Do Juvenile White Perch Morone americana Grow Betterin Freshwater Habitats of the Blackwater River Drainage(Chesapeake Bay, MD, USA)?

Joshua James Newhard & Joseph William Love &

John Gill

Received: 25 August 2011 /Revised: 26 January 2012 /Accepted: 30 April 2012 /Published online: 15 May 2012# Coastal and Estuarine Research Federation 2012

Abstract Increasing rates of freshwater habitat loss in theChesapeake Bay (and elsewhere) have renewed interest inthe role of freshwater in population integrity for euryhalinefishes. Freshwater habitats may be important nurseries forjuveniles of anadromous species. Using length–weightresiduals and scales, we determined if body condition andgrowth of juvenile (<120 mm total length) white perchMorone americana (a semi-anadromous species) differedbetween brackish and freshwater tributaries within theBlackwater River drainage (Chesapeake Bay Watershed,U.S.A.). We then examined how monthly variation in bodycondition varied with monthly variation in selected environ-mental factors. Body condition differed between tributaries andwas greater in freshwater (specific conductivity <0.45 mS)than brackish water when water temperature was greaterthan 9.6°C. White perch growth rates did not differ betweentributaries, except for a short time during summer or early fall.Some anadromous fishes may spawn in freshwater to promote

greater body condition, thereby ensuring a quality con-tingent of individuals for the population. With continuedloss or impairment of freshwater habitat, the availabilityof nurseries for juvenile white perch will be reduced andreduce the number of quality juveniles recruiting to the adultpopulation.

Keywords Fish growth . CART . Age . Nurseries . Climatechange

Introduction

Estuarine management strategies are often aimed at improv-ing habitat conditions for juvenile fishes because survivor-ship is generally lowest for the first year of life for fishes.Survivorship may be improved by protecting prey resour-ces, improving refugia from predators (Miranda andHubbard 1994), and ensuring favorable environmental con-ditions (Meng et al. 2000; Phelan et al. 2000). Favorableenvironmental conditions can include suitable oxygen levels(Love et al. 2005) and availability of prey (Meador andKelso 1990). Such conditions may improve growth. Notonly can faster growing juveniles consume a greater diver-sity of prey, but their large size facilitates better survivorshipand escape from predators (Houde 1987; Abrams 1991;Sogard 1992; Post and Parkinson 2001).

Environmental variables that impact fish growth include:temperature, dissolved oxygen (DO), and salinity. Warmertemperatures may promote growth, leading to preference ofsuch conditions by fishes (Hall et al. 1979). However, highwater temperatures typically occur with low DO levels. LowDOmay lead to slowed predatory behavior or foraging, whichcauses a reduction in growth (Kramer 1987; Breitburg et al.1997). If foraging or predatory behavior is inhibited then body

J. J. Newhard : J. W. LoveDepartment of Natural Sciences,University of Maryland Eastern Shore,Princess Anne, MD 21853, USA

Present Address:J. J. Newhard (*) : J. GillU.S. Fish and Wildlife Service,Maryland Fishery Resources Office,177 Admiral Cochrane Drive,Annapolis, MD 21401, USAe-mail: joshua_newhard@fws.gov

Present Address:J. W. LoveMaryland Department of Natural Resources,Division of Inland Fisheries,580 Taylor Avenue, B-2,Annapolis, MD 21401, USA

Estuaries and Coasts (2012) 35:1110–1118DOI 10.1007/s12237-012-9512-0

condition (a measure of robustness) of fishes may be lower(Love et al. 2005), resulting in decreased survivorship (Loveand Rees 2002).

Habitats that provide environmental conditions that en-hance growth and survivorship during the first year of life offishes may be called nurseries (Beck et al. 2001). Nurseriesare a significant contributor to adult age classes (Dahlgren etal. 2006) and may be identified by measuring somaticgrowth (Meng et al. 2000; Minello et al. 2003). Bodygrowth may be faster in nurseries and result in juvenilesthat reach a larger size-at-age than individuals from outsidenursery habitats (Meng et al. 2000; Necaise et al. 2005).Because environmental conditions affect growth, partition-ing variance in growth or body condition to specific envi-ronmental factors helps determine the environmental factorsthat contribute to a productive nursery habitat. The environ-mental differences among nurseries can lead to growthdifferences in juvenile fish from those nurseries, suggestingthat some nurseries are better than others (Able et al. 1999;Vinagre et al. 2008). Moreover, monthly and/or seasonalchanges can affect habitat quality and therefore nursery con-ditions as well (Paperno et al. 2000).

