Latitudinal variation in growth among Arctic charr in eastern North America: evidence for countergradient variation?

CHARR

Latitudinal variation in growth among Arctic charrin eastern North America: evidence for countergradientvariation?

Louise Chavarie • J. Brian Dempson •

C. J. Schwarz • J. D. Reist • G. Power •

M. Power

Received: 29 June 2009 / Accepted: 1 December 2009 / Published online: 8 January 2010

� Springer Science+Business Media B.V. 2010

Abstract Biological data from 66 populations of

Arctic charr, Salvelinus alpinus, from eastern North

America were analysed to test the applicability of the

countergradient hypothesis as an explanation of dif-

ferences in seasonally adjusted growth rates. Samples

were obtained along a 37� latitudinal gradient and

partitioned among anadromous, normal lacustrine, and

dwarf lacustrine Arctic charr morphotypes. Models

relating length-at-age or age-specific growth rates to

latitude were estimated for each morphotype. Length-

at-age declined with latitude for anadromous and

lacustrine charr. Age-specific growth rates also varied

with latitude, particularly for normal lacustrine charr.

Results of analyses provide support for the counter-

gradient hypothesis in growth performance of normal

lacustrine morphotypes, where northern populations

compensate for the shorter growth season with a

greater rate of growth than southern populations.

Anadromous charr exhibited equivocal evidence of

countergradient variation, while results for dwarf

lacustrine Arctic charr populations were inconclusive

owing to the limited range of ages, and latitudes for

which data were available.

Keywords Arctic charr � Growth � Adaptation �Countergradient variation � Climate

Introduction

Analyses of latitudinal variation in life-history traits

are common, with studies investigating reproductive

characteristics and growth perhaps among the most

familiar (e.g., Paulson & Smith, 1977; Leggett &

Carscadden, 1978; Fleming & Gross, 1990; Jonsson &

L’Abee-Lund, 1993; Jensen et al., 2000; Lombardi-

Carlson et al., 2003; Power et al., 2005a). Growth

studies, in particular, are of fundamental importance

Guest editors: C. Adams, E. Brannas, B. Dempson,

R. Knudsen, I. McCarthy, M. Power, I. Winfield /

Developments in the Biology, Ecology and Evolution of Charr

L. Chavarie � M. Power (&)

Department of Biology, University of Waterloo,

200 University Avenue West, Waterloo,

ON N2L 3G1, Canada

e-mail: [email protected]

J. B. Dempson

Fisheries and Oceans Canada, Northwest Atlantic

Fisheries Centre, P. O. Box 5667, St. John’s,

NL A1C 5X1, Canada

C. J. Schwarz

Department of Statistics and Actuarial Science, Simon

Fraser University, Burnaby, BC V5A 1S6, Canada

J. D. Reist

Fisheries and Oceans Canada, Central and Arctic Region,

501 University Crescent, Winnipeg, MB R3T 2N6,

Canada

G. Power

51 Glasgow Street, Conestogo, ON N0B 1N0, Canada

123

Hydrobiologia (2010) 650:161–177

DOI 10.1007/s10750-009-0043-z

with implications for population ecology and under-

standing effects of exploitation (Conover et al., 1997).

Because latitudinal variation in environmental param-

eters, such as temperature, may provide better insight

into understanding future climate-driven shifts in the

biological characteristics of fish populations (Power

et al., 2005a), growth studies have recently acquired

further importance. This is especially relevant in the

context of climate variability and change and its

consequent impacts on northern fishes (Reist et al.,

2006a, b, c).

Across latitudinal gradients temperature and

length of the growing season will vary, and these

factors will combine to have a pervasive effect on fish

growth rate and food consumption, with lower

temperature and shorter summer seasons generally

reducing growth (Power, 1981; Jensen & Johnsen,

1986; Jobling, 1997; Wootton, 1998). Thus in high-

latitude environments, individuals experiencing low

temperatures and shorter growing seasons ought to

exhibit lower growth rates and smaller size-at-age

than individuals at lower latitudes. However, a

number of species-specific studies of geographic

variation in size-at-age and growth rate have demon-

strated latitudinal compensation gradients resulting in

better growth performance in northern fish compared

with southern fish (Conover & Present, 1990;

Conover, 1992; Present & Conover, 1992; Nicieza

et al., 1994; Schultz et al., 1996; Conover et al., 1997;

Billerbeck et al., 2000).

Two hypotheses have been proposed to explain the

occurrence of such gradients. The thermal adaptation

hypothesis suggests that growth rates are maximized

at the temperature most commonly experienced by an

organism in their native environments (Levinton,

1983; Lonsdale & Levinton, 1985). Individuals from

high latitudes will, therefore, have a reaction norm

for better growth at lower temperatures than individ-

uals from lower latitudes (Levinton, 1983). Such

growth responses to temperature imply local adapta-

tions that evolve via genotypic responses to the

environment to maximize fitness for native environ-

ments, and consequent reductions in fitness of those

individuals elsewhere.

In contrast, the countergradient hypothesis focuses

on latitudinal differences in the thermal opportunity

and capacity for growth (e.g., Thorpe et al., 1989;

Conover & Present, 1990), rather than average

temperature. Countergradient theory predicts patterns

in genetic or phenotypic variation that are inversely

related to the prevailing environmental gradient. For

example, evolved genetic capacities for growth in

northern populations may offset, or compensate, for

the effect of reduced growing season length (Conover

& Present, 1990). Alternatively, the suitability of the

thermal environment within the growing season may

differ with latitude, with temperatures at southern

latitudes being unsuitable for growth over significant

periods of the year, and temperatures at northern

latitudes remaining at or near the optimum for

maximal growth for longer periods of time (Conover,

1990). Such differences in the duration of suitable

temperatures for growth would moderate and elevate

average northern seasonal growth rates in a manner

that would yield an inverse relationship between

growth rates and latitude termed as the ‘‘countergra-

dient variation’’ (Conover, 1990).

