Fisheries Management
Iowa’s Lakes Programs
Joe Larscheid, Mike Hawkins, John Downing, Don Bonneau,
and George Antoniou
Assess, Classify, Prioritize
I
owa is considered by many as the
breadbasket of the world. The
landscape is dominated by agriculture
and currently about 89 percent of the
land is farmed. Nutrients and sediments
from these soils are directly transferred
to our waters, making Iowa lakes and
streams some of the most productive in
the world. In fact, most of our lakes are
classified as eutrophic, which means that
we are frequently plagued by nuisance
algal blooms or dense stands of aquatic
vegetation. Maintaining the quality
of surface water has many challenges
but properly managed landscapes can
result in good water quality and high
use lakes, including some tremendous
fishing opportunities. Our comprehensive
assessment and classification process has
allowed the Iowa Department of Natural
Resources (IDNR) the opportunity to
prioritize lakes and lake watersheds for
both protection and restoration. This
prioritization process and funding made
available through Iowa’s Lake Restoration
Program has proven a cost-effective
method for protecting and restoring water
quality and lake use. Our research and
success of several lake restoration projects
have proven biological health of our lakes
is closely associated with the quality
of water and, together, these factors
determine the value of the lake to public.
Species and Ecosystem
Management
Fisheries resources are managed
by county, state, and federal agencies to
enhance recreational opportunities for the
general public. Many of the traditional
approaches to fisheries management in
Iowa are largely species-specific and on a
very small, local scale. These approaches
24
Spring 2008 / LAKELINE
can be very successful, but they also tend
to be short-lived solutions and do not
address the larger problems impairing
fisheries in Iowa (e.g., poor water quality).
Recently, the state of Iowa began a very
aggressive program attacking water
quality issues statewide. The hope is
that improving water quality in our lakes
will translate to healthy, self‑sustaining,
aquatic ecosystems.
Although early approaches to
lake restoration in Iowa (1980s1990s)
emphasized dredging and elimination
of point sources, the current trend in
Iowa and much of North America is to
emphasize ecosystem management, an
approach that identifies and addresses
issues within both the lake and the
watershed. This approach can result in
much longer-term solutions than does
simple, in-lake management. Experience
has shown that good watershed
management is a necessary precursor to
good lake management. Our experience
has also shown that restored systems
support greater public use, including
both lake users and those that enjoy
associated park facilities. As a result of
our transition from traditional fisheries
management to ecosystem and watershed
management, we recognized the need to
consider a variety of information sources,
including fisheries, water quality, land
use, and habitat. Therefore, the IDNR
has coordinated work by several partners
in the construction of a diverse database
compiling multiple years of information
and is planning for the expansion of this
database into the future.
In addition to collecting data for
management purposes, we utilized the
information to prioritize our lakes for
restoration. The IDNR goal has been to
spend money on projects with multiple
benefits, such as improved water quality,
better fishing, and an increase in public
use. Prioritization allows us to allocate
money so that the benefits far out-weigh
costs, the results are observable and
measurable, and the projects are strongly
supported by the public.
Fishing Regulations and
Stocking Programs
Many of our current management
efforts in North America are spent on
regulations and stocking, and there are
some real success stories with these
efforts. However, these options are usually
short-term fixes to complicated fisheries
issues and do not address the underlying
problems such as degraded habitat and
poor water quality.
Currently, much of our management
efforts are centered on regulations
such as daily creel limits, length limits,
and closed seasons. We spend an
extraordinary amount of effort monitoring
the effects of these regulations, evaluating
alternatives, and enforcement. With
proper implementation, we may improve
fishing opportunities by fine-tuning
angler regulations. However, regulations
are mostly implemented for social and
not biological reasons. A regulatory
approach cannot improve fishing if the
real problem is degraded habitat or poor
water quality, which in Iowa lakes, and
perhaps elsewhere, are most often the
causes of poor fishing. In these cases, a
comprehensive approach that results in
measurable and observable improvements
is needed.
State Lakes Classification Project
Watershed and lake renovation
projects are the key to improving
fishing opportunities for our anglers. By
improving the ecosystem, we can provide
society with high-quality resources
and self-sustaining populations of fish.
