Climate Change and DistributionShifts in Marine Fishes

Allison L. Perry,1* Paula J. Low,2. Jim R. Ellis,2 John D. Reynolds1*

We show that the distributions of both exploited and nonexploited North Seafishes have responded markedly to recent increases in sea temperature, withnearly two-thirds of species shifting in mean latitude or depth or both over 25years. For species with northerly or southerly range margins in the North Sea,half have shown boundary shifts with warming, and all but one shifted north-ward. Species with shifting distributions have faster life cycles and smallerbody sizes than nonshifting species. Further temperature rises are likely to haveprofound impacts on commercial fisheries through continued shifts in distribu-tion and alterations in community interactions.

Climate change is predicted to drive species

ranges toward the poles (1), potentially result-

ing in widespread extinctions where dispersal

capabilities are limited or suitable habitat is

unavailable (2). For fishes, climate change

may strongly influence distribution and abun-

dance (3, 4) through changes in growth, sur-

vival, reproduction, or responses to changes at

other trophic levels (5, 6). These changes may

have impacts on the nature and value of com-

mercial fisheries. Species-specific responses are

likely to vary according to rates of population

turnover. Fish species with more rapid turnover

of generations may show the most rapid

demographic responses to temperature changes,

resulting in stronger distributional responses to

warming. We tested for large-scale, long-term,

climate-related changes in marine fish distribu-

tions and examined whether the distributions of

species with fast generation times and asso-

ciated life history characteristics are partic-

ularly responsive to temperature changes.

We studied the demersal (bottom-living)

fish assemblage in the North Sea. This group

is composed of more than 90 species with

varied biogeographical origins and distribu-

tion patterns. North Sea waters have warmed

by an average of 0.6-C between 1962 and

2001, based on four decadal means before

2001, and by 1.05-C from 1977 to 2001 (7),

which correspond with our fish survey time

series. Survey data were used to calculate

catch per unit effort to determine centers of

abundance (mean latitudes and depths) for

all species and boundary latitudes for those

species that have either northerly or souther-

ly range limits in the North Sea (7). No

species range was entirely confined to the

North Sea. Measures of distribution were

regressed against same-year and time-lagged

bottom temperatures, and also a composite

measure of temperatures, the North Atlantic

Oscillation Index, the Gulf Stream Index, and

the ratio of abundances of northern and south-

ern calanoid copepod species (7). We also con-

trolled for changes in abundance that may

have influenced species distributions (7).

Centers of distribution as measured by

mean latitudes shifted in relation to warming

for 15 of 36 species (Table 1). These trends

were shown by both commercially exploited

species Esuch as Atlantic cod (Gadus morhua)

and the common sole (Solea solea)^, and by

species that are not targeted by fisheries Esuch

as scaldfish (Arnoglossus laterna) and snake-

blenny (Lumpenus lampretaeformis)^. Distances

moved ranged from 48 to 403 km (average

distance x 0 172:3 T 98:8 km, n 0 15 spe-

cies) (Fig. 1) and most of these shifts (13 of 15)

were northward (Table 1). The spatial tem-

perature gradient of the North Sea is some-

what unusual; water temperatures become

colder with increasing latitude in the south-

ern North Sea but become slightly warmer

with increasing latitudes in the north (8),

where warm North Atlantic Current waters

enter the region (9). This temperature pattern

may explain one of the two exceptional spe-

cies that moved south, the Norway pout

(Trisopterus esmarkii). Its distribution was

centered in the northern North Sea, and its

southern movement brought it into cooler

waters. The other exception was the com-

mon sole. We speculate that the southward

shift in its distribution may have been

caused by the fact that the cleanup of the

Thames estuary led to its emergence as a

major sole nursery ground during the study

period (10).

Most species that showed climate-related

latitudinal changes also shifted in depth, which

was unsurprising because North Sea depths are

roughly positively correlated with latitude (8).

A further six species, including plaice (Pleuro-

nectes platessa) and cuckoo ray (Leucoraja

58

57

56

55

aLutit

)N°( ed

58

57

56

55

aLutit

)N°( ed

A

60

59

58

57

56

)N°( edutitaL

60

59

58

57

56

)N°( edutitaL

B

Winter temperature (°C)

59

58

57

56

55

54

aLutit

ed)

N°(

876Winter temperature (°C)

59

58

57

56

55

54

aLutit

ed)

N°(

876

C

-4 -2 0 2 4 6 850

52

54

56

58

60

62

A B

C

-4 -2 450

52

54

56

58

60

62

50

52

54

56

58

60

62

A B

C

Longitude (°E)

Latit

ude

(°N

)D

Fig. 1. Examples of North Sea fish distribu-tions that have shifted north with climaticwarming. Relationships between mean lati-tude and 5-year running mean winter bot-tom temperature for (A) cod, (B) anglerfish,and (C) snake blenny are shown. In (D), rangesof shifts in mean latitude are shown for (A),(B), and (C) within the North Sea. Bars onthe map illustrate only shift ranges of meanlatitudes, not longitudes. Arrows indicatewhere shifts have been significant over time,with the direction of movement. Regressiondetails are in Table 1.

1Centre for Ecology, Evolution and Conservation, Schoolof Biological Sciences, University of East Anglia, NorwichNR4 7TJ, UK. 2Centre for Environment, Fisheries andAquaculture Science, Lowestoft Laboratory, LowestoftNR33 0HT, UK.

*To whom correspondence should be addressed.E-mail: a.perry@uea.ac.uk (A.L.P.); reynolds@uea.ac.uk(J.D.R.)..Present address: University Marine Biological StationMillport, Isle of Cumbrae KA28 0EF, UK.

R E P O R T S

24 JUNE 2005 VOL 308 SCIENCE www.sciencemag.org1912

naevus), moved deeper with warming but did

not change in latitude, suggesting that they may

have responded to climatic variation through

local movements offshore or into pockets of

deeper water. Considering both latitude and

depth, nearly two-thirds of species (n 0 21 out

of 36) have shown distributional responses to

climatic warming (table S1).

We tested whether species boundaries have

also been displaced by warming, by exam-

ining those 20 species from our data set with a

southern or a northern range limit in the North

Sea. The boundaries of half of these fishes

moved significantly with warming (Fig. 2 and

table S2). Southern boundaries shifted in 6 of

12 cases, and all shifts were northward. Four

of eight northern boundaries also moved with

warming. All but one of these species shifted

north, despite the fact that their northern range

limits lay in the relatively intensively fished

southern North Sea (11). Shifting species again

included both exploited and nonexploited fishes.