While there is some empirical evidence from

ectothermic species for both hypotheses (Yamahira &

Conover, 2002), overall support for the countergra-

dient hypothesis is often equivocal. For example,

Conover and co-workers have reported pervasive

evidence for the hypothesis (e.g., Conover, 1990,

1992; Present & Conover, 1992; Conover et al., 1997;

Yamahira & Conover, 2002), whereas others have

argued no compensation gradient can be found (e.g.,

Otterlei et al., 1999; Finstad & Forseth, 2006; Forseth

et al., 2009) or that the geographic variation that does

exist is more related to environmental variability than

any intrinsic differences in growth capacity among

populations (e.g., Jensen et al., 2000). Studies of

salmonid species have been particularly non-support-

ive. In brown trout (Salmo trutta), geographic

variation in growth rates was related to local envi-

ronmental differences (Jensen et al., 2000), while in

sockeye salmon (Oncorhynchus nerka), the influence

of any countergradient effect was masked by the

influence of prey resource availability and tempera-

ture (Edmundson & Mazumder, 2001). Among

Norwegian Atlantic salmon (Salmo salar), no clear

pattern in growth in relation to latitudinal compen-

sation was found (Jonsson et al., 2001).

Within the salmonid group of fishes, Arctic charr,

Salvelinus alpinus, is perhaps the most adapted to cold-

water habitats throughout its circumpolar distribution

(Johnson, 1980; Hammar, 1999). In eastern North

America, its natural range extends over approximately

40� of latitude from Maine in the south (44�N;

162 Hydrobiologia (2010) 650:161–177

123

Kircheis, 1980; Bernatchez et al., 2002) to Ellesmere

Island in the north (83�N; Johnson, 1980; Babaluk

et al., 2007) As such the species exists in high Arctic,

Arctic, sub-Arctic, and temperate environments and

thus lends itself well to studies of latitudinal variation

and thermal adaptation. Currently, studies of thermal

adaptation in Arctic charr have found no support for the

premise of differential genetic capacities based on

growth experiments with populations from Scandina-

via and Britain (Larsson et al., 2005). However, few

true comparative studies of geographic variation in

populations of Arctic charr exist. A number of studies

provide anecdotal support for the countergradient

explanation of observed latitudinal variation in size-

at-age characteristics (e.g., Venne & Magnan, 1989;

Tallman et al., 1996). Evidence of latitudinal variation

in population characteristics when coupled with the

wide distribution of Arctic charr at Arctic and temper-

ate latitudes in eastern North America suggests possi-

ble local adaptability within the species, and raises

obvious questions about the underlying causes of

reported variation in size-at-age among populations

(e.g., Johnson, 1980; Klemetsen et al., 2003).

Here, we examine variations in size-at-age among

sampled populations of eastern North American

Arctic charr along a 37� latitudinal gradient from

Maine, USA, in the south, to Ellesmere Island,

Nunavut, in the north; an area of the world, where

one of the steepest latitudinal temperature gradients

exists (Conover, 1992). Specifically, we aim to

document patterns of variation in size-at-age and

growth rates between freshwater resident (lacustrine)

and anadromous populations of Arctic charr and test

the applicability of the countergradient hypothesis as

an explanation of those differences.

Methods

Biological data (length, age, and sex) on 66 Arctic charr

populations located in eastern North America (Fig. 1;

Table 1), principally Canada, were obtained from

varying sources including Fisheries and Oceans Canada

databases, personal archival, and published data (e.g.,

Grainger, 1953). In this study, eastern North America

was defined to include Maine, Quebec, insular

0 250 500 750

Kilometres

H u d s o n

B a y

Q u e b e c

E l l e s me r e

I s l a n d

L a b r a d o r

B a f f i nI s l a n d

2625

24 2322 2120

19

18

1711

3

1

80° 70° 60° 50° 40°

80°

70°

60°

50°

16

1514131210

9 87

6

5

4

2

0 250 500 750

Kilometres

H u d s o n

B a y

Q u e b e c

E l l e s me r e

I s l a n d

L a b r a d o r

B a f f i nI s l a n d

62

636465

66

Lake Resident

Dwarf

6160

59

535756

5455

52

4846

5149

47

44433937 38

3029

2827

80°

70°

60°

50°

80° 70° 60° 50° 40°

3134

32

4041

36 3533

50

58

Fig. 1 Maps showing the general location of Arctic charr populations included in this study: left panel for freshwater lacustrine

populations and the right panel for anadromous charr. Sample location numbers coincide with those listed in Table 1

Hydrobiologia (2010) 650:161–177 163

123

Table 1 Populations of Arctic charr sampled with corresponding latitude and longitude location coordinates