Nursery habitats are a challenge to describe for manyestuarine fishes. White perch (Morone americana) is acommercially important, estuarine (0–12 ppt) and semi-anadromous species of the Chesapeake Bay. Over 45 metrictons of white perch have been commercially harvested eachyear from the Chesapeake Bay since 1995 (Maryland De-partment of Natural Resources et al. 2005). Adults aregenerally harvested either during spring when they enterlow salinity water (<4.2 ppt) to spawn (Mansueti 1961;Murdy et al. 1997) or during fall (September–November).Habitat conditions of the spawning area, such as salinity,may affect growth rates of juvenile white perch (Wallace1971; Boeuf and Payan 2001). While growth rates were notcompared, Kerr and Secor (2012) reported no difference insize-at-age between brackish and freshwater contingents ofwhite perch. Nonetheless, juveniles reared in freshwaterhabitats can be an important component of adult, migratorypopulations (Kraus and Secor 2005a, b). We further exam-ined growth characteristics of juvenile white perch fromfreshwater and brackish habitats. Our work contributes to abroader understanding of watershed management for anad-romous or semi-anadromous fishes.

The objectives of our study were: (1) to compare bodycondition and growth of juvenile white perch between abrackish and a freshwater tributary within the same drain-age; and (2) to examine the relationship between monthlyvariation in body condition with monthly variation in se-lected environmental factors. With regard to objective 1, wehypothesized that body condition and growth would behighest in freshwater habitat. For objective 2, we hypothe-sized that body condition would be highest in habitats with

low specific conductivities and when water temperature,dissolved oxygen, and water visibility were high.

Materials and Methods

Study Location

The Blackwater River drainage is a sub-estuary of the Ches-apeake Bay Watershed, located on the east coast of theChesapeake Bay (Fig. 1). Over 50 % of freshwater marshhabitat of Blackwater River has converted to open waterbecause of subsidence and sea level rise, which is occurringat two to three times the global rate within the drainage(Stevenson et al. 2000). Two major waterways of the Black-water sub-estuary are: the Blackwater River and the LittleBlackwater (LB) River. The upstream habitats of the LittleBlackwater River are non-tidal and the last reaches of fresh-water for this historically freshwater wetland (Love et al.2008). Adjacent waterways, such as Buttons Creek (BC;Fig. 1), are tidally influenced and brackish. Water qualitywas characterized at two nearshore locations of LB and BCusing YSI Sondes (Model 6600) (LB2, BC2; see Fig. 1)from 23 May 2008 to 1 September 2008. Water temperature(degrees Celsius), specific conductivity (milliSiemens), andDO (percent) were measured every 15 min. Measurementswere downloaded using Ecowatch software (Version 3.18,YSI Incorporated). These data showed that BC was morebrackish than LB (Fig. 2). At BC2, specific conductivityvaried from 0 to 12 mS from May–September, in contrast togenerally low (<2 mS) specific conductivity at LB. Watertemperatures ranged 15.31–36.58°C and was similar be-tween sites (LB2, 27.57±2.84 SD; BC2, 28.90±2.77 SD).Dissolved oxygen ranged from 0 to 267 %, and was lower atLB2 (39.53±32.37 SD) than BC2 (61.12±53.80 SD).

Field Sampling

We compared body condition and growth of juvenile whiteperch between brackish (BC) and freshwater (LB) habitats.Two sites were sampled in each of BC and LB (Fig. 1). Sitesin each waterway were approximately the same distanceapart. Prior to sampling for fish (see below), water qualitywas recorded to later characterize monthly changes in bodycondition with respect to variation in water quality varia-bles. AYellow Springs Instrument (YSI) model 85 was usedto measure DO (milligrams per liter), water temperature(degrees Celsius), salinity (parts per thousand), and specificconductivity (milliSiemens). Visibility was measured bydividing water clarity (measured as the depth of light pen-etration as measured by a Secchi disk, in millimeters) bywater depth (in millimeters). In order to compare environ-mental variables between sites, separate analyses of variance

Estuaries and Coasts (2012) 35:1110–1118 1111

(ANOVA) were used to test for differences in averagemonthly water temperature, salinity, DO, and water visibil-ity between LB and BC. Water temperature, salinity, andDO were log-transformed to normalize variance, while wa-ter visibility was arc-sine square root transformed.

