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North American Journal of Fisheries Management
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Brook Trout Distribution, Genetics, and Population
Characteristics in the Driftless Area of Minnesota
R. John H. Hoxmeiera, Douglas J. Dietermana & Loren M. Millerb
a Minnesota Department of Natural Resources, 1801 South Oak Street, Lake City, Minnesota
55041, USA
b Minnesota Department of Natural Resources, 200 Hodson Hall, University of Minnesota,
1980 Folwell Avenue, St. Paul, Minnesota 55108, USA
Published online: 01 Jul 2015.
To cite this article: R. John H. Hoxmeier, Douglas J. Dieterman & Loren M. Miller (2015) Brook Trout Distribution, Genetics,
and Population Characteristics in the Driftless Area of Minnesota, North American Journal of Fisheries Management, 35:4,
632-648, DOI: 10.1080/02755947.2015.1032451
To link to this article: http://dx.doi.org/10.1080/02755947.2015.1032451
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ARTICLE
Brook Trout Distribution, Genetics, and Population
Characteristics in the Driftless Area of Minnesota
R. John H. Hoxmeier* and Douglas J. Dieterman
Minnesota Department of Natural Resources, 1801 South Oak Street, Lake City, Minnesota 55041, USA
Loren M. Miller
Minnesota Department of Natural Resources, 200 Hodson Hall, University of Minnesota,
1980 Folwell Avenue, St. Paul, Minnesota 55108, USA
Abstract
The Driftless Area in southeastern Minnesota is on the southwestern edge of the native range of Brook Trout
Salvelinus fontinalis. It was assumed that native Brook Trout were extirpated from this region in the early 1900s
due to degraded stream conditions and stockings of eastern-origin Brook Trout and European Brown Trout Salmo
trutta. Our objectives were to examine Brook Trout populations in the region to determine their spatial and genetic
distribution and quantify population characteristics. Information on presence or absence of Brook Trout was
gathered by electrofishing 174 streams in southeastern Minnesota. Brook Trout were present in 68% of coldwater
streams compared with only in 3% in the early 1970s. The increase is likely due to increasing stream discharge
throughout the Driftless Area, enabling recolonization or successful establishment of stocked populations. Streams
with higher base flow discharge also had higher abundance, larger size at maturity, and larger Brook Trout
present. Genetic data on 74 populations were analyzed to characterize genetic variation within populations, assess
genetic structure among populations, and determine possible origins. Numerous populations were not associated
with known hatchery sources but were primarily composed of geographic groupings that could represent remnant
lineages. Although population characteristics were similar among genetic origins, potentially remnant populations
should be given conservation priority because they have proven their ability to sustain themselves in this region.
Management actions that emphasize maintaining or increasing stream base flows throughout the region will likely
enhance remnant Brook Trout populations in the Driftless Area.
Populations found at the edge of a species range are impor-
tant in terms of range contraction, genetic divergence, and life
history variants. While edge populations are more susceptible
to declines than their centrally located counterparts, the risk
becomes even greater with intolerant coldwater species such
as trout (family Salmonidae) (Haak et al. 2010). A relatively
tolerant, nonnative trout species may be more likely to succeed
along the periphery of an intolerant trout species’ native range
given that the environmental conditions are often suboptimal
for the native trout species. Also, coldwater fish such as Brook
Trout Salvelinus fontinalis are predicted to decline along the
edge of their southern range due to a warming climate
(Meisner 1990; Flebbe et al. 2006; Lyons et al. 2010). Con-
versely, an increase in stream base flows resulting from
increased precipitation could have a positive impact on both
water quality and instream habitat for stream fishes (Hakala
and Hartman 2004; Novotny and Stefan 2007). Because Min-
nesota represents the southwestern edge of the native range of
Brook Trout, conservation measures are of added importance.
Managers would benefit from a detailed distributional analysis
of these populations given that they may differ from those of
more central populations and may be more likely to show
adverse effects from stressors such as climate change and
invasive species. However, habitat characteristics do not
*Corresponding author: john.hoxmeier@state.mn.us
Received July 25, 2014; accepted March 17, 2015
632
North American Journal of Fisheries Management 35:632–648, 2015
ÓAmerican Fisheries Society 2015
ISSN: 0275-5947 print / 1548-8675 online
DOI: 10.1080/02755947.2015.1032451
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necessarily follow a strict latitudinal or linear gradient. The
Driftless Area of southeastern Minnesota, due to its distinct
geology, may provide quality habitat that makes its Brook
Trout populations more resistant to stressors than would be
expected for peripheral populations.
While coarse-level modeling exercises can lend insight into
species spread and declines, they need to be relevant on both a
temporal and spatial scale to effectively measure the impacts
of disturbance (Dauwalter et al. 2009). On a spatial scale, the
knowledge of a species presence in a watershed does little to
help define the factors influencing the species distribution in
an individual stream. Range contraction of trout due to climate
change has focused on entire watersheds or latitudes, as
opposed to individual streams. Because individual streams dif-
fer in water temperature (based on groundwater inputs, shad-
ing, orientation, etc.), base flow, instream habitat, and other
physical and biological conditions, it is unlikely that all
streams in a watershed or latitude will respond in the same
way to large stressors. Similar to downscaling global climate
models, efforts are needed to gather distributional data of
fishes at a finer scale that is useful to both scientists and fisher-
ies managers. In addition to land use and environmental condi-
tions, competition from invasive species can also alter native
species distribution (Wagner et al. 2013). Brook Trout popula-
tions are negatively affected throughout their native range by
the introduction of both Brown Trout Salmo trutta and Rain-
bow Trout Oncorhynchus mykiss (Larson and Moore 1985;
Fausch 2008). Information on the distribution of trout is
needed on a finer scale to better understand the factors influ-
encing their spread or decline.
The knowledge of genetic origin and diversity is another
critical need in identifying the status of a population. Because
of the ubiquitous movement of trout by state and governmental
agencies during the last century, attempts must first be made to
determine genetic origin. Remnant populations of Brook Trout
in the Driftless Area would deserve the highest conservation
priority because of their locally adapted genetic characteris-
tics. Populations that have successfully naturalized and per-
sisted in the region also deserve conservation consideration
because of the potential for rapid evolution in salmonids
(Hendry et al. 2000; Pearse et al. 2009). Low genetic diversity
may result from founder effects associated with colonization,
isolation, and small population size, especially where compet-
ing in reaches with Brown Trout (Whiteley et al. 2013). Low
genetic diversity within populations may limit a population’s
ability to adapt to changes. Information on genetic origin and
diversity will help to prioritize conservation efforts in the
Driftless Area.
Before fishes disappear from a region or stream, early indi-
cations of stress can be found in population parameters such as
mortality, growth, and maturity. However, little information
exists in the published literature on genetics or other popula-
tion characteristics of Brook Trout in the Driftless Area or on
how these populations may differ from those found in the
central part of their range. Stressed trout populations may
show signs of slow growth, decreased survival, and few age-
classes (Marschall and Crowder 1996). Defining the popula-
tion characteristics of Brook Trout in the Driftless Area is
needed to develop conservation management strategies and
establish baseline information.