Location Region Latitude Longitude Map #

Anadromous charr

Sand Hill Labrador 53�340 56�210 1

Ikadlivik River Labrador 56�180 62�050 2

Richmond Gulf Quebec 56�210 76�260 3

Fraser River Labrador 56�390 63�100 4

Okak Bay Labrador 57�280 62�200 5

Napartok Bay Labrador 58�010 62�190 6

Ikarut River Labrador 58�090 63�050 7

Pangertok Inlet Brook Labrador 58�210 63�100 8

Southwest Arm Brook Labrador 58�280 63�320 9

North Arm Brook Labrador 58�330 63�280 10

Leaf River Quebec 58�390 70�250 11

George River Quebec 58�470 66�100 12

Koroc River Quebec 58�510 65�480 13

Ramah Bay Labrador 58�520 63�130 14

Nachvak Fiord Labrador 59�010 64�030 15

Sappukkait River Quebec 59�280 65�180 16

Finger Lake Quebec 59�300 70�220 17

Deception River Quebec 61�460 73�430 18

Sylvia Grinnell River Baffin Island, NU 63�440 68�340 19

Lake Avataktoo Baffin Island, NU 66�150 67�180 20

Ikalojuak Bay Baffin Island, NU 66�250 66�240 21

Kangerk Fiord Baffin Island, NU 66�270 67�270 22

Shilmilk Bay Baffin Island, NU 66�350 67�220 23

Koukjuak River Baffin Island, NU 66�380 71�500 24

Ikaluit River Baffin Island, NU 71�580 79�150 25

Salmon River Baffin Island, NU 72�400 78�040 26

Dwarf lacustrine charr

Trois Caribous Quebec 47�360 72�090 30

Godaleich Pond Newfoundland 48�110 56�070 31

Lloyds Lake Newfoundland 48�230 57�350 32

Trinity Pond Newfoundland 48�250 53�280 33

Solomon Pond Newfoundland 48�430 56�470 34

Lac Davidson Quebec 49�270 67�260 38

Harding Pond Newfoundland 49�380 57�380 40

Long Pond Newfoundland 49�500 57�290 41

Charr lake Labrador 58�110 63�020 50

Unnamed Lake-3 Baffin Island, NU 65�180 63�480 58

Normal lacustrine charr

Rainbow Lake Maine, USA 45�490 69�100 27

Lac Larose Quebec 46�360 73�040 28

Lac Duchene Quebec 47�210 72�410 29

Butts Pond Newfoundland 48�490 54�160 35

Gander Lake Newfoundland 48�550 54�350 36

Lac Sans Baie Quebec 49�170 68�120 37

164 Hydrobiologia (2010) 650:161–177

123

Newfoundland, Labrador, and the eastern portion of the

Canadian Arctic archipelago (Baffin and Ellesmere

islands). Thus, the analysis that follows uses only

information for populations generally located east of

80�W to avoid the possible confounding effects of any

longitudinal gradient (Power et al., 2005a).

Data included observations on three life-history types:

anadromous, normal lacustrine, and dwarf lacustrine

Arctic charr. Dwarf lacustrine populations of Arctic charr

were defined as populations in which maximal observed

fork-length did not exceed 22 cm (e.g., Parker &

Johnson, 1991; Power et al., 2005a, b). Normal lacustrine

populations were those where the length of [50% of

mature individuals exceeded 25 cm. Anadromous Arctic

charr were defined as populations known to use near-

shore marine areas for summer feeding.

The majority of the data included in this study

consists of individual specimen observations of fork-

length (cm), mass (g), and age (years) obtained from

summer or early autumn sampling programmes that

used multi-meshed gillnets, typically in the range 38–

114 mm, or weirs to monitor and sample the studied

population (e.g., Power et al., 2005a). The numbers of

individuals sampled in each age-class varied by

population. In order to avoid problems associated with

the use of single observations, population age-class

data were included only if the study dataset contained

information on at least five specimens in each age-

class. Population age-class means were computed from

available individual data and age-class analysis was

completed only if at least five populations could be

included in the analysis, and where populations were

distributed across a range of latitude. For anadromous

Arctic charr, application of the above criteria permitted

the use of data for age-classes 5–15. For normal

lacustrine populations, age-classes 3–15 were

Table 1 continued

Location Region Latitude Longitude Map #

Lac Cavanagh Quebec 49�370 67�260 39

Lake Michel Newfoundland 50�150 57�000 42

Matamek Lake Quebec 50�220 65�540 43

Lac Victor Quebec 50�350 61�500 44

Lac Bonhome Quebec 57�130 74�320 45

Lac Minto Quebec 57�130 75�000 46

Lake Aigneau Quebec 57�140 70�070 47

Mini Minto Quebec 57�190 75�140 48

Lac Ducreux Quebec 57�470 69�340 49

Lac Noname Quebec 58�150 69�080 51

Crater Lake Quebec 61�170 73�180 52

Neakok Lake Baff in Island, NU 64�350 75�210 53

Unnamed Lake-1 Baffin Island, NU 64�360 76�030 54

Kinguk Lake Baffin Island, NU 64�400 75�300 55

Scarp Lake Baffin Island, NU 64�150 76�410 56

Unnamed Lake-2 Baffin Island, NU 65�050 76�060 57

Unnamed Lake-4 Baffin Island, NU 65�290 68�330 59

Dewar Lake Baffin Island, NU 68�340 71�100 63

Unnamed Lake-5 Baffin Island, NU 69�280 75�310 61

Erichsen Lake Baffin Island, NU 70�440 80�380 62

Murray Lake Ellesmere Island, NU 81�200 69�340 63

Alexandra Lake Ellesmere Island, NU 81�470 65�360 64

Lake Hazen Ellesmere Island, NU 81�500 70�250 65

Lake B Ellesmere Island, NU 82�080 68�290 66

Designated morphotypes are described in ‘‘Methods’’. Map # corresponds to the number used to plot locations in Fig. 1

Hydrobiologia (2010) 650:161–177 165

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included, while age-classes 3–6 were included in

analyses of dwarf lacustrine populations.

In order to account for the differences in the

opportunity for growth among populations, an index

of the thermal opportunity for growth (TOG) was

calculated from available air temperature data. Air

temperature information was used as a surrogate for

insight into general water temperature conditions

experienced by the fish owing to the frequent strength

of the association between air and water temperature

variables (e.g., Banfield & Jacobs, 1998; Drinkwater,

2000; Colbourne, 2004). TOG was defined as the

cumulative number of degree-days [0�C and calcu-

lated on the basis of literature that indicated Arctic

charr can survive and feed at 0�C (Johnson, 1980;

Brannas & Wiklund, 1992; Baroudy & Elliott, 1994;

Larsson et al., 2005). Degree-days [0�C were

cumulated over the life of individual fish to estimate

growing season TOGs at age (e.g., age-1, age-2) and

a cumulative life-time total. Cumulative degree-day

data were then combined with individual fish length

information to estimate the mean growth rate for each

age and location (fish length in cm/cumulative

degree-day[0�C) as a function of the thermal growth

opportunity as represented by TOG (e.g., Conover,

1990; Power & McKinley, 1997).

Air temperatures used in the analyses were obtained

from the Center for Climatic Research, Department of

Geography, University of Delaware (http://climate.

geog.udel.edu/*climate/index.shtml). Data are grid-

ded one degree latitude and one degree longitude

spacings starting at the prime meridian and the equator,

respectively. Data represent spatial monthly means

interpolated from a two-stage estimation procedure

that combines general circulation model predictions

with actual gridded observations to restore local cli-

mate detail (Rayner et al., 2003). The data for the grid

containing latitudinal and longitudinal co-ordinates of

a given Arctic charr population were used to represent

prevailing meteorological conditions for the popula-

tion. In some circumstances, correction for altitude was

required where, for example, coastal anadromous

populations were located in data grids largely domi-

nated by upland or glacial terrain. In such instances,

Environment Canada data (http://www.ec.gc.ca/) or

data from the nearest adjacent sea-level grid were used

to represent the prevailing meteorological conditions

for the population.

