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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. Received July 25, 2014; accepted March 17, 2015
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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
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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
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:
Received July 25, 2014; accepted March 17, 2015
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
Downloaded by [John Hoxmeier] at 05:27 02 July 2015
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.
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
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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
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).
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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 (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
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.
Downloaded by [John Hoxmeier] at 05:27 02 July 2015
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
), mean lengths at age (m
), and stan-
dard deviations of length-at-age distributions (s
). 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
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
) 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
/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.
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).
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
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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
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.
Downloaded by [John Hoxmeier] at 05:27 02 July 2015
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
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
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
). 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
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)
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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:
TABLE 1. Continued.
Sample ID Year NExpected HObserved HG–W A
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
South Pine Creek IOWA 1999 54 0.62 0.60 0.65 3.1
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
Data from King, unpublished data.
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).
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.
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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.
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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
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
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.
Length at maturity
mortality PSD
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)
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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.
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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
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
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
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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).
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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... Brook Trout genetic studies have been conducted in a number of areas across the Midwest, including Lake Superior (Sloss et al. 2008;Wilson et al. 2008;Stott et al. 2010;Scribner et al. 2012;Leonard et al. 2013) and the Driftless Areas of Wisconsin (Hughes 2008) and Minnesota (Hoxmeier et al. 2015). These studies utilized the microsatellite marker set developed by King et al. (2012) and thus afford an opportunity to aggregate data from multiple research efforts to gain novel insights of broadscale patterns of genetic structure in the region. ...
... Trout stocking began in the Midwest during the late 19th century through the cooperation of the federal government, private hatcheries, conservation groups, and eventually state agencies (U.S. Commission of Fish and Fisheries 1888; . The origin of early hatchery strains is largely unknown, although there is speculation that these strains were derived from local populations (Fields and Philipp 1998;Hoxmeier et al. 2015). However, the use of these strains occurred during an era when Brook Trout were readily transferred across state, provincial, international, and hydrological boundaries, thereby leading to the possibility that these putatively native strains underwent periodic infusions of alleles originating from divergent sources (U.S. Commission of Fish and Fisheries 1888; Wisconsin State Conservation Commission 1930). ...
... Populations are color coded by hydrologic unit codes (HUC) defined by the U.S. Geological survey at the subregional (HUC4) level, and gray lines correspond to regional (HUC2) drainage boundaries in the United States. 4 in the 1970s and 1980s in favor of strains developed by hatcheries located along the Atlantic seaboard (Fields and Philipp 1998;Hoxmeier et al. 2015). The most commonly stocked strain in Wisconsin since this time has been the St. Croix Falls hatchery strain. ...
Brook Trout Salvelinus fontinalis have faced significant declines throughout their native range and have been stocked in Midwestern waters since the late 1800s to offset such losses. Several studies have investigated the genetic effects of these stockings, but these efforts have been confined to relatively small spatial scales. In this study, we compiled 8,454 Brook Trout microsatellite genotypes from 188 wild Midwestern populations and 26 hatchery strains to provide novel insights of broadscale population structure, regional patterns of genetic diversity, and estimates of hatchery introgression for inland Wisconsin populations. Our results indicate high levels of differentiation among our study populations, a lack of hydrological population structuring, lower estimates of genetic diversity in the Driftless Area, and that hatchery introgression has been largely confined to regions of inland Wisconsin that have been heavily affected by anthropogenic disturbances (i.e., the Driftless Area). We also provide evidence that populations may be able to purge hatchery‐derived alleles, discuss possible mechanisms behind this phenomenon, and consider their relevance to accurate estimation of hatchery introgression. Collectively, these results summarize the genetic effects of over a century of anthropogenic disturbance on native Brook Trout populations and emphasize the importance of integrating historical data into contemporary genetic research of intensively managed species.
... More comprehensive research was subsequently initiated to better understand available Brook Trout resources and ecological aspects surrounding populations in the Driftless Area. Hoxmeier et al. (2015) found Brook Trout in 68% of Southeast Minnesota streams and 21% of streams had remnant populations. This resulted in the development of a new Heritage hatchery strain and increased management efforts towards Brook Trout. ...
... Depending on the strain used, ancestry from stocked fish ranged from none to an almost complete replacement of native populations. Several groups of Brook Trout in southeastern Minnesota descend from remnant populations or from unknown stocked sources, but not from the known strains stocked from the 1970s onward (Hoxmeier et al. 2015). ...