These projects are very popular, and
many local communities want their lakes
improved. A system was needed to help
prioritize restoration activities and provide
a roadmap for our citizenry on our
restoration activities.
A very aggressive lake classification
project was started in Iowa beginning in
the spring of 2000 and was completed
in 2005. The goals of this project were
to improve and streamline access to
past and current Iowa lake water quality
data, to create a Web site that serves as
an information and educational resource
for Iowa’s citizens, and to develop a
lake classification system that facilitates
management and restoration decisions.
The roadmap toward this goal was
designed by a committee of scientists
and agency employees from across the
state. The committee met frequently for
a year, uniting academic and government
scientists in the common goal of
assessing, classifying, and improving
water quality in the state.
Detailed data were collected and
compiled from 132 of Iowa’s principal
lakes and impoundments. All of these
data were included into a comprehensive
database that is available to any interested
stakeholders via the World Wide Web
(http://limnology.eeob.iastate.edu/
lakereport/). This system is very useful for
developing lake classifications, describing
historical trends, providing very detailed
information on individual lakes, and
comparing our lakes across the state.
Additionally, this system will combine
all linked water quality data, fisheries
information, management experiences,
maps, land use, and other data into up-todate mini-reports that provide citizens and
managers with interpretive synopses of
any lake in the information system.
An EPA-sponsored collaborative
program between IDNR, several agencies,
and Iowa State University took a first step
toward uniting diverse data on physical,
chemical, and biological water quality,
public valuation, and potential restoration
potential toward an initial classification
tool. Additional collaboration between
IDNR and the university simplified
this approach. For the purposes of
classification, a water quality score was
determined for each lake. These scores
varied from zero (poor water quality) to
one (high water quality). These scores
were determined using statistical analysis
and a predefined set of good (highquality) and poor (low-quality) lakes. The
model produced a classification function
that separated good and poor lakes using
the following water quality variables:
clarity (Secchi depth), nutrients (total
phosphorus, total nitrogen, and nitrogen
to phosphorus ratio), and total suspended
solids. This combination of water quality
variables separated the predefined set of
good and poor lakes very well. In fact,
most of the variation in what separates the
good from the poor lakes was accounted
for by this classification function.
Next, we asked our local managers
to review the classification list. The
manager’s opinion of average lake
condition agreed with the model output.
Lakes with low water quality scores were
lakes that were perpetually in a turbid
water state, with low water quality and
high variability, and, the lakes with high
water quality scores were lakes with
high water quality and low variability.
The classification model made sense
to our managers, which gave us added
confidence that the model will be useful
for classification.
To continue toward the goal of lake
classification, we developed a watershed
score for each lake. This score varied from
zero (almost no potential soil loss from
the watershed) to over 4,000 (massive
potential soil loss from the watershed).
The watershed score was derived by
combining the Revised Universal Soil
Loss Equation (RUSLE) value with the
lake and watershed areas in the following
way:
For instance, lakes with good
watersheds and good water quality scores
(top right) do not require any renovations.
They are already high-quality systems.
However, these high-quality systems
need some protection to keep their status.
Lakes with poor water quality but good
watersheds (bottom right) may benefit
from in-lake renovations to improve water
quality. Lakes with poor water quality
and poor watersheds need significant
work in the watershed before any in-lake
improvements are made. Lakes with good
water quality and poor watersheds need
watershed improvements to maintain good
water quality.
There is a strong, non-linear
relationship between watershed and water
quality scores (Figure 2). This relationship
was best described by the twodimensional Kolmogorov–Smirnov test
(2D KS). This non-parametric model tests
for non-random patterns in bivariate plots
controlled by thresholds, or breakpoints
in the data. In this case, the threshold
identified was a watershed score of 262
(fair rating) and a water quality score of
0.3 (fair rating). These thresholds may
be interpreted as critical points where the
relationship between water quality and the
watershed changes. For instance, a lake
with a watershed score of 262 or higher
is likely to have lower water quality. On
the other hand, lakes with a watershed
score less than 262 have the range of
possibilities from very good to very poor
water quality scores. This relationship
is significant and allows us to determine
how much we need to improve watersheds
to increase the chance of improving water
quality.
