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Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Data files contain the simulated mean daily environmental conditions experienced by particles (which can be assumed to be planktonic larval alewife or yellow perch) in Lake Michigan during March 15 - July 31 of past and future years. Simulations were generated by integrating a series of climatic, hydrodynamic, biogeochemical, and Lagrangian particle dispersion (LPD) models. For each year, 42,765 particles (i.e., each representing a theoretical larval fish) were released from coastal and nearshore locations and tracked sub-hourly for 50-days following their release. Each year's dataset summarizes individual particle experiences (e.g., light, zooplankton prey, temperature) into daily averages.
This data was used for the analysis in the paper "Assessing factors related to Walleye stocking success in the midwestern United States". This data includes stocking records of walleye from the Midwestern United States and subsequent evaluations of these stockings as provided by state agencies. Additionally, attributes of lakes such as size (depth, area), trophic state, and temperature are included to evaluate factors that relate to walleye stocking success. A second copy of the data is included that relies on imputation to fill in data gaps. Methodological processes are outlined in the associated paper.
These data include aerobic scope and thermal tolerance measurements from two cisco (Coregonus artedi) populations to evaluate performance and potential adaptation to warming Great Lakes habitats. Cisco come from two stock sources: 1) a northern latitude Lake Huron stock collected as gametes from Les Cheneaux Islands, MI, USA in 2015 and raised in a USGS aquaculture lab in Ann Arbor, MI, and 2) a southern latitude stock from Crooked Lake, Noble County, IN, USA collected as adults from the wild in 2021 and 2022 and brought to Ann Arbor, MI. Data include three primary datasets. "Aerobic Scope Compiled Data" provides measures of cisco (Coregonus artedi) metabolic rates from 30L swim chamber respirometry trials (n=88)....
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