Fish assemblages respond to altered flow regimes via ecological...
Transcript of Fish assemblages respond to altered flow regimes via ecological...
Fish assemblages respond to altered flow regimes viaecological filtering of life history strategies
MERYL C. MIMS AND JULIAN D. OLDEN
School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, U.S.A.
SUMMARY
1. In riverine ecosystems, streamflow determines the physical template upon which the life history
strategies of biota are forged. Human freshwater needs and activities have resulted in widespread
alteration of the variability, predictability and timing of streamflow, and anticipating the biotic
consequences of anthropogenic streamflow alteration is critical for successful environmental flow
management. In this study, we examined relationships between dam characteristics, metrics of flow
alteration and fish functional community composition according to life history strategies by coupling
stream flow records and fish survey data in paired flow-regulated and free-flowing rivers across the
conterminous United States.
2. Dam operations have generally reduced flow variability and increased flow constancy based on a
comparison of pre- and post-dam flow records (respective mean record lengths 26.2 and 43.1 years). In
agreement with ecological theory, fish assemblages downstream of dams were characterised by a lower
proportion of opportunistic species (a strategy favoured in environmental settings dominated by
unpredictable environmental change) and a higher proportion of equilibrium species (a strategy
favoured in more stable, predictable environments) compared to free-flowing, neighbouring locations.
3. Multiple linear regression models provided modest support for links between alteration of specific
flow attributes and differential life history representation below dams, and they provided strong
support for life history associations with dam attributes (age and release type). We also found support
for a relationship of both reduced flow variability and dam age with higher representation of non-native
species below dams.
4. Our study demonstrated that river regulation by large dams has significant hydrological and
biological consequences across the United States. We showed that on ecological time scales (i.e. the
order of years to decades), dams are effectively changing the functional composition of communities
that have established over millennia. Furthermore, the changes are directional and indicate a filtering by
dams for some life histories (equilibrium strategists) and against other life histories (opportunists).
Finally, our study highlights that dependence upon long-term flow records and availability of biotic
surveys extracted from national survey efforts limit our ability to guide environmental flow standards
particularly in data-poor regions.
Keywords: dams, flow regulation, freshwater fishes, life histories, United States
Introduction
Streamflow defines the physical template of riverine eco-
systems (Poff et al., 1997), provides longitudinal and lateral
access to foraging, spawning and recruitment habitat (Junk,
Bayley & Sparks, 1989), and acts as an evolutionary
selective force and an ecological filter of various survival
strategies employed by aquatic and riparian organisms
(Townsend & Hildrew, 1994; Lytle & Poff, 2004). At the
same time, human society requires water for life. Over the
millennia, humans have altered streamflow in riverine
systems for a myriad of reasons, including harnessing
water for drinking, irrigation and recreation and providing
flood control and hydropower (Gleick, 2003). The human
freshwater footprint encircles the globe with nearly half of
major river systems affected by dams (Vorosmarty et al.,
Correspondence: Meryl C. Mims, School of Aquatic and Fishery Sciences, University of Washington, 1122 NE Boat Street, Seattle, WA 98105,
U.S.A. E-mail: [email protected]
Freshwater Biology (2013) 58, 50–62 doi:10.1111/fwb.12037
50 � 2012 Blackwell Publishing Ltd
2010; Lehner et al., 2011). Future construction of dams,
particularly in economically developing nations, is an
inevitable consequence of human population growth and
the increasing freshwater and electricity needs in a chang-
ing climate (Palmer et al., 2008).
Despite providing many societal benefits, river regula-
tion by dams has also caused considerable ecological
damage and the loss of important ecosystem services
valued by society. Dams fragment rivers creating strings
of artificial lakes punctuated by often impassable barriers
(Reidy Liermann et al., 2012), and they alter physical
riverine habitat (Vorosmarty et al., 2003) and water quality
in both up- and downstream directions (Olden & Naiman,
2010). In particular, dams have been shown to be the
primary driver of altered streamflows throughout the
United States (Carlisle, Wolock & Meador, 2011), resulting
in reduced flow seasonality and variability (Poff et al.,
2007) and generally increasing short-term minimum flows
while decreasing short-term maximum flows (Magilligan
& Nislow, 2005). These changes alter the historical
disturbance regime, rendering some biotic adaptations
to these regimes obsolete while potentially favouring
others. For example, reduced flow variability by dams has
been associated with significant losses of native fish
species (Meador & Carlisle, in press) while concurrently
creating new niche opportunities that are often occupied
by non-native species with life histories novel to the
system or basin (Bunn & Arthington, 2002; Olden, Poff &
Bestgen, 2006).
Social, political and scientific pressure to ‘legitimise’
rivers as water users has resulted in a move to find
compromises in dam management to meet both human
and ecosystem water needs (Arthington et al., 2010)
through the provisioning of ‘environmental flows’
(Arthington et al., 2006) and large-scale flood events
(Konrad et al., 2011). However, despite the growing
recognition of ecologically sustainable water manage-
ment, natural resource agencies cite a lack of scientific
information required to support the application of this
approach. Poff & Zimmerman (2010) conducted an
extensive review of ecological responses to flow regula-
tion and reported that the biotic integrity of fish assem-
blages generally decreased with increased flow alteration.