Watershed Coefficient = (RUSLE value
* watershed area) / lake area
Lakes Program
Our lake database and classification
project are continually improving and
changing as new data are added and
updated. However, existing data have
allowed us to classify and prioritize 132
our principal lakes for restoration and
garner money to fund our restoration
activities. The final step in lake
classification was to combine the water
quality and watershed scores with other
factors such as socio-economic variables,
public participation, and feasibility. Then
rate each lake as “high”, “medium”, or
“low” priority for restoration (Figure 3).
Much environmental restoration is
justified by the great value society places
The RUSLE model predicts potential
soil loss from the watershed based on
the following variables: soil erodibility,
land-use, rainfall, slope, length of slope,
and current practice. Combining RUSLE
values with watershed to lake area ratio
provides a general index of watershed
health. On average, the typical lake in
Iowa had a fair watershed index. For
classification purposes, we plotted the
watershed scores against the water quality
scores (Figure 1).
Spring 2008 / LAKELINE
25
Figure 1. Summary of how lakes were grouped for management purposes.
Figure 2. Plot of watershed coefficient versus water quality coefficient.
on good water quality. In spite of this,
there are few tests of the linkage between
limnological measures of water quality
and the value of water to society. The
principal impediment to this knowledge
is that such analyses fall within the field
of non-market valuation. Using revealed
26
Spring 2008 / LAKELINE
preference techniques, we estimated
the value of Iowa lake water quality to
Iowa citizens and found a very strong
relationship between the value people
place on water quality and how often they
visit and enjoy those lakes for recreational
usage. Specifically, those lakes with better
water quality, irrespective of size and
origin, had more value than low water
quality lakes and the study estimates that
Iowa citizens would be willing to pay for
significant improvements in water clarity
rather than do without it. These analyses
employed a unique and rich data set of
water quality attributes in conjunction
with detailed household characteristics
and trip information to develop a model
of recreational lake usage across the
entire state, including data on 132 major
lakes. Estimates of the public’s value of
lake water quality improvements result
in many cases to very high benefit to cost
ratios for lake restoration projects.
Additionally, the local economic
impact of Iowa’s 132 most important
lakes indicated that rates of lake use
were extremely high. Although the
population of Iowa is only about 3
million, Iowans make over 11 million
visits to lakes annually, with >16 percent
of these (1.8 million) being overnight or
multi-day visits. This lake use generates
$977 million in annual local spending.
In addition, associated with lakes and
water courses, Iowa has 85 state parks,
which receive 14.1 million visits per
year including >700,000 campers, all
generating another $748 million in
spending per year. County parks, also
associated with water bodies, receive
almost 24 million visitors per year,
generating $597 million in expenditures.
Lakes alone generate in excess of $1.6
billion of spending annually in Iowa,
creating $243 million in labor income,
adding $425 million to the GDP, and
creating nearly 12,000 jobs. Use,
visitation, spending, and job creation all
increase with improved water quality,
rendering water quality improvement an
essential and powerful economic engine.
The IDNR initially provided
the legislature with a list of 35 lake
restoration candidates. These projects
require a lake and watershed restoration
assessment and plan, and local resources
in combination with state and federal
funds. In addition, projects have the
following water quality goals:
• Phosphorus and sediment coming from
the watershed must be controlled before
lake restoration begins.
• Shallow lakes management will
be considered among options for
restoration.
Water Quality
Watershed Hydrology
Ranking of Iowa’s Lakes for Restoration
+
Socio-economic Value
Lake Restoration Potential/Feasibility
Lake Prioritization for Restoration
Figure 3. Overview of lake classification and
prioritization for restoration.
• 4 ½ foot Secchi disk transparency
(water clarity) 50 percent of the time,
April-September.
• Water quality impairments must be
eliminated.