Boundaries moved over distances ranging from

119 to 816 km (x 0 304 T 196 km, n 0 10),

with the highest value describing the range

of movement of the southern boundary of

blue whiting (Micromesistius poutassou),

which is the target of the largest fishery in

the Atlantic (12). In the case of bib (Trisopte-

rus luscus), the northern boundary shifted by

342 km from 1978 to 2001, a trend that is

supported by observations that North Sea

catches of this species have been increasing

(13).

To identify shifts that may have been

driven by fishing or other nonclimatic influ-

ences, we also examined distribution changes

over time. Fishing pressure could not be in-

cluded explicitly in our analyses because reli-

able fishing effort data on a comparable spatial

and temporal scale do not exist for the North

Sea. However, during at least the last decade

of the 25-year period of analysis, the spatial

distribution of effort remained relatively con-

stant (11), and total fishing effort may have

declined slightly (14). Temporal trends in dis-

tribution suggested that fishing alone could not

explain climate-related shifts; despite the gen-

eral increase in temperature over the study

period, warming-related shifts occurred inde-

pendently of time for centers of distribution

in 8 of 36 species and for range limits in 4 of

20 species (table S3). Such shifts may have

reflected year-to-year environmental variabil-

ity, with northward movement during warm

years cancelled by southward movement dur-

ing cool years. If so, long-term distribution

shifts could depend strongly on future climat-

ic variability, in addition to longer-term av-

erage conditions.

The examination of temporal trends also

allowed for rough comparisons to be drawn

with rates of warming-related distribution shifts

in other taxa. A recent meta-analysis of climate-

change impacts on natural systems estimated

the mean annual rate of boundary movement

for 99 species of birds, butterflies, and alpine

herbs at 0.6 km northward or 0.6 m upward

(1). From the current study, the mean rate of

movement for the six fish species whose

boundaries shifted in relation to both climate

and time Ebib, blue whiting, lesser weever

Table 1. Statistically significant multiple regressions of the effects of threemeasures of North Sea warming on mean latitudes of 36 demersal fishes from1977 to 2001. PC1, first principal component from principal components anal-

ysis (PCA) of eight environmental variables (PC1 generally describes warming).Winter temp. and summer temp. indicate 5-year running mean bottom tem-peratures for December to March and June to September, respectively.

Species Common name dfMean

latitude(-N)

SD PC1 r2 PWintertemp.

r2 PSummer

temp.r2 P

Agonus cataphractus Pogge 22 54.67 0.90Anarhichus lupus Atlantic wolffish 21 58.14 0.46Argentina spp. Argentines 24 59.59 0.30Arnoglossus laterna Scaldfish 15 54.17 0.31 0.456 0.43 0.006Buglossidium luteum Solenette 23 54.14 0.28Callionymus lyra Dragonet 23 55.40 0.65 0.265 0.16 0.049 0.937 0.34 0.002Echiichthys vipera Lesser weever 24 53.30 0.13 0.191 0.39 0.001Eutrigla gurnardus Grey gurnard 23 56.13 0.35 0.194 0.30 0.006 0.651 0.61 G0.001 0.402 0.17 0.040Gadiculus argenteus Silvery pout 23 59.83 0.41Gadus morhua Atlantic cod 23 56.81 0.34 0.256 0.58 G0.001 0.534 0.38y G0.001 0.578 0.33y G0.001Glyptocephalus cynoglossus Witch 24 58.22 0.42Hippoglossoides platessoides Long rough dab 24 57.62 0.21 0.304 0.40 0.001Lepidorhombus boscii Fourspot megrim 24 60.51 0.37Leucoraja naevus Cuckoo ray 19 58.06 0.57Limanda limanda Dab 24 55.86 0.13 0.180 0.35y 0.001Lophius piscatorius Anglerfish 23 57.99 0.58 0.254 0.19 0.032 0.818 0.37 0.001Lumpenus lampretaeformis Snake blenny 12 56.52 1.15 3.174 0.81 G0.001Melanogrammus aeglefinus Haddock 24 57.91 0.16Merlangius merlangus Whiting 23 56.57 0.15 0.066 0.19 0.034Merluccius merluccius Hake 24 58.84 0.59Micromesistius poutassou Blue whiting 21 60.13 0.48Microstomus kitt Lemon sole 24 57.06 0.24Molva molva Ling 24 59.26 0.74Myxine glutinosa Hagfish 11 57.51 0.62Pleuronectes platessa Plaice 24 55.52 0.18Pollachius virens Saithe 24 59.44 0.20Psetta maxima Turbot 13 54.73 0.31Rhinonemus cimbrius Four-bearded rockling 22 56.05 0.68 0.419 0.40 0.001 1.147 0.53 G0.001 0.950 0.28 0.008Scyliorhinus canicula Small-spotted catshark 20 58.34 0.89Sebastes spp. Redfish 18 59.89 0.49Solea solea Common sole 13 53.68 0.66 –0.941 0.38 0.020 –0.963 0.34 0.028Squalus acanthias Spurdog 19 56.29 0.68Trigla lucerna Tub gurnard 19 53.89 0.50Trisopterus esmarkii Norway pout 23 58.59 0.26 –0.190 0.52 G0.001 –0.304 0.25 0.010 –0.429 0.37 0.001Trisopterus luscus Bib 9 53.29 0.51 0.489* 0.45 0.035Trisopterus minutus Poor cod 23 55.63 0.66 0.334 0.26 0.012 0.877 0.33 0.003 0.753 0.18 0.035

*A relationship with annual mean summer or winter temperature. .To identify the proportion of variance in distribution accounted for by warming, r2 and P describe the squaredsemi-partial correlation coefficient, where abundance was also a significant predictor of distribution.

R E P O R T S

www.sciencemag.org SCIENCE VOL 308 24 JUNE 2005 1913

(Echiichthys vipera), Norway pout, scald-

fish, and witch (Glyptocephalus cynoglos-

sus)^ was 2.2 km per year. It is perhaps

unsurprising that the rate of shift might be

higher for marine fishes than for alpine herbs

and butterflies, given that marine fish may

generally face fewer constraints on movement.

However, if such a difference is indicative of

more widespread trends in marine fishes, cli-

mate change could pose a greater threat to

fish populations that are constrained by their

dispersal capabilities or habitat requirements.

