lake Michigan 15 Lakebed

Table 2.8. The confusion matrix for the dominant substrate map developed from lidar data. AA sites are listed as columns and corresponding mapped habitats, as rows. Diagonal cell values denote the number of correctly classified sites. Off-diagonal cell values denote the number of incorrectly classified sites. AA (i) Cont. Patchy Scat. Cont. Patchy Scat. Cont. User's Unknown n Hard Clay Hard Clay Hard Clay Cobbles Cobbles Cobbles Sediment -j Accuracy (%) Continuous 2 0 1 0 0 0 0 0 3 67% Hard Clay Patchy Hard 4 5 1 0 0 0 0 0 10 50% Clay Scattered 0 1 4 0 0 0 0 0 5 80% Hard Clay Continuous 0 0 0 0 0 0 0 0 0 NA Cobbles Patchy 0 0 0 2 32 1 0 0 35 91% Cobbles

map(j) Scattered 0 0 0 0 0 1 0 0 1 100% Cobbles Continuous

Chapter 2 Chapter 0 0 0 1 1 1 9 0 12 75% Sediment Unknown 0 0 0 0 1 0 0 0 1 0%

ni- 6 6 6 3 34 3 9 0 67 Producer's 33% 83% 67% 0% 94% 33% 100% NA OA = 79.1% Accuracy (%)

Te = 0.76

2.3 CURRENT CONDITIONS AND TRENDS 2.3.1 Geomorphology The lakebed geomorphology in the surveyed area was a mixture of flat unconsolidated sediment, coarse gravel fields (in this report gravel refers to any particles larger than sand, 2 mm), glacial-lacustrine hard clay deposits, and several other rarer geoforms (Table 2.9). The majority of the lakebed (69%) was comprised of the flat geoform, which as the name implies has little or no relief. Flats were observed across all surveyed depths and are characterized by a gently sloping mass of loose fine sediment. Flats occurred throughout most of the surveyed area, except for a nearshore 1 km-wide swath south of Manitowoc where it was noticeably absent (Figure 2.5).

Coarse gravel fields comprised almost a Table 2.9. Areal estimates of geoform types in the surveyed area. quarter of the surveyed lakebed (24%). They Geoform Area (km2) % of Map were composed of unsorted unstratified Flat 54.64 68.79% boulders, cobbles and pebbles. Cobbles were by far the most abundant particle size of the Coarse gravel field 18.79 23.66% gravel fraction, although pebbles and boulders Glacial-lacustrine deposit 5.67 7.14% were not uncommon. The majority of coarse Sediment wave field 0.10 0.13% gravel fields were organized in patches larger Ridge 0.08 0.11% than 1 km2 and were enclosed by flats. The Pipeline area 0.06 0.08% largest coarse gravel field was located close to the center of the lakebed survey south of Dredge deposit 0.05 0.06% Two Rivers. This large region covered 8 km2 Unknown 0.03 0.04% (10% of the surveyed lakebed) and extended

16 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

0 1 2 3 Kilometers ¯ Two 10 m 0 0.75 1.5 Miles Rivers

44°8'

10 m

30 m 44°6' Manitowoc Chapter 2 Chapter 44°4'

Geoform Flat Coarse gravel field 10 m Glacial-lacustrine deposit Sediment wave field Suspected dredge deposit 44°2' Ridge Pipeline area

30 m Unknown

-87°40' -87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.5. Map of lakebed geoforms off Manitowoc. continuously from 7-22 m water depth. Close to the center of the map and extending south to the edge of the map, coarse gravel fields were well-mixed with glacial-lacustrine deposits, and were organized as noticeably smaller patches than gravel fields elsewhere.

Glacial-lacustrine deposits covered 7% of the lakebed and were seen in the southern two thirds of the surveyed area. A sharp divide running southeast from shore and extending across the surveyed area divided the region with glacial-lacustrine deposits to the southwest and no deposits observed to the northeast. This divide appears to be in line with the last ice-margin position(s) of the Lake Michigan lobe in the Lake Michigan basin 13,000 years ago (S. Brown, pers. comm.). The dominant substrate of glacial-lacustrine deposits was hard clay. Two distinct hard clay morphologies were evident. The most common morphology were outcrops of hard clay elevated 1-2 m off the lakebed. These outcrops were organized as a set of parallel ridges and swales oriented in a NW-SE bearing. The least common morphology was flat hard clay, similar to hardpan. It was common to see the two morphologies smoothly transition from one to the other, making it difficult to separate each on a map. In both outcrop and flat morphologies, the hard clay surface was uniformly smooth and comprised of a homogenous fine particle matrix. Pebbles or larger particles were not observed mixed in the clay. Occasionally, outcrop formations were fractured and heavily eroded with large blocks of clay broken off the outcrop and smooth narrow channels etched into the outcrop. Boulders and cobbles were common among swales, and infrequently were perched atop ridges.

Ecological Assessment of Wisconsin - Lake Michigan 17 Lakebed

Sediment wave fields made up a small percentage of the lakebed (0.13%). These geoforms were readily seen in sidescan backscatter mosaics and GV imagery as wave sets with wave periods between 20 and 100 cm, and wave heights between 5 and 20 cm. Waves were commonly stratified by particle size fractions, with pebbles in troughs and finer sand on wave crests. Very fine grained sediment such as silt and mud were not observed among sediment waves. Wave fields were commonly distributed as isolated elongated tendrils within larger featureless flat regions or as small patches along the perimeter of coarse gravel fields. Sediment wave fields were not detected deeper than 20 m even though unconsolidated sediment was common.

A single long winding ridge 2 km in length was detected close to the southern extent of the map. The ridge was 1 m higher than the surrounding lakebed and was comprised of mostly cobbles. It extended from shore at an oblique angle and the ridge width expanded as depth increased. No other ridges of similar size or shape occurred in the surveyed area. Given its shape, geographic position and composition, the ridge could be a glacial esker (i.e., a long ridge of gravel and other sediment deposited by meltwater from a retreating or ice sheet).

Several pipeline areas extended southeast from the southern shore of Manitowoc (Figure 2.6). These isolated areas were heavily disturbed and were characterized by approximately 10 m wide depressions in fine sediment

Chapter 2 Chapter and clay. A thin elevated ridge ran parallel to approximately half of the depression length, which was likely made

0 0.45 0.9 1.35 Kilometers ¯ 10 Two Rivers 0 0.25 0.5 Miles 5 Wisconsin

Manitowoc

44°6'

Manitowoc

5 10 5

5 5 5 5

5

10

Man-made geoforms 44°4' Suspected dredge deposit 5 Pipeline area 15 Extent of lakebed map Contours (m)

-87°38' -87°36' Figure 2.6. Map of suspected dredge deposits and pipeline areas in the surveyed area. 10 m

18 Ecological Assessment of Wisconsin - Lake Michigan Lakebed up of excavated material taken from the depressions. Substrate within pipeline areas was not characterized because insufficient GV data were collected in the areas. All pipeline areas were well-marked as pipelines on nautical charts, however their precise position on charts was offset by several meters compared to our survey (OCS W00440).

Suspected dredge deposits were rare, yet very conspicuous features in remotely sensed imagery. Deposits were made up of cobbles and occasionally boulders arranged in consistently sized and shaped circles approximately 20 m in diameter. The insides of circles were commonly fine unconsolidated sediment, but rarely included cobbles and boulders as well. There were approximately 50 suspected dredge deposits clustered 3 km east of Manitowoc in water 10 to 15 m deep, and dispersed over a 2 km2 area (Figure 2.6).

2.3.2 Substrate A wide variety of substrates were observed in the study area (Figure 2.7). Substrate size fractions ranged from fine grained clays to large boulders. Bedrock was not observed. The most abundant dominant substrate type was continuous fine sediment, made up of unconsolidated clay, silt and sand, and was observed almost exclusively within flats (Table 2.10). The rest of the lakebed was made up of mostly of patchy cobbles (21%) and patchy hard clay (5%). Chapter 2 Chapter

0 1 2 3 Kilometers ¯ Two 10 m 0 0.75 1.5 Miles Rivers

44°8'N

10 m

30 m 44°6'N Manitowoc

44°4'N

Dominant substrate

10 m Continuous hard clay Continuous pebbles Patchy hard clay Patchy pebbles Scattered hard clay Scattered pebbles 44°2'N Continuous cobbles Continuous fine sediment Patchy cobbles Unknown Scattered cobbles 30 m

87°40'W 87°38'W 87°36'W 87°34'W 87°32'W 87°30'W Figure 2.7. Map of lakebed dominant substrate off Manitowoc.

Ecological Assessment of Wisconsin - Lake Michigan 19 Lakebed

Substrate composition was strongly associated with Table 2.10. Areal estimates of dominant substrates in the survey area. geoforms. Most geoforms were made up of one Dominant Substrate Area (km2) % of Map or two substrate types. For instance, all flats were Continuous fine sediment 54.64 68.79% dominated by continuous fine sediments, and 89% Continuous cobbles 0.22 0.28% of coarse gravel fields were dominated by patchy Patchy cobbles 16.71 21.03% cobbles (Figure 2.8). The overall spatial distribution Scattered cobbles 1.61 2.03% of substrate types is similar to the distribution of Continuous pebbles 0.35 0.44% geoforms, but includes greater spatial heterogeneity (Figure 2.7). Patchy pebbles 0.08 0.10% Scattered pebbles 0.05 0.06% Continuous hard clay 0.12 0.16% Patchy hard clay 4.15 5.22% Scattered hard clay 1.41 1.77% Unknown 0.09 0.11% Chapter 2 Chapter

Figure 2.8. Areal distribution of dominant substrate types within each geoform of the Manitowoc map. Proportion of area relative to area within each geoform.

2.3.3 Invasive Mussels Invasive mussels were common across a third (34%) Table 2.11. Areal estimates of dominant substrates in the survey area. of the area surveyed by sidescan and multibeam Mussel Coverage Area (km2) % of Map sonars (Figure 2.9, Table 2.11). Mussels were not Continuous (80-100%) 8.56 15.85% discernible in remotely sensed lidar data, so mussel Patchy (30-79%) 8.47 15.69% coverage was not mapped over the nearshore lidar Scattered (5-29%) 1.23 2.28% survey area. Observed mussels were probably all quagga mussels (Dreissena rostriformis bugensis), None or minimal (0-4%) 35.63 66.01% given their dominance over zebra mussels (Dreissena Unknown 0.09 0.16% polymorpha) documented by Rowe et al. (2015).

The overall distribution of mussel coverage is similar to the combined distributions of patchy hard clay and patchy cobbles, except for an area of patchy mussel coverage over continuous fine sediment in the deepest region of the survey. Across the majority of fine sediments, mussel coverage rarely exceeded 5% and only

20 Ecological Assessment of Wisconsin - Lake Michigan Lakebed ¯ 0 1 2 3 Kilometers Two 0 0.55 1.1 Miles Rivers

10 m

44°8'

10 m

30 m 44°6' Chapter 2 Chapter

44°4' 10 m Mussel coverage Continuous (80-100%) Patchy (30-79%) Scattered (5-29%) None or minimal (0-4%) Unknown

-87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.9. Map of mussel coverage in the surveyed area.

appeared as isolated druses or on erratic boulders and cobbles. However, among fine sediments deeper than 22 m (75 ft), mussel coverage was typically 30% to 70%, and mussels were organized as dense patchy mussel beds. Mussels among mussel beds rested atop and embedded within the top layers of sediment as opposed to attached to cobbles or boulders.

Underwater videos showed that attached mussels covered almost all exposed surfaces of boulders and cobbles and in deeper water were commonly dense enough to completely cover the underlying substrate. Mussels were markedly absent from hard Dense mussel beds in fine sediment on lakebed, Lake Michigan. Credit: clay substrate. NOAA NOS/NCCOS.

Ecological Assessment of Wisconsin - Lake Michigan 21 Lakebed

2.3.4 Macroalgae Maps of macroalgae coverage were not created because macroalgae was not discernible in remotely sensed data. Instead, general patterns are characterized using in situ video data (Figure 2.10). Almost all observed fleshy macroalgae was likely Cladophora based on its morphology. Cladophora has been considered a nuisance algae, because it can detach from the lakebed and wash up onshore where it Cladophora on lakebed, Lake Michigan. Credit: NOAA NOS/NCCOS. is unattractive (Bootsma et al. 2005). Detached Cladophora was present at 7% (27 of 362) of sites all shallower than 13 m (42 ft). In its detached state Cladophora rolled and floated in patchy drifts close to the lakebed, and was common in fine sediment wave troughs. In addition, dense drifts up to 0.5 m deep and several meters across were observed along some hard clay outcrop edges. Chapter 2 Chapter

0 1 2 3 Kilometers ¯ Two 10 m 0 0.75 1.5 Miles Rivers ! ! (! (!( ( (! ! ! !! !! ! 44°8'N ! ! ! (! ! ! !!! !! ! ! ! ! ! ! ! !(!!!! 10 m !! !! !! ! !! ! !(! !( ! ! !!!(! !!! ! ( ! !! ! ! ! ! (! ! ! (! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! (! ! ! ! 30 m ! ! ! ! ! 44°6'N !!!! ! ! ! ( !! !!! ! ! ! !!!! ! (! !!! ! ! ! ! ! ! ! ! ! (( ! ! ! !! !! ! ! Manitowoc !( ! ! !! ! !!(! ! ! !(! !! (! !! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !!! ! !! ! ! !!! !!! !! ! !! !!! !! ! ! !!!! ! !!(! !! !!!!(! ! 44°4'N ! ! !! ! ! ! ! ! ! 10 m !!! ! !!! Macroalgae coverage (!! !!! !! ! !! ! 0 - 4 % ! 44°2'N (! ! ! ! ! 5 - 79 % ! ! ! 80 - 100 % ! ( 30 m Algae drift

87°40'W 87°38'W 87°36'W 87°34'W 87°32'W 87°30'W Figure 2.10. Map of macroalgae coverage among ground validation and accuracy assessment sites. Black circles identify sites were algal drifts were observed.

22 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

Attached fleshy macroalgae was present at 91% (330 of 362) of GV and AA sites and regularly colonized all substrate types, except hard clay. Coverage was generally highest at sites between 3 m and 12 m (10 ft and 40 ft) deep and in a region extending offshore of Manitowoc to the southern edge of the map (Figure 2.10). Deeper than 22 m (75 ft), macroalgae coverage was consistently below 10% and macroalgae was not observed at the two sites deeper than 29 m (95 ft).

2.3.5 Human Disturbance Three forms of human disturbance were observed on the lakebed. Suspected dredge deposits and pipeline areas were described in the geoform section of this chapter, since the disturbance was sufficient to extensively modify the physical structure and composition of the lakebed. Trawl marks, the third form of human disturbance, idid not appear to affect the composition of the lakebed.

Trawl marks were ubiquitous in depths below 28 m and covered an area of 1.5 km2 or approximately 3% of the mapped area (Figure 2.11). They were clearly seen in sidescan backscatter in areas characterized by unconsolidated fine sediment with patchy mussel beds. Most trawl marks were aligned parallel to the 30 m contour, and most marks occurred as pairs with parallel lines 50 to 54 m apart. In underwater video, trawl marks appeared as long continuous furrows approximately 10 cm deep in mussel beds and in fine unconsolidated sediment. Chapter 2 Chapter

0 1 2 3 Kilometers

Two 10 m ¯ 0 0.75 1.5 Miles Rivers

44°8'

100 500 m

Pipeline areas 10 m

30 m 44°6' Manitowoc

Trawl scars 44°4'

Human disturbance Suspected 10 m Contours (m) dredge Suspected dredge deposits

deposits Pipeline areas 44°2' Trawled None 100 500 m 100 500 m 30 m Unknown

-87°40' -87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.11. Map showing locations of suspected dredge fill, pipeline scars and trawl marks. Insets show underlying sidescan backscatter for suspected dredge deposits and trawl scars, and lidar bathymetric variance for pipeline areas observed.

Ecological Assessment of Wisconsin - Lake Michigan 23 Lakebed

2.3.6 Biotope By design, biotopes were associated with consistent geoform, substrate and mussel coverage combinations. Consequently, the distribution of biotopes was similar to the distributions of other mapped lakebed classes and were mapped only in areas with sidescan imagery (Figure 2.12).

The most common biotope was fine Table 2.12. Distribution of mapped biotope coverage in the survey area sediment without mussel beds (Table Biotope Area (km2) % of Map 2.12). We did not call it uncolonized fine sediment, because macroalgae and other Fine sediment without mussel beds 35.52 65.92% living organisms were commonly present, Cobbley mussel bed 12.07 22.40% but could not be discerned from remote Fine sediment with mussel beds 3.24 6.02% sensing data. As the name implies, fine Hard clay 2.95 5.47% sediment without mussel beds was Fine Sediment with waves 0.10 0.19% made up of continuous fine sediment flats, where invasive mussel beds were not observed. In addition, boulders, cobbles and fish, including round gobies, were exceedingly rare. In contrast, sediment disturbance (likely bioturbation) and macroalgae were common. Although mussel beds were absent, mussels were found as sporadic and isolated druses or very 2 Chapter 2 Chapter small beds covering less than 10 m . ¯ 0 1 2 3 Kilometers Two 0 0.55 1.1 Miles Rivers

10 m

44°8'

10 m

30 m 44°6'

Biotope 44°4' 10 m Hard clay Cobbley mussel bed Fine sediment with mussel beds Fine Sediment with waves Fine sediment without mussel beds Unknown

-87°38' -87°36' -87°34' -87°32' -87°30' Figure 2.12. Map showing biotopes in the surveyed area.

24 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

Cobbley mussel beds covered approximately 22% of the lakebed map and were particularly concentrated several kilometers south and south east of Two Rivers. Among cobbley mussel beds, invasive mussels were attached to all cobbles and boulders, and formed beds on unconsolidated substrates in between cobbles. Invasive mussel colonization was typically dense enough to obscure most of the underlying substrate. In addition to invasive mussels, macroalgae and round gobies were common among cobbley mussel beds. Of the rare large-bodied fish, we observed off Manitowoc, Cobbley mussel beds on lakebed, Lake Michigan. Credit: NOAA NOS/ such as bloater and trout, most were seen on cobbley NCCOS. mussel beds.

Fine sediment with mussel beds made up 6% of the mapped area, and it was all concentrated in deeper water. Fine sediment with mussel beds made up 94% of the lakebed map deeper than 25 m (82 ft) and 100% of the lakebed mapped deeper than 28 m (92 ft). In this biotope, mussels were organized as dense patchy mussel

beds resting atop and embedded in fine sediment. Mussel bed patch density increased from 25 m to 28 m, 2 Chapter and deeper than 28 m patches covered from 50% to 80% of the lakebed. Macroalgae and round gobies were not seen in this biotope. The abundance of trawl marks in this biotope suggests the presence of fish. There is an ongoing effort carried out in partnership between the Wisconsin Department of Natural Resources (DNR), Wisconsin Sea Grant and commercial fishermen to trawl for lake whitefish in this area (T. Seilheimer, pers. comm.).

Hard clay made up roughly 3% of the mapped lakebed and for the most part was uncolonized by macroalgae, invasive mussels or other benthic invertebrates. Rarely hard clay features were colonized by a thin veneer of turf algae. Round gobies were commonly seen on hard clay, but other fish were not. Occasionally, deep drifts of detached macroalgae were observed along the edges of hard clay features.

The fine sediment with waves biotope is equivalent to the sediment wave field geoform. Fish, invasive mussels, attached macroalgae, and bioturbation were seldom seen among waves, but unattached algae was commonly observed in wave troughs. When mussels Loose rolling algae in troughs of sediment waves on lakebed, Lake were detected on fine sediment with waves, they Michigan. Credit: NOAA NOS/NCCOS. occurred attached to rare scattered cobbles.

2.4 DISCUSSION We interpreted lakebed data from an existing lidar survey and a new hydrographic sonar survey to characterize 3% of the study area’s lakebed. Resulting maps provide the most detailed information on geomorphological patterns, substrates and habitats available in the interpreted area east of Manitowoc and south of Two Rivers. Taken together the lakebed maps show new information defining resources, opportunities, impacts, and hazards on the lakebed.

Ecological Assessment of Wisconsin - Lake Michigan 25 Lakebed

2.4.1 Rocky Substrate A large extent of the lakebed within the Great Lakes is made up of large homogenous regions of soft, sandy substrate, yet much of the study area including the mapped area is recognized as a rare location within the Great Lakes with rocky substrate (Mozley and Howmiller 1977, Janssen et al. 2005). Unfortunately, detailed information on the extent, composition, and structural heterogeneity of most of these rocky areas is lacking. The new lakebed maps in this chapter document the extent, substrate composition and biological colonization of these rocky areas in the study area.

Approximately a quarter of the mapped lakebed was dominated by cobble substrate. Knowing the location of cobbles and other rocky habitats is critical to managing fish such as lake trout and yellow perch, which prefer spawning on rocky substrate (Janssen and Luebke 2004), and where to focus research to inform fisheries management.

Previous research by Coberly and Horrall (1980) and Goodyear et al. (1982) identified important habitats off Manitowoc, but employed older technologies and anecdotal reports. Consequently, much of what was known of important habitats lacked detail describing substrate composition and geographic accuracy. For instance, Coberly and Horrall (1980) identified lake trout spawning habitat off Manitowoc as a generalized areaof

Chapter 2 Chapter “honeycombed rock reef”. The new lakebed maps presented in this chapter which made use of more modern sonar echosounders, precisely show the position of this reef, and characterize its size, shape and substrate composition. In addition, the new maps identify the impact of invasive mussels and human disturbance on this historical spawning and nursery ground.

Understanding the location of soft, sandy substrate is also important. Knowing the distribution of sand and other unconsolidated habitats can support beach management, and reduce impacts from coastal development. Soft, sandy substrate is also important to the distribution of species which use softbottom substrates as habitat, such as the invasive (Nalepa et al. 2009).

