Modelling Complexity and Uncertainty in Fisheries Stock Assessment

Stock assessment models are used to determine the population size of fish stocks. Although stock assessment models are complex, they still make simplifying assumptions. Generally, they treat each species separately, include little, if any, spatial structure, and may not adequately quantify uncertainty. These assumptions can introduce bias and can lead to incorrect inferences. This thesis is about more realistic models and their inference. This realism may be incorporated by explicitly modelling complex processes, or by admitting our uncertainty and modelling it correctly. We develop an agent-based model that can describe fish populations as a collection of individuals which differ in their growth, maturation, migration, and mortality. The aim of this model is to better capture the richness in natural processes that determine fish abundance and subsequent population response to anthropogenic removals. However, this detail comes at considerable computational cost. A single model run can take many hours, making inference using standard methods impractical. We apply this model to New Zealand snapper (Pagurus auratus) in northern New Zealand. Next, we developed an age-structured state-space model. We suggest that this sophisticated model has the potential to better represent uncertainty in stock assessment. However, it pushes the boundaries of the current practical limits of computing and we admit that its practical application remains limited until the MCMC mixing issues that we encountered can be resolved. The processes that underpin agent-based models are complex and we may need to seek new sources of data to inform these types of models. To make a start here we derive a state-space model to estimate the path taken by individual fish from the day they are tagged to the day of their recapture. The model uses environmental information collected using pop-up satellite archival tags. We use tag recorded depth and oceanographic temperature to estimate the location at any given time. We apply this model to Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea. Finally, to reduce the computational burden of agent-based models we use Bayesian emulation. This approach replaces the simulation model with an approximating algorithm called an emulator. The emulator is calibrated using relatively few runs of the original model. A good emulator provides a close approximation to the original model and has significant speed gains. Thus, inferences become tractable. We have made the first steps towards developing a tractable approach to fisheries modelling in complex settings through the creation of realistic models, and their emulation. With further development, Bayesian emulation could result in the increased ability to consider and evaluate innovative methods in fisheries modelling. Future avenues for application and exploration range from spatial and multi species models, to ecosystem-based models and beyond

Scientific, Technical and Economic Committee for Fisheries (STECF) - Report of the SGMED-10-01 Working Group on Preparation of assessment process

SGMED-10-01 meeting was held on 22-26 March 2010 in Barcelona (Spain). The meeting was dedicated to the preparation of the stock assessment process for the Mediterranean stocks and fisheries to be implemented during 2010.STECF reviewed the report during its Plenary meeting on 26-30 April in Norwich.JRC.DG.G.4-Maritime affair

Application of decision analysis in the evaluation of recreational fishery management problems

Thesis (Ph.D.) University of Alaska Fairbanks, 1995Fisheries management is a decision-making process, yet typically formal decision analysis techniques are not used in structuring problems, quantifying interactions, or arriving at a prioritized solution. Decision analysis tools are applied in the decision-making process for Alaska's recreational fisheries management as a means to reduce risk in management at the policy (Chapter 2) and field (Chapter 3) levels. In Chapter 2 the analytic hierarchy process is applied to the recreational fishery for chinook salmon (Oncorhynchus tshawytscha) in the Kenai River. Model structure is developed through an iterative interview process involving individuals asked to represent the perspectives of 15 different stakeholders. Individual stakeholder judgments are combined using a geometric mean, and maximax and maximin criteria. The sensitivity of the results to under-representation is explored through various models. Despise the contentious differences of perspective represented among stakeholders, the analytic hierarchy process identifies management options that enjoy broad support and limited opposition. In Chapter 3 decision analysis is applied to the recreational spear fishery for humpback whitefish (Coregonus pidschian) in the Chatanika River. A modified form of catch-age analysis is used to combine information derived from creel surveys and run age composition with auxiliary information in the form of mark-recapture estimates of abundance. Four systems are used in weighting annual observations: prior beliefs regarding their reliability, by the inverses of their variances, through a combination of these two weighting schemes, and equal (no) weights. The perception-weighted model generates the most reasonable estimates of abundance, which are relatively precise and associated with small bias. Forecasts of mature exploitable abundance are calculated based on various recruitment scenarios, maturity schedules, and exploitation rates. From these outcomes, the odds of stock abundance occurring below a threshold level are presented. By applying decision analysis methodologies which incorporate judgments and perceptions into decision-making affecting fisheries, sensitivity to uncertain information is made explicit, components of the problem are structured, interactions among components of the problem are quantified, and options are prioritized, thus increasing the chances of finding an optimal solution