Our objectives were to examine Brook Trout populations in
the Driftless Area of southeastern Minnesota to (1) determine
the current spatial distribution of Brook Trout populations,
(2) determine genetic diversity and structure and identify
potential remnant lineages, and (3) quantify population char-
acteristics (abundance, growth, size structure, annual mortal-
ity, and length at maturity) to compare with other populations
in their native range.
METHODS
Study area and stocking history.—In addition to being on
the southwestern edge of the native Brook Trout range, south-
eastern Minnesota has a unique landscape of karst geology
combined with agricultural land use. The Driftless Area of
southeastern Minnesota consists of steep valleys dominated by
hardwood forests, with a mix of agriculture and forests on the
flatter uplands and valley bottoms. Agricultural practices
mainly include row crops and pasture. Coldwater streams in
this region are supported by groundwater inputs, often near the
headwaters. Many streams warm as they reach downstream
lower-gradient portions of the valleys and are further away
from groundwater inputs. The western portion of the study
area receives most of its groundwater from the Galena and
Decorah Edge rock formations and the eastern half receives
most of its groundwater from the St. Lawrence Edge and Prai-
rie Du Chien. Groundwater from the latter two formations typ-
ically originates from deep, confined aquifers, and therefore
water temperatures are very stable with minimal annual varia-
tion (Luhmann et al. 2011). Most coldwater streams in this
region are very fertile with high alkalinity (Kwak and Waters
1997). Brook Trout are the only native stream-dwelling salmo-
nid in the Driftless Area (MacCrimmon and Campbell 1969).
During the mid-1800s, logging and intense agriculture
degraded many trout streams in southern Minnesota, causing a
precipitous decline in Brook Trout populations throughout the
region (MacCrimmon and Campbell 1969; Thorn et al. 1997).
By the late 1800s, most native Brook Trout populations in
southern Minnesota were presumed extirpated and introduc-
tions of eastern-strain Brook Trout, Brown Trout, and Rain-
bow Trout were used to provide fishable populations (Thorn
et al. 1997). Brook Trout stocking began in Minnesota in the
late 1800s by public and private hatcheries. The source of
these Brook Trout is unknown but likely came from local
stocks. Starting in the 1980s, the origins of Brook Trout were
recorded when they were brought into state hatcheries. Many
of the Brook Trout brought into Minnesota hatcheries were
from domesticated stocks originating in the eastern United
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 633
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States. Two strains were widely stocked during this time in
southeastern Minnesota. The St. Croix Falls strain, obtained
from the St. Croix Falls hatchery in Wisconsin but originally
from Nashua fish hatchery, New Hampshire, was stocked from
1983 to 1997. The Owhi strain, obtained from the White Sulfer
Springs hatchery, West Virginia, was stocked from 1986 to
1992. Other strains were used for short periods. In 1982 and
1983, fish from Rome, New York, and North Attleboro, Mas-
sachusetts, were raised and stocked from Minnesota hatcher-
ies, as were fish from Phillips hatchery in Maine in the mid to
late 1980s. The strain used in current reintroductions and sup-
plemental stocking is referred to as Minnesota Wild
(MNWILD) and has been stocked since 1995. This strain was
developed by crossing Brook Trout from Spring Brook in Rice
County, Minnesota, and those from Coolridge Creek in
Winona County, Minnesota. Given the numerous strains that
have been stocked, it is difficult to know the ancestry of Brook
Trout in Minnesota streams. Often times multiple strains were
stocked into the same stream. Also, connectivity among cold-
water streams allows Brook Trout to move among streams.
Some streams in southeastern Minnesota that have no records
of being stocked have reproducing Brook Trout populations,
which could represent remnant populations or could have
resulted from unknown stocking (either public or private) or
been established through immigration from stocked or rem-
nant populations. Brown Trout are naturally reproducing in
most of the area’s coldwater streams; however, some supple-
mental stocking of fingerling Brown Trout continues. Rainbow
Trout are stocked as fingerlings and yearlings in areas with
high fishing pressure but are not known to naturally reproduce.
Spatial distribution.—Coldwater streams in southeastern
Minnesota were sampled from 2005 through 2010 by electro-
fishing. We assessed 174 streams located in nine major water-
sheds (U.S. Geological Survey subbasins; level 4) for the
presence of Brook Trout (Figure 1). There are 181 coldwater
streams in southeastern Minnesota that could potentially sup-
port trout, not including the larger warmwater rivers. We did
not sample the remaining seven streams due to access issues.
Sampling locations were based on whether Brook Trout were
reported at a location previously or on landowner and angler
accounts of Brook Trout being present, if such information
was available. In the absence of such information, we sampled
headwater reaches and areas of known spring sources. Warm-
water streams were only sampled if there were previous
reports of Brook Trout in a particular stream. Although Brook
Trout are occasionally collected in larger warmwater rivers,
we considered these individuals as transients and not year-
round residents of these larger systems.
Brook Trout were sampled with either a backpack or barge
electrofisher, depending on stream size. Typically, a single
pass was made upstream collecting all Brook Trout observed,
while counting the numbers of adult and age-0 Brown Trout.
Station length was a minimum of 35 times the mean stream
width or until at least 25 Brook Trout were collected for
genetic analysis. Some streams were sampled at multiple loca-
tions if Brook Trout were not found at the initial sampling site
or in order to increase sample sizes for genetic analysis. At the
beginning and end of each station, GPS locations were taken
to determine length. Brook Trout were measured for total
length and an adipose fin was collected for genetic analysis.
Brook Trout populations were classified based on numbers of
fish per kilometer collected on a single pass as none (0/km),
rare (<30/km), common (between 30 and 155/km) or abun-
dant (>155/km).
Genetics.—We examined genetic diversity in most south-
eastern Minnesota Brook Trout populations to characterize
genetic variation within populations, assess genetic structure
among populations, and determine if lineages of the original
Brook Trout in the Driftless Area may remain in the region.
Tissue samples were collected during electrofishing surveys
as described above. Populations not included in the genetic
study typically had very low abundance or were currently
being stocked with the MNWILD hatchery strain. In addi-
tion, we obtained data for six Brook Trout hatchery brood-
stocks derived from eastern U.S. sources (W. Stott, U.S.
Geological Survey Great Lakes Science Center, unpublished
data). These included samples from hatcheries in Maine
(Phillips hatchery; PHP), New York (Rome hatchery;
ROME), Michigan (Marquette hatchery; MARQ), Utah
(Egan hatchery’s Owhi strain; OWHI), Wisconsin (Bayfield
hatchery’s Nashua strain; NASH), and Minnesota (derived
from Wisconsin’s Nashua strain; SCF). Data for one Iowa
DriftlessArea(IOWA)populationpresumedtoberemnant
to that area was also obtained (T. King, U.S. Geological
Survey, unpublished data).
Samples were prepared for polymerase chain reaction
(PCR) amplification using a simple DNA extraction based on
Walsh et al. (1991). A small piece of fin tissue was placed in a
1.5-mL tube with 250 mL of a 5% solution of a chelating resin
(Chelex; Sigma Chemical, St. Louis, Missouri). Samples were
incubated overnight in a 56C water bath and boiled 8 min.