We collected 236 white perch (≤120 mm) while samplingmonthly (March 2007–January 2008) using fyke nets (1.25-cmmesh, 15.2-m leader). Fyke nets were set for 24 h and mostwhite perch were collected during spring (March–May) andfall (September–November; Table 1). Fish were measuredfor total length (TL; millimeters) and weighed (grammes).Four scales were taken from the mid-dorsal region abovethe lateral line (Mansueti 1960) to measure growthbetween circulus deposition for 159 juveniles collectedMarch–October (Mansueti 1960, 1961; Sheri and Power1969; Wallace 1971). We used the most readable scale(of the four taken) instead of otoliths because scales arenon-lethal and because spacing of scale circuli is sensitiveenough to compare growth among juvenile fish (Fisher and

Pearcy 1990; Kingsford and Atkinson 1994; Cheung et al.2007) and seasons (Fisher and Pearcy 2005). Scales that wereregenerated or damaged were discarded.

Scale images were digitized with an Accu-scope stereo-scope (Accu-scope Inc., New York) and analyzed withMicroMetrics SE software (2005). Two readers made inde-pendent counts of scale circuli to determine the number andlocations of circuli. Discrepancies between readers resultedin either a third reading of the scale or scale abandonment.

Statistical Analysis

Changes in mass (M) by length (L) were modeled byM0aLb. While b03 for many organisms (Calder 1996),the slope can vary and may bias comparisons of bodycondition among populations (Cone 1989). Relative bodycondition (Kn) was calculated as the average of residuals inmass from a log-transformed (base10) length–weight rela-tionship (Cone 1989). Variance in Kn was not normally

Fig. 1 Location of Blackwaterdrainage (38°27′30″N 76°06′41″W) within Chesapeake BayWatershed. Inset: Location ofsampling sites along brackish,Buttons Creek (BC1 and BC2;triangles) and freshwater, LittleBlackwater River (LB1 andLB2; circles)

1112 Estuaries and Coasts (2012) 35:1110–1118

distributed (Shapiro–Wilk statistic00.95, p<0.01). A nonpara-metric, Kruskal–Wallis (KW) statistic was used to test whetherKn (dependent variable) significantly differed between LB andBC (independent variable) for each season: spring (March–May); summer (June–August); fall (September–November);and winter (December–January).

The Kn was averaged among individuals for each site andeach month, which reduced the dataset to 31 observations.Variance in average Kn was partitioned to concurrent meas-urements of water temperature, specific conductivity, DO,

and water clarity using a classification–regression tree(CART). A CART is a nonparametric analysis that partitionsvariance in the dataset into successive groups using rulestatements. Rule statements are conditional “if–then” state-ments related to environmental predictors used in the anal-ysis. Successive groups are observations of Kn grouped byminimizing variance in each group using least squares. Thegroups formed a classification tree built by rule statementsthat could be used to classify unknown samples into a group(Urban et al. 2002). The ability of rule statements to mini-mize variance during the grouping process was measuredand summed to yield a proportional reduction of error(PRE), which is similar to r2 in least squares regressionanalysis. Reproducibility of rule statements leading togroups of observations was determined by jack-knifing,which was performed 30 times by removing one observationin the dataset. For each jack-knifed dataset, CART wasperformed. The PRE and first occurrence for each rulestatement (RUL) were recorded and averaged across jack-knifed datasets. A value of 11 was given to any habitatvariable not included in the tree because only 10 splitsleading to groups were allowed.

The change in fish size over time was determined fromgrowth of scales. Scales were taken from 141 individuals.There were positive correlations between TL and the num-ber of circuli (Spearman's ρ00.74) or scale size (Spearman'sρ00.77), supporting the use of circuli as units of age. Usingthe distance to the last circulus of the scale and TL of thefish, size-at-age was back-calculated to each circulus by:

Lt ¼ �ða=bÞ þ ðLp þ a=bÞ � ðrt=rpÞ ð1Þwhere Lt is length at time t, Lp is length at time of capture, rtis scale radius at time t, rp is scale radius at time of capture,and a and b are parameters from the linear regression of TLand scale radius (Jennings et al. 2001; of the form y0ax+b).