In 2006, the Iowa legislature
responded with the Lake Restoration
Program (HF 2782) and appropriated
$8.6 million for the first year. In 2007,
the IDNR was able to continue work
on improving Iowa’s lakes because of
the status quo funding from HF 911
through the Restore Iowa Infrastructure
Fund (RIIF), which appropriated $8.4
million toward lake restoration. This is
the largest legislative appropriation for
lake restoration in Iowa history. With
continued research, prioritization, and
lake restoration successes, we feel this
is the start of an aggressive, well-funded
plan to restore impaired waters in Iowa.
Success Story
Recent experiences from Lake
Ahquabi and Lake of Three Fires show
that significant improvement in water
quality can be expected following lake
restoration. At Lake Ahquabi, water
clarity improved from 20 inches to more
than four feet. Visits to the state park
and fishing trips to the lake increased
three-fold following lake restoration.
Based on the average economic value of
visits to the lake and park, the $4 million
restoration cost was estimated to be
returned within two years. Restoration
efforts at Lake Ahquabi first focused on
watershed management activities. It is
estimated that 95 percent of watershed
land is now farmed under Natural
Resource Conservation Service (NRCS)
approved soil conservation practices. In
addition, two existing sediment basins
were renovated and five new wetlands
were developed above the lake. Following
watershed efforts 422,339 cubic yards
of sediment were removed from the
system. The fishery was renovated and
spillway modifications were put in
place to eliminate the re-introduction of
undesirable species.
In Lake of Three Fires, summer
water clarity (above) improved from an
average of 2 feet (2000-2004) to 5½ feet
(2005-2006) following the completion of
substantial watershed improvement and
lake restoration work. Approximately
500,000 cubic yards of sediment were
dredged from the lake in 2004. The lake
was drained and the existing fishery
dominated by common carp and gizzard
shad was eliminated in fall 2004. The
lake was refilled and fish were restocked
in spring 2005. Water clarity is much
improved compared with pre-restoration
years and game fish (bluegill, largemouth
bass) growth is reportedly outstanding.
A recently constructed wetland directly
above the lake will further protect
water quality and provide additional
environmental benefits.
Future Directions
Fisheries and Lake Water Quality
Relationships. Fisheries researchers at
Iowa State University are conducting
a study on the link between lake water
quality and fisheries quality. The purpose
of the study is to describe fish population
and assemblage structure among lakes,
and determine relationships among
fish, limnological conditions, lake basin
morphology, and watershed characteristics
in Iowa lakes. This information is
necessary to understand relations between
fish assemblage characteristics and water
quality, a relationship important to the
protection and improvement of Iowa’s
lake resources.
Aquatic Vegetation BMPs. We are halfway
through the IDNR’s cooperative study
with Iowa State University to develop
both short- and long-term strategies
needed to address the impact of aquatic
plants on fish, fishing, and other lake
uses. The goal of this study is to develop
lake-by-lake management plans that
strike a balance among clear water, plant
growth, and lake use. Although aquatic
plants are an essential component of
lake ecosystems, the combination of
clear and nutrient-rich water can result
in excessive growths of vegetation,
especially in near shore shallow water.
These same, near shore areas are also
the portions of our lakes most used by
the public. Information gained in this
study will result in a detailed knowledge
of the relationships between water
quality, lake basin characteristics, fish,
and plants. This information will greatly
benefit assessment of aquatic plant
communities and methods used to control
nuisance growths. The result will be
implementation of those practices most
suited to management of plants in Iowa’s
valuable and heavily used lakes.
Biological Integrity. Beginning in 2006
the Limnology Laboratory, under the
Department of Ecology, Evolution
and Organismal Biology at Iowa
State University, expanded biological
monitoring to collect bottom-dwelling
invertebrates that represent an important
link in the food web of lake ecosystems.
They will use these data to develop a lake
biological quality index based on species
diversity and abundances. The index
will complement existing water quality
indicators of lake health and provide
another tool to measure progress toward
lake restoration goals.