Microsatellite amplification was performed in 15-mL reactions
containing 1X polymerase buffer (10 mM tris-HCl, 50 mM
KCl, 0.1% Triton X-100), 1.5 mM MgCl2, 0.2 mM each
dNTP, 0.5 mM of the forward and reverse primers, with the
forward primer labeled with a fluorescent dye (6FAM, VIC,
NED, or PET), and 0.5 units Taq DNA polymerase (Promega,
Madison, Wisconsin). We used seven microsatellite DNA loci
designed for Brook Trout: SfoC24, SfoC38, SfoC86, SfoC88,
SfoC113, SfoD115, and SfoD75 (King et al. 2012). Each set of
samples included a water blank as a negative control to detect
possible contamination of PCR solutions. Amplification was
carried out in a thermocycler with 35 cycles at 95C for 30 s,
50C for 30 s, and 72C for 1 min, followed by a 20-min
extension at 72C. We submitted PCR products to the Biomed-
ical Genomics Center (University of Minnesota, St. Paul, Min-
nesota) for electrophoresis on an ABI Prism 3130xl Genetic
Analyzer (Applied Biosystems, Foster City, California).
634 HOXMEIER ET AL.
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Alleles were scored using the software program Genotyper 2.1
and later Genemapper 4.1 (Applied Biosystems).
We estimated measures of genetic diversity, allelic rich-
ness, and expected and observed heterozygosities and evalu-
ated genetic equilibrium within each population. The data
were tested for deviations from Hardy–Weinberg expectations
and linkage equilibrium using exact tests in the software
GENEPOP version 4 (Raymond and Rousset 1995). Allelic
richness, the number of alleles in a sample standardized to a
common sample size, was estimated using HP-RARE
(Kalinowski 2005). The Garza–Williamson index (M; the ratio
of the number of alleles to the range in allele size), estimated
for each population in ARLEQUIN 3.5.1.2 (Excoffier and
Lischer 2010), was used as a further indicator of possible pop-
ulation bottlenecks. Garza and Williamson (2001) showed
that, under a stepwise mutational model for microsatellites,
populations with an M<0.68 can be assumed to have experi-
enced a reduction in population size.
The measure of population differentiation F
ST
was esti-
mated for all population pairs in ARLEQUIN and tested for
significant deviation from 0 (i.e., no genetic differentiation)
using 16,000 permutations. To assess population relationships,
we calculated Cavalli-Sforza and Edwards’ (1967) chord dis-
tances between each pair of populations and constructed a
neighbor-joining tree, with 1,000 bootstrap replicates, using
the program POPULATIONS 1.2.30 (Langella 1999). The tree
was visualized using TREEVIEW 1.6.6 (Page 1996).
The program STRUCTURE 2.3.3 (Pritchard et al. 2000)
was used in a stepwise fashion to further examine the genetic
relationships among populations (Coulon et al. 2008). The
program STRUCTURE determines the number of distinct
genetic clusters (K) and assigns ancestry of each individual to
these clusters. It is useful because it can identify possible
admixture between distinct populations, which was possible
because multiple hatchery strains were stocked, populations
were translocated between drainages, and relatively few
FIGURE 1. Distribution and genetic strains of Brook Trout in southeastern Minnesota delineated by major watersheds. Brook Trout populations were catego-
rized based on genetic analysis as remnant (unique to Minnesota), MNWILD (the current strain used in Minnesota hatcheries), and eastern USA (populations
associated with hatchery strains originating in the eastern USA). Absent indicates catchments where Brook Trout were not found.
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 635
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barriers to movement exist within some watersheds. Five repli-
cations were run for each value of KD1 through 12 using a
burn-in of 20,000 iterations followed by a run of 100,000 itera-
tions. Each simulation was performed using models with
admixture and correlated allele frequencies but without prior
population information. The best value of Kwas chosen
according to an ad hoc statistic described by Evanno et al.
(2005), and populations were assigned to a cluster if their aver-
age probability exceeded 0.50 (with a few exceptions noted in
the results). The Evanno method often identifies high-level
structure (i.e., low K) when hierarchical structure exists
(Evanno et al. 2005); thus, we repeated STRUCTURE analy-
ses within the clusters to identify further substructure.
Population characteristics.—To gain a better understanding
of population characteristics, we intensively examined six
streams (East Indian Creek, Maple Creek, Coolridge Creek,
Trout Valley Creek, Trout Brook, and Garvin Brook) over a 2-
year period in both spring and fall. To encompass potential vari-
ation, we chose Brook Trout populations from different water-
sheds, stream sizes, and genetic origins. Populations were
categorized as hatchery associated or potential remnants based
on whether or not they clustered with known hatchery samples
in the genetic analysis. We assessed genetic origin because
both the source of a broodstock and its history of captive rearing
may affect the characteristics of the population in the wild.
Brook and Brown trout population estimates were made
from two-pass depletion techniques (Zippin 1956) using a
backpack electrofisher in Coolridge Creek, Garvin Brook, and
Trout Brook, whereas a barge electrofisher was used in Maple
Creek, Trout Valley Creek, and East Indian Creek. The lengths
of the sampling stations depended on mean stream width and
ranged between 165 and 311 m. Sampling stations started and
ended at shallow riffles to avoid trout leaving the area while
sampling was conducted. Density estimates were averaged
across the four time periods to account for temporal variabil-
ity. Both Brook Trout and Brown Trout were measured (near-
est mm) and weighed (nearest g). We removed otoliths from a
subsample of Brook Trout (minimum of 40 per stream) for age
determination. Otoliths were read in whole view under a dis-
secting microscope with reflected light on a black background.
Mean length at age was estimated using mixed distribution
models developed from length frequency histograms from fall
collections (both years combined) seeded with “known-age”
fish. Known-age fish were those marked at age 0 and recap-
tured as age 1 and a subsample of fish aged with otoliths.
Length frequency histograms were divided into 10-mm
length-groups. We used the mixdist package (Macdonald and
Du 2010) in the software program R (R Development Core
Team 2009) to fit finite mixture distribution models to the
length frequency histograms. Mixdist provides estimates for
mixing proportions (p
a
), mean lengths at age (m
a
), and stan-
dard deviations of length-at-age distributions (s
a
). Mixing
proportions are described as the relative abundance of that
age-group as a proportion of the entire measured sample. We
tested several different constraints and probability distribu-
tions and compared model results using minimum x
2
-values.
The best models were used for mean length-at-age estimates.
Annual mortality was derived from instantaneous mortality
rates from the descending limb of the catch curve. Catch
curves were generated by using mixing proportions (p
a
) from
the mixed distribution models described above. Fall sampling
data were combined for both years to help alleviate the effects
of variable recruitment.
A subsample of trout was sacrificed during fall sampling for
internal examination of gonads to assess maturity. The num-
bers of fish examined for maturity ranged from 79 (Garvin
Brook) to 161 (Trout Valley). Maturation was determined by
visual examination of gonads and scored as 0 for immature
and 1 for mature. For each population, we then used logistic
regression with length as our independent variable to calculate
size at maturation for males and females (R Development
Core Team 2009). Equations derived from the logistic regres-
sion model were used to determine the length at which 50%
were mature. We combined data across years to increase sam-
ple size and encompass annual variability.
