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Fisheries Research 148 (2013) 18– 26

Contents lists available at ScienceDirect

Fisheries Research

j our nal ho mep ag e: www.elsev ier .com/ locate / f i shres

inking physiological, population and socio-economic assessments oflimate-change impacts on fisheries

na Norman-Lópeza,∗, Éva Plagányib, Tim Skewesb, Elvira Poloczanskaa,arren Dennisb, Mark Gibbsb, Peter Baylissb

CSIRO Climate Adaptation Flagship, CMAR, PO Box 2583, Brisbane, QLD 4001, AustraliaCSIRO Wealth from Ocean Flagship, CMAR, PO Box 2583, Brisbane, QLD 4001, Australia

a r t i c l e i n f o

rticle history:eceived 18 October 2011eceived in revised form 18 February 2012ccepted 20 February 2012

eywords:limate

nput–output analysisanulirus ornatusorres Straitisk assessment

a b s t r a c t

Climate change is postulated to influence marine resources worldwide with consequent ramifications forthe management of commercially important fisheries. There is a need to understand the likely impacts ofclimate change affecting the biology of fisheries at each of the different levels: (a) individual (reproductivepotential, larval settlement, spatial distribution); (b) population (carrying capacity, productivity, spatialdistribution); (c) multi-species (replacement of one fishery by another) and (d) ecosystem (dependentpredator species, shifts in community composition). When addressing these problems it is importantto integrate information across a range of dimensions pertaining to the resource and stakeholders,using a combination of biological, economic and social research elements. This is necessary for a bet-ter understanding of the likely changes to catches and in turn the possible socio-economic implications.We assessed the impact and likelihood of a range of plausible climate impacts on a number of lobsterlife history parameters, using the Torres Strait tropical rock lobster Panulirus ornatus as a case study. Thehypothesised high risk effects of climate change were implemented through modifications to the lob-ster stock assessment model. Projected catches and an input–output model of the Australian economy

were used to determine the flow-on effects of climate-change impacts affecting this lobster fishery. Wehighlight the potential of this combination of quantitative and qualitative approaches as a pragmatic firststep to exploring climate-change impacts on a fishery and summarise implications for management. Ourresults suggest that there may be positive as well as negative consequences. Our integrated methodol-ogy is a step towards linking the interrelation between different variables and fishery productivity, andquantifying the resultant socio-economic effects to fishers, their communities and national economies.

. Introduction

Fish populations respond to a variety of natural and anthro-ogenic pressures, which coupled with density-dependent pro-esses result in changes to stock status and resultant managementesponses for targeted species. Climate change is an additionalmpact on top of existing pressures that will affect fish stocks inifferent ways. Studies have concentrated on the direct (growth,eproductive capacity, mortality, distribution, etc.) and indirectstructure of ecosystems) consequences of climate change on

arine species, populations and fishery production. However,oncurrent pressures from other stressors including fishing, pol-

ution, ecological and socio-economic interactions can reduce theesilience of marine fish stocks and as such intensify the effects fromlimate change. A more holistic approach is to evaluate the likely

∗ Corresponding author.E-mail address: ana.norman@csiro.au (A. Norman-López).

165-7836/$ – see front matter. Crown Copyright © 2012 Published by Elsevier B.V. All rioi:10.1016/j.fishres.2012.02.026

Crown Copyright © 2012 Published by Elsevier B.V. All rights reserved.

effects from climate change together with other factors impactingmarine systems (Hollowed et al., 2009). This could provide a moreaccurate representation of future changes in fishery productivitywhich in turn can be used to assess the expected socio-economiceffects on dependent fishing sectors, and on regional and nationaleconomies (MacNeil et al., 2010).

We outline a methodology for linking and quantifying the bio-logical and socio-economic implications of climate change on afishery. The biological effects from climate change are consid-ered with respect to individuals, populations and the ecosystem.Using a lobster stock assessment model these effects are integratedwith other natural and anthropogenic effects already impactingthe fishery. This model then projects future changes to catchesthat would allow the fishery to continue operating sustainably(Plagányi et al., 2009). The employment and income effects follow-

ing changes to catches are then estimated for the dependent fishingsectors, the region and the national economy using an input–outputmodel (Norman-López and Pascoe, 2011; Norman-López et al.,2011).

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A. Norman-López et al. / Fish

Rock lobsters may be particularly vulnerable to climate changeiven their apparent sensitivity to associated physical param-ters such as temperature, winds, ENSO event frequency andcean acidity (Caputi et al., 2010; Frusher et al., 2007). Givenheir dual role as a commercially highly valuable resource andheir “keystone species” role in maintaining ecosystem structureBarkai and Branch, 1988; Barkai and McQuaid, 1988; Barrett et al.,009; Haley et al., 2011; Shears and Babcock, 2002; Ye et al.,008), they are an important species to focus our understandingf possible climate-change effects, and appropriate managementesponses.

The Torres Strait tropical rock lobster (Panulirus ornatus) (TRL)as selected for our study because of the long time series of

mpirical information and relatively good understanding of lob-ter ecology (Pitcher et al., 1992; Ye et al., 2005). Further, thisshery is unusually complex: it overlaps the international bor-er between Papua New Guinea and Australia and is exploitedy two different sectors within Australia; indigenous inhabi-ants (Islanders hold traditional inhabitant boat – TIB licenses)nd non-traditional fishers (non-Islanders operate as transfer-ble vessel holders – TVH) (Fairhead and Hohnen, 2007). Thetrong dependency of local fishers on rock lobster is likely to fur-her complicate the management of the resource under climatehange.

The stated objectives for this fishery include maintaining thepawning stock at levels that meet or exceed the level requiredo produce the maximum sustainable yield, to optimise the valuef the fishery and in accordance with the Torres Strait Treaty,o protect the traditional way of life and livelihood of traditionalnhabitants, particularly in relation to their traditional fishing forRL. The fishery is currently the most important fishery to Islandersnd provides significant financial independence for Island com-unities in the region. More than 15% of employment in Islander

ommunities is estimated to come directly from lobster fishingArthur, 2005). Tropical rock lobster is also a highly valuable fish-ry for non-Islanders, with this sector’s numbers restricted toromote the socio-economic development and maintain the tra-itional lifestyle of Torres Strait Islanders. In 2008–2009, only 10on-Islander vessels were operating in the fishery compared to 279

slander vessels. Nevertheless, non-Islander vessels caught nearly3% (99 t) of the total Australian catch (228 t) because they are

arger, and apply more effort. In addition, unlike Islander vessels,on-Islander vessels supply most catches live obtaining a higherarket price and hence revenue. Overall the total value of the fish-

ry in 2008–2009 was estimated to be AU$7 million (Ward et al.,009).