2.4.2 No Bedrock Detected The proportions of fine sediment, cobbles and clay in new maps are similar to those identified by Edsall et al. (1995a, 1995b), Waples et al. (2005), and Creque et al. (2010). These previous studies used similar mapping techniques and although they are not within the study area, help provide a basin-wide geographic context and corroborate findings within the study area. One of the significant differences between the lakebed maps presented here and previous studies is the lack of bedrock observations in new maps. Edsall et al. (1995b) describe a major habitat type referred to as “bedrock and rubble” several kilometers to the north of our survey area off Algoma, WI, and Waples et al. (2005) detected exposed bedrock to the south of the study area. Hard clay outcrop, Lake Michigan. Credit: NOAA NOS/NCCOS.

26 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

We are fairly confident bedrock is not in the study area, because it was one of the substrate types we expected and explicitly searched for. We also have not found any explicit identification of bedrock in previous research, including characterization of important habitats by Coberly and Horrall (1980) and Goodyear et al. (1982). Out of 362 collected lakebed videos we found no evidence of exposed bedrock. Initially we believed outcrops in the mapped area were made of bedrock, but determined they were hard clay with assistance from Jeffrey Scott Houghton and John Janssen from the University of Wisconsin. They manually collected outcrop substrate samples, to help determine outcrop substrate comprised hard clay. The hard clay outcrops certainly looked like bedrock underwater.

It is possible bedrock occurred in the surveyed area and we did not detect it because it was obscured by invasive mussels and fleshy macroalgae. A substantial portion of the nearshore lakebed was heavily colonized, and mussels and algae obscured much of the underlying substrate. These areas were classified by extrapolating in situ observations from nearby areas where underlying substrate could be seen, and from contacting the lakebed with our cameras to assess induration and consolidation. These areas could have included obscured bedrock, but we did not see any evidence. In the future, more intrusive in situ sampling methods, such as scraping by SCUBA divers, could improve substrate identification under heavy benthic colonization.

2.4.3 Suspected Dredge Deposits 2 Chapter One of the most interesting findings in the surveyed area, where observations of numerous circular rocky features on the lakebed. We defined these as dredge deposits, but their origin remains unconfirmed. Many characteristics of these features suggest they were man-made and their shape, size and spatial distribution are similar to dredge deposits in other locations (Tauber 2009). All suspected dredge deposit features were clustered in a 4 km2 area 3 km east of Manitowoc harbor, and were found nowhere else. They were consistently circular arrangements of cobbles with diameters of 18-22 m. We asked local maritime archaeologists, geologists, ecologists and the USACE what they thought these features were and there wasn’t a consensus. Other possibilities included seep sites, debris from nearby manufacturing plants, and stone ballast from early sailing vessels. If these deposits are man-made, it’s possible they have archaeological significance.

2.4.4 New Interpretations of Lidar Data Bathymetry and sidescan data have been used extensively to map lakebed character in discrete areas of Lake Michigan outside the study area (e.g., Edsall 1995a, 1995b, Waples et al. 2005). In contrast, there are very few examples of lidar used for lakebed characterizations in the Great Lakes (e.g., Kerfoot et al. 2014), even though it has been successfully used for benthic classification in marine environments (e.g., Costa et al. 2009). The vast extent of coastal lidar information available in the study area yet not interpreted is an untapped trove of potential information for lakebed mapping. Our work shows that lidar can be used to develop accurate substrate maps of nearshore areas. If hyperspectral and/or lidar reflectance information are collected and interpreted alongside future lidar surveys as planned, we expect that the accuracy of substrate maps will improve and accurate maps of invasive mussel coverage will be possible. Sequential lidar data also offers the opportunity to see how the lakebed changes over time, which could be quite valuable to understanding sediment movement, and impacts of human disturbance and .

2.4.5 Lakebed Maps Support Submerged Cultural Resource Management The new lakebed character maps were focused on understanding geomorphology, lakebed substrates and habitats, however, they are useful to the management of submerged cultural resources as well. In the course of collecting sidescan and multibeam data we identified several submerged cultural artifacts andlakebed features with unnatural shapes. Corresponding imagery and coordinates were sent to and investigated by the Wisconsin Historical Society in 2018 (Zant et al. unpublished).

Ecological Assessment of Wisconsin - Lake Michigan 27 Lakebed

In addition to detecting submerged cultural resources, lakebed surveys provide information on geology and lakebed substrate which are important factors affecting site formation and survival of archaeological remains (Muckelroy 1978). The new maps provide valuable information to predict forces acting upon cultural resources when they were initially deposited on the lakebed, and subsequent forces from burial, wave action, chemical reactions, mussel colonization and sediment movement. A better understanding of these factors can maximize the effectiveness of archaeological interpretation, so that maritime archaeologists can better preserve and protect sites, and inform conservators so that they may better stabilize artifacts.

2.5 REFERENCES Bootsma, H.A., E.B. Young, and J.A. Berges. 2005. Temporal and spatial patterns of Cladophora biomass and nutrient stoichiometry in Lake Michigan. pp. 81-88. In: Cladophora research and management in the Great Lakes. Workshop Proceedings at Great Lakes WATER Institute, University of Wisconsin-Milwaukee. Great Lakes WATER Institute Special Report No. 2005-01. 211 pp.

Brown, S.E. Illinois State Geological Survey. Champaign, IL. Personal communication.

Card, D.H. 1982. Using known map categorical marginal frequencies to improve estimates of thematic map Chapter 2 Chapter accuracy. Photogrammetric Engineering and Remote Sensing 48: 431-439.

Coberly, C.E., and R.M. Horrall. 1980. Fish Spawning Grounds in Wisconsin Waters of the Great Lakes. University of Wisconsin, Marine Studies Center. Madison, WI. 49 pp.

Congalton, R.G., and K. Green. 1999. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC/Lewis Press. Boca Raton, FL. 137 pp.

Costa, B.M., T.A. Battista, and S.J. Pittman. 2009. Comparative evaluation of airborne lidar and ship-based multibeam sonar bathymetry and intensity for mapping coral reef ecosystems. Remote Sensing of Environment (113): 1082-1100. doi: https://doi.org/10.1016/j.rse.2009.01.015

Creque, S.M., K.M. Stainbrook, D.C. Glover, S.J. Czesny, and J.M. Dettmers. 2010. Mapping Bottom Substrate in Illinois Waters of Lake Michigan: Linking Substrate and Biology. Journal of Great Lakes Research 36(4): 780-789. doi: https://doi.org/10.1016/j.jglr.2010.08.010

Edsall, T.A. and G.W. Kennedy. 1995a. Availability of lake trout reproductive habitat in Lake Michigan. Journal of Great Lakes Research 21: 290-301. doi: https://doi.org/10.1016/S0380-1330(95)71103-0

Edsall, T.A., M.E. Holey, B.A. Manny, and G.W. Kennedy. 1995b. An evaluation of lake trout reproductive habitat on Clay Banks Reef, northwestern Lake Michigan. Journal of Great Lakes Research 21(Suppl. 1): 418-432. doi: https://doi.org/10.1016/S0380-1330(95)71114-5

FGDC. 2012. Coastal and Marine Ecological Classification Standard. FGDC-STD-018-2012. Federal Geographic Data Committee. Reston, VA. Online: https://www.fgdc.gov/standards/projects/cmecs-folder/CMECS_ Version_06-2012_FINAL.pdf (Accessed 30 April 2019)

Folk, R.L. 1954. The Distinction between Grain Size and Mineral Composition in Sedimentary-Rock Nomenclature. The Journal of Geology 62: 344-359. doi: https://doi.org/10.1086/626171

28 Ecological Assessment of Wisconsin - Lake Michigan Lakebed

Fucciolo, C.S. 1993. Littoral Zone Habitat Classification and Mapping of Illinois Lake Michigan Coastal Areas; Bathymetry and Distribution of Bottom Materials. Illinois Geological Survey Publication OFS 1993-7. Illinois State Geological Survey, Department of Natural Resources. 166 pp.

GLAHF. 2018. Great Lakes Aquatic Habitat Framework. University of Michigan, Institute for Fisheries Research. Ann Arbor, MI. Online: https://www.glahf.org/ (Accessed 30 April 2019)

Goodyear, C.S., T.A. Edsall, K.M. Ormsby-Dempsey, G.D. Moss, and P.E Polanski. 1982. Atlas of the spawning and nursery areas of Great Lakes fishes. Volume four: Lake Michigan. U.S. Fish and Wildlife Service, Washington, DC, FWS/OBS-82-52. 201 pp.

Janssen, J. University of Wisconsin - Milwaukee. Milwaukee, WI. Personal communication.

Janssen, J., and M. Luebke. 2004. Preference for rocky habitat by young-of-the-year yellow perch and alewives. Journal of Great Lakes Research 30: 93-99. doi: https://doi.org/10.1016/S0380-1330(04)70332-9

Janssen, J., M.B. Berg, and S.J. Lozano. 2005. Submerged terra incognita: Lake Michigan’s abundant but

unknown rocky zones. pp. 113-139. In: T. Edsall and M. Munawar (eds.), State of Lake Michigan: Ecology, 2 Chapter Health and Management. Michigan State University Press. 641 pp.

Karatayev, A.Y., and L.E. Burlakova. 2017. Lake Erie and Lake Michigan Benthos: Cooperative Science and Monitoring Initiative. Final Report. USGS-GLRI G14AC00263. Great Lakes Center, SUNY Buffalo State. Buffalo, NY. 123 pp.

Karatayev, A.Y., K. Mehler, L.E. Burlakova, E.K. Hinchey, and G.J. Warren. 2018. Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales. Journal of Great Lakes Research 44(4): 629-638. doi: https://doi.org/10.1016/j.jglr.2018.05.003

Kendall, M.S., K. Buja, and C. Menza. 2018. Priorities for Lakebed Mapping in the Proposed Wisconsin-Lake Michigan National Marine Sanctuary. NOAA Technical Memorandum NOS NCCOS 246. Silver Spring, MD. 24 pp. https://doi.org/10.7289/V5/TM-NOS-NCCOS-246

Kerfoot, C.W., M.M. Hobmeier, F. Yousef, S.A. Green, R. Regis, C.N. Brooks, R. Shuchman, J. Anderson, and M. Reif. 2014. Light Detection and Ranging (Lidar) and Multispectral Scanner (MSS) Studies Examine Coastal Environments Influenced by Mining. ISPRS International Journal of Geo-Information 2014 3(1):66-95. doi: https://doi.org/10.3390/ijgi3010066

Mozley, S.C., and R.P. Howmiller. 1977. Environmental status of the Lake Michigan Region. Vol. 6. Zoobenthos of Lake Michigan. ANL/ES-40 Vol. 6. Argonne National Laboratory. Argonne, IL. 148 pp

Muckelroy, K. 1978. Maritime Archaeology. Cambridge University Press. 270 pp.

Nalepa, T.F., D.L. Fanslow, and G.A. Lang. 2009. Transformation of the offshore benthic community in Lake Michigan: recent shift from the native amphipod Diporeia spp. to the invasive mussel Dreissena rostriformis bugensis. Freshwater Biology 54: 466-479. doi: https://doi.org/10.1111/j.1365-2427.2008.02123.x

Ecological Assessment of Wisconsin - Lake Michigan 29 Lakebed

NOAA NGDC. 1996. Bathymetry of Lake Michigan. NOAA National Centers for Environmental Information (formerly National Geophysical Data Center). doi:10.7289/V5B85627. Online: https://www.ngdc.noaa.gov/ mgg/greatlakes/michigan.html (Accessed 30 April 2019)

NOAA ONMS. 2016. Wisconsin - Lake Michigan National Marine Sanctuary Designation Draft Environmental Impact Statement. NOAA National Ocean Service, Office of National Marine Sanctuaries, Silver Spring, MD. 125 pp. Online: https://nmssanctuaries.blob.core.windows.net/sanctuaries-prod/media/archive/wisconsin/ wisconsin-proposed-deis-dmp.pdf (Accessed 28 Feb 2019)

Powers, C.F., and A. Robertson. 1968. Subdivisions of the benthic environment of the upper Great Lakes, with emphasis on Lake Michigan. Journal of the Fisheries Research Board of Canada 25: 1181-1197. doi: https:// doi.org/10.1139/f68-104

Riseng, C.M., K.E. Wehrly, L. Wang, E.S. Rutherford, J.E. McKenna, Jr., L.B. Johnson, L.A. Mason, C. Castiglione, T.P. Hollenhorst, B.L. Sparks-Jackson, and S.P. Sowa. 2018. Ecosystem classification and mapping of the Laurentian Great Lakes. Canadian Journal of Fisheries and Aquatic Sciences 75:1693-1712, https:// doi.org/10.1139/cjfas-2017-0242 Chapter 2 Chapter Rowe, M.D., D.R. Obenour, T.F. Nalepa, H.A. Vanderploeg, F. Yousef, and W.C. Kerfoot. 2015. Mapping the spatial distribution of the biomass and filter-feeding effect of invasive dreissenid mussels on the winter- spring phytoplankton bloom in Lake Michigan. Freshwater Biology 60(11): 2270-2285. doi: https:// doi.org/10.1111/fwb.12653

Seilheimer, T. University of Wisconsin - Manitowoc. Manitowoc, WI. Personal communication.

Shuchman, R.A., M.J. Sayers, and C.N. Brooks. 2013. Mapping and monitoring the extent of submerged aquatic vegetation in the Laurentian Great Lakes with multi-scale satellite remote sensing. Journal of Great Lakes Research 39(Suppl. 1): 78-89. doi: https://doi.org/10.1016/j.jglr.2013.05.006

Tauber, F. 2009. Sidescan sonar survey of a dumping site in the Mecklenburg Bight (south-western Baltic Sea). Journal of Marine Systems 75(3-4):421-429. doi: https://doi.org/10.1016/j.jmarsys.2008.04.006

University of Wisconsin. 2019. SSEC RealEarth: Cladophora map. University of Wisconsin-Madison, Space Science and Engineering Center. Dataset Online: https://realearth.ssec.wisc.edu/? products=WICoast,clad.50 (Accessed 30 April 2019)

Waples, J.T., R. Paddock, J. Janssen, D. Lovalvo, B. Schulze, J. Kaster, and J.Val Klump. 2005. High Resolution Bathymetry and Lakebed Characterization in the Nearshore of Western Lake Michigan. Journal of Great Lakes Research 31(Suppl. 1): 64-74. doi: https://doi.org/10.1016/S0380-1330(05)70290-2

Wentworth, C.K. 1922. A Scale of Grade and Class Terms for Clastic Sediments. The Journal of Geology 30(5): 377-392. doi: https://doi.org/10.1086/622910

Wickham J.T. D.L. Gross, J.A Lineback, and R.L. Thomas. 1978. Late Quaternary Sediments of Lake Michigan. Environmental Geology Notes No. 84. Illinois State Geological Survey, Urbana, IL. 42 pp.

Zant, C., T. Thomsen, and V. Kiefer. Unpublished. Ground Truthing Targets Identified in the Lake Bed Mapping of the Mid-Lake Michigan Region, June 2018 [DRAFT]. Unpublished report by the Wisconsin Historical Society. 30 Ecological Assessment of Wisconsin - Lake Michigan Chapter 3 Water Quality Charles Menza1, Dan S. Dorfman1,2, Ayman Mabrouk1,2, Varis Ransibrahmanakul1

UV Radiometer deployment in Lake Michigan. Credit: NOAA GLERL

3.1 INTRODUCTION Water quality is inextricably linked to the condition and use of resources within Lake Michigan. Good water quality protects people, supports the economy, and maintains a vibrant ecosystem. Water quality is also a key factor in the preservation of and access to the many underwater cultural resources in the study area (NOAA ONMS 2016). This chapter focuses on a core set of chemical, physical, and biological parameters that are commonly used as indicators of water quality and which broadly characterize the status and trends of ecological health needed to support aquatic life, and safe access to lake resources.

Communities of Wisconsin’s Lake Michigan coast have been assessing and managing water quality since at least the 1800s when early industries, particularly lumber mills and slaughterhouses, routinely dumped waste into Lake Michigan and tributary rivers. As coastal communities and economies grew, so too did pollution and water quality concerns. Toxic metals, chemicals, pesticides, and fertilizers flowed from factories and sewage plants, seeped from dumps, and ran off cities and farmland into the lake. Poor water quality has led to beach closures, degraded fish and wildlife habitats, siltation of harbors and streams, diminished recreational uses, and reduced aesthetic value (Nalepa et al. 2009, Weiskerger and Whitman 2018). Two areas immediately adjacent to our study area, the Sheboygan River and Milwaukee Estuary, became so environmentally degraded that they were identified as Great Lakes Areas of Concern in 1987 and in need of focused, long-term efforts to restore the ecosystem. With dedicated effort, cleanup in the Sheboygan River is now complete and there has been significant progress in the Milwaukee Estuary (WDNR 2017).

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch. Silver Spring, MD. 2 CSS, Inc. Fairfax, VA

Ecological Assessment of Wisconsin - Lake Michigan 31 Water Quality

Recognizing the importance of maintaining good water quality within the Great Lakes, the United States and Canada entered into a comprehensive binational agreement known as the Great Lakes Water Quality Agreement (GLWQA) in 1972 and reaffirmed it in 2012. The overall goal of the agreement was “to restore and maintain the chemical, physical, and biological integrity of the Great Lakes Waters” (ECCC and EPA 2012). Accordingly, the U.S. Environmental Protection Agency (EPA) established a water quality monitoring program for the Great Lakes in 1983 to understand the ecosystem and eliminate or reduce impacts from environmental threats such as harmful algae, toxic chemicals, and discharges from vessels. The Wisconsin Department of Natural Resources (WDNR) also assesses, manages, protects, and enhances water resources in the study area. The environmental parameters characterized in this chapter link to the goals set forth by the GLWQA and use data collected by the associated EPA long-term monitoring program and by WDNR.

In this chapter, we synthesize information on temperature, turbidity, nutrients, dissolved oxygen, chlorophyll a, and Escherichia coliform (E. coli) concentrations within the study area. These data are used to characterize temporal and spatial patterns of water quality over the past 20 years.

3.2 DATA AND METHODS We used several water quality datasets from various sources to describe spatial and temporal patterns in water quality variables (Table 3.1). Since this water quality assessment relied on different readily-available datasets, the time spans among different datasets do not precisely coincide. However, they all provide information from 2003-2013 (11 years), and together they provide a more holistic characterization of the study area than any one dataset on its own.

We used two remote sensing datasets to characterize the spatial and temporal patterns of surface temperature, upwelling, chlorophyll a concentration and turbidity. These data were limited to the lake surface and offshore Chapter 3 Chapter waters (commonly greater than 5 km from shore), but provided exceptional temporal resolution and spatial coverage.

The Great Lakes Aquatic Habitat Framework (GLAHF; https://www.glahf.org/) database provides remotely sensed mean monthly surface water temperature and upwelling data at 1.8 km resolution from 1995 to 2013 (Riseng et al. 2018). Monthly temperatures were calculated from daily data collected by NOAA Great Lakes CoastWatch and upwelling was calculated by GLAHF using methods established by Plattner et al. (2006). We used mean monthly surface temperature and the monthly number of upwelling events to characterize lake-wide spatial patterns, and broad-scale changes of temperature and upwelling over time.

Table 3.1. Summary of datasets used to characterize water quality Spatial Time Dataset Variables Resolution Frequency scale period U.S. EPA Great Lakes National water temperature (deg C) Program Office (GLNPO) water Once per turbidity index (m-1) Lake-wide 24 stations 1996-2014 quality monitoring program - year dissolved oxygen (mg/L) Summer observations only The Great Lakes Aquatic Habitat surface water temperature (deg C) Lake-wide 1.8 km 1995-2013 Monthly Framework (GLAHF) upwelling index (days) NOAA/NCCOS water quality maps turbidity index (m-1) derived from MODIS, SeaWIFS, and Lake-wide 1 km 1995-2015 Monthly chlorophyll a concentration (ug/L) VIIRS sensors fecal coliform concentration, Wisconsin variable, by 1-10 times Wisconsin Beach Health Program specifically Escherichia coli 2003-2017 coast beach per month (CFU/100 ml)

32 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality

We developed new remotely-sensed spatial layers for relative turbidity and chlorophylla concentration for this water quality assessment. Mean monthly turbidity and chlorophyll a concentration surface layers were derived from a combination of MODIS (Moderate Resolution Imaging Spectroradiometer), SeaWIFS (Sea-Viewing Wide Field-of-View Sensor) and VIIRS (Visible Infrared Radiometer Suite) sensors. We used a multiband quasi- analytical algorithm described by Lee et al. (2002) to derive turbidity and chlorophyll a from water color at 1 km resolution for 1995-2015. Relative turbidity is measured by beam attenuation (m-1) in this report which is appropriate for assessing relative differences between locations or between times.

Remote sensing data were used to characterize spatial variation and long-term trends (1995-2013) for water temperature, upwelling events, relative turbidity, and chlorophyll a concentration. Ordinary least squares (OLS) regression was used to assess trends over time for the study area. For surface water temperature, a subset of mean monthly measurements from July to September were used to also assess temperature in warm summer months when the lake is stratified.

The EPA Great Lakes National Program Office (GLNPO) water quality monitoring program provides water quality information from 24 stations distributed throughout Lake Michigan once in late March (spring cruise) and again in August (summer cruise). Monitoring stations are located in 46°0'N offshore waters (>30 m deep) to ¯ Michigan ! 50 monitor basin-wide chemical, physical, MI52B and biological integrity. One monitoring km MI53B station, MI31B, occurs within the study ! area, is 8 km from shore between MI47 MI51B ! ! Manitowoc and Sheboygan, WI and is in MI42B 45°0'N approximately 40 m water depth (Figure 3 Chapter MI40 3.1). We use MI31B throughout this !!! ! chapter to set the context for how a site MIFO MI41M within the study area compares relative Kewaunee ! to the rest of the lake. The GLNPO data Manitowoc !MI32 MI34 provide lake-wide context of water ! ! 44°0'N !Ludington quality variables, but are too broad Wisconsin ! ! MI31B MI30B to characterize spatial or temporal ! Sheboygan MI27M Michigan patterns within the study area. !