We tested for differences in mortality, length at maturity,
length at age (age 0–3), and adult density between genetic ori-
gins (remnant versus eastern) using a t-test with streams as
replicates. Because stream size can influence population char-
acteristics, we correlated summer base flow discharge and
population metrics using Pearson’s correlation coefficient. All
tests were set at an alpha level of 0.05.
We measured discharge (m
3
/s) near the downstream bound-
ary of each reach during summer base flow conditions. Veloc-
ity was measured with a Marsh-McBirney Model 2000
electromagnetic flowmeter following standard cross-sectional
methods (Gallagher and Stevenson 1999). Continuous temper-
ature loggers were placed in each of the six stream reaches
where Brook Trout were collected.
RESULTS
Spatial Distribution
Brook Trout were present in 119 (68%) of streams sampled.
Brook Trout were found in all of the major watersheds except
for the Cedar River watershed, where only one stream was
sampled. We sampled the most streams and Brook Trout popu-
lations in the eastern half of the Root River watershed
(Figure 1). Brook Trout populations were categorized as abun-
dant in 40 populations but rare in 21, with some samples only
having one Brook Trout (Figure 2).
Genetics
We collected genetic data for seven microsatellite DNA
loci on populations in 74 southeastern Minnesota streams and
1 Minnesota hatchery broodstock (MNWILD). Average sam-
ple size was 31 and ranged from 14 to 61. All but eight
636 HOXMEIER ET AL.
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samples had more than 20 individuals and more than half had
30 or more individuals. Most loci in most populations con-
formed to Hardy–Weinberg expectations. The number of tests
per locus with P-values <0.05 ranged from 2 to 11 and 4 to
14 for heterozygote deficits and excesses, respectively, out of
505 tests (locus £sample). Only five tests remained signifi-
cant after sequential Bonferroni correction (Rice 1989) for
multiple testing. Loci SfoC38, SfoC113, and SfoC115 showed
significant heterozygote deficits in the Rome hatchery sample,
and SfoC88 had a heterozygote deficit in the Nashua hatchery
sample, while SfoC24 had an excess in Camp Hazard Creek.
Significant linkage disequilibrium was found in only 10 tests,
with no locus pair significant for more than two samples.
Expected heterozygosities averaged 0.64 and ranged from
0.19 to 0.77 in samples from southeastern Minnesota and Iowa
populations (Table 1). The lowest heterozygosity was found
in the Pleasant Valley tributary sample (0.19), but the next
lowest was substantially higher at 0.39 in the Deering Valley
Creek sample, and all but two others (Spring Brook and Trout
Pond tributary) had values greater than 0.50. Allelic richness
had a similarly skewed distribution with an average of 4.2
(resample size of 22 genes), a range of 1.8–5.4, and all but
seven samples with values greater than 3.1. Heterozygosities
in hatchery samples ranged from 0.38 to 0.73. Phillips and
Rome samples had relatively low heterozygosities of 0.38 and
0.42, respectively, while other hatchery samples exceeded
0.60. Allelic richness averaged 2.7 in Phillips and Rome sam-
ples but 4.7–4.8 in the other hatchery samples.
The Garza–Williamson index Mwas relatively high for
most populations (mean D0.75; SD D0.28) but was at or
below the critical value of 0.68 in several populations. Low
values were found in Spring Brook and populations founded
by translocations from Spring Brook (Deering Valley Creek,
Miller Valley Creek, Trout Valley Creek), PHP hatchery,
Pleasant Valley tributary, Schad tributary, IOWA, and East
Beaver Creek.
Most sample pairs were significantly differentiated (F
ST
>
0; following sequential Bonferroni adjustment; Supplementary
Table S.1 available in the online version of this article). The
majority of samples that were not differentiated involved the
FIGURE 2. Relative Brook Trout abundance in coldwater streams in southeastern Minnesota delineated by major watersheds. Abundance was categorized with
a single electrofishing pass as abundant (>155/km), common (30–155/km), rare (<30/km), and none (0/km). Streams indicated as stocked are currently being
stocked with Brook Trout, and natural reproduction has not been evaluated.
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 637
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MNWILD strain and populations recently founded from this
strain. Most other undifferentiated pairs came from tributaries
and their recipient streams. In addition, replicate samples
taken 2 years apart at both the unnamed Riceford Creek tribu-
tary Number 3 and Spring Brook Creek were not significantly
differentiated (data not shown), demonstrating the stability of
allele frequencies over short time periods. Samples taken
8 years apart at Coolridge Creek had a significant but low F
ST
of 0.01 (data not shown).
The clustering algorithm based on Cavalli-Sforza–Edwards
chord distances (Cavalli-Sforza and Edwards 1967) grouped
populations into several distinct clusters. Several of the main
clusters contained hatchery samples and varying numbers of
southeastern Minnesota populations (Figure 3), indicating
likely contributions of these hatchery strains to the current
populations. The MNWILD hatchery sample and several pop-
ulations recently founded from this strain clustered together
but near another cluster containing Coolridge Creek, one of
the two source populations for MNWILD. Several clusters of
populations were not closely associated with hatchery sam-
ples. These clusters were primarily composed of geographic
groupings from Rush Creek, Zumbro River, and South Fork
Root River tributaries (Figure 3). Rush Creek and Zumbro
River clusters were part of a major branch separated from
branches with hatchery samples (with the exception of
MNWILD). The South Fork Root River cluster incorporated
the Iowa sample from South Pine Creek, the last putative rem-
nant Brook Trout population in Iowa. In all, 36 streams had
Brook Trout populations that were not closely associated with
known hatchery samples (Figure 3).
The STRUCTURE analyses identified multiple clusters that
were mostly consistent with major groupings on the neighbor-
joining tree (Figure 4). Three major clusters were initially
identified using all data, and further analysis broke some clus-
ters into distinct subclusters. The hatchery sample MNWILD
and populations reintroduced with this strain showed mixed
ancestry, as expected, from the two clusters containing its
founding populations. These samples were removed from fur-
ther analysis along with a tributary to a MNWILD-stocked
stream. The three hatchery samples MARQ, SCF, and NASH
did not assign with probability >0.50 to any one group but
were included in the two highest clusters to which they
assigned for further analysis. The first cluster contained PHP
and ROME hatchery samples and several Minnesota samples.
Further analysis including MARQ, SCF, and NASH formed
three subclusters, one with PHP, ROME, and two Minnesota
samples, a second with Spring Brook and several populations
founded by translocations from Spring Brook, and a third with
MARQ, SCF, and NASH hatchery samples and two Minnesota
samples. The second major cluster contained OWHI hatchery,
the IOWA sample, and numerous Minnesota samples from the
South Fork Root River, other Root River tributaries, and three
Zumbro River samples. A few samples were slightly below
0.50 but were included because of geographic proximity to
others in this cluster. Further analysis separated primarily the
Iowa and South Fork Root River samples from the hatchery
and other Minnesota samples. The third cluster contained
numerous samples from Rush Creek tributaries and their trans-
located populations (Swede Bottom Creek, East Burns Valley
Creek, East Indian Creek) and four samples from the Zumbro
River. This differed from the tree diagram, in which all Zum-
bro River samples grouped together. The STRUCTURE analy-
ses identified additional partitioning, but these subclusters
isolated hatchery samples from numerous Minnesota samples
and grouped many of those Minnesota samples by watershed.