Climatic changes to sea surface temperatures, ocean acidifica-ion, sea level rise, cyclone intensity, rainfall, river flows and soorth, are expected to affect catches (Hobday et al., 2008). Changesn Torres Strait lobster catches will impact the fisheries’ profitabil-ty, fishers’ wages and employment. This in turn will change theshers’ expenditure/consumption on other industries’ productsroduced within and outside the Torres Strait region. In addi-ion, changes in catches will require the fishing industry to adjustts demand for fishing inputs (i.e., fuel, labour, repairs), and theupply of lobster products to intermediate (i.e., processors) andnal demand sectors (i.e., restaurants) located in the Torres Straitegion, other Australian regions and internationally. This will haveubsequent socio-economic flow-on effects in terms of produc-ion, incomes and employment to other upstream and downstreamndustries.

In this paper, we assessed the plausible impact of climate

hange operating on a range of levels on the P. ornatus popula-ion, summarise the implications for management, and quantifyhe resultant socio-economic effects to fishers, their communitiesnd national economies.

Research 148 (2013) 18– 26 19

2. Methods

The possible biological and socio-economic effects of climatechange on the P. ornatus fishery in Torres Strait were investigatedin three steps. In the first step, we assessed the potential impact onseveral rock lobster biological response variables from changes inan array of climate change-related physical variables and ecolog-ical components. Potential impacts were then assigned to a “risk”category (high, medium or low) depending on the likelihood ofthe climate-related change and the size of the potential impact(or consequence) on the biological response variable. From this,two scenarios were outlined and their combined impacts on thelobster biological response variables were estimated; a high riskimpact scenario and a combined high and medium risk impactscenario. The latter scenario was combined because the mediumrisk impacts are additional to the high risk impacts. In the secondstep, the hypothesised high risk and high plus medium risk sce-narios of potential impacts were implemented as changes in rocklobster production through modifications to a lobster stock assess-ment model. Finally, in the third step, projected catches obtainedfrom the lobster stock assessment model were incorporated toan input–output model of the Australian economy to determinethe income and employment flow-on effects to the regional andnational economy.

2.1. Step 1. Assessing risks of climate impacts on the rock lobsterpopulation

Our estimation of risk is similar to traditional risk assess-ment approaches, however, in this case, risk is “risk of impact”,not “risk of negative impact”, as we consider both detrimen-tal and advantageous outcomes. Risk rankings for potentialimpacts on lobster biological variables from climate-changerelated changes in physical variables were formulated from thelikelihood of the climate-related change and the consequencethat the change has on the lobster biological response vari-able.

The likelihood and the projected changes to several physicalvariables in Torres Strait due to climate change were obtained fromthe literature (Table 1). The projections were considered for short-term to 2030 as this has higher management relevance than longerterm projections. Projections of global warming were consideredonly for the mid–high range greenhouse gas emission scenario(A1B) (IPCC, 2007) as there is little deviation by 2030 among differ-ent emission scenarios. Marine ecosystems will also be indirectlyimpacted through flow-on effects from changes to primary produc-tivity and disruption to food webs (Poloczanska et al., 2007), and weintegrated these impacts where possible. Likelihood scores of thephysical parameter changing were assigned based on confidenceratings by experts in the field (Poloczanska et al., 2007); >70% like-lihood was considered as high, <30% low and intermediate valuesmedium (Table 1).

The potential impacts of changes to physical variables andrelated changes to three critical habitats (deep epibenthic com-munities, coral reefs and seagrass beds) on a range of life historyvariables (growth, mortality, movement, distribution and repro-duction) were assessed separately for three rock lobster life historystages (larvae, juvenile and adult) in Torres Strait. Each potentialimpact was described and quantified to the fullest extent possibleusing information from literature reviews, unpublished experi-mental studies and expert consultation. Considerable uncertaintyexists for most combinations of physical and (lobster) biological

variables. We took the approach, in this case, of using all avail-able information to outline likely potential impacts for use in thesubsequent stages of the analysis. Where no information was avail-able, that combination of physical and biological variables was

20 A. Norman-López et al. / Fisheries Research 148 (2013) 18– 26

Table 1Climate-change related changes to different physical parameters in Torres Strait by 2030 under scenario A1B.

Physical parameter Projections 2030 Likelihood (expert weighting) Source and Justification

Sea surfacetemperature (SST)

+1 ◦C 80% SSTs around Australia have warmed (+0.7 ◦C) since the early 20thcentury and are highly likely to continue warming (CSIRO, 2007;Lough, 2009). Greater warming expected in shallow areas (<30 m)

Sea level rise 5–15 cm 80% Recent (1993–2008) sea level rise is greatest to the north of Australia;global sea levels projected to continue rising during the 21st centuryand beyond (Church et al., 2009)

Current systems,Torres Strait

No change 25% Large internal tidal currents with westerly set in winter and easterlyset in summer largely driven by tidal phase differences between CoralSea and Arafura Sea, and wind fields during monsoons. Pattern appearsstable in down-scaled BlueLink projections (Oke et al., 2007)

Current systems, CoralSea Gyre

+5% 10% Coral Sea Gyre and East Australian Current (EAC) driven by the SouthPacific Gyre. EAC, the western boundary of the South Pacific Gyre, isprojected to strengthen by 5% by 2030 driven by latitudinal shift in thewesterly wind fields (Cai, 2006; Cai et al., 2005)

Storms and cyclones 2030: small increase inintensity

10% Global projections for cyclones are uncertain but some suggestion ofincreases in intensity with warming (Meehl et al., 2007)

Rainfall −10% to +10% 20% Rainfall impacts river flow which in turn affects lobsters. Projections ofrainfall highly uncertain in northern Australia (CSIRO, 2007). Somestudies indicate little freshwater incursion into Torres Strait fromrivers (Hemer et al., 2004)

