SYMPOSIUM

Turbidity and Salinity Affect Feeding Performance andPhysiological Stress in the Endangered Delta SmeltMatthias Hasenbeindagger Lisa M KomoroskeDagger Richard E Connon Juergen Geistdagger andNann A Fangue1Dagger

Department of Anatomy Physiology and Cell Biology School of Veterinary Medicine University of California

Davis CA 95616 USA daggerAquatic Systems Biology Unit Department of Ecology and Ecosystem Management

Technische Universitat Munchen Muhlenweg 22 D-85354 Freising Germany DaggerDepartment of Wildlife

Fish amp Conservation Biology University of California Davis CA 95616 USA

The first two authors contributed equally to this work

From the symposium lsquolsquoPhysiological Responses to Simultaneous Shifts in Multiple Environmental Stressors Relevance in

a Changing Worldrsquorsquo presented at the annual meeting of the Society for Integrative and Comparative Biology January 3ndash7

2013 at San Francisco California

1E-mail nafangueucdavisedu

Synopsis Coastal estuaries are among the most heavily impacted ecosystems worldwide with many keystone fauna

critically endangered The delta smelt (Hypomesus transpacificus) is an endangered pelagic fish species endemic to the

SacramentondashSan Joaquin Estuary in northern California and is considered as an indicator species for ecosystem health

This ecosystem is characterized by tidal and seasonal gradients in water parameters (eg salinity temperature and

turbidity) but is also subject to altered water-flow regimes due to water extraction In this study we evaluated the

effects of turbidity and salinity on feeding performance and the stress response of delta smelt because both of these

parameters are influenced by water flows through the San Francisco Bay Delta (SFBD) and are known to be of critical

importance to the completion of the delta smeltrsquos life cycle Juvenile delta smelt were exposed to a matrix of turbidities

and salinities ranging from 5 to 250 nephelometric turbidity units (NTUs) and 02 to 15 parts per thousand (ppt)

respectively for 2 h Best statistical models using Akaikersquos Information Criterion supported that increasing turbidities

resulted in reduced feeding rates especially at 250 NTU In contrast best explanatory models for gene transcription of

sodiumndashpotassium-ATPase (NaK-ATPase)mdashan indicator of osmoregulatory stress hypothalamic pro-opiomelanocor-

tinmdasha precursor protein to adrenocorticotropic hormone (expressed in response to biological stress) and whole-body

cortisol were affected by salinity alone Only transcription of glutathione-S-transferase a phase II detoxification enzyme

that protects cells against reactive oxygen species was affected by both salinity and turbidity Taken together these data

suggest that turbidity is an important determinant of feeding whereas salinity is an important abiotic factor influencing

the cellular stress response in delta smelt Our data support habitat association studies that have shown greater delta smelt

abundances in the low-salinity zone (05ndash60 ppt) of San Francisco Bay a zone that is also understood to have optimal

turbidities By determining the responses of juvenile delta smelt to key abiotic factors we hope to aid resource managers

in making informed decisions in support of delta smelt conservation

Introduction

Aquatic systems worldwide are changing in profound

ways and as the human population continues to

grow the impacts of anthropogenic stressors are

likely to increase (Halpern et al 2008) Stressors

such as habitat loss over-exploitation pollution

invasive species and climatic change have

consequences for speciesrsquo extinctions loss of biodi-

versity and overall ecosystem function (Dudgeon

et al 2006 Geist 2011) Since contemporary aquatic

species are being challenged with suites of anthropo-

genic stressors unlike those which have dominated

their evolutionary histories and because natural sys-

tems are almost always simultaneously subject to

Integrative and Comparative BiologyIntegrative and Comparative Biology volume 53 number 4 pp 620ndash634

doi101093icbict082 Society for Integrative and Comparative Biology

Advanced Access publication August 5 2013

The Author 2013 Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology All rights reserved

For permissions please email journalspermissionsoupcom

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multiple and possibly interacting stressors there is a

need to more comprehensively account for this in

physiological and ecological studies as well as in con-

servation planning (Crain et al 2008) Coastal estu-

aries are among the most degraded aquatic habitats

worldwide and the management of estuaries and

their resources are among our greatest conservation

challenges The San Francisco Bay Delta (SFBD) is

one of the most highly anthropogenically-impacted

estuaries in the United States (Cloern and Jassby

2012) and its decline is well documented and not

in dispute (Healey et al 2008 Lund et al 2010)

Current water-management practices in the SFBD

are challenging because resource managers are

charged with achieving co-equal goals the provision

of ecosystem services (largely the provision of a re-

liable water supply to Californians) and the mainte-

nance of ecosystem health and function The SFBD is

subject to marine influences from the Pacific Ocean

mixing with seasonally fluctuating freshwater input

from the Sacramento and San Joaquin Rivers

(Cloern and Jassby 2012) providing unique gradients

in water parameters (eg salinity and temperature)

and providing the sediment and energy needed to

shape the physical habitat However diversion of

water for anthropogenic demands has vastly reduced

the amount of freshwater inflow into the SFBD by

approximately 40 in the average year (Lund et al

2010) and waters of higher salinity now move fur-

ther upstream during the fall (Cloern and Jassby

2012) Simultaneously a rise in sea level is expected

to force saline waters further inland and upstream

(Smithson 2002)

The SFBD is substantially different from the his-

torical Delta and the effects of this change on native

species are widespread (Moyle and Bennett 2008

NRC 2012) Three pelagic fishes of the upper SFBD

estuary (delta smelt Hypomensus transpacificus long-

fin smelt Spirinchus thaleichthys and age-0 striped

bass Morone saxatilis) have declined sharply since

the early 2000s and their populations have remained

low over the past decade The underlying causes of

the pelagic organism decline are vigorously debated

and considerable efforts are underway to evaluate

complex multistressor interactions that may be con-

tributing to speciesrsquo declines such as entrainment

(ie fish drawn through intakes) at water pumping

stations loss of critical habitat competition with and

predation from non-native species limited food due

to changes in plankton communities altered abiotic

conditions contaminants and poor water quality

(Bryant and Souza 2004 Hieb 2005 Feyrer et al

2007 Sommer et al 2007 Brown et al 2009

Winder and Jassby 2011 Brooks et al 2012)