Dam-induced changes to the flow regime can vary by
region and modes of dam operation (Magilligan &
Nislow, 2005; McManamay, Orth & Dolloff, 2012); how-
ever, due to overall sample size and disparate reporting
practices across studies, Poff & Zimmerman (2010) were
unable to distinguish the impacts of different components
of the flow regime and were limited to reporting the
effects of altered flow magnitudes.
Broader applicability of realised relationships between
flow alteration and biotic responses is important for
understanding the ecological impacts of dams and for
guiding environmental flow practices for ecologically
sustainable river management (Poff et al., 2010; Konrad
et al., 2011). General frameworks for prediction of biotic
responses to flow regulation, such as vegetation-flow
response guilds built upon traits rather than taxonomy
(Merritt et al., 2010), are more widely applicable than river
or reach-specific models that often do not translate
beyond their intended locality. Increasingly, freshwater
ecologists have turned to the use of species traits as a
universal currency for studying flow:ecology relation-
ships across diverse taxonomies and geographies
(reviewed in Poff et al., 2006; Frimpong & Angermeier,
2010). Life history traits of freshwater fishes are well
studied and well suited as a platform to test general
relationships between the flow regime and biological
communities; they also have direct implications for
ecosystem functioning (Winemiller, 2005). Winemiller &
Rose (1992) identified three life history strategies in both
freshwater and marine fishes that represent the essential
trade-offs among the basic demographic parameters of
survival, fecundity and onset and duration of reproduc-
tion. Opportunistic strategists are small-bodied species
with early maturation and low juvenile survivorship and
are predicted to be associated with habitats defined by
frequent and intense disturbance. Periodic strategists are
characterised by large body size, late maturation, high
fecundity and low juvenile survivorship and are likely to
be favoured in highly periodic (seasonal) environments.
Equilibrium strategists are typically small to medium in
body size with intermediate times to maturity, low
fecundity per spawning event and high juvenile survi-
vorship largely due to high parental care and small clutch
size. Equilibrium strategists are predicted to be favoured
in more stable habitats with low environmental variation.
The three life history strategies of the continuum are
hypothesised to be adaptive with respect to variability,
predictability and seasonality of environmental regimes
(Winemiller, 2005). Convergence of trait composition
along hydrologic gradients has been demonstrated for
freshwater fishes (e.g. Lamouroux, Poff & Angermeier,
2002; Logez, Pont & Ferreira, 2010), and empirical inves-
tigations that test predictions from life history theory
support these relationships (e.g. Tedesco et al., 2008;
Olden & Kennard, 2010; Carlisle et al., 2011). Recently,
we reported that life history composition of fish assem-
blages in free-flowing rivers of the United States are
associated with critical flow dimensions of variability,
predictability and seasonality and that these associations
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are largely predicted by Winemiller and Rose’s trilateral
continuum model (Mims & Olden, 2012). Taken together,
a traits-based approach to establishing flow–ecology
relationships provides a promising yet largely untested
framework to evaluate and generalise the ecological
effects of flow regulation by dams.
In this study, we quantified the relationships between
major facets of the flow regime and life history compo-
sition of fish assemblages downstream from large dams
across the United States and tested whether these asso-
ciations are predicted by life history theory. We posited
and tested three main hypotheses. (i) We expected dams
to reduce variability and increase predictability of flows,
and we also expected to see changes in timing and
duration of seasonal flows. (ii) We predicted fish assem-
blages at flow-regulated sites to show proportionally
lower number of species exhibiting opportunistic and
periodic life histories and higher richness of equilibrium
life history strategies relative to fish assemblages at free-
flowing sites. (iii) We predicted that observed changes in
three primary components of the flow regime (variability,
predictability and seasonality) caused by dam operations
will predictably shape native and non-native fish assem-
blage structure via the ecological filtering of life history
strategies.
Methods
Study sites
Study sites consisted of ‘triplet’ sets of a dam, flow gauge
and fish survey that met strict search criteria to ensure
that the hydrologic conditions measured at the gauge
station reflect the conditions where fish assemblages were
surveyed (following Larned et al., 2010). Dams were
identified through the Army Corps National Inventory
of Dams (NID: U.S. Army Corps of Engineers, 2000), a
data set of c. 79 000 large dams (>2 m) throughout the
United States. Pre- and post-impoundment daily flow
records were obtained from the U.S. Geological Survey’s
(USGS) gauge records, reflecting over 25 000 gauging
stations. Fish occurrence data for sites were synthesised
from a number of regional and national survey efforts,
including the Environmental Protection Agency’s (EPA)
Environmental Monitoring and Assessment Program
(EMAP) and the regional counterpart (Regional EMAP
or REMAP) (Hughes, Paulsen & Stoddard, 2000), the
USGS National Water Quality Assessment Program
(NAWQA) (Gilliom, Alley & Gurtz, 1995) and from
various state agencies. This resulted in a national database
of 5951 unique sampling sites (data collected between
1989 and 2002) with 530 native and non-native fishes in
North America represented (Herlihy, Hughes & Sifneos,
2006). Because the data available to us represented one-
time surveys spanning a 14-year period from potentially
disparate (but effective and efficient) survey techniques,
we examined species presence ⁄absence rather than abun-
dance.