We used GLNPO data collected only MI23 !Muskegon ! MI46B in August since observations in March ! ! were not available in several years. Milwaukee 43°0'N Water quality parameters were MI17 MI18M MI19 !!! !MI48B characterized at the lake surface ! and at the lake bottom separately, MIFE !MI11 since the lake is stratified in August. Surface conditions were described by Illinois the average of records from 0 to 2 m 42°0'N water depth, and bottom conditions ! as the average from the deepest 10 m of records. We excluded data from 89°0'W 88°0'W 87°0'W 86°0'W 85°0'W GLNPO stations inside Green Bay, Figure 3.1. Map of EPA Great Lakes National Program Office long term monitoring which were significantly different than stations and the proposed sanctuary boundaries.

Ecological Assessment of Wisconsin - Lake Michigan 33 Water Quality

0 1 other offshore stations, and records for 10 0 10 20 30 km 30 chlorophyll a concentration collected ¯ 0100 10 20 mi prior to 2002, because of a change Algoma 44.6° N Crescent Beach in methodology described by Dove 200 and Chapra (2015). We also excluded Green Bay Kewaunee records for bottom conditions taken in Selner Park 44.4° N 2007, because reported depths were vastly different than other years and 100 likely represented a different location. Two Point Beach State (3 beaches) OLS regression was used to characterize Rivers 44.2° N 200 Neshotah Beach Memorial Drive Parkway trends over time. Memorial Drive Thiede Memorial Drive Mariners at Waldo YMCA Beach Manitowoc Blue Rail Marina Beach Warm Water Beach Red Arrow Park Beach Manitowoc The Wisconsin Beach Health program 44° N monitored 38 Wisconsin beaches Fischer Park Beaches for fecal coliform, specifically E. Hika Park Bay

coli, from 2003 to 2017 (Figure 3.2). 100 43.8° N Deland Park Beach Measurements are collected during Blue Harbor Beach Sheboygan Kite Surfing Area - Clara Ave !( Monitored beaches the summer months (May to October) General King Park Beach Proposed Sanctuary Boundaries Kohler Andrae State Park when recreational swimming is most (6 beaches) Alternative A (preferred) KK Road Beach Alternative B 43.6° N common. We characterized the spatial Van Ess Road Beach Contours (m) and temporal patterns of E. coli levels, Amsterdam Beach Harrington SP Beach (3 beaches) County Road D Boat Launch Beach advisories and beach closures in the Port Cedar Beach Rd Beach study area. Following water quality 43.4° N Washington Upper Lake Park Beach criteria recommended by the EPA and South Beach Lion's Den Gorge Nature Preserve Study Area Lake

Chapter 3 Chapter Grafton adopted by the Wisconsin DNR, beach Huron Lake

10 30 advisories indicate E. coli concentrations Mequon Concordia University 100 Ontario Lake 43.2° N exceeded 235 colony-forming units Michigan Lake Erie Milwaukee (CFU) per 100 ml and beach closures -88° W 87.8° W 87.6° W 87.4° W 87.2° W -87° W indicate when concentrations exceeded Figure 3.2. Map of beaches monitored by the Wisconsin Beach health program and 1,000 CFU E. coli/100 ml (EPA 2002). the proposed sanctuary boundaries.

3.3 CURRENT CONDITIONS AND TRENDS 3.3.1 Temperature Temperature is an important water quality parameter, because it affects many physical, chemical, and biological processes. For example, temperature affects metabolic rates and habitat selection of fish, algae and other taxa, it affects pH and dissolved oxygen concentration, and it is one of the factors controlling water circulation (Simpson 1991, Wetzel 2001, ECCC and EPA 2012). Water temperature has been of keen interest for climate change research and is commonly monitored by lake condition reports (e.g., ECCC and EPA 2017).

Lake Michigan is characterized by a broad-scale temperature gradient between the southeastern and northwestern regions of the lake (Figure 3.3), a well-defined annual temperature cycle, and seasonal stratification. Although the study area is positioned mid-lake along the central Wisconsin coast, thelong- term average surface temperature of the study area is similar to the northwestern and northern shores of the lake (except for Green Bay) and is much colder than most of Lake Michigan in general (Figure 3.3). The study area is cold for two reasons. The general circulation patterns in the lake move cold water into the study area from the northern basin along the western lakeshore (Beletsky et al. 1999), and meteorological forcing produces frequent cold-water upwelling along Lake Michigan’s western shore (Beletsky and Schwab 2008). The combined effect is to give the study area distinctly colder water temperature than the rest of the lake.

34 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality

Lake Michigan is thermally stratified during summer and entirely thermally ¯ Michigan 46°0'N mixed in winter. The onset and duration 50 of stratification can vary across years, km but typically begins in April to May and lasts until November to December (Beletsky and Schwab 2008). Nearshore areas, including the study area, are 45°0'N stratified earlier and longer than offshore areas. Once the whole lake is stratified a well-developed thermocline Kewaunee ! persists until fall (Beletsky and Schwab 2008). The thermocline at station Manitowoc ! 44°0'N MI31B normally extended from 5 to Wisconsin !Ludington 30 meters (average 12 m) in August. In ! some years, notably, 2003 and 2009, Sheboygan Michigan the thermocline was not evident, and temperature decreased at a consistent !Muskegon rate throughout the measured water ! column. In these years it’s likely the Milwaukee 43°0'N thermal bar extended to the lakebed. Surface temp deg C Lake surface temperatures at MI31B in 12 August averaged (standard error, SE) 18.1 °C (n = 12, standard error [SE] = 3 Chapter Illinois 0 0.76) and showed considerable year-to- 42°0'N year variability. Bottom temperatures ! Chicago averaged 6.0 °C (n = 12, SE = 0.57), and varied substantially less than surface Indiana temperatures. Compared to other 89°0'W 88°0'W 87°0'W 86°0'W 85°0'W offshore stations, surface temperatures Figure 3.3. The average lake surface temperature between 1995 and 2013. Temperature derived from satellite data. at MI31B were consistently colder and bottom temperatures were typically warmer (Figure 3.4). Colder surface temperatures reflect the general circulation patterns and upwelling, whereas the warmer bottom temperatures reflect the fact that MI31B is one of the shallowest GLNPO stations (approximately 40 m water depth). Using the OLS for analysis, neither surface (R2 = 0.08, p = 0.36) nor bottom (R2 = 0.11, p = 0.29) temperatures showed significant long-term trends. Satellite derived surface water temperatures across all months and for only summer months (July-September) also did not show significant long-term temperature trends within the study area (Figure 3.5)(OLS, R2 = 0.00, p = 0.32; and OLS, R2 = 0.00, p = 0.79, respectively).

Ecological Assessment of Wisconsin - Lake Michigan 35 Water Quality

Lake Surface 28 y = −0.000461 * x + 24.2 ● P = 0.36● ●

26 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 24 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 22 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● 20 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● 18 ● ● ● ● ● ● ● ●● ● ● ●● 16 ● ● ● ● ● ● ● ● ● 14 ● ● ● ● ●

Water Temperature (deg C) Temperature Water 12 ● 10 Lake Bottom 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 14 Year ● y = −0.000374 * x + 11.1 P = 0.29 12 ●

10 ●

● ● ● ● 8 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 6 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 4 ● ● ● ● ● ● ● ● Water Temperature (deg C) Temperature Water

Chapter 3 Chapter 2 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Figure 3.4. Lake surface (top) and lake bottom (bottom) water temperature (°C) at GLNPO stations in Lake Michigan during summer (August) from 1999 to 2014. Temperatures at station MI31B are represented by large black points and other stations by smaller grey points. The black line is a linear least square regression fit to MI31B temperatures and the grey ribbon is the corresponding 95% confidence interval.

25 All Months y = 0.00023 * x + 6.17 P = 0.31 Jul − Sept y = 3.54e−05 * x + 18.5 P = 0.79

20

15

10

5 Water Temperature (deg C) Temperature Water

0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Figure 3.5. Lake surface temperature in the study area derived from remote sensing between 1995 and 2014. The black line defines a linear least square regression fit to surface temperatures across all months. The red line is a linear least square regression fit to surface temperatures from only summer months (July-September). The grey ribbons correspond to the 95% confidence interval of each regression fit. Temperature data from GLAHF.

36 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality 3.3.2 Upwelling 46°0'N Coastal upwelling occurs when winds ¯ Michigan blow warmer surface waters offshore, 50 and colder nutrient-rich water rises km from depth to the lake’s surface. Since the wind in the Great Lakes region typically blows from west to east, coastal 45°0'N upwelling generally occurs on the western edge of Lake Michigan (Plattner et al. 2006). Tracking upwelling is important because upwelling is generally Kewaunee ! linked to biological productivity (Kämpf Manitowoc and Chapman 2016). ! 44°0'N Wisconsin !Ludington Coastal upwelling in Lake Michigan was ! classified and forecasted by Platter et al. Sheboygan Michigan (2006). They defined upwelling as areas where the local median temperature was !Muskegon 4 °C or colder than the median regional ! temperature. Using this definition, Milwaukee 43°0'N the study area is clearly an upwelling Upwelling days/yr hotspot in the lake and included 31% of 0 all upwelling days in Lake Michigan from 0.1 - 3 1994 to 2013 (Figures 3.6 and 3.7). 3.1 - 10 10.1 - 15 Chapter 3 Chapter Illinois 15.1 - 25 3.3.3 Turbidity 42°0'N 25.1 - 40 Turbidity is a measure of water clarity, Chicago ! expressed by the amount of light Indiana scattered by material in the water column. Many different materials can 89°0'W 88°0'W 87°0'W 86°0'W 85°0'W Figure 3.6. The total number of days from 1995 to 2013 with upwelling in Lake scatter light such as silt, algae, organic Michigan. Upwelling data from GLAHF. Color classes refer to the 50th, 75th, 90th, matter, and plankton. These materials 95th, and 99th percentile of upwelling events in the lake. can have varied sources, including sediment runoff from land, algae 60 50 blooms from land-based phosphorus 40 contributions, or sediment resuspension 30 caused by water movement. 20 10

Consequently, turbidity can be used Days # of Upwelling Avg. 0 Year as a proxy for anthropogenic impacts 0.7 from activities such as from dredging, 0.6 0.5 , and (Iannuzzi et 0.4 al. 1996, Ruffink 1998, Montes-Hugo et 0.3 0.2 al. 2003). 0.1

Prop. of Upwelling Days of Upwelling Prop. 0.0 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Understanding changes in turbidity Year is important because turbidity that is Figure 3.7. The average number of days with upwelling in the study area from 1994-2013 (top), and the proportion of days with upwelling in the study area either too high or too low turbidity relative to the number of days with upwelling in the rest of Lake Michigan (bottom). can cause significant environmental Upwelling data from GLAHF.

Ecological Assessment of Wisconsin - Lake Michigan 37 Water Quality

damage. For instance, turbidity that is too low can deepen the euphotic zone providing more habitat for nuisance algae Cladophora (Bootsma et al. 2015). Alternatively, an increase in turbidity can smother benthic organisms and habitats, and incur costly treatments to municipal and industrial water supplies (AWWA 1990). Yet not all changes to turbidity are deleterious. Low turbidity can increase the visibility of submerged cultural resources (Schott 2016) or allow for greater areas of the lake to be surveyed using LiDAR.

In general, Lake Michigan currently has very low turbidity levels compared to Lakes Erie and Ontario, but turbidity can temporarily be high in Green Bay and in some nearshore areas, particularly the southern shore. Turbidity within the study area is also

very low. Turbidity tends to be higher 46°0'N nearshore and is relatively homogenous ¯ Michigan further than 20 km from shore. 50 Turbidity in most of the study area’s km nearshore areas were not remotely measured, because sensors can’t distinguish turbidity from the lakebed. 45°0'N However, in an isolated nearshore area off Manitowoc and Two Rivers, WI with turbidity estimates, relative turbidity is higher than the rest of the study area Kewaunee ! and much of the rest of the lake (Figure Manitowoc 3.8). ! 44°0'N Wisconsin !Ludington We detected significant decreasing Sheboygan ! Michigan Chapter 3 Chapter trends over time in turbidity within the study area using remotely sensed

estimates, but didn’t detect any !Muskegon

comparable long-term trends using in ! Milwaukee 43°0'N situ observations from MI31B. Satellite derived beam attenuation decreased by 33% between 1998 and 2015 (Figure Turbidity hotspot index 3.9). In situ summer surface and bottom High : 1 turbidity did not decline in the study area or among other stations (Figure Illinois Low : 0 3.10). The most evident turbidity 42°0'N patterns among in situ observations Chicago ! were a three-fold increase in variability Indiana

among surface measurements after 89°0'W 88°0'W 87°0'W 86°0'W 85°0'W 2004 and a slight decrease in variability Figure 3.8. A map showing persistent relative turbidity hotspots. Areas in red are among bottom measurements after more likely to be the most turbid areas of Lake Michigan in any given month. The persistent turbidity hotspot index is a relative measure of how often areas are in 2004. An increase in variability after the top 90th percentile of monthly relative turbidity values for the whole lake from 2004 is also evident in the remote 1998-2015. sensing time series (Figure 3.9).

38 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality Study Area 0.15 y = −7.13e−06 * x + 0.207 0.14 P < 0.001 0.13 0.12 0.11 0.10 0.09 0.08 0.07 Relative Turbidity (1/m) Turbidity Relative 0.06 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Year Figure 3.9. Time series of monthly relative turbidity within the study area (top) and in the whole of Lake Michigan (bottom) between 1998 and 2015. Data derived from MODIS, SeaWIFS and VIIRS sensors. Blue lines represent linear trend lines, and the grey ribbon represents the 95% confidence interval of the trend line. Gaps in the line indicate when data are unavailable due to cloud cover or other data quality issues.

Lake Surface

5 ● y = 0.000169● * x + 0.305

● P = 0.78 ● ● ●

● ● 4 ● ● ● ● ●

● 3 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● 2 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 3 Chapter ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1 ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Beam Attenuation (1/m) Beam Attenuation ● ● ● ● ●● 0

Lake Bottom 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 6 Year y = −0.000281 * x + 4.83

●P = 0.11 ●

4 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 2 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● Beam Attenuation (1/m) Beam Attenuation 0 ● ● 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Figure 3.10. Beam attenuation (1/m) the lake surface (top) and lake bottom (bottom) of GLNPO stations in Lake Michigan during summer (August) from 1999 to 2014. Beam attenuation measurements at station MI31B are represented by large black points and other stations by smaller grey points. The black line is a linear least square regression fit to MI31B beam attenuation measurements and the grey ribbon is the corresponding 95% confidence interval.

Ecological Assessment of Wisconsin - Lake Michigan 39 Water Quality

3.3.4 Phosphorus and Nitrogen Nutrients, especially phosphorus and nitrogen (P and N), are essential for the growth of phytoplankton and algae in the Great Lakes. However, an excess of these nutrients above certain levels can lead to the development of nuisance and harmful algal blooms (HABs) and be detrimental to the ecosystem and human health (ECCC and EPA 2017).

Prior to the 1980s, phosphorus concentration was elevated in Lake Michigan, including in the study area, and led to nuisance levels of phytoplankton and macroalgae (Dove and Chapra 2015). In the 1980s and early 1990s, regulation of phosphorus concentrations in detergents, investments in sewage treatment, and the implementation of best management practices on agriculture lands reduced nutrient-related runoffand decreased phosphorus to well below the 7 μgP/L GLWQA target. However, most monitoring has focused in offshore waters, and in some nearshore areas elevated phosphorus is observed and may be supporting nuisance algae growth (Bootsma 2015). The causes of the nearshore algae resurgence are not clear and are likely associated with the ecosystem engineering by invasive mussels.

Nitrogen levels in Lake Michigan have been increasing since the 1970s, but the rate of increase has slowed

since 2000 (Dove and Chapra 2015). Nitrate-plus-nitrite (NO3 NO2) concentrations in Lake Michigan are the lowest of the Great Lakes with the exception of central Lake Erie, where it is readily taken up by algal blooms. Given that phosphorus limits productivity in Lake Michigan, there are currently no water quality objectives for nitrogen.

3.3.5 Chlorophyll a Chlorophyll a concentration is used to measure photosynthetic activity and algal biomass in water. As such, chlorophyll a can serve as an indicator of primary productivity, eutrophication, and events. Chapter 3 Chapter Chlorophyll a concentrations within Lake Michigan and in the study area are relatively low, particularly when compared to Green Bay (Figure 3.11) or Lakes Erie and Ontario. The mean (standard deviation, SD) monthly chlorophyll a concentration within the study area was typically below 1 μg/L (mean = 0.81, SD = 0.27) between 1997 and 2015, and exceeded 5 μg/L in only isolated instances and in very small areas off Kewaunee, WI. This 5 μg/L threshold is used by the EPA to distinguish good water quality (<5 μg/L) from fair (>5 μg/L and 20 μg/L) water quality (EPA 2015). In relation to the Lake Michigan basin, there is a persistent relative chlorophyll a concentration hotspot off Manitowoc, which is the same area with a persistent relative turbidity hotspot.

One limitation of the remotely sensed chlorophyll a concentration estimation is the lack of nearshore data. Within the study area there are very few estimates of chlorophylla concentration within 5 km from shore. This limitation is especially relevant to understanding spatially-explicit changes of chlorophyll a concentration over time. Several studies have shown pronounced changes in chlorophyll a concentrations in offshore regions, however changes in nearshore regions have been more equivocal. Some of this discrepancy is related to mussels capturing nutrients in nearshore areas and disrupting transport of nutrients into the offshore (Hecky et al 2004, Bootsma and Liao 2014, Bunnell et al. 2018).

Based on satellite derived estimates, average annual chlorophyll a concentration decreased by 45% in the study area between 1998 and 2015 (Figure 3.12). This decreasing trend inside the study area is well studied at the basin level, and includes a strong seasonal component, with the largest chlorophyll a concentration declines occurring in the spring (Vanderploeg et al. 2010).

40 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality

¯ Michigan 46°0'N ¯ Michigan 46°0'N 50 50 km km

45°0'N 45°0'N

Kewaunee ! Kewaunee !

Manitowoc Manitowoc ! ! 44°0'N 44°0'N !Ludington ! Wisconsin Wisconsin Ludington Sheboygan ! Michigan Sheboygan ! Michigan

!Muskegon !Muskegon

! ! Milwaukee 43°0'N Milwaukee 43°0'N

Chlorophyll hotspot Chlorophyll a max index ug/L High : 1 0 - 5 Illinois 5 - 20 Illinois Low : 0 42°0'N 42°0'N 20 - 32 Chicago ! Chicago ! Indiana Indiana

89°0'W 88°0'W 87°0'W 86°0'W 85°0'W 89°0'W 88°0'W 87°0'W 86°0'W 85°0'W

Figure 3.11. Maximum monthly chlorophyll a concentration (left) and persistence of relative chlorophyll a concentration hotspots 3 Chapter (right) in Lake Michigan between 1997 and 2015. Chlorophyll concentration thresholds identify good (<5 μg/L), fair (>5 μg/L and 10 μg/L) and poor (>10 μg/L) water quality (EPA 2015). The persistence of relative chlorophyll a concentration hotspots is defined as the proportion of months an area is within the top 90th percentile of chlorophyll a concentration relative to the rest of the remotely sensed portion of the lake.

Study Area 2.0 y = −8.19e−05 * x + 1.94 1.8 P < 0.001 1.6 1.4 1.2 1.0 0.8 0.6

Chl a conc. (micrograms/L) 0.4 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Year Figure 3.12. Time series of monthly chlorophyll a concentration within the study area between 1998 and 2015. Data derived from MODIS, SeaWIFS and VIIRS sensors. Blue lines represent linear trend lines, and the grey ribbon represents the 95% confidence interval of the trend line. Gaps in the line indicate when data are unavailable due to cloud cover or other data quality issues.

Ecological Assessment of Wisconsin - Lake Michigan 41 Water Quality

3.3.6 Dissolved Oxygen Dissolved oxygen (DO) is essential for most aquatic plants and to survive and is a key factor in many chemical reactions (Simpson 1991, Carlson and Simpson 1996). Low DO in Lake Michigan has caused habitat loss for lake trout (Plumb and Blanchfield 2009) and the copepodLimnocalanus macrurus (Gannon and Beeton 1971), and has been associated with increases in the toxic bacterium Clostridium botulinum (Getchell and Bowser 2006, Tyner 2013). As a result of wide ranging impacts, DO is not only used in water quality monitoring programs, but also in habitat criteria and population sustainability metrics for important lake resources (e.g. Evans 2007, Plumb and Blanchfield 2009).

Average DO concentrations at the lake surface and lake bottom were 6.2 mg/L and 12.3 mg/L, respectively. Concentrations at the surface and bottom both had high variability across stations and years, and although both tended to be increasing over time, neither time series was statistically significant (Figure 3.13).

DO concentrations below 2 mg/L are thought to be stressful to many organisms (Diaz and Rosenberg 1995, EPA 2000), and concentrations below 5 mg/L are considered to be fair (i.e., not good) by the EPA (2015). None of the DO measurements collected in Lake Michigan in any year were below 2 mg/L. DO between 2 mg/L and 5 Lake Surface 14 y = 0.000388 * x + 2.05 P = 0.31

12 ●

● ● ● ● ● ● ● ● ● ● ● ● ● 10 ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 8 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Chapter 3 Chapter ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 6 ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 4 ● Dissolved Oxygen (mg/L) Dissolved ● ● ● 2 Lake Bottom

15 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 y2010 = 0.0001622011 * x2012 + 9.78 2013 2014 Year P = 0.07

● ● ● ● 14 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 13 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● 12 ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 11 ● ● ● ● ● ● ● ●

Dissolved Oxygen (mg/L) Dissolved ● ● ● ● 10 ● 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Figure 3.13. Dissolved oxygen concentrations at the lake surface (top) and lake bottom (bottom) of GLNPO stations in Lake Michigan during summer (August) from 1999 to 2014. Dissolved oxygen concentrations at station MI31B are represented by large black points and other stations by smaller grey points. The black line is a linear least square regression fit to MI31B dissolved oxygen concentrations and the grey ribbon is the corresponding 95% confidence interval.

