fishing impacts on the marine inorganic carbon cycle

8/8/2019 Fishing Impacts on the Marine Inorganic Carbon Cycle

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Fishing impacts on the marine inorganic carbon cycle

Simon Jennings1,2* and Rod W. Wilson3

1Centre for Environment, Fisheries and Aquaculture Science, Pakefield Road, Lowestoft, NR33 0HT, UK; 2School

of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK; and 3School of Biosciences, Hatherly

Laboratories, University of Exeter, Exeter, Devon EX4 4PS, UK

Summary

1. Teleost fish excrete precipitated carbonate and make significant contributions to the marine inor-

ganic carbon cycle at regional and global scales. As total carbonate production is linked to fish size

and abundance, fishing is predicted to affect carbonate production by modifying fish abundance

and size-structure.

2. We draw on concepts from physiology, metabolic ecology, life history theory, population

dynamics and community ecology to develop, validate and apply analytical tools to assess fishingimpacts on carbonate production. Outputs suggest that population and community carbonate pro-

duction fall rapidly at lower rates of fishing than those used as management targets for sustainable

yield.

3. Theoretical predictions are corroborated by estimated trends in carbonate production by a

herring population and a coral reef fish community subject to fishing. Our analytical results build

on widely applicable relationships between life history parameters and metabolic rates, and can be

generalized to most fished ecosystems.

4. Synthesis and applications. If the maintenance of chemical processes as well as biological process

were adopted as a management objective for fisheries then the methods we have developed can be

applied to assess the effects of fishing on carbonate production and to advise on acceptable rates of

fishing. Maintenance of this ecosystem service would require lower rates of fishing mortality than

those recommended to achieve sustainable yield.

Key-words: community, ecosystem approach, ecosystem services, fish carbonate, fisheries,

management, population

Introduction

Fisheries managers tend to focus on achieving sustainable and

profitable fisheries while minimizing impacts on non-target

species and habitats (Sinclair & Valdimarsson 2003). However,

fisheries also impact ecosystem services and these impacts needto be assessed to determine whether they should be managed.

One important ecosystemservice provided by teleost fishis car-

bonate production, as a recent (conservative) estimate suggests

they contribute 315% of new oceanic carbonate production

globally per year and that this may account for 77262%

of carbonate dissolution in the top 1000 m of the ocean,

with implications for the acidbase balance in the upper ocean

(Wilson et al. 2009). Higher than average rates of fish carbon-

ate production and dissolution are expected in shelf seas and

upwellings, as >50% of global fish biomass occurs in these

regions (Jennings et al. 2008).

Teleost fish living in salt water precipitate carbonates in the

intestine and subsequently excrete them in mucus-coated tubes

or pellets and in the faeces (Walsh et al. 1991; Wilson et al.

1996; Wilson, Wilson, & Grosell 2002; Grosell 2006). Follow-

ing excretion, the organic parts of the tubes, pellets or faeces

rapidly degrade, leaving inorganic crystals of calcium carbon-ate (Walsh et al. 1991). Carbonate precipitates are formed

whether or not the fish are feeding (Wilson et al. 1996; Taylor

& Grosell 2006) because the essential process of drinking

seawater results in the supersaturation of calcium and magne-

sium carbonates in the intestine (Wilson et al. 2002; Wilson &

Grosell 2003). Walsh et al. (1991) suggested that carbonate

excretion might make a significant contribution to the

inorganic carbon cycle, and this has since been confirmed by

the global analysis of Wilson et al. (2009). Fish carbonates

have a higher magnesium content and are therefore expected

to have greater solubility than other marine carbonates. This

would result in faster dissolution with depth, providing a novel

explanation for much of the increase in titratable alkalinity

within upper 1000 m of the ocean (Wilson et al. 2009).*Correspondence author. E-mail: [email protected]

Journal of Applied Ecology 2009, 46, 976982 doi: 10.1111/j.1365-2664.2009.01682.x

2009 The Authors. Journal compilation 2009 British Ecological Society


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The rate of carbonate production by fish is assumed to be

proportional to the seawater drinking rate and metabolic rate

(Takei & Tsukada 2001). This is because osmoregulatory pro-

cesses such as drinking and active ion transport serve to coun-

terbalance passive ion and water fluxes (primarily at the gills)

and these passive fluxes (water loss and ion gain in marine fish,and the opposite in freshwater fish) are directly proportional to

gill ventilation and perfusion and therefore proportional to the

oxygen uptake rate and metabolic rate (Nilsson 1986; Gonz-

alez & McDonald 1992). As the metabolic rates of individuals

and species vary with environmental temperature and body

size (Clarke & Johnston 1999; Glazier 2005), the temperature

of the surrounding environment as well as the size composition

and total abundance of a fish population or community, will

determine the total rate of carbonate production.

