This readme.txt file was generated on <2023.04.14> by Holly Kundel

Recommended citation for the data: 
Kundel, H and G.J.A. Hansen. (2023). Data in Support of Widespread declines in walleye recruitment following zebra mussel invasion in Minnesota lakes. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/n6tz-vj60


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GENERAL INFORMATION
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1. Title of Dataset 
Data in Support of Widespread declines in walleye recruitment following zebra mussel invasion in Minnesota lakes

2. Author Information

  Principal Investigator Contact Information
        Name: Holly Kundel
           Institution: University of Minnesota - Twin Cities
           Address: 2003 Upper Buford Circle, St. Paul, MN 55108
           Email: kunde058@umn.edu
           ORCID: 0000-0002-5154-4150

  Associate or Co-investigator Contact Information
        Name: Gretchen J. A. Hansen
           Institution: University of Minnesota - Twin Cities
           Address: 2003 Upper Buford Circle, St. Paul, MN 55108
           Email: ghansen@umn.edu
           ORCID: 0000-0003-0241-7048

3. Date published or finalized for release: 2023.04.14

4. Date of data collection (single date, range, approximate date): 1993-09-29 to 2019-10-08

5. Geographic location of data collection (where was data collected?): Minnesota, USA

6. Information about funding sources that supported the collection of the data: 
Funding for this project was provided by the Minnesota Environment and Natural Resources Trust Fund as recommended by the Minnesota Aquatic Invasive Species Research Center (MAISRC) and the Legislative-Citizen Commission on Minnesota Resources (LCCMR).
 This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. (1839286).

7. Overview of the data (abstract): 
These data contain 1,438 electrofishing surveys performed by the Minnesota Department of Natural Resources on 318 Minnesota lakes from 1993 through 2019. This dataset was derived from a larger set of over 5,700 electrofishing surveys that were then filtered by the following attributes: survey must be done at night, target age-0 walleye, have gear code EW, EF, or SEF, started August 1st or later, have an electrofishing run time (shock time) or at least 30 minutes, and be performed when the water temperature is between 10°C and 20°C. We believed these electrofishing surveys to be the most reliable for reporting age-0 walleye relative abundance. This data supports Kundel et al. In Review [DOI].


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SHARING/ACCESS INFORMATION
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1. Licenses/restrictions placed on the data: CC0 1.0 Universal (https://creativecommons.org/publicdomain/zero/1.0/)

2. Links to publications that cite or use the data: 
Kundel, H., T. Wagner, and G.J.A. Hansen. Widespread declines in walleye recruitment following zebra mussel invasion in Minnesota lakes. In Review

3. Was data derived from another source? No
           If yes, list source(s):

4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use


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DATA & FILE OVERVIEW
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1. File List
   A. Filename: EF_DATA_Final.csv  
      Short description: electrofishing surveys targeting age-0 walleye catch and effort data, and lake characteristics including zebra mussel invasion status

2. Relationship between files: NA


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METHODOLOGICAL INFORMATION
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1. Description of methods used for collection/generation of data: 
Electrofishing data used in this study were collected by the Minnesota Department of Natural Resources between 1993 and 2019. These electrofishing surveys are conducted in the Fall, and target age-0 and age-1 walleye, with a goal of estimating size structure and relative abundance of young walleye. The sampling gear will be boom pulsed-DC electrofishing conducted along lakeshores at night between sunset and sunrise from late August to early October in most lakes, and this sampling targets walleye < 15 in. Fall electrofishing catch per unit effort (CPUE) at night derived from representative sampling methods crudely reflects population density of age 0 and age 1 walleye within lakes over time or among Iowa and Wisconsin lakes (Larscheid et al. 2001; Hansen et al. 2004; Madsen 2008; Hansen et al. 2012). However, CPUE of age 1 walleye appeared better than CPUE of age 0 walleye for predicting strengths of the same cohort at age 3 in Escanaba Lake, Wisconsin, the lake with the better methods of estimating population size (Madsen 2008). However, because electrofishing catchability of age 0 and age 1 walleye decreased with increasing population density, electrofishing CPUE becomes a poor indicator of population density when densities become high (Larscheid et al. 2001; Hansen et al. 2004). Both age 0 and age 1 walleye are caught with day electrofishing, catchability is much higher at night (McInerny and Cross 2004). Lastly, measuring for total length appears important because stronger year-class strengths of walleye occurred in Lake of the Woods, Leech Lake, and Lake Vermillion when average lengths of age 0 walleye caught with fall boom electrofishing were higher (Ward 2014; T. Heinrich, MNDNR, personal communication; D. Williams, MNDNR, personal communication). Entire shorelines are sampled in smaller lakes and sampling stations selected via representative sampling methods are electrofished in larger waterbodies with an aim of sampling at least three miles of shoreline. 