If the differences in rates of movement

among the taxa documented here result from

differential rates of population turnover, we

would expect species with life history traits

associated with fast population growth to have

responded most strongly to climate change. To

test this prediction, we compared life history

traits between shifting and nonshifting species

(7). As predicted, shifting species tend to have

faster life histories than do nonshifting species,

with significantly smaller body sizes, faster

maturation, and smaller sizes at maturity

(Fig. 3). Body growth rates did not differ

significantly between shifting and non-

shifting species (P 0 0.19). These relation-

ships therefore provide a starting point for

predicting species_ responses to future climate

change. These predictions could be refined,

through detailed studies of the relative sensitiv-

ities of different life history stages, to uncover

the specific mechanisms driving the patterns.

Our study shows that climate change is

having detectable impacts on marine fish dis-

tributions, and observed rates of boundary

movement with warming indicate that future

distribution shifts could be pronounced. Mean

annual surface temperatures in the North Sea

are predicted to increase by 0.5 to 1.0-C by

2020, 1.0 to 2.5-C by 2050, and 1.5 to 4.0-Cby 2080 (15). We used the midpoints of

these temperature ranges as the basis for a

rough approximation, which suggested that

two types of commercial fishes, blue whiting

and redfishes (Sebastes spp.), may retract

completely from the North Sea by 2050, and

by 2080, bib may extend its range northward

to encompass the entire region. Such changes

will clearly also depend on the responses of

their predators and prey to increases in bottom

temperature and on the availability of suitable

habitat.

These findings may have important im-

pacts on fisheries. For example, species with

slower life histories are already more vul-

nerable to overexploitation (16–18) and may

also be less able to compensate for warming

through rapid demographic responses. A fur-

ther concern is that differential rates of shift

could result in altered spatial overlap among

species, thereby disrupting interactions and

also potentially compounding the decoupling

effects of climate-driven changes in phenol-

ogy (19). Previous work off the eastern United

States has shown that fishes with the most

temperature-sensitive distributions included

key prey species of nonshifting predators (20).

Such changes could have unpredictable ef-

fects in an ecosystem already under heavy

anthropogenic pressure.

A

0

20

40

60

80

100

umixa

Mhtgnel

mc(

)m

0

20

40

60

80

100

0

20

40

60

80

100

umixa

Mhtgnel

mc(

)m

B

0

1

2

3

4

5

6

7

)y( ytirutam ta eg

A

0

1

2

3

4

5

6

7

)y( ytirutam ta eg

A

C

0

10

20

30

40

50

ytirutam ta htgne L

)mc(

Shiftingspecies

Non-shiftingspecies

0

10

20

30

40

50

ytirutam ta htgne L

)mc(

Shiftingspecies

Non-shiftingspecies

Shiftingspecies

Non-shiftingspecies

Shiftingspecies

Non-shiftingspecies

Shiftingspecies

Non-shiftingspecies

Shiftingspecies

Non-shiftingspecies

Fig. 3. Differences in life-history traits between shifting (n 0 15) and nonshifting (n 0 21) specieswith respect to centers of distribution (mean latitudes). (A) Maximum body size [t 0 –2.41, degreesof freedom (df) 0 34, P 0 0.02]. (B) Age at maturity (t 0 –2.86, df 0 27, P 0 0.01). (C) Length atmaturity (t 0 –2.29, df 0 29, P 0 0.03). Means are shown with standard errors.

8

6

4

2

0

8

6

4

2

0

8

6

4

2

0

A D

8

6

4

2

0

8

6

4

2

0

8

6

4

2

0

B E

30

20

10

0

3002001000-100

30

20

10

0

3002001000-100 3002001000-100 3002001000-100

C

121086420-2-4-6-8 121086420-2-4-6-8 121086420-2-4-6-8

F

Shift rate (km/°C) Shift rate (km/y)

Fig. 2. Frequency distributions of fish species shift rates in relation to warming and time. (A) Ratesof shift for northerly species’ (southern) boundaries with climate. (B) Southerly species’ (northern)boundaries with climate. (C) All species’ mean latitudes with climate. (D) Northerly species’(southern)boundaries over time. (E) Southerly species’ (northern) boundaries over time. (F) All species’ meanlatitudes over time. Rates for shifting species are slopes from regressions.

R E P O R T S

24 JUNE 2005 VOL 308 SCIENCE www.sciencemag.org1914

References and Notes1. C. Parmesan, G. Yohe, Nature 421, 37 (2003).2. C. D. Thomas et al., Nature 427, 145 (2004).3. C. M. Wood, D. G. McDonald, Eds., Global Warming:

Implications for Freshwater and Marine Fish (Cam-bridge Univ. Press, Cambridge, 1997).

4. K. Brander et al., Int. Counc. Explor. Sea Mar. Sci.Symp. 219, 261 (2003).

5. G. Beaugrand, K. M. Brander, J. A. Lindley, S. Souissi,P. C. Reid, Nature 426, 661 (2003).

6. G. Beaugrand, P. C. Reid, F. Ibanez, J. A. Lindley, M.Edwards, Science 296, 1692 (2002).

7. Materials and methods are available as supportingmaterial on Science Online.

8. R. J. Knijn, T. W. Boon, H. J. L. Heessen, J. F. G. Hislop,Atlas of North Sea Fishes [International Council forthe Exploration of the Sea (ICES) CooperativeResearch Report 194, ICES, Copenhagen, 1993].

9. A. N. Strahler, A. H. Strahler, Physical Geography:Science and Systems of the Human Environment(Wiley, New York, 1997).

10. R. M. Thomas, in A Rehabilitated Estuarine Ecosystem:The Environment and Ecology of the Thames Estuary,

M. J. Attrill, Ed. (Kluwer, Dordrecht, Netherlands, 1998),pp. 115–139.

11. S. Jennings et al., Fish. Res. 40, 125 (1999).12. ICES Advisory Committee on Fishery Management

(ACFM), Report of the Northern Pelagic and BlueWhiting Fisheries Working Group (ICES CM 2004/ACFM:24, ICES, Copenhagen, 2004).

13. S. I. Rogers, J. R. Ellis, Int. Counc. Explor. Sea J. Mar.Sci. 57, 866 (2000).

14. N. Daan, H. Gislason, J. Pope, J. Rice, Changes in theNorth Sea Fish Community: Evidence of Indirect Effectsof Fishing? (ICES CM N:10, ICES, Copenhagen, 2003).

15. U.K. Climate Impacts Programme, UKCIP02 ScenariosGateway—Maps Gateway; available at www.ukcip.org.uk/scenarios/marine/marine.html.