Ocean acidification Very small change, <0.05 units 50% High variability in coastal zone (Dai et al., 2009). Still expected todecline around Australia (Poloczanska et al., 2007). River run-off couldlessen buffering effect

Phytoplankton 50–100% 20% Uncertain but modelling indicates increased phytoplankton

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ot assigned a potential impact. Interactions between potentialmpacts were taken into consideration by the application of anterative approach to formulating potential impacts: all potentialmpacts were assessed in a cyclical fashion several times and poten-ial interactions between them were accounted for in the finalssessment. In this fashion, final outcomes for combined poten-ial impacts for each change in physical variable were formulated.he relative consequence of the potential impacts was a subjec-ive assessment based on expert opinion – generally impacts thatesulted in greater than a 5% change in a biological response wereonsidered as a high consequence, and greater than 2% as a mediumonsequence. The ratings criteria used were arbitrary, but took intoccount that relatively small changes in growth or survival rateould potentially have a large effect on overall population produc-ivity.

The “risk” of each potential impact was estimated as the productf the likelihood of the climate related change in the environmen-al variable (Table 1) and the consequence of the potential impactf the biological variable into high, medium and low for each com-ination of physical and biological variables (Table 2). Once riskalues were assigned, two impact scenarios were outlined, one con-aining the high risk impacts only (Scenario I) and the second theigh and medium risk impacts (Scenario II).

.2. Step 2. Assessing climate-change impacts using a stock

ssessment model

Monitoring of the Torres Strait rock lobster population was ini-iated in 1989 when a diver survey was conducted of 542 allocated

able 2isk matrix for assigning risk categories to impacts based on likelihood andonsequence.

Risk Consequence

L M H

LikelihoodL, <30% L L MM, 30–70% L M HH, >70% M H H

productivity in Coral Sea (Brown et al., 2010)

sites (Pitcher et al., 1992). Since 1994, around 100 sites have beensurveyed annually in Torres Strait. The surveys provide fishery-independent information on lobster recruitment and abundance,as well as on habitat composition. The information obtained fromthe diving surveys and commercial catches by Australian (Islandersand non-Islanders) and Papua New Guinean fishers are integratedin a lobster population model. The purpose of the model is to assessthe resource status and productivity to inform management recom-mendations.

In this analysis, the stock assessment model of Plagányi et al.(2009) was modified to simulate likely future climate-changeimpacts. The projected catches are computed using the same tar-get fishing mortality rate (0.15 year−1) and harvest control rules(a hockey-stick form with fishing mortality decreasing linearly inproportion to biomass decreases below the target level, and zero atthe limit reference point) as in the current stock assessment. Twoclimate-change scenarios and a no-climate-change scenario (base)are considered and catches projected to 2030. The climate impactssummarised under the two scenarios (high risk (I) and high andmedium risk (II)) were implemented in the population model byscaling the natural mortality parameters as well as the estimatedrecruitment levels upwards or downwards using the percentages asgiven in Table 3. The von Bertalanffy growth co-efficient (but notmaximum size parameter Linf) was assumed to increase linearlyover time to represent faster individual growth rates or maximumsize achieved (see Table 3) (Dennis et al., 1997; Skewes et al., 1997).Gradual increases in growth over time were implemented as incre-mental annual increases commencing from 2009. To account forthe increased fishing pressure that would result in younger-agedlobsters (because a larger proportion of them would have grownabove the minimum legal size limit and hence be available to fish-ers), the fishing selectivity parameter was increased appropriately(one-third increase for first age class). The stock assessment modelassumes the management and structure of the rock lobster fishery,together with other environmental impacts unrelated to climate

change and economic complexities remain constant over time. Inthis way, this study highlights the effects from climate change tothe fishery without other factors potentially overshadowing theresults.

A. Norman-López et al. / Fisheries Research 148 (2013) 18– 26 21

Table 3High and medium risk of climate impacts on different life stages of the rock lobster population in Torres Strait. Values obtained from literature and expert opinion.

Risk Life stage Lobster componentimpacted

Explanation

HighLarvae Growth Development and growth are temperature sensitive (Caputi et al., 2010; Wahle and Fogarty, 2006). Higher

SST will speed growth up to physiological tolerances. Faster growth will mean faster development andlarvae ready to metamorphose into settling puerulus when they encounter the outer Great Barrier Reef.This will likely increase larval supply back to Torres Strait, and the estimated net impact from a 1 ◦Caverage rise in SST is estimated to be of the order of about ∼5%

Juvenile Growth Warmer SST generally means faster growth up to a physiological tolerance (Wahle and Fogarty, 2006).Regional lobster growth studies in Torres Strait have identified a growth vs temperature relationship, thevon Bertalanffy growth co-efficient, k, changing from 0.44 year−1 to 0.573 year−1 with a change in averagetemperature from 25.7 ◦C to 27.1 ◦C (Skewes et al., 1997). Assuming k changes in proportion to averagetemperature (and not Linf), and that no physiological tolerance is reached under current projections to2030 (Dennis et al., 1997), then with 1 ◦C change projected by 2030, k(2030) = 1.095k(current). Given publishedgrowth rates for Torres Strait rock lobsters (Phillips et al., 1992) this change in growth means theminimum legal size (MLS) (115 mm CL) is reached 1.75 months earlier, and 2+ lobsters in May areapproximately 7.5% larger by carapace length and 26% larger by weight in May (mid season)

Adult Growth Assuming a similar change in the growth co-efficient k, and that no physiological tolerance is reached,then we would expect an increase in adult lobster size. However, adult lobsters (post maturation moult)do not contribute a significant proportion of the Torres Strait fishery (Skewes et al., 1994; Ye et al., 2008),as they do on the Queensland North East Coast (Pitcher et al., 2005)

MediumMortality Higher SST could increase mortality rates due to physiological thresholds, though interactions with other

factors (i.e., higher phytoplankton) could ameliorate this factor to some extent. Estimate reduction oflarval survival by 2.5%

Juvenile Mortality Higher SST, physiological thresholds, disease and parasites may result in higher mortality, thoughpredation pressure will be reduced due to faster growth. Estimated an increase in mortality rate of 10%