Identification of candidate study sites was performed
by overlaying (in a Geographic Information System)
locations of dams, gauges and fish surveys onto a national
hydrography of streams and rivers (NHD Plus: Simley &
Carswell, 2009). Dams with both a fish survey and a gauge
within a radius of 20 km were identified. Candidate
triplets were then manually evaluated to ensure (i) the
gauge and survey were downstream of the dam; (ii) the
components of the triplets were within 20 river km of each
other and (iii) maximum difference in mean annual flow
(modelled by NHD Plus) between the components of the
triplets was <20% in order to ensure that tributary input
did not disproportionately influence flow conditions at
the fish survey location. Additionally, we screened for any
upstream dams (within 50 river km on the mainstem or
any major tributaries with >10% of mean annual flow at
the dam) built prior to the pre-impoundment flow record.
Once candidate sites were identified, gauge records
were evaluated for completeness. We required at least
15 years of data (<10 days of missing data per year) prior
to the fish survey to ensure accurate and precise estimates
of hydrologic metrics following Kennard et al. (2010). Our
only exception to this rule was the Ridgeway Dam study
site for which only 12 years of flow data are available
post-impoundment and pre-fish survey due to the rela-
tively recent construction of the dam. The McCloud and
Trenton Dam study sites required a second gauge to
provide complete pre-impoundment flow records. In both
these cases, the total maximum distance of the triplet was
minimally relaxed to incorporate the second gauge. The
maximum difference in mean annual flow for these
additional gauges adhered to our search criteria (13.3%
for McCloud and 6.1% for Trenton).
Finally, each study site was assigned a reference fish
survey from a nearby free-flowing stream because pre-
impoundment fish surveys were not available. Search
criteria were designed to identify the best available
reference survey and were as follows: (i) candidate
surveys were geographically close (within a 200-km
search radius) and located in the same major river
drainage; (ii) reference site had no dams within 50-km
upstream along the mainstem or any major (>10%)
tributaries and (iii) if multiple candidate sites were
identified, the reference site selected was that most similar
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in cumulative drainage area to triplet fish survey (mean %
difference in cumulative drainage area = 33.8, SD = 26.0).
Species life history strategies
Fish life history strategies were evaluated according to the
model of Winemiller & Rose (1992) that positions species
along three primary life history axes defining the oppor-
tunistic, periodic and equilibrium endpoints. The three
axes of the model are (i) ln(fecundity) defined as the
number of eggs or offspring per female per spawning
season; (ii) ln(length at maturation) defined as mean
female total length at maturation (mm) and (iii) ln(egg
size + 1) + ln(parental care + 1) (termed juvenile invest-
ment), defined as the mean diameter of mature, fully
yolked ovarian oocytes (mm) and an index of parental
care following Winemiller (1989). Fish life history traits
were obtained from a comprehensive database for fresh-
water fishes of the United States and Canada synthesised
from various literature, agency and expert accounts
(reported in Mims et al., 2010). Because many species
occupy intermediate positions in life history space, we
followed Olden & Kennard (2010) by conducting a ‘soft’
classification according to a species’ relative affinity with
each strategy. This was accomplished by calculating the
Euclidean distance in trivariate life history space between
the species’ position and the strategy endpoints, normal-
ising the distances between 0 and 1, and then computing
the inverse of these values to provide a ‘strategy weight’
for each species. This resulted in each fish species having
a proportional weight or affinity to the opportunistic,
periodic or equilibrium strategies. For each site, we
summed the strategy weights of species present and
computed the proportional value for each strategy to
represent relative life history composition.
Hydrologic metrics
We examined six key hydrologic metrics: annual coeffi-
cient of variation (AnnCV), high pulse count (HPC), base
flow index (BFI), flow predictability (FPred), flow con-
stancy ⁄flow predictability (Const ⁄Pred) and high pulse
duration (HPD). These metrics were chosen because they
address fundamental dimensions of the flow regime
(variability, predictability and seasonality) that drive
patterns of fish occurrence via the selection of life history
strategies (Bunn & Arthington, 2002; Lytle & Poff, 2004;
Mims & Olden, 2012) and represent the broader suite of
hydrologic metrics that are available from the literature
(Olden & Poff, 2003). The metrics were calculated for pre-
and post-impoundment records using the software Indi-
cators of Hydrologic Alteration (Mathews & Richter,
2007).
We also calculated an overall flow alteration index by
performing a principal component analysis (PCA) of the
six hydrologic metrics for each pre- and post-alteration
record to extract synthetic axes representing the dominant
gradients of variability in flow conditions. All hydrologic
metrics were first ln(x + 1) transformed to help achieve
normality, and we performed a PCA by computing a
singular value decomposition of a correlation matrix to
account for data measurement along disparate scales. The
index of flow alteration was then computed for each site
as Euclidean distance between the pre- and post-alteration
scores from the first three PCs (all statistically significant
according to a Monte Carlo randomisation test of the
eigenvalues). All statistical analyses were performed in
R version 2.14.1 (R Development Core Team, 2011) using
the vegan 2.0-3 package (Oksanen et al., 2012).