42 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality mg/L was detected in surface measurements frequently between 1999 and 2014, and was observed in 2001 and 2005 at MI31B. These records characterize fair water quality conditions, which are not impaired, but should be monitored.

3.3.7 Fecal Contamination,Escherichia coliform (E. Coli) Many of the beaches in Wisconsin along Lake Michigan are used for recreation. People swim, , kite board, surf and SCUBA dive in the water adjacent to beaches. There has been increasing awareness that recreational waters can be impaired by fecal pollution from human sources and zoonotic reservoirs since the Federal BEACH Act (Beaches Environmental Assessment and Coastal Health [BEACH] Act, 33 U.S.C. §1313 et seq. [2000]). In order to alert the public about potentially unhealthy water quality conditions local health departments frequently test water quality and use results to post swim advisories or close beaches.

Over a 15-year period from 2003 to 2017, E. coli concentrations were sampled at 38 different beaches in Kewaunee, Manitowoc, Sheboygan, and Ozaukee counties. Beaches were sampled an average of 33 times a year, but sampling frequency among beaches was not consistent. Wisconsin generally issued a beach advisory when E. coli concentration was 236 to 999 CFU/100 ml, and generally issued a beach closure when E. coli concentration was equal to or greater than 1,000 CFU/100 ml. In some cases, advisories and closures were issued without water samples and were prompted by rainfall or other factors linked to high E. coli counts in the past. These rare and nonstandard advisories and closures are not included in this analysis, because we did not find corresponding data.

Every beach sampled in two or more years had E. coli concentrations that exceeded 235 CFU/100 ml at least once in the 15-year period. The average number of days E. coli concentrations exceeded the advisory and closure thresholds in the study area were 6.2 and 1.8 days per beach per year, respectively. Upper Lake Park Beach off Port Washington had the greatest number of advisory and closure days, with averages of 14.1 and 3 Chapter 5.5 days per year, respectively. Several beaches south of Sheboygan also had a relatively high number of advisory and closure days.

E. coli concentrations are measured from May to October, but concentrations are 1500 Advisory notably higher in June, July, and August. Closure Correspondingly, beach advisories and closures are greater in these months as well (Figure 3.14). Across the 15- year time period, the annual number 1000 of days E. coli concentrations exceeded advisory and closure thresholds in the study area varied considerably (Figure 3.15). The number of days where E. coli 500 concentrations exceeded the advisory threshold has decreased over time, but a temporal trend in closures was not

evident. The number of advisories were

exceeds EPA criteria at beaches beaches at criteria EPA exceeds coli E. highest in four of the first five years of days of Number 0 sampling (2003-2007) and lowest in the May Jun Jul Aug Sep Oct last two years of sampling. Month Figure 3.14. Monthly number of days E. coli records exceeded advisory (>235 CFU/100 ml) and closure (>1,000 CFU/100 ml) thresholds in the study area. Data collected by the Wisconsin Beach Health monitoring program from 2003 to 2017.

Ecological Assessment of Wisconsin - Lake Michigan 43 Water Quality

400

Advisory 300 Closure

200

100

0 No. of days with Exceedances of days No. 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Year Figure 3.15. Annual number of days E. coli concentrations exceed advisory (>235 CFU/100 ml) and closure (>1,000 CFU/100 ml) thresholds in all study area beaches. Data collected by the Wisconsin Beach Health monitoring program from 2003 to 2017 in May to October.

3.4 DISCUSSION Prior to the 1970s and the GLWQA, excessive algal growth was a major threat to Lake Michigan (Beeton 1965). The GLWQA set a basis for collecting, interpreting, and using data to improve water quality, and largely the associated new programs and policies worked. Overall, the main body of Lake Michigan is considered to have good to fair water quality. Green Bay has continued to struggle with water quality. Monitoring data indicate

Chapter 3 Chapter Lake Michigan is now oligotrophic, has safe drinking water, has reasonably clean beaches for swimming, and does not have harmful algal blooms. However, shifts in climate trends, nutrient imbalances and the presence of toxic chemicals are enduring water quality concerns (ECCC and EPA 2017). It is also clear that there has been significant change in some water quality parameters since the 1990s. These changes are mainly driven by the invasion of dreissenid mussels, and to a lesser extent climate change and continued decreases in phosphorus input due to phosphorus abatement programs and increasing inventory of phosphorus in mussel tissue (Nalepa et al. 2009, Fahnenstiel et al. 2010, Pothoven and Fahnenstiel 2013, Rowe et al. 2017). These concerns are also germane to the study area.

Within the study area, we detected substantial declines in turbidity and chlorophyll a concentration. These declines were similar to those reported for the whole lake (Vanderploeg et al. 2010, Mida et al. 2010, Kerfoot et al. 2010, Fahnenstiel et al. 2010, Yousef et al. 2017), and are explained by the filtering impacts of invasive dreissenid mussels (Fahnenstiel et al. 2010). These changes are recent, and it is unknown if turbidity and chlorophyll a will continue to decline, but it appears as though the trend has been leveling off since 2012 in the time series we Deploying NOAA GLERL ReCON (Real-Time Coastal Observation Network) Buoy in Lake Michigan, May 2014. investigated (Ransibrahmanakul 2018). Credit: NOAA.

44 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality

Lake Michigan currently has lower productivity than Lake Superior, which was historically the most oligotrophic lake (Barbiero et al. 2012, Fahnenstiel et al. 2016). Whether or not the current lower levels of turbidity and chlorophyll a are “good” is unsettled (ECCC and EPA 2017). On one hand, the shift is a sign Lake Michigan has improved from its eutrophic condition 50 years ago as desired by the GLWQA. On the other hand, decreases in turbidity have led to increases in nuisance algae (Auer et al. 2010), and lower levels of primary production could be reducing resources for higher trophic levels and reducing the carrying capacity of the lake. A lower carrying capacity has significant impacts on commercial and recreational lake fisheries.

Changes in productivity, chlorophyll a and turbidity are not uniform across the lake basin or within the study area. There is a dichotomy in productivity between nearshore and offshore regions created by a nearshore nutrient shunt linked to invasive mussels. The mussels and associated shunt have led to increases of macroalgae like Cladophora nearshore and concurrently the decline of phytoplankton offshore, particularly the spring bloom (Hecky et al. 2004). Much of this redistribution is challenging to identify using remotely sensed data, since nearshore estimates are Water quality sampling on RV Laurentian, June 2015 CSMI Cruise. Credit: NOAA unattainable. 3 Chapter

At more local scales, we identified relatively higher chlorophyll a concentrations and turbidity in an isolated nearshore region off Manitowoc and Two Rivers, WI. These relatively higher values never exceeded action levels, but they highlight relative differences in productivity and water clarity between nearshore and offshore regions. These nearshore areas are characterized by less light reaching the lakebed, higher rates of sedimentation, and greater primary productivity.

Potentially the most undesirable water quality observations were impaired water conditions at many beaches in the study area caused by high levels of E. coli. These beaches are popular summer tourist destinations in Wisconsin, and advisories and closings limit access to these beaches. It is possible high levels of E. coli also impact adjacent offshore recreational and educational opportunities, such as SCUBA diving on shipwrecks, and access to those sites. Edge et al. (2013) found waterborne pathogens up to 2 km from shore, but pathogens generally occurred infrequently and in relatively low concentrations. Forty-two shipwrecks are located or predicted to be located within 2 km of beaches with high enough E. coli concentrations to have posted an advisory or closure. There currently is no monitoring for bacterial concentrations at dive sites or other locations Wisconsin Beach Health sampling location at Blue Rail Marina Beach, Manitowoc, Wisconsin. Credit: Wisconsin beyond recreational beaches. Beach Health, WDNR/USEPA.

Ecological Assessment of Wisconsin - Lake Michigan 45 Water Quality

Overall the water quality condition of beaches in Lake Michigan is considered fair to good (ECCC and EPA 2017) and it’s likely getting better. The percent of the swimming season during which beaches are safe to swim is significantly better than Lake Erie, and slightly better than , but is worse than Lakes Superior or Huron. We also found a weak trend indicating a decrease in the number of beach advisories, and Weiskerger and Whitman (2018) report a similar downward trend in E. coli concentrations for Lake Michigan.

One of the most striking findings from this assessment is how different the study area is from the broader lake when considering temperature. There is significant “upwelling” positioned largely within the study area and not in other areas of Lake Michigan. This feature is noteworthy, because upwelling in the Great Lakes has been linked to unique community composition (Haffner et al. 1984, Megard et al. 1997), higher local fish abundance (Heufelder et al. 1982, Fitzsimons et al. 2002), and higher benthic biomass (Wilson et al. 2006). It is undoubtedly a defining feature of the study area and likely plays an important role in defining the central-western region of Lake Michigan as highly productive (Hook et al. 2003).

Another notable finding related to temperature is the lack of surface water warming over time within the study area. Other assessments by Mason et al. (2016) in Lake Michigan, and Austin and Colman (2007) in Lake Superior, and Dobiesz Chapter 3 Chapter and Lester (2009) across Great Lakes found significant lake- wide summer warming trends. The absence of warming in the study area is due to significant spatial variation in surface warming of Lake Michigan (Mason et al. 2016) and it is likely associated with the presence of frequent upwelling. One possible avenue for future research is to determine how the study area might behave as a thermal refuge for Deploying temperature mooring in Lake Michigan. Credit: species affected by rising lake temperatures elsewhere. NOAA

Existing data provided ample information to understand broad-scale changes in water quality within offshore environments and along beaches. Yet, there is a distinct data gap in the nearshore area (within 10 km from shore). The paucity of water quality data in the nearshore environment is particularly challenging, because nearshore environments are more disturbed, more dynamic and different than offshore environments (Yurista et al. 2015); human interaction is concentrated nearshore; nearshore habitats connect terrestrial inputs to offshore areas; and the strongest water quality signals occur nearshore. More information is needed in the nearshore environment to understand how water quality will impact coastal managers’ most pressing challenges including, how water quality influences nuisance Cladophora, invasive mussels, prey fish and submerged cultural resources.

Certainly, there are other water quality issues in the study area which were not addressed by our characterization. We explicitly did not characterize radionuclides, metals, and most organic chemical contaminants, to concentrate on the few parameters we considered most aligned to ecological integrity, and which are commonly measured in the study area. More information on some of the excluded parameters can be found in the 2017 State of the Great Lakes Report (ECCC and EPA 2017) and the 2010 National Coastal Condition Assessment (EPA 2015).

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Riseng, C.M., K.E. Wehrly, L. Wang, E.S. Rutherford, J.E. McKenna, Jr., L.B. Johnson, L.A. Mason, C. Castiglione, T.P. Hollenhorst, B.L. Sparks-Jackson, and S.P. Sowa. 2018. Ecosystem classification and mapping of the Laurentian Great Lakes. Canadian Journal of Fisheries and Aquatic Sciences 75:1693-1712, https:// doi.org/10.1139/cjfas-2017-0242

Rowe, M.D., E.J. Anderson, H.A. Vanderploeg, S. Pothoven, A.K. Elgin, J.L. Wang, and F. Yousef. 2017. Influence of invasive quagga mussels, phosphorus loads, and climate on spatial and temporal patterns of productivity in Lake Michigan: A biophysical modeling study. Limnology and Oceanography 62(6): 2629-2649. doi: https://doi.org/10.1002/lno.10595

Ruffink, K. 1998. The persistence of anthropogenic turbidity plumes in a shallow water estuary. Estuarine, Coastal and Shelf Science 47(5): 579-592. doi: https://doi.org/10.1006/ecss.1998.0366

Simpson, J.T. 1991. Volunteer Lake Monitoring: A Methods Manual. U.S. Environmental Protection Agency, office of Water. EPA 440/4-91-002. 65 pp.

Schott, B.K. 2016. Lake Michigan: Milwaukee-area shipwrecks. Alert Diver Q1 Winter 2016, DAN: The Magazine of Divers Alert Network. Online: http://www.alertdiver.com/Lake-Michigan (Accessed 30 April 2019)

50 Ecological Assessment of Wisconsin - Lake Michigan Ecological Assessment of Wisconsin - Lake Michigan Water Quality

Tyner, E.H. 2013. Nearshore Benthic Oxygen Dynamics in Lake Michigan. University of Wisconsin Milwaukee Theses and Dissertations 171. 86 pp.

Vanderploeg, H.A., J.R. Liebig, T.F. Nalepa, G.L Fahnenstiel, and S.A. Pothoven. 2010. Dreissena and the disappearance of the spring phytoplankton bloom in Lake Michigan. Journal of Great Lakes Research 36 (Suppl. 3): 50-59. doi: https://doi.org/10.1016/j.jglr.2010.04.005Wetzel, R.G. 2001. Limnology: Lake and River ecosystems, 3rd Edition. Academic Press. 1006 pp.

Weiskerger, C.J., and R.L. Whitman. 2018. Monitoring E. coli in a changing beachscape. Science of the Total Environment 619-620:1236-1246. doi: https://doi.org/10.1016/j.scitotenv.2017.11.167

Wilson, K.A., E.T. Howell, and D.A. Jackson. 2006. Replacement of Zebra Mussels by Quagga Mussels in the Canadian Nearshore of Lake Ontario: the Importance of Substrate, Round Goby Abundance, and Upwelling Frequency. Journal of Great Lakes Research 32(1): 11-28. doi: 10.3394/0380-1330(2006)32[11:ROZMBQ]2.0. CO;2

WDNR. 2017. Remedial Action Plan Update for the Milwaukee Estuary Area of Concern. Wisconsin Department of Natural Resources, Office of the Great Waters. Online: https://dnr.wi.gov/topic/ GreatLakes/documents/MilwaukeeAOCRAP2017.pdf (Accessed 30 April 2019)

Yousef, F., R. Shuchman, M. Sayers, G. Fahnenstiel, and A. Henareh. 2017. Water clarity of the Upper Great Lakes: Tracking changes between 1998-2012. Journal of Great Lakes Research 43(2): 239-247. doi: https:// doi. org/10.1016/j.jglr.2016.12.002

Yurista, P.M. J.R. Kelly, A.M. Cotter, S.E. Miller, and J.D. Van Alstine. 2015. Green Bay: Spatial variation in 3 Chapter water quality, and landscape correlations. Journal of Great Lakes Research 41(2): 560-572. doi: https://doi. org/10.1016/j.jglr.2015.03.014

Ecological Assessment of Wisconsin - Lake Michigan 51 52 Ecological Assessment of Wisconsin - Lake Michigan Chapter 4 Lake Ice Christopher Clement1

MODIS image of ice cover on Lake Michigan, March 6, 2014. Credit: NOAA Great Lakes CoastWatch and NASA

4.1 INTRODUCTION This chapter focuses on the characteristics of ice cover for the Wisconsin - Lake Michigan study area. The waters of the study area are subject to a regular yearly cycle of winter freezing and spring melting. The first ice formation is depth dependent, where ice forms in shallow nearshore waters first and then grows offshore into deeper waters as the winter season progresses. As the season advances into warmer weather, the spatial characteristics of ice cover begin to be affected by winds and currents. The total amount of ice cover and timing of ice formation, growth and melting are markedly variable from year to year (Wang et al. 2012).

Lake ice is important to understand, because it impacts coastal and lake economics through its effects on navigation, hydropower generation, lake levels, flooding, recreational opportunities, and damage to shore structures. Lake ice can also impact lake ecosystems by affecting hydrodynamics, plankton communities and fish recruitment (Vanderploeg et al. 1992, Brown et al. 1993). Its impact on conservation of submerged cultural resources is less well studied, but presumably ice cover will affect preservation of nearshore submerged cultural resources, access to shipwrecks and other cultural heritage locations, and may also impact the logistics of on- water activities related to the research and monitoring of those cultural resources, such as buoy placement.

The data summaries provided in this chapter characterize the spatial and temporal variability of ice cover in the study area. These data will inform logistical aspects of research and monitoring of cultural resources, the exposure of submerged cultural resources, and the limitations and opportunities of recreational access that are influenced by lake ice.

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch, Silver Spring, MD.

Ecological Assessment of Wisconsin - Lake Michigan 53 Lake Ice 4.2 DATA AND METHODS The Great Lakes Environmental Research Laboratory (GLERL) has been developing methodologies to monitor and document ice cover of the Great Lakes region for over 46 years (NOAA GLERL 2018). Through the Coastwatch program within GLERL, satellite data is obtained from the U.S. National Ice Center (NIC)(NIC 2018) and processed to produce maps of synthesized ice cover observations. GLERL has produced multiple ice cover reports for the entire Great Lakes region, including Lake Michigan (Figure 4.1)(Assel 2003, Assel et al. 2013, Wang et al. 2017). Many of the data synthesis and presentation methodologies in those reports are pertinent to this study and have been followed in this report.

Figure 4.1. Percent annual maximum ice cover in Lake Michigan. Plot created by the Great Lakes Environmental Research Laboratory (from Wang et al. 2017).

The source data GLERL provides comes from a synthesis of multiple data sources, compiled by the U.S. National Ice Center (NOAA GLERL 2018). This includes satellite data, derived satellite products, buoy data, weather, and analyst interpretation of current ice conditions. These sources include but are not limited to: RADARSAT Imagery, NOAA Imagery, Advanced Very High Resolution Radiometer, OLS Imagery, QuikScat Imagery, ERS Imagery, ENVISAT Imagery, MODIS, SAR Imagery, and SLAR Imagery (NIC 2018). Additional information about this data set is described by Assel (2003), Assel et al. (2013) and Wang et al. (2017). The GLERL ice grid (raster) data has a nominal spatial resolution of 1.275 km (1.63 2km ) at approximately 45 degrees N. Each grid cell in the data set includes an ice concentration value, given as the fraction of the total raster grid cell area that

Chapter 4 Chapter contains solid ice. The concentration values are provided in the following increments: 0%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% and 100%. Each raster file in the data set represents ice cover for an individual date within an ice season. For ice years 2008-2010, ice measurement frequency was approximately every two to four days. For seasons 2011-2017, measurement frequency was almost daily (Assel et al. 2013).

Ice concentration grid cell values provide an indication of when, where, and how much ice cover forms. Ice concentration values also provide the basis for determining the percentage of the area within the proposed sanctuary boundary that is covered by solid ice on any given day, which in turn allows for determination of the maximum extent of ice cover that was reached in a winter season.

The ice cover data allow for calculation of surface area covered by ice but does not provide an indication of ice thickness. Currently, there are no programs that measure ice thickness on a regular basis within the study area.

The time period for data analysis was from 2008 through 2017 to constrain the scope of this assessment to recent years. Ice grid data was imported into ArcGIS geodatabases (ESRI, v. 10.5). All calculations were performed in ArcGIS (ESRI, v. 10.5) using Spatial Analyst. The following parameters were calculated: first ice, last ice, length of ice season, number of ice days, percent spatial cover and maximum ice cover.

54 Ecological Assessment of Wisconsin - Lake Michigan Lake Ice

First Ice and Last Ice - First ice and last ice dates provide the information necessary to examine the variability of when an ice season starts each year and when it ends, as well as the variability of ice season length from year to year. First and last ice dates also help describe the spatial-temporal pattern of ice growth and decline during the annual ice cycle. For this report, only grid cells with greater than or equal to ten percent ice concentration values were used to determine first ice and last ice dates. This allows for analysis that describes when appreciable amounts of ice cover first start to form or ablate, and is consistent with similar ice cover analyses (Assel 2003, Assel et al. 2013, Wang et al. 2017, NSIDC 2018). The first and last ice dates were determined for each raster for each year, and then medians were calculated for the ten year study period.

Ice Season Length - The length of an ice season was determined by taking the difference between the first and last ice dates (where raster ice concentration was greater than or equal to 10 percent).

Number of Ice Days - There may be periods during any given ice season where ice melts entirely and later refreezes. Therefore, the total number of actual ice days reported was also calculated for each grid cell for ice seasons 2011 through 2017 in order to provide more detail on the temporal nature of ice cover (seasons 2008 through 2010 did not have sufficient data for this calculation). Yearly averages and a seven-year average were then also calculated.

Percent Spatial Cover - A three-step process determined percent cover for the study area boundary (to determine days of maximum ice cover). First, for each day in the ice season, and for each grid cell raster within the study area, the ice concentration value (fraction of a raster completely covered by ice) was multiplied by the area of the raster (1.63 km2). Second, the multiplication products were added together to obtain a total sum of all ice within the study area. Finally, the ice sum was divided by the total study area and multiplied by 100 to obtain the percentage of ice cover within the boundary of the study area (for each date). These calculations were performed for each year and then averages were calculated for the ten-year study period.

Maximum Percent Ice Cover - The maximum percent ice cover was determined by sorting the percent spatial cover results to yield the date with the highest percent cover reached within the study area in a given year. An average of each of the maximums was then calculated for the ten-year study period.

