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Holly Kundel

This dataset provides shapefile outlines of the 7,150 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is also included. This dataset is part of a larger data release of lake temperature model inputs and outputs for 7,150 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9CA6XP8).
This dataset summarized a collection of annual thermal metrics to characterize lake temperature impacts on fish habitat for 7,150 lakes from uncalibrated models (PB0) and 449 from calibrated models (PBALL). The dataset includes over 172 annual thermal metrics.
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Fish data on six species (black crappie (Pomoxis nigromaculatus), bluegill (Lepomis macrochirus), largemouth bass (Micropterus salmoides), northern pike (Esox lucius), walleye (Sander vitreus), and yellow perch (perca flavescens)) caught in gill nets and trap nets between 2000 and 2019 during Minnesota Department of Natural Resources (MNDNR) fisheries surveys done in the months of June through September. Fish catch and effort (number of nets set overnight) comes from over 1,000 Minnesota lakes. In addition to fisheries data, we included additional information concerning lake characteristics, predicted water temperature, and watershed land use. Lake area and maximum depth were obtained from MNDNR public databases....
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. General Lake Model verion 2 process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error for 449 lakes (PBALL). Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations for 7,150 lakes.
Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in...
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