... However, the status of native Brook Trout populations varies considerably across their Midwestern range primarily due to differences in historical declines attributed to habitat loss due to agricultural practices (Sullivan 2000;Marshall et al. 2008;Kelly et al. 2021) and the introduction of non-native Brown Trout Salmo trutta Mutel 2008;McKenna et al. 2013). Though Brook Trout currently occupy approximately 68% of the Minnesota Driftless Area (Hoxmeier et al. 2015) and 41% (16,883 of 41,097 stream reaches) of coldwater streams in Wisconsin (Mitro et al. 2019), they occupied only 14% (19 of 138 sites) of Iowa Driftless Area streams (Kelly et al. 2021). Given that Brook Trout have a disproportionate influence on the currently available FIBIs created for Midwestern low-gradient coldwater streams (Lyons et al. 1996;Mundahl and Simon 1998), FIBI protocols that weight Brook Trout presence or absence differently than one another may be more or less appropriate for a study area due to historical spatial differences in Brook Trout distributions. ...
... The metric-rich FIBI used in this study was primarily developed for use in states throughout the Driftless Area like southwest Wisconsin, southeast Minnesota, northwest Illinois, or northeast Iowa (Mundahl and Simon 1998). However, Iowa streams tend to have lower occurrence and abundance of Brook Trout compared to surrounding states in the Driftless Area (Hoxmeier et al. 2015;WI DNR 2019;Kelly et al. 2021). Although restoration efforts for Brook Trout in Iowa are ongoing, only 28 streams have received restoration stockings at this time and only 11 of those streams have developed self-sustaining wild populations (Iowa Department of Natural Resources, unpublished data). ...
Full-text available
Multiple fish-based indices of biotic integrity (FIBI) exist to estimate stream health using fish community structure. Yet, these metrics require different amounts of data and may result in different interpretations of stream health. We compared functionality of “low-metric” (5 metrics) and “metric-rich” (12 metrics) coldwater FIBIs for estimating stream health in 138 coldwater streams of northeastern Iowa, USA. Then, we investigated associations between FIBI scores and environmental factors at local and catchment scales using mixed effects linear regression. FIBI scores from both protocols were positively correlated (R² = 0.77); the majority of streams scored fair (n = 31, mean = 45; fair) using the metric-rich index but scored very poor using the low-metric index (n = 35, mean score = 25; poor). FIBI scores were higher (mean = good) when Brook Trout Salvelinus fontinalis were present with both indices. When Brook Trout were absent, scores were lower and less variable with the low-metric index (mean = 19.63; poor) compared to the metric-rich index (mean = 40.38; fair). Local habitat was more related to both FIBI scores than catchment-scale habitat: maximum daily stream temperature and bare bank severity index were negatively correlated with both FIBI scores whereas canopy coverage correlated positively with metric-rich FIBI scores. Brook Trout presence was indicative of coldwater stream health for both indices. Our results suggest the metric-rich FIBI index has improved ability to differentiate lower quality sites due to increased sensitivity. Our results can be used to improve stream health estimates and restoration prioritizations.
... Brook Trout occurrence in headwater streams at the southwestern edge of their range in the Iowa Driftless Area was rare (~14%) and most strongly associated with summer stream temperatures. Neighboring states with low-gradient, groundwater-fed streams have much higher occurrence rates, with recent studies finding that Brook Trout occupied 68% of Driftless Area streams in Minnesota (Hoxmeier et al. 2015) and an estimated 41% (16,883 of 41,097 stream reaches) of Wisconsin coldwater streams (Mitro et al. 2019). Conversely, nonnative Brown Trout occupied 55% of our study sites and occupancy was most strongly associated with instream flow and macrohabitat homogeneity. ...
... Elevated Brown Trout occurrence can likely be attributed to widespread historical stockings by the IDNR and higher survival and reproductive rates compared to Brook Trout (Kirby et al. 2020). Similarly, naturalized Brown Trout occupy a greater portion (78%) of the Driftless Area of Minnesota than native Brook Trout (Hoxmeier et al. 2015). Our results indicate that although catchment-scale models may be appropriate for predicting Brook and Brown Trout occupancy, environmental conditions at fine spatial scales have stronger effects and are likely better indicators of habitat suitability, particularly for the Brook Trout, an intolerant coldwater species. ...
