Link on DRUM: https://conservancy.umn.edu/handle/11299/228403 ____________________________________________________________________________ This codebook.txt file was generated on 2022.07.11, and updated 2023.02.07 by Holly Kundel ------------------- GENERAL INFORMATION ------------------- 1. Data in Support of Predicting climate change impacts on poikilotherms using physiologically guided species abundance models 2. Author Information Principal Investigator Contact Information Name: Gretchen Hansen Institution: University of Minnesota Address: 2003 Upper Buford Circle, St. Paul, MN 55108 Email: ghansen@umn.edu ORCID: https://orcid.org/0000-0003-0241-7048 Associate or Co-investigator Contact Information Name: Erin Schliep Institution: University of Missouri Address: 146 Middlebush Hall, Columbia, MO 65211 Email: schliepe@missouri.edu ORCID: https://orcid.org/0000-0002-2803-3467 Additional Authors Name: Joshua North Institution: University of Missouri Name: Holly Kundel Institution: University of Minnesota Name: Christopher Custer Institution: Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University Name: Jenna Ruzich Institution: University of Minnesota 3. Date published or finalized for release: 2022.06.23 4. Date of data collection (single date, range, approximate date): 1988 - 2019 5. Geographic location of data collection (where was data collected?): Minnesota, USA 6. Information about funding sources that supported the collection of the data: This work was supported by the U.S. Geological Survey Midwest Climate Adaptation Science Center Grant No.G20AC00096. Data were assembled by collaborators at the University of Minnesota - Twin Cities. Original fish data were collected by the Minnesota Department of Natural Resources (MNDNR) as part of their standard sampling program. 7. Overview of the data (abstract): Fish catch and effort data for three species caught in gill nets and trap nets between 1988 and 2019 as part of Minnesota Department of Natural Resources (MNDNR) fisheries surveys conducted during the summer and early fall are included from over 1,300 Minnesota lakes. The three fish species included are: bluegill (Lepomis marochirus) a warm-water adapted species, yellow perch (Perca flavescens) a cool-water adapted species, and cisco (Coregonus artedi) a cold-water adapted species. Additional data concerning lake characteristics and surrounding land cover were also included. Mean July lake surface temperature was calculated using simulated daily water temperatures. Watershed land use including agricultural, barren, forest, grass, shrub, urban, and wetland cover, was determined using the 2016 National Land Cover Database. Secchi, a measure of water clarity was calculated from remotely sensed Secchi depth courtesy of Max Glines. Lastly, lake area and maximum depth were obtained from MNDNR public databases. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/) 2. Links to publications that cite or use the data: Wagner, T., E.M. Schliep, J.S. North, H. Kundel, C.A. Custer, J.K. Ruzich, and G.J.A. Hansen. Predicting climate change impacts on poikilotherms using physiologically guided species abundance models. In Prep. 3. Links to other publicly accessible locations of the data: Daily lake surface temperature predictions: doi:10.5066/P9CEMS0M 2016 National Landcover Database: https://www.mrlc.gov/national-land-cover-database-nlcd-2016 MNDNR Lake Data: https://gisdata.mn.gov/dataset/water-lake-basin-morphology 4. Recommended citation for the data: Hansen, G.J.A., E.M. Schliep, J.S. North, H. Kundel, C.A. Custer, and J.K. Ruzich (2022) Predicting climate change impacts on poikilotherms using physiologically guided species abundance models. Retrieved from the Data Repository for the University of Minnesota --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: BLG_YEP_TLC_MN_with_predictors_allyears.csv Short description: Fish, lake characteristics, and landcover data. 2. Are there multiple versions of the dataset? No -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: Fish catch and effort data were