A productivity-susceptibility risk analysis for the effects of fishing on Arctic Char ( Salvelinus alpinus ) stocks from the Nunavut Territory
Marie-Julie Roux* and Ross F. Tallman Fisheries and Oceans Canada Central and Arctic Region
*Present address :Current Address: National Institute of Water and Atmospheric Research , 301 Evans Bay Parade, Greta Point, Wellington, New Zealand Problems
( ) “what needs to be done to address priority gaps” paucity of too large too many data a place stocks
195 Arctic Char 350 FW and Anadromous Background Problems
( ) “what needs to be done to address priority gaps”
paucity of too large too many data a place $ stocks
prohibitive time and financial costs to gather standard assessment data Background Problems
( ) “what needs to be done to address priority gaps”
paucity of too large too many charr data a place $ stocks diversity
prohibitive time and financial costs to gather standard makes it difficult to generalize assessment scientific information for the data species and related management plans/actions Background from Gaps to Solutions
( ) “forsolutions addressing of gaps for the scientific understanding and management of Arctic charr fisheries
charr modelling charr diversity Objective Life history traits determine stock productivity
life history traits age at maturity ( R) fecundity ( R) growth rate ( G) survival ( M)
elements of productivity R = reproductive capacity G = growth M = mortality = 1 survival Conceptual approach
(productivity ≈ resilience) Life history traits determine stock productivity
life history traits stable population: age at maturity ( R) fecundity ( R) growth rate ( G) survival ( M) R + G = M
elements of productivity
R = reproductive capacity R G M G = growth M = mortality = 1 survival
population trend = nil (0)
traits are in balance and the population persists Conceptual approach
(productivity ≈ resilience) Conceptual approach Charr modelling using life history traits history life using modelling Charr Z GR F AM life history traitslifehistory elementsproductivityof M G R = instantaneous mortality = fecundity = reproductive capacity = growth = mortality = growth rate = age at maturity F R AM G GR M Z Conceptual approach Charr modelling using life history traits history life using modelling Charr Z GR F AM population response information) (management history and H life history traitslifehistory elementsproductivityof M G R = instantaneous mortality = fecundity = reproductive capacity = growth = mortality = growth rate = age at maturity = harvest harvest rate F R AM G GR H M Z Conceptual approach Charr modelling using life history traits history life using modelling Charr Z GR F AM H population response information) (management history and life history traitslifehistory elementsproductivityof M G R = instantaneous mortality = fecundity = reproductive capacity = growth = mortality = growth rate = age at maturity = harvest harvest rate harvest harvest rates as input parameters to a a model using history life traits and exploresustainableidentifyand F predict predict population trends R AM G GR R + + G – M M Z > > 0 H H H anger Conceptual approach Charr modelling using life history traits history life using modelling Charr F R AM G GR exposure M Z (FULLQUANTITATIVE ANALYSIS) testing and development model • (SEMI QUANTITATIVE RISK ANALYSIS) vulnerability of fi relative to stocks charr Arctic evaluat for used be can this how and traits history variabi inter population of extent the demonstrate • phase phase 1 : phase phase 2 : shing activities activities shing ing ing the lity life in Risk assessment using life history traits
a relative (as opposed to absolute) risk assessment method