Fishing takes place in all the global oceans and has substan-

tially modified the structure of fish populations and communi-

ties. Of those factors that influence rates of carbonate

production by fish communities, both total biomass and size

structure are affected by fishing (Quinn & Deriso 1999; Bianchi

et al. 2000; Shin et al. 2005). Comparisons among areas subject

to different fishing intensities and temporal comparison within

areas where fishing effort has increased over time, have both

shown that increased fishing mortality is associated with

decreases in total biomass and a shift in the size distribution

from larger to smaller individuals (Bianchi et al. 2000; Shin

et al. 2005).

Here, we develop, validate and apply methods for describing

relationships between fishing intensity and carbonate produc-

tion by fish populations and communities. These methods can

be used to predict how the size composition and abundance offish communities changes in response to fishing mortality and

the consequent impact on rates of carbonate production. Our

new methods provide a quantitative approach for assessing

whether the management of renewable resources should focus

on chemistry as well as biology, an important step in incorpo-

rating concerns about the sustainability of ecosystem services

into environmental management.

Materials and Methods

The analyses comprise fourstages: (i) development of a model linking

fish carbonate production to body mass and temperature, (ii) devel-

opment of a model of fishing effects on population carbonate produc-

tion, (iii) development of a model of fishing effects on community

carbonate production, and (iv) validation and application of the

models, based on data that demonstrate fishing-related changes in

the body size composition and abundance of a population and

community.

C A R B O N A T E P R O D U C T I O N

A model that links the rate of carbonate production to fish body size

and temperature was used to estimate rates of carbonate production.

This is based on the observation that rates of drinking by fish are

directly proportional to metabolic rate, and that drinking rates deter-

mine rates of carbonate production (Takei & Tsukada 2001; Wilsonet al. 2002; Taylor & Grosell 2006). Given this indirect link between

carbonate production and metabolic rate, changes in relative rates of

carbonate production with temperature can be approximated with

the Arrhenius relationship. This relationshipprovidesa good descrip-

tion, but not a causal explanation, of the effects of temperature on

metabolic rate(e.g. Clarke& Johnston 1999). TheArrhenius relation-

ship

R AeE=kT eqn 1

links the rate coefficients of a chemical reaction (R) to the absolute

temperature T, where A is a prefactor, E is the activation energy of

the reaction and k is the Boltzmann constant (or the Gas constant

when E is expressed in molar units). Over biologically relevant tem-

perature ranges E is assumed to be independent of temperature and

the minor temperature dependenceofA is regarded as negligiblecom-

pared with the temperature dependence of the e)E kTterm (Clarke &

Johnston 1999).

Takingthe natural logsof the Arrhenius equation gives:

loge R Ek1T loge A eqn 2

thusa plotof logeR vs T)1 is a straightline of slope Ek and intercept

logeA. This approach was used to estimate )Ek from the data com-

pilation of Clarke & Johnston (1999) that listed temperature and pre-

dicted resting (standard) metabolic rates for a range of fish species at

body mass 50 g. Therelationship washighly significant F = 81451,88

(P < 00001), slope ()Ek) was )472736 (95% C.I. )36864 to

)57683) and theintercept was 1427(95%C.I. 10591795).

We assumed that the scaling of metabolism with body mass (W),

both within and among species, could be approximated as W075. In

reality, the value of the exponent can vary within and among species

(Clarke& Johnston 1999; Glazier 2005) but we consider W075 an ade-

quate approximation for developing a generically applicable

approach, and the exponent could easily be modified in the subse-

quent equations if species-specific data were available. We combined

the relationship between body mass and metabolism with the Arrhe-

nius equation describing temperature effects following the approach

of Gillooly et al. (2002). Assuming that the rate of metabolism is pro-

portional to the rate of carbonate production C (given the effects of

metabolism on drinking rate; Takei & Tsukada 2001)

