P R IMA R Y R E S E A R CH A R T I C L E

Patterns and drivers of fish extirpations in rivers of theAmerican Southwest and Southeast

John S. Kominoski1 | Albert Ruh�ı2,3,4 | Megan M. Hagler5,6 | Kelly Petersen6 | John

L. Sabo2 | Tushar Sinha7,8 | Arumugam Sankarasubramanian8 | Julian D. Olden9

1Department of Biological Sciences, Florida

International University, Miami, FL, USA

2School of Life Sciences and Julie Ann

Wrigley Global Institute of Sustainability,

Arizona State University, Tempe, AZ, USA

3National Socio-Environmental Synthesis

Center (SESYNC), University of Maryland,

Annapolis, MD, USA

4Department of Environmental Science,

Policy, and Management, University of

California, Berkeley, CA, USA

5Sponsored Research, Lewis & Clark

College, Portland, OR, USA

6Odum School of Ecology, University of

Georgia, Athens, GA, USA

7Department of Environmental Engineering,

Texas A&M University – Kingsville,

Kingsville, TX, USA

8Department of Civil, Construction, and

Environmental Engineering, North Carolina

State University, Raleigh, NC, USA

9School of Aquatic and Fishery Sciences,

University of Washington, Seattle, WA,

USA

Correspondence

John S. Kominoski, Department of Biological

Sciences, Florida International University,

Miami, FL, USA.

Email: jkominos@fiu.edu

Funding information

National Science Foundation, Grant/Award

Number: CBET 1204368, 1204478,

1318140, DBI-1052875

Abstract

Effective conservation of freshwater biodiversity requires spatially explicit investi-

gations of how dams and hydroclimatic alterations among climate regions may

interact to drive species to extinction. We investigated how dams and hydrocli-

matic alterations interact with species ecological and life history traits to

influence past extirpation probabilities of native freshwater fishes in the Upper

and Lower Colorado River (CR), Alabama-Coosa-Tallapoosa (ACT), and

Apalachicola-Chattahoochee-Flint (ACF) basins. Using long-term discharge data for

continuously gaged streams and rivers, we quantified streamflow anomalies (i.e.,

departure “expected” streamflow) at the sub-basin scale over the past half-

century. Next, we related extirpation probabilities of native fishes in both regions

to streamflow anomalies, river basin characteristics, species traits, and non-native

species richness using binomial logistic regression. Sub-basin extirpations in the

Southwest (n = 95 Upper CR, n = 130 Lower CR) were highest in lowland

mainstem rivers impacted by large dams and in desert springs. Dampened flow

seasonality, increased longevity (i.e., delayed reproduction), and decreased fish

egg sizes (i.e., lower parental care) were related to elevated fish extirpation prob-

ability in the Southwest. Sub-basin extirpations in the Southeast (ACT n = 46,

ACF n = 22) were most prevalent in upland rivers, with flow dependency, greater

age and length at maturity, isolation by dams, and greater distance upstream.

Our results confirm that dams are an overriding driver of native fish species

losses, irrespective of basin-wide differences in native or non-native species rich-

ness. Dams and hydrologic alterations interact with species traits to influence

community disassembly, and very high extirpation risks in the Southeast are due

to interactions between high dam density and species restricted ranges. Given

global surges in dam building and retrofitting, increased extirpation risks should

be expected unless management strategies that balance flow regulation with eco-

logical outcomes are widely implemented.

K E YWORD S

biodiversity loss, dams, flow regime, global change, imperiled species

Received: 13 May 2017 | Revised: 2 October 2017 | Accepted: 6 October 2017

DOI: 10.1111/gcb.13940

Glob Change Biol. 2018;24:1175–1185. wileyonlinelibrary.com/journal/gcb © 2017 John Wiley & Sons Ltd | 1175

1 | INTRODUCTION

Climate-induced changes in freshwater environments interact with

hydrologic alterations by dams to affect the persistence of aquatic

life (V€or€osmarty et al., 2010). Worldwide presence of dams has dra-

matically impacted riverine flow regimes (McManamay, Orth, & Doll-

off, 2012; Poff, Olden, Merritt, & Pepin, 2007), fundamentally

altering physical habitat and putting at risk numerous threatened and

endangered fish species (Dudgeon et al., 2006; Freeman, Irwin, Burk-

head, Freeman, & Bart, 2005; Jelks et al., 2008; V€or€osmarty et al.,

2010). Both flow quantity and variability (i.e., the characteristic mag-

nitudes, frequencies, and timings of seasonal high and low flows) are

critical for supporting ecological integrity in rivers (Poff et al., 1997).