based on the principle that population vulnerability to fishing activities depends on:
• its ability to recover from increased mortality (productivity≈resilience) (more productive = less vulnerable)
• the extent of the impacts due to fishing activities (susceptibility≈exposure) (more exposed = more vulnerable) PSA introduction PSA
PSA Productivity Susceptibility Analysis Risk assessment using life history traits
not a new method:
•Australian Northern Prawn fishery by catch spp. (see Stobutzki et al. 2001)
• recently proposed as a semi quantitative step in a hierarchical ecological risk assessment for the effects of fishing (ERAEF) framework by the Marine Stewardship Council (MSC eco certification body) (see Hobday et al. 2007)
• currently being evaluated for use in determining the vulnerability of U.S. fisheries by NOAA (see Patrick et al. 2009)
but has never been experimented on a single species basis PSA introduction PSA
PSA Productivity Susceptibility Analysis Productivity-Susceptibility risk assessment
STEP 1 : define and estimate productivity and susceptibility attributes
Productivity Susceptibility attributes attributes PSA methods PSA Productivity-Susceptibility risk assessment
STEP 1 : define and estimate productivity and susceptibility attributes
Productivity Susceptibility attributes attributes
CANADA
ARCTIC OCEAN
BAFFIN SEA historical data base for charr from across Nunavut (1971 2003) Nunavut
ATLANTIC OCEAN
HUDSON BAY 97 anadromous stocks PACIFIC OCEAN (5.5” (139.7 mm) gillnet studies) PSA methods PSA PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 1 higher higher more mortality productive= individualgrowthrate faster growthmore faster productive= younger = maturity first age at : : age atagematurity first short lived more productive= defineestimateandproductivitysusceptibilityand attri Productivity more more productive attributes mortality lifespan estimation (all 139.7mm 139.7mm (all data gillnet pooled) curves (catch at age plots) annual mortality estimated from catch 139.7mm (all data gillnet pooled) maximum age observed in the sample recruited age groups* fitting vonBertalanffy growth curves to fully Brody (K) growth coefficient calculated by predictoras age max using model a linear from approximatedor first age group withmature fish (all 139.7mm 139.7mm (all data gillnet pooled) (all data data (all pooled) butes PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 1 ratio ratio of mean fork length over mesh size (in mm) : : distance distance from nearest defineestimateandproductivitysusceptibilityand attri anadromous stocks human community ranked ranked high for estimation overlap overlap between fishing effort likelihood likelihood will that stock the Susceptibility encounterability potential potential gear the for to encounter encounter fishing gear and and stock distribution capture/retain capture/retain fish availability attributes selectivity butes PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 2 Quality S c ore Data data quality scores = data= qualityameasureuncertaintyscores of 5 4 3 2 1 : : rankindividualproductivity attributesdatafor quality bereliable are not met. Sample size is <100 bereliable are not met. Sample size is <300 but >100 samplesize is large( Estimate wasapproximated using life history inform Samplesize is <100 AND other conditions Samplesize >100is BUT other conditions – OR sample size >300is BUT other conditions – OR Datanot is recent and unlikely to reflectcurrent All conditionsapriori determined for theestimat samplesize is large( Datarecent is and is likely reflectto currentst All conditions reliablearenot met. apriori ≥ ≥ determined for the estimateto be reliableare met. 300). 