C aqaW0:75AeE=kT eqn 3

where a is a constant. Constantsa andqwere added to correct experi-

mentally measured mass specific rates of carbonate production (Wil-

son et al. 2009) for the ratio between carbonate production in activeand resting fish (a) and the relatively higher resting metabolism and

drinking rates of fish species living in the water column (q) (Clarke &

Johnston 1999; Takei & Tsukada 2001). Alpha exceeds one in wild

fish because metabolic rate, and hence drinking rate and carbonate

production, rise above resting (experimental) levels during normal

activity (Kerr 1982). Carbonate production per unit mass can thus be

expressed as

C=W aqaW0:25AeE=kT eqn 4

To fit equation (4) to data for resting unfed benthic fish, the values of

a and q were both set to one. This equation was fitted to data for car-

bonate production per unit mass by Gulf toadfish Opsanus beta andEuropean flounder Platichthys flesus, as recorded experimentally in

Fishing impacts on the carbon cycle 977

2009 The Authors. Journal compilation 2009 British Ecological Society, Journal of Applied Ecology, 46, 976982


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resting unfed fish (Walsh et al. 1991; Wilson et al. 2002; Taylor &

Grosell 2006; Taylor et al. 2007), to determine constants a and A, giv-

ing the equation

C=W aq9:81 108W0:25e47271=T eqn 5

where carbonate production per unit mass is expressed as l mol C

kg)1 h)1 (molarC = g C12), Wis bodymass in g and Tis tempera-

ture in Kelvin (C+273) (Wilson et al. 2009). We set the valueofa to

25 to q 24 based on the differences between resting and activity

metabolism and the relative activity levels of bottom living and pela-

gic fishes reported in Wilson et al. (2009). For simplicity, and given

the very limited data currently available to parameterise the model,

we assume the same model applies within and among species. How-

ever, the general formof the model willallow it to be re-parameterised

if additional data on rates of carbonate productionare collected.

F I S H I N G E F F E C T S O N P O P U L A T I O N S

Total carbonate production by a population at a given temperaturedepends on size composition and abundance. Changes in carbonate

production by a cohort (year class) with time are a function of the

changes in the number of individuals owing to mortality and the

changes in the size of individuals owing to growth. The number of

individuals in a cohort at time t can be estimated using (e.g. Quinn &

Deriso 1999)

Nt N0eMFt eqn 6

where N0 is the number of individuals present at t = 0, F is fishing

mortality and M is natural mortality. The von Bertalanffy Growth

Equation can be used to describe W at time t as a function of the

asymptotic mass W(e.g. Quinn & Deriso 1999)

Wt W11 eKtt0 3 eqn 7

where t0 is the time when W is theoretically zero and K is the Brody

growthcoefficient.

Following equation 3, carbonateproduction at time t will be

Ct NtaqaW0:75t Ae

E=kT eqn 8

where Nt is the number of individuals present at time t as determined

from equation (6) and Wt is determined from equation (7). Assuming

temperature is constant through the cohort lifespan, the time when a

cohort is producing the maximum amount of carbonate tCmax can

thus be determined by substituting (6) and (7) into (8), differentiatingwithrespect to t andsolving for tCmax whenthe first derivative is set to

zero.

tCmax t0 loge 1 9

4

K

M F

1=Keqn 9

Equation (9) can be substituted into (7) to give the weight of fish in a

cohort when they are producing the maximum amount of carbonate

WCmax andthe equation for WCmax reduces to

WCmax W1 1= 1M F

2:25K

3eqn 10

The advantage of equations (9) and (10) is that for F = 0, the

MKratio, which is relatively constant among many fish populations

(Beverton 1992), can be used to predict the time and body mass when

an unexploited cohort is producing most carbonate. This allows the

application of the method when Mand Karenot known separately.

Observed values of tCmax and WCmax in fished populations can be

compared with theoretical values for unfished populations, providing

an indicator of the relative impacts of fishing on carbonate produc-

tion.

As most fish populationassessments areage based, a summation of

Ct across age classes up to the maximum age tmax provides an ade-

quate assessment of total carbonate production throughout the life-

span of a cohort Ctotp (and hence the carbonate production of a

populationat steady state). This is given by

Ctotp Xtmaxt0

F MtNtaqaW075t Ae

E=kT eqn 11

The methods of population-based analysis were applied to the her-

ring population in the North Sea, for which there are long-term age-

structured data and very large fluctuations in abundance and mortal-

ity over time (ICES 2007). We estimated carbonate production based

on a full age-structured population assessment for the fished popula-

tion and for the population in the absence of fishing. The life history

parameters of the herring population were W = 332g, t0 = )11,

K = 04 and mean M = 031, with age-specific M based on ICES

(2007) in the age-structured analysis. Mean sea temperature in the

North Sea was taken as 105 C (ICES, unpublished data).

