Track A - Water Resources Center - University of Minnesota

Lori A. Krider
Joseph A. Magner
Jim Perry

Investigations
• Temperature regimes of
groundwater-fed streams
vs. surface water fed
streams
• Affect of air temperature
on the water temperature
in groundwater-fed
streams
• Implications for climate
change
• Use in guiding land
management

Importance
• Air temperatures are very influential on surface and
groundwater temperatures (Erickson et al., 2000;
Meisner et al., 1988)
• Water temperatures dictate species composition and
cold water habitat supports trout populations
• No published work investigates this relationship in
carbonate systems across watersheds
• Other uses: relate water temperatures to trout growth
patterns and diet; choose study sites when research is
related to water temperature

Study Area
• Southeastern Minnesota’s Driftless
Region
• Lacks glacial scouring; old valleys
with dramatic changes in elevation
• Carbonate rocks: made of easily
eroded minerals
• Karst geology: well-developed
surface features such as springs and
sinkholes
• Incipient karst geology: seeps and
groundwater recharge through
infiltration

Temperature ( o C)
Time Frame
• “Present” data set
• If climate change
has been escalating
in the past several
decades, how far
back will the
measurements still
represent present
conditions?
9.0
8.5
8.0
7.5
7.0
6.5
6.0
5.5
5.0
Temperature Over Time, 1986 - 2008: Rochester IA
(3-Month Moving Window Average)
1998
1998
Year
Rochester IA: approximately in the middle
of our study streams

Data Details
• 7 counties
• 40 study streams
Rice
Goodhue
Wabasha
• 106 temperature
loggers
• 3,606 weekly
averages
Olmstead
Winona
Fillmore
Houston

Data Source
• Water temperature data
• STORET, DNR, David Huff and Toby Dogwiler
• Discrete and continuous -> weekly averages
• Year-round, winter intensive or non-winter intensive
• Air temperature data
• NOAA weather stations
• Thiessen polygons were created for six counties
• Between 7.1 km and 53.8 km from the streams they were
matched to

Statistical Analysis
• Linear regression models
(y = mx +b -> T w =B(T a )+A)
• Produces R 2 value (0 – 1)
• How well the model
explains the variation in
the data
• Closer to one is better
• Marginal R 2 improvements
with non-linear models
(between 0.0001 and
0.135)
http://www.unr.edu/math/events/index.html

Terminology
• Regressions explained in terms of the project
• Slope: how quickly water temperatures rise as a function
of air temperatures
• Intercept: temperature of the water when the air
temperature becomes freezing
• R 2 value: how much of the variation in stream
temperature can be explained by air temperatures

Temporal Scale
• What is best for regressions of groundwater-fed streams?
• Pilgrim et al. (1998): 36 surface water streams and 3
groundwater-fed streams across MN
• monthly produces highest R 2 (Apr. – Oct.)
• Time lags up to 7 days for rivers up to 15 ft deep (Stefan and
Pred’homme, 1993)
• R 2 for a sub-set of our streams
• 0.56 at monthly scale, April – October data
• 0.86 at weekly scale, year-round data
• Number of data points
• 431 monthly averages, Apr. – Oct.
• 1734 weekly averages, year-round

Results Summary & Comparison
• Slopes, intercepts and R 2 varied much between streams
• Slopes and intercepts were markedly different from
values displayed by surface water fed streams
Study Streams
Slopes
0.18 - 0.74
Intercepts
2.90 - 8.29
Pilgrim et al.’s Study Streams
Slopes
0.85 - 1.15
Intercepts
-1.51 - 4.01

Average Weekly Water Temperature (C)
Average Weekly Water Temperature (C)
Exemplary Results
20.00
Snake Creek Weekly Linear Regression
1999 - 2000, 2003, 2005, 2007
y = 0.3218x + 7.3901
R² = 0.591
Winnebago Creek Weekly Linear Regression
2000 - 2003 & 2008
20
y = 0.3424x + 6.93
R² = 0.9771
15.00
15
10.00
10
5.00
5
0.00
0.00 5.00 10.00 15.00 20.00 25.00 30.00
Average Weekly Air Temperature (C)
0
-20 -15 -10 -5 0 5 10 15 20 25 30
Average Weekly Air Temperature (C)
Lowest R 2
Highest R 2