Habitat: seagrass Seagrass habitats may be negatively impacted by increased SST (mostly shallow) and sea level rise (drivenby light and species niches) (Connolly, 2009). However, settling juvenile lobsters rely more on subtidalseagrass for habitat. Estimated an overall negative impact on lobster recruitment of ∼5%

Adult Reproduction Faster growth and bigger lobsters will mean an increased fecundity due to strong size fecundity SST c10%

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.3. Step 3. Estimating socio-economic effects to the fishery,egion and national economy

Projected catches represent the total across the three fisheryectors (TVH, TIB, PNG) and we assume that the relative allocationsetween sectors remain constant in future, and focus on the Aus-ralian sector only. For the latter, changes to rock lobster catchesre likely to have socio-economic implications to both Islander andon-Islander fishers in Torres Strait. This in turn will have subse-uent flow-on socio-economic effects to other intermediate andnal demand sectors in the region of Torres Strait and the rest of theational economy. The projected catches to 2030 in step 2 followingwo climate-change risk scenarios and a base scenario (no-climate-hange) were incorporated to an input–output (I–O) model of theustralian economy to determine the direct income and employ-ent effect to fishers and the flow on effects. The use of nationalultipliers to estimate flow on effects for Torres Strait will result in

ow on effects being over-estimated. This is because regional mul-ipliers are smaller than national multipliers for which they are aart.

The I–O model is static and it is built on the notion that produc-ion of output by industries (i.e., fish by fisheries) requires inputsi.e., fuel, boats, etc.) from other industries. In turn the manufac-urers of these goods require goods from their suppliers and son, thereby creating a multiplier effect. The I–O model used in thisnalysis has been adapted from Norman-López and Pascoe (2011).heir model was derived from the latest Australian national I–Oable available (2004–2005), produced by the Australian Bureauf Statistics. In their national I–O model the non-fishing sectorsre aggregated into a total of 9 sectors and the fishing sectors to aotal of 12. One of the fishing sectors represents the national pro-

uction of rock lobster. In this analysis, the Torres Strait Islandernd non-Islander rock lobster fisheries were disaggregated fromhe national rock lobster sector. The disaggregation of the Islandernd non-Islander rock lobster fisheries was based on: the values

ould also result in an earlier and longer reproductive season. Estimate increased

of production provided by ABARE (2008); cost structure informa-tion obtained from cost and earnings (Fairhead and Hohnen, 2007);and the distribution of production to other intermediate sectorsand final consumers (Arthur, 2005; Fairhead and Hohnen, 2007)and expert opinions. For the scenario analysis, input costs andprices were assumed to remain constant to 2030 allowing track-ing of the effects that changes in catches will have in the wholeeconomy under no-climate-change (base scenario) and the twoclimate-change scenarios. Prices and costs are predicted to varyover time, but these changes and their implications for the demandof rock lobster products are not understood, and we therefore prefernot to speculate.

3. Results

3.1. Assessing risks of climate effects on the lobster population

Biological variables that were assessed as having a high ormedium risk of being impacted by climate change are summarisedin Table 3. Growth in all life history stages (larval, juvenile andadults) was assessed as being at high risk due principally to a likelyincrease in sea temperatures. This effect was assessed as beingmostly positive based on experimental studies demonstrating theenhancement of growth by warmer sea surface temperatures upto 30 ◦C (Dennis et al., 1997; Skewes et al., 1997). Medium riskscontained both positive and negative effects. Positive effects wereassociated with an increase in larval growth due to projectedincreases in primary production in the Coral Sea (Brown et al.,2010), and faster adult growth and bigger lobsters resulting in anincrease in adult reproduction. Negative effects were associatedwith increased larval and juvenile mortality related to higher sea

surface temperatures and detrimental effects on the juvenile lob-sters’ seagrass habitats.

Following the classification of those life history variables andcritical habitats that could experience high or medium risks to

22 A. Norman-López et al. / Fisheries Research 148 (2013) 18– 26

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Base case catch Scenario I Scenario II

Fig. 1. Summary of modelled changes to projected P. ornatus catches (t) when using a deterministic scenario and assuming a constant future fishing mortality and whenc s I an

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omparing the base-case no-climate-change scenario with climate-change scenario

limate change, two impact risk scenarios were considered. In Sce-ario I, only high risk impacts are considered. Scenario II considersigh and medium risk impacts.

Scenario I: Lobster growth increased by 7.5% (carapace length,mplemented as incremental annual increases commencing from009) and larval supply increased by 5%.

Scenario II: Lobster growth increased by 7.5% (carapace length),arval supply increased by 7.5%, juvenile mortality rate increasedy 10%.

.2. Stock assessment model projections

The stock assessment model was used to estimate changes torojected P. ornatus spawning biomass (t) assuming a constantuture fishing mortality and when comparing the base-case sce-ario with climate-change risk scenarios I and II. Historical Torrestrait lobster catches show large inter-annual fluctuations due tohe fishery effectively catching one single cohort (2–3-year-old lob-ters) and hence depending on the numbers of lobsters in the 3 ageroups. Given the extremely fast growth of the Torres Strait rockobster, impacts on growth are rapidly translated into impacts onield. The projected fluctuations in resource biomass are therefore

consequence of the large fluctuations that are observed histor-cally and are replicated by the model over the historic periodommencing in 1989. The changes in future biomass over andbove the natural level of variability can be used to assess the nethanges to lobster catches (computed by applying a fixed targetortality fishing rate). In this way, likely climate-induced changes

n individual growth, mortality and reproduction rates are inte-rated to the population and hence fishery level. Fig. 1 presents theariation in catches under no-climate-change (base scenario) andnder the two risk scenarios (I and II). The positive effects assumednder Scenario I produce higher projected catches compared tohe no-climate-change scenario. However, the mixed positive andegative effects assumed under Scenario II result in lower pro-

ected catches compared to the no-climate-change scenario. Theeterministic projection shown is illustrative only, and the actual

uture fluctuations may be larger than shown due to environmentaluctuations or climate change effects that interact in a non-linear

ashion with existing environmental drivers of recruitment vari-bility.

d II as described in the text.