F I S H I N G E F F E C T S O N C O M M U N I T I E S

To assess the potential effects of fishing on carbonate production by

fish communities we modified a model that captures the direct and

indirect effects of fishing on community abundance and size structure

(Pope et al. 2006). The model predicts interrelationshipsbetween fish-

ing, population and community dynamics that are supported by

empirical analysis and uses 15 parameters to describe a 13 speciesfish community, where species are defined by their maximum body

size (asymptotic length L) and size-related life history parameters.

An overall Facts on all species and can be modified by defining spe-

cies and size selectivity. The parameter values followed the key run

of Pope et al. (2006) but the exploitation pattern was modified so that

all species were fished at the same F. This pattern is indicative of

exploitation in many multispecies fisheries where small and large

fishes are targeted. The model is intended to mimic the effects of fish-

ing in a shallow (typically


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of areas subject to different levels of fishing effort thatincluded lightly

or unfished areas (Jennings & Polunin 1997).

Fish abundance was determined by underwater visual censusin ten

reef fishing grounds on the western coast of Kadavu Island, Fiji. The

boundaries of each fishing ground enclose areas of reef where people

from specific villages have exclusive rights to fish. As a result, varia-

tions in human population density and reef area among grounds

mean that they are subject to a range of fishing intensities. Reef fishes

in the families studied do not move extensively among grounds and

thus their abundance is determined by the recruitment of larvae from

the plankton, natural mortality and local fishing intensity. Further

details of the study areas, associatedfish communities, datacollection

andprocessingare provided in Jennings & Polunin (1997).

All fish census work was conducted in 1995 and 1996 and 144 spe-

cies were censused. Abundances were determined at seven randomly

selected replicate sites in each of the fishing grounds. At each site, the

abundance and size of census species 8 cm length was estimated

within 12 adjacent census areas of 7 m radius by counting each fish

and estimating its length to 1 cm. Species in each census area were

recorded sequentially, with the most active species being first. Whena count for one species was complete, all further movements of that

species were disregarded. Fish lengths were converted to mass from

published lengthmass relationships. Carbonate production was cal-

culated from mass at a temperature of 275 C, the annual mean

water temperature (NOAA 2007).

An index of fishing intensity in each fishing ground was calculated

by dividing the number of people in the villages that have fishing

rights in the fishing grounds by the length of reef front. In Fijian vil-

lages, all villagers have fishing rights and so the population approxi-

mates the number of fishers and consumers (Jennings & Polunin

1997). Human population data were obtained from the most recent

census. The length of reef front was measured on aerial photographs

or navigational charts.

Results

The theoretical analysis of relationships between the body

weight at which a cohort has maximum carbonate production

WCmax, asymptotic weight W and fishing mortality F

showed that WCmax was 216% ofW in the absence of fish-

ing and decreased to 60% from the value when

F = 0. Total carbonate production by the population (Ctotp)

as a proportion ofCtotp when F = 0 is almost linearly related

to WCmaxW (Fig. 1c).

Estimated carbonate production per recruit by the North

Sea herring population fluctuated from 1960 to 1996 (Fig. 2a)

and, when CR was expressed as a proportion of CRF = 0, it

was negatively correlated with fishing mortality (Fig. 2b).

Total carbonate production varied substantially among

cohorts and among years, with both trends tending to precede

decreases in total population biomass (Fig. 3).

The relationship between the age at maximum carbonate

production tCmax or WCmax and Ffor herring (Fig. 4) showedthat tCmax or WCmax would be expected to occur early in life

and at low body mass if the population were fished at

F = 068; the mean F in the period 19601996. At the target

F of 025 (ages 26) which applies when spawning population

biomass is >13 106 tonnes (ICES 2007), carbonate produc-

tion at tCmax or WCmax would be more than double the value at

F = 068. The predicted tCmax or WCmax for the population

are broadly consistent with the values calculated from the age-

structured assessment, with the age 0 group always having

highest estimated carbonate production from 1960 to 1996 and

average mass of this group being 13 g.

The model of the effects of fishing on carbonate production

suggested that the greatest decreases in community carbonateproduction would occur at relatively low rates of mortality

Fishing mortality

Rela

tiveC/RorY/R

00

02

04

06

08

10

(a)

(b)

(c)

00 02 04 06 08 10

Fishing mortality

00 02 04 06 08 10

WCmax

/W

WCmax/W

000

005

010

015

020

025

005 010 015 020 025

Re

lativeCtotp

00

02

04

06

08

10

Fig. 1. Relationships between (a) body mass at maximum carbonate

production as a proportion of asymptotic mass (WCmaxW) and

fishing mortality, (b) relative carbonate production per recruit (con-

tinuous line) or yield per recruit (solid line) and fishing mortality and

(c) relative carbonate production by the population (CtotpCtotpF=0)

and body mass at maximumcarbonate production as a proportion of

asymptotic mass (WCmaxW). We assumed W = 1000, k = 03

and MK = 15.