Average Weekly Water Temperature (C)
Lumped Model
Our Study Streams
Slope: 0.38
Intercept: 6.63
R 2 value: 0.83
SE: 1.98
SD: 4.79
Pilgrim et al.’s Study Streams
Slope: 0.97
Intercept: 1.88
All Streams Weekly Regression
1999 - 2008
25
20
15
10
5
y = 0.3819x + 6.6257
R² = 0.82913
0
-30 -20 -10 0 10 20 30
Average Weekly Air Temperature (C)

Intercept
Mechanisms of Control
• Adapted from
O’Driscoll and
DeWalle (2004)
• Our R 2 is
considerably
lower (vs. 0.89)
• due to spatial
and temporal
differences
• Protection vs.
restoration
9
8
7
6
5
4
3
Slope vs. Intercept
All Streams Weekly Linear Regression
Groundwater Control
BSC
NBC
Gil C
CSB
Co C
Ba C
He C
Be C
y = -4.6744x + 8.1617
R² = 0.3893
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Slope
Ma BW
Ru C
No BW
SD = 0.13, SE = 0.10
Pi C
Meteorological Control
NFZR

Contributing Factors
• Factors that affect the air-water temperature relationship
• No/little effect on R 2 , slope or intercept
• Number of weekly averages (< .0.08 for all)
• Number of known springs within 50 m (< 0.07 for all)
• Number of known springs within 250 m (< 0.005 for all)
• Number of temperature loggers (< 0.11 for all)
• Minor watershed area (acres) (< 0.14 for both R 2 & intercept)
• Some effect on R 2 , slope or intercept
• Minor watershed area vs. slope (R 2 = 0.36)

Groundwater vs. Surface Water
• Groundwater-fed streams have drastically different
temperature regimes than surface water fed streams
• Comparison between slopes and intercepts
• Groundwater input doesn’t affect the strength of the airwater
temperature correlation
Our Study Streams
R 2 values: range
0.59 - 0.98
R 2 values: lumped
0.83
Pilgrim et al. Study Streams
R 2 values: range
0.67 - 0.96
R 2 values: lumped
0.83

Other Findings
• Could not provide concrete evidence that the amount of
groundwater input affects R 2 , slope, or intercept
• Incomplete karst inventory database
• Groundwater inputs are difficult to quantify accurately
• Graphing slope vs. intercept suggests mechanisms for
control
• Asymptote near or above 0 o C water temperatures with
air temperatures well below 0 o C
• Surface water fed streams asymptote at 0 o C water
temperatures with air temperatures at 0 o C

Groundwater Inflow
• Most important
determinant of water
temperatures in
groundwater-fed streams
• Discharge
• Lentz farm
• Stream velocity
• Shade
• Source of resurgence
• Water table vs. interflow
Artisan spring on Ralph Lentz farm:
400 gallons /minute

Implications for Climate Change
• Streams in northerly climates do not always follow unity
at air temperatures > 20 o C
• Suggested by Mohensi & Stefan, 2000
• Varies from stream to stream: some level slightly, some
follow unity and some produce more scatter
• Streams that follow unity and have high R 2 values are
most promising as predictive tools
• Streams with higher slopes and lower intercepts are
more susceptible

Climate Change Continued
• A1B SRES regional climate change scenario for central
North America
• 2.4 and 6.4 o C above 2000 conditions for the summer
months (June – August) by the years 2080 – 2099 (IPCC
Working Group I, 2007)
• Transform marginal or near marginal habitat into unsuitable
habitat
• Restrict suitable summer habitat to directly downstream of
springs and expand suitable winter habitat (Meisner et al.,
1988)

Management for Mitigation
•Increase snow trapping in riparian areas
•Provide riparian shading
•Encourage stream deepening and
narrowing
•Reduce temperatures of shallow
groundwater aquifer