The delta smelt is of particular interest as it is an

endangered pelagic fish species endemic to the

SacramentondashSan Joaquin Estuary in northern

California it acts as an indicator of ecosystem

health in its habitat range and has been listed as

endangered under both the USA Federal and

Californian State Endangered Species Acts Delta

smelt are an annual estuarine species able to with-

stand moderate fluctuations in salinity (Swanson

et al 2000) however their distribution in the

SFBD has been correlated with the low-salinity

zone (LSZ) centered at 2 parts per thousand (ppt)

The position of the 2-ppt-salinity isohaline (also re-

ferred to as lsquolsquoX2rsquorsquo) is defined as the distance in kilo-

meters from the Golden Gate Bridge to its location

in the estuary (Jassby et al 1995 Kimmerer 2002)

Although adult delta smelt have been found to tol-

erate short-term exposures to salinities up to approx-

imately 19 ppt (Swanson et al 2000) typically few

are observed at salinities 44 ppt suggesting reduced

performance or aversion to environments of higher

salinity (Kimmerer 2002 Bennett 2005) If so then

the impact of climatic change pushing the LSZ fur-

ther upstream could result in the reduction of opti-

mal habitat for this species in the SFBD

Additionally adult delta smelt annually migrate up-

stream in the late fallndashearly winter to spawn where

their larvae develop in freshwater habitat until they

reach post-larval stages and migrate downstream in

the spring toward the LSZ (Bennett 2005) The X2 is

seasonally variable and dependent on flow regimes

which can be manipulated it is closely managed to

maintain habitats understood to be optimal for the

delta smelt

Turbidity in the SFBD can also vary greatly by

location and season and is dependent on a range

of factors such as tidal flux wind rainfall and

water flow algal growth ambient light levels and

depth Turbidity levels in excess of 100 NTU occur

primarily during winter storms or during summer

when irrigation return-flows contribute substantially

to sediment loads (Dahlgren et al 2004) Turbidity

can impact fishes indirectly by influencing primary

productivity and thus food-web dynamics but tur-

bidity levels can also affect some fish species directly

For example it has been shown that larval delta

smelt will not feed in clear water (Baskerville-

Bridges et al 2004) and it has been postulated that

turbidity provides the visual contrast needed for

delta smelt to see their prey However highly

turbid waters may also reduce delta smeltsrsquo feeding

success likely by reducing their ability to visually

identify the prey however this is greatly dependent

on light intensity (Baskerville-Bridges et al 2004)

Multistressor effects on delta smelt 621

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The introduction of non-native species (eg the in-

vasion of the suspension-feeding overbite clam

Corbula amurensis believed to be largely responsible

for large reductions in plankton populations) has

also impacted turbidity in many regions of the

SFBD (Nichols et al 1986 1990 Carlton et al

1990 Jassby et al 2002) Given the likely sensitivity

of delta smelt both to salinity and turbidity levels it

is important to understand how they impact delta

smeltsrsquo performance survival and overall distribu-

tion in the SFBD

In this study we evaluated the effects of turbidity

and salinity both on the feeding performance and on

the stress response of delta smelt because both of

these physicochemical parameters are influenced by

water flows through the SFBD and these factors are

known to be of critical importance to the completion

of the delta smeltrsquos life cycle (Bennett 2005) We

hypothesize that the response of delta smelt to phys-

icochemical parameters can be determined by com-

bining mechanistic investigations (ie measuring the

stress response using gene transcription and cortisol)

with organismal and ecological measures of perfor-

mance (ie feeding ability) under environmentally

relevant combinations of environmental stressors

Our aim was to determine whether the habitat asso-

ciations of delta smelt recorded in the field are a

consequence of physicochemical parameters such as

turbidity and salinity rather than other constraints

such as interspecific competition or predatorndashprey

relationships We highlight how physiological and

behavioral studies that consider multiple and poten-

tially interacting stressors are not only mechanisti-

cally revealing but also can aid resource managers

in making informed decisions in support of fish

conservation

Materials and methods

Study animals

Juvenile delta smelt (120 days post hatch dph) were

raised at the Fish Conservation and Culture

Laboratory (FCCL) UC Davis in Byron CA follow-

ing specific aquaculture methods for this delicate

species (Baskerville-Bridges et al 2005 Lindberg

et al 2013) Fish were spawned in April 2012 and

reared at 154ndash1648C under a natural photoperiod

and at low light intensities (1ndash20 lux Lindberg et al

2013) Fish were fed four times daily to satiation

with Artemia franciscana (Argent Chemical

Laboratories WA USA) and acclimation conditions

in the holding tanks prior to experimentation were

as follows dissolved oxygen (DO)frac14 899 mg O2 l1

(SEfrac14 021) pHfrac14 764 (SEfrac14 01) salinityfrac14 02 ppt

(SEfrac14 006) and turbidityfrac14 456 NTU (SEfrac14 033)

All handling care and experimental procedures

used were reviewed and approved by the UC Davis

Institutional Animal Care and Use Committee

(IACUC Protocol 16591)