It was difficult to ascertain admixture because of the many
populations and relatively few loci, and these difficulties were
compounded by the lack of strong assignment of several
hatchery samples to any one cluster. Despite these complica-
tions, there were suggestions of admixture in some population
groupings. Many samples in the upper South Fork Root River
grouped with Iowa in the tree diagram, but while Iowa
assigned to a STRUCTURE cluster with 0.85 probability, the
South Fork Root samples assigned with an average probability
of only 0.61 (range D0.46–0.68), possibly resulting from mix-
ture of a lineage similar to Iowa with other lineages. Consis-
tent with admixture, many of the South Fork Root River
samples had relatively high heterozygosity and allelic richness
compared with most samples and considerably higher than
that for Iowa. In a second instance, all Zumbro River samples
grouped in the tree diagram but STRUCTURE split them into
two main clusters. Four samples from the lower Zumbro River
assigned with an average probability of 0.76 to cluster 3, while
three from the upper Zumbro River assigned with an average
probability of only 0.55 to cluster 2. This lower assignment
may have resulted from admixture in the latter three samples.
Population Characteristics
The six intensively studied populations were grouped into
two categories based on genetic origin. Trout Brook, Trout
Valley, and Garvin Brook were associated with eastern U.S.
hatchery samples and were categorized as Eastern USA.
Maple Creek, Coolridge Creek, and East Indian Creek were
not associated with hatchery samples and were categorized as
remnant (Figure 3). Mean summer water temperatures were
warmest in East Indian Creek and Maple Creek (Table 2).
These streams had the warmest summer temperatures and the
coldest winter temperatures. Water temperatures did not
exceed maximum limits (»20C) for adult Brook Trout in any
of the study streams.
Brook Trout density ranged from 0.023 to 0.174/m
2
across
streams but did not differ between genetic strains (t-test: PD
0.52; Table 2). Brook Trout density was positively related to
stream discharge (rD0.98; P<0.001). All six streams had
low densities of Brown Trout, but there was no relationship
between Brook Trout density and Brown Trout density
(rD0.40; PD0.42).
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TABLE 1. Stream identification with year of sample collection, sample size, expected and observed heterozygosities (H), the Garza–Williamson index (G–W),
and allelic richness (A
R
). Samples include Driftless Area streams from southeastern Minnesota and Iowa and known hatchery strains. The six streams intensively
studied for population characteristics are in bold italics.
Sample ID Year NExpected HObserved HG–W A
R
Southeastern Minnesota
Badger Creek tributary BCT 2003 29 0.67 0.71 0.80 5.0
Bee Creek BEE 2008 16 0.64 0.64 0.76 3.7
Blagsvedt Creek BLAG 2003 26 0.66 0.62 0.75 4.6
Borson Spring Creek BRS 2003 30 0.69 0.73 0.69 4.3
Bridge BDG 2008 24 0.61 0.62 0.78 4.3
Brush Valley BRV 2009 24 0.65 0.70 0.72 4.3
Bullard Creek BUL 2006 30 0.57 0.52 0.83 3.7
Butterfield BUT 2006 24 0.66 0.64 0.70 4.2
Camp Hazard Creek CHC 2003 31 0.66 0.82 0.71 3.9
Campbell CAM 2008 26 0.74 0.75 0.77 5.1
Chickentown Creek CKC 2003 29 0.61 0.62 0.84 4.0
Cold Spring Brook CSB 2003 25 0.68 0.74 0.78 4.2
Coolridge Creek CC 2001 46 0.68 0.69 0.78 4.3
Corey COR 2006 25 0.75 0.71 0.75 5.2
Crooked Creek CRK 2006 39 0.70 0.73 0.64 4.9
Crooked Creek, South Fork CRC 2008 28 0.65 0.63 0.82 4.5
Dakota Creek DKC 2003 32 0.63 0.60 0.65 3.9
Deering Valley Creek DVC 2009 32 0.39 0.39 0.80 2.4
Diamond DIA 2006 40 0.66 0.65 0.83 4.6
East Beaver Creek EBC 2008 16 0.55 0.58 0.71 3.0
East Burns Valley Creek EBVC 2003 27 0.56 0.59 0.73 3.4
East Indian Creek EIC 2006 56 0.70 0.69 0.70 4.7
Ferguson Creek FER 2007 26 0.64 0.77 0.79 3.7
Ferndale FDL 2008 30 0.65 0.60 0.78 4.5
Garvin Brook GAR 2006 27 0.64 0.66 0.78 3.7
Girl Scout Camp Creek GSCC 2003 26 0.71 0.69 0.77 4.8
Gribben GRB 2010 30 0.63 0.65 0.74 4.1
Hallum HAL 2009 25 0.72 0.70 0.79 5.3
Hammond Creek HMC 2003 30 0.69 0.63 0.78 4.9
Helbig Creek HEL 2009 42 0.69 0.72 0.75 4.1
Hemmingway Creek HEM 2001 34 0.69 0.64 0.79 4.4
Larson Creek LAR 2006 24 0.70 0.69 0.81 4.5
Long LNG 2006 30 0.67 0.70 0.75 4.5
Looney Creek LVC 2003 30 0.65 0.67 0.80 4.4
Maple Creek MAP 2006 32 0.70 0.67 0.74 4.8
Mazeppa Creek MAZ 2006 34 0.68 0.71 0.62 4.2
Middle Branch Whitewater MBW 2007 22 0.67 0.67 0.76 4.9
Middle Creek MDC 2003 27 0.62 0.60 0.80 4.2
Miller Valley Creek MVC 2009 37 0.55 0.54 0.76 3.3
Nepstad Creek NEP 2003 30 0.73 0.73 0.75 4.8
Newburg NEW 2006 15 0.70 0.63 0.75 4.6
Peterson Creek PTC 2003 31 0.60 0.61 0.70 3.5
Pine Creek PIC 2010 21 0.58 0.56 0.77 3.6
Pine New Hartford PCR 2007 25 0.70 0.69 0.78 4.8
Pine New Hartford, south fork PINE 2008 28 0.77 0.76 0.78 5.3
(Continued on next page)
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 639
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Growth was variable across streams, with Coolridge Creek,
Trout Brook, and Garvin Brook having the slowest growth
rates to age 3 (Table 3). These three streams also had the
lowest summer water temperatures. Maple Creek and Trout
Valley Creek had larger Brook Trout than the other popula-
tions as a result of having older fish but not necessarily
faster growth rates (Table 3; Figure 5). Length at age 3 was
positively related to stream discharge (rD0.89; PD0.017),
but discharge was not related to mean length at age for youn-
ger Brook Trout (ages 0–2, all P>0.05). Mean length at
age did not differ by genetic origin for any age-class (t-test:
P>0.05).
TABLE 1. Continued.