However, the habitats of regulated rivers are often disconnected

both laterally and longitudinally, and many of the flow regime fea-

tures that shaped morphological, behavioral, and life history adapta-

tions of biota, are dampened or lost through complex interactions

between hydroclimatic changes and dams (Bunn & Arthington, 2002;

Olden, 2016; Rolls, Leigh, & Sheldon, 2012).

Conservation efforts in flow-regulated rivers have attempted to

balance water needs for both humans and threatened plant and ani-

mal species (Arthington, 2012; Olden et al., 2014). Achieving this

goal is challenging because over-allocation of freshwater resources

continues to drive water scarcity, threatening both water security

and freshwater biodiversity (Dudgeon et al., 2006; V€or€osmarty et al.,

2010). In the American Southwest, surface and groundwater

resources are increasingly used by humans, often at the expense of

native species (Sabo et al., 2010). Human demands for fresh water,

coupled with climate-driven increases in regional water scarcity (Sea-

ger et al., 2007, 2013), will further alter both extreme low- and

high-flow events, threatening native fish communities and favoring

invasion by non-native species (Jaeger, Olden, & Pelland, 2014; Ruh�ı,

Olden, & Sabo, 2016). Similarly, high dam densities in the American

Southeast have restricted the ranges of native fishes, leading to

reductions in population size and geographic range of imperiled

fauna (Freeman et al., 2005; Sabo et al., 2010).

Mounting evidence suggests that environmental change is the

cause of biologic communities being disassembled (i.e., altered)

according to spatially and temporally heterogeneous rates of species

losses (Zavaleta et al., 2009). Changes in species composition, rather

than systematic reductions in species richness, appear more common

(Dornelas et al., 2014), and regions with high biodiversity may

support the persistence of threatened species (Weeks, Gregory, &

Naeem, 2016). Traits-based approaches have proven powerful for

understanding species-specific reductions in native and increases in

non-native species ranges (Olden, Poff, & Bestgen, 2006), and

responses to changing riverine conditions, including alterations in

flow regimes (Mims & Olden, 2013) and land use practices (Moore &

Olden, 2017). This information, coupled with spatially explicit

quantification of flow and hydroclimatic alteration in different cli-

mate regions, is needed to predict impending extinctions and better

conserve threatened species in regulated river networks.

In the American Southwest, surface and groundwater resources

are increasingly used by humans at the expense of supporting native

freshwater species and the ecosystems on which they depend (Sabo

et al., 2010). Here, we quantified multi-decadal hydrologic variation

throughout river basins of the American Southwest (low native spe-

cies richness) and Southeast regions (high native species richness) to

test whether hydroclimate and river regulation by dams are the dom-

inant drivers of native fish community change. We accomplished this

by estimating fish extirpation probabilities for all sub-basins in

response to extrinsic factors (flow variation, basin characteristics)

and intrinsic traits of native species (Figure 1). Dam operations gen-

erally homogenize flow regimes (Poff et al., 2007; but see McMana-

may et al., 2012); therefore, we predicted species traits would

explain fish responses to flow regime alteration (Lytle & Poff, 2004;

Olden et al., 2006).

2 | MATERIALS AND METHODS

Our methodological approach was as follows: (i) We first character-

ized flow regimes in the US Southwest (Upper and Lower Colorado

river basin, CR) and Southeast (Alabama-Coosa-Tallapoosa, ACT;

Apalachicola-Chattahoochee-Flint, ACF) river basins (Figure 2), using

spectral methods to analyze long-term discharge time series; (ii) We

computed fragmentation (i.e., dam-related) metrics for each sub-

basin; (iii) We compared fish taxa lists at different time horizons, to

determine extirpation status of each species within each sub-basin;

and (iv) We assembled a fish species traits database for all the spe-

cies that were present (or had been extirpated) from the study area,

to understand biologic correlates of extirpation. Finally (v), binomial

logistic regression models combining all of the above data (i–iv)

allowed identification of the flow regime characteristics, sub-basin

characteristics, and species trait characteristics, which increase or

decrease fish extirpation probability in each basin.