Fish exposures

Two experimental tests are presented in this study

one to assess the feeding ability of delta smelt in

response to exposures to salinity and turbidity and

the second to assess the physiological stress response

measured via changes in gene transcription and

assays of whole-body cortisol associated with expo-

sures to salinity and turbidity In both experimental

tests juvenile delta smelt (120 dph) were exposed in

95 l black high-density polyethylene buckets (US

Plastic Corp) for a period of 2 h to an experimental

matrix of turbidities and salinities Preliminary tests

in juvenile delta smelt held under culture conditions

revealed a complete clearance time of 18 h from fore-

gut through the intestine Fish were therefore starved

for 16 h prior to initiation of the test and an addi-

tional 2 h during acclimation to the test buckets to

ensure their guts were empty Delta smelt are com-

monly caught in the field in turbid waters up to 50

NTU and in the LSZ (05ndash6 ppt) Broadly delta smelt

habitat extends from the freshwater reaches of the

Delta seaward to 19 ppt and includes temperatures

of 258C or lower Distribution of delta smelt at a

finer scale (ie in relation to life stage tidal seasonal

and diurnal movements turbidity salinity tempera-

ture biotic variables the environmental conditions

conducive to feeding and how these variables inter-

act) are poorly understood (Bennett 2005 Feyrer

et al 2007 Nobriga et al 2008) and the mechanisms

responsible for complex distribution patterns are lar-

gely unknown In a preliminary range-finding study

we found elevated mortaility after 24 h at turbidities

4120 NTU and salinities of 12 ppt We therefore

chose turbidity and salinity treatments that were

physiologically challenging but nonlethal over at

least 3 h and encompass values typical and maximal

for the habitats of juvenile delta smelt

Turbidity levels were adjusted using

Nannochloropsis algae (Nanno 3600mdashHigh yield

grow out feed Reed Mariculture Inc USA) whereas

salinity was adjusted using Instant Ocean sea salt

(Spectrum Brand Inc USA) Handling control sam-

ples contained culture water without additional algae

or sea salt Air stones were used in all exposure ves-

sels to maintain oxygen concentrations near satura-

tion Temperature (8C) was constantly monitored

during exposures using iBcod temperature loggers

622 M Hasenbein et al

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(Alpha Mach Inc Canada) DO (mg l1) salinity

(ppt) turbidity (NTU) and light intensity (lux)

were measured at the beginning of a test using a

YSI 55 DO meter (YSI Inc) a YSI 63 handheld

meter (YSI Inc Xylem Brand for conductance and

salinity) a Hach 2100q portable turbidity meter

(Hach company) and a Extech instruments easy

view 30 light meter (FLIR commercial Systems)

Our experimental design consisted of a 6 5

matrix of turbidities and salinities respectively The

nominal exposures were 0 12 25 50 120 and 250

NTU and 0 2 6 12 and 15 ppt Average measured

salinities for each group were 02 ppt (SEfrac14 00) 21

ppt (SEfrac14 01) 60 ppt (SEfrac14 00) 120 ppt

(SEfrac14 00) and 150 ppt (SEfrac14 00) Measured

average turbidities were 413 NTU (SEfrac14 032) 126

NTU (SEfrac14 03) 259 NTU (SEfrac14 04) 509 NTU

(SEfrac14 15) 122 NTU (SEfrac14 2) and 248 NTU

(SEfrac14 2) Light intensity pH and temperature re-

mained constant throughout each test at 104 lux

(SEfrac14 034) 815 (SEfrac14 003) and 1618C (SEfrac14 01)

respectively DO in all test buckets remained near

saturation and ranged from 855 to 924 mg O2 l1

Feeding tests were conducted in triplicate each

containing 10 juveniles per bucket (total 30 fish)

After the 2-h exposure fish were fed with freshly

hatched live A franciscana in abundance dispensed

in 100 ml solution at a density approximating 600

Artemia per ml (593 98) based on current culture

methodology (Baskerville-Bridges et al 2004 2005)

and resulting in a final density of 7 Artemia ml1

Fish were allowed to feed for a period of 25 min

(determined through preliminary tests as the opti-

mal time for ingesting Artemia to the foregut only

and prior to digestion data not shown) after which

time they were immediately euthanized and stored

in 75 ethanol for analysis of gut contents Fish

were euthanized with an overdose of MS-222

(Tricaine methanesulfonate Finquel) at a dosage

of 50 mg l1 buffered to a neutral pH with sodium

bicarbonate (NaHCO3) Guts were later dissected

and the number of Artemia ingested was counted

under a dissecting microscope Termination of the

test and sampling of each bucket was accomplished

in 520 s The assessments of physiological stress

were conducted similarly using 10 juvenile delta

smelt per 95ndashl bucket fish were not fed for the

duration of the test Following the 2-h exposure

period fish were euthanized as described earlier

but whole fish were then immediately snap frozen

in liquid nitrogen and stored at 808C for assays

of gene transcription and measurement of whole-

body cortisol

RNA isolation and quantitative polymerase chain

reaction assessments

Total RNA was extracted from whole-body homog-

enates of individual fish using TRIzol Reagent

(Ambion RNA Life Technologies Corporation) ac-

cording to manufacturerrsquos guidelines RNA concen-

trations were determined using a NanoDrop ND1000

Spectrophotometer (NanoDrop Technologies Inc

Wilmington DE USA) total RNA 260280 and

260230 ratios ranged between 186ndash215 and 175ndash

205 respectively Total RNA integrity was verified

through electrophoresis on a 1 (wtvol) agarose

gel Between three and five fish per treatment were

assessed by quantitative polymerase chain reaction

(qPCR) Complementary DNA (cDNA) was synthe-

sized using 1 mg total RNA per sample Primers and

probes for qPCR analyses (Table 1) were designed

using Roche Universal Probe Library Assay Design

Center (httpswwwroche-applied-sciencecom)

Primers were obtained from Eurofins MWG

Operon (httpwwweurofinsdnacom) and

TaqMan probes were supplied by Roche or Applied

Biosystems SDS 221 software (Applied Biosystems)

was used to quantify transcription and data were

analyzed using the Log2Ct method (Livak and

Schmittgen 2001) relative to handling control sam-

ples Differences in transcription were calculated rel-

ative to Beta-Actin (b-actin) identified as a suitable

reference gene for this assessment using GeNorm

(Vandesompele et al 2002) Genes were selected to

determine alterations in osmotic (NaK-ATPase) ox-

idative (GST) and general (HSP70) stress as well as

to integrate parameters involved in corticosteroid

stress pro-opiomelanocortin (POMC) and regulation

(GR2 and MR1) and gluconeogenesis (GLUT2) in

delta smelt (Table 1)