16. N. K. Dulvy, Y. Sadovy, J. D. Reynolds, Fish Fish. 4, 25(2003).

17. S. Jennings, J. D. Reynolds, S. C. Mills, Proc. R. Soc.London Ser. B 265, 333 (1998).

18. J. D. Reynolds, S. Jennings, N. K. Dulvy, in Conserva-tion of Exploited Species, J. D. Reynolds, G. M. Mace,K. H. Redford, J. G. Robinson, Eds. (Cambridge Univ.Press, Cambridge, 2001), pp. 145–168.

19. M. Edwards, A. J. Richardson, Nature 430, 881 (2004).20. S. A. Murawski, Trans. Am. Fish. Soc. 122, 647 (1993).21. We thank A. Taylor, P. C. Reid, T. Osborn, P. Jones,

the ICES Oceanographic Database, and the UK Cli-mate Impacts Programme for providing data; J. Gill,W. Sutherland, and A. Watkinson for commenting onearlier drafts; and M. Attrill, K. Brander, R. Clark, C.Fox, J. Gill, and S. Jennings for valuable discussion.This research was undertaken under the Defra-fundedproject MF0730, with additional support from a Com-monwealth Scholarship to A.L.P. and an NERC grantto J.D.R.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/1111322/DC1Materials and MethodsTables S1 to S4References

22 February 2005; accepted 28 April 2005Published online 12 May 2005;10.1126/science.1111322Include this information when citing this paper.

Community Proteomics of aNatural Microbial Biofilm

Rachna J. Ram,1 Nathan C. VerBerkmoes,3,4 Michael P. Thelen,1,6

Gene W. Tyson,1 Brett J. Baker,2 Robert C. Blake II,7

Manesh Shah,5 Robert L. Hettich,4 Jillian F. Banfield1,2*

Using genomic and mass spectrometry–based proteomic methods, we eval-uated gene expression, identified key activities, and examined partitioning ofmetabolic functions in a natural acid mine drainage (AMD) microbial biofilmcommunity. We detected 2033 proteins from the five most abundant species inthe biofilm, including 48% of the predicted proteins from the dominant biofilmorganism, Leptospirillum group II. Proteins involved in protein refolding andresponse to oxidative stress appeared to be highly expressed, which suggeststhat damage to biomolecules is a key challenge for survival. We validated andestimated the relative abundance and cellular localization of 357 unique and215 conserved novel proteins and determined that one abundant novel pro-tein is a cytochrome central to iron oxidation and AMD formation.

Microbial communities play key roles in the

Earth_s biogeochemical cycles. Our knowledge

of the structure and activities in these communi-

ties is limited, because analyses of microbial

physiology and genetics have been largely con-

fined to studies of organisms from the few lin-

eages for which cultivation conditions have been

determined (1). An additional limitation of pure

culture–based studies is that potentially critical

community and environmental interactions are

not sampled. Recent acquisition of genomic

data directly from natural samples has begun to

reveal the gene content of communities (2) and

environments (3). Here we combined Bshotgun[mass spectrometry (MS)–based proteomics

(4–6) with community genomic analysis to

evaluate in situ microbial activity of a low-

complexity natural microbial biofilm.

The biofilm samples used in this study and

prior work (2) were collected from under-

ground sites in the Richmond mine at Iron

Mountain, near Redding, California (USA).

These pink biofilms grew on the surface of

sulfuric acid–rich (pH È0.8), È42-C solu-

tions that contain near-molar concentrations

of Fe and millimolar concentrations of Zn,

Cu, and As (7) (Fig. 1). We used oligo-

nucleotide probes (8) to demonstrate that

Leptospirillum group II dominated the sample,

but it also contained Leptospirillum group III,

Sulfobacillus, and Archaea related to Ferro-

plasma acidarmanus and BG-plasma[ (Fig. 2).

This was similar in structure and composition

to the community previously used as a source

of genomic sequence (2).

In general, proteins could be assigned to

organisms, because the genes that encode them

are on DNA fragments (scaffolds) that have

been assigned to different organism types (2).

From the genomic dataset (2), we created a

database of 12,148 proteins (Biofilm_db1)

that was used to identify two-dimensional

(2D) nano–liquid chromatography (nano-LC)

(200 to 300 nl/min) tandem mass spectrome-

try (MS/MS) spectra (8–13) from different

biofilm fractions. One or more peptides were

assigned to È5994 proteins (Table 1). This

corresponds to È49% of all proteins encoded

by the genomes of the five most abundant or-

ganisms. We estimated the likelihood of false-

positive protein identification using a variety

of detection criteria and databases derived

from organisms not present in this environ-

ment (8). Because of these results, for all

subsequent analyses, we required matching of

two or more peptides per protein for confident

detection (8). After removal of duplicates, we

detected 2003 different proteins (table S1). An

additional 30 proteins were found that were

encoded by alternative or overlapping open

reading frames (8).

We detected 48% of the predicted proteins

(i.e., 1362 of 2862) from Leptospirillum group

II (table S2). This percentage exceeded those

of most prior proteomic studies of microbial

isolates (10, 12, 13). In part, this may reflect

the presence of cells in many different growth

stages, as well as microniches within the

biofilm (14). We also detected 270 Leptospi-

rillum group III, 84 Ferroplasma type I, 99

Ferroplasma type II, and 122 BG-plasma[proteins. In addition, we found 30 proteins on

unassigned archaeal scaffolds and 36 on un-

assigned bacterial scaffolds. The proportion of

proteins detected from each organism type

was similar to the proportion of cells from

each organism type in the biofilm (8). Most

proteins from low-abundance members were

probably in concentrations too low to be

detected by the presence of two peptides.

1Department of Environmental Science, Policy, andManagement, 2Department of Earth and PlanetaryScience, University of California at Berkeley, Berkeley,CA 94720, USA. 3Graduate School of GenomeScience and Technology University of Tennessee–Oak Ridge National Laboratory, 1060 CommercePark, Oak Ridge, TN 37830, USA. 4Chemical SciencesDivision, 5Life Sciences Division, Oak Ridge NationalLaboratory, Oak Ridge, TN 37831, USA. 6BiosciencesDirectorate, Lawrence Livermore National Laborato-ry, Livermore, CA 94551, USA. 7College of Pharmacy,Xavier University, New Orleans, LA, 70125, USA.