4.3 CURRENT CONDITIONS AND TRENDS 4 Chapter 4.3.1 Ice Season Temporal Characteristics During the ten year study period, ice Table 4.1. Ice season duration and total number of ice days in the study area. season duration ranged from 25 days in Season Year First Ice Last Ice Total Ice Days 2012 to 104 days in 2014 in the study Duration area (Table 4.1 and Figure 4.2A-B). 2008 24-Jan 13-Mar 50 not available 2009 22-Dec 10-Mar 79 not available The 2014 ice season also possessed the 2010 5-Jan 14-Mar 69 not available greatest annual ice concentration and 2011 16-Dec 8-Mar 83 43 greatest areal ice cover, and set a 41- 2012 20-Jan 13-Feb 25 6 year record for most ice cover on Lake 2013 30-Dec 28-Mar 89 33 Michigan (NOAA NWS 2014). For the 2014 10-Dec 23-Mar 104 90 ten year study period, observed first ice dates ranged from as early as December 2015 2-Dec 8-Mar 97 58 2 to as late as January 20 (Figure 4.3 and 2016 11-Jan 3-Mar 53 29 Table 4.1). 2017 16-Dec 14-Mar 89 33

Ecological Assessment of Wisconsin - Lake Michigan 55 Lake Ice

2008 2009 2010 2011

No Ice 1 – 14 15 – 29 There was There was There was 30 – 44 insufficient insufficient insufficient data to data to data to 45 – 59 calculate total calculate total calculate total number of ice number of ice number of ice 60 – 74 days for 2008. days for 2009. days for 2010. Number of Ice Days 75 – 89

No Ice Dec 1 - 14 irst t irst t irst t irst t Dec 15 - 31 Jan 1 - 14 Jan 15 - 31 Feb 1 - 14

First Ice Dates Feb 15 - 28 Mar 1 - 14 Mar 15 - 30

No Ice

Dec 1 - 14 st t st t st t st t Dec 15 - 31 r r r r Jan 1 - 14 Jan 15 - 31 Feb 1 - 14 Last Ice Dates Feb 15 - 28 Mar 1 - 14 Mar 15 - 30 Chapter 4 Chapter No Ice 1 – 9 % 10 – 19 % 20 – 29 % Concentrations Average Annual Ice Annual Average

o t t t t d d d d Yearly MaximumYearly Ice Cover Figure 4.2A. Lake ice characteristics in the study area 2008-2011.

56 Ecological Assessment of Wisconsin - Lake Michigan Lake Ice

2012 2013 2014 2015 2016 2017 Number of Ice DaysIce of Number

irst t irst t irst t irst t irst t irst t Dates Ice First

st t st t st t st t st t st t Last Ice Dates Ice Last r r r r r Avg.AnnualIce Conc. Chapter 4 Chapter

t t t t t t d d d d d d

r r Cover Max

Figure 4.2B. Lake ice characteristics in the study area 2012-2017.

Ecological Assessment of Wisconsin - Lake Michigan 57 Lake Ice

The median first ice dates for the period occurred in late December to early January (Figure 4.4A), while the median last ice dates were in early March (Figure 4.4B). The initial formation typically occurs along a narrow nearshore band (roughly 10 to 20 km outward from shore) following the entire coastline of the study area (Figure 4.4A). Ice growth continues outward from shore in another discernible band roughly 20 km in width toward the lake center during the remainder of January. The rest of the study area did not show median ice formation until February and, for the furthest reaches from shore, ice formation did not occur until March (Figure 4.4A). First ice appeared in December in five of the ten seasons, but only in one season Figure 4.3. Ice season duration by year in the study area for 2008 to 2017. (2014) did ice form in the first half of December. Last ice dates ranged from as early as February 13 to as late as March 28 (Figure 4.2A-B and Table 4.1). A. First Ice Median Dates B. Last Ice Median Dates First and Last Ice Dates

Dec 15 - 31 Jan 1 - 14 Jan 15 - 31 Feb 1 - 14

Chapter 4 Chapter Feb 15 - 28 Mar 1 - 14 Mar 15 - 30

Figure 4.4. Ten year medians of first ice and last ice dates in the study area.

Because each winter ice season (period of time between first and last observed ice dates) will typically include periods of time when ice melts and later reforms, the total number of ice days will be less than the duration of the ice season as a whole. Total ice days ranged from six days in 2012 to 90 days in 2014 (Table 4.1). Generally, the average number of ice days decreases with distance from shore with 0 to 10 km, 10-20 km and >20 km characterized by 30-44, 15-29 and 1-14 days of ice cover during the winter months. This trend holds for most

58 Ecological Assessment of Wisconsin - Lake Michigan Lake Ice of the study area, except for a 50 km swath of coast centered at Port Washington, which had on average 29 or fewer days of ice cover per year during the ten year period (Figure 4.5).

4.3.2 Ice Concentration and Spatial Coverage For the winter seasons of the ten-year study period, ice concentration values averaged between 10-19% for a narrow band (approximately up to 10 km outward from shore) following the shoreline of the study area. The rest of the study area averaged less than 10 percent ice concentration values over the ten year period (Figure 4.6A). It should be noted that although the 10 year average only reaches up to 19% coverage, there is a noticeable amount of inter-annual variability Figure 4.5. Average number of ice days in the study area for the 2008-2017 of ice concentration values (Figure 4.3). time period.

Maximum ice cover typically occurs between late January and mid-February (Figure 4.3 and Figure 4.7). Maximum yearly ice concentrations for the ten year period averaged 70-79% percent ice concentration values for a narrow band approximately 10 km outward from shore for most of the length of the study area shoreline (Figure 4.6B). In five of the 10 studied years, the spatial extent of maximum ice coverage was 100% of the proposed sanctuary, and varied between 25 and 70% for the remaining years (Figure 4.3).

A. Average Annual Percent Cover B. Average of Annual Maximum Percent Cover Chapter 4 Chapter Percent Ice Cover No Ice 1 – 9 % 10 – 19 % 20 – 29 %

30 – 39 % 40 – 49 %

50 – 59 % 60 – 69 % 70 – 79 %

Figure 4.6. Ten year percent ice cover averages in the study area

Ecological Assessment of Wisconsin - Lake Michigan 59 Lake Ice

Figure 4.7. Local polynomial regression (LOESS) curve summarizing percent ice cover of the study area for each ice season date across all years for seasons from 2008 to 2017. Chapter 4 Chapter

4.4 DISCUSSION As a whole, ice onset in the Great Lakes region occurs in early December, peaks around mid-February to early March and then declines until complete ice melt sometime between late April and late May (Wang et al. 2017). The study area differs from these general conditions in timing of first and last ice. The study area experiences ice onset somewhat later than the Great Lakes as a whole; typically late December to early January. Annual maximum ice cover generally occurs slightly earlier (late January to early February) than the rest of the lakes (mid- February). Final ice melt in the study area typically occurs in early March, ahead of the typical April/May Ice formation on Lake Michigan near St. Joseph 1998. Credit: M. time frame of the Great Lakes as a whole (Figure 4.2 McCormick (NOAA GLERL) and Figure 4.7).

60 Ecological Assessment of Wisconsin - Lake Michigan Lake Ice

The timing of first ice formation is driven by atmospheric conditions, such as air temperature, wind, and snowfall. However, the patterns of spatial development for first ice are related primarily to depth, with shallower areas forming ice earlier than deeper waters (Assel 2003). This pattern is observed in the study area, where, as noted above, ice forms earliest in narrow bands following along the shallower nearshore areas (roughly less than 30 meters depth) and grows eastward and outward into deeper waters as the cold weather season continues.

The last ice charts in Figure 4.2 show that the study area does not have discernible spatial or temporal patterns over the ten year period. This is not surprising given that ice ablation is dependent on many variable factors, including available energy at the lake surface, in the water column (heat content), existing amount of ice cover, and ice movement by winds and currents (Assel 2003).

Prior to December, ice cover is unlikely to be an impediment to access of underwater cultural resources and related management equipment, such as buoys, anywhere in the study area. Since ice forms close to shore earliest, lake access further than 30 km offshore is typically unaffected by ice cover in most years until late January to early February.

We did not detect a temporal pattern in ice cover metrics, but we believe this may be because the investigated 10-year time period was too short to detect long-term trends amidst significant inter-annual variability. Wang et al. (2017) have shown annual mean ice cover since 1973 in Lake Michigan has experienced a negative trend, decreasing by -0.36% per year. This decrease translates to a 16% loss in annual average ice cover since 1973 (Wang et al. 2017). If this lake-wide trend continues, the management, commercial and recreational activities limited by lake ice would become less of a challenge over time. However, planning for such a change is risky given the high degree of inter-annual variability of ice cover means poor predictability of medium- and long-range ice conditions (Wang et al. 2012). Additionally, long-term decreases in ice cover could potentially lower water levels and limit the cargo capacity of Chapter 4 Chapter large commercial vessels, because less ice cover leads to greater evaporation during the winter and spring (NOAA NCEI 2014).

Lake ice likely plays a major role in the degradation of nearshore submerged cultural heritage resources, but the extent of ice’s impact is not well studied. Several of the shipwrecks known in the study area are shallower than 1 m deep, and surface ice may commonly reach these depths (Sleator 1995). Ice also plays an indirect role in the management of shipwrecks by influencing Freighter moving through ice-laden channel, Great the timing of dive buoy deployment and retrieval, and times Lakes. Credit: NOAA GLERL when documentation and impact assessments are feasible.

While beyond the scope of this study, coastal managers along the study area could benefit from future research assessing how ice cover affects shipwrecks, as well as coastal recreational activities, including ice fishing, ice skating, boating and scuba diving. These activities will presumably be impacted by timing of ice onset and ablation and the certainty of ice cover predictions.

Ecological Assessment of Wisconsin - Lake Michigan 61 Lake Ice 4.5 REFERENCES Assel, R.A. 2003. Great Lakes Ice Cover, First Ice, Last Ice, and Ice Duration: Winters 1973-2002. NOAA Office of Oceanic and Atmospheric Research, Great Lakes Environmental Research Laboratory. NOAA Technical Memorandum GLERL-125. Ann Arbor, MI. 49 pp.

Assel, R.A., J. Wang, A.H. Clites, and X. Bai. 2013. Analysis of Great Lakes Ice Cover Climatology: Winters 2006- 2011. NOAA Office of Oceanic and Atmospheric Research, Great Lakes Environmental Research Laboratory. NOAA Technical Memorandum GLERL-157. Ann Arbor, MI. 27 pp.

Brown, R., W. Taylor, and R.A. Assel. 1993. Factors affecting the recruitment of lake whitefish in two areas of northern Lake Michigan. Journal of Great Lakes Research 19(2): 418-428. doi: https://doi.org/10.1016/S0380- 1330(93)71229-0

NIC. 2018. Great Lakes Ice Analysis Products. U.S. National Ice Center. Online: http://www.natice.noaa.gov/ products/great_lakes.html (Accessed 30 April 2019)

NOAA GLERL. 2018. Great Lakes Ice Cover. NOAA Office of Oceanic and Atmospheric Research, Great Lakes Environmental Research Laboratory. Online: https://www.glerl.noaa.gov/data/ice (Accessed 30 April 2019)

NOAA NCEI. 2014. National Climate Report - February 2014, Great Lakes Ice. NOAA National Centers for Environmental Information. Online: https://www.ncdc.noaa.gov/sotc/national/2014/2/supplemental/page- 6/ (Accessed 30 April 2019).

NOAA NWS. March 8, 2014 Record Ice Coverage on Lake Michigan. NOAA , Weather Forecast Office, Milwaukee/Sullivan, WI. Online: https://www.weather.gov/mkx/030814_Record_Ice_ Coverage_on_Lake_Michigan (Accessed 30 April 2019)

NSIDC. 2018. All About Sea Ice: Data Terminology. National and Ice Data Center. Online:http://nsidc.org/ cryosphere/seaice/data/terminology.html (Accessed 30 April 2019)

Chapter 4 Chapter Sleator, F.E. 1995. GLERL Great Lakes Ice Thickness Data Base, 1966-1979, Version 1. Data set ID: G00803. National Snow and Ice Data Center. Online: https://nsidc.org/data/G00803 (Accessed 30 April 2019). doi: https://doi.org/10.7265/N5KW5CXG

Vanderploeg, H.A., S.J. Bolsenga, G.L. Fahnenstiel, J.R. Liebig, and W.S. Gardner. 1992. Plankton ecology in an ice-covered bay of Lake Michigan: Utilization of a winter phytoplankton bloom by reproducing . Hydrobiologia 243(1): 175-183. doi: https://doi.org/10.1007/BF00007033

Wang, J., X. Bai X., H. Hu, A. Clites, M. Colton, and B. Lofgren. 2012. Temporal and Spatial Variability of Great Lakes Ice Cover, 1973-2010. Journal of Climate 25: 1318-1329. doi: https://doi.org/10.1175/2011JCLI4066.1

Wang, J., J. Kessler, F. Hang, H. Hu, A.H. Clites, and P. Chu. 2017. Great Lakes Ice Climatology Update of Winters 2012-2017: Seasonal Cycle, Interannual Variability, Decadal Variability, and Trend for the period 1973-2017. NOAA Office of Oceanic and Atmospheric Research, Great Lakes Environmental Research Laboratory. NOAA Technical Memorandum GLERL-170. Ann Arbor, MI. 14 pp.

62 Ecological Assessment of Wisconsin - Lake Michigan Chapter 5 Invasive Mussels Simon Pittman1,2,3, Charles Menza1, Ashley Elgin4

Mussel bed, Lake Michigan. Credit: NOAA NOS/NCCOS

5.1 INTRODUCTION This chapter focuses on characterizing spatial and temporal patterns of invasive zebra (Dreissena polymorpha) and quagga (Dreissena rostriformis bugensis) mussels in the study area and highlights some of the known ecological consequences. Both species are filter-feeding biofoulers that have fundamentally transformed the physical, chemical, and biological components of Lake Michigan’s ecosystem and are considered a threat to underwater maritime heritage (Simpkins and Jones 1997). Both mussel species are considered key drivers of a regime shift throughout the Great Lakes that has changed nutrient and energy dynamics, altered food webs, and incurred economic costs. Here we characterize changes in mussel abundance patterns in the study area and discuss how their presence and associated ecological impacts are relevant to maritime heritage.

Zebra and quagga mussels are non-indigenous freshwater dreissenid mussels introduced into the Great Lakes in the late 1980s from their native range in Eurasia. In the 1990s they quickly spread throughout the Great Lakes and caused severe and pervasive ecological changes that are widely evident and well-documented (Nalepa et al. 2009, Nalepa and Schloesser 2014). Zebra mussels were first recognized in Lake Michigan in 1990, only two years after they were first identified in the Great Lakes region. One of the first sightings in Lake Michigan was within the study area off Sheboygan, WI (Nalepa et al. 2014). Quagga mussels were first observed in Lake Michigan in 2000 on the heels of the invasion (Fleischer et al. 2001) and have since flourished (Rowe et al. 2015a).

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch. Silver Spring, MD 2 CSS, Inc. Fairfax, VA 3 Seascape Analytics Ltd. Plymouth, UK 4 NOAA Oceanic and Atmospheric Research, Great Lakes Environmental Research Laboratory. Muskegon, MI

Ecological Assessment of Wisconsin - Lake Michigan 63 Invasive Mussels

Both invasive mussels are prolific breeders and filter-feeders, and have dramatically altered the Great Lakes ecosystem, predominantly through depressing plankton densities, altering nutrient cycling, outcompeting native species, and fouling habitats (Vanderploeg et al. 2010, Pothoven and Fahnenstiel 2013, Yousef et al. 2014). Quagga mussels are arguably now a foundation species, given their strong role in structuring the benthic and pelagic lake communities, and as a generator of new biogenic habitat.

Most of the shipwrecks in the study area are now colonized by invasive mussels. Zebra and quagga mussel’s propensity to attach to hard substrates Quagga (Dreissena rostriformis bugensis; top row) and zebra such as shipwrecks has diminished the visible (Dreissena polymorpha; bottom row) mussels. Photo credit: NOAA detail among and potentially worsened OAR/GLERL structural integrity of artifacts (Watzin et al. 2001, Meverden and Thomsen 2008, Thomsen and Zant 2016, Thomsen et al. 2017). However, invasive mussels have also positively impacted maritime heritage conservation by increasing water clarity. Greater clarity has led to increased visibility and accessibility of shipwrecks to scientists, managers, and the public.

5.2 DATA AND METHODS This report makes use of data and specialist knowledge generated from an existing long-term benthic monitoring program coordinated by the NOAA Great Lakes Environmental Research Laboratory (GLERL), lake-wide predicted distribution maps of invasive mussels, and a lakebed survey focused off the coastof Manitowoc, Wisconsin to document invasive mussel abundance and biomass in the study area (Table 5.1). The monitoring program established by GLERL uses a lake-wide distribution of benthic grab samples to monitor the macroinvertebrate community across Lake Michigan. This whole-lake survey is now conducted as a part of the Coordinated Science and Monitoring Initiative (CSMI) research cycle and receives support through the Great Lakes Restoration Initiative.

Table 5.1. Data types and sources. Dataset Data type Source NOAA Great Lakes Environmental Research Dreissenid mussel density and biomass Mussel density and biomass from Laboratory (GLERL), Great Lakes Restoration (per square meter) at sample sites at benthic grab samples at selected Initiative (via the Environmental Protection

Chapter 5 Chapter depths of between 6 and 208 m georeferenced stations Agency [EPA] and the United States Geological Survey [USGS]) turbidity index (m-1) See Nalepa et al. 2014, 2017 Monthly chlorophyll a concentration (ug/L) Lake-wide geostatistical models of mussel biomass (1994-95, 2000, 2005, 2010) in Interpolated point data from Supplementary material from Rowe et al. 2015a grams ash-free dry tissue mass (g AFDM geostatistical model with permission from author. m-2) NOAA National Centers for Coastal Ocean Mussel coverage observations at Manitowoc lakebed survey Science (NCCOS), Office of National Marine 362 drop camera stations Sanctuaries (ONMS), and GLERL

64 Ecological Assessment of Wisconsin - Lake Michigan Invasive Mussels

The long-term benthic survey includes sample sites across the entirety of Lake Michigan and was conducted in 0 approximately five-year increments ¯ (i.e., 1994/1995, 2000, 2005, 2010 and 2015). In each year, 90 to 160 stations Kewaunee! were sampled across Lake Michigan EEE1 E5 and between five and 17 stations were #### # sampled within the study area (Figure 0 Manitooc 5.1). The methods used for the long- survey area # term benthic monitoring program are 5 described in detail by Nalepa et al. (2014). Manitowoc! #5

Rowe et al. (2015a) developed lake-wide predicted distribution maps of invasive S1 S 0 ##### mussels using the long-term benthic S S5 survey and a geostatistical model with a categorical depth covariate. Predictive Sheboygan! model performance and thorough explanation of model development is 0 provided by Rowe et al. (2015a).

The Manitowoc lakebed survey used a Port combination of sidescan and multibeam echosounders, and underwater Washington! 2 camera imagery to map 83 km (23 0 mi2) of lakebed off Manitowoc, WI in 2017 (Figure 5.1; see Chapter 2). This chapter focuses on mussel coverage 0 0 0 patterns in camera imagery at 362 stations, whereas Chapter 2 provides Milwaukee! m maps of mussel coverage interpreted from sonar data. The survey comprises 0 0 Figure 5.1. Location of long-term benthic survey stations (black triangles) and the approximately 3% of the study area and Manitowoc lakebed survey (shaded polygon) in the study area. Solid and dashed is focused on nearshore lakebed, yet it outlines refer to proposed sanctuary boundary alternatives A and B, respectively. provides finer-scale spatial information to complement the long-term lake- 5 Chapter wide benthic monitoring program and geostatistical models, and provides new information on rocky substrates.

Dense mussel bed in the Lake Michigan study area. Credit: NOAA NOS/NCCOS

Ecological Assessment of Wisconsin - Lake Michigan 65 Invasive Mussels 5.3 CURRENT CONDITIONS AND TRENDS Invasive mussels are a relatively new pressure and ecosystem component of Lake Michigan that have been thoroughly tracked by the long-term benthic monitoring program since the very beginning of the invasion in the early 1990’s (Nalepa et al. 2014). The resulting data (Nalepa et al. 2014, 2017) and derived predictive maps (Rowe et al. 2015a) document the invasion and rapid expansion of both zebra and quagga mussels throughout Lake Michigan (Figure 5.2). Zebra and quagga mussels were first detected in Lake Michigan by GLERL in 1994 and 2000, respectively, and were first recorded in the study area in 2000 and 2005, respectively. In 1994 and 2000, zebra mussels were found throughout much of northern Lake Michigan and were common in nearshore habitats throughout the lake, but were not ubiquitous. In the study area, zebra mussels attained high densities, particularly between Manitowoc and Sheboygan before quagga mussels displaced them sometime between 2000 and 2005.

The mussel invasion followed patterns observed in other lakes, with zebra mussels establishing onhard substrates in shallow depths, then later quagga mussels attaining relatively high densities in moderate depth regions (30-50 m) and outcompeting zebra mussels over time, in all but shallow, productive regions (Mills et al. 1999, Karatayev et al. 2015). The displacement of zebra mussels by quagga mussels from 2000 to 2010 is clearly visualized in lake-wide density maps (Figure 5.2)(Nalepa et al. 2017). Chapter 5 Chapter

Figure 5.2. Zebra (top panel) and quagga mussel (bottom panel) densities (no./m2) over time in Lake Michigan. Small red crosses and white areas denote sampling sites and zero mussel density, respectively. Maps from Nalepa et al. 2017.

66 Ecological Assessment of Wisconsin - Lake Michigan Invasive Mussels

In 2005, quagga mussels were pervasive in shallow (0-30 m) and moderate depths (30-50 m) and had attained higher densities than zebra mussels had at their zenith. All but the deepest portions of Lake Michigan were colonized. Five years later in 2010, quagga mussels had colonized deep water habitats too, and could be found throughout Lake Michigan at all depths, including the deepest benthic monitoring station at 207 m (Nalepa et al. 2014). In 2015, quagga mussels were found at every single station in the study area and in 99% of lake-wide stations, with increases in density and biomass at depths greater than 90 m (Nalepa et al. 2017).

The average density (standard error, SE) of quagga mussels across all stations in the study area from 2005 to 2015 was 9,509 per m2 (SE = 1,225 per m2) with high variability among stations. The highest mussel densities were recorded at stations between 30 and 90 m deep, with substantially fewer mussels at the only station deeper than 90 m (station 9574; Figure 5.3).