Measures of whole-body cortisol

Cortisol extraction was performed on five fish per

treatment and the method was modified from stud-

ies carried out on zebrafish (Vijayan and Leatherland

1990 Alsop and Vijayan 2009 Cachat et al 2010)

Briefly samples were thawed and homogenized in 1

ml ice-cold 1 phosphate-buffered saline (PBS

buffer sodium potassium combo 008 mol l1 diso-

dium hydrogen phosphate 136 mol l1 sodium chlo-

ride mol l1 potassium chloride 0017 mol l1

potassium phosphate monobasic) using a hand-held

homogenizer The homogenate was then split in

equal amounts (500 ml) into two different tubes

one aliquot was transferred into a pyrex glass tube

for the extraction of cortisol and the second aliquot

into a 15 ml eppendorf tube for determination of

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protein content The cortisol extraction was per-

formed three times for maximum yield using

25 mL diethyl ether (VWR International LLC

USA) per sample Glass tubes were capped and vor-

texed for 1 min Subequently samples were centri-

fuged for 15 min at 5000 rpm 3214 relative

centrifugal forces (RCF) at 48C The supernatant

was retained and transferred to a new 20 ml glass

vial Samples were left overnight in the fume hood

for complete evaporation of diehtyl ether before

resuspension in 1 mL 1 PBS and stored at 48Covernight The cortisol assay (Cortisol Salivary

Immunoassay Salimetrics LLC) was then performed

according to the manufacturerrsquos instructions and

cortisol levels (mg d l1) were calculated with a

four-parameter sigmoid standard curve (minus

curve fit) Cortisol levels were normalized to the pro-

tein content of each sample Protein concentrations

in the homogenate were determined using the

bicinchoninic acid method (Pierce Thermo Fisher

Scientific Inc) Protein samples were diluted

20-fold with 1 PBS Buffer to match kitrsquos serum

albumin standards and assay was performed accord-

ing to manufacturerrsquos instruction Protein levels

(mg m l1) were calculated using a linear standard

curve Cortisol levels were normalized to total pro-

tein and expressed as cortisol concentration (pg cor-

tisol mg protein1)

Statistical analysis

Statistical analyses were performed using R version

2152 (R-CoreTeam 2012) Specific R packages used

are listed with corresponding analyses For data on

feeding the glmmADMB package (Skaug et al 2012)

was used to construct generalized mixed models to

evaluate relationships of salinity and turbidity with

number of Artemia consumed (Bolker et al 2009)

Models employed a negative binomial distribution

with a zero-inflation parameter to meet the needs

of the data Fish length (fork length in millimeters)

was included as a covariate to account for variation

in feeding response due to fish size Models were

generated for combinations of the hypothesized pre-

dictor relationships (9 total) (Table 2) and were

compared and selected using Akaikersquos Information

Criterion corrected for small sample sizes (AICc

Anderson and Burnham 2002 Burnham and

Anderson 2004) AICc is defined as

2logL(jjy)thorn 2Kthorn (2K[Kthorn 1]nK 1) where

logL(jjy) is the maximized log-likelihood of the

model parameters given the data K is the number

of estimable parameters and n is the sample size

(Burnham and Anderson 2002) The best explanatory

model was identified based on AICc difference (i

ie the difference between the AICc of model i and

the lowest AICc observed) and Akaike weight (wi

calculated as the model likelihood normalized by

the sum of all model likelihoods) Models with an

AICc difference (i ie the difference between the

AICc of model i and the lowest AICc observed)

52 were considered to be the most favored models

and wi closer to 1 indicated greater confidence in the

selection of the favored explanatory model (Burnham

and Anderson 2004) The penalty imposed by AICc

for each additional parameter in a model is

2Kthorn (2K[Kthorn 1]nK 1) such that the inclusion

of an additional parameter may result in a new

model that is i52 even if the parameter has no

Table 1 Primer and probe systems used for quantitative PCR analyses

Gene name Primer Roche probe no

Sodiumpotassium ATPase (NaK-ATPase)Forward gtcatcccaatctactgcacca

88Reverse catgatgtcgccaatcttgc

Heat shock protein 70 kDa (HSP70)Forward aagattctggagaagtgcaacga

20Reverse ccttctcagcggtctggttct

Pro-opiomelanocortin (POMC)Forward tgttcacctgtgcaggtctga

127Reverse gagaagctctcttccgtggaca

Glutathione-S-transferase (GST)Forward aatctccctggcagacattgtt

127Reverse ggccggctctcaaacacat

Glucocorticoid receptor 2 (GR2)Forward catcgtgaagcgtgaggagaa

129Reverse tgcatggagtccagtagtttgg

Mineralocorticoid Receptor 1 (MR1)Forward tttctacactttccgcgagtca

39Reverse tgatgatctccaccagcatctc

Glucose transporter 2 (GLUT2)Forward gccatgtcagttggcctcat

130Reverse gacatgctgacgtagctcatcc

b-ActinForward tgccacaggactccatacc

12Reverse catcggcaacgagaggtt

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additional explanatory ability (Burnham and

Anderson 2002 Arnold 2010) Therefore in the

few cases where multiple models had i52 but dif-

fered by the inclusion of an additional parameter

(K) all models are reported but the more parsimo-

nious model was selected (Arnold 2010)

Biochemical data were transformed (cubed root)

to meet assumptions of normality and analyzed with

the R stats package 2152 (R-CoreTeam 2012) For

biochemical and transcriptomic responses salinity

and turbidity were treated as categorical variables

in general linear models (GLMs Quinn and

Keough 2002) Biochemical and transcriptomic re-

sponses can reflect a large variety of response

curves such as sublethal thresholds followed by

nonmonotonic patterns of upregulation or downreg-

ulation as an organism heads toward their tolerance

limit for a given stressor Since this was the first time

biochemical and transcriptional changes have been

quantified in delta smelt in response to turbidity

and salinity this approach allowed us to focus on

a smaller set of models to evaluate the contributions

of the estimated parameters (Johnson and Omland

2004) which can then inform future studies charac-

terizing response curves in greater depth (Niehaus

et al 2012) Models were generated compared and

selected using similar methods as those described

above for each gene or biochemical marker Genes

were checked against one another for issues of col-

linearity (none were found) and GLMs were con-

structed for each gene response Model assumptions

of normality of residuals were checked graphically

and homogeneity of variances was confirmed with

FlignerndashKilleen tests (Crawley 2007) Graphics were

created in the ggplot2 package version 093

(Wickham and Chang 2012) and Sciplot 11ndash0

(Morales 2012)