*To whom correspondence should be addressed.E-mail: jill@seismo.berkeley.edu

R E P O R T S

www.sciencemag.org SCIENCE VOL 308 24 JUNE 2005 1915

1

Supporting Online Material Materials and Methods Data

Annual data describing demersal fish distribution and abundance in the North

Sea (between 51-62° latitude) from 1977-2001 were taken from the English Groundfish

Survey (EGFS) programme. Species were included in analyses if they were caught at a

minimum of five stations each year, during at least ten years. Blue whiting

(Micromesistius poutassou), although not considered a demersal fish, was retained in

the dataset because the EGFS is considered to sample this species effectively in the

North Sea. In accordance with EGFS records, redfishes (Sebastes spp.) were combined,

as were argentines (Argentina silus and A. sphyraena). Abundance-weighted mean

annual latitudes and depths were derived for each species. For fishes with northern or

southern range limits in the North Sea, abundance-weighted annual boundary latitudes

were also calculated, based on the three most extreme stations of occurrence in each

year.

Bottom temperature data were obtained from the International Council for the

Exploration of the Sea, for 1° x 1° boxes in the North Sea. Annual means and five-year

running means (to allow for potential lagged effects) were calculated for winter (the

four coldest months, December-March) and summer (the four warmest months, June-

September). Data on the winter North Atlantic Oscillation Index (NAOI) (the

normalised sea level pressure difference between Gibraltar and Reykjavik, Iceland),

which is associated with changes in fish abundance, growth, and productivity (S1, S2)

were from Jones et al. (S3), with updated values provided by the Climatic Research

Unit, University of East Anglia (S4). Gulf Stream Index (GSI) data (measuring the

relative extent of the northern wall of the Gulf Stream along the east coast of North

2

America) were obtained from the Plymouth Marine Laboratory (S5). Average annual

abundances of the calanoid copepod species Calanus helgolandicus and C.

finmarchicus (which are major food sources for many juvenile fish) (S6), were provided

by the Sir Alister Hardy Foundation for Ocean Science.

Life history parameter estimates were compiled from the primary literature,

FishBase (S7), and regional fish guides (S8, S9). Growth rates and maximum lengths

were described as K and L∞ from the von Bertalanffy growth equation,

(where L)1( )( 0ttKt eLL −−

∞ −= t is length at age t, L∞ is the asymptotic length at which

growth rate is theoretically zero, K is the rate of growth towards this asymptote, and t0 is

the age at which length would theoretically have been zero (S10)). Maximum observed

length (Lmax) was included, because it was available for more species than L∞, and

serves as a useful surrogate for L∞, (S11). We also used mean age and length at

maturity (Tmat, and Lmat) for 50% of the population. For parameter estimates and

references, see Table S4. Values were used for North Sea populations where possible,

and otherwise were selected for the closest available region. Means were calculated

where sex-specific values were reported or multiple estimates were available, and mean

values were also used for the combined redfish and argentine species.

Statistical analyses

In order to assess the direct effects of warming on species distributions, winter

and summer temperatures (same-year and five-year running means) and abundance

were entered into multiple regressions for each species, using (a) mean latitude (b)

mean depth and, where applicable, (c) boundary latitude as dependent variables. Where

significant models included both abundance and environmental predictors, semi-partial

correlation coefficients were examined to determine the relative influence of warming.

3

We also examined less direct effects of warming on distributions, through

multiple regressions in which we again controlled for changes in abundance and

regressed the distribution variables against composite variables of warming rather than

temperatures. These new variables were the first and second factors from a Principal

Components Analysis of eight environmental variables that generally described

warming (winter temperature, five-year running mean winter temperature, summer

temperature, five-year running mean summer temperature, NAOI, NAOI with a 1-year

lag, GSI, and the ratio of C. helgolandicus abundance: C. finmarchicus abundance) and

were correlated with the position of species centres and boundaries. The first principal

component (PC1) explained 47% of the variance in these variables, and generally

described warming. PC2 accounted for a further 18% of the variance. Finally, we used

simple linear regression to examine changes in mean latitudes and boundary latitudes

over time.

We tested for life history differences between species whose mean latitudes

shifted and did not shift in relation to warming. Small sample sizes limited the use of

phylogenetically paired comparisons, although life history differences lay in the

expected direction for 6 of 9 pairs.

The effects of using mean values for life history parameters estimates for

redfishes and argentines were checked by redoing analyses using values for individual

species from each group, and by excluding these groups altogether. None of these

variations altered our findings.

4

Tabl

e S1

Sta

tistic

ally

sig

nific

ant m

ultip

le re

gres

sion

s of

the

effe

cts

of 3

mea

sure

s of

Nor

th S

ea w

arm

ing

on m

ean

dept

hs o

f 36

dem

ersa

l fis

hes,

197

7-20

01.

PC

1, fi

rst P

rinci

pal C

ompo

nent

from

PC

A o

f eig

ht e

nviro

nmen

tal v

aria

bles

(PC

1 ge

nera

lly d

escr

ibes

war

min

g).

Win

ter a

nd s

umm

er te

mp.

, 5-y

ear r

unni

ng m

ean

botto

m te

mpe

ratu

res

for D

ec-M

ar a

nd J

un-S

ep, e

xcep

t whe

re a in

dica

tes

a re

latio

nshi

p w

ith a

nnua

l mea

n su

mm

er o

r win

ter t

empe

ratu

re. W

here

abu

ndan

ce

was

als

o a

sign

ifica

nt p

redi

ctor

of d

istri

bion

, s den

otes

that

r2 and

P d

escr

ibe

the

squa

red

sem

i-par

tial c

orre

latio

n co

effic

ient

(to

iden

tify

the

prop

ortio

n of

var

ianc

e

in d

istri

butio

n ac

coun

ted

for b

y w

arm

ing)

.

Spec

ies

Com

mon

nam

e df

M

ean

dept

h (m

) SD

PC1

r2 P

Win

ter

tem

p.

r2 P

Sum

mer

te

mp.

r2

P

Ago

nus

cata

phra

ctus

Po

gge

22

46.7

6.

6 A

narh

ichu

s lu

pus

Atla

ntic

wol

ffish

21

103.

0 8.

0 A

rgen

tina

spp.

Arge

ntin

es24

13

8.1

7.

6

A

rnog

loss

us la

tern

a Sc

aldf

ish

1535

.5

4.3

4.

153a

0.34

0.01

7B

uglo

ssid

ium

lute

um

Sole

nette

22

33.8

3.9

2.17

00.

320.

005

2.76

5a 0.

250.

012

5.46

10.

280.

007

Cal

liony

mus

lyra

D

rago

net

23

55.7

12.4

6.88

20.

310.

005

17.7

68

0.35

0.00

213

.973

0.16

0.04

9E

chiic

hthy

s vi

pera

Le

sser

wee

ver

24

33.2

2.

9

3.30

00.