Statistical analyses
A paired Student’s t-test was used to evaluate directional
differences in flow metrics (variability, predictability and
seasonality) and proportional life histories (opportunistic,
periodic and equilibrium) between free-flowing and flow-
regulated river sites. A Wilcoxon signed rank test was
performed for those comparisons where the assumption
of normality was not met.
Next, we examined whether dam-induced changes in
flow variability, predictability and seasonality were
related to differences in proportional life history compo-
sition at flow-regulated versus free-flowing sites. This
involved modelling a series of response variables as a
function of the hydrologic metrics and dam attributes
using multiple linear regression. Comparisons of fish
assemblages in flow-regulated versus free-flowing rivers
resulted in four response variables representing per cent
change in proportional life history composition of the
opportunistic, periodic and equilibrium strategies and
proportional species composition of fishes non-native to
the particular locality at the scale of the 6-digit hydrologic
unit code (HUC) as described by Lawrence et al. (2011). A
total of 11 predictor variables was examined: the %
difference of the six previously described hydrologic
metrics, number of years since dam construction refer-
enced to the year of fish survey (YearsAlt), location of
water release from dam (hypolimnetic or surface) and the
overall index of flow alteration. We also considered %
difference in cumulative drainage area (%DCDA) and
linear distance between the flow-regulated versus free-
flowing sites to account for the possible effects of
Fish assemblages respond to altered flow regimes 53
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reference river selection. Similarly, we also tested for
relationships between the response variables and the
straight-line distance between surveys to check for spatial
autocorrelation that may confound analyses.
An iterative but strategic approach was used to evaluate
candidate models. Each response variable was modelled
independently as a function of both dam descriptors and
hydrologic alteration. Hydrologic alteration was mea-
sured either by the Flow Alteration Index or by a subset of
the six major hydrologic variables. Rather than modelling
all six major hydrologic variables, we modelled a maxi-
mum of three hydrologic metrics at one time. This was
done both to avoid over-parameterisation of the model
(given our limited sample size) and to minimise correla-
tion between hydrologic metrics. The six major hydrologic
variables were divided into two groups of three variables
each (first group: HPC, HPD and BFI; second group:
AnnCV, constancy ⁄predictability and flow predictability).
The fundamental characteristics of the flow regime (var-
iability, predictability and seasonality) were represented
in each set. We then evaluated models using backward
stepwise model selection. Goodness of fit of models was
evaluated by the Akaike information criterion, corrected
for low sample size (AICc) (Burnham & Anderson, 2002).
DAICc, likelihood and the evidence ratios were calculated
for the top four candidate models for each response
variable.
Results
We identified 12 sites that met our strict criteria for
inclusion (Table 1, Fig. 1). The length of pre-impound-
ment discharge records in our study ranged from 15 to
52 years (mean = 26.2 years), and the length of post-
impoundment discharge records ranged from 12 to
95 years (mean = 43.1 years). Distance between flow-reg-
ulated and free-flowing survey pairs was not correlated
with any measure of per cent difference in fish assem-
blages, and although free-flowing sites were generally
located higher in watersheds than flow-regulated surveys,
per cent difference in cumulative drainage was not
correlated with any observed difference in fish assem-
blages.
Dams significantly reduced downstream flow variabil-
ity with lower AnnCV (Wilcoxon signed rank test, n = 12,
z = )2.12, P = 0.034) and fewer high flow pulses (HPC,
Wilcoxon signed rank test, n = 12, z = )2.11, P = 0.037)
(Fig. 2a). Dam operations also increased flow con-
stancy ⁄predictability ratios (ConstPred, paired t-test,
t11 = 2.26, P = 0.045) but decreased flow predictability
(FlowP, paired t-test, t11 = 2.39, P = 0.036) (Fig. 2a). Dams
did not cause a significant overall reduction or increase
BFI or HPD (Fig. 2a). Fish assemblages downstream of
dams had proportionally lower representation of the
opportunistic life history strategy than their free-flowing
counterparts (paired t-test, t11 = 3.43, P = 0.006), propor-
tionally higher representation of the equilibrium life
history strategy (paired t-test, t11 = )3.575, P = 0.004),
and no significant difference in the proportion of species
displaying periodic strategies (Fig. 2b).
We identified a consistent assemblage shift towards
dominance by equilibrium strategists and away from
opportunistic strategists downstream of dams (Fig. 3a).
The direction of change in strategy composition was
largely independent of primary dam purpose. We also
identified via PCA two major axes characterising 74% of
the overall variation observed among the six major
hydrologic metrics (Fig. 3b). The first principal compo-
nent (PC1) explained 55% of the variation along a
gradient from more variable flows (positive scores asso-
ciated with higher Annual CV) to more steady flows
(negative scores associated with higher BFI). Sites gener-
ally shifted towards steadier, less variable flows post-
impoundment with 10 of 12 sites having a lower score
along PC1 for post-impoundment flow records than pre-
impoundment records; this pattern was largely indepen-
dent of dam purpose. PC2 explained 19% of the total
variation and represented a gradient from more seasonal
flows (negative values associated with an increase in
HPD) to less seasonal flows (positive values associated
with an increase in HPC). In contrast to PC1 (x-axis),
trends were less clear, with movement following no
general uniform direction along PC2 (y-axis).