Fish populations at the fringe of their geographic range often inhabit marginal habitats and are vulnerable to ecological disturbances such as species invasion, land cover conversion, and climate change. The Driftless Area of northeastern Iowa, USA, represents the southwestern edge of Brook Trout’s Salvelinus fontinalis native range, where endemic populations have been greatly reduced due to habitat degradation and introduced Brown Trout Salmo trutta. Therefore, documenting Brook Trout occurrence patterns at the southern tip of their range may prove useful for the conservation of peripheral populations. We fit single species occupancy models at multiple spatial scales to estimate the relative effects of biotic (e.g., Brown Trout density) and habitat (instream, riparian, and watershed) variables on Brook Trout and Brown Trout occupancy to predict their current distribution in the Iowa Driftless Area. Species occurrence and physical habitat data were collected at 138 stream segments of the Upper Iowa, Yellow, and Little Maquoketa watersheds (HUC8) during May through September, 2018 and 2019. Brook Trout occupancy was low (19 of 138 sites) and affected by local (instream and riparian) habitat covariates, particularly August‐September stream temperatures, but no adverse effects of Brown Trout density were detected. Brown Trout occupied 54% of streams (74 of 138 sites) and occupancy was influenced by a combination of local (mean stream velocity, the percentage of run macrohabitat, and August‐September stream temperatures) and catchment‐scale (percent forested land cover and upstream catchment area) habitat variables. Our results provide evidence that instream thermal conditions are a critical determinate of Brook Trout distribution while Brown Trout exhibit plasticity in habitat suitability and increased colonization in areas where introduced. Given Brook Trout’s dependence on cold stream temperatures, the projected loss of thermally suitable habitats due to climate change may facilitate their replacement by naturalized Brown Trout at the southwestern extent of their range.
... No summary models that explained observed variation in size-or age-at-maturity were strongly supported by the data. In stream populations, size-at-maturity has been found to be longer in populations with larger bodied fish and higher abundance, and higher discharge (Hoxmeier et al. 2015); which is interesting because studies on lentic Brook Trout have shown decreased size at maturity in response to experimental harvest (Donald and Alger 1989). Age-at-maturity has been attributed to fast growth early in life, but there are complex relationships among growth, fecundity, and survival that describe age-at-maturity (Hutchings 1993), especially in iteroparous spawners. ...
... McNair) length-at-fifty-percent-maturity only varied by 40 mm. Our length-at-fifty-percent-maturity results fall well within the wide range of length-atmaturity observed in Brook Trout(Stearns and Hendry 2003;Hoxmeier et al. 2015;Hoxmeier and Dieterman 2016) ...
Primary demographic attributes such as somatic growth, mortality, size- and age-at-maturity, fecundity, and recruitment drive the structure of fish populations, and these processes are also influenced by density-dependent and -independent processes. Here I study multiple populations of unexploited (i.e. assumed equilibria), lentic Brook Trout to describe variation in population structure. Studying unexploited populations gives fisheries managers and scientists an understanding of the intrinsic variation in systems absent from harvest pressure. First, I identify how much primary demographic attributes vary among populations, then attempt to attribute the observed variation to a suite of nested models containing terms for ecosystem productivity (total phosphorus concentration), climate (growing degree days or GDD), and density (fish biomass per hectare) in 9 lakes. I found that (1) populations varied substantially in somatic growth parameters (two-fold), natural mortality (three-fold), age-at-maturity (three-fold), length-at-maturity (two-fold) and recruitment (three-fold), (2) growth early in life was negatively correlated with density (r = -0.58), but maximum length was positively correlated with GDD (r = 0.61), and (3) spawning stock density was negatively correlated with recruitment (r = -0.57), but positively correlated with GDD (r = 0.55). I then experimentally harvested these previously unexploited populations with size selective gillnets by removing 30-70 % of the largest individuals from 5 of the 9 populations over 2 consecutive years. I tested the compensatory response to harvest with a BACI analysis, where I looked to see if absolute growth rate, size- and age-at-maturity, reproductive investment, and recruitment compensate for fisheries harvest. I found (1) strong evidence of recruitment compensation, (2) that overall (i.e. site-wide) stock-recruitment relationship was strongly density dependent and over-compensatory (i.e. a humped, Ricker type relationship), (3) positive but nonsignificant compensation in growth and age-at- iii maturity, and (4) no change in reproductive investment, but noted that populations may compensate for reproductive capacity in other ways (e.g. a combination of increased somatic growth and younger age-at-maturity). Comparing observed variation in unexploited populations’ demography with environmental variables helps fisheries managers and scientists understand intrinsic variability, and drivers of said variability; further exploiting these populations in an experimental fishery shows the initial mechanisms behind compensation. Examining both unexploited and responses to fisheries will help fisheries managers and scientists understand which populations can have their density reduced (via setting appropriate harvest rates), set realistic targets to recover populations, and increase understanding of the mechanisms that structure populations.