Hansen, J.F., A.H. Fayram, and J.M. Hennessy. 2012. The relationship between age-0 walleye density and adult year-class strength across northern Wisconsin. North American Journal of Fisheries Management 32:663-670.

Hansen, M.J., S.P. Newman, and C.J. Edwards. 2004. A reexamination of the relationship between electrofishing catch rate and age-0 walleye density in northern Wisconsin lakes. North American Journal of Fisheries Management 24:429-439.

Larscheid, J.G., E. Thelen, and M. Hawkins. 2001. The relationship of catch per unit effort data to estimated density of YOY and yearling walleyes in Spirit, East Okoboji, Clear and Storm Lakes, and an evaluation of the use of trend data for managing natural lakes in northwest Iowa. Completion Report (Study 7014), Iowa Department of Natural Resources, Des Moines.

Madsen, E.R. 2008. Forecasting walleye abundance in northern Wisconsin lakes. North American Journal of Fisheries Management 28:481-499.

McInerny, M.C., and T.K. Cross. 2004. Comparison of day electrofishing, night electrofishing, and trap netting for sampling inshore fish in Minnesota lakes. Minnesota Department of Natural Resources Special Publication 161, St. Paul.

Minnesota Department of Natural Resources (MNDNR). 2017. Manual of Instructions for Lake Survey. Minnesota Department of Natural Resources, Special Publication No. 180, St. Paul, Minnesota (version 1.04, released January 2019).

Ward, M. 2014. Large lake sampling program assessment report for Leech Lake 2013. Minnesota Department of Natural Resources Division of Fisheries and Wildlife. Completion report. St. Paul.

2. Methods for processing the data: <describe how the submitted data were generated from the raw or collected data

Electrofishing data used in this study were collected by the Minnesota Department of Natural Resources (Minnesota Department of Natural Resources [(MNDNR)] 2017).  We started with over 5,700 surveys spanning 1975 through 2019, and filtered data using the following criteria and based on extensive consultation with agency staff to ensure (to the degree possible) that surveys were representative of age-0 walleye relative abundance and followed recommended protocols (Minnesota Department of Natural Resources (MNDNR) 2017). We used data from several survey types, including standard surveys, targeted surveys, large lake surveys, and external research surveys Surveys coded as electrofishing for walleye (EW), which is a newer gear code, along with standard electrofishing (EF), and special electrofishing (SEF) which also target walleye, and were used on older surveys targeting walleye before the “EW” gear code was created (R. Bruesewitz, personal communication, 2020).  We restricted our analysis to surveys performed at night and conducted on August 1st or later. State protocol recommends that fall electrofishing surveys be conducted for at least two hours of run time (i.e. time that shocking unit was on) (Minnesota Department of Natural Resources (MNDNR) 2017). Only 367 surveys met those criteria, so we applied a more liberal standard for minimal effort and included surveys in which 30 minutes or more was recorded as electrofishing run time. Next, we ensured that age-0 walleye were being targeted based on target species listed in the database or survey code (i.e., fall electrofishing for walleye) where possible. When no target species were listed, we contacted MN DNR Area Managers to confirm that walleye were targeted. Lastly, it is recommended that these surveys take place when surface water temperatures are between 10 and 20°C (Borkholder and Parsons 2001), so we filtered based on the temperature recorded at the time of the survey. If no in situ water temperature was recorded, lake- and date-specific modeled surface temperature (Read et al. 2021) was used, and surveys done at water temperatures outside this temperature range were excluded from the final analysis. With this final list of surveys, we recorded “effort” as the number of seconds electrofished. Walleye catch data associated with these surveys were then compiled; this method ensured that our data included zeros where surveys that targeted age-0 walleye but didn’t catch any were still included.