300). Conditions apriori ateenvironmental conditions. a priori apriori state environmentalconditions. eto be reliableare met. determined anfor estimate beto ation. determined anfor estimateto determined anfor estimate to PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 3 1=High 1=Low *DQ divide this range into thirds: into range divide this attribute each for values of range a determine : : individual individual growthrate age at first maturity age at first Productivity rankproductivitysusceptibilityattributesand into tiers Productivity attributes mortality correspondingto different risklevelsof lifespan 2=Moderate 2=Moderate Risk 3=Low 3=High 1=Low 1=Low Susceptibility encounterability attributes availability Susceptibility selectivity 2=Moderate 2=Moderate Risk 3=High 3=High PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility *only values stocks with corresponding to data qualityscore Ageat first Attribute Growthrate (K) maturity Mortality (Age Lifespan STEP 3 max *DQ ) : : Productivity rankproductivitysusceptibilityattributesand into tiers attributes correspondingto different risklevelsof ObservedRange 0 .0 2 8 0.17 Min 12 3 0 .1 7 5 Max 0.66 12 31 0.028 0.079 0.17 0.34 LOW LOW =1 2 4 3 1 9 12 ProductivityTiers and Scores s ≤ 3 were used were used 3 define to observed the range MODERATE=2 0.080 0.127 0.35 0.50 1 8 2 3 6 8 0.128 0.175 HIGH HIGH = 3 0.51 0.66 1 2 1 7 3 5 PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility Distance community from (km) noneaiiyscoresEncounterability encounterability scores encounterability STEP 3 : : Susceptibility rankproductivitysusceptibilityattributesand into tiers attributes correspondingto different risklevelsof 3= High ≤ 10 5 1 6 0 2.5 101 110 2=Mod 151 160 1.5 1 = Low ≥ 201 PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 3 : : Susceptibility rankproductivitysusceptibilityattributesand into tiers attributes correspondingto different risklevelsof Observedrange MIN 501 (meanFL) MAX 772 (MeanFL Mesh/ size) 3.60 MIN Observedrange MAX 5.55 3.60 4.25 LOW LOW 1 = Gear Selectivity Tiersand Scores selectivity scores selectivity MODERATE=2 4.26 4.90 HIGH=3 4.91 5.55 PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 3 : : Susceptibility rankproductivitysusceptibilityattributesand into tiers attributes correspondingto different risklevelsof ndoos large lake fishery anadromous autie large lake fisherylacustrine low=1 anadromous medium size medium lake fishery anadromous autie mediumsize lake fisherylacustrine Availabilitytiers and scores moderate=2 availabilityscores ndoos river mouth fishery anadromous high=3 PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 4 *DQ unrblt astheEuclidean distancetheorigin from vulnerability : : Productivity plotproductivity susceptibilityaverage scoresestimateand 1=High 1=Low
Susceptibility Productivity average score (P)
(Low) (High) Productivity 1.0 1.5 2.0 2.5 3.0 2=Moderate 2=Moderate Risk (High) 3.0 attributes Low Low Susceptibility = = vulnerableleast High Productivity High 3=Low 3=High 2.5 Productivity 2.0 average Susceptibility Susceptibility average score (S) HighSusceptibility = most = vulnerable Low Low Productivity 1.5 Susceptibility 1=High 1=Low (Low) 1.0 Susceptibility 2=Moderate 2=Moderate Risk (Euclidean (Euclidean distance from origin) attributes 3=Low 3=High ( 3)√(P = V Vulnerability(V) 2 S–1)– (S + 2 ) PSA methods Productivity-Susceptibility assessmentrisk Productivity-Susceptibility STEP 5 *DQ Productivity : : averagequalityscoresdataintoquality indexa data 1=High 1=Low
Susceptibility Productivity average score (P)