... Noted increases in the density and biomass of slimy sculpin populations at recovering sites, therefore, could lead to greater predation on brook trout eggs and fry and negatively affect their local populations. In addition, other studies support the assertion that nonnative brown trout (and rainbow trout) frequently out-compete, reduce, or displace native brook trout where both species coexist in streams, especially where water quality has been degraded (Hoxmeier et al., 2015). Consider for example, that during a 6-year study in two Minnesota streams with sympatric brook trout and brown trout populations, Hoxmeier and Dieterman (2016) found that the abundance and growth rates of brook trout increased, and their size structure shifted towards larger individuals after brown trout were removed. ...
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Decades of acidic deposition have adversely affected aquatic and terrestrial ecosystems in acid-sensitive watersheds in parts of the eastern United States. The national Acid Rain Program (Title IV of the 1990 Clean Air Act Amendments - CAAA) helped reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) and resulted in sharp decreases in the acidity of atmospheric deposition. The decrease in acidic deposition produced a steady decline in the acidity of streams in many poorly buffered waters across the western Adirondacks and parts of the Catskill Mountains of New York. Until recently, however, there has been little evidence of biological recovery in most acid-sensitive streams in both regions. Long-term deposition and stream-chemistry records and fish-community data from quantitative surveys done during 1991-93 and again during 2012-19 at 13 sites in the upper Neversink River and its tributaries were evaluated to determine if chemical and biological recovery were evident in this Catskill Mountain watershed and if they could be linked to regional declines in acidic deposition. Between 1991 and 2019, large decreases in sulfate and nitrate deposition in the basin mirrored declines in total nationwide SO2 and NOx emissions. There were corresponding decreases in sulfate and nitrate concentrations in deposition at a National Trends Network station at Frost Valley (NY68) and coincident declines in sulfate concentrations at four long-term monitoring sites in the Neversink River watershed. Mean acid neutralizing capacity and pH increased and inorganic aluminum (Ali) concentrations from routine summertime samples decreased significantly at most moderately to severely acidified sites between the two study periods. Community richness, density, and biomass increased at most sites, while the density and biomass of brook trout Salvelinus fontinalis populations increased at fewer sites that were undergoing chemical recovery. Although recovery is far from complete, trends in deposition chemistry, water quality, and fish assemblages in streams of the upper Neversink watershed indicate that the 1990 CAAA is having positive impacts on aquatic ecosystems in the Catskill Mountain region, New York.
... benefitted more streams).The data add to the growing body of evidence that Driftless Area streams may serve as an important climate refugium or climate shield (sensuIsaak, Young, Nagel, Horan, & Groce, 2015). Although some earlier climate change models predicted decreasing abundance and distribution of salmonids in this area (e.g.Lyons et al., 2010), data showing increasing trends in brook trout distribution(Hoxmeier, Dieterman, & Miller, 2015), brook trout abundance(Hoxmeier & Dieterman, 2019), stream baseflow (e.g.Juckem et al., 2008) and brown trout abundance in this study suggest otherwise. In addition, anecdotal information indicates increasing distributions of stream salmonids in southeast Minnesota. ...
