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Fisheries Economics: Coastal and Oceanic

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1 Fisheries Economics: Coastal and Oceanic
Philip James, Fisheries Economist Steven Hare, National Scientist Graham Pilling, Principle Fisheries Scientist Introduction – Phil then Steve Session make up: 1. Listen to the presentation for about 30 mins! 2. Plenary questions/comments/requests 15 mins 3. Breakout group work 45 mins The presentation is not to give you a list of what we have done over the past two years, But to provide examples of economic analysis to stimulate questions and ideas for future analysis, therefore the presentation is mostly case study based.

2 Background Pressure on resources increase, economic analysis becomes increasingly important. Not financial analysis Utilised throughout the policy and project life cycle: Design Implementation Evaluation Analysis is critical to fully understanding the implications and impact of policy decisions Economics is not accounting! Economic analysis is about providing Practical advice that accounts for the socioeconomic dimensions of fisheries as well as the scientific dynamics of the resource. Leading to practical, implementable and justifiable advice for policy action, helping to avoid the social, financial and biological collapse of a fishery. Used throughout the policy and project lifecycle to provide deeper insights into actual or potential impacts of policy decisions. Now lets get into the interesting stuff – or at least what economists think is interesting. There will be opportunity for questions at the end of this plenary session.

3 Case study 1: Deep water snapper bioeconomic modelling
Work on DWS endorsed at HoF9 Effort multiplier based bioeconomic model Used to advise on proposed management plan: Management measures Fishery sustainability, Efficient regulatory regime, Other government objectives (e.g. employment, food security) Further work on deep water snapper was endorsed by Hof9. NZ funded, NIWA implemented project We produced a first stage, simple, bioeconomic model for tongan deepwater fishery This modelling brings together science and economics to project fleet behavior and catch over multiple years. Because it brings together science and economics in can be used to predict what the impact of management measures may be on various aspects of the fishery but also it can be used to develop efficient regulation, and advise governments on how to maximise employment, food security etc. Delivered under a project managed by NIWA and funded by NZ Aid Programme

4 Case study 1: Bioeconomic modelling
The data used here is false as the management plan is still in consultation in Tonga and therefore remains confidential. You can see that this fictional fishery is currently fishing above proposed total allowable catch limits, which in this case are equal to the sustainable limits The model can show us the impact of this over time

5 Case study 1: Bioeconomic modelling
What is the impact of fthis level of fishing overtime then? See how at three years, maxim fleet size is 23 (where the blue line crosses the x axis) and fleet profit maxed at 7 (the peak of the line) 5 years – max fleet size 19 vessels and economic max 4 10 years max fleet size 14 economic max is 4 vessels We can see that when fishing above the sustainable limits over time this reduces the possible fleet size in terms of the economic maximum and the maximum number of vessels However if fleet modelling had not been undertaken it could have led to wrong policy conclusions e.g. a fleet size of 24 was viable.

6 Case study 1: Bioeconomic modelling
So what is the impact of management? Here we just investigate 10 years but it can be done for any time period of interest. A simple management measure of TAC is implemented and this actually shows that management measure increases fleet viability and the maximum fleet size over 10 years from 14 to 16 vessels. So management helps to ensure sustainable fishery, protect businesses and protect employment. These results have proved very powerful in dicussions with stakeholders. Bioeconoimic modelling is critical to have an informed view of the future of a fishery and to understand the impact of management measures. As such, this work will be advanced to a more technical model in the coming years accounting for elements of viability theory that are better able to inform management.