3.3. Income and employment distribution effect of climate changein the rock lobster fishery

Climatic changes to rock lobster catches will have a directeffect on the employment and income (wages and profits) ofIslander (TIB) and non-Islander fishers (TVH), and in turn havea flow on effect to other sectors through changes in demandfrom these two fishing groups. We divide the flow on effectsto these “other sectors” into intermediate sectors (intermediateeffect) and final consumers (consumption effect). The estimatedincome and employment flow on effects from Islander and non-Islander fishers will vary depending on how total catches are likelyto change under a no climate change (base scenario) and two cli-mate change risk scenarios. The changes in catches were consideredfor the years 2004–2005 and 2029–2030. The year 2004–2005was chosen following the availability of data in the input–outputmodel for this particular year. The income and employment (directeffects) received for the different scenarios by Islander and non-Islander fishers were obtained directly from the I–O model. Theincome and employment flow on effects to other intermedi-ate sectors (i.e., fuel, processors, retailers) and consumption (i.e.,households, exports) were estimated by multiplying the directincome and employment values in Islanders’ and non-Islanders’fisheries by the appropriate income and employment multiplier(Table 4).

The direct and flow on income effects from changes to Islanderand non-Islander rock lobster catches under no-climate-change(base scenario) and two climate-change risk scenarios are pre-sented in Fig. 2. Overall, expected higher catches (Scenario I)generated higher income effects and vice versa (Scenario II). Directincome effects are higher in the non-Islander fishery than theIslander fishery when comparing across the three scenarios. Thisis not surprising since the non-Islander fishing boats are more effi-cient (they are larger, apply more effort using less boats and catchnearly as much as the Islanders). Therefore the wages received bynon-Islander fishers are higher than those obtained from Islanderfishers. However, the flow on income effects received by othersectors (intermediate and consumption effects) from non-Islander

fisheries are lower compared to flow on effects received fromIslander fishers. This is because non-Islander vessels are mostlyoperated by large companies that assign specific wages to fish-ers and keep profits separate. Non-Islanders’ income flow to other

A. Norman-López et al. / Fisheries Research 148 (2013) 18– 26 23

0.0

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wages(direct effect)

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intermediateeffect

consumptioneffect

Islanders Non islanders

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ion

base scena

Fig. 2. Changes in income to the Islander fishing industry, the interme

Table 4Intermediate and final consumption (type 2) income and employment multipliersin the base and scenario analysis.

Rock lobster fishery inTorres Strait

Base (no-climate-change)

Scenario I Scenario II

Income multipliersIslanders• Intermediate effect 0.655 0.550 0.799• Final consumptioneffect

1.071 1.003 1.165

Non-Islanders• Intermediate effect 0.555 0.466 0.677• Final consumptioneffect

1.006 0.949 1.086

Employment multipliersIslanders• Intermediate effect 0.023 0.023 0.023• Final consumptioneffect

0.038 0.042 0.034

Non-Islanders

itct(hfi

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a

• Intermediate effect 0.343 0.343 0.343• Final consumptioneffect

0.602 0.676 0.532

ndustries will only depend on the expenditure from the wageshey receive. On the other hand, the Islander skippers do not allo-ate a specific wage to themselves or family members, insteadhey live from the profits obtained from their fishing operationsFairhead and Hohnen, 2007). Therefore, Islander fishers have aigher flow on income effect on other sectors than non-Islandershers.

The direct and flow-on employment effects from changes toslander and non-Islander rock lobster catches under no-climate-hange (base scenario) and two climate-change risk scenarios areresented in Fig. 3. Overall, expected higher catches (Scenario I)enerated higher employment effects and vice versa (Scenario II).he direct employment effects (fishers employed in the Islandernd non-Islander fisheries) and flow on employment effects (peo-le employed in other sectors) stay constant for all scenarios underhe assumption that the capacity in the fishery remains the same

o 2030.1 The flow on employment effects for the final consump-ion sectors vary for the different climate-change scenarios. This isecause the change in Islanders’ and non Islanders’ fisheries income

1 If the capacity remains the same, the amount of inputs from other industriesnd the flow on effects would remain the same.

rio 1 scenario 2

diate and final consumption sectors for the different scenarios.

and the flow on income effects will change the demand for goodsand services from other sectors which in turn will have to adjustproduction and employment levels in order to satisfy demand.

Finally, we summarise our results to identify whether theIslander and non-Islander income and employment flow on effectsremain in the Torres Strait region or go to the rest of the nationaleconomy. The flow on effects will be important for the TorresStrait regional economy given the rock lobster fishery is an impor-tant source of income and employment to the region, and thereare few other opportunities. On the other hand, the employmentand income effects from the Torres Strait lobster fishery outsideTorres Strait are likely to be negligible compared to the incomeand employment opportunities from other industries. Fig. 4 sum-marises the net income and employment effects in the Torres Straitregion and elsewhere in the Australian economy for the base caseand two risk scenarios. Non-Islanders’ full income and employ-ment effects (direct, intermediate and consumption effects) wereassumed to be spent outside of Torres Strait. We based this assump-tion on the fact that non-Islander vessels are operated by largecompanies located outside Torres Strait and the majority of thecrew also live and spend their income outside Torres Strait. As somecrew are Islanders living in Torres Strait and they spend their wageslocally our assumption of full income and employment effects fromthe non-Islander group leaving Torres Strait is a slight overestima-tion. With respect to Islander fishers, we considered the direct andconsumption flow on effects obtained from Islanders’ fisheries arelikely to remain in the Torres Strait because Islanders living in Tor-res Strait do not tend to travel outside the region. In contrast, theintermediate flow on effects from Islander fisheries are likely tomove outside Torres Strait. This is because many goods and ser-vices are produced elsewhere in Australia and imported into TorresStrait. Overall, the underlying assumptions have opposing impactson the estimated flow on effects for Torres Strait. Using nationallevel multipliers for the Islander effect overstates this impact how-ever in assuming that all the non-Islander effects are external tothe region the true flow on effect this group has in the region isconsequently understated.