18

0.03

4E

utrig

la g

urna

rdus

G

rey

gurn

ard

2362

.66.

54.

223

0.42

0.00

110

.534

0.47

<0.0

0110

.809

0.

360.

001

Gad

icul

us a

rgen

teus

Si

lver

y po

ut

23

160.

1 9.

1

Gad

us m

orhu

a At

lant

ic c

od

23

81

.77.

95.

5024

0.

33s

<0.0

019.

692

0.

22s

0.00

113

.465

0.

31s

<0.0

01

Gly

ptoc

epha

lus

cyno

glos

sus

Witc

h24

12

0.5

10.3

Hip

pogl

osso

ides

pla

tess

oide

s Lo

ng ro

ugh

dab

23

97.5

4.

4

2.29

3

0.28

0.

009

5.95

1

0.35

0.00

26.

014

0.

270.

008

Lepi

dorh

ombu

s bo

scii

Four

spot

meg

rim24

14

8.3

9.8

Leuc

oraj

a na

evus

C

ucko

o ra

y 19

81

.2

14.6

19.9

860.

360.

005

Lim

anda

lim

anda

D

ab23

58.8

3.5

2.03

30.

340.

003

3.62

10.

200.

024

5.81

1

0.39

0.

001

Lo

phiu

s pi

scat

oriu

s An

gler

fish

23

99.4

10

.5

5.

841

0.28

0.00

9

14.0

490.

340.

002

Lum

penu

s la

mpr

etae

form

is

Snak

e bl

enny

12

10

1.1

21.3

61

.100

0.

87<0

.001

M

elan

ogra

mm

us a

egle

finus

H

addo

ck24

98

.53.

53.

999

0.

240.

013

Mer

lang

ius

mer

lang

us

Whi

ting

2476

.4

4.5

Mer

lucc

ius

mer

lucc

ius

Hak

e24

12

1.1

13.8

Mic

rom

esis

tius

pout

asso

u Bl

ue w

hitin

g 20

16

5.0

14.0

7.

889

0.33

0.00

712

.645

a 0.

400.

002

Mic

rost

omus

kitt

Le

mon

sol

e 24

80

.7

4.5

Mol

va m

olva

Li

ng24

129.

316

.3

Myx

ine

glut

inos

a H

agfis

h11

11

3.5

12.6

Ple

uron

ecte

s pl

ates

sa

Plai

ce23

53

.13.

5 1.

92

0.

31

0.00

53.

348

0.

170.

041

5.42

7

0.33

0.00

3P

olla

chiu

s vi

rens

Sa

ithe

24

143.

37.

1

Pse

tta m

axim

a Tu

rbot

13

43.7

6.6

Rhi

none

mus

cim

briu

s Fo

ur-b

eard

ed ro

cklin

g 22

91

.4

13.1

6.05

8

0.22

0.

024

16.7

90

0.31

0.00

5S

cylio

rhin

us c

anic

ula

Sm

all-s

potte

d ca

tsha

rk

20

83.8

9.

9 S

ebas

tes

spp.

R

edfis

h18

13

7.9

17

.1

8.

201

0.

27

0.02

415

.044

a 0.

390.

004

Sol

ea s

olea

C

omm

on s

ole

1337

.5

6.7

S

qual

us a

cant

hias

Sp

urdo

g19

69

.811

.8

Trig

la lu

cern

a Tu

b gu

rnar

d 19

33

.12

2.3

Tr

isop

teru

s es

mar

kii

Nor

way

pou

t 23

11

8.0

4.3

-1

.922

0.

200.

029

Tr

isop

teru

s lu

scus

Bi

b9

39.5

6.

5

Tr

isop

teru

s m

inut

us

Poor

cod

23

67

.1

8.6

4.12

60.

230.

018

11.2

460.

330.

003

5

Tabl

e S2

Sta

tistic

ally

sig

nific

ant m

ultip

le re

gres

sion

s of

the

effe

cts

of 3

mea

sure

s of

Nor

th S

ea w

arm

ing

on b

ound

ary

latit

udes

of 2

0 de

mer

sal

fishe

s, 1

977-

2001

. P

C1,

firs

t Prin

cipa

l Com

pone

nt fr

om P

CA

of 8

env

ironm

enta

l var

iabl

es (P

C1

gene

rally

des

crib

es w

arm

ing)

. W

inte

r and

sum

mer

tem

p., 5

-yea

r run

ning

mea

n bo

ttom

tem

pera

ture

s fo

r Dec

-Mar

and

Jun

-Sep

, exc

ept w

here

a indi

cate

s a

rela

tions

hip

with

ann

ual m

ean

sum

mer

or

win

ter t

empe

ratu

re.

Whe

re a

bund

ance

was

als

o a

sign

ifica

nt p

redi

ctor

of d

istri

butio

n, s d

enot

es th

at r2 a

nd P

des

crib

e th

e sq

uare

d se

mi-p

artia

l

corr

elat

ion

coef

ficie

nt (t

o id

entif

y th

e pr

opor

tion

of v

aria

nce

in d

istri

butio

n ac

coun

ted

for b

y w

arm

ing)

.

S

peci

es

Com

mon

nam

e df

Bou

ndar

y la

titud

e (°

N)

SD

PC

1r2

P

W

inte

r te

mp.

r2

P

S

umm

er

tem

p.

r2 P

Nor

ther

ly s

peci

es

A

narh

ichu

s lu

pus

Atla

ntic

wol

ffish

2156

.18

0.77

Gad

icul

us a

rgen

teus

Si

lver

y po

ut

2358

.50

0.59

Gly

ptoc

epha

lus

cyno

glos

sus

Witc

h23

55.7

00.

740.

293

0.15

s 0.

012

0.70

60.

17s

0.01

0.89

3

0.18

s

0.

007

H

ippo

glos

soid

es p

late

ssoi

des

Long

roug

h da

b 23

54

.11

0.28

0.

138

0.

24 0.

016

0.

545

0.

60s

<0.0

01 Le

pido

rhom

bus

bosc

ii Fo

ursp

ot m

egrim

24

59.0

11.

00Le

ucor

aja

naev

us

Cuc

koo

ray

1956

.80

0.38

Mel

anog

ram

mus

aeg

lefin

us

Had

dock

2353

.96

0.49

0.26

70.

28s

0.00

60.

379a

0.29

0.00

8M

icro

mes

istiu

s po

utas

sou

Blue

whi

ting

20

57.6

71.

720.

923

0.

29 0.

011

1.

452a

0.34

0.00

5

Mol

va m

olva

Li

ng23

56.4

11.