Multiple linear regression analysis identified some
potential mechanisms for observed differences in life
history composition between flow-regulated and free-
flowing river sites (Table 2). Proportional change in
opportunistic strategist composition was positively
related to BFI; this model was more than twice as likely
given the data than the next most competitive model that
included the constancy ⁄predictability ratio. The most
supportive model for proportion of periodic strategists
included a positive relationship with dam age (YearsAlt),
with younger dams being associated with reduced repre-
sentation of the periodic life history at flow-regulated
sites. Proportional change of equilibrium strategists was
associated with the positive effect of flow predictability
(FlowP) alone, with this model having 1.7 times more
support than hypolimnetic release alone (HypoRels) and
2.9 times more support than both flow predictability and
hypolimnetic release (HypoRels) together. Finally, the
most supportive model for proportion of non-native
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species included a negative association with annual
variability (AnnCV) and dam age (YrsAltered); both
drivers together had 2.9 times the support of annual
variability alone.
Overall flow alteration (Flow Alteration Index) was not
identified as a significant predictor of any response
variables. This may be due to more nuanced relationships
that vary by dam operation or flow regime. Our sample
size prohibits explicit statistical testing of relationships by
dam operation purpose; however, we plotted Flow Alter-
ation Index versus proportional life history and % non-
native changes to explore possible associations (Fig. 4).
Perhaps the most suggestive pattern is that flow alteration
downstream of hydropower dams appears to have a
negative relationship with periodic life history (Fig. 4b)
(the opposite being true for flood control dams) and a
positive relationship with equilibrium life history
(Fig. 4c); no trends are readily apparent for the opportu-
nistic life history (Fig. 4a) or the % non-native species
(Fig. 4d).
Discussion
Our study demonstrates that river regulation by large
dams has significant hydrological and biological conse-
quences for riverine ecosystems across the United States.
Despite varying release schedules due to different dam
purposes, changes in flow variability and representative
fish life history composition were in most cases consistent
in direction across study sites and largely agreed with our
Table 1 Study site attributes, including dam type that indicates primary dam purpose and includes hydropower (Hydro), flood control
(FloodC) and locks. Fish survey year’ refers to the year the flow-regulated survey was conducted; ‘Triplet distance’ refers to the maximum
distance between any two components (gauge(s), fish survey and dam) of a given triplet; ‘D MAF’ indicates absolute value of maximum %
difference (estimated using NHD+) between any two components of a given triplet; ‘D Drainage area’ refers to % difference between drainage
area at flow-regulated and free-flowing fish survey pairs (calculated as [(reference ) dam) ⁄ dam] · 100) and ‘Survey distance’ is the straight-line
distance between flow-regulated and free-flowing fish survey pairs
Site Dam River
Construction
year
Dam height
(m) and type
Hypolimentic
release?
Drainage
area at dam
(km2)
A McCloud McCloud 1965 73, Hydro Yes 912
B Morrow Point Gunnison 1967 143, Hydro Yes 10276
C Ridgeway Uncompahgre 1986 101, FloodC Yes 656
D Structure 65D Kissimmee 1965 12, Lock No 7464
E Yellowtail Big Horn 1965 160, Hydro Yes 50905
F Trenton Republican 1952 44, FloodC No 17940
G Dillon Licking 1960 36, FloodC Yes 1958
H Delaware Olentangy 1948 34, FloodC No 1060
I Mohawk Walhonding 1937 28, FloodC No 3870
J Allegheny Lock
and Dam 8
Allegheny 1931 18, Lock No 22876
K Wanship Weber 1956 53, Hydro No 854
L Glen Ferris Kanawha 1901 8, Hydro No 21702
Site DMAF
Drainage area at
survey
(km2)
D Drainage
area
(km2)
Survey
distance
(km)
Flow
gauge
Fish survey
year
Triplet
distance
(km)
A 13.3 696 )24 190 11367500 (pre)
11367760 (post)
1998 20.6
B 9.7 5501 )46 56 09128000 1998 17.1
C 8.3 607 )8 97 09146200 1998 4.5
D 1.7 3614 )52 91 02273000 1998 11.3
E 0.2 40807 )20 66 06287000 2001 4.9
F 6.1 5155 )71 89 06828000 (pre)
06829500 (post)
1995 42.0
G 1.2 1200 )39 58 03147500 1994 4.5
H 3.4 1058 )0.3 27 03225500 1999 8.5
I 0.1 976 )75 22 03138500 1994 3.3
J 0.0 10866 )53 66 03036500 1997 9.5
K 18.4 863 1 62 10130500 2001 16.1
L 0.0 17343 )20 24 03193000 1997 1.8
Fish assemblages respond to altered flow regimes 55
� 2012 Blackwell Publishing Ltd, Freshwater Biology, 58, 50–62
predictions. Dams reduced flow variability across sites
and altered seasonality and predictability of flows (as
evidenced by reduced flow predictability and increased
flow constancy). Consistent with this pattern, fish
assemblages downstream of dams generally had lower
representation of opportunistic strategists and higher
McCloud RiverMcCloud Dam (A)
Big Horn RiverYellowtail Dam (E)
Weber RiverWanship Dam (K) Gunnison River
Morrow Point Dam (B)
Uncompahgre RiverRidgeway Dam (C)
Republican RiverTrenton Dam (F)
Olentangy RiverDelaware Dam (H)
Walhonding RiverMohawk Dam (I)
Licking RiverDillon Dam (G)
Kanawha RiverGlen Ferris Dam (L)
Kissimmee RiverStructure 65D (D)
Allegheny RiverAllegheny Lock and Dam 8 (J)