2.1 | Hydrologic alterations and historical dischargevariance

We quantified effects of altered hydrology from dams and climate

change on streamflow anomalies within sub-basins (U.S. Geological

Survey [USGS] Hydrologic Unit Code 8 [HUC8]) over the selected

four major river basins, using daily discharge data from 1948 to

2012 from gages with virgin flows (i.e., Hydro-Climatic Data Net-

work [HCDN] basins) and controlled flows (non-HCDN basins) from

the U.S. Geological Survey (USGS; www.usgs.gov). HCDN basins are

characterized by streamflow records that have limited/no anthro-

pogenic influences such as upstream reservoirs and groundwater

pumping and have been specifically identified for hydroclimatic anal-

yses (Slack, Lumb, & Landwehr, 1993; Vogel & Sankarasubramanian,

2005). Gages were selected if the maximum number of missing

observations was ≤0.1% of the total observations in a given year

and ≤1% of the total observations over the time period 1948–2012.

1176 | KOMINOSKI ET AL.

A total of 79 gages met these criteria for the Upper (n = 58 sub-

basins) and Lower CR (n = 65 sub-basins), 14 gages for the ACF

(n = 12 sub-basins), and 6 gages for the ACT (n = 14 sub-basins). For

sub-basins lacking a gage, we selected the nearest downstream gage

to represent discharge within that sub-basin, and mean discharge

was used for sub-basins (i.e., ACF) with multiple gages. Daily

F IGURE 1 Conceptual model relating extrinsic (habitat, discharge) and intrinsic (species distribution and traits) factors as predictors andtools to assess extirpation probability of freshwater riverine fish species. Covariates associated with distribution (historical fish speciespresence/absence), hydrology (historical discharge daily time series, using Discrete Fast Fourier Transform [DFFT]), and basin characteristics(using Geographic Information Systems [GIS]) influence extirpation (local extinction) patterns among species

F IGURE 2 Map of the study river basins in the Southwest (Upper and Lower Colorado River) and Southeast U.S. (Alabama-Coosa-Tallapoosa River basin, left; Apalachicola-Chattahoochee-Flint River basin, right)

KOMINOSKI ET AL. | 1177

discharge (measured as liters per second from USGS data) was

estimated for each sub-basin based on data from the nearest

downstream gage. The Discrete Fast Fourier Transform (DFFT)

allowed parsing out seasonal from interannual variation in discharge,

and resulting departures from “expected” streamflow or streamflow

anomalies (after Sabo & Post, 2008), to obtain metrics of interest

(described below). The DFFT routine was performed on mean daily

discharge data at the selected gages, using the discharge package

(https://sourceforge.net/projects/discharge/) in R (R Development

Core Team, 2015). After running DFFT, we first extracted signal-to-

noise ratios (hereafter SNR), a ratio between seasonal and interannual

variation in daily discharge (with both elements being measured as a

root mean squared amplitude, delivering a unitless ratio expressed on

a decibel scale). SNRs are ecologically meaningful because they repre-

sent a measure of the relation between predictable, seasonal flow

patterns (i.e., those that have driven organismal adaptations) relative

to stochastic flow variability (i.e., ecological disturbances) (Sabo &

Post, 2008). Second, we estimated “catastrophic” flow variation

based on the distribution of positive (high-flow) and negative (low-

flow) residuals (after Sabo & Post, 2008). Extreme low (rlf) and high

streamflow intensities (rhf) reflect the standard deviation of residual

discharge events, and thus quantify how common are extreme resid-

ual flows compared to small deviations from the seasonal trend. See

Supporting Information for all streamflow covariates from each basin

(Table S1), which includes additional covariates which we did not

relate to extinction probabilities (see below).

2.2 | River basin characteristics

To understand the effects of fragmentation by dams on fish extirpa-

tion, we computed dam-related metrics at the sub-basin scale. The

United States has a rich history of dam construction, with subse-

quent effects on riverine hydrologic regimes (Graf, 1999). We

focused on rivers in the Upper and Lower CR, ACT, and ACF basins

to test for effects of altered discharge on extirpation probability

among diverse fish communities. A total of 53 large dams exist in

the CR (Upper n = 32, Lower n = 21), 13 in the ACT, and 7 in the

ACF. For each sub-basin in the CR, ACT, and ACF river basins, we

determined the presence/absence of dams, the distance (km) from

the river mouth, and river km impounded by dams using ArcGIS

spatial data layers in ARCMAP (version 10.2) Esri, Redlands, CA, USA.

See Table S1 for a complete database of streamflow alterations and

basin characteristics from individual HUC8 sub-basins for (CR),

(ACT), and (ACF) basins.