(Low) (High) Productivity 1.0 1.5 2.0 2.5 3.0 2=Moderate 2=Moderate Risk (High) 3.0 attributes Low Low Susceptibility = = vulnerableleast High Productivity High 3=Low 3=High 2.5 Productivity 2.0 average Susceptibility Susceptibility average score (S) HighSusceptibility = most = vulnerable Low Low Productivity 1.5 Susceptibility 1=High 1=Low (Low) 1.0 Susceptibility 2=Moderate 2=Moderate Risk attributes 3=Low 3=High LOW LOW (L) ≥3.6 Mediumdata quality dataHigh quality Lowdata quality overall DATAQUALITY Index MEDIUM (M) 2.1 3.5 HIGH (H)HIGH ≤ 2 PSA results (1.47) Becher Becher (1.47) River PerryRiver (1.28) Nakyoktok (1.28) River Kellett (1.27) River Arrowsmith (1.27) River Productivity-Susceptibility assessmentrisk Productivity-Susceptibility Less Less Vulnerable Kitikmeot Kitikmeot Region (2.46) Lord Lord (2.46) LakeLindsay Abernethy (2.30) River Jayco (2.24) River Hayes (2.08) River Paliryuak (2.07) River Freshwater (2.06) Creek Less Vulnerable stocks Less Vulnerable stocksVulnerable MorestocksVulnerable Low data qualitydata Low qualityMedium data qualityHighdata More More Vulnerable
Susceptibility (Low) (High) 1.0 1.5 2.0 2.5 3.0 (High) 3.0 2.5 Productivity 2.0 1.5 (Low) 1.0 PSA results (1.19) Steep Steep (1.19) BayBank Hanway(1.18) River Gore (1.18) BayArea Lorillard (1.15) River Robinhood (1.10) Bay Barbour (1.10) Bay Stony (1.09) AreaPoint Productivity-Susceptibility assessmentrisk Productivity-Susceptibility Less Less Vulnerable (1.36) Ranger Ranger (1.36) BaySeal Rankin (1.36) Inlet Area Chesterfield (1.36) Inlet Pistol Bay(1.23) KivalliqRegion MorestocksVulnerable Less Vulnerable stocks Less Vulnerable stocksVulnerable Low data qualitydata Low qualityMedium data qualityHighdata (2.05) Ross Ross (2.05) Inlet More More Vulnerable
Susceptibility (Low) (High) 1.0 1.5 2.0 2.5 3.0 (High) 3.0 2.5 Productivity 2.0 1.5 (Low) 1.0 PSA results (1.42) Nettilling Nettilling (1.42) Lake AvaInlet (1.42) Tugaat (1.41) River Kipisa Lake(1.41) Tasirululik (1.30) Lake Ikalukjuaq (1.23) Lake Riverand Productivity-Susceptibility assessmentrisk Productivity-Susceptibility Less Less Vulnerable Baffin High Region Less Vulnerable stocks Less Vulnerable stocksVulnerable MorestocksVulnerable Low data qualitydata Low qualityMedium data qualityHighdata (2.29) Gifford Gifford (2.29) River MagdaRiver(2.23) Tarsiujuak (2.20) Arm Stanwell Fletcher Lake(2.15) Ikikeesarjuq (2.15) Lake Kukaluk (2.14) River Ijaruvung (2.14) Lake More More Vulnerable
(2.44) Neergaard Neergaard Lake(2.44) Ikpikiturjuaq (2.41) Lake Rowley(2.39) River Hall Lake(2.35) Naulingiavik Lake(2.30) Koluktoo (2.30) Bay Ivisarak Lake(2.30) Susceptibility (Low) (High) 1.0 1.5 2.0 2.5 3.0 (High) 3.0 (2.56) Fury (2.56) StraitHecla and Windless River(2.55) Hall Beach (2.50) Area Ravn (2.44) River 2.5 Productivity 2.0 1.5 (Low) 1.0 Productivity-Susceptibility risk assessment
Pond Inlet Arctic Bay
Clyde River
Kugluktuk Cambridge Bay Taloyoak Igloolik Gjoa Haven Kugaaruk Hall Beach
Pangnirtung
Repulse Bay
Iqaluit
Kimmirut
Chesterfield Inlet Rankin Inlet PSA results PSA
Arviat Less Vulnerable stocks (more sustainable fisheries)
Vulnerable stocks (sustainable fisheries) More Vulnerable stocks (less sustainable fisheries) Productivity-Susceptibility risk assessment
Pond Inlet Arctic Bay
Clyde River
Kugluktuk Cambridge Bay Taloyoak Igloolik Gjoa Haven Kugaaruk Hall Beach
Pangnirtung
Repulse Bay
Iqaluit
Kimmirut
Chesterfield Inlet • 15% of fisheries examined Rankin Inlet
PSA results PSA • 45% of more sustainable fisheries
Arviat Less Vulnerable stocks (more sustainable fisheries)
Vulnerable stocks (sustainable fisheries) More Vulnerable stocks (less sustainable fisheries) Productivity-Susceptibility risk assessment
• 22% of fisheries examined
Pond Inlet • 60% of less sustainable fisheries Arctic Bay
Clyde River
Kugluktuk Cambridge Bay Taloyoak Igloolik Gjoa Haven Kugaaruk Hall Beach
Pangnirtung
Repulse Bay
Iqaluit
Kimmirut