Sample ID Year NExpected HObserved HG–W A
R
Southeastern Minnesota
Pleasant Valley tributary PVT 2009 14 0.19 0.18 0.62 1.8
Rush tributary–Fillmore URUF 2008 29 0.69 0.70 0.75 4.3
Rush tributary–Winona URUW 2008 26 0.62 0.59 0.80 3.9
South Branch Whitewater tributary SBWTr 2003 29 0.68 0.68 0.73 2.9
Schad tributary–Boynton SCD 2008 16 0.56 0.69 0.58 4.5
Schueler Creek SHC 2003 26 0.70 0.69 0.78 4.1
Second Creek SEC 2003 26 0.65 0.70 0.69 4.8
Shamrock SHA 2007 25 0.72 0.71 0.82 5.1
Silver SIL 2009 25 0.71 0.72 0.83 4.4
Silver Springs SSP 2010 15 0.67 0.77 0.72 3.2
Sorenson SRN 2008 20 0.54 0.61 0.69 2.8
Spring Brook SBC 2001 32 0.47 0.46 0.60 3.5
Stockton Valley Creek SVC 2008 19 0.59 0.56 0.70 4.5
Storer STR 2006 29 0.72 0.72 0.76 4.2
Sullivan Creek SUL 2006 27 0.68 0.71 0.77 4.5
Swede Bottom Creek SWB 2003 26 0.68 0.69 0.78 4.7
Thompson Creek THM 2006 30 0.70 0.73 0.75 3.7
Trail Run TRN 2009 61 0.60 0.59 0.73 4.5
Trout Brook TRB 2007 33 0.68 0.69 0.78 4.6
Trout Brook TBW 2009 21 0.63 0.69 0.77 2.7
Trout Pond tributary TPT 2008 27 0.46 0.56 0.70 4.5
Trout Run TTR 2009 27 0.71 0.79 0.78 3.7
Trout Valley Creek TVC 2007 25 0.57 0.56 0.68 4.4
Unnamed Riceford3 3UN 2006 29 0.73 0.73 0.81 4.1
Unnamed Riceford4 4UN 2006 26 0.61 0.59 0.81 4.6
Vesta VES 2009 27 0.60 0.65 0.78 4.2
Voelker Brook VKB 2003 28 0.64 0.72 0.79 4.6
West Beaver Creek BCW 2006 25 0.71 0.71 0.80 5.2
Wisel Creek WIS 2009 24 0.71 0.69 0.80 5.0
Iowa
a
South Pine Creek IOWA 1999 54 0.62 0.60 0.65 3.1
Hatcheries
b
Phillips PHP 1998 51 0.38 0.41 0.63 2.7
Marquette MARQ 2003 73 0.61 0.59 0.87 4.8
MN Wild MNW 1998 60 0.67 0.70 0.78 4.7
Nashua NASH 1997 37 0.72 0.68 0.85 4.8
Owhi OWHI 1998 52 0.73 0.73 0.80 4.7
Rome ROME 1998 50 0.42 0.33 0.74 2.7
St. Croix Falls SCF 1998 48 0.67 0.63 0.81 4.5
a
Data from King, unpublished data.
b
Data from Stott, unpublished data.
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Annual mortality rates were similar across three of the six
study streams (»63%; Table 2). The high mortality rate in
East Indian Creek may have resulted from predation on Brook
Trout by North American river otter Lontra canadensis
(R. J. H. Hoxmeier, personal observation). Mortality did not
differ between genetic origin (t-test: PD0.94) nor was it
related with either stream discharge (rD0.22; PD0.67) or
mean summer water temperature (rD0.59; PD0.22).
Brook Trout matured at a small size across all streams
(Table 2). Males matured at a smaller size than females,
except in Maple Creek. Males often matured in their first year
of life. Maple Creek and Trout Valley Creek had the largest
size at maturation for both males and females, with Coolridge
Creek and Trout Brook having the smallest. Size at maturity
did not differ by genetic origin (t-test: males, PD0.47;
females, PD0.81), but it increased with increasing stream dis-
charge (P<0.01; Figure 6).
DISCUSSION
Intolerant coldwater fishes, such as trout, are predicted to
decline given changes in both climate and land use (Flebbe
et al. 2006; Hudy et al. 2008; Lyons et al. 2010); however,
our study documented an increase in the distribution of a cold-
water native trout during the last several decades. We found
robust, remnant Brook Trout populations increasing in number
in the Driftless Area of Minnesota, which is likely the result of
the cumulative effects of land-use conservation practices,
improved fisheries management strategies, and the unique
landscape of the Driftless Area.
Previous reports suggested that native Brook Trout were
extirpated in southeastern Minnesota around 1900 and that
only hatchery-supported stocks remained (MacCrimmon and
Campbell 1969; Thorn et al. 1997). Thorn and Ebbers (1997)
reported that 3% of coldwater streams in southeastern Minne-
sota contained Brook Trout in the early 1970s compared with
FIGURE 3. Radial neighbor-joining tree diagram, based on chord distances, showing the genetic relationships among Brook Trout populations in southeastern
Minnesota streams and known hatchery strains (nD102). Potential remnant Driftless Area Brook Trout in southeastern Minnesota are in blue and cluster accord-
ing to watersheds (Zumbro River, Rush Creek, South Fork Root River). Hatchery strains are in bold and include MNWILD (green lines) and those with eastern
U.S. origins (red lines). Stream abbreviations are defined in Table 1.
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 641
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FIGURE 4. Assignment of populations to genetic clusters using a stepwise STRUCTURE analysis (Pritchard et al. 2000). Populations were initially assigned to
one of three distinct genetic clusters if their average assignment exceeded 0.45 (top box). Hatchery populations are in bold. Populations derived from recent Min-
nesota Wild stocking (MNWILD) showed similar assignments to clusters 2 and 3, which contained their source populations, and are listed separately. Several
other populations did not assign strongly to any one cluster (low probability, <0.45). Populations assigning to clusters 1 and 2 were then analyzed in separate
STRUCTURE runs to identify subclusters (lower two boxes). Geographic groupings described in the text are outlined: South Fork Root River (thin solid line),
Rush Creek (thick solid line), and Zumbro River (dashed line). Stream abbreviations are defined in Table 1.
642 HOXMEIER ET AL.
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54% in the mid-1990s. Our study found that 68% of coldwater
streams in southeastern Minnesota contained Brook Trout. We
attribute this recent increase to successful fisheries manage-
ment and a regionwide increase in stream base flows. Since
the late 1990s, numerous successful Brook Trout reintroduc-
tions have been implemented by the Minnesota Department of
Natural Resources (MN DNR) using the MNWILD strain.
This strain was developed with wild founders from a potential
remnant population and a naturalized population associated
with eastern hatchery strains but with no known recent stock-
ing. The MNWILD strain has been successful in streams
where earlier stocking attempts with other strains has failed
(MN DNR, file data). Wisconsin has had similar success
developing self-sustaining populations of naturalized Brown
Trout using wild populations to found broodstocks (Mitro
2004).
Streams in the Driftless Area offer quality habitat due to
groundwater inputs from deep, confined aquifers, which con-
trasts with streams north and east of the region in which tem-
peratures are regulated primarily by atmospheric conditions.