2.3 | Fish species traits

To understand the biologic correlates of native extinction risk, a trait

database was developed for all fish species (native and nonnative)

known to occur (either in the past or in the present) in the study

area. This included a total of 18 species in the Upper CR, 37 species

in the Lower CR, 130 species in the ACF and 201 species in the

ACT. Ecological traits associated with macrohabitat preference, flow

dependence, reproductive strategy, longevity, and maximum body

length were derived from multiple sources (Boschung & Mayden,

2004; Goldstein & Meador, 2004; Mims, Olden, Shattuck, & Poff,

2010; Page & Burr, 1991) (see Table S2 for the full trait database).

The subset of traits included in the subsequent analyses were as fol-

lows: fluvial dependence (reliance on flowing waters for completing

life cycle, e.g., flow required for feeding or reproduction [classified

as yes or no]), longevity (maximum potential lifespan [years]), length

at maturation (cm), age at maturation (years), fecundity (total number

of eggs or offspring per breeding season), egg size (mean diameter

of mature [fully yolked] ovarian oocytes [mm]), and caudal fin aspect

ratio (A = h2/s, h = height of the caudal fin; s = surface area of fin)

as a measure of swimming ability. We focused on these life history

traits based on previous studies that assessed the importance of

geographic range on vulnerability of native fishes to flow alteration

(Olden et al., 2006; Rolls & Sternberg, 2012).

2.4 | Fish extirpation status

Imperilment status of native fishes was determined from Jelks et al.

(2008), and extirpation status was estimated from historical obser-

vations, databases (NatureServe, Aquatic GAP, Georgia Museum of

Natural History), and expert opinion. Building on a previous effort

in the ACT (Freeman et al., 2005), we expanded assessments of

individual species imperilment and extirpation status to all sub-

basins in the ACT and ACF. A species was considered extirpated if

it was not found after repeated surveys for a period of at least

20 years (Freeman et al., 2005). For the CR, detailed pre-1980 fish

surveys were lacking, so we determined historical (pre-1980) ranges

based on data from NatureServe and present-day (post-1980)

ranges from a large compilation of databases that ensured compre-

hensive coverage of the entire basin (Strecker, Olden, Whittier, &

Paukert, 2011; Moore & Olden, 2017; J. Olden, unpublished data).

Historical species lists were used as the taxonomic basis for com-

paring present-day occurrences (if a species is historically absent,

extirpation probability cannot be quantified). In addition, we quanti-

fied species richness of non-native fishes within each sub-basin as

an additional covariate for models of native species extirpation (see

below).

2.5 | Data analysis

2.5.1 | Covariate selection and extirpationprobabilities

To discern to what extent differences in flow regimes were due to

climate vs. flow regulation, we compared the magnitude of stream-

flow anomalies from HCDN and non-HCDN gages within each basin

(CR, ACT, and ACF) using two sample t-tests and Welch’s test for

unequal variance. Due to lack of spatial representativeness through-

out entire river basins, we pooled streamflow anomalies from

HCDN and non-HCDN basins across sub-basins within each river

basin.

1178 | KOMINOSKI ET AL.

We combined data on flow regime characteristics, sub-basin

characteristics, and species trait characteristics, to understand the

drivers of native fish extirpation probability. To this end, we first

tested for multicollinearity among covariates using the variance

inflation factor (vifcor function and usdm package in R) (Naimi, et al.,

2014). Covariates with high collinearity (>.9) were removed (see

Table S2 for all covariates), obtaining the following subset of

covariates: extreme low- and high-flow intensities, SNR (streamflow

anomalies); distance (km) upriver, km impounded, dam isolated

(sub-basin characteristics); flow dependence, longevity, length and

age at maturity, fecundity, egg size, aspect ratio (species traits); and

nonnative species richness within each sub-basin.

We then ran binomial logistic regression models using extirpation

probability of each native freshwater fish within a sub-basin as a

response, and all covariates plus species identity as explanatory vari-

ables. Covariates (n = 14) were treated as fixed effects. Covariates

were standardized to z-score to scale measurements and aid inter-

pretation among continuous predictors (Gelman & Hill, 2007). Model

selection was based in all possible subsets, and was determined

using the bestglm package in R with the information criterion set to

cross-validation across various model selection criteria types

(McLeod & Xu, 2010). We calculated the percentage (%) difference

in odds by subtracting 1 from the odds ratio and multiplying by 100,

where the odds ratio is the exponent of the regression coefficient.