There was also high variability in mussel densities among years within each station (Figure 5.3). Most stations showed a peak in mussel density between 2005 and 2010, and a decrease in mussel density between 2010 and 2015. This decrease in density mirrors the lake-wide pattern observed by Nalepa et al. (2017). However, while the density of mussels has generally decreased, biomass has shown some increases because of the mussels getting larger (Nalepa et al. 2017). Indeed, mean mussel size at the study area sites increased approximately 29% (range: 0-47%) from 2010-2015 (Elgin, unpublished data). This is due in part to a decline in the relative

10000 ●

7500 ● 0−30 m 5000 ● 2500 ● ● 0 ● 30000 ● ● Station 31−50 m ● KE−1

2) 20000 ● ● SY−1 ● ● ● ● SY−2 10000 ● ● ● ● KE−2 ● ● ● 82902 0 ● ● ● KE−3 ● 20000 ● 82882 ● 51−90 m ● SY−4 15000 ● ● ● ● SY−5 ● ● 10000 ● ● ● 9577 Mussel density (no./m 5000 ● ● KE−5 ● ● 9574 0 ● ● ● 5 Chapter ● 500

400 >90 m 300 200 ● 100 0 ● ● ● 1995 2000 2005 2010 2015 Year Figure 5.3. Changes in quagga mussel density (no./m2) at long-term benthic monitoring stations within the study area, separated by depth zone. Note the different y-axis scales among depth zones.

Ecological Assessment of Wisconsin - Lake Michigan 67 Invasive Mussels

number of small mussels, which indicates reduced recruitment. A similar phenomena was observed in offshore sites in Lake Erie and was attributed to food limitation (Karatayev et al. 2018). It is worth noting that even with these declines in density, quagga mussels are still present in sufficient numbers to have economic and ecological impacts. In water deeper than 90 m, mussel density has continued to increase at the single station deeper than 90 m within the study area (i.e., station 9574) and lake-wide (Nalepa et al. 2017).

Although the long-term benthic monitoring data have wide spatial and temporal coverage, and good replication, it does not cover all lakebed types. Long-term monitoring focuses on sites characterized by fine unconsolidated sediments because the Ponar grabs used for benthic sampling cannot effectively sample cobbles or hard substrates. Consequently, there is less information available on invasive mussels on coarse unconsolidated sediments and hard (rocky) substratum in commonly found in the study area (Janssen et al. 2005). This bias particularly limits monitoring for zebra mussels which are most commonly found on cobbles and hard substrates. Fortunately, there is a growing collection of mussel data on hard substrates in the nearshore of western Lake Michigan (Janssen et al. 2005, Waples et al. 2005, Creque et al. 2010; Chapter 2 of this report).

100 ●

●

75

50 ● ●

● Mussel coverage (%) Mussel coverage 25

●

● 0 n = 21 n = 43 n = 31 n = 15 n = 101 n = 56 n = 79 n = 9 Chapter 5 Chapter Patchy cobbles Patchy Patchy hard clay Patchy Scattered cobbles Scattered hard clay Continuous cobbles Continuous Deep fine sediment * Continuous hard clay Continuous Shallow fine sediment * Shallow Dominant substrate type Figure 5.4. Invasive mussel coverage among dominant lakebed substrate types off Manitowoc, WI. Estimates of mussel coverage are from underwater observations collected by a drop camera in 2017. Shallow and deep fine sediment are divided into depths shallower and deeper than 25 m, respectively. Box and whisker plots show the distributional characteristics of mussel coverage within each dominant substrate type. The horizontal line that divides the box into two parts represents the median, the top and bottom edges of the box show the upper and lower quartiles, the vertical lines show the range to the highest and lowest values excluding outliers, and black dots identify outliers. Outliers are outside 1.5 times the interquartile range above the upper quartile and below the lower quartile. The number of interpreted camera images is identified beneath each box and whisker.

68 Ecological Assessment of Wisconsin - Lake Michigan Invasive Mussels

In the Manitowoc lakebed survey, invasive mussels were detected across all observed depths from 2 to 32 m (5 to 110 feet) and across a diversity of fine unconsolidated and rocky substrates. Within this depth range, mussels colonized the vast majority of boulders and cobbles, although colonization dropped substantially at depths shallower than 6 m (Figure 5.4). Mussels were very rare on hard clay substrate, although lakebed classified as hard clay contained mussels on ancillary boulders and cobbles. On fine unconsolidated substrates, mussel colonization patterns shifted at a depth of approximately 25 m. At depths shallower than 25 m, invasive mussels were uncommon and usually distributed as isolated druses on fine sediments. Mussel beds on fine sediments were rare and were recorded at only four of 79 sites shallower than 25 m (5% of sites). At depths deeper than 25 m, rocky substrate was not recorded, and mussels were abundant and organized as densely packed beds overlaying fine unconsolidated sediments (Figure 5.4). See Chapter 2 for more information on invasive mussel spatial patterns in the surveyed area.

10 The long-term benthic monitoring data 10 0 10 0 0 m 0 and Manitowoc lakebed survey reveal ¯ 0 the study area has been impacted by Algoma 0 100 10 0 mi Stony Cree eef invasive mussels for the past 20 years 00 and that densities and biomass are not Green Bay Eleven athom eef Kewaunee uniformly distributed in time or space. America We developed a map of invasive mussel

100 0 exposure by averaging 1994/1995 ouse Simmons through 2010 lake-wide geostatistical Two Milton biomass predictions (Figure 5.5; Rivers ernon 00 2015 geostatistical predictions were not available to include in this map). Manitowoc enry ust oss Recognizing there are caveats to using the geostatistical models, most notably the focus on unconsolidated Selah Chamberlain fine sediments, these maps indicate 100 a broad region between 30 m and 50 Sheboygan m deep that has likely experienced Proposed Sanctuary Alternative A 0 greater cumulative mussel exposure etty aylor Proposed Sanctuary Alternative than other locations. We delineated the Contours m ! non shiprec areas above the top 90th percentile of yron ? Potential shiprec Advance mussel exposure relative to whole lake Port # Selected Spaning or Nursery ocations to reference areas with the greatest Washington istoric fish spaning areas Invasive Mussel Exposure exposure to mussels. One of the lake’s 0 Grafton g AFDM m-2 mussel exposure hotspots covers a broad 0 50th percentile

10 0 100 5 505 percentile band running through the middle of the Mequon 5 Chapter 5 15 50 percentile study area. This area of high exposure Milwaukee 15 15 0th percentile contains different types of important 0 0 and sensitive lake resources including, Figure 5.5. Map showing invasive mussel exposure alongside locations of known and potential shipwrecks, and shipwrecks, historic fish spawning areas (Coberly and Horrall 1980) and selected historical fish spawning and nursery spawning or nursery areas (Goodyear et al. 1982). Invasive mussel exposure is the average of estimated 1994/1995, 2000, 2005, and 2010 lake-wide geostatistical habitats (Coberly and Horrall 1980, biomass predictions provided by Rowe et al. (2015a). Mussel exposure is classified Goodyear et al. 1982). into <50th, 50-75th, 75-90th, and >90th percentile groups. Only shipwrecks and spawning or nursery areas within the top 90th percentile of mussel exposure are labeled.

Ecological Assessment of Wisconsin - Lake Michigan 69 Invasive Mussels 5.4 DISCUSSION The dreissenid mussel invasion in the Great Lakes is a human-caused, but entirely unintentional, bioengineering of the ecosystem. High rates of filter feeding by mussels has led to increased water clarity and a cascading chain of consequences to the food web, as well as the structure and function of the ecosystem. The lake looks and functions quite differently now than it did 40-years ago before the mussel invasions.

The ecosystem regime shift has been detected and monitored through extensive scientific studies and long- term monitoring programs. To support an ecosystem-wide perspective of the changing conditions in the study area we have constructed a diagrammatic conceptual model of dreissenid-induced impacts to the using evidence from the scientific literature (Figure 5.6).

The model documents environmental impacts that have had complex cascading consequences to ecosystem conditions attributed primarily to the invasion of dreissenid mussels since the 1980s. Based on the scientific literature (see cited literature in Figure 5.6 diagram and the reference section), this diagram shows the linkages (direct and indirect) between mussels and other ecosystem components and also the potential impacts on the condition of maritime heritage (primarily shipwrecks) on the lakebed. The conceptual diagram depicts a major ecosystem regime shift where productivity and energy flow has shifted from a pelagic-dominated ecosystem to a lakebed (benthic)-dominated ecosystem – a process termed ‘benthification’ (Higgins and Vander Zanden 2010, Mayer et al. 2013, Pilcher et al. 2017).

In the Great Lakes, the relative contribution of benthic processes has increased dramatically since the introduction of dreissenid mussels. The mussel-dominated benthic community is now capable of controlling ecological processes and dynamics that were once largely dominated by pelagic processes. Long-term (>15 years) data from several lakes suggest that dreissenid mussels are driving this “benthification” even more than recent nutrient reductions entering the lakes via nutrient abatement programs (Mayer et al. 2013). In Lake Michigan, Fahnenstiel et al. (2010) document a major decrease in chlorophyll that occurred during the winter-spring transition with widespread decline of the spring phytoplankton bloom. The impacts of dreissenid feeding during this winter-spring period when the water column is well-mixed has a major impact on production throughout the year (Vanderploeg et al. 2002, Rowe et al. 2015b). As a result, large offshore regions of Lake Michigan have transformed from intermediate levels of productivity Chapter 5 Chapter (mesotrophic) to low levels of primary productivity Mussels on Lake Michigan lakebed. Credit: NOAA NOS/NCCOS (oligotrophic)(Mida et al. 2010).

It is clear that mussel feeding, excretion, and physical engineering, have affected both pelagic and benthic food webs. Fish that depend on these energy pathways have also been negatively impacted and a shift in habitat use to nearshore benthic zones has been observed for many fishes (Simpson et al. 2016, Fera et al. 2017). For example, a significant decline in the populations of Diporeia and of Mysids, crustaceans that were once an abundant nutritious (lipid-rich) food of many commercially and recreationally important fish species, has coincided with the spread of dreissenid mussels (Nalepa et al. 2009, Bunnell et al. 2014, Madenjian et al. 2015, Pothoven and Vanderploeg 2017).

70 Ecological Assessment of Wisconsin - Lake Michigan Invasive Mussels growth growth 1998 2015 toxic metals metals toxic et al. et al. 1999 al. et and Jones 1997 beach users beach Claiborne 2000 Claiborne Watzin et al. 2001 LaValle biodeposit Benthic algal Karatayev McLaughlin et al. Increased recreational recreational Increased Simkins due to improved visibility visibility to due improved SCUBA diving boating and diving SCUBA unappealing to divers and and divers to unappealing Toxin bioaccumulation Toxin Deterioration of of Deterioration wrecks, wrecks than zebra mussels mussels zebra than wrecks in sediments on shipwrecks on sediments in and steel. and in steel. Bacteria mussel accelerated corrosion of corrosion of accelerated iron Weight Weight mussels of on wrecks Quagga invade deeper water water deeper invade Quagga may impact structural stability? structural may impact beds causes pitting pitting causes beds of the metal Mussels 2017 Pathogens Chun et al. 2015, a lgae Zanden ecosystems and heritage ecosystems mercury et al. 2005 al. et - 2010 et al. 2006 al. et et al. 2015 al. et benthos on production Lepak Less energy for Wilson zooplankton and and zooplankton Methyl Bootsma Higgins and Vander resources Increased water clarity Increased nuisance nuisance Increased Binnie et al. 2000 (see Water Quality Water (see Quality chapter) maritime heritage heritage maritime Colonized submerged submerged Colonized 2015 2015 mussels mussels Hypoxia Tyner 2013 Tyner Turner 2010 2010 Turner Lesht et al. 2004 al. et Hecky 2010 Warner and decrease in in decrease pelagic Phosphorus increase increase Phosphorus Mosley and Bootsma in benthic nearshore & & nearshore benthic in et al. 2016 al. et et al. al. et 2010 et al. al. et 2013 shift 2010 regime regime Yousef et al. 2014 Rowe et al. 2015a al. et Rowe Kerfoot Ecosystem Ecosystem Levinton 1994 Pothoven et al. 2016 Mida et al. 2010 Mayer Mayer Fahnenstiel Pilcher et al. 2017 Vanderploeg et al. 2010 Zanden of spring & winter blooms blooms winter & spring of Diverted nutrients and and nutrients Diverted Filtered plankton and decline decline and plankton Filtered Higgins Vanderand Zanden et al. 2014 al. et et al. 2017 al. et productivity, shunt” “nearshore productivity, Fera Simpson et al. 2016 Turschak of Quagga and Zebra Causal link uncertain nearshore benthic benthic zone nearshore Shift in fish habitat use to to use habitat in fish Shift Higgins and Vander Mysis & )? et al. 2011 et al. 2009 et al. 2012 al. et declines et al. 2001 al. et habitats et al. 1997 al. et Nalepa Barbiero Pothoven et al. 2017 Diporeia Chapter 5 Chapter Burlakova Karatayeval. 2002 et Modified benthic benthic Modified Knoll et al. 2008 community ( Increase in in Increase toxic Ricciardi Vanderploeg Change in benthic in benthic Change macroinvertebrate macroinvertebrate cyanobacterial blooms blooms cyanobacterial 2014 2014 resulting in in resulting et al. 2015 et al. 2012 al. et et al. 2005 al. et planktonic et al. declines et al. 2005 al. et et al. 2010 al. et et al. 2006 al. et et al. 2012 al. et outcompete ogan et al. 2007ogan et Yule et al. 2006 al. et Yule Kornis H Fera et al. 2015 al. et Fera fish Bunnell parasites, viruses parasites, Hondorp round goby goby round Bioaccumulation of of Bioaccumulation Madenjian Kornis Wilson et al. 2006 Wilson zebra mussels zebra Nalepa contaminants, toxins, toxins, contaminants, Baldwin et al. 2002 Reduced Bootsma Karatayeval. 2015 et Increase in in Increase food & for nuisance a lgae nuisance for habitat for invasive invasive for habitat native mussels and mussels native Increased substrate substrate Increased food for fish Pothoven and Fahnenstiel Quagga Conceptualizing the effects the effects Conceptualizing Figure 5.6. A conceptual model showing the impacts of quagga and zebra mussels on the study area. mussels on the study the impacts of quagga and zebra model showing Figure 5.6. A conceptual

Ecological Assessment of Wisconsin - Lake Michigan 71 Invasive Mussels

Mussel colonization increases the structural complexity of the lakebed which has resulted in an increase in some benthic invertebrates through provision of settlement substrate, food resources and refuge from predators (Karatayev et al. 2002). For instance, the round goby (Neogobius melanostomus), an invasive fish species that is well adapted to living with mussels has proliferated across mussel beds and has become a key prey item for higher trophic level predators such as Double-crested Cormorants (Phalacrocorax auritus), lake trout (Salvelinus namaycush), burbot (Lota lota), lake whitefish ( clupeaformis), and Common Loons (Gavia immer)(Pothoven and Madenjian 2008, Madenjian et al. 2011, Kornis et al. 2012, Foley et al. 2017). There is increasing concern Round goby perched on zebra mussels. Zebra mussels have increased over the bioaccumulation of sediment-related structural complexity of the lakebed, ideal for round gobies. Credit: contaminants and toxins from the mussel beds USFWS National Digital Library. up through the food web (Kornis et al. 2012).

Large abundances of phytoplankton act much like a forest canopy does, limiting light to primary producers in deeper habitats. Dreissenid mussels can filter the phytoplankton out of more than one liter of water per mussel per day (Diggins 2001), which allows for deeper light penetration. In southwest Lake Michigan, for example, Secchi depth increased from 3.98 m in the 1980s before mussels invaded Lake Michigan to 5.21 m in the 1990s after the invasion (University of Wisconsin WATERBase, http://www.waterbase.glwi.uwm.edu/ index.php). Where the filtration activity of mussels has exceeded phytoplankton growth rates, increases in water clarity together with an increase in biogenic substrate has promoted dramatic growth of benthic algae and macrophyte biomass including the nuisance algae species Cladophora (Auer et al. 2010, Shuchman et al. 2013, Bootsma et al. 2015, Brooks et al. 2015).

Of course, the impacts of invasive dreissenid mussels are not limited to the ecological realm. The Wisconsin Historical Society (WHS) has documented the impact of mussel colonization on numerous shipwrecks within the study area and has found thick layers of quagga mussels

Chapter 5 Chapter on several shipwrecks, including the Wisconsin, , Grace A Channon, and S.C. Baldwin (Meverden and Thomsen 2008, Thomsen and Zant 2016, Thomsen et al. 2017).

Invasive mussels physically impact archaeological sites and decrease “archaeological visibility” by covering and obscuring structures underlying the thick beds. In addition, growth of Cladophora facilitated by invasive mussels, has reduced La Salle Shipwreck Rouse Simmons, Lake Michigan. Credit: Tamara Thomsen, visibility of shallow water wrecks such as Wisconsin Historical Society

72 Ecological Assessment of Wisconsin - Lake Michigan Invasive Mussels and Lookout (Thomsen and Zant 2016). Mussel colonization can accelerate corrosion, and increase rates of breakage through higher water turbulence over the uneven surface of attached shells and added weight from high densities of shells (Watzin et al. 2001, NOAA ONMS 2013, Thomsen and Zant 2015). As early as 1993, WHS reported that divers had first discovered invasive mussels on the wreck of Francis Hinton with initial colonization having obscured much of the vessels wooden structure making it difficult to document the condition of the wreck (Jensen et al. 1995). More recently, Mertes et al. (2017) documented mussels have modified Shipwreck Francis Hinton, Lake Michigan, colonized extensively by degradation patterns of the shipwreckWisconsin . mussels and algae. Credit: NOAA NOS/NCCOS

Knowing where invasive mussel impacts do not occur can be just as important as knowing where they do. WHS has documented numerous shipwrecks with little or no mussel colonization. Nearshore shipwrecks at sites influenced by heavy wind and ice action or sand burial, such as theGrape Shot, Alaska and Lookout, had no or very low mussel colonization when they were assessed in 2015. Unlike most shipwrecks colonized by mussels, these wrecks were noted as well-preserved and allowing for detailed observations (Thomsen and Zant 2016). Important habitats influenced by the same erosive dynamics are likely sheltered from invasive mussels as well.

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Ecological Assessment of Wisconsin - Lake Michigan 75 Invasive Mussels

Karatayev, A.Y., L.E. Burlakova, and D.K. Padilla. 2015. Zebra versus quagga mussels: a review of their spread, population dynamics, and ecosystem impacts. Hydrobiologia 746(1): 97-112. doi: https://doi.org/10.1007/ s10750-014-1901-x

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Kerfoot, W.C., F. Yousef, S.A. Green, J.W. Budd, D.J. Schwab, H.A. Vanderploeg. 2010. Approaching storm: disappearing winter bloom in Lake Michigan. Journal of Great Lakes Research 36(Suppl. 3): 30-41. doi: https:// doi.org/10.1016/j.jglr.2010.04.010

Knoll, L.B., O. Sarnelle, S.K. Hamilton, C.E. Kissman, A.E. Wilson, J.B. Rose, and M.R. Morgan. 2008. Invasive zebra mussels (Dreissena polymorpha) increase cyanobacterial toxin concentrations in low-nutrient lakes. Canadian Journal of Fisheries and Aquatic Sciences 65(3): 448-455. doi: https://doi.org/10.1139/f07-181

Kornis, M.S., N. Mercado-Silva, and M.J. Vander Zanden. 2012. Twenty years of invasion: a review of round goby Neogobius melanostomus biology, spread and ecological implications. Journal of Fish Biology 80(2): 235- 285. doi: https://doi.org/10.1111/j.1095-8649.2011.03157.x

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LaValle, P.D., A. Brooks, and C.C. Lakhan. 1999. Zebra mussel wastes and concentrations of heavy metals on shipwrecks in western Lake Erie. Journal of Great Lakes Research 25(2): 330-338. doi: https://doi.org/10.1016/ S0380-1330(99)70741-0

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Mayer, C.M., L.E. Burlakova, P. Eklöv, D. Fitzgerald, A.Y. Karatayev, S.A. Ludsin, S. Millard, E.L. Mills, A.P. Ostapenya, L.G. Rudstam, B. Zhu, and T.V. Zhukova. 2013. The benthification of freshwater lakes: exotic mussels turning ecosystems upside down. pp 575-586. In: T.F. Nalepa and D.W. Schloesser (eds.), Quagga and zebra mussels: biology, impacts, and control. 2nd edition. CRC Press. Boca Raton, FL. 815 pp.

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Nalepa, T.F., D.L. Fanslow, and S.A. Pothoven. 2010. Recent changes in density, biomass, recruitment, size structure, and nutritional state of Dreissena populations in southern Lake Michigan. Journal of Great Lakes Research 36 (Suppl. 3): 5-19. doi: https://doi.org/10.1016/j.jglr.2010.03.013

Nalepa, T.F., D.L. Fanslow, G.A. Lang, K. Mabrey, and M. Rowe. 2014. Lake-wide benthic surveys in Lake Michigan in 1994-95, 2000, 2005, and 2010: Abundances of the amphipod Diporeia spp. and abundances and biomass of the mussels Dreissena polymorpha and Dreissena rostriformis bugensis. NOAA Technical Memorandum GLERL-164. NOAA Great Lakes Environmental Research Laboratory. Ann Arbor, MI. 21 pp.

