Data Package Summary   View Full Metadata

  • LAGOS - Predicted and observed maximum depth values for lakes in a 17-state region of the U.S.
  • Oliver, Samantha; University of Wisconsin
  • Soranno, Patricia; Michigan State University
  • Fergus, C.; Michigan State University
  • Wagner, Tyler; Pennsylvania Cooperative Fish and Wildlife Research Unit
  • Webster, Katherine; Trinity College
  • Scott, Caren; Michigan State University
  • Winslow, Luke; University of Wisconsin
  • Downing, John; Department of Ecology, Evolution and Organismal Biology
  • Stanley, Emily; University of Wisconsin
  • 2015
  • Oliver S., P. Soranno, C. Fergus, T. Wagner, K. Webster, C. Scott, L. Winslow, J. Downing, E. Stanley. 2015. LAGOS - Predicted and observed maximum depth values for lakes in a 17-state region of the U.S.. Environmental Data Initiative. Dataset accessed 3/20/2018.
  • This dataset includes predicted and observed values of maximum depth for lakes in the upper Midwest and northeast United States. All observed values came from LAGOS ver 1.040.0 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 40 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, observed maximum depth values (n = 8164) were used to train and validate a predictive mixed effects model for lake depth using terrestrial and lake morphology as predictors (Oliver et al., submitted). Predicted values (n = 50 607) generated by the model had a root mean squared error of 7.1 m. This research was supported by the NSF Macrosystem Biology awards 1065786, 1065818, and 1065649.
  • N: 48.99      S: 34.716      E: -97.904      W: -67.091
  • Data Policies Copyright Board of Regents, University of Wisconsin, Madison. This information is released to the public and may be used for academic, educational, or commercial purposes subject to the following restrictions: The Data User must realize that these data sets are being actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the NTL lead Principal Investigator,, to check on other uses of the data. Where appropriate, the Data User may be encouraged to consider collaboration and/or co-authorship with original investigators. The Data User must realize that the data may be misinterpreted if taken out of context. We request that you provide the NTL lead Principal Investigator, ATTN: Data Access, Center for Limnology, University of Wisconsin-Madison, 680 North Park St., Madison, WI 53706 with a copy of any manuscript using the data so that it may be reviewed and comments provided on the presentation of our data. The Data User must acknowledge use of the data by an appropriate citation (see Citation) of the NTL-LTER database. A generic citation for our databases is: name of data set, North Temperate Lakes Long Term Ecological Research program, NSF, contact person for data set, Center for Limnology, University of Wisconsin-Madison. The data set name and contact person for each data set can be found in the metadata header of the online data sets. The Data User must send two reprints of any publications resulting from use of the data to the address above. We would like to include such manuscripts in our LTER publications list. The Data User must not redistribute original data and documentation without permission from Emily Stanley, lead Principal Investigator, ( While substantial efforts are made to ensure the accuracy of data and documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is". The North Temperate Lakes LTER shall not be liable for damages resulting from any use or misinterpretation of data sets. Data users should be aware that we periodically update data sets. Our goal is to release all long term data associated with core research areas within 2 years of collection. These data and accompanying metadata will be available for download from the NTL-LTER web site. By using these data, the Data User agrees to abide by the terms of this agreement. Thank you for your cooperation.
  • doi:10.6073/pasta/f00a245fd9461529b8cd9d992d7e3a2f

EDI is proud to be affiliated with the following organizations: DataCite logo DataONE logo ESIP logo re3data logo