We calculated % difference in odds of extirpation within each sub-

basin for every 1-unit increase in a given quantitative covariate (or

presence of a binary covariate). A different model selection proce-

dure was run for each basin (CR, ACT, ACF), thus obtaining basin-

specific drivers of native fish extirpation.

3 | RESULTS

3.1 | Hydrologic alterations and historical dischargevariance

Climate vs. human controls on streamflow anomalies were signifi-

cantly different in Southwest but not Southeast rivers. Specifically,

climate drivers increased high-flow anomalies and decreased stream-

flow seasonality in the CR but not in the ACT or ACF (Fig. S1). Spa-

tial patterns in long-term flow anomalies (extreme low- and high-

flow intensities from daily discharge measured as liters per second)

varied within and among sub-basins of Southwest and Southeast riv-

ers. Differences in extreme low- and high-flow intensities were 3–4

times greater in the CR (Figure 3a,b) than either the ACT or ACF

(Figure 4a,b). The greatest high-flow intensities were estimated in

lowland basins of the Lower CR (Figure 3b), which are directly influ-

enced by seasonal monsoonal storms. Extreme low- and high-flow

intensities in the Southeast were 2 times greater in Piedmont and

Coastal Plain than upland rivers of both the ACT and ACF (Fig-

ure 4a,b). The Upper CR sub-basins were characterized by high SNRs

relative to Lower CR sub-basins; these differences are explained in

part by higher contributions of seasonal snowmelt to daily discharge

in the Upper CR (Figure 4c).

3.2 | Trait correlates of fish extirpation

A total of 37 native species was recorded in the Lower CR and 18 in

the Upper CR (Figure 5a). Sub-basin species richness was more hetero-

geneous in the Lower CR basin than the Upper CR basin, with generally

higher richness within a given sub-basin for the Upper CR. In the CR,

combinations of species-watershed extirpations (n = 95 Upper CR,

n = 130 Lower CR) have been highest among large-bodied, migratory,

and endemic fishes (e.g., cutthroat trout, bonytail chub, humpback

chub) in lowland mainstem rivers directly impacted by large dams, as

well as a number of spring-dwelling fishes (Figure 5a). Extirpation prob-

abilities were greatest for endemic, fluvial-dependent fishes in main-

stem rivers of the Southwest and endemic headwater fishes restricted

by dams in the Southeast (Table 1). Flow SNR, longevity and egg size

were highly correlated with the probability of extirpation in the CR.

Declines in SNR (decreasing seasonality in streamflow) as well as smal-

ler egg size (denoting low parental care to offspring) were related to

increased extirpation probability by 36% and 24%, respectively. Longer

lifespan increased extirpation probability by 65% (Table 1). Despite

high non-native species richness in many sub-basins throughout the

CR (Table S1), this covariate was not a predictor of past native species

extirpation risk at the spatial grain examined here.

A total of 201 native species was recorded in the ACT and 130 in

the ACF (Figure 5b). Sub-basin species richness was higher and more

heterogeneous in the ACT than the ACF. Combinations of species-

watershed extirpations in the ACT (n = 46) have occurred largely in

upland sub-basins involving small-bodied endemic species (e.g., dar-

ters), and migratory and large-bodied fishes (e.g., sturgeon, shad, pike,

eel), and combinations of species-watershed extirpations in the ACF

(n = 22) have occurred in upland sub-basins for migratory and large-

bodies fishes (e.g., sturgeon, shad, eel; Figure 5b). In the ACT, dis-

tance from river mouth (km upstream), flow dependence, age and

maximum length at maturity, fecundity, longevity, and egg size were

all important covariates explaining extirpations (Table 1). Distance

from river mouth increased extirpation probability by 101%, and

dependence on flow had greatly increased extinction risk (Table 1).

Higher age and maximum length at maturity both greatly increased

probability of being extirpated, whereas lower fecundity, lower long-

evity, and smaller egg size were associated with higher extirpation risk

(Table 1). In the ACF, distance from river mouth, dam isolation, age at

maturity, longevity, and fecundity were covariates explaining extirpa-

tions (Table 1). Fish that were isolated upstream by dams, had higher

age at maturity, or higher fecundity were predicted to have high extir-

pation probabilities, whereas long-lived fishes had a 100% decreased

probability of being extirpated (Table 1). Non-native species richness

was low among sub-basins of the ACT and ACF (Table S1) and was

not a predictor of past native species extirpation risk in either basin.