7 Case study 2: Interactions between artisanal fishers and industrial vessels
HoF7 requested SPC investigate interactions between artisanal and industrial fisheries. Most analysis has been on the stock effects. A different approach: “how does the presence of the industrial fishery impact the artisanal fishers willingness to go fishing” Requested by HoF 7 to investigate interactions between ART and IND vessels and something I am passionate about Most analysis on impacts within the stock Using data 2012 – 2016 using data from a transshipping port in the Pacific we take a different approach and look at how industrial vessels impact the willingness of artisanal fishers to go fishing Work jointly developed by CFP Economist and Alex Tidd (OFP)

8 Case study 2: Interactions
Left graph:The presence of industrial vessels does very clearly reduce the willingness of artisanal fishers to go fishing. If no vessels are in port about 13 vessels are expected to go fishing, but with 15 vessels in port this drops to half this and when the port is very busy (20 vessels or greater) the number of fishers fishing is minimal at 4 or 5 on average. Right graoh: CPUE – KG of fish per hour fishing – shows that 20 vessels in port reduces the catch rates by more than half. Why this happens we are unclear, it could be a stock issue as stocks take a long time to recover after a large removal or it could be more experienced fishers stay at home and do not go fishing and so there is a consequential decline in CPUE. We however do not have the data to support a conclusions either way – a point of further research perhaps.

9 Case study 2: Interactions
Implications are significant, over the period of analysis we estimated: 2,200 artisanal fishing days were lost Over 5,000 lost days of employment 676 tons of fish were not landed by artisanal vessels, equivalent to yearly consumption of 11,500 people USD2.7m in revenue to artisanal fishers lost The analysis suggests that over the 4 years: 2,200 artisanal fishing days were lost – over 5,000 employment days 676 tons of fish were not landed by artisanal vessels, equivalent to yearly consumption of 11,500 people USD2.7m in revenue to artisanal fishers lost These implications sound massive but lets put them in context.

10 Case study 2: Interactions
Implications are significant, however comparison to industrial data: Over 5,000 lost days of employment but we estimate that transshipping brought at least twice this amount of employment. The ‘lost catch’ is close to or slightly greater than off loads. Revenue – SI earn $27m from license fees, Tuvalu 85% of government revenue is from license fees and Marshall Islands $17m is for access rights in 2014 (Gillett 2016) This is not to say that there is not a problem but there is some substitution of the losses in the artisanal by the industrial fishery. The issue is therefore one of distribution and therefore of government policy. Compared to the industrial data this certainly seems a smaller issue 5,000 lost employment days but at least twice that is estimated to be created for locals in transshipping jobs. Industrial vessels often off-load by-catch and damaged fish, which is about equal to the estimated losses in ART catch Revenue – license fees make up a significant contribution to government budgets and therefore support a whole range of activities including health, education and infrastructure programmes for the benefits of all local peoples. However, at the micro-scale it is impacting the lives of many individuals who often have few other choices for employment, livelihood support and food security. Demonstrates the tradeoffs inherent in all policy decisions, however analysis such as this can help understand these trade-offs and attempt to find the best possible solution to meeting maximizing welfare of all sections of society.

11 Case study 3: Cost benefit analysis: Using UBA to harvest sea cucumber in Fiji
SPC science and management team were requested to assist Fiji Fisheries providing policy advice on the use of UBA to harvest sea cucumbers. This scientific policy advice was complimented with an economic cost benefit analysis which assessed the financial and social implications of the policy options - providing evidence to indicate which management options were preferable from a “whole of society perspective”. Involved the assessment of three elements: 1. Income from harvest – estimated from surveys and literature 2. Financial cost of treatment – transport to hospital, cost of running the decompression chamber, cost of inpatient and outpatient care estimated from a range of sources Shows that the earnings from sea cucumber under the exemptions far out weighed the costs of treatment. However, Cost Benefit Analyses (CBA) takes into account other impacts on society that simple financial analysis does not – for example in this case we used a range of economic techniques to value the impact on individual’s health (and the consequential impact on society). CBA can also look at the ‘costs’ associated with other impacts such as the habitat, climate change, risk, etc. Therefore we also included the impact of accidents on the health of individuals impacted. Including the impact on peoples’ health the impact of UBA was extremely negative. Without economic analysis, only the financial benefits then the practice would not have been banned and the government would not have fulfilled its obligation to do all it can to protect the people.