In order to determine the influence of latitude

(covariate) on either of the response variables, mean

fish length, or mean growth rate (fish length/cumu-

lative degree-day [0�C), across different age-classes

of Arctic charr (i.e., test the countergradient hypoth-

esis), a series of mixed-model analyses of covariance

(ANCOVA) were run for each morphotype with

model selection based on an information theoretic

approach using the Akaike Information Criterion

corrected for sample size (AICc; Anderson, 2008):

Ysj ¼ l þ Aj þ bZs þ AZð Þsjþ esa;

where Ysj is the mean response variable in site s at age

j, Aj represents the different age-classes, Zs is the

covariate latitude for site s, (AZ)sj is the interaction

term, and esa is a normally distributed error term. We

allow for common site effects by relaxing the usual

independence assumption on the esa and allowing for

a compound-symmetric covariance structure on the

epsilons (e). This covariance structure implies that all

age classes at a given site tend to have similar

residuals from the regression line. For example, if a

particular site leads to better than expected growth for

a given latitude, then growth at all ages tended to be

better than predicted by the simple regression line.

This covariance structure was suggested from exam-

ination of the residuals from individual regression

lines for each age. The common site effect has been

seen in previous studies (e.g., latitudinal variation in

fecundity of Arctic charr; Power et al., 2005a). Thus,

we used AICc to examine both the covariance and

mean structure of the linear models as suggested by

Gurka (2008).

We fix six models differing in their covariance and

structural components. The first model (M1) incor-

porates the correlation error structure among age-

classes within an area into the analysis. A second

model (M2) treats each age completely independently

such that there is no inherent linkage among the

residuals for a particular location from the relation-

ship that associates fish length with latitude across the

different age-classes. Two additional covariance

models were also considered (M3 with the error

structure among age-classes included; M4 with the

error structure omitted), but where the interaction

term was dropped, and a simpler common slope

model was fit with model parameters as defined

above:

166 Hydrobiologia (2010) 650:161–177

123

Ysj ¼ l þ Aj þ bZs þ esa:

Later, to better evaluate the above models regard-

ing support for a latitudinal effect, two means models

were also fit (M5 and M6, with and without the error

structure among age-classes included). Thus, the

latitude parameter was excluded from these models:

Ysj ¼ l þ Aj þ esa:

Model evaluation was done by comparing Akaike

weights (= model probabilities) as described by

Anderson (2008) whereby the differences between a

particular model and the best model (minimum AICc

value, or DAICc = 0) were determined. Regression

coefficients and their 95% confidence intervals were

considered as evidence of an effect of latitude on either

mean fish length (slope\0.0—negative effect) or mean

growth rate (slope [0.0—positive effect; Anthony

et al., 2006). All models were fit using the Proc Mixed

routine of SAS (Littell et al., 2006).

Results

The 66 populations for which information was

available were distributed between 45�490 N (Rain-

bow Lake, Maine; Michaud, 2006) and 82�080 N

(Lake B, Ellesmere Island, Nunavut; Babaluk et al.,

2007) (Fig. 1; Table 1). Of those populations, 26, 30,

and 10 were classed as anadromous, normal, and

dwarf, respectively. Anadromous Arctic charr

(N = 8,478) ranged in age from 3 to 15 years, and

in fork-length from 14.3 to 73.3 cm. Normal lacus-

trine Arctic charr (N = 3,323) varied in age from 3 to

17 years and in length from 9.8 to 52.6 cm, whereas

dwarf lacustrine Arctic charr (N = 846) ranged from

3 to 13 years and 8.9 to 21.5 cm.

Influence of latitude on fish length

The analysis of the anadromous Arctic charr included

data for age-classes 5–15 years for fish distributed

from Sand Hill River, Labrador (53�340 N) to Salmon

River, Baffin Island (72�400 N). The selected age series

avoided the inclusion of a limited range of latitudes for

which only a younger and older spectrum of ages were

originally available. AICc criterion indicated that an

unequal slope covariance model incorporating the

correlated error structure among age-classes provided

the best fit (Table 2) whereby the effect of latitude

varied by age-class for anadromous Arctic charr.

Indeed, individual slope estimates were largely nega-

tive, with 95% confidence intervals for ages 6–12

(Table 3; plots of selected ages shown in Fig. 2) all in

the range of less than zero indicating a general

tendency for length-at-age to decline with an increase

in latitude for these ages. The relative change in fork-

length across latitudes (slope) was greatest at age 7

with a progressive decline in the magnitude of the slope

as age increased (Table 3).

Analyses of lacustrine normal Arctic charr incor-

porated ages ranging from 3 to 15 years for fish

distributed from Rainbow Lake, Maine (45�490 N) to

Lake B, Ellesmere Island (82�080 N). Populations

with age 16- and 17-year-old fish were clustered at

81�–82�N with only one population at 57�N, and thus

were excluded from further analysis. A common

slope covariance model provided the best fit to the

data (Table 2) indicating that there was a negative

effect of latitude on fork-length that can be modeled

by a set of parallel lines for each age (Table 3; plots

of selected ages shown in Fig. 3). The relative change

in length across latitudes (slope) was generally less

than that observed for anadromous Arctic charr

(Table 3).

Dwarf lacustrine charr suitable for analysis ranged

in age from 3 to 6 years, and were distributed from

Trois Caribous, Quebec, Labrador (47�360 N) to an

unnamed lake on Baffin Island (65�180 N). Any older

Arctic charr ([age 7) were subsequently excluded

from further analysis owing to the single location for

which specimens were available. Similar to the

analysis of lacustrine normal Arctic charr, AICc

criterion indicated that a common slope covariance

model provided the best fit with latitude again having

a negative effect on fork-length of dwarf Arctic charr

(Table 2). The relative change in length across

latitudes was greater than that observed for normal

Arctic charr, but less than those ages where there was

a significant change in fork-length with latitude for

anadromous Arctic charr (Table 3). However, exam-

ination of individual plots of length versus latitude

illustrate that one location (Charr Lake, 58�110 N)

was a particularly strong influential point for ages 3

and 4 Arctic charr (Fig. 4). A re-analysis of the same

common slope model indicated that even with the

exclusion of the Charr Lake location there was still a

negative effect of latitude on fork-length for ages 3–6

Hydrobiologia (2010) 650:161–177 167

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Table 3 Estimated slope coefficients for the relationship of mean fork-length (cm) on latitude for different morphs of Arctic charr in