Estimating unreported catches in Norwegian fisheries

A discard ban for fish was introduced in Norway in 1987, which requires that all commercial catches must be landed and reported. In theory, this regulation creates a full record of total removals from all fisheries. However, exemptions and varying compliance rates create a risk that unreported catches still occur. Estimating unreported catches of all species in multiple fisheries is a large task that is complexified by the many influential factors related to unique fishery regulations, market demands, fishing gear, and species biology. There is therefore a need to standardise the estimation procedure, but this requires compromises that affect the bias and precision variably across individual species which must be understood if results are used as scientific advice. In Norwegian fisheries, the largest source of detailed data on unreported catches comes from the Norwegian Reference Fleet, a group of active fishing vessels that are paid to sample their catches at sea. However, participation in the programme is voluntary, meaning there are uncertainties about how representative the Norwegian Reference Fleet are of the wider fisheries. In such a complex system, it is important to address uncertainties in the entire estimation process, including from sampling data and the estimators used. The aim of this thesis is to develop standardised estimators for unreported catches in Norwegian fisheries. To identify the current knowledge gaps in Norwegian fisheries, global best practices for estimating unreported catches were collated and applied to Norwegian fisheries. Following from this, two research paths were identified. Firstly, there is a demand to understand the quality of data collected by the Norwegian Reference Fleet. Based on the available data, this was confined to quantifying the representativeness of samples. Secondly, previous studies estimating unreported catches have used bespoke model-based approaches to improve predictive performance, but simple design-based approaches have been applied based on assumptions that have not yet been tested. There is therefore a demand to evaluate the assumptions behind the current design-based estimators. To evaluate representativeness, the sampling design of the Norwegian Reference Fleet was simulated using reported catches, for which fleet-level information is available. The simulation study identified that nonprobability sampling of vessels in the Norwegian Reference Fleet results in a tendency to overestimate reported catches, but the bias is still within the bounds of expected variation from probability sampling. Representativeness varied greatly across species and years, and there was evidence that the estimators traditionally used for unreported catches may be introducing bias due to assumptions being unmet. These results provide support for the development of improved estimators and consideration of a more conservative estimation of uncertainty. Applying a cluster-based estimator that better describes true variations between sampled vessels produces a more realistic, albeit more uncertain estimate of unreported catches. This is also the case for additional uncertainty incurred from converting numbers of fish to biomass, which must use an additional modelling step due to a lack of information on fish weights. The current methodology for estimating discards in coastal fisheries is restricted by the fishery-level data that is used for extrapolating estimated discard rates. However, current developments in mandatory reporting requirements suggest that future model-based approaches could improve discard estimates. Therefore, an exploratory model was fitted to the sampling data to identify potentially important variables that explain variations in discarding. This model can then inform the variable selection in a future model-based approach when fishery-level data collection is improved. The estimation methodologies presented in this thesis form the basis of a national routine for estimating unreported catches in Norwegian fisheries. Quantifying the bias of estimators and accounting for additional, important sources of uncertainty provides a standardised design-based estimator for unreported catches in Norwegian fisheries. Predictive performance is now supported by quantitative evidence and further improvements have been identified to optimise estimators in the future such as accounting for rare occurrences and size-based estimates. Furthermore, the lessons learnt throughout this doctoral research highlight the importance of creating a standardised framework for estimating unreported catches. This ensures that improvements are centralised rather than being hidden within individual case studies.I Norge ble det innført et utkastforbud for fisk fanget allerede i 1987. I henhold til dette skal all kommersiell fangst føres på land. I teorien oppnår denne forskriften en fullstendig oversikt over totale uttak fra alle fiskerier. Unntak og varierende etterlevelse skaper imidlertid en risiko for at det fortsatt forekommer urapporterte fangster. Å estimere urapporterte fangster av alle arter i flere fiskerier er en stor og komplisert oppgave på grunn av de mange innflytelsesrike faktorene knyttet til unike fiskerireguleringer, markedskrav, fiskeredskaper og artsbiologi. Det er derfor behov for å standardisere estimeringsprosedyren, men dette krever kompromisser som påvirker nøyaktighet og presisjonen i varierende grad på tvers av individuelle arter, og som må forstås hvis resultatene brukes som vitenskapelig råd. I norske fiskerier er Referanseflåten den største kilden til detaljerte data om urapporterte fangster. Referanseflåten er en gruppe aktive fiskefartøyer som får betalt for å ta prøver fra fangstene sine. Siden deltakelse i programmet er frivillig, er det usikkerhet om hvor representativ Referanseflåten er for hele fiskeflåten. I et så komplekst system er det viktig å adressere usikkerhet i hele estimeringsprosessen, inkludert data og estimatorene som brukes. Målet med denne oppgave er å utvikle standardiserte estimatorer for urapportert fangst i norske fiskerier. For å kartlegge dagens kunnskapshull i norske fiskerier, ble den globale beste praksis for estimering av urapportert fangst sammenstilt og brukt på norske fiskerier. Etter dette ble det definert to forskningsretninger. Det første er nødvendigheten om å forstå kvaliteten på data som samles inn av Referanseflåten. Basert på tilgjengelige data ble dette begrenset til å kvantifisere hvor representativt de innsamlede data er. For det andre har tidligere studier som estimerte urapportert fangst tatt i bruk tilpassede modellbaserte tilnærminger for å forbedre prediktiv ytelse, men noen designbaserte tilnærminger som har blitt brukt er basert på antakelser som ennå ikke er testet. Det er derfor et behov for å evaluere forutsetningene bak designbaserte estimatorer som brukes i dag. For å vurdere Referanseflåten sin representativitet, ble data innsamlingsdesignet simulert med bruk av rapporterte fangster som er tilgjengelig for hele flåten. Simuleringene viste en tendens til å overestimere rapportert fangst fordi båtene ble ikke valgt ved bruk av sannsynlighet. Likevel er nøyaktigheten fortsatt innenfor rammen av forventet variasjon hvis båtene ble valgt ved bruk av sannsynlighet. Representativiteten varierte sterkt på tvers av arter og år, og det var bevis på at estimatorene som tradisjonelt ble brukt for urapportert fangst, kan innføre unøyaktighet på grunn av at forutsetningene ikke er oppfylt. Disse resultatene gir støtte til utvikling av forbedrede estimatorer og vurdering av en mer konservativ estimering av usikkerhet. Bruk av en klyngebasert estimator som bedre beskriver sanne variasjoner mellom utvalgte fartøyer gir et mer realistisk, om enn mer usikkert estimat av urapporterte fangster. Dette er også tilfellet for ytterligere usikkerhet som følge av konvertering av antall fisk til biomasse, som må bruke et ekstra modelleringstrinn på grunn av mangel på informasjon om fiskevekten. Dagens metodikk for å estimere utkast i kystfiske er begrenset av kvaliteten på dataene på fiskerinivå som brukes for å ekstrapolere estimerte utkastrater. Pågående utvikling i obligatoriske rapporteringskrav tyder imidlertid på at fremtidige modellbaserte tilnærminger kan forbedre estimatene på utkast. Derfor ble en utforskende modell tilpasset prøvetakingsdataene for å identifisere mulige viktige variabler som forklarer grunnene til utkast. Denne modellen kan deretter informere variabelutvalget i en fremtidig modellbasert tilnærming når datainnsamlingen på fiskerinivå forbedres. Metodene for utkastestimering fremlagt i denne oppgaven kan danne grunnlaget for en nasjonal rutine for å estimere urapportert fangst i norske fiskerier. Å kvantifisere nøyaktigheten til estimatorer og redegjøre for ytterligere viktige kilder til usikkerhet gir en standardisert designbasert estimator for urapporterte fangster i norske fiskerier. Prediktiv ytelse støttes nå av kvantitative bevis og ytterligere forbedringer er identifisert for å optimalisere estimatorer i fremtiden, for eksempel regnskap for sjeldne hendelser og størrelsesbaserte estimater. Erfaringene gjennom denne forskningsoppgave fremhever viktigheten av å skape et standardisert rammeverk for å estimere urapportert fangst. Dette sikrer at forbedringer er sentralisert, i stedet for å være skjult i individuelle casestudier.Doktorgradsavhandlin