Literature Cited
• Brooks, K. N., P. F. Ffolliott, H. M. Gregersen, & L. F. DeBano. 2003. Hydrology and the Management of
Watersheds (3 rd ed.). Ames, Iowa: Iowa State University Press.
• Coldwater Fish and Fisheries Working Group. 2010. Wisconsin Initiative on Climate Change Impacts. First
Report: Released February 2011.
• Cristea, N., & J. Janisch. 2007. Modeling the Effects of Riparian Buffer Width and Effective Shade and
Stream Temperature. Environmental Assessment Program of the Washington State Department of
Ecology. Publication No. 07-03-028.
• Erickson, T. R. & H. Stefan. 2000. Linear Air/Water Temperature Correlations for Streams During Open
Water Periods. Journal of Hydrological Engineering 5(3): 317 – 321.
• Intergovernmental Panel on Climate Change Working Group I. 2007. Contribution of the Working Group I
to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007. Accessed
online 10 April 2011.
• Meisner, J. D., Rosenfeld, J. S., & Regier. 1988. The Role of Groundwater in the Impact of Climate Warming
on Stream Salmonines. Fisheries 13(3): 2 -8.
• Mohensi, O., H. G. Stefan & T. R. Erickson. 1998. A nonlinear regression model for weekly stream
temperatures. Water Resources Research 34: 2685 – 2692.
• O’Driscoll, M. A., & DeWalle, D. R. 2004. Stream-Air Temperature Relationships as Indicators of
Groundwater Inputs. AWRA Watershed Update 2(6).
• Pilgrim, J., X. Fang & H. Stefan. 1998. Stream Temperature Correlations with Air Temperatures in
Minnesota: Implications for Climate Warming. Journal of the American Water Resources Association
34(5): 1109 – 1121.
• Stefan, H. G. & E. B. Preud’homme. 1993. Stream Temperature Estimation from Air Temperature. Water
Resources Bulletin 29(1): 27 – 46.

Natural short-term declines in curly-leaf pondweed across a
network of sentinel lakes: potential impacts of snowy winters
Ray Valley, Steve Heiskary, Cindy Tomcko

Comprehensive report is in the
works
• Covers findings here
in addition:
• Correlations between
water quality and
curly-leaf growth and
summer plant growth
• Case studies
• Suggested future
investigations

Sustaining Lakes in a Changing Environment
(SLICE)
‣ 24 sentinel lakes; sites of cooperative
long-term monitoring and research.
DNR, PCA, USGS, SNF major
partners
‣ Water quality, zooplankton, aquatic
plants, fish and continuous
temperature data monitored since
2008
‣ Curly-leaf pondweed (CLP) occurs in
14; annual spring surveys (pointintercept)
in 11

Assessment Methods – Point Intercept
• Conducted during the
peak of growth (typically
late May/Early June)
• Rake throws at uniformly
space points spaced 80-m
apart.
• % Frequency is correlated
with % areal cover

Genesis: Serendipity
• Noticed declines in CLP cover across
most sentinel lakes since monitoring
began in 2008.
• Due to simultaneous declines across
network, knew immediately that something
environmental must be going on.

Curly-leaf declines
37%
decline
overall
80%
95%

Decline in surface growth in Pearl
Lake (Stearns Co.)
22.6% 0.75% 0.5%

Hmm…

Curly-leaf pondweed life history
‣ Invasive plant that’s
been present in MN
since 1907.
‣ Can grow abundantly
in spring then
senesces in July
‣ Algae blooms often
follow senescence in
productive lakes

Curly-leaf distribution
‣ Documented in 730 lakes;
probably occurs in many
more
‣ Most are found in the
central transition forest
landtype (min of 5% of all
lakes w/ DNR ID#’s).
‣ Speculation that range is
expanding northward

Curly-leaf pondweed life history
‣ Produces turion
propagules in summer.
‣ Turion production is
correlated with
temperature and
photoperiod
‣ Turions sprout in fall
and plant overwinters
green
‣ Boom-bust growth in
south, not so in the
north
‣ Good info on life
history; not on
ecosystem effects

Conservation value in the South
‣ In many SW prairie lakes
and urban lakes, CLP is
one of only a few plant
spp. that grow
‣ Supports vegetation
dependent native fish
communities in the SW
(e.g., largemouth bass,
bluegill, northern pike)
‣ Killing the plant in these
lakes may do more harm
than good in terms of
habitat and WQ if no
natives come in behind.