The slope of back-calculated size and age (i.e., growthrate) was determined by:

lnðLtÞ ¼ aþ G lnðrÞ ð2Þwhere Lt is back-calculated length (i.e., size), G is growthrate, a is the intercept, and r is the circulus number (i.e.,age). Parameters were derived from least squares methodsand a Gauss–Newton algorithm. To compare growth ratesbetween LB and BC, Eq. (2) was fit to size-at-age data forpooled samples (LB+BC), BC samples only, and LB sam-ples only. The residual sum-of-squares (ARSS) from growthcurves were compared using F statistics (Chen et al. 1992):

F ¼RSSp�RSSs

DFRSSp�DFRSSs

RSSs=DFRSSsð3Þ

where RSSp is the residual sum-of-squares (RSS) for allpooled growth curves, RSSs is the sum of the RSS from

Fig. 2 Changes in water temperature (a), dissolved oxygen (b), andspecific conductivity (c) over time (23 May 2008–1 September 2008)in Buttons Creek (BC2) and Little Blackwater River (LB2) of theBlackwater River drainage (Chesapeake Bay Watershed, Maryland,USA; see Fig. 1)

Estuaries and Coasts (2012) 35:1110–1118 1113

each individual growth curve, and DF is degrees of free-dom. The calculated F statistic was compared with critical F(α00.05) from an F table to determine if there was asignificant difference among growth curves. Analyses weredone with SYSTAT (ver. 11.0, SYSTAT Software Inc.,Chicago, IL).

Results

Buttons Creek (BC) had greater salinity than Little Black-water River (LB) (ANOVA, F1,2306.23, p00.02). Salinityand specific conductivity at the time of sampling weregenerally lower at LB1 and LB2 than at BC1 and BC2(Table 1). Specific conductivity increased throughout theyear until September and October, after which it began todecline to initial levels. Water temperature increased fromMay until August; however, it was not significantly differentbetween BC and LB (Table 1; ANOVA, F1,2300.40, p00.54). Dissolved oxygen was not significantly different

between sites (ANOVA, F1,2300.74, p00.40). For bothsites, DO was lowest between June and July, increasingthereafter (Table 2). To relate DO to body condition (below),DO was treated as a dummy variable whereby months withDO<5 mg/L (i.e., stressful; Uphoff et al. 2011) were sepa-rated categorically from months with DO≥5 mg/L. Fresh-water sites LB1 and LB2 had lower water visibility thanbrackish sites, BC1 and BC2 (ANOVA, F1,2103.89, p00.06). However, water visibility varied greatly amongmonths for both sites (Table 1). The principal differencesbetween BC and LB were related to salinity or specificconductivity and not to other environmental variables mea-sured here.

Body Condition

From March 2007–January 2008, 236 juvenile whiteperch individuals were captured to estimate body condition(Table 2). Captured fish ranged in size from 49 to 120 mmTL (average, 98.23±16.23 SD) and 1.9–27 g (average,

Table 1 Water temperature (WTEMP; degrees Celsius), dissolvedoxygen (DO; milligrams per liter), specific conductivity (SPCO; milli-Siemens), salinity (SAL), and calculated water visibility (WVISI;

Secchi depth/depth) for each site in the Little Blackwater River (LB)and Buttons Creek (BC) (Blackwater River drainage, MD, U.S.A.)from March 2007–January 2008

