SSA6 Søndeledfjord, Norway

1. Final simulation and interactivedemonstration SSA6 Søndeledfjord, Norway Erlend Moksness, Jakob Gjøsæter, Esben Moland Olsen and Jon Helge Vølstad Institute of Marine Research, Norway Eirik Mikkelsen NORUT (Northern Research Institute), Tromsø, Norway Håkan T. Sandersen Bodø University College Istanbul, 5 February 2010

2. SSA6 Søndeledfjord, Norway

3. SSA 7.6 Søndeledfjorden

4. SSA6 Søndeled fjord-system. Southeast Norway Norway

5. Policy issue • Policy issue developed together with municipal authorities + + Minimise conflicts with local users Minimise impacts on local coastal cod stock Maximise local economic benefits from tourism Social component Ecology component Economics component

6. Coastal cod stock Focus, and indicator for ecosystem Seals, commorants Recreational fisheries Commercial cod and prawn fishery Eel fishery, with bycatch of cod Tourism: Building and maintenance of cabins. Construction of marinas and sandy beaches Other tourist services Fishing by tourists Shell-fish aquaculture Fjord system elements

7. Modelling objective • Useful tool for policy-makers and regulators • connections between factors / trade-offs between objectives. • i.e. qualitatively more than quantitatively output • Demonstrated model for municipal authorities; interested • Regulatory options for municipality • Land regulations: Construction of cabins, marinas and beaches • Marine wildlife regulations (seal and comorant) • Fishing regulations (commercial, tourists, recreational) • Tourist service provisions (accomodation for fishing tourists) • Rear cod juveniles for release, to enhance local cod stock • Aquaculture regulation

8. Factors affecting cod stock Recreational fishing Tourism and recreation R Tourist fishing Recruitment Commercial fishing 2nd homes R COD-STOCK Cannibalism Marinas and beaches Seal and comorant R R Habitat 0-1 yr Cod rearing

9. Tourist Categories: • Hotel-tourists • 2nd home owners • Fishing tourists • 2nd home renters • Camping-tourists Local economic benefits from tourism Factors No. of tourist-days Expenditure/day 2nd homes Tourism expenditure Building Local economic benefits Maintenance LEB = Expenditure x Local share x Multiplier

10. Factors affecting number of tourist-days for tourist categories No of tourist-days Conflict level (SC) Coastal cod stock state (EC) Accomodation capacity No. of tourist-days Fishing tourist accomodation Landscape/environment quality (EC) Regulations on tourist fishing GDP-growth rate SC=Social component EC=Ecological component

11. Guest days Risør

12. Tourist days and expenditures • Figures used by us: • Original expenditure data: Source Statistics Norway/TØI

13. Local economic benefits from expenditure • Parameters for LEB (local economic benefits) from tourist expenditure in the different groups: gi = (Local share) * (Multiplier) Hotel 2nd Home owners Fishing tourists 2nd home renters Camping tourists (From Auno and Sørensen 2009)

14. Other economic effects • Commercial fishery affected by cod stock state • ”Static approach” • Changes in cod stock state (stock size) translates directly into relativel lower/higher catches, revenues and LEB • Potentially: cost of rearing cod juveniles • Potentially: Aquaculture-production, and effects on wild fish

15. Factors affecting conflict levelTourist – local inhabitants • (But… legitimacy… process... output… conflicts…) No of tourist-days No of tourist-days Conflict levelindicator High = Local economic benefits from tourism Medium ”Low” conflict level Local economic benefits from tourism

16. Policy issue & examples of links Tourist days Maximise local economic benefits from tourism Fishing pressure 2nd homes Minimise conflicts with local users Minimise impacts on local coastal cod stock

17. Number of 2nd homes Habitat conservation (”MPA Habitat”) Cod fishing regulations (”MPA Cod”) Fishing tourist dedicated accomodation Number of seals and comorants Eel fishers Regulations / Governance

18. Base example • Cod numbers by age-group • Cod biomass • Commercial fishery LEB

19. Base example • Tourist days • LEB direct touristexpenditure • Sum LEB

20. Example 2 • No marinas/beaches • No nets or trawl-fishing • More dedicatedfishing-touristaccomodation(80 *****) • Leads to: • No commercial fishing • More fishingtourists

21. Example 2 • Local economicbenefits bycategory • Bottom diagram • No nets/trawl • No habitatdestruction • More dedicatedfishing touristaccomodation

22. Challenges… • Make and use model when data availability and quality is low! • Estimate tourist-days from ”tourists-factors” • Lack of available data • Lack of relevant studies in literature • Calibrate model to produce ”reasonable” numbers for tourist-days • Understand and model in a good manner • conflict potential • Landscape quality • Get data, and better data • Tourist fishers’ catches (IMR) • Expenditure and LEB from tourists fishers (NORUT) • LEB from tourism (SSB)

23. Way forward…? • Run scenarios for municipality • Demonstrate/discuss with stakeholders • Involve high-schools in project • Demonstration made • Educational use of model • Field data collections and questionnaires for data and model improvements? • Commercial fishery • Better model for estimating changes in economic benefits due to changes in cod stock? • Include profit maximisation by fishers? • Include ? • Cod rearing • Aquaculture • Employment-effects of tourism • Search for funding to use Spicosa-framework/methodology in new projects, elaborate and refine

24. Thank you

25. Tourist-day numbers and expenditures • Tourist day numbers this year = Initial level + Effect of factors changed from initial level x Effect of economic development (GDP-growth) • Daily expenditures from national survey, + adjustments • Local economic benefits from I/O-database and own estimates

26. Tourist days and GDP-growth Norway

28. Commercial fishery • Assume linear (Schaefer) harvest function: h = q E X • Assume constant fishing effort • Fixed prices • Stock changes -> direct changes in harvest, revenues, local economic benefits

29. Landscape quality index • Subjective index Or • A calculated index • No of 2nd homes • Boat-places in marinas, and area of constructed sandy beaches • Coastal cod stock state • Number of seals and birds (comorants) • Number/area of aquaculture plants

30. Tourist groups Hotel-tourists 2nd home owners Fishing tourists 2nd home renters Camping-tourists Factors affecting number of tourist-days Total number of tourist-days Boat facilities in town centre Level of conflict between tourists and locals Standard on tourist-related services Accomodation capacity 2nd homes for rent Accomodation capacity dedicated for fishing tourists Accomodation capacity Hotel Accomodation capacity Camping Landscape and environmental quality index Regulation on construction of 2nd homes Regulation on construction of boat marinas Regulation on construction of sandy beaches State of coastal cod stock Regulations on tourist fishing Marketing expenditure tourism GDP growth in Norway same year Factors for tourist days

31. Tourist factors

32. Tourist-day numbers and expenditures • Tourist day numbers this year= Initial level+ effect of change in ”factors” from their initial level + effect of economic development (GDP-growth) • Daily expenditures from national survey + modifications • Local economic benefits from literature, I/O-database and own estimates

33. Available data, approach..? • Tourist numbers – history in Risør/Sørlandet? • Countings from tourist information? • Other data • How to build scenarios? • Based on policy instruments • Based on primary outcomes of policies • Thank you

36. Shell-farming in Søndeledfjord