00P

olla

chiu

s vi

rens

Sa

ithe

2456

.89

0.88

Seb

aste

s sp

p.

Red

fish

1858

.46

0.83

1.39

1

0.38

0.00

5

Tris

opte

rus

esm

arki

i N

orw

ay p

out

24

54.8

50.

51

0.35

9a 0.

230.

015

Sou

ther

ly s

peci

esA

gonu

s ca

taph

ract

us

Pogg

e22

57.4

71.

07

Arn

oglo

ssus

late

rna

Scal

dfis

h15

54.9

10.

610.

542

0.

11

0.02

9

Bug

loss

idiu

m lu

teum

So

lene

tte23

55.2

50.

53E

chiic

hthy

s vi

pera

Le

sser

wee

ver

23

54.7

00.

370.

162

0.

19 0.

035

0.

500

0.

30 0.

004

P

setta

max

ima

Turb

ot13

55.9

70.

92S

olea

sol

ea

Com

mon

sol

e13

54.9

10.

78Tr

igla

luce

rna

Tub

gurn

ard

19

55.2

30.

85

-1.0

84

0.24

0.02

9Tr

isop

teru

s lu

scus

Bi

b8

54.2

30.

730.

549

0.88

<0.0

010.

997

0.55

0.01

52.

026

0.82

<0.0

01

6

Tabl

e S3

Sta

tistic

ally

sig

nific

ant l

inea

r reg

ress

ions

bet

wee

n tim

e an

d (i)

bou

ndar

y la

titud

es; a

nd (i

i) m

ean

latit

udes

of N

orth

Sea

dem

ersa

l fis

hes,

197

7-

2001

. *La

titud

e sh

ifted

sou

th w

ith w

arm

ing.

Arr

ows

indi

cate

whe

re a

bund

ance

has

incr

ease

d or

dec

reas

ed s

igni

fican

tly o

ver t

ime.

See

Tab

le 1

and

Tab

le

S2

for f

ull s

peci

es li

sts

and

rela

tions

hips

bet

wee

n di

strib

utio

ns a

nd w

arm

ing.

Spe

cies

Com

mon

nam

e df

La

titud

e (°

N)

SD

Y

ear

coef

ficie

nt

r2 P

La

titud

e re

late

d to

war

min

g?

Abu

ndan

ce

trend

ove

r tim

e (i)

Bou

ndar

y La

titud

es

N

orth

erly

spe

cies

Ana

rhic

has

lupu

s A

tlant

ic w

olffi

sh

2156

.18

0.77

0.

079

0.48

<0

.001

No

↓ G

lypt

ocep

halu

s cy

nogl

ossu

s W

itch

2455

.73

0.73

0.06

80.

46

<0.0

01Y

esLe

pido

rhom

bus

bosc

ii Fo

ursp

ot m

egrim

24

59.0

1 1.

000.

076

0.32

0.00

3N

oM

icro

mes

istiu

s po

utas

sou

Blu

e w

hitin

g 21

57.7

1 1.

69

0.11

1 0.

27

0.01

4Y

es

M

olva

mol

va

Ling

2356

.41

1.00

0.06

80.

24

0.01

5N

oTr

isop

teru

s es

mar

kii

Nor

way

pou

t

2454

.85

0.51

0.04

1

0.35

0.00

2Y

es

↑

Sou

ther

ly s

peci

es

A

rnog

loss

us la

tern

a S

cald

fish

1554

.91

0.61

0.

052

0.32

0.

022

Yes

Ech

iicht

hys

vipe

ra

Less

er w

eeve

r 24

54.7

2 0.

39

0.03

5 0.

43

<0.0

01Y

es

↑ Tr

isop

teru

s lu

scus

B

ib9

54.4

30.

940.

093

0.

80

0.00

1Y

es (ii

) M

ean

latit

udes

Ago

nus

cata

phra

ctus

P

ogge

2254

.67

0.90

-0

.074

0.37

0.

002

No

Cal

liony

mus

lyra

D

rago

net

2455

.44

0.69

0.

063

0.45

<0

.001

Yes

Eut

rigla

gur

nard

us

Gre

y gu

rnar

d 24

56.1

5 0.

36

0.03

6 0.

54

<0.0

01Y

es

↑ G

adus

mor

hua

Atla

ntic

cod

24

56.8

4 0.

36

0.03

5 0.

53

<0.0

01Y

es

↓ Le

pido

rhom

bus

bosc

ii Fo

ursp

ot m

egrim

24

60.5

1 0.

370.

021

0.17

0.04

1N

oLu

mpe

nus

lam

pret

aefo

rmis

S

nake

ble

nny

1256

.52

1.15

0.

107

0.63

0.

001

Yes

Rhi

none

mus

cim

briu

s Fo

ur-b

eard

ed ro

cklin

g 24

56.0

70.

670.

055

0.36

0.00

2Y

esS

cylio

rhin

us c

anic

ula

Sm

all-s

potte

d ca

tsha

rk

2058

.34

0.89

-0

.077

0.

35

0.00

4N

o ↑

Sol

ea s

olea

C

omm

on s

ole

1353

.72

0.66

-0

.049

0.

36

0.02

4Y

es*

Tr

isop

teru

s es

mar

kii

Nor

way

pou

t 24

58.5

9 0.

26

-0.0

19

0.29

0.

005

Yes

* ↑

7

Table S4 Life history parameter estimates for 36 North Sea demersal fish species. L∞,

asymptotic (maximum) length; K, growth rate from the von Bertalanffy equation; Lmax, maximum

recorded length; Tmat, age at which 50% of the population are mature; Lmat, length at which 50%

of the population are mature.