Base flows have increased in Driftless Area streams as a result
of earlier land-use changes and increased precipitation (Gebert
and Krug 1996; Trimble 1999; Juckem et al. 2008; Lenhart
et al. 2011). An increase in base flow can benefit trout popula-
tions by providing protection from avian and mammalian pre-
dation, increasing available habitat, and increasing growth
rates (Hakala and Hartman 2004; Harvey et al. 2006; Sotiro-
poulos et al. 2006). In our study, base flow discharge was posi-
tively related to Brook Trout density, length at age 3, and size
at maturation. Size structure and size at maturity for trout is
positively related to stream size in other regions (Jonsson et al.
2001; Meyer et al. 2003; Petty et al. 2005; Schill et al. 2010).
Interestingly, our large streams with robust Brook Trout popu-
lations also had the highest summer water temperatures. Moni-
toring and protecting base flows in the Driftless Area may be
as important as monitoring water temperatures in a changing
climate.
Our study indicates that considerable genetic diversity
exists within and among Brook Trout populations in southeast-
ern Minnesota, which could have facilitated the recent expan-
sion of Brook Trout and could help the species adapt and
persist in a changing environment. In many instances diversity
is likely sustained because of connectivity within portions of
watersheds, forming larger metapopulations that incorporate
TABLE 2. Habitat and Brook Trout population characteristics of six streams in southeastern Minnesota. Temperature (C) is the mean (SD in parentheses) sum-
mer (June–August) temperature for 2008 and 2009. Genetic origin is categorized as either remnant (R) or eastern USA (E). Length (mm) at maturity for males
(M) and females (F) was determined from logistic regression. Annual mortality was estimated from catch curves combined across years to account for variable
recruitment. Proportional stock density (PSD) is the number of Brook Trout over 200 mm divided by the number of Brook Trout over 130 mm. Brook Trout
(BKT) and Brown Trout (BNT) density is the mean adult (age 1 and older) density across four sampling periods.
Stream
Station
length
(m)
Discharge
(m
3
/s)
Mean
width
(m)
Mean
temperature
Genetic
origin
Length at maturity
Annual
mortality PSD
BKT
density
(N/m
2
)
BNT
density
(N/m
2
)
MF
Coolridge Creek 515 0.03 2.7 10.9(0.7) R 118 132 54.5 41 0.023 0.020
Maple Creek 180 0.19 5.3 14.1(1.1) R 179 172 63.2 24 0.174 0.023
East Indian Creek 209 0.11 5.7 14.1(1.0) R 133 157 76.0 40 0.102 0.016
Garvin Brook 311 0.08 5.6 11.2(0.6) E 127 149 62.4 36 0.064 0.017
Trout Valley Creek 278 0.11 4.8 12.4(0.9) E 138 164 63.0 26 0.080 0.011
Trout Brook 165 0.05 3.4 11.6(1.0) E 119 137 69.9 20 0.052 0.001
TABLE 3. Mean total length at capture (mm; SE in parentheses) for Brook Trout caught in six southeastern Minnesota streams in fall 2008 and 2009. Genetic
strain is categorized as either remnant (R) or eastern U.S. origins (E). Mean length at age was determined from a subsample of aged fish, and length frequency
data was analyzed with mixed-distribution models.
Length at age
Stream Strain Age 0 Age 1 Age 2 Age 3 Age 4
Coolridge Creek R 97.1 (1.1) 169.7 (2.6) 209.2 (4.1) 217.0 (10.1)
Maple Creek R 107.8 (0.7) 165.2 (1.5) 208.3 (4.7) 272.1 (9.0) 307.6 (16.9)
East Indian Creek R 116.7 (0.6) 203.8 (1.6) 238.1 (4.1) 261.6 (9.9)
Garvin Brook E 108.7 (0.8) 185.1 (3.9) 216.8 (13.0) 246.9 (9.3)
Trout Valley Creek E 128.4 (0.6) 196.5 (2.5) 222.9 (3.1) 257.5 (8.5) 300.5 (7.7)
Trout Brook E 115.5 (0.9) 166.0 (5.5) 209.7 (7.7) 245.7 (12.4)
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 643
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the relatively small populations in individual tributaries. How-
ever, the Garza–Williamson index identified several probable
bottlenecked populations with genetic diversity that was lower
than other populations in the region. Population origins were
linked to eastern U.S. hatchery strains, translocations within
the region, current MNWILD broodstock, and potential rem-
nant Driftless Area Brook Trout.
Several population clusters were not associated with known
hatchery sources from the past three decades, and these could
represent remnant Driftless Area Brook Trout lineages. One
consistent cluster in both the neighbor-joining tree and
STRUCTURE analyses incorporated all populations in the
Rush Creek subbasin of the Root River. An adjacent cluster in
the tree diagram incorporated the populations from Zumbro
River tributaries, although some populations are split off in
STRUCTURE analyses. A third group is separated from the
previous groups but includes tributaries of the South Fork
Root River along with an Iowa sample from what is thought to
be that state’s last remnant population of Brook Trout (B.
Kalishek, Iowa Department of Natural Resources, personal
communication). Several associations of populations were
inconsistent with geography but can be accounted for by
recorded translocations rather than stocking of hatchery strains
(MN DNR, file data). While these populations do not associate
closely with known recent stocking sources, establishing their
histories will require further genetic data and potential source
population samples. Whether these lineages prove to be
descendants of remnant Driftless Area populations or other
unknown exogenous populations stocked in the past, they
have proven their ability to persist in southeastern Minnesota
and deserve extra conservation attention.
The persistence of native genotypes despite the stocking of
exogenous sources would not be unprecedented for Brook
Trout. It has been reported throughout their range, including in
Ontario (Danzmann and Ihssen 1995), Maryland (Hall et al.
2002), Massachusetts (Annett et al. 2012), Wisconsin
(Krueger and Menzel 1979), and the southern Appalachians
(Galbreath et al. 2001; Habera and Moore 2005). Similar to
Minnesota, streams in the southern Appalachians experienced
extreme habitat degradation in the early 1900s from logging,
causing a decrease in Brook Trout distribution and yet native
and mixed-ancestry stocks persist (Habera and Moore 2005).
In neighboring Wisconsin, Krueger and Menzel (1979) argued
that natural patterns of genetic variation existed among popu-
lations despite years of stocking hatchery fingerlings and
catchable-sized fish.
FIGURE 5. Length frequency distributions of Brook Trout collected in fall
2008 and 2009 for six streams (Coolridge Creek, Maple Creek, East Indian
Creek, Garvin Brook, Trout Valley Creek, and Trout Brook) in southeastern
Minnesota. Brook Trout populations were characterized as either remnant
(solid bars) or hatchery origin (open bars).
FIGURE 6. Length at maturity (mm) for male (solid line) and female (dashed
line) Brook Trout related to stream discharge from six southeastern Minnesota
streams. Stream discharge was measured during summer base flow conditions.
644 HOXMEIER ET AL.
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Although we propose that remnant Driftless Area lineages
may persist, we do not imply that Brook Trout populations sur-
vived in all of the streams with potential remnant ancestry.