Results

Feeding

The full model (Artemia SalinityNTUthorn Length)

and one including turbidity and the covariate fish

length (ArtemiaNTUthorn Length) were supported

by AICc and wi (i52 Table 2) The more parsi-

monious model (ArtemiaNTUthorn Length) was se-

lected as the best explanatory model (Arnold 2009)

however it is possible that salinity and its interac-

tions with turbidity may also influence delta smeltsrsquo

feeding (Supplementary Fig S1) The best model de-

picted a negative impact of turbidity on juvenile

smeltsrsquo feeding (Supplementary Table S1 and

Fig 1) with the number of Artemia ingested per

fish particularly reduced at high turbidites (ie 250

NTU) The covariate fish size was also present in the

supported model while larger fish consumed more

Artemia the slope of this relationship was weak but

consistent across all treatments (Fig 2 and

Supplementary Table S1)

QPCR and biochemical assessments

In contrast to our findings that turbidity impacted

feeding performance salinity was the stressor that

more consistently related to physiological stress as

measured by qPCR (Table 3 and Figs 3 and 4)

The most favored models for NaK-ATPase and

POMC included only salinity as a predictor whereas

GST was best described by an additive model includ-

ing both salinity and turbidity (GST

SalinitythornTurbidity) The MR1 Salinity model was

also within the ifrac14 2 cutoff for model selection

(ifrac14 16) however the null model was selected be-

cause it was more parsimonious and its wi was sub-

stantially above that of MR1 Salinity Interestingly

the null model was the best-fit model for all other

genes including genes involved in the general re-

sponse to stress that is HSP70 and specifically to

corticosteroid regulation (GR2) and glucose trans-

port (GLUT2) GLM tables of the selected models

for genes (other than those for which the null

model was selected) are detailed in Supplementary

Table S2

SodiumndashPotassium ATPase is a key enzyme in-

volved in ion transport during osmoregulation in

fish and is a molecular indicator of osmoregulatory

stress Transcription of NaK-ATPase increased with

Table 2 Analysis of selection of a model for delta smeltsrsquo

consumption of Artemia

Model parameters i df wi

ArtemiaNTUthorn Length 00 6 0443

Artemia salinityNTUthorn length 03 8 039

Artemia salinitythornNTUthorn length 20 7 0167

Artemia salinitythorn length 328 6 50001

Artemia 1 (null model) 697 3 50001

ArtemiaNTU 1402 5 50001

Artemia salinityNTU 1580 7 50001

Artemia salinitythornNTU 1699 6 50001

Artemia salinity 1895 5 50001

Note The best explanatory model selected is indicated in bold AICc

difference (i) is the difference between the AICc of model i and the

lowest AICc observed Akaike weight (wi) is calculated as the model

likelihood exp(i2) normalized by the sum of all model likeli-

hoods values close to one indicate greater confidence in the selec-

tion of a model All models were adjusted for zero inflation and used

a negative bionomial distribution with a log link function

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higher salinities (Supplementary Table S2 and

Fig 3b) Glutathione-S-transferase (GST) is a detox-

ification system that defends cells against reactive

oxygen species (ROS) and is also known to respond

to osmotic stress in fishes (Choi et al 2008)

Increasing salinity and turbidity affected the upregu-

lation of GST transcription (Fig 3c) Hypothalamic

POMC is a precursor protein of many hormonal

peptides including the pituitary adrenocorticotropic

hormone (ACTH) which is transcribed in response

to biological stress (Palermo et al 2012)

Transcription of POMC also increased with salinity

(Supplementary Table S2 and Fig 4a) However as

stated earlier other genes related to glucocorticoid

regulation and glucose transport (ie GR2 MR1

and GLUT2) did not exhibit the same pattern

(Fig 4bndashd)

The best explanatory model for the response of

whole-body homogenate cortisol was 3ˇCortisol

Salinity (Table 4 and Supplementary Table S3)

Lactate exhibited a similar pattern however ifrac14 1

for the more parsimonious 3ˇLactate 1(null)

model and therefore was selected as more favorable

This was the same for glucose for which the most

parsimonious supported model was 3ˇGlucose

1(null) GLM tables of the selected models for cor-

tisol are detailed in Supplementary Table S4

Discussion

Turbidity impacted juvenile delta smeltsrsquo feeding per-

formance over the 2-h exposure period Overall

there was a negative relationship between turbidity

levels and feeding performance with highest feeding

rates at low turbidity (512 NTU) relatively

0

2

4

6

0 25 50 75 100 125 150 175 200 225 250Turbidity (NTU)

log

No

Art

emia

Con

sum

ed

Fig 1 Graphic relationship between turbidity and feeding performance (number of Artemia ingested in 25 min) of juvenile delta smelt

(see Table 2 for selection of model) Line denotes best-fit linear regression with shading of 95 confidence intervals Data points are

displayed with random position jitter (x yfrac14 3 02) and opacity to portray density of overlapping individual data points The y-axis is

depicted on a log scale to reflect the log link function applied in the negative binomial model

0

100

200

300

400

500

20 30 40Length (mm)

No

Art

emia

Con

sum

ed

Fig 2 Graphic depiction of the shallow positive relationship

between the length (fork length in millimeters) of juvenile delta

smelt and number of Artemia ingested during the 25-min feeding

period as covariate in a generalized linear mixed model (see

Table 2 for specific output of model) Line denotes best-fit linear

regression with shading of 95 confidence intervals Data points

are displayed with random position jitter (x yfrac14 3 02) and

opacity to portray density of overlapping individual data points

626 M Hasenbein et al

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persistent feeding rates over a broad range of turbid-

ities (12ndash120 NTU) and a strong decline in feeding

rates at levels of 250 NTU Turbidity defined as the

distance that light penetrates the water column and

caused by individual particles such as suspended sed-

iment dissolved organic matter and phytoplankton

(Rice et al 1994) can have both positive and nega-

tive effects on fish depending on the species (Utne-

Palm 2002) For instance in bluegill (Lepomis macro-

chirus) and adult cape silverside (Atherina breviceps)