In addition, ISU will incorporate this
information into the recently approved
five-year project entitled “Benchmarks
of biological integrity for lake restoration
success: fish, invertebrate, and plankton
communities in Iowa lakes”. The purpose
of this project is to provide the IDNR
with an evaluation of protocols for
assessing the biological integrity of fish
and macroinvetebrates in Iowa lakes,
to develop standard sampling protocols
for these organisms, to execute this
sampling design on lakes identified as
priorities for restoration and protection,
and to assemble and calibrate biological
condition metrics and indices to use in
developing benchmarks for restoration
success.
Conclusion
We have many challenges facing
Iowa’s lakes. However, when lakes and
their watersheds are properly managed we
Spring 2008 / LAKELINE
27
Lake of Three Fires – Taylor County
Avg. Summer Water Clarity (Secchi Depth Feet)
0
2000
2001
2002
2003
2004
2005
2006*
2
4
6
Lake Restoration Goal (4.5’)
Lake Restoration
Substantially Complete
Spring 2005
8
*2006 data source University of Iowa Hygienic Laboratory,
data all other years from Iowa State University Limnology
10
Secchi disk at same depth (8”) Before (2004) and After (2005)
Figure 4. Lake of Three Fires water clarity.
can overcome these challenges and benefit
both water quality and recreational use.
The classification process has allowed us
to prioritize our restoration efforts and to
establish a well-funded and cost-effective
statewide effort to improve our lakes.
In addition, the IDNR maintains and
regularly updates a very comprehensive
database that allows on-the-fly up-dates
to our assessments of lakes and lake
watersheds, including their classification
and prioritization for protection and
restoration. Current research is directed
at improving the biological component
of our lakes database. This information
will add the much-needed biological
dimension to the assessment of our
success in our lake protection and
improvement work.
Joe G. Larscheid
Figure 5. Fisheries populations may provide an important link between ecological health and
water quality.
28
Spring 2008 / LAKELINE
is currently a fisheries
research biologist with
the Iowa Department
of Natural Resources
located at the NW
regional headquarters
in Spirit Lake, Iowa. He
is primarily responsible
for the research program conducted on
Iowa’s natural lakes, but is also involved
Figure 6. Healthy aquatic vegetation is key to the health of our lakes.
with many other projects, including a very
comprehensive inventory of Iowa’s principal
lakes and impoundments. Joe’s primary goals
as a fishery scientist are to provide the tools
and insights managers and administrators
need to make sound resource decisions. You
may reach Joe at: joe.larscheid@dnr.iowa.
gov.
Mike Hawkins is
currently a fisheries
management biologist
with the Iowa
Department of Natural
Resources at the NW
Regional Headquarters
in Spirit Lake, Iowa.
Before taking this job he
was a fisheries research biologist with Iowa’s
Natural Lakes Research Team. Mike works
with partners and communities to manage
fisheries, water quality, and watersheds as a
whole to provide the best chance for success.
You may reach Mike at: michael.hawkins@
dnr.iowa.gov.
Dr. John A.
Downing is currently a
professor at Iowa State
University as a member
of the Departments of
Ecology, Evolution and
Organismal Biology and
Agricultural Engineering.
His research interests
span the range from aquatic to terrestrial
ecology; from microbial ecology to
biogeochemistry; and from population
conservation to whole ecosystem restoration
and management. Principal projects include
global comparative limnology and working
with communities to improve water quality.
You may reach John at downing@iastate.edu.
Don Bonneau is
currently a Supervisor of
Fisheries Research with
the Iowa Department of
Natural Resources, Des
Moines, Iowa. He has
also served as Iowa’s
coordinator of EPA’s
Clean Lakes Program. Don’s interests include
research on issues impacting fish and fishing
in an agricultural landscape. Don serves on
the Association of Fish and Wildlife Agencies
Agriculture Conservation Committee, and
assisted in development of the National Fish
Habitat Action Plan. You may reach Don at
don.bonneau@dnr.iowa.gov.
George Antoniou
is currently a Program
Planner with the Iowa
Department of Natural
Resources, Des Moines,
Iowa. He is responsible
for the administration
of the statewide Lake
Restoration Program
including identification of priority projects
and working with local, state and federal
agency to implement projects and ensure
completion of restoration activities. You may
reach George at george.antoniou@dnr.iowa.
gov. x
Spring 2008 / LAKELINE
29