WTEMP WTEMP WTEMP WTEMP DO DO DO DOBC2 BC1 LB1 LB2 BC2 BC1 LB1 LB2

Mar 18.00 17.70 8.80 9.60 6.70 2.14 7.04 8.32

Apr 10.30 10.00 9.50 10.30 7.72 5.30 NA 6.83

May 25.00 24.60 21.80 21.80 5.00 6.70 5.97 4.50

Jun 30.10 30.20 28.30 28.90 1.00 4.00 1.92 1.50

Jul 27.10 26.90 28.70 29.30 5.29 2.31 1.89 2.76

Aug 29.20 28.60 26.50 27.10 4.51 3.84 3.88 4.85

Sep NA 24.30 20.90 21.90 NA 6.42 2.95 2.91

Oct NA 19.10 17.00 16.60 NA 13.90 4.52 6.88

Nov 9.30 8.60 7.90 8.30 13.30 7.11 8.58 10.60

Dec 4.50 4.20 2.00 3.90 13.80 7.70 9.22 11.80

Jan 6.60 NA 4.80 5.80 13.80 NA 11.16 11.34

SPCO (SAL) SPCO (SAL) SPCO (SAL) SPCO (SAL) WVISI WVISI WVISI WVISI

BC2 BC1 LB1 LB2 BC2 BC1 LB1 LB2

Mar 1.10 (0.50) 0.44 (0.20) 0.09 (0.00) 0.10 (0.00) 0.44 0.46 1.00 1.00

Apr 0.20 (0.10) 0.13 (0.10) 0.08 (0.00) 0.08 (0.00) 0.77 0.59 0.33 0.25

May 2.25 (1.20) 2.21 (1.10) 0.19 (0.10) 0.28 (0.10) 0.33 0.21 0.35 0.16

Jun 5.61 (3.00) 4.17 (2.20) 0.22 (0.10) 0.52 (0.30) 1.00 NA NA NA

Jul 9.67 (5.40) 8.53 (4.70) 0.75 (0.40) 2.04 (1.0) 0.48 0.34 0.20 0.14

Aug 14.62 (8.40) 14.07 (8.40) 2.38 (1.20) 5.47 (2.90) 0.89 0.76 0.18 0.17

Sep NA 14.18 (8.20) 3.80 (2.00) 6.90 (3.80) NA 0.34 0.21 0.17

Oct NA 14.70 (8.60) 6.41 (3.50) 9.30 (5.20) NA 0.39 0.17 0.18

Nov 10.75 (6.10) 8.30 (4.60) 2.36 (1.20) 4.06 (2.20) 1.00 0.39 0.44 0.48

Dec 9.15 (5.10) 6.28 (3.40) 2.38 (0.40) 3.02 (1.60) 0.50 0.50 0.40 0.39

Jan 10.09 (5.70) NA 0.64 (0.30) 0.91 (0.40) 1.00 NA 0.54 0.69

1114 Estuaries and Coasts (2012) 35:1110–1118

ll.61±6.33 SD). The relationship of length (L) to mass (M)was: M0(0.021×L)3.373 (r200.89; p<0.0001). Body condi-tion was greater in LB than BC during spring (n0111; KW025.31, p<0.0001), fall (n0103; KW029.44, p<0.0001), andwinter (n033; KW05.52, p00.019). This relationshipcould not be tested during summer because only onefish was collected in BC (Table 2). Thus, for mostseasons we found support for our hypothesis that bodycondition was greater in freshwater (i.e., LB) thanbrackish water (i.e., BC) habitats.

We found partial support for our hypothesis that relativebody condition (Kn) was highest in habitats with low spe-cific conductivities and when dissolved oxygen, water vis-ibility, and water temperatures were high (Fig. 3). Variancein Kn was importantly partitioned to water temperature,specific conductivity, and water visibility (PRE00.50;Table 3), but not DO. Of these, water temperature (RUL01.7±0.5) and specific conductivity (RUL02.2±0.3) werealmost equivalently important in explaining variance inKn (Table 3); though, error was proportionately reduced more

by adding water temperature (PRE00.25±0.01) than specificconductivity (PRE00.11±0.01). Body condition was onlygreater in freshwater (Specific Conductivity <0.45 mS) thanbrackish water when water temperature was greater than9.6°C (Fig. 4). In warm and (>9.6°C) and brackish water(>0.45 mS), body condition was higher when water visibilitywas high (>21.2 %).

Instantaneous Growth

Juveniles collected from March–October (n0137) wereused to estimate growth using scales; scales from 22 addi-tional fish were collected, but discarded. For the pooleddataset, the growth parameter (or G) estimated from thelength-at-age data was 1.297±0.004 SE (r200.958, p<0.0001); individuals grew an average of 1.3 mm betweeneach circulus formation. The intercept (or a) was 2.812±0.005 SE; individuals were 2.81 mm at birth (i.e., circulusnumber00), which is similar to that reported for white perchin the Chesapeake Bay Watershed (Margulies 1988).

