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STUDY PERFORMANCE REPORT
State: Michigan
Project No.:
Study No.: 230756
Title: Development of management scenarios
for lake and stream habitat and fisheries
under current and future land-use and
climate conditions
Period Covered:
F-80-R-12
October 1, 2010 to September 30, 2011
Study Objectives: The overall objective of this project is to develop a tool that incorporates land-use
and climate change scenarios and societal values of lakes and streams to identify management
priorities based on assessed sensitivity and risk. The specific objectives of this study are to:
1. Assess habitat conditions for all lakes and streams statewide under current land-use and
climate conditions.
2. Determine how current habitat conditions influence sport fish populations and fish
community structure in lakes and streams
3. Determine the potential changes in habitat suitability, sport fish populations, and fish
community structure in response to changes in land-use and climate conditions.
4. Identify and map the lakes and streams that are most at risk to change.
5. Develop statistical models to predict how anglers use lake and stream resources at a
statewide scale.
6. Generate information for evaluating none-fisheries uses of lake and stream resources at a
statewide scale using GIS techniques.
7. Prioritize lakes and streams for management based on their habitat and fisheries risks and
social uses and values.
Summary: During this first year of the study, we assembled and calculated numerous data that
describe the usage of lakes. We will use these data, in combination with another lake database
built from a previous project, to evaluate impacts of climate and land-use changes and to develop
management scenarios. We have developed models for predicting residential development, lake
surface temperature, and growing degree days for over 6,500 unsampled lakes based on the
database we built. A preliminary Neural Network model for predicting daily stream temperature in
Michigan from April through September was developed.
Findings: Jobs 1–6 and 9 were active this year. The progress of each active job is reported below.
Job 1. Title: Develop temperature models.–For Streams and rivers, a preliminary Neural Network
model for predicting daily stream temperature in Michigan from April through September was
developed. We assembled a database for running the model to predict daily water temperature.
The model output daily temperature will be used to generate stream/river temperature variables
to describe thermal regimes that will be linked with fish distribution and climate changes. For
lakes, progress was made in assembling the information required to run temperature models for
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F-80-R-12, Study 230756
inland lakes. Detailed lake temperature models require information on weather, lake
morphometry, and inflows and outflows. An Access database was compiled containing hourly
weather data for 64 weather stations across the state (4,154,489 hourly records of air
temperature, precipitation, relative humidity, total solar flux density, wind speed, and wind
direction; there are an average of 7.4 years of hourly data per station). Under another project,
lake area at successive depths has been tabulated for about 2,000 inland lakes. Computer code for
a lake temperature model was obtained but not yet applied.
Job 2. Title: Develop lake profile models.–Nutrient data, lake temperature and dissolved oxygen
profiles, and lake morphology data were assembled into a database. Preliminary statistical
models were developed that predict temperature and oxygen characteristics from landscape and
lake morphology data.
Job 3. Title: Develop community/habitat models.–Fish species data were assembled into a
database. Preliminary empirical models were developed for predicting species presence/absence
and abundance from lake surface temperature, oxygen concentration, and stratification pattern.
Job 4. Title: Develop bioenergetics models.–A bioenergetics model was coded in R language and
used to simulate growth of walleye in over 9,000 inland lakes 5 acres and larger. Bioenergetics
parameters were assembled for representative fish species from each of the six Michigan fish
assemblages identified by Wehrly et al. (submitted). These species include bluegill, largemouth
bass, smallmouth bass, yellow perch, walleye, northern pike, lake trout, and a generalized
coregonid representing other coldwater species.
Job 5. Title: Assemble and generate human dimension data.–Information on lake and stream
stocking were assembled into a database and organized into a GIS spatial data layer. Data
describing societal uses of lakes were assembled and generated for 6810 lakes that are 10 acres
or bigger. These data include total population, median income, total income, total households,
number of campgrounds, and total fishing license sales from 10 separate buffers (100 m, 1 km, 5
km, 10 km, 20 km, 30 km, 40 km, 50 km, 75 km, and 100 km) around each lake. They were
calculated using 2010 US census data, Michigan campground locations, Michigan state park
locations, and Michigan fish license sales. We acquired fishing access data for each lake from
related DNR databases and are in the process of assembling boaters’ information for each lake.
Job 6. Title: Develop fishing effort and harvest models.–We compiled a Michigan Inland Creel
Access database that contains seasonal total catch, catch rate, and fishing effort estimates for 182
inland lake angler surveys spanning from 1976 to 2010. A unique ID was assigned to each
surveyed lake in order to link the creel data to the Michigan Lake Database and other data
sources. The anglers’ survey data was linked with the inland lake data and boat access data.
Exploratory data analyses were conducted and preliminary regression models have been set up to
examine factors affecting angling effort.
Job 9. Title: Write annual performance reports.–This performance report was prepared as
scheduled.
Prepared by: Lizhu Wang, James Breck, Kevin Wehrly, and Zhenming Su
Date: October 28, 2011
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