4 | DISCUSSION

Understanding how species traits interact with changes in environ-

mental conditions to mediate community alteration can help

KOMINOSKI ET AL. | 1179

(a) (b) (c)

F IGURE 3 Streamflow anomalies measured as extreme (a) high and (b) low flow (c hf, c lf) intensities, and (c) signal-to-noise ratio from1948 to 2012 throughout the Upper and Lower Colorado River. SNR reflects the relation between predictable (seasonal) flows relative tostochastic flows. Blue triangles denote location of major dams and date of completion of each dam. Discharge was measured as liters persecond from USGS data [Colour figure can be viewed at wileyonlinelibrary.com]

(a) (b) (c)

F IGURE 4 Streamflow anomalies measured as extreme (a) high and (b) low flow (c hf, c lf) intensities, and (c) signal-to-noise ratio from1948 to 2012 throughout the Alabama-Coosa-Tallapoosa River and Apalachicola-Chattahoochee-Flint basins. SNR reflects the relationbetween predictable (seasonal) flows relative to stochastic flows. Blue triangles denote location of major dams and date of completion of eachdam. Discharge was measured as liters per second from USGS data [Colour figure can be viewed at wileyonlinelibrary.com]

1180 | KOMINOSKI ET AL.

(a) (b)

F IGURE 5 Species richness of native freshwater fishes within individual sub-basins (U.S. Geological Survey [USGS] Hydrologic Unit Code 8[HUC8]) of the (a) Upper and Lower Colorado River (CR), and (b) Alabama-Coosa-Tallapoosa and Apalachicola Chattahoochee-Flint Riverbasins. Numeric values within HUC8s refer to the number of species extirpated from historical to present-day (see Materials and methods fordetails) [Colour figure can be viewed at wileyonlinelibrary.com]

TABLE 1 Binomial logistic regression models selected for all-possible subsets of covariates (n = 14), treated as fixed effects, on extirpationprobability of native freshwater fishes within individual sub-basins (U.S. Geological Survey [USGS] Hydrologic Unit Code 8 [HUC8]) Upper andLower Colorado River (CR), Alabama-Coosa-Tallapoosa (ACT), and Apalachicola-Chattahoochee-Flint (ACF) basins. Model covariates included:species traits (flow dependent, length and age at maturity, aspect ratio, longevity, fecundity, egg size), streamflow anomalies (extreme low andhigh flows, signal-to-noise ratio [SNR]), sub-basin characteristics [distance (km) upriver, km impounded, dam isolated], and sub-basin nonnativespecies richness. SNR reflects the relation between predictable (seasonal) flows relative to stochastic flows. Percentage (%) difference in oddsis calculated as the (odds ratio �1) 9 100, where the odds ratio is the exponent of the regression coefficient (estimate). Quantitativecovariates were centered using z-scores. Binary covariates were not centered. Model selection was determined using the bestglm package in R

Basin Model covariates Estimate SE z value Pr(>|z|) Odds ratio % Difference

ACF Intercept �6.55 0.67 �9.71 2.61E-22

Age at maturity 6.41 0.92 6.99 2.85E-12 607.89 6E04

Dam isolated 3.35 0.85 3.94 8.02E-05 28.50 2,750

Fecundity 2.26 0.33 6.74 1.54E-11 9.58 858

Distance (km) from mouth 0.85 0.23 3.74 1.80E-04 2.34 134

Longevity �6.82 0.97 �7.03 2.04E-12 0.001 �100

ACT Intercept �252.83 707.64 �0.36 7.21E-01

Flow dependent 16.11 705.18 0.02 9.82E-01 9.9E05 9.9E07

Length at maturity 9.25 1.90 4.78 1.11E-06 1E04 1E06

Age at maturity 3.98 1.23 3.23 1.24E-03 53.52 5,252

Distance (km) from mouth 0.70 0.19 3.71 2.07E-04 2.01 101

Egg size �0.60 0.23 �2.56 1.04E-02 0.55 �45

Longevity �15.84 2.70 �5.86 4.54E-09 0 �100

Fecundity �909.02 232.47 �3.91 9.22E-05 0 �100

CR Intercept �0.88 0.09 �9.88 5.20E-23

Longevity 0.50 0.10 4.78 1.76E-06 1.65 65

Egg size �0.28 0.10 �2.68 7.33E-03 0.76 �24

Flow seasonality �0.45 0.09 �5.01 5.51E-07 0.64 �36

KOMINOSKI ET AL. | 1181

quantifying current and impending extirpation risk (Moore & Olden,

2017; Zavaleta et al., 2009). Trait-based approaches in stream ecol-

ogy allow for a mechanistic understanding of species distribution

and abundance by considering environmental constraints or “filters”