Fig. 3 Measurements of body condition (Kn) of juvenile white perch(Morone americana) decreased with changing habitat conditions (di-agonally from left to right) in Blackwater River drainage (ChesapeakeBay Watershed, Maryland, USA) (March 2007–January 2008). At eachnode, the number reflects the relative importance of splitting body

condition measurements according to the habitat rule (i.e., range)written above the preceding branch. Dashed line represents increasingbody condition across habitat variables. Habitat variables subjected tothe analysis were: specific conductivity (SC), water temperature (WT),water visibility (WC), and dissolved oxygen

Table 2 Total catches in fykenets (N) and size range(millimeters) of white perch foreach site in the Little BlackwaterRiver (LB) and Buttons Creek(BC) (Blackwater River drain-age, MD) for each monthsampled from March 2007–March 2008

Freshwater Freshwater Brackish Brackish

LB1 LB2 BC1 BC2

Month N Size N Size N Size N Size

Mar 0 – 4 92–112 6 115–119 18 105–120

Apr 10 105–116 9 108–120 0 n/a 6 108–120

May 3 112–118 6 96–118 5 108–117 7 112–120

Jun 1 118 13 105–120 0 n/a 0 –

Jul 1 115 2 49–111 0 n/a 0 –

Aug 1 114 10 72–117 1 120 0 –

Sep 14 78–120 16 78–120 1 85 0 –

Oct 19 75–96 3 87–118 3 110–115 0 –

Nov 2 98–120 20 76–97 5 76–90 20 74–93

Dec 0 – 1 86 0 – 6 79–97

Jan 0 – 3 101–120 0 – 20 74–89

Estuaries and Coasts (2012) 35:1110–1118 1115

Average growth for white perch throughout the studyperiod did not differ between LB and BC (ARSS F00.37, p>0.05). Length increased similarly with age (ornumber of circuli) for LB and BC (Fig. 4). However,when fish scales had formed 20–30 circuli then size-at-age was marginally larger for fish from LB than BC(Fig. 4). Sign-rank tests were performed for age groups1–10, 10–20, 20–30, and >30 circuli. Size-at-age wassignificantly larger for the 20–30 age group (p<0.001),but not for others (p≥0.75). Thus, the growth advantagefor fish in freshwater occurred across a short timeperiod and was relatively negligible.

Discussion

Relative body condition (Kn) for juvenile white perch washigher in freshwater than brackish habitats. Migration of whiteperch into freshwater to spawn may be evolutionarily benefi-cial for white perch if it maximizes fitness of juveniles byincreasing early growth and survivorship (Gross 1987; Postand Parkinson 2001). Growth, however, did not differ betweenfreshwater and brackish habitats, except within a narrow timeframe. Growth rates should not have been sampling errorbecause of movement of individuals between waterways; theshort timeframe of this study and great distance between LBand BC sites likely precluded suchmovement. Kraus and Secor(2004) similarly found that white perch growth was enhancedin freshwater for a narrow time frame (from 20 to 45 days oflife). If there is little difference in size-at-age between juve-niles residing in freshwater and brackish water habitats (Kerrand Secor 2012), then the main fitness advantage for juvenilesin freshwater appears to be related to body condition.

Freshwater habitats of the Little Blackwater River arenursery habitats that provide for greater robustness in juve-nile white perch. White perch in brackish habitats withvariable salinity may exert more energy to maintain homeo-stasis (Boeuf and Payan 2001; but see Musselman et al.1995). Such maintenance can reduce energy that is investedin mass accumulation in brackish habitats and explain thenarrow time frame of improved growth in freshwater, whichseemingly occurs in summer or early fall (see Fig. 5; Newhard

Fig. 5 Histogram depicting variation in body condition (Kn) for whiteperch (Morone americana) collected from Little Blackwater River (LB)and Buttons Creek (BC) of the Blackwater River drainage (ChesapeakeBay Watershed, Maryland, USA; March 2007–January 2008)

Fig. 4 Comparison of lengths-at-age for white perch (Morone amer-icana) collected from Buttons Creek and Little Blackwater River in theBlackwater River drainage (Chesapeake Bay Watershed, Maryland,USA) from March 2007–January 2008

Table 3 Results from classification-regression tree analyses relatinghabitat variables to body condition of white perch (Morone americana)from the Blackwater River drainage (Maryland, U.S.A.)