Borkholder, B.D., and Parsons, B.G. 2001. Relationship between Electrofishing Catch Rates of Age-0 Walleyes and Water Temperature in Minnesota Lakes. North American Journal of Fisheries Management 21(2): 318–325.

Minnesota Department of Natural Resources (MNDNR). 2017. Manual of Instructions for Lake Survey. Minnesota Department of Natural Resources, Special Publication No. 180, St. Paul, Minnesota (version 1.04, released January 2019).

Read, J.S., Zwart, J.A., Kundel, H., Corson-Dosch, H.R., Hansen, G.J.A., Vitense, K., Appling, A.P., Oliver, S.K., and Platt, L. 2021. Data release: Process-based predictions of lake water temperature in the Midwest US. U.S. Geological Survey. doi:10.5066/P9CA6XP8.

3. Instrument- or software-specific information needed to interpret the data: None

4. Standards and calibration information, if appropriate: NA

5. Environmental/experimental conditions: NA

6. Describe any quality-assurance procedures performed on the data:
data have been closely reviewed. Outliers have either been corrected by MN DNR researchers or removed. Data have been vetted by several MN DNR researchers and fisheries managers.

7. People involved with sample collection, processing, analysis and/or submission:
Data Collation: 
* Steve Shroyer, Dale Logsdon, and Paula Phelps for providing the electrofising survey data and walleye stocking data. 
* Kelsey Vitense, for her work on collating and cleaning up water clarity data, and improving the crosswalk between lake identifiers of MN DOW and NHD ID 
* MN DNR Fisheries managers and staff for tracking down additional data, and clarifying electrofishing survey details, including Eric Altena, Marc Bacigalupi, Rick Bruesewitz, Dave Coahran, Bill Evarts, Edie Evarts, Chris Foster, Leslie George, Jon Hansen, Deserae Hendrickson, Dale Logsdon, Kristan Maccaroni, Luke Schalekamp, Doug Schultz, Tony Standera, Kevin Stauffer, Tanner Stevens, Joe Stewig, Phil Talmage, Benjamin Vondra, David Weitzel, and Dan Wilfond. 
* Max Glines for providing remotely sensed Secchi. 
* Jordan S. Read, Alison P. Appling, Samantha K. Oliver, Lindsay Platt, Jacob A. Zwart, Kelsey Vitense, Gretchen J.A. Hansen, Hayley Corson-Dosch, Holly Kundel for modeled lake temperature data. 

Data Processing and Analysis: Holly Kundel


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DATA-SPECIFIC INFORMATION FOR: EF_DATA_Final.csv 
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1. Number of variables: 54

2. Number of cases/rows: 1438

3. Missing data codes:
        Code/symbol  NA      Definition: Item is missing because it is unknown. But in the case of variables concerning zebra mussel presence, it can mean that a lake remains uninvaded with zebra mussels.
        
4. Variable List
                  
1. Name: SURVEY_ID
Description: unique identifier for the electrofishing survey performed. Each survey ID represents a combination of the lake, survey type, and survey date.

2. Name: SURVEY_YEAR
Description:  Year the electrofishing survey occurred.

3. Name: DOW_KITTLE
Description: Unique 8 digit ID for MN lakes. Note that the last two digits can at times be specific to different bays/locations in the same lake, so at times using a parent DOW (only the first 6 digits) is more appropriate.