eastern North America

Morph Sample size for

ages analysed

Age Coefficient

estimate

S.E. 95% CI

Lower Upper

Anadromous 6,256 5 -0.04 0.34 -0.71 0.63

6 -0.77 0.27 -1.30 -0.24

7 -1.22 0.25 -1.72 -0.73

8 -1.15 0.23 -1.61 -0.70

9 -0.98 0.22 -1.40 -0.55

10 -0.86 0.19 -1.24 -0.48

11 -0.87 0.23 -1.32 -0.42

12 -0.63 0.24 -1.10 -0.16

13 -0.39 0.26 -0.90 0.12

14 0.01 0.35 -0.68 0.70

15 0.18 0.48 -0.76 1.12

Normal 3,201 3–15 -0.25 0.10 -0.45 -0.05

Dwarf 731 3–6 -0.38 0.08 -0.54 -0.22

Table 2 Model selection results assessing the effect of latitude on the response variable, fork-length (Y), for different age classes,

and morphs of Arctic charr in eastern North America

Morph/Model Structure Error structure

among age classes

AICc DAICc Akaike

weight

Anadromous

M1—unequal slopes Age ? Lat ? Age * Lat Included 1,219.50 0.00 1.00

M2—unequal slopes Age ? Lat ? Age * Lat Excluded 1,439.30 219.80 0.00

M3—common slope Age ? Lat Included 1,241.50 22.00 0.00

M4—common slope Age ? Lat Excluded 1,446.60 227.10 0.00

M5—means model Age Included 1,272.10 52.60 0.00

M6—means model Age Excluded 1,517.50 298.00 0.00

Normal

M1—unequal slopes Age ? Lat ? Age * Lat Included 1,011.50 15.10 0.00

M2—unequal slopes Age ? Lat ? Age * Lat Excluded 1,128.40 132.00 0.00

M3—common slope Age ? Lat Included 996.40 0.00 0.79

M4—common slope Age ? Lat Excluded 1,130.50 134.10 0.00

M5—means model Age Included 999.00 2.60 0.21

M6—means model Age Excluded 1,140.80 144.40 0.00

Dwarf

M1—unequal slopes Age ? Lat ? Age * Lat Included 109.40 7.90 0.02

M2—unequal slopes Age ? Lat ? Age * Lat Excluded 147.00 45.50 0.00

M3—common slope Age ? Lat Included 101.50 0.00 0.98

M4—common slope Age ? Lat Excluded 145.40 43.90 0.00

M5—means model Age Included 113.70 12.20 0.00

M6—means model Age Excluded 150.20 48.70 0.00

DAICc is the difference between the specified model and the best model based on the lowest AICc value

168 Hydrobiologia (2010) 650:161–177

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dwarf Arctic charr over the limited latitudinal range

for which data remained.

Influence of latitude on growth rate

Among all three morphs of Arctic charr, initial

analyses found that a common slope model provided

the best fit with a positive effect of latitude on growth

rate that could be modeled by a set of parallel lines

for each age (models M1–M4, Table 4; plots of

selected ages illustrated in Figs. 2, 3, and 4 for

anadromous, normal, and dwarf Arctic charr, respec-

tively). Thus, growth rate appears to increase mar-

ginally across latitudes with fish in the north growing

somewhat faster than those in more southerly loca-

tions (Table 5). However, as noted above for the

analysis of fish length and latitude, the inclusion of

Charr Lake, Labrador, had a strong influence on the

results for dwarf Arctic charr, and in conjunction with

the limited range of ages, the evidence in support of a

10.0

20.0

30.0

40.0

50.0

60.0

50 55 60 65 70 75

Latitude °N

Mea

n le

ngth

(cm

)

Age 6

y = 78.225 -0.771x

10.0

20.0

30.0

40.0

50.0

60.0

50 55 60 65 70 75

Latitude °N

Mea

n le

ngth

(cm

)

Age 8

y = 110.890 - 1.153x

20.0

30.0

40.0

50.0

60.0

70.0

50 55 60 65 70 75

Latitude °N

Mea

n le

ngth

(cm

)

Age 10

y = 100.540 - 0.862x

20.0

30.0

40.0

50.0

60.0

70.0

80.0

50 55 60 65 70 75

Latitude °N

Mea

n le

ngth

(cm

)

Age 12y = 89.926 - 0.627x

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

50 55 60 65 70 75

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 10

y = - 0.00943 + 0.00031x

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

50 55 60 65 70 75

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 12

y = - 0.00988 + 0.00031x

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

50 55 60 65 70 75

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

y = -0.00906 + 0.00031x

Age 6

0.000

0.005

0.010

0.015

0.020

0.025

50 55 60 65 70 75

Latitude °N G

row

th r

ate

(cm

/deg

ree

day)

Age 8y = -0.00868 + 0.00031x

Fig. 2 Scatter plots of mean fork length at age (left column) or mean growth rate at age (cm/cumulative degree-days; right column)

versus latitude for selected ages 6, 8, 10, and 12 years, for anadromous Arctic charr from eastern North America

Hydrobiologia (2010) 650:161–177 169

123

latitudinal influence on growth rate for this morph is,

therefore, highly suspect (Fig. 4).

The situation regarding anadromous charr is also

inconclusive. Examination of individual scatter

plots of growth rate on latitude for selected ages

show mixed results (Fig. 2). The common slope

model provides a reasonable fit to the growth rate

data at some of the older ages (e.g., ages 10–12),

but a poor fit at younger ages (e.g., ages \10;

Fig. 2). In contrast, there appears to be more of a

consistent tendency for growth rate to increase with

latitude for the normal Arctic charr morph with the

common slope model providing an adequate fit for

most ages (Fig. 3). The subsequent comparisons of

the various covariance models against the means

models showed only minimal support for the

proposition that latitude affected the growth rate

of anadromous Arctic charr, as the means model

provided a better overall fit to the data for this

morphotype (Table 2).