imposed across the range of hierarchical spatio-temporal scales

(Chessman, 2013; Poff, 1997; Rolls & Sternberg, 2015). Thus, they

may allow for a better understanding of the relationships between

environmental change and threats to native species persistence. For

example, increases in stream temperatures select for smaller body

size among fishes (Daufresne, Lengfellner, & Sommer, 2009), and

both small- and large-bodied species can have high extinction risk in

ecosystems with degraded habitat (Olden, Hogan, & Vander Zanden,

2007). In addition, determining species sensitivity vs. adaptation to

changing environmental conditions needs to be considered in the

context of evolutionary life history. Although we found more

extreme streamflow events in selected basins in the Southwest than

in the Southeast, such findings may simply reflect differences in the

natural flow regime between these regions rather than extreme

flows that could generate ecological disturbances (sensu Poff, 1992).

Species traits interact with environmental changes to mediate

community disassembly among contrasting hydroclimatic regions

undergoing strong hydrologic alterations (both climate and human-

modified). We found that effects of dams and climate change on

decreasing streamflow variance and anomalies were greater in

Southwest than Southeast rivers. We measured higher magnitude

changes in streamflow anomalies, a distinct shift in the seasonality

of discharge, and stronger effects of dams on reducing discharge

variance in the Southwest than the Southeast (Figures 3 and 4).

However, presence of dams disproportionately affected extirpation

risk of species isolated in upland streams of the ACF and of flow-

dependent species in the ACT (Table 1). Extirpations have been rela-

tively evenly distributed across sub-basins in the Southwest (Fig-

ure 5a). By contrast, extirpation risk in the Southeast was greater in

upland basins than in lowland basins of the Upper ACT and ACF,

where dams impede migratory species and restrict the ranges of

endemic headwater fishes (Figure 5b). Despite higher magnitudes in

hydrologic alteration in the Southwest, the density and distribution

of dams in Southeast rivers, especially in the ACT (Figure 4a–c),

increase extirpation probabilities even in these diverse fish assem-

blages (Figure 5b). In both regions (Southwest and Southeast), spe-

cies life histories and geographic ranges, and hydrologic alterations

explained extirpation probabilities. Our findings are critical, as we

need to understand impending extinctions among river basins world-

wide that have many threatened native species (Arthington, Dulvy,

Gladstone, & Winfield, 2016; Jelks et al., 2008; V€or€osmarty et al.,

2010). Further understanding of how extirpation risk among native

fish species may vary among regions with different levels of biodi-

versity (e.g., Weeks et al., 2016) is needed to enhance global species

conservation.

Variation in streamflow is a critical driver of native species per-

sistence even in highly invaded regions (Rolls et al., 2012; Ruh�ı,

Holmes, Rinne, & Sabo, 2015; Ruh�ı et al., 2016). Our multi-basin

analysis of historical vs. present-day occurrences indicates that

extreme low- and high-flow events as well as direct effects of dams

on seasonal variability in streamflow, likely contribute to localized

fish extinctions. A recent analysis of native and nonnative species

abundances from multiple Southwest rivers found that quasi-extinc-

tion risk, defined as the probability of 80% decline within 10 years,

is higher for native than non-native fishes and is intensified by low-

flow anomalous discharge (Ruh�ı et al., 2016). Trends of declining dis-

charge throughout the Southwest suggest that native species will

continue to be negatively impacted by projected increases in

drought, whereas non-native fishes are predicted to replace col-

lapsed native fish communities (Ruh�ı et al., 2016). Water with-

drawals and reduced streamflows will continue to threaten the

persistence of southwestern fishes into the future (Gido et al., 2010;

Jaeger et al., 2014).

Climate-driven changes in discharge may continue to be stronger

drivers of species vulnerability in Southwest than Southeast rivers.

Although many freshwater fishes listed as imperiled are from South-

east rivers (Jelks et al., 2008), populations of these listed species

have remained persistently static, implicating range restriction effects

from upland dams as opposed to continual declines in habitat (Free-

man et al., 2005). Overall decreases in—and shifts in the timing of—

precipitation, as well as increases in mean temperatures, are fore-

casted for the American Southwest (Seager et al., 2013). In the

American Southeast, on the other hand, most climate models indi-

cate increases in precipitation, with simultaneous evaporation

increases resulting in reduced runoff (Seager, Tzanova, & Nakamura,

2009). Droughts are typically shorter in duration with greater vari-

ability in occurrence in the Southeast than in the Southwest, which

increases projection uncertainty for drought frequency and severity

in the Southeast compared to the Southwest (Seager et al., 2009).