Based on these assumptions, the full income and employmenteffects received by the Torres Strait regional economy are slightlyless than the full income and employment effects leaving the

region. Nevertheless, the estimated full income and employmenteffects in Torres Strait are large relative to the size of the regionaleconomy and hence the extra benefits or losses under climatechange could be considered substantial

24 A. Norman-López et al. / Fisheries Research 148 (2013) 18– 26

0

100

200

300

400

500

600

Direct effect Intermediateeffect

Consumption effect

Direct effect Intermediateeffect

Consumptioneffect

Islanders Non islanders

Empl

oym

ent (

pers

ons)

e sce

e inter

4

mrftpmfcfimc

aaccip

bas

Fig. 3. Changes in employment for the Islander fishing industry, th

. Discussion

The need to improve and maintain the management and use ofarine resources to ensure their continued sustainability is cur-

ently complicated by concerns as to how to additionally accountor climate-change impacts. Central to this is a need to understandhe underlying effects of changes in physical variables on systemroductivity and functioning, to enable strategic planning as toanagement responses to changing climate. We present results

rom a pragmatic approach that can be used to explore likelylimate-change impacts on a fishery, when using only slight modi-cations to existing methodology rather than undertaking detailedechanistic modelling coupled to downscaled physical climate-

hange models.Rather than selecting climate impacts in isolation, this study

ttempted to use a comprehensive multiple impact assessmentpproach that considered the effect of a full suite of climate-change

omponents against a suite of life history components and criti-al habitats, taking into account the interactions between positedmpacts where possible. As there is uncertainty around changes inhysical parameters and the potential impacts of those changes, we

0

2

4

6

8

10

12

Base Scen 1 Scen 2

Torres Strait

Inco

me

(AU

$m)

Income Employ ment

Fig. 4. Net income (broad bars) and employment (narrow bars) effects to Torres Stra

n 1 scen 2

mediate and final consumption sectors for the different scenarios.

took a risk assessment approach to rank potential impacts based onthe likelihood of the change and its consequence. This qualitativerisk assessment was then used to inform and prioritise scenarios fortesting using the stock assessment model. This approach will likelybe iteratively updated in the future as more information comes tohand.

A range of modelling approaches have been described forincorporating climate and environmental variability (Keyl andWolff, 2008). In our study, several scenarios proved readily imple-mentable in a standard stock assessment population dynamicsmodel (for example, increases in the natural mortality rate and lar-val supply). Some others required only minor changes to the model– for example, the von Bertalanffy rate parameter was assumed toincrease linearly over time as a proxy for modelling increases insomatic growth rate of individual lobsters. This approach allowedintegration of climate-change effects at the individual level to theoverall population level, as well as simultaneous testing of a mul-

titude of impacts – thereby permitting integration of the net effectof impacts operating in opposite directions and at different scales.

Climate change is often presented as resulting in predominantlynegative effects. Our analysis suggests climate change could either

Base Scen 1 Scen 2

Non-Torres Strait

0

100

200

300

400

500

600

700

Empl

oym

ent (

pers

ons)

it and the rest of the Australian national economy for the different scenarios.

eries

bFaicecSoti(rSppcttD2bibota

stTctoolefimca

dcpviHfiatits

cacnTfiaapc

A. Norman-López et al. / Fish

ring higher catches (Scenario I) or lower (Scenario II) by 2030.rom these scenarios the net income change from the Islandernd non-Islander lobster industries together could approximatelyncrease (Scenario I) or decline (Scenario II) by $4 million whenompared to the no climate change scenario (base scenario). Nev-rtheless, this study has ignored the likely effects from climatehange on fishing infrastructure and gear and demand for Torrestrait rock lobster. We expect an increased frequency and intensityf cyclones, sea level rise and other extreme events may increasehe risk of displacement of Islander communities, damage to fish-ng infrastructure and gear and reduce the time spent out at seaDasgupta et al., 2009; Hobday et al., 2008). Also, Torres Straitock lobster is likely to compete with similar products in markets.imulations on the effects from climate change on changes in sup-ly to world seafood markets are hence necessary to understandossible price changes of Torres Strait rock lobster and their impli-ations to fishers and consumers. Studies have already examinedhe implications of climate change on global markets for agricul-ure, timber and fish meal (Julia and Duchin, 2007; Mendelsohn andinar, 2009; Merino et al., 2010; Reilly et al., 1994; Sohngen et al.,001). Unfortunately, for Australian fisheries, the substitutabilityetween Australian seafood products and between Australian and

nternational seafood products, must be understood before possi-le price changes can be simulated. Given the lack of informationn the impacts that cyclones are likely to have on fishing infrastruc-ure and possible market changes, we have preferred not to makessumptions on changes in demand and costs.

Non climate change effects that will in reality add extra pres-ures in the fishery have also been ignored. As an example, by 2030,he management arrangements and reallocation of quota betweenIB and TVH will be different, there could be new non climatehange related environmental and anthropogenic effects impactinghe lobster industry and complex interactions in the global econ-my will most likely alter exchange rates, market regulations andverall the interactions between products in markets. Neverthe-ess, we are unaware what the changes are likely to be and thextent of the impact in the Torres Strait fishery. We have there-ore chosen to focus on the effects from climate change on thendustry’s productivity rather than assume impacts that might or

ight not happen and could potentially overshadow the climatehange effects for which we have a comprehensive multiple impactssessment approach.

Climate change, as manifested through changes to oceanic con-itions over seasons, annual cycles and decades, has the ability tohange the distribution and productivity of a range of populationsresently utilised for capture fisheries. Our study aims to pro-ide insights into the possible implications to yields, and flow-onmpacts to communities dependent upon specific capture fisheries.owever equally important is how managers and participants insheries go about managing the associated changes to allocationsnd wealth that accompany changes in the distribution and produc-ivity of target stocks. Whilst it is beyond the scope of this study tonvestigate how the specific impacts of climate change will needo be managed in this case, it is worthwhile briefly considering thecale and scope of this issue.

In the study presented here, the region under considerationomprises a mix of non indigenous (non-Islander) commercialnd local scale indigenous (Islander) fishers that operate underomplicated multi-jurisdictional governance arrangements. Theon-Islander commercial fishers (TVH) are based mostly outsideorres Strait and travel large distances whilst Islander commercialshers (TIB) operate locally. In one sense, the mixed property right

rrangements between Islander and non-Islander fishers can actu-lly be reasonably resilient to gross changes in the distribution androductivity of target species. This is because the mixture of remoteommercial and local commercial fishers can be flexible enough

Research 148 (2013) 18– 26 25

to adjust fishing effort and location. However, in adapting to thesechanges there are likely to be winners and losers in terms of the gen-eration and distribution of wealth. For example, if the distributionof particular species such as rock lobsters relocate from the inshorefishing grounds of local-range fishers to distant or even deeperwaters, it may be relatively straightforward for longer-ranging non-Islander commercial fishers to maintain the same overall level ofharvesting to compensate for effort unable to be maintained byIslander fishers operating locally. In other words, the total yieldfrom the fishery may be maintained but the distribution of wealthgenerated by the fishery may change substantially.