reduced feeding rates were reported at higher turbid-

ities (Gardner 1981 Hecht and Van der Lingen

1992) This is supported by our findings in which

delta smelt exhibited reduced feeding rates at 250

NTU Studies carried out by Baskerville-Bridges

et al (2004) on larval delta smelt found highest feed-

ing rates at 11 NTU and 228 lux and stressed the

significant interaction between turbidity and light in-

tensity This interaction may explain why feeding was

highest at low turbidity as the average light intensity

utilized in our test was 104 lux matching that of the

holding tanks but lower than the reported tests con-

ducted on larval delta smelt This low light intensity

may also have further impeded feeding at the highest

turbidity levels of 250 NTU It is known that increas-

ing turbidity reduces the reactive distance in fish

(Utne-Palm 2002) thereby minimizing the volume

of water that the fish can potentially search for

food (Hecht and Van der Lingen 1992) Delta

smelt are visual predators thus feeding is more

likely to occur through direct encounters with prey

under highly turbid conditions such as the tested 250

NTU A general observation while conducting this

test was that swimming activity increased at low tur-

bidity and fish were seen more often swimming near

the surface in the clear treatments This higher ac-

tivity may be due to the fish sensing the handlerrsquos

presence thus triggering escape responses and

Table 3 Analysis of selection of a model for delta smeltsrsquo

transcriptomic responses

Model parameters i Df wi

HSP70 1(null) 00 2 0766

HSP70 salinity 26 6 0207

HSP70 turbidity 73 7 0020

HSP70 salinitythorn turbidity 94 11 0007

HSP70 salinityturbidity 340 31 50001

Catalase 1(null) 00 2 0887

Catalase salinity 46 6 0090

Catalase turbidity 76 7 0020

Catalase salinitythorn turbidity 124 11 0002

Catalase salinityturbidity 324 31 50001

NathornKthorn ATPase Salinity 00 6 0890

NathornKthorn ATPase 1(null) 45 2 0093

NathornKthorn ATPase salinitythorn turbidity 81 11 0015

NathornKthorn ATPase turbidity 125 7 0002

NathornKthorn ATPase SalinityTurbidity 196 31 50001

POMC salinity 00 6 0964

POMC salinitythorn turbidity 73 11 0025

POMC 1(null) 91 2 0010

POMC salinityturbidity 130 31 0001

POMC turbidity 172 7 50001

GR 1(null) 00 2 0864

GR salinity 51 6 0067

GR turbidity 52 7 0065

GR salinitythorn turbidity 106 11 0004

GR salinityturbidity 293 31 50001

MR 1(null) 00 2 0681

MR salinity 16 6 0299

MR turbidity 78 7 0014

MR salinitythorn turbidity 95 11 0006

MR salinityturbidity 295 31 50001

Glucose transporter 1(null) 00 2 0801

Glucose transporter salinity 32 6 0161

Glucose transporter turbidity 65 7 0032

Glucose transporter salinitythorn turbidity 98 11 0006

Glucose transporter salinityturbidity 287 31 50001

SGK3 1(null) 00 2 0866

SGK3 salinity 41 6 0112

SGK3 turbidity 76 7 0020

SGK3 salinitythorn turbidity 114 11 0003

SGK3 salinityturbidity 233 31 50001

NF KB 1(null) 00 2 0724

NF KB salinity 23 6 0229

NF KB turbidity 61 7 0034

NF KB salinitythorn turbidity 81 11 0013

NF KB salinityturbidity 142 31 50001

(continued)

Table 3 Continued

Model parameters i Df wi

GST salinitythorn turbidity 00 11 0813

GST salinity 38 6 0123

GST salinityturbidity 53 31 0058

GST turbidity 104 7 0005

GST 1(null) 116 2 0002

Note Best explanatory model selected is indicated in bold AICc

difference (i) is the difference between the AICc of model i and

the lowest AICc observed Akaike weight (wi) is calculated as the

model likelihood exp(i2) normalized by the sum of all model

likelihoods values close to one indicate greater confidence in the

selection of a model

Multistressor effects on delta smelt 627

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searching behavior since turbidity is expected to

reduce stress levels in fish by providing protection

from predators (Gregory and Northcote 1993

Sirois and Dodson 2000) Our test was designed

however to function at low light intensity due to

the depth restrictions imposed by the exposure ves-

sels Low light intensity within a shallow container

may have allowed delta smelt to utilize the available

water column occupying the surface and utilizing

darker (simulating depth) zones that would not

have been available had higher light intensities been

used It is important to note that this study was

conducted using algal suspensions of

Nannochloropsis to modify turbidity This is the

same algal suspension that is used at the culture fa-

cility to rear larval delta smelt (Baskerville-Bridges

et al 2005) and there were no signs of ingested

algae in the smeltsrsquo guts in any of the treatments

Although this approach is not directly representative

of the mixed and highly variable composition of

suspended particles dissolved organic matter and

diverse phytoplankton communities present in the

SFBD our data do provide evidence for relatively

consistent feeding performance at turbidities up to

120 NTU at the light intensity assessed In nature

delta smeltsrsquo feeding performance may vary due to

variation in turbidity as well as to natural light in-

tensity Delta smelt are known to be relatively abun-

dant in the LSZ (Moyle et al 1992 Hobbs et al

2006) and wild delta smelt collected during moni-

toring efforts often are observed in association with

turbidities between 10 and 50 NTU (Feyrer et al

2007) Our data are consistent with these observa-

tions and suggest that juvenile delta smelt are capable

of consistent feeding across the range of turbidities

and salinities that are typical of their SFBD habitat

Although turbidity was the factor that significantly

impacted juvenile delta smeltsrsquo feeding performance

the gene transcription and biochemical data suggest

that salinity was the dominant factor affecting

Fig 3 Gene markers for general stress salinity and oxidative stress in delta smelt (120 dph) dependent on salinity and turbidity

variables following a 2-h acclimation period Log2-fold change in gene transcription relative to b-actin standard errors Heat Shock

Protein 70 kDa (HSP70) sodiumndashpotassium ATPase (NaK-ATPase) and glutathione-s-transferase (GST)