Chesterfield Inlet Rankin Inlet PSA results PSA
Arviat Less Vulnerable stocks (more sustainable fisheries)
Vulnerable stocks (sustainable fisheries) More Vulnerable stocks (less sustainable fisheries) PSA implications Productivity-Susceptibility assessmentrisk Productivity-Susceptibility predominantlyormore vulnerablebyless charr Arctic pop PSAanalysis allowsdistinguishusto between charregions • prevalencemoreof vulnerable overfi= ofriskstocks greater prevalencelessof vulnerable = overfishingstockslower ofrisk Regionaldifferences invulnerabilitystock over over a broad geographic landscape: ulations acterized shing PSA results Productivity-Susceptibility assessmentrisk Productivity-Susceptibility CambridgeBay Area Less Vulnerable stocks Less Vulnerable stocksVulnerable MorestocksVulnerable Low data qualitydata Low qualityMedium data qualityHighdata
Susceptibility (Low) (High) 2.5 3.0 1.0 1.5 2.0 (High) 3.0 Lauchlan 2.5 Halovik Perry Ekalluk Productivity Kulgayuk 2.0 Ellice Paliryuak 1.5 Jayco (Low) 1.0 Yield Calculations log L∞= 0.044 + 0.9841 log Lmax (Froese & Binohlan 2000)
K = ln (1 Lm/L∞) / (tm t0) (Froese & Binohan 2003)
M = 1.5K F = Z – M – Z calculated from catch curve (Jensen 1996)
Biomass = Yield/F
Max Sustainable Production = 0.33 x Z x Biomass Estimation of Maximum Sustainable Production Estimation of Maximum Sustainable Production
General conclusion Charr modellingCharrtraits usinglifehistory charr populations in Nunavutin charr populations Variability Among population historylife in traits • is a is characteristic of Arctic General conclusion Charr modellingCharrtraits usinglifehistory fish (intermediate data quality)or fish usin approximated(intermediatedata fromdetermineda Life traitsbe for historya can stock • Nunavutin charr populations Variability Among population historylife in traits • is a is characteristic of Arctic g life g theoryhistorylife single 200 single sample ≈ of General conclusion Charr modellingCharrtraits usinglifehistory smaller smaller areas. within and landscape geographic activities broad a over relative vulnerability of Arctic charr fishing tostocks (susceptibilitytheexposuredetermineoftoattributes) withmeasure a together Life used traits can history be • quality)or fish usin approximated(intermediatedata fromdetermineda Life traitsbe for historya can stock • Nunavutin charr populations Variability Among population historylife in traits • is a is characteristic of Arctic g life g theoryhistorylife
single 200 single sample ≈ of
F R AM G exposure GR M Z General conclusion Charr modellingCharrtraits usinglifehistory forarctic CNA thein charr region. scientific offormulation facilitate thea thereby and stockfor a harvestratessustainable identify explore and model quantitative a in Life used traits can history be • soon: smaller areas. within and landscape geographic activities broad a over relative vulnerability of Arctic charr fishing tostocks (susceptibilitytheexposuredetermineoftoattributes) withmeasure a together Life used traits can history be • quality)or fish usin approximated(intermediatedata fromdetermineda Life traitsbe for historya can stock • Nunavutin charr populations Variability Among population historylife in traits • is a is characteristic of Arctic dvice dvice g life g theoryhistorylife
to single 200 single sample ≈ of
F R AM G GR exposure M Z Gaps Solutions
( ) “forsolutions addressing of gaps for the scientific understanding and management of Arctic charr fisheries
life history traits charr diversity
exposure
F AM GR Z
R G M
relative risk assessment full quantitative analysis General conclusion Questions ? Acknowledgments
Theresa Carmicheal DFO
YK area office
DFO Nunavut Implementation Fund
Nunavut Wildlife Management Board