Species Common Name L∞ (cm)

Lmax (cm)

K (y-1)

Tmat (y)

Lmat (cm)

References

Agonus cataphractus Pogge 15 20 0.475 . . S8, S12, S13 Anarhichas lupus Atlantic wolffish 162.5 125 0.0435 6.5 55 S8, S14 Arnoglossus laterna Scaldfish 15 25 0.936 . 6.8 S8, S15, S16 Buglossidium luteum Solenette 10.75 12.5 0.573 3 7 S8, S15, S17 Callionymus lyra Dragonet 23 25 0.47 2.5 13 S8, S18 Echiichthys vipera Lesser weever . 17 . . . S19 Eutrigla gurnardus Grey gurnard 46 45 0.16 3 23 S8, S20 Gadiculus argenteus Silvery pout 15.5 15 0.693 . . S8, S21 Gadus morhua Atlantic cod 123.1 131.8 0.23 3.8 69.7 S11, S22 Glyptocephalus cynoglossus Witch 44 60 0.2 4.5 29 S20 Hippoglossoides platessoides Long rough dab 25 30 0.34 2.6 15 S7, S20 Lepidorhombus boscii Fourspot megrim 50 35 0.155 1.5 . S7, S23, S24 Leucoraja naevus Cuckoo ray 92 70 0.11 9 59 S8, S20 Limanda limanda Dab 27 40 0.26 2.3 13 S8, S20 Lophius piscatorius Anglerfish 106 74.6 0.18 4.5 61 S11, S20 Lumpenus lampretaeformis Snake blenny . 50 . 3 20 S8 Melanogrammus aeglefinus Haddock 68.3 75.5 0.19 2.5 33.5 S22 Merlangius merlangus Whiting 42.4 44.9 0.32 1.5 20.2 S11, S22 Merluccius merluccius Hake 105 135 0.184 6.75 51.75 S8, S25 Micromesistius poutassou Blue whiting 37.1 34 0.23 2.3 25.1 S7, S22 Microstomus kitt Lemon sole 37 60 0.42 4 27 S8, S20, S26 Molva molva Ling 183 200 0.118 6.5 90 S8, S27 Myxine glutinosa Hagfish . 80 . . 25 S8 Pleuronectes platessa Plaice 54.5 95 0.11 2.5 26.6 S8, S22 Pollachius virens Saithe 177.1 130 0.07 4.6 55.4 S8, S22 Psetta maxima Turbot 69.6 100 0.2497 4.5 49 S8, S15, S17, S28 Rhinonemus cimbrius Four-bearded rockling 36 40 0.2 3 25 S8, S20 Scyliorhinus canicula Small-spotted catshark 88 100 0.2 5 58 S8, S20 Sebastes marinus Redfish 74.4 100 0.0615 11 35 S8, S29 Sebastes viviparus Norway haddock 36 35 0.07 20 12.5 S8, S20 Solea solea Common sole 45.3 60 0.363 4 29 S8, S15 Squalus acanthias Spurdog 90 105 0.15 6.5 67 S8, S20 Trigla lucerna Tub gurnard 68.15 75 0.1524 . . S8, S30, S31 Trisopterus esmarkii Norway pout 23 25 0.52 2.3 19 S8, S22 Trisopterus luscus Bib 42.35 46 0.211 2 22.5 S17, S32 Trisopterus minutus Poor cod 20 40 0.51 2 15 S8, S20

8

References S1. M. J. Attrill, M. Power, Nature 417, 275 (2002). S2. G. Ottersen et al., Oecologia 128, 1 (2001). S3. P. D. Jones, T. Jónsson, D. Wheeler, Int. J. Climatol. 17, 1433 (1997). S4. T. Osborn, North Atlantic Oscillation (www.cru.uea.ac.uk/~timo/projpages/nao_update.htm, 2002). S5. A. H. Taylor, Latitude of the Gulf Stream (www.pml.ac.uk/gulfstream, 2002). S6. L. S. Parsons, W. H. Lear, Prog. Oceanogr. 49, 167 (2001). S7. R. Froese, D. Pauly, FishBase (www.fishbase.org, 2002). S8. B. J. Muus, J. G. Nielson, Sea Fish (Scandinavian Fishing Year Book, Hedehusene, Denmark, 1999). S9. P. J. Miller, M. J. Loates, Fish of Britain and Europe (Harper Collins, London, 1997). S10. R. J. H. Beverton, S. J. Holt, On the Dynamics of Exploited Fish Populations (Ministry of Agriculture, Fisheries and Food, London, 1957). S11. N. H. Denney, S. Jennings, J. D. Reynolds, Proc. R. Soc. London Ser. B 269, 2229 (2002). S12. S. Le Gall, Vie milieu 20A, 153 (1969). S13. E. Ehrenbaum, Eier und Larven von Fischen. Nordisches Plankton (Lipsius & Tischer, Kiel, 1905). S14. G. Beese, R. Kändler, Ber. Deut. Wiss. Komm. 20, 21 (1969). S15. C. Déniel, J. Fish Biol. 37, 149 (1990). S16. O. Giovanardi, C. Piccinetti, “Biology and fishery of the scaldfish Arnoglossus laterna (Walbaum 1792) in the Adriatic Sea” (FAO Fish. Rep. 290, FAO, Rome, 1983). S17. R. J. Knijn, T. W. Boon, H. J. L Heessen, J. F. G. Hislop, “Atlas of North Sea Fishes” (ICES Coop. Res. Rep. 194, ICES, Copenhagen, 1993). S18. H. W. van der Veer et al., Neth. J. Sea Res. 26, 139 (1990). S19. E. Tortonese, in Checklist of the fishes of the north-eastern Atlantic and of the Mediterranean (CLOFNAM), J. C. Hureau, T. Monod, Eds., vol II, (UNESCO, Paris, 1986), pp. 951-954 . S20. S. Jennings, S. P. R. Greenstreet, J. D. Reynolds, J. Anim. Ecol. 68, 617 (1999). S21. R. Letaconnoux, Bull.Inst. Océanogr. 913 (1947). S22. S. Jennings, J. D. Reynolds, S. C. Mills, Proc. R. Soc. London Ser. B 265, 333 (1998). S23. R. Castilho, M. T. Dinis, K. Erzini, Fish. Res. 16, 339 (1993). S24. J. R. Fuertes, Invest. Pesq. 42, 241 (1978). S25. G. Belloc, Rev. Trav. Inst. Pêch. Marit. 2, 231 (1929). S26. B. B. Rae, The Lemon Sole (Fishing News, London, 1965). S27. G. Joenoes, Ber. Deut. Wiss. Komm.16, 129 (1961). S28. T. Mengi, Ber. Deut. Wiss. Komm. 7, 119 (1963). S29. V. I. Travin, Dok. Akad. Nauk. SSSR 77, 741 (1951). S30. J. Collignon, Bull. Inst. Pêch. Maroc 16, 3 (1968). S31. C. Papaconstantinou, et al., “Investigations on the abundance and distribution of demersal stocks of primary importance in the Thermatikos Gulf and the Thracian Sea (Hellas)” (Tech. Rep., North Aegean Sea Series 4., National Centre for Marine Research, Athens, 1994). S32. U. Labarta, M.J. Ferreiro, “Age and growth of the Galician coast pouting (Trisopterus luscus L.). Preliminary data.” (ICES C.M. G:65, ICES, Copenhagen, 1982).