Understanding the adaptive capacity of different sectors willfacilitate strategic management planning. In our study, for exam-ple, the Islander fleets that were harvesting the species may beunable to adapt to the changing stock distribution. This may be anoverall cost or benefit depending on what, if any, marine popula-tion inhabits the niche created by the departing species, or howalternative employment arrangements are put in place by govern-ments. In other words, a complete picture of the changes can only beobtained given information on not only how the distribution andproductivity of presently harvested species may change, but alsohow the distribution and abundance of associated and dependentspecies, and species that play similar ecological roles, may adapt toclimate change.

Acknowledgements

This research was funded by the CSIRO Climate Adaptation andWealth from Oceans Flagships, Australia. Malcolm Haddon, SeanPascoe, Ingrid Van Putten and Alistair Hobday provided many help-ful comments.

References

ABARE, 2008. Australian Fisheries Statistics (2007). Canberra.Arthur, B., 2005. Torres Strait Islanders and Fisheries: An Analysis of Economic

Development Programs. Centre for Aboriginal Economic Policy Research, TheAustralian National University.

Barkai, A., Branch, G.M., 1988. The influence of predation and substratal complexityon recruitment to settlement plates – a test of the theory of alternative states. J.Exp. Mar. Biol. Ecol. 124, 215–237.

Barkai, A., McQuaid, C., 1988. Predator–prey role reversal in a marine benthic ecosys-tem. Science 242, 62–64.

Barrett, N.S., Buxton, C.D., Edgar, G.J., 2009. Changes in invertebrate and macroalgalpopulations in Tasmanian marine reserves in the decade following protection.J. Exp. Mar. Biol. Ecol. 370, 104–119.

Brown, C.J., Fulton, E.A., Hobday, A.J., Matear, R.J., Possingham, H.P., Bulman, C., Chris-tensen, V., Forrest, R.E., Geherke, P.C., Gribble, N.A., Griffiths, S.P., Lozano-Montes,H., Martin, J.M., Metcalf, S., Okey, T.A., Watson, R., Richardson, A.J., 2010. Effects ofclimate-driven primary production change on marine food webs: implicationsfor fisheries and conservation. Global Change Biol. 16, 1194–1212.

Cai, W., 2006. Antarctic ozone depletion causes an intensification of the SouthernOcean super-gyre circulation. Geophys. Res. Lett. 33.

Cai, W., Shi, G., Cowan, T., Bi, D., Ribbe, J., 2005. The response of the Southern AnnularMode, the East Australian Current and the southern mid-latitude circulation toglobal warming. Geophys. Res. Lett. 32.

Caputi, N., Melville-Smith, R., de Lestang, S., Pearce, A., Feng, M., 2010. The effect ofclimate change on the western rock lobster (Panulirus cygnus) fishery of WesternAustralia. Can. J. Fish. Aquat. Sci. 67, 85–96.

Church, J.A., White, N.J., Hunter, J.R., McInnes, K.L., Mitchell, W.M., O’Farrell, S.P.,Griffin, D.A., 2009. Chapter 7. Sea level. Report Card of Marine Climate Change forAustralia; detailed scientific assessment. NCCARF publication 05/09, pp. 74–91.

Connolly, R.M., 2009. Seagrass. In: Poloczanska, E.S., Hobday, A.J., Richardson, A.J.(Eds.), Marine Climate Change Impacts and Adaptation Report Card for Australia2009. NCCARF Publication 05/09.

CSIRO, 2007. Climate Change in Australia. Technical Report.Dai, M., Lu, Z., Zhai, W., Chen, B., Cao, Z., Zhou, K., Cai, W.-J., Chen, C.-T.A., 2009. Diurnal

variations of surface seawater pCO2 in contrasting coastal environments. Limnol.Oceanogr. 54, 735–745.

Dasgupta, S., Laplante, B., Meisner, C., Wheeler, D., Yan, J., 2009. The impact of sea

level rise on developing countries: a comparative analysis. Climatic Change 93,379–388.

Dennis, D.M., Skewes, T.D., Pitcher, C.R., 1997. Habitat use and growth of juve-nile ornate rock lobsters, Panulirus ornatus (Fabricus, 1798), in Torres Strait,Australia. Mar. Freshw. Res. 48, 663–670.

2 eries

F

F

H

H

H

H

I

J

K

L

M

M

M

M

N

6 A. Norman-López et al. / Fish

airhead, L., Hohnen, L., 2007. Torres Strait Islanders Improving Their EconomicBenefits from Fishing. ABARE Research Report 07.21. Prepared for the FisheriesResources Research Fund, Canberra.

rusher, S., Gardner, C., Ling, S., Johnson, C., Ridgway, K., 2007. Is climate changeimpacting on lobster stocks in Tasmania? In: 8th International Conference andWorkshop on Lobster Biology and Management, Charlottetown, Prince EdwardIsland, Canada.

aley, C.N., Blamey, L.K., Atkinson, L.J., Branch, G.M., 2011. Dietary change of the rocklobster Jasus lalandii after an ‘invasive’ geographic shift: effects of size, densityand food availability. Estuar. Coast. Shelf Sci. 93.

emer, M.A., Harris, P.T., Colemen, R., Hunter, J., 2004. Sediment mobility due tocurrents and waves in the Torres Strait Gulf of Papua region. Cont. Shelf Res. 24,2297–2316.

obday, A.J., Poloczanska, E.S., Matear, R.J., 2008. Implications of Climate Change forAustralian Fisheries and Aquaculture: A Preliminary Assessment. Report to theDepartment of Climate Change, Canberra, Australia.

ollowed, A.B., Bond, N.A., Wilderbuer, T.K., Stockhausen, W.T., A’Mar, Z.T., Beamish,R.J., Overland, J.E., Schirripa, M.J., 2009. A framework for modelling fish andshellfish responses to future climate change. ICES J. Mar. Sci. 66, 1584–1594.