4. Name: WATER_BODY_NAME
Description: Name of the lake.

5. Name:COUNTY_NAME
Description: Minnesota County that the lake is located in.

6. Name: AREA_NAME
Description: Name of the MN DNR Fisheries Area Office that oversees and samples that particular lake. Useful when we have questions about surveys, helps us determine who to contact.

7. Name: REGION_NAME
Description: Arbitrary split of the state of MN into 4 regions (Central, Northeast, Northwest, and Southern). This system was used to split up the individual fish data to make it more manageable. 

8. Name: SURVEY_TYPE_NAME
Description: Survey type that the electrofishing survey sampling was done during. These names come from the MN DNR. 

9. Name: SURVEY_LIFE_STATUS_NAME
Description: Denotes how the survey ended up in the DNR database. Either signed off by the region or if it was migrated from a paper copy or older database. 

10. Name: SAMP_STA_TYPE_ABBREV
Description: Abbreviation for the type of electrofishing sampling done. The only three that were kept are “EW” which is electrofishing for walleye, “SEF” which stands for special electrofishing, and “EF” which is standard electrofishing (with a boat). EW is a newer code used, so older surveys targeting walleye were either coded as SEF or EF. 

11. Name: SAMP_STA_TYPE_NAME
Description: Name for the electrofishing sampling done. The full name of “SAMP_STA_TYPE_ABBREV.”

12. Name: SAMPLING_START_DATE
Description: Day that the electrofishing survey started in YYYY-MM-DD.

13. Name: SAMPLING_END_DATE
Description: Date that the electrofishing survey ended in YYYY-MM-DD. (Often start and end dates are the same).

14. Name: EFFORT
Description:  Number of hours spent electrofishing. 

15. Name: EF_SECONDS
Description: Number of seconds electrofished. 

16. Name: WATER_TEMP_F
Description: Temperature of the water recorded on the electrofishing report in Fahrenheit. Is NA if temperature was NOT recorded during the survey.

17. Name: SPECIES_TARGETED
Description: Species of fish targeted during the survey, (WAE is walleye). Kept any survey listing walleye as a target, and all NAs. We wanted to include any survey where walleye were reasonably sampled. We also wanted to keep surveys that intended on catching walleye, but didn’t (0 catch surveys).

Species Abbreviation	Common Name	Scientific Name
	BLC		black crappie	Pomoxis nigromaculatus
	LMB		largemouth bass	Micropterus salmoides
	NOP		northern pike	Esox lucius
	SMB		smallmouth bass	Micropterus dolomieu
	WAE		walleye		Sander vitreus
	WHB		white bass	Morone chrysops
	YEP		yellow perch	Perca flavescens


18. Name: NUMBER_OF_NETTERS
Description: Number of individuals netting fish on the electrofishing boat. Not always a whole number, likely an average of netters participating. 

19. Name: REPRESENTATIVE_SAMPLING
Description: A code included with the original data, Y if person conducting the survey thought it was a representative survey, a N if it wasn't, and NA if it was not recorded. 

20. Name: DAYLIGHT_SAMPLING
Description: Indicates (Y/N) if electrofishing was done during the daylight or at night. Only kept those that were no because walleye electrofishing ought to be done at night. 

21. Name: INTERMITTENT_SHOCKING
Description: continuous or intermittent use of power while electrofishing

22. Name: STOCKING_DAT_SOURCE
Description: Source that provided the stocking data. If “Steve”, this is from Steve Shroyer’s database that he put together using data from 2014 and prior. If “Paula” this is from Paula Phelps that pulled data from the MN DNR’s database called “FishPad.” If “AM” this information was provided by contacting the DNR Fisheries Area Office. If “Paula2” this comes from a list of lakes put together by Paula Phelps that do not have any stocking records and hence were not stocked. 

23. Name: FRY
Description: Indication of walleye fry stocking prior to the electrofishing survey in the Fall. “Y” means that fry were stocked prior to the survey, and “N” means fry were not stocked prior to the electrofishing survey, but fry may still have been stocked after the survey.