Both regions have experienced unprecedented population growth,

and the potential for changing energy demands linked to water pose

one of the greatest water resources challenges moving forward

(McDonald et al., 2012).

Recent decades have witnessed heightened attention on

advancing the science underpinning environmental flow manage-

ment for river conservation (Arthington, 2012; Poff et al., 2010).

Achieving ecological integrity of flowing waters, including flow and

temperature requirements of many native freshwater species, is a

tremendous challenge; yet, evidence from across the world

demonstrates its potential to conserve native fishes (Olden et al.,

2014). The use of hydroclimatic models to understand past hydro-

logical changes is a critical first step, followed by predictive mod-

els that forecast when and where alterations are likely to occur

and compromise ecological integrity. Modeling efforts need to

quantify environmental uncertainty across multiple temporal and

spatial scales to dynamically adjust conservation priorities. Under-

standing where extirpation probabilities are high and can be attrib-

uted to specific abiotic and biotic variables plays an important

role in setting conservation priorities. Furthermore, understanding

where uncertainties in both predictor and estimator variables are

high may guide monitoring and restoration efforts (Wenger et al.,

2013).

1182 | KOMINOSKI ET AL.

It is clear that natural flow variability and sufficient water avail-

ability are essential to maintaining ecological health and native spe-

cies persistence in streams and rivers (Ruh�ı et al., 2015, 2016; Sabo

et al., 2010). To advance effectiveness of restoring regulated flow

regimes, we must move beyond the study of isolated extreme flow

events to integrated time series of hydroclimatic changes and their

effects on native and nonnative communities and ecosystem func-

tions (Gillespie, Desmet, Kay, Tillotson, & Brown, 2014; Olden et al.,

2014). Protecting environmental needs for flow variability and water

security need to be prioritized through adaptive management

approaches that include (i) regional environmental flow targets (Poff

et al., 2009), (ii) setting human water-use ceilings that are sufficiently

constrained to meet environmental needs across variable (high and

low) flow conditions (Bunn & Arthington, 2002), and (iii) holistic

hydropower planning that uses models and technologies to minimize

biological impairment (McDonald et al., 2012; Winemiller et al.,

2016). The former strategy is often prescribed in basins that have

imperiled species present but is rarely implemented. Furthermore,

increases in human water-use efficiency (reduction in consumptive

use) are rarely made to allow for meeting environmental needs,

rather those efficiencies are made for expanding human water use

(Richter, 2010).

Adequate environmental flows in a river basin indicate that all

water allocations and dam regulations are being managed in a sus-

tainable manner, such that the net outcome of human and environ-

mental water needs is attained (Richter, 2010). To enhance

ecological integrity, flow regimes need to be designed to meet speci-

fic ecological outcomes that more effectively inform water manage-

ment decisions using existing infrastructure (Acreman et al., 2014;

Poff et al., 2016). We must shift prioritization from restoring refer-

ence conditions (e.g., natural flow regime) or discrete large-scale flow

experiments (Olden et al., 2014) to prescribe flows that increase

native species resilience and help mitigate extirpations with fore-

casted climate-driven changes in streamflow. Dams will continue to

represent barriers for species dispersal, but if seasonal flow patterns

and large-scale flow releases are designed to enhance hydromorpho-

logic and ecological connectivity, novel flow regimes could achieve

sustainable ecological outcomes.

ACKNOWLEDGEMENTS

We thank Byron Freeman, Mary Freeman, and Seth Wenger for

helpful suggestions and comments on previous draft manuscripts.

Data were provided by the University of Georgia River Basin Center,

Georgia Museum of Natural History, NatureServe, and USGS Aquatic

GAP Program. Funding was provided by the National Science Foun-

dation (CBET 1204368, 1204478, and 1318140) Water Sustainabil-

ity & Climate grant awarded to Kominoski, Arumugam, Sabo, and

Kunkel. Albert Ruh�ı was also supported by the National Socio-Envir-

onmental Synthesis Center (SESYNC), under funding received from

the National Science Foundation DBI-1052875. Julian Olden gra-

ciously recognizes the H. Mason Keeler Endowed Professorship

(School of Aquatic and Fishery Sciences, University of Washington)

for support.

ORCID

John S. Kominoski http://orcid.org/0000-0002-0978-3326

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