12 Case study 4: Economic contribution of game fishing in New Caledonia
SPC requested by HOF9 to provide economic advice on sports fishing. Two years of data collection on catch and spending Data collected on 452 fish caught by 59 fishers Average spending per night of AUD850 Potential to support up to 41 jobs Endorsed by HoF9 to provide more analysis on game/sports fishing Two years of data collection with one operator Caught 452 fish and 59 fishers Average spending was AUD 850 We could also tell how this spending broke down e.g. on accommodation or gifts, where most of the fishing occurred etc The analysis of the data suggested that the total potential value of the industry to NC was 1.25m. I have said it before, but say it again…Economists however are not accountants! We also look at the wider implications – call the indirect economic value, this is spending by sports fishing operators on mechanics, outfitters or spending by employees on food, rent etc. We estimated that the wider economic value of 10 potential operators in NC would be between 1.1m and 3m dollars. This was also used to estimate that the industry could support both directly and indirectly up to 41 jobs. This information is important to inform fisheries management, investment and regulatory decisions such as supporting industry. This data is still being collected and we aim to move this to an electronic base later in the year and we are looking for other opportunities to expand this data collection in other locations.

13 Case study 5: Development of a bioeconomic “Longline Tuna Tool” (LTT)
SPC, in collaboration with FFA, has been using bioeconomic modeling to assist member countries in establishing biologically, and economically, sustainable industrial longline fleet sizes for their EEZs To streamline and standardize the presentations to government and industry, a sophisticated Excel spreadsheet tool was developed (with assistance from EDF)

14 Two versions of the LTT This is the “teaching” version

15 Maximum Economic Yield (MEY) and Breakeven (BE)
User defined variables (costs and prices) are input Resultant levels of effort (hooks, days, vessels) to produce MEY and BE are output. Users keep the tool for use in what-if type discussions While the LTT is “user-friendly”, it requires expert assistance from SPC/FFA analysts when used for actual management advice and actions

16 National level work tied to regional-scale bioeconomic analyses
The tool had been deployed in several countries and has indicated ways to achieve more profitable fisheries Further deployments are scheduled for 2017 In light of sub-regional management arrangements, the LTT may help define optimum fishing levels within those TAC or effort limits

17 Data collection and M&E
To effectively evaluate fisheries development initiatives data collection is critical. Standardised: support provided for data collection programmes such as FAD monitoring using SPC standardised- systems (e.g. Vanuatu). To do analysis we need data and therefore I am extensively involved in data collection programmes around the region – for example of FADs but others as well. We also are involved in capacity development for fishers, fisheries officers. You can see in the picture two fisheries officers who we trained to provide the course to others around Tonga (and will deliver in May) New attachments this year where data specialists visited the economist for up to 3 weeks to analyse a specific problem of interest and gained some general training also. World Bank Survey Solutions – which SPC can provide detailed support for and we recommend that for ah-hoc data collection Survey Solutions is the way to go. Ad-hoc: data collection using other e-collection platforms such as World Bank Survey Solutions used for ad-hoc data collections and evaluations.

18 Capacity development NFDS Capacity Development: Since 2015, 66 individuals trained in basic finance and more than 30 individuals trained in data collection. Three attachments to SPC for economic and data analysis in 2016. We also are involved in capacity development for fishers, fisheries officers. You can see in the picture two fisheries officers who we trained to provide the course to others around Tonga (and will deliver in May) New attachments this year where data specialists visited the economist for up to 3 weeks to analyse a specific problem of interest and gained some general training also. Stock assessment workshops have trained 150 since 2006

19 Thank you and please contact philipj@spc.int for more information
Conclusions Economists are involved in three main areas: Policy and project analysis Monitoring of policy and project impacts Capacity development More detail is in the economic policy brief and the working paper prepared for this session. Case studies have demonstrated some of the policy analysis that we can do, it has suggested that economic analysis enhances policy decisions by indicating possible impacts – both positive and negative –informing management decisions including resource management, regulatory regimes and efficient investment options. Most of all it is about providing practical implementable and justifiable advice for the whole process of policy making. Thank you and please contact for more information

20 Thank you and please contact philipj@spc.int for more information
Group Work Following the group work, could country representatives please complete the questionnaire during tea break and return to me or the conference reception center. Thank you and please contact for more information


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