collected by the Minnesota Department of Natural Resources (MDNR) between 1988 and 2019 using gill nets and trap nets as part of their standard sampling program (Minnesota Department of Natural Resources (MNDNR) 2017). These gears are designed to index the abundance of sport fishes in the littoral (nearshore) zone, although gill nets are deployed in deeper waters. To account for changes in survey types throughout the time series and to maximize standardization across surveys, we restricted our analysis to a subset of survey types that minimize among-survey variation in survey methodology (Minnesota Department of Natural Resources (MNDNR) 2017). Both gill nets and trap nets were deployed at multiple index stations within a lake. One unit fixed effort consisted of one net (gill net or trap net) deployed for a 24-hour sampling period. Depending on management goals for each lake, sampling occurred during the ice-free season in Minnesota on an every 1-year to every 10-year rotation, resulting in a different number of observations for each lake. The data used in our analysis consist of lakes sampled between June 1 and September 30 during the 32-year time period. The median number of surveys per lake was 4, with a minimum and maximum of 1 and 26, respectively. Catch and effort data are for three ecologically and socioeconomically important species including bluegill (Lepomis macrochirus), yellow perch (Perca flavescens), and cisco (Coregonus artedi). For each species, catch was calculated as the sum of individuals captured in each gear type, and effort was the sum of the number of nets deployed for each gear type from a given survey. We included environmental variables associated with fish abundance as possible covariates in our model. Environmental variables were derived from various sources. Lake area and maximum depth were obtained from MNDNR public databases (https://gisdata.mn.gov/dataset/water-lake-basin-morphology). Watershed land use was calculated based on the 2016 National Land Cover Database (Homer et al. 2020), quantified as the proportion of watershed area falling into agricultural, barren, forest, grass, shrub, urban, or wetland land use categories and extracted using the LAGOSNE R package (Sorano et al. 2017; Stachelek et al. 2019). Water clarity was quantified using annual lake-specific median values of remotely sensed Secchi depth (Max Gilnes, Rensselear Polytechnic Institute, Personal Communication). Mean July water temperature was used to inform us of how warm MN lakes became in the summer for our three species of interest. The temperature data used to calculate the mean July surface temperature and the rolling mean for July surface temperature come from the estimated daily surface temperatures for the contiguous United States (Willard et al. 2022). Works Cited Homer, C., Dewitz, J., Jin, S., Xian, G., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., Stehman, S., Auch, R. & Riitters, K. (2020) Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 184–199. https://dx.doi.org/10.1016/j.isprsjprs.2020.02.019. Massie, D.L., Hansen, G.J., Li, Y., Sass, G.G. & Wagner, T. (2021) Do lake-specific characteristics mediate the temporal relationship between walleye growth and warming water temperatures? Canadian Journal of Fisheries and Aquatic Sciences, 78, 913–923. https://dx.doi.org/10.1139/cjfas-2020-0169. Minnesota Department of Natural Resources. 2014. Lake Basin Morphology. Distributed by Minnesota Geospatial Commons. https://gisdata.mn.gov/dataset/water-lake-basin-morphology Minnesota Department of Naural Resources (MNDNR) (2017) Manual of instructions for lake survey. Minnesota Department of Natural Resources, Special Publication No 180, St. Paul, Minnesota (version 104, released January 2019). Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., Bremigan, M.T., Carpenter, S.R., Carr, J.W., Cheruvelil, K.S., Christel, S.T., Claucherty, M., Collins, S.M., Conroy, J.D., Downing, J.A., Dukett, J., Fergus, C.E., Filstrup, C.T., Funk, C., Gonzalez, M.J., Green, L.T., Gries, C., Halfman, J.D., Hamilton, S.K., Hanson, P.C., Henry, E.N., Herron, E.M., Hockings, C., Jackson, J.R., Jacobson-Hedin, K., Janus, L.L., Jones, W.W., Jones, J.R., Keson, C.M., King, K.B.S., Kishbaugh, S.A., Lapierre, J.F., Lathrop, B., Latimore, J.A., Lee, Y., Lottig, N.R., Lynch, J.A., Matthews, L.J., McDowell, W.H., Moore, K.E.B., Neff, B.P., Nelson, S.J., Oliver, S.K., Pace, M.L., Pierson, D.C., Poisson, A.C., Pollard, A.I., Post, D.M., Reyes, P.O., Rosenberry, D.O., Roy, K.M., Rudstam, L.G., Sarnelle, O., Schuldt, N.J., Scott, C.E., Skaff, N.K., Smith, N.J., Spinelli, N.R., Stachelek, J., Stanley, E.H., Stoddard, J.L., Stopyak, S.B., Stow, C.A., Tallant, J.M., Tan, P.N., Thorpe, A.P., Vanni, M.J., Wagner, T., Watkins, G., Weathers, K.C., Webster, K.E., White, J.D., Wilmes, M.K. & Yuan, S. (2017) LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes. GigaScience, 6, 1–22. https://dx.doi.org/10.1093/gigascience/gix101. Stachelek, J., Oliver, S. & Masrour, F. (2019) LAGOSNE: Interface to the lake multi-scaled geospatial and temporal database. R package version 202. Willard, J., Read, J.S., Topp, S.N., Hansen, G.J.A., and Kumar, V., 2022, Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020): U.S. Geological Survey data release, https://doi.org/10.5066/P9CEMS0M. 2. Methods for processing the data: Programs were written for R. Analyses were performed using R version 4.2.0 (2022-04-01) 3. People involved with sample collection, processing, analysis, and/or submission: Tyler Wagner, Erin Schliep, Joshua North, Holly Kundel, Christopher Custer, Jenna Ruzich, Gretchen Hansen, and numerous state agency staff (especially Corey Geving). ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: BLG_YEP_TLC_MN_with_predictors_allyears.csv ----------------------------------------- 1. Number of variables: 22 2. Number of cases/rows: 29,562 3. Missing data codes: NA 4. Variable List A. Name: DOW Description: An 8-digit lake ID number used by MN DNR and other state agencies as a unique lake identifier B. Name: Site.id Description: National hydrography dataset, high resolution (nhdhr) unique lake identifier used at the national level by USGS C. Name: MNDOW_ID Description: Another version of the first column ‘DOW’ that contains the prefix ‘mndow_’ prior to the 8-digit lake ID number D. Name: year Description: Year fish was caught in survey E. Name: COMMON_NAME Description: Name of the fish species. Either bluegill, cisco, or yellow perch. F. Name: TOTAL_CATCH Description: Total number of that species caught in a net type (either trap net or gill net) G. Name: EFFORT Description: Total number of nets of a particular type (either trap net or gill net) set out overnight H. Name: TN Description: Indicates if a trap net was used Value labels: 0: trap net was not used, gill net was used 1: trap net was used I. Name: GN Description: Indicates if a gill net was used Value labels: 0: gill net was not used, trap net was used 1: gill net was used J. Name: Mean.July.Temp Description: Mean July surface temperature for the lake in the year listed in the ‘year’ column K. Name: july_temp_rolling_mean Description: A five-year rolling mean of July surface temperature L. Name: urban Description: Percentage of watershed land use that is urban M. Name: forest Description: Percentage of watershed land use that is forested N. Name: ag Description: Percentage of watershed land use that is agricultural O. Name: wetlands Description: Percentage of watershed land use that are wetlands P. Name: shrub Description: Percentage of watershed land use that is shrub land Q. Name: grass Description: Percentage of watershed land use that is grassland R. Name: barren Description: Percentage of watershed land use that is barren S. Name: annual.median.rs Description: Remotely sensed Secchi value T. Name: secchi_rolling_mean Description: Five-year rolling mean Secchi depth for that lake. Secchi depth is used to measure water clarity. U. Name: LAKE_AREA_GIS_ACRES Description: The surface area of the lake in acres V. Name: MAX_DEPTH_FEET Description: Maximum depth of the lake in feet