A 40+ year programme to monitor brown trout, Salmo trutta L. populations at 25 groundwater-fed stream sites in southeast Minnesota, USA, was initiated to identify population trends, evaluate management actions and test ecological theories regulating populations. Significant increases between 1970 and 2018 were found for total biomass (an average of 5% annually) and abundance of juveniles (7%), all adults (7%) and adults >305 mm (3%). Sites managed with instream habitat projects had an additional 30% higher abundance for trout >305 mm and 57% higher for trout >355 mm. Sites managed with a catch-and-release regulation had nearly 130% higher abundance of trout >305 mm and 100% higher for trout >355 mm. Trout recruitment was temporally synchronous over the 9,200 km2 area but not associated with spatial distance. There was little support for stock-recruitment relationships, and density-dependent growth was only detected at half of the study sites. Increasing abundance trends represent a fisheries management success and suggest that these populations were largely regulated by a coupling of abiotic factors managed at two spatial scales: watershed (improved land use practices facilitating greater water infiltration) and instream (habitat improvement projects).
... Despite the lack of empirical landscape data, there are multiple lines of evidence that suggest brook trout has extensively declined across its native range (DeWeber & Wagner, 2014;Hudy, Thieling, Gillespie, & Smith, 2008;McKenna & Johnson, 2011;Power, 1980;Wesner, Cornelison, Dankmeyer, Galbreath, & Martin, 2011) to levels where it is considered extirpated from substantial portions of historical sites (Hoxmeier, Dieterman, & Miller, 2015;Hudy et al., 2008). For example, brook trout in the Lake Ontario tributaries is believed to have been reduced to approximately 21% of its historical distribution and is confined to the headwaters (Stanfield, Gibson, & Borwick, 2006), and only remnant population of coaster brook trout remain in the Great Lakes (Huckins, Baker, Fausch, & Leonard, 2008;Mucha & MacKereth, 2008). ...
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Ontario supports a vast fisheries resource with an abundance of lakes, rivers and streams. A landscape approach to management informed by a broad‐scale moni‐ toring programme has been initiated to assess the status of fisheries within lakes. However, not all species are assessed by this programme, and there is no provincial monitoring of species inhabiting rivers and streams. As such, changes in the status of a species such as brook trout, Salvelinus fontinalis (Mitchill), could be entirely missed. Brook trout is a highly valued and sought after species by anglers within the province, but there are concerns the species is declining. Given the paucity of broad, empirical data, the status and trends of brook trout across the province have been based on expert opinion at multiple local scales. In 2016, a online questionnaire was sent to brook trout experts to determine status, stressors, management approaches and as‐ sess risks (magnitude and probability) to lake and river/stream populations in differ‐ ent geographic areas of Ontario. A Bayesian network was used to analyse responses and develop a risk assessment based on expert opinion for brook trout at multiple scales within the province.
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Following centuries of declines, there is growing interest in conserving extant wild populations and reintroducing Brook Trout (Salvelinus fontinalis) populations of native ancestry. A population genetic baseline can enhance conservation outcomes and promote restoration success. Consequently, it is important to document existing patterns of genetic variation across the landscape and translate these data into an approachable format for fisheries managers. We genotyped 9,507 Brook Trout representing 467 wild collections at 12 microsatellite loci to establish a genetic baseline for North Carolina, USA. Rarefied allelic richness and observed heterozygosity, which reflect within‐population diversity, were low to moderate relative to levels typically observed at higher latitudes (means = 3.12 and 0.42, respectively). Effective population sizes varied widely, but were often very low (151 collections with an estimated Ne < 10). Despite decades of intensive stocking across the state, we found little to no evidence of hatchery introgression in most populations. Although genetic variation was significant at a variety of spatial scales (mean pairwise F’ST = 0.73), substantial genetic variation occurred between patches within individual watersheds. Analysis of molecular variance (AMOVA) found that a substantial portion (28.5%) of the observed genetic variation was attributed to differences among populations, with additional genetic variation among hydrological units (HUCs; 16.0%, 16.6%, 12.1%, and 9.4% of the overall variation among twelve‐, ten‐, eight‐, and six‐digit HUCs, respectively). We discuss a suite of potential applications for this type of genetic data to enhance management outcomes, such as conservation prioritization and selection of source stocks for reintroductions or genetic rescue.