HydropowerFlood controlLock
Big Horn River, Yellowtail Dam (E)
U.S. Bureau of Reclamation
Uncompahgre River, Ridgeway Dam (C)
U.S. Bureau of Reclamation
Allegheny River, Allegheny Lock and Dam 8 (J)
U.S. Army Corps of Engineers
Hypolim. release (black fill)Surface release (grey fill)
Fig. 1 Study sites (n = 12) coded by dam function. Flood control sites (n = 5) are shown as triangles, hydropower sites (n = 5) are shown as
circles and locks (n = 2) are shown as squares. Black symbols represent sites with hypolimentic releases. Specific sites are coded by letters, and
dam names and rivers are as follows: A: McCloud Dam, McCloud River, CA; B: Morrow Point Dam, Gunnison River, CO; C: Ridgeway Dam,
Uncompahgre River, CO (pictured lower left); D: Structure 65D, Kissimmee River, FL; E: Yellowtail Dam, Big Horn River, MT (pictured lower
middle); F: Trenton Dam, Republican River, NE; G: Dillon Dam, Licking River, OH; H: Delaware Dam, Olentangy River, OH; I: Mohawk Dam,
Walhonding River, OH; J: Allegheny Lock and Dam 8, Allegheny River, PA (picture lower right); K: Wanship Dam, Weber River, UT; L: Glen
Ferris Dam, Kanawha River, WV.
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representation of equilibrium strategists than their free-
flowing counterparts. Life history theory (Winemiller &
Rose, 1992; Winemiller, 2005) and empirical evidence
(stream reaches: Mims & Olden, 2012; catchments: Tede-
sco et al., 2008) from free-flowing rivers suggest that
reduced flow variability and increased flow constancy
will favour equilibrium strategists that are well suited to
environments characterised by low disturbance.
Although the correlation between flow alteration and
life history representation below dams was predicted
robustly by life history theory, isolating and identifying
mechanistic relationships between individual flow met-
rics and individual life histories proved more difficult.
The positive relationship between equilibrium strategists
and flow predictability is in agreement with life history
theory; however, because flow predictability is largely
reduced by dams in our data set, increased flow predict-
ability is not a likely driver for elevated representation of
equilibrium strategists below dams. Life history theory
predicts that increased variability and reduced predict-
ability ⁄constancy should favour opportunistic species;
instead, we found a positive relationship between oppor-
tunistic strategists and flow predictability (BFI) and
constancy (ConstPred). Our inability to identify mecha-
nistic relationships predicted by life history theory might
be resolved with a larger data set allowing for analysis
within regions or by dam operation type, or may point to
alternative drivers of lower opportunistic and higher
equilibrium representation below dams.
The negative correlation between streamflow variabil-
ity (AnnCV) and % non-native species is consistent
with increased invasion success of non-native species as
streamflow variability is reduced. By changing the dis-
turbance regime in rivers, dams can select against
native species well adapted to a historical regime but
poorly equipped for a new one (Bunn & Arthington,
2002). Meador & Carlisle (in press) report an association
between decreased streamflow variability and a loss of
native species, particularly fluvial specialists, at roughly
half of 97 locations in the eastern United States. Similar
declines in fluvial specialist species have been reported
for the Guadalupe and San Marcos Rivers in Texas (Perkin
& Bonner, 2011) and for the White River in Arkansas
(Quinn & Kwak, 2003) following impoundment. A new
flow regime creates new niche opportunities, and
although natural flow variability can result in a range of
life history strategies represented among native taxa
(Freeman et al., 2001), not all life history niche space is
occupied in all assemblages (Olden et al., 2006). Phyloge-
netic constraints operating at regional scales and ecolog-
ical ‘filters’ acting at local scales restrict available life
histories in a given assemblage (Southwood, 1977; Jack-
son, Peres-Neto & Olden, 2001). Dominant life history
strategies of North American freshwater fishes indeed
vary regionally and are associated with historical large-
scale climatic selection pressures (Mims et al., 2010). Dams
can create different thermal and flow regimes that
suddenly provide ecological niches to which few native
species are adapted. Non-native species equipped for new
flow and thermal regimes are particularly well poised to
establish downstream of dams. In one example, species
tending towards the equilibrium life history endpoint
strategy are notably rare from native fish assemblages of
the Colorado River Basin (U.S.A.), historically character-
ised by flashy, highly variable flows. However, as flow
Opportunis�c Periodic Equilibrium
Variability Predictability Seasonality
AnnCV HPC FlowP BFI ConstPred HPD
* *
* * * *
Flow regime
Life histories
(333.3)(802.5, 560.8)(a)
(b)
Fig. 2 Box plots of per cent difference between free-flowing reference
sites and flow-regulated rivers of (a) six flow metrics and (b) three
major life history strategies. Open circles indicate outliers; values of
large outliers are noted in parentheses (a). Variables for which paired
t-test results were significantly different from 0 (P < 0.05) are marked
with an asterisk (*).