Back to the question – Curlyleaf
declines – what might be
going on here?

37%
decline
overall
Curly-leaf declines

Growing Season
Differences?

Growing
Degree
Days
Departure
from
Normal

Nah that’s not it –
2010 was actually
very warm and CLP
growth was lowest
we’ve seen

Links to spring water
temperatures?
In other words, cooler
springs = less growth?

Nah that’s not it –
spring water temps
have gotten warmer
since 2008

Spring Water Temperatures (°C
Ice-off - May 31st)
16
14
12
10
8
6
2008
2009
2010
4
2
0
St. Olaf Pearl St. James Portage Peltier

Links to ice cover
duration?
In other words,
increases in ice-cover
duration = reduced
growth?

Nope not it either –
duration of ice cover
has gotten shorter
since 2008 (34 fewer
days in St. James
between 2008 and
2010)

Days of Ice
180
160
140
120
100
80
60
2008
2009
2010
40
20
0
St. Olaf Pearl St. James Portage Peltier

Links to snow cover?
In other words,
increases in snow cover
early in winter =
reduced growth?

EUREKA!!

Dec. + Jan. Snowfall (in) Departure from 1971-2000
Normal
40
St. Olaf Pearl St. James Portage Peltier
30
20
10
0
-10
-20
-30
2000 2002 2004 2006 2008 2010 2012
Year

Findings
• Winters during most of the 2000’s were
less snowy than normal
• Easy winters for CLP expansion
• Last few winters have been snowier than
normal.
• Stressful on overwintering CLP plants
needing light for basal metabolism

What did 2011 bring?

Dec. + Jan. Snowfall (in) Departure from
1971-2000 Normal
Winter was even snowier
40
30
20
10
0
-10
-20
-30
2000 2002 2004 2006 2008 2010 2012
Year
St. Olaf Pearl St. James Portage Peltier

Curly-leaf declines leveled off

Implications of Climate Change
• Winters and ice-cover will be shorter
(Fang and Stefan 2000, 2009)
• Regional variability on effects on the
underwater environment:
• Dependent on water levels, eutrophication,
and winter snowfall (Danylchuk and Tonn
2003)

Winters may get snowier in the
north; rainier in the South

Critical Temp Thresholds
High turion production; rapid senescence
Turions start to form

Temperature Mediation of CLP
‣ Some northern lakes never get warm
enough to facilitate high turion production
and rapid senescence.
‣ CLP exists in northern lakes but rarely at
high levels and usually all-yr round.
‣ As climate change increases summer
temperatures, so too can conditions
conducive to abundant CLP growth

Summary
• Winter possibly plays some role in limiting curly-leaf
pondweed growth
• Results from 2011 neither refute nor confirm a
relationship. Follow up studies are needed.
• Future CLP status in the north may depend on
interplay of changes in snowfall and summer water
temperatures

Suggested Future Investigations
• A more comprehensive analysis of the response of
biota to curly-leaf proliferation.
• Controlled studies in well-defined sites (e.g.
mesocosm studies) could allow for improved
understanding of curly-leaf response to snow cover
• The correlation of curly-leaf cover to water quality
varies among lakes. The sentinel lakes may provide
a good opportunity to better quantify and model the
impact of curly-leaf senescence on lake water
quality – take advantage of our free data!!