24. Name:FRL
Description: Indication of walleye fryling (in between fry and fingerling) stocking prior to the electrofishing survey in the Fall. “Y” means that fryling were stocked prior to the survey, and “N” means fryling were not stocked prior to the electrofishing survey, but fryling may still have been stocked after the survey.

25. Name:FGL
Description: Indication of walleye fingerling stocking prior to the electrofishing survey in the Fall. “Y” means that fingerling were stocked prior to the survey, and “N” means fingerling were not stocked prior to the electrofishing survey, but fingerling may still have been stocked after the survey.

26. Name: YRL
Description: Indication of walleye yearling stocking prior to the electrofishing survey in the Fall. “Y” means that yearling were stocked prior to the survey, and “N” means yearling were not stocked prior to the electrofishing survey, but yearling may still have been stocked after the survey.

27. Name: DD5: 
Description: Growing degree days, base temperature 5 degrees Celsius up to day of sampling. Source: GLM 2 model ((General Lake Model v2 Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton, D.P., Hanson, P.C., Read, J.S., de Sousa, E., Weber, M. and Winslow, L.A. (2019). A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON), Geosci. Model Dev., 12(1), 473-523.)

28. Name: DD0
Description: Growing degree days, base temperature 0 degrees Celsius up to day of sampling. Source: GLM 2 model ((General Lake Model v2 Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton, D.P., Hanson, P.C., Read, J.S., de Sousa, E., Weber, M. and Winslow, L.A. (2019). A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON), Geosci. Model Dev., 12(1), 473-523.)

29. Name: MODELED_TEMP_F
Description: Surface water temperature prediction for that particular lake, on that particular day from the GLM2 model (General Lake Model v2 Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton, D.P., Hanson, P.C., Read, J.S., de Sousa, E., Weber, M. and Winslow, L.A. (2019). A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON), Geosci. Model Dev., 12(1), 473-523.) in degrees Fahrenheit. 

30. Name: SURFACE_TEMP_F
Description: This column uses reported water temperature at time of survey (WATER_TEMP_F) if it was recorded, and wasn’t accidentally reported as a 0 (likely an NA that was somehow switched to a zero), and if there is no appropriate reported water temperature from the time of the survey, then modeled temperature (MODELED_TEMP_F) is used here. If modeled temp did not exist for the lake and no temperature was recorded, then it will say NA.  

31. Name: ANNUAL_MED_SECCHI_M
Description:  Annual median Secchi in meters, for that particular lake and year. Derived first from Dr. Kelsey Vitense’s model (Hierarchical GAM of seasonal and annual trends), then by observed Secchi measurements if not in Dr. Kelsey Vitense’s model and lastly from remotely sensed data if no data existed from the previous two sources.

32. Name: SECCHI_SOURCE
Description: Source of the Secchi data in “ANNUAL_MED_SECCHI_M” KV = output from Dr. Kelsey Vitense’s model, Obs = observed secchi data, and RS = data from remote sensing. 

33. Name: ANNUAL_GDD_5C
Description: growing degree days based on water temperature, base temperature of 5 degrees celsius. This is the annual value, whereas “DD5” only represents the growing degree days up until the day of the survey. This represents GDD accumulated throughout the year. 

34. Name: AREA_HECTARES 
Description: Surface area of the lake in hectares.

35. Name:MAX_DEPTH_M
Description: Maximum depth of the lake in meters.

36. Name: MEDIAN_93_19_GDD
Description: a calculated median of annual growing degree days of water temperature, base temperature of 5 degrees C, from 1993 through 2019. 1993 - 2019 is the range of the data, hence why these dates were used in calculating the median here.

37. Name: TOTAL_CATCH
Description: Total number of YOY walleye caught during the electrofishing survey. This figure was obtained by summing the individual YOY fish caught. It is 0 if a survey looking for walleye was done but none were caught. 