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(Fig. 5a). At F = 05, relative carbonate production had fallen

to about 60% of that in the unfished community. At higher

rates of F, there was relatively little change in the rate of car-bonate production. The rate of decrease in carbonate produc-

tion with fishing was slightly lower than the rate of decrease in

total biomass (Fig. 5a). The mean mass of individuals in the

modelled community broadly declined with increasing fishing

mortality while the mean rate of carbonate production per unit

mass showed a corresponding increase (Fig. 5b). In these simu-

lations, F = 025 corresponded to the multispecies Fat which

the maximum sustainable yield could be taken from the most

vulnerable species, while maximum multispecies yield would

be taken at F > 10.

Fishing intensity in the Fijian reef fisheries was expressed in

terms of effort rather than F, owing to the absence of data

describing population-specific exploitation rates. The range of

fishing effort spanned more than an order of magnitude with

one ground infrequently fished. Community biomassdecreased rapidly with low and increasing levels of fishing

effort but stabilized at higher effort (Fig. 6a). Estimated car-

bonate production was highest in the least frequently fished

ground, on average 20% higher than at other grounds, where

production was lower and more variable, and did not show a

clear relationship with fishing intensity (Fig. 6b). Carbonate

production per unit biomass increased with fishing effort,

probably reflecting the dominance of smaller fishes that pro-

duce more carbonate per unit mass in the more heavily

exploited grounds (Fig. 6c).

Discussion

For populations and communities, lower rates of fishing mor-

tality than those associated with obtaining high and sustain-

able yields lead to substantial reductions in population

carbonate production. Relatively small changes in rates of

carbonate production at higher fishing mortalities imply that

current management interventions intended to achieve high

and sustainable yield will have limited effects on carbonate

production. The analytical methods and hence the results

depend on widely applicable relationships between mortality,

population and community size structure and metabolism, and

we therefore expect they can be generalized to populations and

communities in most fished ecosystems. In general, fishingmortality reduces total carbonate production and CR in the

Fishing mortality F

00 02 04 06 08 10 12 14 16 18

C/Ra

sproportionC

/RF=

0

015

020

025

030

035

Year class

1960 1970 1980 1990

C/R(

g)

06

07

08

09

10

11(a)

(b)

Fig.2. Predicted carbonate production per recruit for the North Sea

herring stock for the year classes from 1960 to 1996 (a) and the rela-

tionship between CR as a proportion CRF = 0 and thefishing mor-tality (Fforages 36) in each of thesecohorts (b).

Year class or year

1960 1970 1980 1990

CaCO3(103t

onnesyears1)

0

20

40

60

80

100

120 Populationbiomass(106tonnes)

0

1

2

3

4

5

CaCO3 by cohortsCaCO3 by yearspopulation biomass

Fig.3. Trends in estimated CaCO3 production by the North Sea

herring population by cohorts (closed circles, solid line) and by years

(open circles, broken line) from 1960 to 1996 Total population

biomass over the same time period is shown with the dotted line and

small circles.

WCm

ax t

Cmax

00

05

10

15

20

25

Fishing mortality F

00 02 04 06 08 100

50

100

150

200

Fig.4. Relationship between WCmax (solid line) and tCmax (broken

line) andfishingmortalityfor the North Sea herring population.

980 S. Jennings & R. W. Wilson



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population because the abundance of fished cohorts will fall

more rapidly with age. However, carbonate production per

unit mass increases with fishing mortality in fished populations

and communities because these are dominated by smaller indi-viduals.

The model that links size and temperature to carbonate

production assumed that the intercepts of relationships

between R and C and W were the same for all species. This

would not be the case in reality, as active species of pelagic fish

(e.g.tunas) have higher metabolic rates than less active bottom-

dwelling species (e.g. groupers, flatfishes) at a given body size

and temperature (Clarke & Johnston 1999) and this would

influence their drinking rates. However, the model structure is

sufficiently general that it could easily be parameterised with

species-specific data as they become available. In the case of

the community analysis, larger bottom-dwelling species do

tend to be more vulnerable to fishing than smaller pelagic

species and changes in their relative abundance could lead to

relative increases in the rate of carbonate production per unit

biomass at different fishing intensities. The predicted trend in

carbonate production with fishing will also be influenced by

the proportion of teleosts (carbonate producing) and elasmo-

branchs (not carbonate producing) in the fish community.