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Ecological Assessment of Wisconsin - Lake Michigan 77 Invasive Mussels

Pothoven, S.A., and C.P. Madenjian. 2008. Changes in Consumption by Alewives and Lake Whitefish after Dreissenid Mussel Invasions in Lakes Michigan and Huron. North American Journal of Fisheries Management 28(1): 308-320. doi: https://doi.org/10.1577/M07-022.1

Pothoven, S.A., and G.L. Fahnenstiel. 2013. Recent change in summer chlorophyll a dynamics of southeastern Lake Michigan. Journal of Great Lakes Research 39(2): 287-294. doi: https://doi.org/10.1016/j.jglr.2013.02.005

Pothoven, S.A., and G.L. Fahnenstiel. 2014. Declines in the energy content of yearling non-native alewife associated with lower food web changes in Lake Michigan. Fisheries Management and Ecology 21(6): 439-447. doi: https://doi.org/10.1111/fme.12092

Pothoven, S.A., G.L. Fahnenstiel, H.A. Vanderploeg, and T.F. Nalepa. 2016. Changes in water quality variables at a mid-depth site after proliferation of dreissenid mussels in southeastern Lake Michigan. Fundamental and Applied Limnology/Archiv für Hydrobiologie 188(3): 233-244. doi: https://doi.org/10.1127/fal/2016/0883

Pothoven, S.A., and H.A. Vanderploeg. 2017. Changes in abundance and life history patterns following a shift toward oligotrophy in Lake Michigan. Fundamental and Applied Limnology/Archiv für Hydrobiologie: 199-212. doi: https://doi.org/10.1127/fal/2017/1039

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Rowe, M.D., D.R. Obenour, T.F. Nalepa, H.A. Vanderploeg, F. Yousef, and W.C. Kerfoot. 2015a. Mapping the spatial distribution of the biomass and filter-feeding effect of invasive dreissenid mussels on the winter-spring phytoplankton bloom in Lake Michigan. Freshwater Biology 60(11): 2270-2285. doi: https://doi.org/10.1111/ fwb.12653

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Shuchman, R.A., M.J. Sayers, and C.N. Brooks. 2013. Mapping and monitoring the extent of submerged aquatic vegetation in the Laurentian Great Lakes with multi-scale satellite remote sensing. Journal of Great Lakes Research 39(Suppl. 1): 78-89. doi: https://doi.org/10.1016/j.jglr.2013.05.006

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80 Ecological Assessment of Wisconsin - Lake Michigan Chapter 6 Fish David Moe Nelson1, Larry Claflin1

Lake trout. Credit: Andrew Muir, Great Lakes Fishery Commission (GLFC)

6.1 INTRODUCTION This chapter provides a baseline description of the fish and fisheries of our study area in Wisconsin waters of western Lake Michigan. Fish and fisheries are key components of the ecology of the proposed sanctuary, although the proposed sanctuary is not involved in fisheries management. The purpose of this chapter is not to assess the status of individual species or fisheries, but rather to describe their role in the ecological context of the study area. A table of the common names, scientific names, and ancillary information of fish species mentioned here are provided in Table A.1 (in Section 6.6 Appendix A). This is not a list of all species present, but includes many of the species of ecological, commercial, and recreational importance.

The study area supports a diverse set of fish species with ecological, recreational, and commercial importance. Most of these species are Great Lakes natives, but several non-native fish species are also well-established, including (Petrymyzon marinus), round goby (Neogobius melanostomus), alewife (Alosa pseudoharengus), (Osmerus mordax), and several popular gamefish including Chinook ( tshawytscha) and coho (Oncorhynchus kisutch) salmon, and steelhead/rainbow trout (Oncorhynchus mykiss). Some species are primarily pelagic and highly mobile, i.e., occupying the water column and areas well above the bottom, whereas others are associated with bottom structure such as rocky reefs or shipwrecks.

Habitats of the study area range from shallow inshore waters with wide variation in seasonal temperatures, to deep and consistently cold waters. This is reflected in the fish species present, with warm water species such as (Micropterus salmoides), bluegill (Lepomis macrochirus) and cool water species such as (Micropterus dolomieu), and yellow perch (Perca flavescens) species more common inshore, and a cold water assemblage including lake trout (Salvelinus namaycush), lake whitefish (Coregonus

1 NOAA National Ocean Service, National Centers for Coastal Ocean Science, Marine Spatial Ecology Division, Biogeography Branch, Silver Spring, MD.

Ecological Assessment of Wisconsin - Lake Michigan 81 Fish

clupeaformis), and burbot (Lota lota) offshore. Coastal and tributary river mouths are important habitats for many of the fish species in the study area (Jude and Pappas 1992, T. Seilheimer pers. comm.), although most of these habitats are outside (landward) of the boundaries of the proposed sanctuary. Depending on the life history of a given species, inshore wetlands and tributaries may function as nursery, feeding, spawning, or migration habitats. The study area of western Lake Michigan is unique in the higher frequency of coastal upwelling events, when warmer surface waters are blown eastward by prevailing westerly winds, and colder nutrient-rich waters are brought inshore from deeper parts of the lake in summer and autumn months (Plattner et al. 2006, Yurista et al. 2015, E. Rutherford pers. comm.). A link between coastal upwelling and fish productivity is not well demonstrated, but some studies suggest higher abundance of phytoplankton, zooplankton, and alewives in areas with frequent upwelling events (Hook et al. 2003, E. Rutherford pers. comm.).

Lake trout and burbot are the prominent native top-level predator fish species of the coldwater fish assemblage. A major effort to restore self-sustaining lake trout populations has been underway for decades (Bronte et al. 2008). A majority of the other popular gamefish are , including Chinook and coho salmon, brown trout (Salmo trutta), and steelhead (lake-run rainbow trout). These species are largely maintained by stocking of hatchery-reared young fish (Burzynski 2017), although there is some natural reproduction in cold water tributary streams with suitable habitat. Coded wire tag returns indicate that more than 60% of the caught in Lake Michigan are wild reproduced and not stocked (Kornis et al. 2018, T. Seilheimer pers. comm.). Several tributary rivers that flow into the study area feature runs of returning adult steelhead (anadromous rainbow trout) in the spring, and Chinook and coho salmon in the autumn. These include the Ahnapee and Kewaunee Rivers in Kewaunee County, Manitowoc River in Manitowoc County, and Sheboygan River in Sheboygan County. Some smaller tributary streams may also have migratory salmon, though not stocked, including Silver Creek, Fischer Creek, and Little Manitowoc River (T. Seilheimer pers. comm.). Some inshore areas in this region such as bays, harbors, and river mouths, feature a cool- and warm-water fish community (Fago 1985, 1992), and support recreational fishing for species such as yellow perch, (Sander vitreus), northern pike (Esox lucius), largemouth and smallmouth bass, crappies, and bluegill (Lepomis macrochirus) and pumpkinseed (Lepomis gibbosus) sunfish.

In addition to their intrinsic ecological importance, fish populations support recreational and commercial fisheries within the study area. Species sought by the recreational fishery in Lake Michigan waters are primarily coldwater salmonids, including Chinook salmon, coho salmon, lake trout, brown trout, and steelhead (lake-run rainbow trout) (Schmidt 2018).

Compared to historic times, commercial fisheries in the study area are very limited. They are carefully managed by the Wisconsin Department of Natural Chapter 6 Chapter Resources (DNR), in cooperation with other resource agencies (WDNR 2017a). Alewife (top left; NOAA NMFS), steelhead trout (top right; NOAA NMFS), rainbow Through the past 20 years, species smelt (bottom left; NOAA NMFS/Katrina Mueller), coho salmon (bottom right; in the commercial catch include lake NOAA NMFS).

82 Ecological Assessment of Wisconsin - Lake Michigan Fish whitefish, bloater chub (), and non-native rainbow smelt. The commercial fisheries include a trap net fishery off of Two Rivers/Manitowoc and Sheboygan (T. Seilheimer pers. comm.)(Figure 6.1). Lake whitefish is the targeted species, and other non-target “bycatch” species are released live and unharmed. Bloater chubs are targeted by a small commercial gill net fishery (T. Seilheimer pers. comm.), but catch and effort in this fishery has declined from the 1990s to present (Kroeff et al. 2017). Bloater chubs are now increasing from a lakewide historic low estimated in 2014, while rainbow smelt in 2018 are up slightly from recent lows (WDNR 2017a, Bunnell et al. 2019, D. Bunnell pers. comm.). Overall, lake whitefish is the only species to support a stable commercial fishery from historic times to the present, whereas fisheries for other species have declined or are now closed. An experimental trawl study since 2015 has been investigating the possibility of a commercial trawl fishery for lake whitefish (T. Seilheimer pers. comm.)(Figure 6.1).

10 0 1 0 10 0 0 m Contours m Claybans 0 0N Proposed Sanctuary Boundaries Algoma 0100 10 0 mi Alternative A preferred Stony Cree eef Alternative 00 aules eef Historic Fish Spawning Areas Elevenathom eef ¯ Green Bay eaunee Shoal ae erring Kewaunee ae rout ello Perch Historic Spawning and Nursery Sites 0N 100 (! Aleife (! loater Two (! urbot Rivers (! Emerald shiner o ivers arbor 00 (! ae aley Point Manitowoc (! ae trout (! ae hitefish (! ia ay N ainbo smelt (! Slimy sculpin (! Smallmouth bass (! alleye (! 100 ello perch Commercial ral rounds Sheboygan Mid ae rout efuge

0N

Port ae Washington Superior Sheboygan eef Grafton 0N Study Area ae uron 10 0 ae Mequon 100 Northeast eef ae Ontario Milwaukee Milauee eef Michigan ae Erie

0 0 Figure 6.1. Map of study area, including commercial trawl area, Mid-Lake Reef Complex and Refuge, and historic spawning areas for key species (Coberly and Horrall 1980, Goodyear et al. 1982). Chapter 6 Chapter

Ecological Assessment of Wisconsin - Lake Michigan 83 Fish 6.2 DATA AND INFORMATION SOURCES Several sources of information and data were used to describe the fish and fisheries of the study area. These include GIS layers mapped in Figures 6.1 and 6.2, tabular data, published research reports, and fisheries reference volumes.

Key information sources and data sets include: ● U.S. Geological Survey (USGS) Forage Fish Bottom Trawl Survey, 2005-2016 (Madenjian et al. 2016, USGS 2017, Bunnell et al. 2019). Trawl survey data with sample sites from 18 to 110 m deep, in two transects, offshore of Port Washington and Sturgeon Bay (Figure 6.2). The survey is conducted in the fall months, and the trawl nets feature a small mesh size to target forage species such as bloater and alewife. ● Annual stock assessment of yellow ! perch in Wisconsin waters of Bay Michigan using consistent beach seine, # # ## graded mesh gill net, and other sampling ¯ ## ## # # methods (Hirethota and Schindelholz 0 Sturgeon 2017). Incidental catch documents the ay presence of other small fish species in ransect inshore waters, such as spottail shiner Kewaunee! (Notropis hudsonius) and others.

● Lake Michigan salmon and trout 0 harvest estimates for 2004 to 2018, based on sportfishery creel surveys and presented as tabular data (WDNR 2018). Manitowoc! ● Commercial Fisheries Statistics for the U.S., including Great Lakes. Annual landings are reported for each state

in both pounds and dollars (NOAA 10 m 0 m NMFS 2016). Great Lakes data are also available from USGS, with landings Sheboygan! reported by state and lake, parsed by 100 m 0 state versus tribal licensed fisheries (USGS 2016). ● Historic Fish Spawning Grounds Port # in Wisconsin Waters of the Great Washington Lakes (Coberly and Horrall 1980). ! ###### # # This landmark volume captured and Port 0 compiled expert knowledge of 65 ashington 0 0 0 commercial fishermen active from ransect the 1920s to the 1950s, identifying m spawning areas for lake trout, yellow Milwaukee perch and lake herring. The maps have 0 0 Chapter 6 Chapter been digitized as GIS polygons, and are Figure 6.2. Location of USGS forage fish bottom trawl survey sample sites in transects (black triangles) offshore of Sturgeon Bay (10 sites) and Port viewable online in NCCOS’ Wisconsin Washington (nine sites). Site depths range from 18-110 m (USGS 2017). Solid – Lake Michigan Digital Atlas (NOAA and dashed outlines refer to proposed sanctuary boundary alternatives A and NCCOS 2018). B, respectively.

84 Ecological Assessment of Wisconsin - Lake Michigan Fish

● Atlas of the Spawning and Nursery Areas of Great Lakes Fishes, Volume IV, Lake Michigan (Goodyear et al. 1982). This volume is based on a synthesis of expert knowledge, and recently developed as a digital GIS layer, with known spawning and nursery locations represented as points, viewable online on the Great Lakes Aquatic Habitat Framework (GLAHF 2018). ● Hydro-acoustic surveys of Lake Michigan pelagic prey fish species, including alewife, bloater chub, and rainbow smelt (Fabrizio et al. 1997, Mason et al. 2001, Warner et al. 2016). ● Recent integrative studies of the dynamic ecological linkages between lower trophic levels andfish populations in Lake Michigan (Bunnell et al. 2014, 2018, Rogers et al. 2014, Madenjian et al. 2015) ● Wisconsin DNR Fish Mapping Application (WDNR 2017b). Online portal to query and display fish sampling locations on a basemap, for both Great Lakes and inland waters of Wisconsin. Some of the species sample location information was also used in the maps presented in Fishes of Wisconsin (Becker 1983). ● Fishes of Wisconsin (Becker 1983). This is the comprehensive landmark reference book, with extensive information on biology, ecology, and distribution of all Wisconsin fishes. ● Wisconsin Fishes 2000 (Lyons et al. 2000). This volume provides a supplement and update to Becker (1983) Fishes of Wisconsin, with information on recent surveys, results of additional research, and non-native species.

The sources above provide a wealth of information, but leave some questions with incomplete certainty. Many of the information sources are not spatially-explicit, for example, fishery landings may be reported for large areas (e.g., counties or statistical zones) rather than linked to specific locations. The fishery-independent trawl survey targets small species such as alewife and bloater chub, and there are few fishery-independent estimates for larger species. The numbers of hatchery-reared salmonids, such as lake trout and Chinook salmon, that are stocked are well known. The extent and relative of natural reproduction by these species is less certain, but assessment is substantially improved by the mass-marking of hatchery-origin fish (Kornis et al. 2018).

6.3 CURRENT CONDITIONS AND TRENDS BY SPECIES The fish fauna of the study area in Wisconsin waters of western Lake Michigan is diverse, and includes species from warm and cool water assemblages inshore, and cold water species in deeper waters offshore. A selected set of the major species are discussed here, based on their ecological importance and prevalence in the commercial and recreational fisheries of the study area. Topics featured for each species include its ecology, habitat, life history, and population trends. Species from the warm and cool water assemblages of tributary streams and inshore river mouth embayments are not featured here, because these areas are outside of the study area.

6.3.1 Lake Trout (Salvelinus namaycush) Lake trout are the largest native salmonid species in the Great Lakes, and are considered to be at the highest trophic level of the food web. They generally reach maturity around 60 cm (24 in) in length, and can live to 20 years and grow much larger. Adults spawn over bottom reef areas from October to December. Common prey items are invertebrates and small Chapter 6 Chapter fish such as alewife, rainbow smelt, and sculpins (Turschak and Bootsma 2015), and in recent years, round goby as well (Happel et al. 2018). By the late 1950s, stocks of lake trout in the Great Lakes had been severely depleted by decades of Lake trout (Salvelinus namaycush). Credit: NOAA GLERL

Ecological Assessment of Wisconsin - Lake Michigan 85 Fish

and predation by the non-native sea lamprey. Some native stocks survived this extirpation in parts of Lakes Superior and Huron, but native lake trout in Lake Michigan were virtually extirpated (Eschmeyer 1957). Diverse phenotypes, or forms, locally adapted to different habitats were also lost, although several examples of lake trout diversity are still present in Lake Superior (Muir et al. 2016). Hatchery-reared lake trout have been stocked in Lake Michigan since the 1960s in an effort to re-establish reproductive populations, although natural reproduction has been very limited. Within Western Lake Michigan (near the study area), several sites have been targeted for restoration of lake trout by stocking juveniles on reef areas on which fish had historically successfully spawned (Bronte et al. 2008). These areas include Sheboygan Reef, Northeast Reef, East Reef, and Milwaukee Reef, within the Mid Lake Reef Complex and “Mid Lake Trout Refuge (Figure 6.1). In 2016, over 300,000 yearling lake trout were planted on both Sheboygan Reef and Northeast Reef. There are historic reported spawning areas in nearshore areas as well, including Hika Bay offshore of Manitowoc County (T. Seilheimer pers. comm.), and shoals and reefs offshore of Kewaunee County (Coberly and Horrall 1980). Commercial fishing for lake trout ceased in the 1950s. They are still well represented in the sport fishing catch in the study area, although salmon are more often targeted by recreational anglers. In 2018, creel surveys reported landings (including charter and private ) of 3,396 lake trout in Ozaukee County, 3,421 in Sheboygan County, 1,312 in Manitowoc County, and 2,447 in Kewaunee County, for a total of 8,762 within the four-county study area (WDNR 2018). Figure 6.3 depicts a 27-year timeline of recreational angler catch of five major salmonid species (lake trout, Chinook salmon, coho salmon, rainbow trout, brown trout) in the four-county study area (Ozaukee, Sheboygan, Manitowoc, Kewaunee) of Lake Michigan, by species and year, from 1992-2018. Chapter 6 Chapter

Figure 6.3. Total angler catch of five major salmonid species in four-county study area of Lake Michigan, by species and year, from 1992-2018. Data source: WDNR 2018.

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6.3.2 Chinook Salmon (Oncorhynchus tshawytscha) and Coho Salmon (Oncorhynchus kisutch) Chinook and coho salmon were introduced into the Great Lakes in the late 1960s as predators to create a sport fishery that utilized the explosive growth of the non-native alewife population, and to provide a resource for sport fishing (Tody and Tanner 1966, Lyons et al. 2000). Chinook salmon commonly reach sizes of 86 cm (34 Chinook salmon (Oncorhynchus tshawytscha; top) and Coho salmon (Oncorhynchus in), while coho salmon are smaller and kisutch; bottom). Credit: NOAA GLERL reach sizes of 63 cm (25 in)(Becker 1983). Common prey items for both species include invertebrates and small fish such as alewife, bloater chub, and rainbow smelt. Hatchery-reared Chinook are stocked the spring after being spawned in the fall, while coho are stocked as yearlings, in tributary rivers and harbors including Ahnapee, Kewaunee, Manitowoc, Twin, and Sheboygan Rivers (Burzynski 2017). Pacific salmon adults will return to these waters in the four-county study area for spawning runs in the fall months after 3 to 4 years. Survival estimated from lake-wide coded wire tagging efforts indicates that survival of Chinook salmon stocked into the study area (Statistical Areas WM4 and WM5) are the highest in Lake Michigan for stocked Chinook salmon (Kornis et al. 2018). Chinook salmon are currently the most-harvested species by recreational fishers in the four-county study area, including from charter boat, private boat, pier, shore, and stream. In 2018, the Wisconsin DNR’s creel survey reported landings of over 9,700 Chinook salmon in Ozaukee County, over 7,900 in Sheboygan County, over 10,400 in Manitowoc County, and over 26,500 in Kewaunee County (WDNR 2018), for a total of 54,741 fish in the four-county study area, These landings are lower than in recent years, partly because of a weak 2013 year class (Schmidt 2018). Landings of coho salmon in 2018 were also down from recent years- over 17,300 in Ozaukee, over 3,800 in Sheboygan County, 461 in Manitowoc County, and 1,098 in Kewaunee County were harvested for a total of 22,712 coho salmon from the four-county area (Figure 6.3)(WDNR 2018).

6.3.3 Steelhead/Rainbow Trout (Oncorhynchus mykiss), Brown Trout (Salmo trutta), and Brook Trout (Salvelinus fontinalis) Migratory strains of rainbow trout or steelhead are native to the Pacific Coast of , from California to the Aleutians. The experimental introduction of lake-run (potamodromous) steelhead to Great Lakes tributaries dates back to the 1800s, but in recent decades, hatchery release records for Wisconsin’s Lake Michigan tributaries date to 1963 – several years before the introduction of coho and Chinook salmon in the late 1960s (Burzynski 2017). Rainbow trout or steelhead (Oncorhynchus Lake-run steelhead often reach a size of 65 cm (26 in) or more, mykiss). Credit: NOAA GLERL and typical prey items include invertebrates and small fish. In 2016, over 190,000 yearling steelhead trout were planted in tributary streams of the four-county study area. Steelhead are known to return to these streams for spring spawning runs, and there is evidence of successful natural reproduction in some small tributaries, including Sauk Creek and Willow Creek in the Sheboygan River watershed (Hirethota and Burzynski 2015), and Fischer Creek in Manitowoc County (Watson et al. 2018). Steelhead anglers are avid, and 2018 creel survey data shows that over 40,000 steelhead / rainbow trout were caught by anglers in the four-county study area, by all angling methods combined, such as private boat, 6 Chapter charter, shore, pier and stream (Figure 6.3)(WDNR 2018).

Ecological Assessment of Wisconsin - Lake Michigan 87 Fish

Brown trout are native to Europe, and experimental introductions in Wisconsin date back to the late 1800s (Lyons et al. 2000), with annual plantings of yearling and fingerlings in Lake Michigan tributaries since the 1960s (Burzynski 2017). In Great Lakes waters, brown trout tend to grow larger than they do in streams, commonly reaching 55 cm (22 in), but they tend to remain inshore in waters less than 15 m deep (Lyons et al. 2000). Lake-run brown trout feed on invertebrates and small fish, and there is some evidence to suggest that they may be more effective predators of non-native round goby than are other introduced salmonids Brown trout (Salmo trutta). Credit: NOAA GLERL (Hirethota 2015, Turschak and Bootsma 2015). In 2016, over 397,000 juvenile brown trout (yearlings and fingerlings) were planted in tributary streams in the four-county study area, and some brown trout return to these streams as adults for their spawning runs in October to December. In 2018, creel survey data indicate that over 6,500 brown trout were caught by anglers in Lake Michigan waters of the same four counties (Figure 6.3)(WDNR 2018).