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Climate warming is a threat to the survival of fishes adapted to cold water. Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta are two cold-water species occurring in streams in Wisconsin, where climate change may make these species particularly vulnerable. Vulnerable trout populations need to be identified to aid in the development of adaptation strategies. We used web-based stream temperature and fish-distribution models in FishVis to predict current (late twentieth century) and project future (mid-twenty-first century) distributions of Brook Trout and Brown Trout. The models predict the suitability of habitat for trout in individual reaches using environmental variables in a geographic information system, including adjacent and upstream channel characteristics, surficial geology, landcover, and climate. Future projections of air temperature and precipitation were obtained from 13 general circulation models downscaled for Wisconsin. Currently, 34,251 km of streams are suitable for Brook Trout and 20,011 km for Brown Trout. The models project a decline of 68% (10,995 km) in stream habitat for Brook Trout and a decline of 32% (13,668 km) for Brown Trout. These projected declines, while substantial, were lower than earlier estimates because our models account for projected increased precipitation that may enhance groundwater inputs and partially offset higher air temperatures. (link to view paper online)
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We examined and summarized existing knowledge regarding the distribution and status of self-sustaining populations of brook trout Salvelinus fontinalis at the subwatershed scale (mean subwatershed area = 8,972 ha) across their native range in the eastern USA. This region represents approximately 25% of the species' entire native range and 70% of the U.S. portion of the native range. This assessment resulted in an updated and detailed range map of historical and current brook trout distribution in the Study area. Based on known and predicted brook trout status, each subwatershed was classified according to the percentage of historical brook trout habitat that still maintained self-sustaining populations. We identified 1,660 subwatersheds (31 %) in which over 50% of brook trout habitat was intact; 1,859 subwatersheds (35%) in which less than 50% of brook trout habitat was intact; 1,482 subwatersheds (28%) from which self-sustaining populations were extirpated; and 278 subwatersheds (5%) where brook trout were absent but the explanation for the absence was unknown (i.e., either extirpation from or a lack of historical Occurrence in those subwatersheds), A classification and regression tree using five core subwatershed metrics (percent total forest, sulfate and nitrate deposition, percent mixed forest in the water corridor, percent agriculture, and road density) was a useful predictor of brook trout distribution and status, producing an overall correct classification rate of 7 1 %. Among the intact subwatersheds, 94% had forested lands encompassing over 68% of the land base. Continued habitat loss from land use practices and the presence of naturalized exotic fishes threaten the remaining brook trout populations. The distribution of brook trout subwatershed status and related threshold metrics can be used for risk assessment and prioritization of conservation efforts.
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Conservation of native fish stocks is an increasingly important task for fishery managers. Genetic research has shown that brook trout (Salvelinus fontinalis) native to the southern Appalachian Mountains differ considerably from stocks originating outside the region. Inventories throughout the southern Appalachians during the past decade identified over 500 km of streams that continue to support native brook trout populations. Genetic information can now be integrated with population dynamics data (e.g., abundance and distribution trends) to shape appropriate management strategies for this important fishery and biological resource given the threats it currently faces. Consequently, the American Fisheries Society's Southern Division Trout Committee developed a position statement to advocate management approaches suitable for conserving native southern Appalachian brook trout. The committee's position emphasizes the significance of these stocks, but also recognizes the value of fisheries provided by wild brook trout populations of mixed genetic heritage. Recommendations are provided for addressing issues including habitat protection and improvement, population restorations, stocking of hatchery brook trout, and angling regulations. The committee believes that these recommendations and guidelines, if implemented, will help ensure the future viability of southern Appalachian brook trout.
We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from
Electronic serial mode of access: World Wide Web via the Michigan DNR, Institute for Fisheries Research site.
The Program MARK was used to generate and test a plausible set of survival models for brook trout Salvelinus fontinalis and brown trout Salmo trutta to determine whether survival differed by season, species or age class. Apparent survival varied with time and age, but not by species. For the older (1999) age class, survival was lowest during the autumn of their age 1+ year whereas survival was lowest for the younger (2000) age class during the early summer of their age 1+ year. Additionally, estimates of survival for the younger age class exceeded those of the older age class in all but one interval (early summer 2001) but significant differences were observed in only one of these intervals (autumn 2000). To determine whether the observed seasonal differences in survival were related to seasonal differences in movement rates, multistrata spatial models were used within Program MARK to determine the probability of moving for each interval. In-site movement rates were found to be low regardless of season (average for all cohorts combined was 5%). The ability of the multi-strata modelling approach to detect temporal variability in movement, however, was potentially limited by spatial scale of the study reach (c. 1 km). Differences in survival between different aged fishes could lead to selection acting on age at maturity or reproductive effort at a given age. (C) 2003 The Fisheries Society of the British Isles.