PCC, 2007. Climate Change 2007: The Physical Basis. Contribution of Working GroupI to the Fourth Assessment Report of the Intergovernmental Panel on ClimateChange (IPCC). p. 996.

ulia, R., Duchin, F., 2007. World trade as the adjustment mechanism of agricultureto climate change. Climatic Change 82, 393–409.

eyl, F., Wolff, M., 2008. Environmental variability and fisheries: what can modelsdo? Rev. Fish Biol. Fish. 18, 273–299.

ough, J.M., 2009. Chapter 3. Temperature. Report Card of Marine Climate Change forAustralia; detailed scientific assessment. NCCARF publication 05/09, pp. 17–28.

acNeil, M.A., Graham, N.A.J., Cinner, J.E., Dulvy, N.K., Loring, P.A., Jennings, S., Pol-unin, N.V.C., Fisk, A.T., McClanahan, T.R., 2010. Transitional states in marinefisheries: adapting to predicted global change. Philos. Trans. R. Soc. B: Biol. Sci.365, 3753–3763.

eehl, G.A., Stocker, T.F., Collins, W.D., Friedlingstein, P., Gaye, A.T., Gregory, J.M.,Kitoh, A., Knutti, R., Murphy, J.M., Noda, A., Raper, S.C.B., Watterson, I.G., et al.,2007. Global climate projections. In: Solomon, S., Qin, D., Manning, M., Chen, Z.,Marquis, M., Averyt, K.B., Tignor, M., Miller, H.L. (Eds.), Climate Change 2007: ThePhysical Science Basis. Contribution of Working Group I to the Fourth Assess-ment Report of the Intergovernmental Panel on Climate Change. , Cambridge,UK.

endelsohn, R., Dinar, A., 2009. Land use and climate change interactions. Annu.Rev. Resour. Econ. 1, 309–332.

erino, G., Barange, M., Mullon, C., 2010. Climate variability and change scenariosfor a marine commodity: modelling small pelagic fish, fisheries and fishmeal ina globalized market. J. Mar. Syst. 81, 196–205.

orman-López, A., Pascoe, S., 2011. Net economic effects of achieving maximumeconomic yield in fisheries. Mar. Policy 35, 489–495.

Research 148 (2013) 18– 26

Norman-López, A., Pascoe, S., Hobday, A., 2011. Potential economic impacts of cli-mate change on Australian fisheries and the need for adaptive management.Climate Change Econ., 237–255.

Oke, P.R., Brassington, G.B., Griffin, D.A., Schiller, A., 2007. The Bluelink ocean dataassimilation system (BODAS). Ocean Model. 21, 46–70.

Phillips, B.F., Palmer, M.J., Cruz, R., Trendall, J.T., 1992. Estimating growth of thespring lobsters Panulirus cygnus, P. argus and P. ornatus. Aust. J. Mar. Freshw.Res. 43, 1177–1188.

Pitcher, C.R., Skewes, T.D., Dennis, D.M., Prescott, J.H., 1992. Estimation of the abun-dance of the tropical lobster Panulirus ornatus in Torres Strait, using visualtransect-survey methods. Mar. Biol. 113, 57–64.

Pitcher, C.R., Turnbull, C., Atfield, J., Griffin, D.A., Dennis, D.M., Skewes, T.D., 2005.Biology, Larval Transport Modeling and Commercial Logbook Data Analysisto Support Management of the NE Queensland Rock Lobster Panulirus orna-tus Fishery. FRDC Project, 2002/008. CSIRO Marine and Atmospheric Research,Cleveland, Qld., p. 144.

Plagányi, E., Dennis, D., Kienzle, M., Ye, Y., Haywood, M., McLeod, I., Wassenberg, T.,Pillans, R., Dell, Q., Coman, G., Tonks, M., Murphy, N., 2009. TAC Estimation andRelative Lobster Abundance Surveys 2008/09. Australian Fisheries ManagementAuthority Torres Strait Research Program Final Report. AFMA Project number:2008/837. p. 81.

Poloczanska, E.S., Babcock, R.C., Butler, A., Hobday, A.J., Hoegh-Guldberg, O., Kunz,T.J., Matear, R., Milton, D., Okey, T.A., Richardson, A.J., 2007. Climate change andAustralian marine life. Oceanogr. Mar. Biol. Annu. Rev. 45, 409–480.

Reilly, J., Hohmann, N., Kane, S., 1994. Climate change and agricultural trade: whobenefits, who loses? Global Environ. Change 4, 24–36.

Shears, N.T., Babcock, R.C., 2002. Marine reserves demonstrate top-down control ofcommunity structure on temperate reefs. Oecologia 132, 131–142.

Skewes, T.D., Pitcher, C.R., Dennis, D.M., 1997. Growth of ornate rock lobsters, Pan-ulirus ornatus, in Torres Strait, Australia. Mar. Freshw. Res. 48, 497–501.

Skewes, T.D., Pitcher, C.R., Trendall, J.T., 1994. Changes in the size structure, sex-ratioand motling activity of a population of ornate rock lobsters, Panulirus ornatus,caused by an annual maturation molt and migration. Bull. Mar. Sci. 54, 38–48.

Sohngen, B., Mendelsohn, R., Sedjo, R., 2001. A global model of climate changeimpacts on timber markets. J. Agric. Resour. Econ. 26, 326–343.

Wahle, R.A., Fogarty, M.J., 2006. Growth and development: understanding and mod-eling growth variability in lobsters. In: Phillips, B.F. (Ed.), Lobsters: Biology,Management, Aquaculture, and Fisheries. Scientific Publications, Oxford.

Ward, P., Rodgers, M., Perks, C., 2009. Chapter 16. Torres Strait tropical rock lobsterfishery. Fishery status reports 2009.

Ye, Y., Pitcher, R., Dennis, D., Skewes, T., 2005. Constructing abundance indices from

scientific surveys of different designs for the Torres Strait ornate rock lobster(Panulirus ornatus) fishery, Australia. Fish Res. 73, 187–200.

Ye, Y.M., Dennis, D., Skewes, T., 2008. Estimating the sustainable lobster (Panulirusornatus) catch in the Torres Strait, Australia using an age-structured stock assess-ment model. Cont. Shelf Res. 28, 2160–2167.