Habitat conditions, especially water quality and flow, were
degraded enough that Brook Trout were likely extirpated from
many streams (Thorn et al. 1997). Remnant lineages may
have persisted near some remaining headwater springs with
suitable habitat or in hatchery broodstocks or trout ponds
maintained in the region. Human assistance or recolonization
could then have spread lineages after base flows increased in
the region. Potential remnant populations in East Indian Creek,
Swede Bottom Creek, and East Burns Valley Creek can all be
traced to recorded translocations from Hemmingway Creek in
the 1970s. Considerable Brook Trout movement between
nearby tributaries has been documented in this region
(Hoxmeier and Dieterman 2013) and connectivity is high, at
least within many subbasins. The remnant population in Bad-
ger Creek tributary was not directly stocked with Hemming-
way Creek fish but meets the South Fork Root River only
0.4 km away from the translocated Swede Bottom Creek
population.
Few demographic characteristics distinguished potential
remnant from hatchery-associated populations; rather, Brook
Trout appear to exhibit phenotypic plasticity. For example, the
population characteristics in the potential-remnant East Indian
Creek were much more similar to those in Trout Valley Creek,
with an identical base flow, than to those in Coolridge Creek,
another remnant population that grouped closely in genetic
analyses but had a much lower base flow. Demographic char-
acteristics may have been similar among populations due to
strong environmental effects coupled with the potential for
rapid evolution in naturalized populations (Hendry et al. 2000;
Pearse et al. 2009). Native southern Appalachian and natural-
ized northeastern U.S. hatchery populations have similar
growth and life spans in the wild, but significant differences
have been observed in laboratory experiments (Habera and
Moore 2005; Wesner et al. 2011). A common garden experi-
ment, in which potential remnant and eastern hatchery strains
are monitored in the same stream, may be needed to determine
if there are genetically based differences in characteristics
between strains.
Adult Brook Trout densities in our six intensively studied
streams were similar to those found in centrally located popu-
lations in Michigan, Massachusetts, and Pennsylvania (Carl-
son and Letcher 2003; Kocovsky and Carline 2006; Grossman
et al. 2012). While temporal variation in trout abundance is
often high and may mask differences across streams located in
the center versus the edge of their range (Dauwalter et al.
2009), it would appear that some Driftless Area streams can
maintain high densities. Length at age for Brook Trout in the
Driftless Area was higher than that reported for several Michi-
gan, New York, Pennsylvania, and Tennessee streams (Cooper
1967; Flick and Webster 1975; Whitworth and Strange 1983;
Alexander and Nuhfer 1993). In a comprehensive age and
growth study in the southern Appalachians, only 3 out of 28
streams had Brook Trout over 200 mm (Konopacky and Estes
1988), whereas all of our six study streams had Brook Trout
this size. The potential of Driftless Area streams to maintain
Brook Trout populations with high densities and large size
structures should provide a recreational benefit to anglers, as
well as conservation benefits.
While Brook Trout distribution has expanded in the Drift-
less Area in the last 40 years, so has the abundance and dis-
tribution of Brown Trout (Thorn et al. 1997). The same
reasons for Brook Trout expansion can be given for the suc-
cess of Brown Trout in the Driftless Area. Even though we
targeted stream reaches towards Brook Trout, Brown Trout
were present in 78% of our samples. Brown Trout density in
our intensively studied streams did not influence Brook
Trout population characteristics; however, Brown Trout den-
sities in these six streams were on the lower end of the range
found in this region (Kwak and Waters 1997). Higher Brown
Trout densities have been shown to have negative effects on
Brook Trout in the Driftless Area (Hoxmeier and Dieterman
2013).
Management Implications
This study represents one of the most comprehensive evalu-
ations of Brook Trout in the Driftless Area and provides a use-
ful baseline for developing conservation strategies and
monitoring future impacts of stressors, such as climate change.
Brook Trout populations in this region did not conform to the
expectations of peripheral populations, likely because of
the quality stream habitat conditions found in the region. The
Driftless Area acted as a refugium during the last glaciation
period for numerous flora and fauna that still persist in the
region today (Rowe et al. 2004; Li et al. 2013). Because of the
thermally stable groundwater and increased base flows, this
region may again act as a refugium for Brook Trout in a warm-
ing climate. However, fisheries managers must ensure the
protection of base flows through enhancing groundwater infil-
tration and reducing groundwater withdrawals. Although
Brook Trout were found in the majority of streams, and in
more than previously recorded, the number of populations
where they were abundant was still low. Also, even though we
found Brook Trout in 68% of Driftless Area streams in Minne-
sota, we presume the remaining 32% had Brook Trout prior to
European settlement. This study should be repeated in the
future at a similar spatial scale to determine whether the Drift-
less Area continues to offer a refugium or whether Brook
Trout distribution declines as predicted for this region due to
warming air temperatures (Lyons et al. 2010).
Only 21% of Driftless Area streams potentially have rem-
nant Driftless Area Brook Trout lineages. These unique popu-
lations should be given conservation priority because they
have proven their ability to sustain themselves in this region.
In addition, their potential for high density and growth should
BROOK TROUT DISTRIBUTION IN THE DRIFTLESS AREA OF MINNESOTA 645
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be of value to fisheries managers. In particular, we recommend
ceasing management attempts to increase Brown Trout in
these remnant streams and treating major watersheds as dis-
tinct management units to conserve genetic diversity among
populations within the Driftless Area. Although we found few
differences in population characteristics associated with poten-
tial remnant versus introduced Brook Trout populations, the
influences of stream size and other environmental variables,
along with a relatively small number of studied populations,
limited our ability to detect differences. A more controlled
study is needed to determine whether differences in population
characteristics, and particularly fitness, exist among genetic
origins. The persistence of these distinct genetic groups
despite stocking of many sources suggests they may be well
adapted to their local environment.
Most populations in the region have moderately high
genetic diversity. To sustain this diversity, management
should focus on preventing drastic population declines and
maintaining the existing connectivity of tributary networks by
preventing the placement of barriers and assuring habitats are
suitable for the movement of Brook Trout within subwater-
sheds (Petty et al. 2012). Several probable bottlenecked popu-
lations were identified, and their genetic diversity was low
compared with other populations in the region. Many of these
populations are isolated and may be candidates for “genetic
rescue,” the addition of individuals from other populations to
enhance diversity and alleviate possible inbreeding depression
(Tallmon et al. 2004). The use of source populations we have
identified as genetically similar could help alleviate short-term
inbreeding risks while lessening the concern about outbreed-
ing depression (Edmands 2007).
ACKNOWLEDGMENTS
We would like to thank R. Bearbower, D. Casper, S. Erick-
son, S. Klotz, B. Lee, J. Magee, J. Melander, M. Peterson,
J. Roloff, J. Schulz, V. Snook, and J. Weiss for their help in
the field and J. Hennig, J. Jensen, S. Mackenthun, and S. Seim
for their help in the laboratory. C. Anderson and three anony-
mous reviewers provided helpful reviews of this manuscript.
This project was funded in part by the Federal Aid in Sport
Fish Restoration Program (Project F-26-R).
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