Stock assessment of whaler and hammerhead sharks (Carcharhinidae and Sphyrnidae) in Queensland

This stock assessment provides detailed results for the most common sharks encountered by Queensland commercial fishers. These sharks come from the whaler (Carcharhinidae) and hammerhead (Sphyrnidae) families and comprise sharpnose sharks (Rhizoprionodon taylori and R. oligolinx), the milk shark (R. acutus), the creek whaler (Carcharhinus fitzroyensis), the hardnose shark (C. macloti), the spot-tail shark (C. sorrah), the Australian blacktip shark (C. tilstoni), the common blacktip shark (C. limbatus), the spinner shark (C. brevipinna), bull and pigeye sharks (C. leucas and C. amboinensis), the winghead shark (Eusphyra blochii), the scalloped hammerhead (Sphyrna lewini) and the great hammerhead (S. mokarran). Reef sharks were excluded because fishery observer data indicated that they were largely spatially segregated from sharks caught in the inshore net fisheries. The three common species of reef sharks in Queensland, which are all whaler sharks, are the grey reef shark Carcharhinus amblyrhynchos, the blacktip reef shark C. melanopterus and the whitetip reef shark Triaenodon obesus

A Review of the Global Commercial Cephalopod Fishery, with a Focus on Apparent Expansion, Changing Environments, and Management

Cephalopods are both important predators and prey in many marine environments and important fishery resources in many countries. The global fishery has expanded almost continuously from landings of 580,000 metric tonnes in 1950 to over 4 m.t. in 2007. Cephalopods are ecological opportunists with highly plastic biological characteristics and varied population dynamics. Nearly all commercially harvested species are short-lived and can reproduce quickly, enabling them to evolve more rapidly under high selection pressure relative to many fish competitors and predators. As a result, they may have the biological means to be successful under conditions of long-term global climate change. This capstone reviews current information on cephalopod life history, morphology and taxonomy, population dynamics, and recruitment as they relate to fishery assessments, proper management, associated gear, and the impacts of their proper or improper use. Despite the adaptive capabilities of cephalopods, the sustainability of heavy fishing effort will be questioned in the future as the impacts of socio-cultural values and economic importance continue to rise across the globe. The correlation between increased oceanic temperatures and the global proliferation of cephalopods may be inferred from the literature; however, this does not provide direct causality, nor does it suggest that cephalopods may be fished extensively without proper management and guidance. Future endeavors to promote stock and population sustainability via proper management and assessments will increase the likelihood of enjoying cephalopod products in all of their forms across the globe