Acknowledgments
• DNR Area Fisheries & Fisheries Research Unit
• Master Naturalist Program
• MPCA Water Monitoring Unit
• MN Climate Working Group
Funding – DNR Game and Fish Fund, Environment and
Natural Resource Trust Fund, Sportfish Restoration,
MPCA, Volunteers

EARLY-WINTER
INVERTEBRATE POPULATIONS
IN TROUT STREAMS
OF SOUTHEASTERN MN
Jane Louwsma Mazack, University of Minnesota

Acknowledgements
Will French
Jennifer Biederman
Pat Sherman
Lori Krider
Bruce Vondracek
Jim Perry
Len Ferrington
Petra Kranzfelder
Jessica Miller

Introduction
Groundwater-fed streams in southeastern Minnesota
are recreationally and economically valuable

Introduction
Trout streams in SE MN are thermally buffered by
groundwater input
Cooler summer temperatures
Warmer winter temperatures
Gribben Creek

Introduction
Cold-adapted (stenotherm) insects are often
abundant in these streams
Diamesa grow at stream temperatures from 2-10 o C
Stenotherm genera include:
Diamesa
Prodiamesa
Micropsectra
Brachycentrus
Adult Diamesa (Chironomidae)

A Conceptual Model
Climate ?
Geomorphology
Riparian zone
Land use
Thermal
buffering
capacity
Aquatic
Invertebrate
community
Trout growth
& abundance

Research Questions
1. What is the diversity, composition, and
heterogeneity of winter invertebrate communities
in groundwater-fed trout streams?
2. What is the relationship between stream thermal
regime and invertebrate community
characteristics?
3. What is the relationship between invertebrate
communities and winter trout diet and condition?

Sampling Sites
12 stream reaches in southeastern Minnesota

Sampling Methods
Early, mid, and late winter samples
Paired with brown trout diets
In each sample event:
5 Hess samples
10 minute dipnet sample
10 minutes pupal exuviae collection

Sample Analyses
Simpson’s Index with jack-knifing
Measure of population diversity (D)
Range from 0 < D < 1
• 0 represents no diversity
• 1 represents infinite diversity
Whittaker’s Percentage Similarity
Measure of within-reach heterogeneity
Range from 0 to 1
• 0 represents complete heterogeneity
• 1 represents complete homogeneity

Question 1
1. What is the diversity, composition, and
heterogeneity of winter invertebrate communities
in groundwater-fed trout streams?

Number of Genera Present
Community Characteristics
70
60
50
40
30
20
73.6
individuals/
meter 2
761
individuals/
meter 2
10
0
Sample Site

Diversity (Simpson's Index)
Community Characteristics
1
R² = 0.8012
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0 5 10 15 20 25 30 35
Number of Genera Present

Diversity (Simpson's Index)
Community Characteristics
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Sample Site

Diversity (Simpson's Index)
Community Characteristics
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Sample Site

Community Characteristics
North Branch
Trout Run
4% 2% EPT
4% 2%
11%
19%
23%
EPT
Stenotherms
30%
71%
Diptera
Other
8%
51%
94%
51%

Whittaker's Similarity
Community Characteristics
1.2
1
0.8
0.6
0.4
0.2
0
Sample Site

Question 2
1. What is the relationship between stream thermal
regime and invertebrate community
characteristics?
Adult Diamesa (Chironomidae)

Slope of water-air temperature regression
Stream Thermal Regime
0.6
0.5
0.4
0.3
0.2
y = -0.0004x + 0.5306
R² = 0.5924
0.1
0
0 100 200 300 400 500 600 700 800
Density (Individuals/m 2 )

Question 3
1. What is the relationship between invertebrate
communities and winter trout diet and condition?

Delta Wr
Trout Condition
Mean Delta Wr
15
10
5
A
AB
A
F=11.78
P

Delta Wr
Diversity (Simoson's Index)
Trout Condition
1
15
10
5
A
Mean Delta Wr
AB
A
F=11.78
P

Conclusion
1. Early-winter trout stream invertebrate communities
exhibit a wide range of diversity, heterogeneity,
and density.
2. Streams with lower temperature variability tend to
have larger early-winter invertebrate communities.
3. In preliminary analysis, the least diverse
invertebrate community reflected the highest rate
of overwinter brown trout growth.

Conclusion
Climate ?
Geomorphology
Riparian zone
Land use
Thermal
buffering
capacity
Aquatic
Invertebrate
community
Trout growth
& abundance