Fish assemblages respond to altered flow regimes 57
� 2012 Blackwell Publishing Ltd, Freshwater Biology, 58, 50–62
alteration has led to more predictable, less variable flows,
many established non-native fishes such as rainbow trout
(Oncorhynchus mykiss) and channel catfish (Ictalurus punct-
atus) represent historically absent equilibrium life history
strategists (Olden et al., 2006).
Although flow regime alteration is often credited as the
primary factor leading to changes in downstream fish
assemblages (Carlisle et al., 2011), other factors may play a
role in the selection of certain life histories by dams. For
example, our results identify hypolimnetic release, pre-
dominantly from hydroelectric facilities releasing cold
water, as a likely driver of increased equilibrium strategists
downstream of dams. Like flow, water temperature plays a
critical role in metabolic rates, physiology and life history
traits of freshwater species and helps determine rates of
important ecological processes such as nutrient cycling and
B
C
A
DL
HK
G
I
J
E F
B
C
A
D
L
HK
GI
JE
F
Base flow Index
Annual CV
Hig
h pu
lse
dura
tion
Hig
h pu
lse
coun
t
(a) (b)
Opportunistic strategists (%)
Equi
libri
um s
trat
egis
ts (%
)
Fig. 3 Directional differences between (a) free-flowing and flow-regulated rivers for per cent opportunistic and equilibrium life history strat-
egies and (b) a principal components ordination summarising variation among rivers according to the six major flow metrics. Dam types are
coded by line type where solid lines indicate hydropower, dashed lines indicate flood control, and dotted lines indicate locks. Sites are labelled
at the base of each arrow, and labels correspond to Fig. 1.
Table 2 Multiple linear regression models quantifying relationships between flow alteration and fish assemblage structure. The best models
(evidence ratios <3) for each response type (three life histories and proportional representation of non-native species) are shown. AnnCV,
annual coefficient of variation; BFI, base flow index. DAICc is the difference between the top performing model (minimum AICc) and each
individual model AICc. The Akaike weight (wi) is calculated as the ratio of each model’s likelihood (relative strength of evidence for the model)
to the sum of all the other model likelihoods for each response type. The evidence ratio is calculated by dividing the wi of each model by the wi of
the top model
Response Model K Multiple R2 AICc DAICc Likelihood wi Evidence ratio
Opportunistic BFI (+) 3 0.321 98.9 0.0 1.000 0.582 1.0
ConstPred (+) 3 0.215 100.6 1.7 0.418 0.244 2.4
Periodic YrsAltered (+) 3 0.584 104.4 0.0 1.000 0.869 1.0
Equilibrium FlowP (+) 3 0.349 97.6 0.0 1.000 0.484 1.0
HypoRels (+) 3 0.290 98.6 1.0 0.598 0.289 1.7
HypoRels (+), FlowP (+) 4 0.474 99.8 2.1 0.343 0.166 2.9
Non-native species AnnCV ()), YrsAltered ()) 4 0.662 132.9 0.0 1.000 0.642 1.0
AnnCV ()) 3 0.402 135.0 2.1 0.343 0.220 2.9
58 M. C. Mims and J. D. Olden
� 2012 Blackwell Publishing Ltd, Freshwater Biology, 58, 50–62
productivity (Caissie, 2006). Fluctuations in cold water
resulting from hydropeaking operations are often associ-
ated with reductions in river productivity (reviewed in
Cushman, 1985), and our study supports predictions that
equilibrium life history strategies of optimising juvenile
survivorship by investing resources into fewer offspring
are favoured in resource-limited environments (McCann,
1998). In some cases, flow and thermal events are so tightly
coupled that only a synergistic change in both is sufficient to
illicit fish responses such as spawning, migration and
foraging (reviewed by Olden & Naiman, 2010). Cooler
temperatures below dams are often desirable for establish-
ment of coldwater (often non-native) salmonid and trout
fisheries popular with recreational fishermen, but these
cooler temperatures are detrimental to native species that
require warmer temperatures to survive and ⁄or reproduce
(Olden & Naiman, 2010). With conditions favouring non-
native species and potentially disadvantaging native spe-
cies, it is not surprising that increases in equilibrium
strategists were positively correlated to sites with hypo-
limnetic releases.