Variable RUL (OD) PRE (OD) RUL (JK) PRE (JK)

WTEMP 1 0.27 1.7±0.5 0.25±0.01

SPOC 2 0.12 2.2±0.3 0.11±0.01

WVISI 3 0.11 3.0±0.3 0.13±0.02

DO 0 0 10.5±0.4 0.00±0.00

Habitat variables were specific conductivity (SPOC; milliSiemens),water temperature (WTEMP; degrees Celsius), water visibility(WVISI), and dissolved oxygen (DO; milligrams per liter). The occur-rence of the rule (RUL) in the tree and proportional reduction error(PRE) by inclusion of the habitat variable are given for the originaldataset (OD) and averages from 30 jack-knifed (JK) datasets

1116 Estuaries and Coasts (2012) 35:1110–1118

2009). In addition to energy expenditure, prey differences be-tween brackish and freshwater habitats may explain differencesin relative body condition. In the Great Lakes where whiteperch have invaded from Hudson River because of favorableclimatic conditions (Johnson and Evans 1990), adult whiteperch have significantly reduced Daphnia densities in fresh-water (Coutture and Watzin 2008). Adults seemingly pre-ferred Daphnia to other zooplankton and macrobenthicfauna (Coutture and Watzin 2008). If Daphnia are abundantor more steadily available in freshwater relative to brackishwater, then body growth may be greater because of the stabil-ity or nourishment of the prey source.

Despite possible fitness costs, juvenile white perch areabundant in brackish habitats. Juveniles from brackish waterhabitats contribute the most to a population and freshwatercontingents contribute to the population when productivityof brackish water areas is low (Kraus and Secor 2004). Theindividuals produced in freshwater habitats have a greaterrelative body condition, even if growth differences are mi-nor. The quality of juveniles from freshwater habitats maybe critically important to recruitment to the migratory con-tingent of white perch (Kraus and Secor 2004; Kerr et al.2009). If so, then the quality of freshwater habitats may bemore important for smaller drainages of the Chesapeake Baywhere the migratory contingent is more abundant than theresidential contingent (Kerr and Secor 2012).

There has been a loss of habitat available to white perch(and freshwater-dependent species, in general) during thespawning season in the Chesapeake Bay Watershed (MarylandDepartment of Natural Resources MDDNR 2010) and inthe mid-Atlantic region (Rogers and McCarty 2000). Fresh-water loss can be explained by sea level rise (Wood et al.2002) and relatively high specific conductance in streamsduring early spring when roads are salted (Kaushal et al.2005). White perch have not only lost spawning habitat, butspawning occurs in poor quality habitats. Some spawninghabitats may later become hypoxic dead zones, which canbe caused by run-off and impervious surface development(Uphoff 2008; Uphoff et al. 2011). Some spawning habitatsincrease in salinity during summer, which possibly contributesto greater levels of emigration in freshwater-fish communities(Love et al. 2008). There were low levels of salinity (<0.5)during the spawning period (March–April) in Buttons Creek,for example; later in the year, though, salinity increased andsubjected juveniles to a brackish environment. Buttons Creekmay therefore represent an ecological trap for white perch(Dwernychuk and Boag 1972). For those juveniles “trapped”in brackish habitats during their first summer, reduced indi-vidual body condition or smaller size may occur. Relativelylow body condition can affect the population by reducing sizeat maturity (Post and Parkinson 2001) or increasing vulnera-bility to predators (Sogard 1992). As suggested by Kraus andSecor (2004), a mosaic of habitat types that include freshwater

and brackish habitats are important for continued persistenceof fisheries and anadromous fish. If freshwater habitats con-tinue to disappear, there may be a reduction in either theweight or number of adults in the migratory contingent overtime. Fishery managers will need to consider such effects orlosses with respect to cost in recruitment and size of spawningstocks.

Acknowledgments We are grateful to Dr. Dixie Birch and the staff atBlackwater National Wildlife Refuge for access to the water and boatusage. We are thankful for the thoughtful comments of two anonymousreviewers, as well as those of the editor. Also, we would like to thankMike Mackinnon, Ryan Corbin, Dan Luers, Eryn Kahler, HeatherWhelan, and Steffi Thomas. This work was funded by U.S. Departmentof Agriculture (grant no. 0-5218).

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The findings and conclusions in this article are those of the author(s)and do not necessarily represent the views of the U.S. Fish and WildlifeService.

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