628 M Hasenbein et al

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osmoregulation and the generalized stress response

in juvenile delta smelt During transfer to saltwater

many fish alter gill NaK-ATPase enzyme activity fa-

cilitating ion exchange and osmoregulation (Evans

2008) An increase in gill NaK-ATPase enzyme activ-

ity is often preceded by or accompanied by in-

creases in NaK-ATPase mRNA expression and

changes in NaK-ATPase mRNA expression patterns

have been shown in many fish species following

transfer to saline conditions for example rainbow

trout (Richards et al 2003) killifish (Scott et al

2004) and Atlantic salmon (Bystriansky and

Schulte 2011) In delta smelt the transcription of

NaK-ATPase as well as GST increased in response

to increasing salinity GST is a detoxification

system that defends cells against ROS and responds

to osmotic stress in fishes (Choi et al 2008) Taken

together these data suggest that the transcription of

NaK-ATPase and GST may play a role in juvenile

delta smeltsrsquo responses to osmotic stress

Cortisol is the main corticosteroid hormone in

fish that is expressed in response to stress and

changes in the transcription profiles of osmoregula-

tory genes in fish gills in response to seawater are

Fig 4 HPI axis corticosteroid regulation stress and glucose transporter responses in delta smelt (120 dph) dependent on salinity

and turbidity variables following a 2-h acclimation period Log2-fold change in gene transcription relative to b-actin standard

errors Pro-opiomelanocortin (POMC) glucocorticoid receptor 2 (GR2) mineralocorticoid receptor 1 (MR1) and glucose transporter 2

(GLUT2)

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thought to be hormonally mediated Many studies

report elevated cortisol following transfer to seawater

(McCormick 1995 2001) and these increases can be

rapid (minutes to hours) and persistent (over days)

depending on the severity of the osmoregulatory

challenge Hypothalamic POMC is a neuroactive li-

gandndashreceptor and precursor protein to the ACTH

which is expressed in the anterior pituitary and is a

major secretagogue of cortisol That is POMC is a

major precursor to the activation of the hypotha-

lamicndashpituitaryndashinterrenal (HPI) axis the system re-

sponsible for the secretion of cortisol in teleosts

(Mommsen et al 1999 Alsop and Vijayan 2009

Schjolden et al 2009 Palermo et al 2012)

Corticosteroid receptors such as glucocorticoid and

mineralocorticoid receptors function to regulate

gene transcriptions that are implicated in responses

to stress (Alsop and Vijayan 2009 Savitz et al 2009)

Glucocorticoid receptors are induced by cortisol

while mineralocorticoid receptors mediate effects on

electrolyte and fluid balance and are known to

downregulate glucose transport systems (Korgun

et al 2011) It is interesting therefore that neither

of the measured corticosteroid receptors nor the glu-

cose transporter responded significantly to the salin-

ity treatments

In delta smelt hypothalamic POMC transcription

was induced at high levels of salinity (15 ppt) sug-

gesting greater effects on activation of the HPI axis

However while the best explanatory models indi-

cated that cortisol from whole-body homogenates

also increased at higher salinities transcription of

neither the corticosteroid receptors nor the glucose

transporter responded Vijayan and Leatherland

(1990) reported that during chronic stress plasma

cortisol in brook charr are elevated then fall back

to resting levels and that cortisol clearance levels are

dependent on corticoid receptors binding proteins

and tissue uptake of cortisol It is probable that cor-

tisol dynamics are complex and highly variable in

delta smelt which are notoriously delicate and sen-

sitive to handling stress with reported mortality rates

above 90 in field-caught adults this sensitivity has

resulted in specific collection and transport proce-

dures published for this species (Swanson et al

1996) It is known that delta smeltsrsquo tolerance to

stress is limited (Swanson et al 1996 Connon

et al 2009 2011a 2011b) which may account for

the variable results related to the cortisol pathways

determined in this study Furthermore and more

specifically assessments need to be conducted to es-

tablish cortisol levels and related genes in delta smelt

elicited by differing stressors (eg high stocking den-

sity confinement and toxicant exposure) and at

different life stages to more fully interpret the com-

plexity in the responses measured

The overall response profiles of gene transcription

measured in this study are nonmonotonic

Nonmonotonic dosendashresponse curves are not un-

common especially in complex mechanistic studies

and inflexions in transcription responses have been

postulated to represent thresholds of maximum

stress (Conolly and Lutz 2004 Heckmann et al

2008 Connon et al 2011b 2012 Vandenberg et al

2012) They have been observed following exposure

to contaminants at concentrations at which signifi-

cant mechanistic effects determined by qPCR cor-

respond with detrimental effects upon behavior such

as swimming performance (Beggel et al 2010 Fritsch

et al 2013) and they have been universally acknowl-

edged by endocrinologists (Vandenberg et al 2012

Zoeller et al 2012) Transcription of the aforemen-

tioned genes (Figs 3 and 4) also profile the same re-

sponse curve with respect to turbidity This response

curve is mostly inversed from that of the salinity

responses but also follows a nonmonotonic re-

sponse increasing with elevated turbidity at either

12 or 25 NTU and reducing at 50 and 120 NTU

with a secondary and significant upregulation at 250

NTU This increase and resulting inflexion is likely to

Table 4 Analysis of selection of a model for delta smeltsrsquo

biochemical responses

Model parameters i df wi

3ˇLactate salinity 00 6 0599

3ˇLactate 1(null) 10 2 0355

3ˇLactate salinitythorn turbidity 61 11 0029

3ˇLactate turbidity 70 7 0018

3ˇLactate salinityturbidity 217 31 50001

3ˇCortisol salinity 00 6 0754

3ˇCortisol salinitythorn turbidity 26 11 0202

3ˇCortisol 1(null) 61 2 0036

3ˇCortisol turbidity 94 7 0007

3ˇCortisol salinityturbidity 138 31 50001

3ˇGlucose 1(null) 00 2 0638

3ˇGlucose salinity 15 6 0307

3ˇGlucose turbidity 58 7 0034

3ˇGlucose salinitythorn turbidity 79 11 0012

3ˇGlucose salinityturbidity 84 31 0010

Best explanatory model selected is indicated in bold AICc difference

(i) is the difference between the AICc of model i and the lowest

AICc observed Akaike weight (wi) is calculated as the model likeli-

hood exp(i2) normalized by the sum of all model likelihoods

values close to one indicate greater confidence in the selection of a

model

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represent maximum tolerance levels beyond which