Brook trout (Salvelinus fontinalis) are native to coldwater streams of Wisconsin, and self-sustaining populations persist in certain tributaries to Lake Michigan from Kewaunee, Manitowoc, and Sheboygan Counties (WDNR 2017c). Lake- run or “coaster” brook trout are not known from this area, as historically they occurred in tributaries to Lake Superior on the Bayfield Peninsula of northwestern Wisconsin. The planting of hatchery-reared brook trout in Lake Michigan waters was curtailed in 2004 (Burzynski 2017), and few landings have been Brook trout (Salvelinus fontinalis). Credit: NOAA GLERL reported by anglers in Wisconsin waters of Lake Michigan in recent years (WDNR 2018).

6.3.4 Alewife (Alosa pseudoharengus) The alewife is a non-native species in Lake Michigan, having entered Lake Erie through the in the 1930s, and established in the upper Great Lakes in the 1950s (Becker 1983, Lyons et al. 2000). They typically reach a size of 15-18 cm (6-7 in), and feed on seasonally-available zooplankton (Becker 1983). They are known to spawn in inshore waters in the summer months from June to August. Alewife populations in Lake Michigan grew exponentially through the 1960s, fueled Alewife (Alosa pseudoharengus). Credit: NOAA GLERL by an abundant zooplankton forage base and absence of top predators due to the extirpation of lake trout in previous decades. Since the 1970s, alewives provided the primary forage base for introduced game species such as Chinook and coho salmon, and were fished commercially until the early 1990s. In recent years, the USGS forage fish bottom trawl surveys have indicated declining abundance of alewife lake-wide in Lake Michigan, with a lake-wide record-low biomass estimate of 500 metric tons in 2015, along with a decline in age-6-plus fish from the breeding population. This decline is generally corroborated by lake-wide acoustic surveys as well (Warner et al. 2016). The causes of the decline of multiple forage species are difficult to identify, but may be related to declines in primary productivity linked to Chapter 6 Chapter invasive filter-feeding dreissenid (quagga and zebra) mussels (Bunnell et al. 2018), combined with continued predation by Chinook salmon and lake trout (Madenjian et al. 2016, Bunnell et al. 2018). These observed lake- wide estimates are consistent with trends in the USGS trawl survey for the Port Washington and Sturgeon Bay transects (Figure 6.4)(USGS 2017). Year-class strength of alewives varies greatly between years and among

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Figure 6.4. Relative abundance of alewife by year, 2005-2016, represented as sums of catch-per-hectare in USGS forage fish bottom trawl survey, summed over sample sites in transects offshore of Port Washington and Sturgeon Bay. different portions of the lake, but there is some evidence to suggest that alewives may benefit fromthe upwelling events in the western Lake Michigan study area, which brings nutrient-rich waters inshore from deeper parts of the lake (Hook et al. 2003, E. Rutherford pers. comm.).

6.3.5 Bloater (Coregonus hoyi) Bloater is a species of coregonid “chub” endemic to the Great Lakes, and gets its name because of how its swim bladder expands when brought to the surface from deep water. Bloater chubs typically reach a size of 20-25 cm (8-10 in), generally feed on zooplankton, and spawn on the bottom in deep water in the winter months, January to March (Becker 1983). While several other species of deepwater Coregonus endemic to the

Great Lakes have been extirpated in Lake Michigan (i.e.,C. , 6 Chapter C. nigripinnis, C. johannae, C. reighardi, C. zenithicus)(Lyons et Bloater (Coregonus hoyi). Credit: NOAA GLERL al. 2000), the bloater has persisted. One possible reason could be its small size – it was less vulnerable to the lake chub commercial fishery in the first half of the 20th century that targeted the larger Coregonus species. It continues to be key forage species for top level predators such as

Ecological Assessment of Wisconsin - Lake Michigan 89 Fish

lake trout. The bloater is one of the few species still targeted by limited commercial fisheries in Lake Michigan (Surendonk 2003), and is sometimes processed as “smoked chub”, in recent years marketed for a premium price. Bloater are harvested in the commercial fishery by small-mesh gill net, and in 2015, over 51,000 pounds were landed in Wisconsin’s “southern zone” which includes the four-county study area (Kroeff et al. 2017). Overall, this represents a drastic decline for the historic fishery, with statewide harvest over 2 million pounds in the 1980s. The USGS forage fish bottom trawl survey program estimates that lake-wide biomass of bloater was 2,800 metric tons in 2015, a nine-fold increase from 300 metric tons in 2014 (Madenjian et al. 2015)(Figure 6.5). However, this illustrates the marked longer-term decline from the 1980s, when lakewide biomass was estimated over 100,000 metric tons (T. Seilheimer pers. comm.).

Figure 6.5. Relative abundance of bloater by year, 2005-2016, represented as sums of catch-per-hectare in USGS forage fish bottom trawl survey, summed over sample sites in transects offshore of Port Washington and Sturgeon Bay. Chapter 6 Chapter

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6.3.6 Round Goby (Neogobius melanostomus) Round goby is native to the Black and Caspian of Eurasia, and is a relatively recent invasive species, arriving in ship ballast water in the 1990s. The round goby is a small (13 cm or 5 in), benthic and structure-oriented fish. It is prevalent in nearshore habitats of the study area (WDNR 2017b) and in many adjacent tributaries (Kornis Round goby (Neogobius melanostomus). Credit: D. and Zanden 2010), and is becoming established in harbor and river Jude, U. of Michigan, 1995 mouth areas such as Milwaukee Harbor and Sturgeon Bay. It may establish nesting areas for spawning among rocks, shipwrecks, or other underwater structure (Lyons et al. 2000), and is thought to spawn from April to September. Round goby may serve as a forage species for inshore gamefish such as brown trout, largemouth and smallmouth bass (Hirethota 2015), and even for lake whitefish which are usually not considered piscivores (T. Seilheimer pers. comm.). There is concern that round goby may adversely impact native species such as slimy and deepwater sculpin through competition for habitat, or lake trout by preying on their eggs (Lyons et al. 2000). Round goby do consume dreissenid (zebra and quagga) mussels, but the effects of this predation across the benthic landscape may vary (Ruetz et al. 2012). The USGS forage fish bottom trawl survey program estimates that lake-wide biomass of round goby was 300 metric tons in 2015, a substantial decline from 2,000 metric tons in 2014 (Madenjian et al. 2015)(Figure 6.6). However, the round goby’s preferred habitat of rocky areas or other bottom structure cannot be sampled by the trawl gear (T. Seilheimer pers. comm.), though they may be highly abundant in these areas. Within the study area, the association of round goby with bottom features such as shipwrecks warrants continued attention. Chapter 6 Chapter

Figure 6.6. Relative abundance of round goby by year, 2005-2016, represented as sums of catch-per-hectare in USGS forage fish bottom trawl survey, summed over sample sites in transects offshore of Port Washington and Sturgeon Bay.

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6.3.7 Sculpins Slimy sculpin (Cottus cognatus) is a native bottom-dwelling species, and an important forage item for young lake trout and burbot (Becker 1983). They typically reach a size of 8 cm (3 in), and feed on small crustaceans (e.g., amphipods) and insect larvae. The USGS forage fish bottom trawl survey program estimates lake-wide biomass of slimy sculpin at a near-record low of 50 metric tons in 2015 (Madenjian et al. 2015). True to its name, the deepwater sculpin is a native bottom-dwelling species inhabiting waters deeper than most other small forage species in Lake Michigan (Becker 1983)(Figure 6.7). They typically reach a size of 13 cm (5 in), and spawn in deep water in the winter months and possibly year-round (Becker 1983). Deepwater sculpin feed on small crustaceans such as opossum shrimp (Mysis diluviana), Diporeia spp., and copepods, and are an important prey species for lake trout and burbot. Lake-wide biomass estimates of Slimy sculpin (Cottus cognatus; top) and deepwater sculpin have been declining since 2009, and were at a deepwater sculpin (Myoxocephalus thompsoni; near-record low of 400 metric tons in 2015 (Madenjian et al. 2015). bottom). Credit: NOAA GLERL Chapter 6 Chapter Figure 6.7. Relative abundance of deepwater sculpin by depth (18-110 m), represented as sums of catch-per-hectare in USGS forage fish bottom trawl survey, summed over sample years (2005-2016) in transects offshore of Port Washington and Sturgeon Bay

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6.3.8 Ninespine Stickleback Pungitius( pungitius) Ninespine stickleback (Pungitius pungitius) is an important forage species in shallower waters of the study area. They typically reach a size of only 6 cm, and nest on the lake bottom in the summer months (June-July)(Becker 1983) (Figure 6.8). They are known as important prey items for lake trout, brown and rainbow trout, and burbot. Abundance of ninespine stickleback appeared to increase Ninespine stickleback (Pungitius pungitius). Credit: Joseph in Lake Michigan waters from 1996 to 2007 during Tomelleri the proliferation of dreissenid mussels and macroalga Cladophora in benthic habitats (Madenjian et al. 2010), but recent estimates from of the USGS forage fish bottom trawl survey program indicate lake-wide biomass of ninespine stickleback has declined toanear- record low of 1 metric ton in 2015 (Madenjian et al. 2015). Chapter 6 Chapter Figure 6.8. Relative abundance of ninespine stickleback by year, 2005-2016, represented as sums of catch-per-hectare in USGS trawl survey, summed over sample sites in transects offshore of Port Washington and Sturgeon Bay

Ecological Assessment of Wisconsin - Lake Michigan 93 Fish

6.3.9 Rainbow Smelt (Osmerus mordax) Rainbow smelt is native to the Atlantic coast from New England northward, and was established in Wisconsin’s waters of Lake Michigan by the 1930s after being introduced to an inland lake in Michigan (Becker 1983). Spring (March-May) “smelt runs” of spawners in small tributary streams historically supported enthusiastic local fisheries. Smelt were also a targeted species in the Lake Michigan winter commercial trawl fishery (Hogler and Surendonk 2007), in a designated area offshore of Manitowoc and Kewaunee Counties (Figure 6.1). Catch and effort declined Rainbow smelt (Osmerus mordax). Credit: NOAA markedly from the 1990s to the 2000s (Surendonk 2003) and GLERL 2010s (Figure 6.10). Rainbow smelt typically reach a size of 18 cm (7 in), and are known to feed on small invertebrates such as Mysis. Rainbow smelt abundance was generally much higher in the 1980s to 1990s than it has been since the 2000s. The USGS forage fish bottom trawl survey program estimates lake-wide biomass of rainbow smelt at a near-record low of 60 metric tons in 2015 (Madenjian et al. 2016), although estimates based on hydro-acoustic surveys were higher (Warner et al. 2016)(Figure 6.9). Chapter 6 Chapter

Figure 6.9. Relative abundance of rainbow smelt by year, 2005-2016, represented as sums of catch-per-hectare in USGS forage fish bottom trawl survey, summed over sample sites in transects offshore of Port Washington and Sturgeon Bay.

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6.3.10 Lake Whitefish (Coregonus clupeaformis) Lake whitefish is the largest of the Great Lakes Coregonus species (commonly 46 cm or 18 in), and is one of the few species to support a commercial fishery from historic times up to the present. They are benthic feeders that historically relied on Diporeia but now feed on dreissenid mussels, Mysis, and benthic invertebrates (Fera et al. 2015), and are also beginning to feed more heavily on fish, particularly the non-native round goby (T. Seilheimer pers. comm.). Lake whitefish are known to spawn in inshore waters October-December (Ebener et Lake whitefish Coregonus( clupeaformis). Credit: NOAA al. 2008). There are no known spawning sites in the study GLERL area, but tag return studies suggest spawning sites in inshore embayments in Door County, WI, and Bay De Noc, MI (T. Seilheimer pers. comm.). In terms of landings (weight and dollar value), lake whitefish account for more than 90% of the harvest in Wisconsin’s commercial fisheries (NOAA NMFS 2016). Harvest in Wisconsin’s Lake Michigan (including Green Bay) waters was over 1.1 million pounds in 2015, and has remained above 1 million pounds annually since the 1990s. Some fresh whitefish are sold locally and used in “fish boils” popular in Door County and other coastal areas, and some are smoked and marketed for a premium price. Within the study area, the commercial fishery is primarily by trap net offshore of Two Rivers / Manitowoc and Sheboygan in the summer months, and annual harvest is regulated by quota (T. Seilheimer pers. comm.). From 2015-2018, an experimental trawl study has been conducted from Two Rivers in Manitowoc County, which has been an effective gear to harvest lake whitefish with low bycatch (Seilheimer, in review). Sport fishermen in Green Bay also target the lake whitefish during the winter months through the ice. Recent estimates of young-of-year whitefish in Green Bay indicate strong year classes (Hansen 2017), although throughout Lake Michigan there are concerns about declining recruitment. Figure 6.10 depicts a 30- year timeline of Wisconsin’s statewide commercial landings, illustrating the decline of these fisheries for most species, and the persistence of lake whitefish (NOAA NMFS 2016).

6.3.11 Yellow Perch (Perca flavescens) Yellow perch is an important native species, especially in cool-water mesotrophic Green Bay, but also in the cold oligotrophic waters of Lake Michigan. They are common in the size range of 13-23 cm (5-9 in), but can grow larger. They are spring spawners (April-May), and are known for extruding distinctive egg strands, often over submerged vegetation or other structure (Becker 1983). Prey items include aquatic insects and crustaceans, sculpins and other small fish. Small perch, in turn, are often prey for cool-water gamefish such Yellow perch (Perca flavescens). Credit: NOAA GLERL as walleye and northern pike. Populations in both Green Bay and Lake Michigan were high in the 1980s and supported both recreational and commercial fisheries. Yellow perch experienced a rapid, lakewide decline in the early 1990s, followed by an extended period of weak year classes (Santucci et al. 2014). Commercial harvest in Lake Michigan was closed in 1996, and recreational harvest has declined from the 1990s to present record-low levels. Yellow perch stocks in Lake Michigan and Green Bay are assessed annually using consistent sampling methods to capture young-of-the-year and older year classes (Hirethota and Schindelholz 2017, Makauskas and Clapp 2018), and results reflect the general Chapter 6 Chapter decline from the 1980s to present, with some year-classes nearly absent. Green Bay year classes have been consistent, but few fish recruit to the fishery (T. Seilheimer pers. comm.). Figure 6.11 depicts a 30-year timeline of recreational catch by anglers in Ozaukee, Sheboygan, Manitowoc, Kewaunee Counties, consistent with the general decline of the species from the 1990s to present (WDNR 2019).

Ecological Assessment of Wisconsin - Lake Michigan 95 Fish

Figure 6.10. This 30-year timeline of Wisconsin’s statewide commercial landings illustrates the decline of fisheries for most species, and the persistence of lake whitefish. Data source: NOAA NMFS 2016. Chapter 6 Chapter

Figure 6.11: This 30-year timeline of anglers’ yellow perch catch in the four-county study area illustrates a decline from the 1990s to present. Data source: WDNR 2019.

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6.3.12 Burbot (Lota lota) This native freshwater cod is one of the top-trophic level predator fish in cold deep waters of the Great Lakes, and typically reach a size of 30-50 cm (12-20 in). They are known to spawn on the lake bottom in the winter months, January to March (Becker 1983). Prey items include invertebrates and small fish including round goby, rainbow smelt, alewives, and sculpins (Jacobs et al. 2010). Young burbot may also serve as prey for species such as lake trout. Along with other Burbot (Lota lota). Credit: NOAA GLERL large fish, burbot are vulnerable to attack by the invasive sea lamprey, and populations declined in the 1940s and 1950s as a result. With the widespread implementation of sea lamprey control efforts in the 1960s, burbot populations recovered. Burbot are generally not a target species for recreational and commercial fisheries in the Great Lakes, although modest numbers are reported in the catch.

6.3.13 Lake Sturgeon (Acipenser fulvescens) Lake sturgeon (Acipenser fulvescens) can attain the largest size of any fish in the Great Lakes, with adults of 115 cm (46 in) or more, and weight over 100 lbs. They feed primarily on benthic invertebrates, and are very slow to mature – over 20 years for females (Becker 1983). Lake sturgeon has a state conservation Lake sturgeon (Acipenser fulvescens). Credit: NOAA GLERL. status of “Special Concern” (WDNR 2015, 2016), and is the focus of targeted restoration actions in Wisconsin and other states. A significant population persists in Green Bay and its tributary waters, including / Fox River / Wolf River system (WDNR 2000), where they spawn primarily in rivers from April to June. They may occur in Lake Michigan, but are likely only transitory in the study area (Lyons et al. 2000, T. Seilheimer pers. comm.).

6.3.14 Sea Lamprey (Petrymyzon marinus) After invading the upper Great Lakes through the in the 1930s, this invasive and predatory jawless fish species was credited with the near-extirpation of lake trout in Lake Michigan. Before targeted control efforts were initiated in the 1960s (e.g., Sea lamprey (Petrymyzon marinus). Credit: NOAA GLERL (left) and T. Lawrence, barriers, traps, selective lampricides), GLFC the population in Lake Michigan was estimated at 600,000. The control efforts continue, and recent population estimates are near 29,000, approximately 5% of the peak, meeting the management targets (GLFC 2018). However, the species persists throughout the Great Lakes, including the study area, and spawns in tributary streams in the spring, April to June. Adults typically reach as size of 30-60 cm, or 12-24 in (Becker 1983). Chapter 6 Chapter

Ecological Assessment of Wisconsin - Lake Michigan 97 Fish 6.4 DISCUSSION The fish fauna of Lake Michigan has been in continuous change over the past century, influenced by non-native species, fluctuating nutrient loads and cycling, contaminants, fisheries, and other ecological factors. Several species of endemic lake chubs (e.g., Coregonus kiyi) have been extirpated (Lyons et al. 2000), some species have been unintentionally introduced (e.g., alewife, sea lamprey), and others were intentionally introduced (e.g., Chinook salmon, steelhead). Emerging concerns include fish pathogens such as viral hemorrhagic septicemia virus (VHSv), and additional non-native species becoming established in Lake Michigan waters (Cogswell et al. 2012).

In recent decades, the proliferation of dreissenid (zebra and quagga) mussels have dramatically altered the nutrient and plankton ecology of the lake, resulting in lower overall primary production, greater water clarity, and increased growth of macroalga Cladophora in lakebed habitats. Many fish species, both native and non- native, have undergone dramatic changes in abundance in parallel with the changing food web and lakebed. Some fish species have declined, some have persisted, and a few apparently increased (Bunnell et al. 2018). Many of the recent changes in fish populations can be linked to these food web changes. Dreissenid mussels became abundant in a food web that was already shaped by invasive/non-native species, such as sea lamprey, alewife, rainbow smelt, and round goby. As primary production has shifted to the benthic zone, there is less phytoplankton to feed the pelagic food web’s zooplankton and forage fishes. As the ecology and food web of the lake continues to change, trends are difficult to predict, and new questions will emerge.

The changes unfolding in Lake Michigan present a set of challenging questions for natural resource managers, illustrating the linkages between the lake’s trophic ecology, fish populations, fisheries and other human dimensions. Can nutrient inputs be managed to discourage the growth of nuisance algae such as Cladophora, while maintaining productivity to support fisheries? Can managers take any action to stem the decline and restore native prey fish species such as (lake herring)? Will lake whitefish continue to be the main commercial species and will other species, like bloater, return to higher population levels that can support harvest? How does the changing food web affect the management of sport fisheries? How will a changing climate affect Harvested lake whitefish. Credit: Andew Muir, GLFC the food web, fish populations, and fisheries? Chapter 6 Chapter

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Ecological Assessment of Wisconsin - Lake Michigan 103 Fish 6.6 APPENDIX A Table A.1 Lists the common and scientific names of fish species mentioned in Chapter 6. This list includes many of the ecologically important species, but is not a comprehensive list of all species that may be present in the study area.

Table A.1. Common and scientific names of fish species mentioned in Chapter 6.. Common name Scientific name Family Notes sea lamprey Petromyzon marinus Petromyzonidae non-native lake sturgeon Acipenser fulvescens Acipenseridae native alewife Alosa pseudoharengus Clupeidae non-native lake whitefish Coregonus clupeaformis native cisco (lake herring) Coregonus artedii Salmonidae native bloater chub Coregonus hoyi Salmonidae native kiyi Coregonus kiyi Salmonidae native, extirpated Coregonus nigripinnis Salmonidae native, extirpated deepwater cisco Coregonus johannae Salmonidae native, extirpated Coregonus reighardi Salmonidae native, extirpated Coregonus zenithicus Salmonidae native, extirpated cylindraceum Salmonidae native lake trout Salvelinus namaycush Salmonidae native brook trout Salvelinus fontinalis Salmonidae native brown trout Salmo trutta Salmonidae non-native rainbow trout (steelhead) Oncorhynchus mykiss Salmonidae non-native chinook salmon Oncorhynchus tshswytscha Salmonidae non-native coho salmon Oncorhynchus kisutch Salmonidae non-native rainbow smelt Osmerus morax Osmeridae non-native northern pike Esox lucius Esocidae native spottail shiner Notropis hudsonius Cyprindae native emerald shiner Notropis atherinoides Cyprindae native longnose dace Rhinichthys cataractae Cyprindae native white sucker Catostomus commersoni Catostomidae native longnose sucker Catostomus catostomus Catostomidae native burbot Lota lota Gadidae native ninespine stickleback Pungitius pungitius Gasterosteidae native slimy sculpin Cottus cognatus Cottidae native deepwater sculpin Myoxocephalus thompsoni Cottidae native pumpkinseed Lepomis gibbosus Centrarchidae native bluegill Lepomis macrochirus Centrarchidae native smallmouth bass Micropterus dolomieu Centrarchidae native largemouth bass Micropterus salmoides Centrarchidae native Ambloplites rupestris Centrarchidae native Chapter 6 Chapter yellow perch Perca flavescens Percidae native walleye Stizostedion vitreum Percidae native round goby Neogobius melanostomus Gobiidae non-native

104 Ecological Assessment of Wisconsin - Lake Michigan

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The mission of the National Centers for Coastal Ocean Science is to provide managers with scientific information and tools needed to balance society’s environmental, social and economic goals. For more information, visit: https://coastalscience.noaa.gov/

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