Elasmobranchs tend to have relatively large body sizes and to

be more vulnerable to fishing owing to their low intrinsic rates

of increase (Stevens et al. 2000), so it might be expected that

they will form a smaller proportion of total biomass at high

fishing mortality. This would exaggerate any predicted

decrease in carbonate production.

The relationship between WCmax and W provides a linearindicator of the extent to which relative carbonate production

Fishing effort (persons km2 reef front)

0 50 100 150 200 250 300010

012

014

016

018

020

45

50

55

60

65

70

75

80

85

Biomass(

gm

2)

C

pro

duc

tion

(g

m

2y

ears

1)

C

pro

duc

tionperuni

tbiomass

(gg

1)

20

30

40

50

60

70

80(a)

(c)

(b)

Fig. 6. Relationships between (a) biomass, (b) carbonate production

and (c) carbonate production per unit mass and fishing effort on

Fijian reef fishing grounds. Vertical bars are 95% confidence inter-

vals.

00

02

04

06

08

10

Carbona

tepro

duc

tion

(C)as

proport

ion

CF=

0

Biomass(B)asproportionBF=0

00

02

04

06

08

10

(a)

(b)

Fishing mortality F

00 02 04 06 08 10 12 14

00 02 04 06 08 10 12 14

Mean

individua

lmass

(g)

26

28

30

32

34

36

38

4042

44

08

09

10

11

12

13

C

orbonateproductionperunit

biomass(relative)

Fig. 5. (a) Changes in total carbonate production (continuous line)

and relative biomass (broken line) of a fish community as a function

of changes in the rate of fishing mortality The rate of carbonate pro-

duction (Ctotc) and biomass (B) are expressed as a proportion of their

values with no fishing (F = 0). (b) Relationship between mean indi-

vidual body mass (continuous line) or carbonate production per unit

biomass (broken line) and fishing mortality in the modelled fish com-

munity.




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per recruit and total carbonate production of a population at

steady state is influenced by fishing. WCmax can be calculated

without a natural mortality for the species concerned, by tak-

ing advantage of the MK ratio, and thus provides a simple

method for assessing the relative effects of fishing on carbonate

production. The disadvantage of this simple technique overage-structured assessment ofCR is the assumption of a single

value ofMin all age classes, when fish typically exhibit higher

Mwhen younger. If size or age-related natural mortality data

are available for some well-studied populations, our analyses

show that it would be straightforward to modify existing popu-

lation assessment methods to predict the effect of various rates

of fishing mortality on Ctotp and CR.

This analysis suggests that fishing will alter the rates of car-

bonate production by fish populations and communities, but

the analysis would be refined by significant additional research,

to include (i) obtaining carbonate production data for a wider

range of species, body sizes and temperatures to better para-

meterise the model linking these variables, (ii) accounting for

differences in the relative activity levels of fishes in the carbon-

ate production modeland in the predictions of changes in com-

munity structure, (iii) accounting for the effects of fishing on

carbonate production by the smaller size-classes of fish, and

(iv) accounting for changes in relative abundance of teleosts

and elasmobranchs in the model of fishing impacts. In addi-

tion, while the analyses provide a method for giving manage-

ment advice on the effects of fishing on an ecosystem service

other than food production, considerable work would still be

needed to identify realistic management objectives for this

service. Such objectives would ultimately be a matter of choice

for society, albeit informed by science (Jennings 2007). Ourunderstanding of the wider consequences of changes in the

rates of fish carbonate production on ocean chemistry and the

consequences for biota will need to be improved to inform any

debate on objectives.

Acknowledgements

We thank Andrew Clarke for providing the compilation of teleost oxygen con-

sumption data from Clarke & Johnston (1999) and John Pope for allowing us

to modifythe size-based model of Pope etal. (2006)for thisanalysis.S.J. thanks

UK DFID (formerly ODA) and NERC for funding the collection of the fish

community data used in this analysis, and the EC and Defra for funding this

research. R.W.thanks BBSRC andThe Royal Societyfor fundingfundamental

studieson intestinalcarbonateproduction in marine fish.

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Received7 March2009;accepted 9 June 2009

Handling Editor: NickDulvy

982 S. Jennings & R. W. Wilson


fishing impacts on the marine inorganic carbon cycle

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