0.0

10.0

20.0

30.0

40.0

50.0

45 50 55 60 65 70 75 80 85

Latitude °N

Mea

n le

ngth

(cm

) Age 6

y = 36.354 - 0.250x

0.0

10.0

20.0

30.0

40.0

50.0

60.0

45 50 55 60 65 70 75 80 85

Latitude °N

Mea

n le

ngth

(cm

) Age 8

y = 43.145 - 0.250x

0.0

10.0

20.0

30.0

40.0

50.0

60.0

45 50 55 60 65 70 75 80 85

Latitude °N

Mea

n le

ngth

(cm

) Age 10

y = 48.401 - 0.250x

0.0

10.0

20.0

30.0

40.0

50.0

60.0

45 50 55 60 65 70 75 80 85

Latitude °N

Mea

n le

ngth

(cm

)

Age 12

y = 53.368 - 0.250x

0.000

0.004

0.008

0.012

0.016

0.020

45 50 55 60 65 70 75 80 85

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 6

y = - 0.01578 + 0.00035x

0.000

0.004

0.008

0.012

0.016

0.020

45 50 55 60 65 70 75 80 85

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 8

y = - 0.01559 + 0.00035x

0.000

0.004

0.008

0.012

0.016

0.020

45 50 55 60 65 70 75 80 85

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 10

y = - 0.01546 + 0.00035x

0.000

0.004

0.008

0.012

0.016

0.020

45 50 55 60 65 70 75 80 85

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 12

y = - 0.01552 + 0.00035x

Fig. 3 Scatter plots of mean fork length at age (left column) or mean growth rate at age (cm/cumulative degree-days; right column)

versus latitude for selected ages 6, 8, 10, and 12 years, for normal lacustrine Arctic charr from eastern North America

170 Hydrobiologia (2010) 650:161–177

123

Discussion

Results of this study provide evidence for latitudinal

compensation in the growth of normal lacustrine

Arctic charr, but questionable evidence of the appli-

cability of the countergradient hypothesis for anadro-

mous populations in eastern North America. The

subsequent analysis of the anadromous Arctic charr

data using a means model, without the inclusion of

latitude in the analysis, was found to provide a better

overall fit to the data based on the Akaike weights and

lent further support to the lack of a consistent influence

of latitude on the growth rate of anadromous Arctic

charr. Information regarding dwarf lacustrine Arctic

charr was inconclusive owing to the limited range of

ages and latitudes for which data were available. In

contrast, the positive association between growth rate

and latitude for normal lacustrine populations

0.0

5.0

10.0

15.0

20.0

45 50 55 60 65

Latitude °N

Mea

n le

ngth

(cm

)

Age 3

y = 31.848 - 0.379x

0.0

5.0

10.0

15.0

20.0

45 50 55 60 65

Latitude °N

Mea

n le

ngth

(cm

)

Age 4

y = 33.687 - 0.379x

0.0

5.0

10.0

15.0

20.0

25.0

45 50 55 60 65

Latitude °N

Mea

n le

ngth

(cm

)

Age 5

y = 33.832 - 0.379x

0.0

5.0

10.0

15.0

20.0

25.0

45 50 55 60 65

Latitude °N

Mea

n le

ngth

(cm

)

Age 6

y = 34.393 - 0.379x

0.000

0.005

0.010

45 50 55 60 65

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 3

y = - 0.02062 + 0.00046x

0.000

0.005

0.010

45 50 55 60 65

Latitude °N G

row

th r

ate

(cm

/deg

ree

day)

Age 4

y = - 0.02093 + 0.00046x

0.000

0.005

0.010

0.015

45 50 55 60 65

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 5

y = - 0.02110 + 0.00046x

0.000

0.005

0.010

0.015

45 50 55 60 65

Latitude °N

Gro

wth

rat

e (c

m/d

egre

e da

y)

Age 6

y = - 0.02134 + 0.00046x

Fig. 4 Scatter plots of mean fork length at age (left column) or mean growth rate at age (cm/cumulative degree-days; right column)

versus latitude for age 3- to 6-year-old dwarf lacustrine Arctic charr from eastern North America

Hydrobiologia (2010) 650:161–177 171

123

indicates that many populations of northern Arctic

charr grow faster than their conspecifics from the

south.

There is a history of literature pointing to latitu-

dinal compensation with respect to growth. See, for

example, Power (1981), Jensen and Johnsen (1986),

and Conover (1990). The existence of a significant

gradient as found here raises obvious questions

concerning possible causal mechanisms. In addition

to evolved differences in the genetic capacities for

growth in northern populations, increases in oppor-

tunity adjusted growth as defined by countergradient

theory may occur for any one of several environ-

mental reasons. Better quality or greater quantities of

food per individual may be available to northern

populations coincident with the critical summer

growth period. Unfortunately, little data on the

quality or quantity of prey items available to Arctic

charr populations along the latitudinal gradient stud-

ied here is available in the literature. The alimentary

and trophic plasticity of Arctic charr as noted in the

literature (e.g., Adams et al., 1998; Fraser et al., 1998;

Guiguer et al., 2002; Power et al., 2005b), however,

suggests differences in food alone would not be

sufficient to explain the phenomenon.

A second possible explanation for increased northern

growth of normal lacustrine populations relates to the

relationship between energy intake, the temperature

range over which growth occurs and the optimum

Table 4 Model selection results assessing the effect of latitude on the response variable, growth rate (Y), for different age classes

and morphs of Arctic charr in eastern North America

Morph/Model Structure Among age

classes

AICc DAICc Akaike

weight

Anadromous

M1—unequal slopes Age ? Lat ? Age * Lat Included -1,710.80 150.40 0.00

M2—unequal slopes Age ? Lat ? Age * Lat Excluded -1,553.30 307.90 0.00

M3—common slope Age ? Lat Included -1,855.90 5.30 0.07

M4—common slope Age ? Lat Excluded -1,697.60 163.60 0.00

M5—means model Age Included -1,861.20 0.00 0.93

M6—means model Age Excluded -1,692.60 168.60 0.00

Normal

M1—unequal slopes Age ? Lat ? Age * Lat Included -1,238.60 185.80 0.00

M2—unequal slopes Age ? Lat ? Age * Lat Excluded -1,138.60 285.80 0.00

M3—common slope Age ? Lat Included -1,424.40 0.00 1.00

M4—common slope Age ? Lat Excluded -1,318.40 106.00 0.00

M5—means model Age Included -1,334.60 89.80 0.00

M6—means model Age Excluded -1,156.60 267.80 0.00

Dwarf

M1—unequal slopes Age ? Lat ? Age * Lat Included -261.10 33.60 0.00

M2—unequal slopes Age ? Lat ? Age * Lat Excluded -218.50 76.20 0.00

M3—common slope Age ? Lat Included -294.70 0.00 1.00

M4—common slope Age ? Lat Excluded -263.30 31.40 0.00

M5—means model Age Included -252.70 42.00 0.00

M6—means model Age Excluded -222.40 72.30 0.00

DAICc is the difference between the specified model and the best model based on the lowest AICc value