We identified dam age as another non-flow driver of life
history differences between free-flowing and flow-
regulated rivers. Dam age was positively associated with
the proportional representation of periodic strategists in
flow-regulated regimes. This at first seems counterintui-
tive given that dams (i) fragment river ecosystems and
often block movement of periodic strategists (Reidy
Liermann et al., 2012) and (ii) dampen predictable, sea-
sonal fluctuations in flow that are important in the
survival and success of many periodic strategists that
often migrate at times of large flow events (Bunn &
Arthington, 2002). However, we identified three reasons
why we may see this pattern. First, we show that,
although dams do generally dampen variability and
increase constancy of flows, seasonal changes vary
between sites and do not show a clear pattern of
alteration. It is possible that these changes act upon
periodic strategists in different ways and thus illicit
varying responses across sites. Second, the ecological
effects of dams vary with time since construction. For
example, water chemistry downstream of dams will
change as organic matter collects and decomposes in the
reservoir, and geomorphological changes to the stream
channel also manifest slowly over time (Ligon, Dietrich &
Trush, 1995). The biotic response to dams may also fall
along a temporal gradient depending on attributes such as
species generation time. Quinn & Kwak (2003) found that
fish assemblages sampled immediately post-impound-
ment on the White River, Arkansas, showed only limited
change and retained many of the native species observed
prior to impoundment. However, sampling 30-year post-
impoundment revealed that many fluvial specialists
adapted to fast-flowing water were absent and that
communities downstream of the dam were dominated
by non-native salmonid species and only a few native
species. Our observation of a positive relationship
between dam age and long-lived periodic strategists
may simply be a proportional response to the decrease
in short-lived opportunistic species. Periodic strategists
Flow alteration index
Dam operation
% Non-nativesEquilibriumPeriodicOpportunistic(a) (b) (c) (d)
Fig. 4 Pairwise per cent differences of (a) opportunistic, (b) periodic and (c) equilibrium proportional life history strategies and (d) % non-
native species versus the Flow Alteration Index. Symbols indicate dam type, and symbol fill indicates release type.
Fish assemblages respond to altered flow regimes 59
� 2012 Blackwell Publishing Ltd, Freshwater Biology, 58, 50–62
may show longer persistence simply due to differential
longevity. Re-analysing species presence ⁄absence data
from Quinn & Kwak’s (2003) study and using life history
data (described in this study), we found that equilibrium
strategists proportionally increased over time (R2 = 0.97),
opportunistic strategists decreased (R2 = 0.72) and peri-
odic strategists showed no strong trend (decreasing
immediately post-impoundment and then increasing
30 years post-impoundment) (R2 = 0.33). This lends sup-
port to this mechanism.
The third possible explanation for the positive relation-
ship between dam age and periodic strategists is that this
relationship is not mechanistic but instead is explained by
regional biogeography. The oldest dams in our data set
are generally located in the eastern or midwestern United
States, and the younger dams are in the western United
States. The presence of the periodic life history in native
fish assemblages increases from east to west across the
United States (Mims et al., 2010), such that fish assem-
blages in the western United States simply have greater
potential for change than assemblages in the eastern
United States. Lastly, dam age was also identified as a
significant predictor of % non-native species with higher
% non-native species downstream of dams associated
with younger dams. This may also be a spurious regional
association as non-native fish species constitute a greater
proportion of fish assemblages in western United States
(Rahel, 2000).
Relationships between flow and life history strategies do
appear to transcend regions (Mims & Olden, 2012); how-
ever, characterisation of biotic responses by region may
provide greater utility to dam managers attempting to set
ecological flow standards (Poff et al., 2010). Our sample size
prevents a rigorous examination of biotic impacts of dams
within-region and within-operation types, and this may
prevent us from detecting biotic relationships that are
indeed present (Magilligan & Nislow, 2005). Despite the
wide availability of dam, gauge and fish survey data, we
were only able to identify 12 sites throughout the United
States that met our strict criteria. Close to 100 candidate
triplets were identified throughout the country, but closer
inspection of flow records from these gauges revealed
many years or even decades of missing flow data. Magil-
ligan & Nislow (2005) reported similar problems when
conducting an analysis of hydrologic changes by dams
throughout the United States, and this issue highlights the
need for continued efforts at hydrologic classification of
flow regimes for data-poor streams (Olden, Kennard &
Pusey, 2012) and predicting altered flow conditions at
ungauged rivers (Eng et al., in press). Furthermore, the
continuation and creation of regional and national biomon-
itoring programmes in data-poor regions as well as the
development of information systems that increase access to
local, state and federal databases are recommended. Sur-
veys and monitoring programmes specifically designed to
understand the roles of flow regime and flow alteration will
help avoid potential biases of monitoring data not designed
for that purpose.
Our findings demonstrate that life history composition
of freshwater fish assemblages that are built over millen-
nia upon particular habitat templates are significantly
altered downstream of dams in the order of a few
decades. That we detected this result using a conservative
presence ⁄absence approach applied to a relatively small
sample size holds promise for the utility of a life history,
traits-based approach to understanding how dams alter
downstream fish communities. Further elucidation of
mechanistic links may require modelling of flow regimes
and biotic communities to inform environmental flow
standards.
Acknowledgments
We thank Alan Herlihy for providing the fish occurrence
data, LeRoy Poff and Zach Shattuck for their contributions
to the trait database and Dave Lawrence for his assistance
with the fish database. Trevor Branch and two anony-
mous reviewers provided valuable comments that im-
proved the manuscript. Funding for MCM was provided
by a University of Washington Top Scholar Graduate
Fellowship, a National Science Foundation Graduate
Research Fellowship (Grant No. DGE-0718124) and by
the John N. Cobb Scholarship in Fisheries and the
H. Mason Keeler Endowment for Excellence through
University of Washington’s School of Aquatic and Fishery
Sciences. JDO acknowledges funding support from the
U.S. Environmental Protection Agency Science To
Achieve Results (STAR) Program (Grant No. 833834).
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