long-term detrimental effects would be observed

We hypothesized that delta smeltsrsquo physiological

performance in response to physicochemical param-

eters (ie salinity and turbidity) could be deter-

mined through measurements of feeding ability and

biochemical and molecular parameters that relate to

physiological stress Integrating both assessments

(feeding and physiological stress) overall responses

following a 2-h acclimation period indicate an opti-

mal performance at low turbidity and at a salinity

between above 0 and 6 ppt with detrimental effects

at turbidities above 120 NTU and salinities at or

above 12 ppt These results are supported by field

studies that associate delta smeltsrsquo abundance with

05ndash6 ppt (Moyle et al 1992 Kimmerer 2002

Hobbs et al 2006) and turbidities of 10 and 50

NTU (Feyrer et al 2007) Our study provides insight

into optima for juvenile delta smelt with respect to

the assessed parameters that will guide future long-

term multi-lifestage evaluations toward assessing the

fundamental niche for this species Future assess-

ments will address larval juvenile and adult life-

stages additional stressors and timescales of

exposures and consider additional light intensities

that encompass ecological and seasonal ranges to

more comprehensively assess the habitat require-

ments of delta smelt Nevertheless this study has

insofar supported past and current field assessments

of delta smeltsrsquo habitat and distribution and should

be informative to SFBD resource managers

Acknowledgments

The authors thank Dr J Lindberg and staff in par-

ticular Luke Ellison and Galen Tigan at the UC Davis

FCCL Byron CA where the experiments were con-

ducted for supplying delta smelt along with invalu-

able knowledge on delta smeltsrsquo culture and

handling They thank Dennis Cocherel Bethany

DeCourten Rebecca Davies and Simone Hasenbein

and all undergraduate student assistants Jason

Dexter Ryan Brill Michael Gurlin Jennifer

Truong and Rina McPherson for their assistance

with experiments and sample processing and Brian

Cheng for consultation about statistical analyses

They also thank three anonymous reviewers and

the journal editor for constructive and thoughtful

comments in improving this manuscript

Funding

Funding was provided by the University of California

Agricultural Experiment Station [grant number

2098-H to NAF] the United States Department

of Interior Bureau of Reclamation [contract

number R12AP20018 to REC and NAF] and

the California Delta Stewardship Council [contract

number 201015533 to REC and NAF] Partial

student funding was provided to MH by the

Bavarian Elite Programme Universitat Bayern

eVmdashScholarship for graduate students and post

graduate students and to LMK by the National

Science Foundation Graduate-12 Fellowship

Program [under DGE grant number 0841297 to

SL Williams and B Ludaescher] and the

California Sea Grant Delta Science Doctoral

Fellowship RSF-56 Communication of this work

was also supported by symposium funds from the

Society for Integrative and Comparative Biology

(DCPB DEE and DIZ) and the NSF

Supplementary Data

Supplementary Data are available at ICB online

References

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Arnold TW 2010 Uninformative parameters and model se-

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and NathornKthorn-ATPase expression and activity during fresh-

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tic and behavioral responses to sublethal

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Hypomesus transpacificus (Fam Osmeridae) BMC

Genomics 10608

Connon RE Beggel S DrsquoAbronzo LS Geist JP Pfeiff J

Loguinov AV Vulpe CD Werner I 2011a Linking molec-

ular biomarkers with higher level condition indicators to

identify effects of copper exposures on the endangered delta

smelt (Hypomesus transpacificus) Environ Toxicol Chem

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Connon RE Deanovic LA Fritsch EB DrsquoAbronzo LS

Werner I 2011b Sublethal responses to ammonia exposure

in the endangered delta smelt Hypomesus transpacificus

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chemicals in the aquatic environment Sensors 1212741ndash71

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relationships mechanistic basis kinetic modeling and im-

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Council NNR 2012 Sustainable water and environmental

management in the California Bay-Delta Washington

(DC) The National Academies Press

Crain CM Kroeker K Halpern BS 2008 Interactive and cu-

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Transparency tube provides reliable water-quality measure-

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diversity importance threats status and conservation chal-

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learned since August Krogh Homer Smith and Ancel Keys

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for three declining fish species habitat patterns and mech-

anisms in the San Francisco Estuary California USA Can J

Fish Aquat Sci 64723ndash34

Fritsch EB Connon RE Werner I Davies RE Beggel S

Feng W Pessah IN 2013 Triclosan impairs swimming be-

havior and alters expression of excitation-contraction cou-

pling proteins in fathead minnow (Pimephales promelas)

Environ Sci Technol 472008ndash17

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Gregory RS Northcote TG 1993 Surface planktonic and

benthic foraging by juvenile chinook salmon

(Oncorhynchus tshawytscha) in turbid laboratory conditions

Can J Fish Aquat Sci 50233ndash40

Halpern BS Walbridge S Selkoe KA Kappel CV Micheli F

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mal stress responses in Daphnia magna Genome Biol 9R40

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Hobbs JA Bennett WA Burton JE 2006 Assessing nursery

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salinity zone of the San Francisco estuary J Fish Biol

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Jassby AD Cloern JE Cole BE 2002 Annual primary pro-

duction patterns and mechanisms of change in a nutrient-

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Isohaline position as a habitat indicator for estuarine pop-

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Johnson JB Omland KS 2004 Model selection in ecology

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Polish Histochem Cytochem Soc 49325ndash34

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managed population of endangered delta smelt N Am J

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pression data using real-time quantitative PCR and the

2CT method Methods 25402ndash8

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ATPase and chloride cell function In Shuttleworth TJ

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McCormick SD 2001 Endocrine control of osmoregulation

in teleost fish Am Zool 41781ndash94

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Scott GR Rogers JT Richards JG Wood CM Schulte PM

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Skaug H Fournier D Nielsen A 2012 glmmADMB gener-

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scientific basis Contribution of Working Group 1 to the

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