Table 5 Estimated slope coefficients for the relationship of

mean growth rate (cm/cumulative degree-day 9 10-3) on lat-

itude for different morphs of Arctic charr in eastern North

America

Morph Age Coefficient

estimate

S.E. 95% CI

Lower Upper

Anadromous 5–15 0.31 0.09 0.13 0.48

Normal 3–15 0.35 0.03 0.30 0.40

Dwarf 3–6 0.46 0.03 0.40 0.52

172 Hydrobiologia (2010) 650:161–177

123

temperature for growth. Salmonids are known to

evidence asymmetrical dome-shaped temperature-

growth relationships (e.g., Brett et al., 1969; Elliott,

1994) reflected in temperature-dependent variation in

the scope for growth (e.g., Elliott, 1994). While

temperature-driven increases in the scope for growth

may be realized in southern environments, associated

increases in caloric demands may preclude the achieve-

ment of the potential either because of basal metabolic

costs or inter- or intra-specific competition for food

resources. At higher latitudes, reduced occupancy

densities vis-a-vis southern locales and/or reduced

inter-specific competition for available food resources

may allow northern populations to more fully realize the

biological potential for growth as described by the scope

for growth. This suggests that at higher latitudes

seasonal rises in ration, coincident with temperature

increases, may be more closely correlated with rises in

the optimum temperature for growth, thereby allowing

higher latitude populations to maintain maximal growth

rates for longer periods of time as compared to lower

latitude populations. Finally, a third possibility is that a

combination of food availability, genetic factors, and the

suitability of the thermal regime for achieving maximal

growth may explain the observed increases in the

capacity for growth among northern populations.

According to the countergradient hypothesis,

genetic effects can act to counteract the environmen-

tal gradients which influence the general zoogeo-

graphic patterns of growth seen in a species, since

shorter growing seasons and lower temperatures

should reduce the size of northern fish (Schultz

et al., 1996). In this study, increased growth rates

partially offset body size differences along the

gradient in lacustrine environments, but not in the

anadromous case once individuals begin to use

marine environments. Thus, lacustrine fish evidenced

negative length-at-age and positive growth relation-

ships with latitude as predicted by countergradient

theory, while anadromous fish evidence only negative

length-at-age relationships with latitude. The preva-

lence of the length-at-age relationship for anadro-

mous fish at younger ages probably relates to the

effect of early lacustrine residency where the count-

ergradient effect acts. Over a lifetime the effect of

periods of marine residency, where growth rate does

not differ along the gradient, cumulate to yield no

evidence of a size-at-age cline. Thus, marine envi-

ronments appear to buffer individuals against the

effects of the environmental gradient imposed on

lacustrine residents, likely as a result of the relative

similarity of marine thermal environments along the

gradient.

Many studies have tested the Conover countergra-

dient hypothesis for latitudinal variation in biological

characteristics as it applies to fish, and a growing body

of literature has found support for the hypothesis (e.g.,

Conover, 1990; Conover & Present, 1990; Nicieza

et al., 1994; Conover et al., 1997; Imsland et al., 2000;

Yamahira & Conover, 2002; Lombardi-Carlson et al.,

2003; Alvarez et al., 2006). Empirical support for the

countergradient hypothesis summarized in largely

North American studies demonstrates a widespread

phenomenon, and illustrates geographic variation in

growth is a potentially important descriptor of differ-

ences among populations. Differences in growth rates

also hold likely consequences for differences in age-at-

maturity given documented trade-offs between growth

and maturation (e.g., Wootton, 1998).

A number of studies with little or no evidence of

countergradient effects on fish growth frequently

included study sites in Europe (e.g., Otterlei et al.,

1999; Jensen et al., 2000; Jonsson et al., 2001;

Larsson et al., 2005; Finstad & Forseth, 2006; Forseth

et al., 2009). The discrepancy between geographic

regions concerning the applicability of the counter-

gradient hypothesis may be related to differences in

latitudinal temperature gradients in North America

and Europe (Fig. 5), with a somewhat more

Fig. 5 Latitudinal regression plots of July mean air temperature

(�C) climate normals (1961–1990) for Eastern Canada (opensquares) and coastal Norway (solid triangles), and for the annual

climate normal sea temperatures along the Labrador Current

(solid circles). Climate normals were obtained from Environ-

ment Canada (http://www.ec.gc.ca) and the Norway Meteoro-

logical Institute (http://met.no/english/index.html). Labrador

Current annual sea surface temperature information was

obtained from the Hadley Centre for Climate Prediction and

Research (http://www.metoffice.gov.uk/research/hadleycentre)

Hydrobiologia (2010) 650:161–177 173

123

pronounced temperature gradient over a much greater

range of temperature in eastern North America (North

American slope = -0.411; Scandinavian slope = -

0.328) meeting the precondition for the development

of geographic variation in biological characteristics

(Conover & Schultz, 1995). The greater differences

in temperature along the gradient in eastern North

America (Fig. 5) may explain, in part, the strength of

the observed latitudinal-related growth differences in

eastern North America by comparison with the more

limited thermal variability often observed in Scandi-

navia, and the associated lack of evidence for

latitudinal clines in growth rates (e.g., Jensen et al.,

2000; Jonsson et al., 2001).