38. Name: CPUE
Description: Catch per unit effort, calculated by taking “TOTAL_CATCH” and dividing by “EFFORT.”

39. Name: PARENT_DOW
Description: The first 6 digits of the 8 digit DOW number (DOW_KITTLE). Useful for whole lake metrics that don’t need to differ across bays or basins. 

40. Name: ZM
Description: Indicates if a lake has zebra mussels currently “zebra mussel” or if the lake is still uninvaded “uninvaded.”

41. Name: YEAR_INFESTED
Description: Year that zebra mussels were confirmed to be in a lake by the MN DNR’s Infested Waters List. IF uninvaded, it is NA.

42. Name: PRE_ZM
Description: A “1” appears if the survey was done in a lake that currently has zebra mussels, but zebra mussels were not present during the time of the electrofishing survey. A “0” appears if the survey occurred after zebra mussels were confirmed. If uninvaded it will be NA.

43. Name: POST_ZM
Description: A  “1” appears in the column if the survey was done in a lake that currently has zebra mussels, and the survey was either done the year zebra mussels were confirmed, or later. A “0” appears if the survey occurred before zebra mussels were confirmed. If uninvaded it will be NA.

44. Name: INVASION_STATUS
Description: Three options for this column. “NO_ZM” means there are no zebra mussels in the lake. “PRE_ZM” means there are currently zebra mussels in the lake, but there were no zebra mussels in the lake during the time of the electrofishing survey. “POST_ZM” means there are currently zebra mussels in the lake, and the electrofishing survey took place either the year that zebra mussels were confirmed in the lake or after zebra mussels were confirmed to be in the lake. 

45. Name: INVASION_STATUS_BINARY
Description: Is a 0 if zebra mussels were not present during the electrofishing survey (PRE_ZM or NO_AM), and a 1 if zebra mussels were present in the lake during the survey. 

46. Name: RECRUITMENT_SUCCESS
Description: arbitrary cutoff of a CPUE of 15 or greater. If greater than or equal to 15, considered a recruitment success (1),  if less than 15, failure (0).

47. Name:LAKE_CENTER_LAT_DD5
Description: Latitude of approximate lake center.

48. Name: LAKE_CENTER_LONG_DD5
Description: Longitude of approximate lake center. 

49. Name: LAKE_CENTER_UTM_EASTING
Description: UTM Easting of approximate lake center. 

50. Name:LAKE_CENTER_UTM_NORTHING
Description: UTM Northing of approximate lake center. 

51. Name: SHORE_LENGTH_MILE
Description:  Perimeter of the lake/ total length of the lake shore in miles. 

52. Name: ZM_LAKE
Description: Indicates if a lake is invaded with zebra mussels AND we have electrofishing data from AFTER the lake was invaded with a “1” (lakes that have at least one survey where POST_ZM == 1), otherwise it is “0”.

53. Name: ZM_2019 
Description: This is very similar to “ZM” except for lakes that were invaded in 2020 and 2021 will be listed as “uninvaded” in this column because they were not invaded during the span of the electrofishing data which only goes through 2019. 

54. Name: STOCKED
Description: A binary of “1” meaning the lake was stocked with fry, or fryling prior to the Fall electrofishing survey. “0” if the lake was not stocked with fry or fryling prior to the Fall electrofishing survey. Note, this doesn’t consider stocked yearlings or adults as they wouldn’t show up as Age-0 in the Fall survey, and surveys, where fingerlings were stocked prior to the Fall electrofishing survey, were excluded from the final data set.

--
Citation: 
Dr. Kelsey Vitense's model is described in: 
Vitense, K. and Hansen, G.J.A. (2023), Nonlinear water clarity trends and impacts on littoral area in Minnesota lakes. Limnol. Oceanogr. Lett. https://doi.org/10.1002/lol2.10323

Data, metadata, and code related to Dr. Kelsey Vitense's model are available at the Data Repository for the University of Minnesota:
Vitense, Kelsey; Hansen, Gretchen J A. (2021). Data and R code supporting “Non-linear water clarity trends and impacts on littoral area in Minnesota lakes”. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/7b2s-gv09.