The potential for geographic differentiation is great

on the east coast of North America, since steep

latitudinal gradients occur in a number of environ-

mental variables (e.g., temperature, ice-free season)

critical to species’ success (Schultz et al., 1996). Given

the notably high phenotypic variability in Arctic charr

(Klemetsen et al., 2003), exaggerated differences in

selective pressures along a given latitudinal gradient

are more likely to elicit measurable differences in

fitness-related measures such as growth rate. There-

fore, both geographic location and the environmental

gradient will act to determine the local selective

pressures on the fish which, in turn, influence the

expression of compensatory responses such as growth

rate measured in countergradient studies.

Similarly, differences in growth rates between

anadromous and normal lacustrine Arctic charr along

the studied gradient may be related to broad scale

differences in the environmental influences on marine

coastal versus freshwater habitats. The observed

consistency in annual sea surface temperature (T�range along a Y� gradient) in the nearshore marine

habitats used by anadromous Arctic charr (Fig. 5;

Labrador Sea slope = -0.149) may partly explain the

lack of evidence for a latitudinal cline in growth rate.

Indeed, coastal waters along the east coast of Baffin

Island and coastal Labrador are influenced by the cold,

southward flowing sub-polar gyre that combine the

east Baffin Island Current with the cold waters exiting

from the Hudson Strait that subsequently form the cold

Labrador Current (see Drinkwater, 1996; Colbourne,

2004; Stein, 2005). As a result, the ocean temperature

gradient along the distributional range that anadro-

mous Arctic charr included in the present analysis

(53�–72�N) may experience likely varies by less than

about 6�C (Drinkwater & Mountain, 1997). Thus, the

broad effect of prevailing maritime currents helps to

dampen environmental variation during the important

summer feeding growth period with fewer extremes in

temperatures occurring in maritime climate zones

(Belk et al., 2005). Thus, eastern North American

anadromous populations using thermal environments

largely influenced by the Labrador Current will

generally experience less of a difference in thermal

habitat as a function of latitude than will stationary

lacustrine populations. The constancy of selective

pressures along the latitudinal gradient, therefore,

correlates well with the lack of consistent differences

in observed growth rates. Further diluting the effect of

any differences in selective pressure that might occur

among anadromous populations is the migratory

exchange known to occur among assemblages of

Arctic charr (e.g., Dempson & Kristoffersen, 1987) and

the variable ages at which fish first migrate to sea

(Johnson, 1980). By comparison, in isolated lacustrine

populations, where differences in thermal selection

pressures among populations are maintained over the

entire life-history and exchange among populations

does not occur, latitudinally based differences in

growth rate are more likely to be observed.

In addition to more uniform temperatures, food

availability is another factor likely contributing to

stability of the environments experienced by anadro-

mous Arctic charr. Feeding conditions in the ocean

are generally more favorable than in freshwater

systems (Gross, 1987; Gross et al., 1988) with the

abundance of food acting to reduce variability in

growth rates among populations. Accordingly, more

uniform thermal regimes may act in conjunction with

non-restricted feeding opportunities to buffer differ-

ences in growth opportunity and reduce the variabil-

ity of growth rates among anadromous Arctic charr

populations along the latitudinal gradient. Similar

lacustrine and anadromous population differences

along latitudinal gradients have been observed in the

study of other biological attributes in Arctic charr.

For example, Power et al. (2005a) observed a lower

among population variability in the fecundity of

anadromous compared to lacustrine Arctic charr

along a latitudinal gradient in eastern North America.

To date, the majority of countergradient studies

have focused on immature fish (e.g., Conover, 1990;

Present & Conover, 1992; Schultz et al., 1996;

Conover et al., 1997; Yamahira & Conover, 2002),

174 Hydrobiologia (2010) 650:161–177

123

where differences in maturation and/or reproductive

investment are not expected to confound the analysis.

Differences in reproductive investment associated

with maturity have been observed to affect the

correlative strength of the association between lake

sturgeon (Acipenser fulvescens) biological character-

istics (e.g., length, weight) and latitude (Power &

McKinley, 1997). Thus, the decline in the strength of

the correlation between length-at-age and latitude in

older anadromous fish may be a consequence of

differences in maturation schedules among studied

populations. Maturity generally occurs at younger

ages in southern populations (e.g., Venne & Magnan,

1989; Tallman et al., 1996) and the trade-off between

somatic growth and gonad development may imply

reductions in growth at maturity that act to decouple

the growth rate response from the environmental

gradient, particularly where the environmental gradi-

ent itself is weak as is the case in marine North

American environments (e.g., Fig. 5). The fact that

similar differences in maturation schedules among

lacustrine Arctic charr do not confound the existence

of a countergradient relationship suggests the conse-

quences of differences in maturation schedules along

the gradient alone do not explain the equivocal results

obtained for the anadromous populations studied

here.

In summary, results of analyses show that the

length-at-age, and to an extent, that growth rate of

eastern North American Arctic charr varied among

populations distributed along a latitudinal gradient

from Maine to Ellesmere Island. Overall, the study

supported the countergradient hypothesis for the

normal lacustrine morphotype, where northern popu-

lations compensated for shorter growing seasons with

higher growth rates. Anadromous populations exhib-

ited little evidence to support the countergradient

hypothesis. Results for dwarf lacustrine populations

were equivocal, possibly due to the limited availability

of study populations. Morphotype-specific responses

along the described thermal gradients suggest that a

minimum temperature gradient may be needed before

latitudinal compensation in growth rates is readily

observed. Accordingly, studies testing the countergra-

dient hypothesis should take into consideration, the

extent of thermal differences along the tested gradient

when assessing the applicability of the hypothesis to a

species of concern. Further resolution of this is

important, since Jobling (1997) has stated that it may

be more difficult to predict the effect of long-term

increases in temperature where countergradient vari-

ation exists. This is because populations may have

differential responses toward the physiological param-

eters that influence attributes such as growth (Imsland

et al., 2000; Jonassen et al., 2000).

Acknowledgments Financial support was provided by the

Natural Resources Canada Climate Change Impacts and

Adaptation program, and the ArcticNet Centre of Excellence

(NSERC) as well as individual operating budgets of the various

researchers (MP, JBD, JDR, and GP) involved with programs

that contributed data over the years that resulted in this analysis.

As such, the most important contributions came from colleagues,

students and field assistants, too numerous to list, who were

directly involved with the collection, processing, and archiving

of these data. We also wish to acknowledge Jennifer Humber and

Neila Cochrane for their efforts in producing the maps.

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