SSA6 Søndeledfjord, Norway

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…for sustainable growth in the Nort 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 Final simulation and interactive demonstration

description

Final simulation and interactive demonstration. 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 - PowerPoint PPT Presentation

Transcript of SSA6 Søndeledfjord, Norway

Page 1: SSA6 Søndeledfjord, Norway

…for sustainable growth in the North

SSA6 Søndeledfjord, Norway

Erlend Moksness, Jakob Gjøsæter, Esben Moland Olsen and Jon Helge VølstadInstitute of Marine Research, Norway

Eirik MikkelsenNORUT (Northern Research Institute), Tromsø, Norway

Håkan T. SandersenBodø University College

Istanbul, 5 February 2010

Final simulation and interactive demonstration

Page 2: SSA6 Søndeledfjord, Norway

…for sustainable growth in the North

SSA6 Søndeledfjord, Norway

Page 3: SSA6 Søndeledfjord, Norway

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SSA 7.6 Søndeledfjorden

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…for sustainable growth in the North

SSA6 Søndeled fjord-system. Southeast Norway

Norway

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Policy issue

• Policy issue developed together with municipal authorities

+ +

Maximise local economic benefits from tourism

Minimise impacts on local coastal cod stock

Minimise conflicts with local users

Economics component

Ecology component

Social component

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Fjord system elements

• 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

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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

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Factors affecting cod stock

Tourism and recreation

COD-STOCK

Recreational fishing

Marinas and beaches

2nd homes

Tourist fishing

Commercial fishing

Habitat 0-1 yr

Seal and comorant

Cod rearing

Cannibalism

R

R

R

R

Recruitment

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Local economic benefits from tourism

No. of tourist-days

Tourism expenditure

Expenditure/day

Factors

2nd homes

Local economic benefits

Building

Maintenance LEB = Expenditure x Local share x Multiplier

Tourist Categories:• Hotel-tourists• 2nd home owners• Fishing tourists• 2nd home renters• Camping-tourists

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Factors affecting number of tourist-days for tourist categories

No. of tourist-days

No of tourist-days

Conflict level (SC)

Accomodation capacity

Fishing tourist accomodation

Landscape/environment quality (EC)

Coastal cod stock state (EC)

Regulations on tourist fishing

GDP-growth rate

SC=Social component EC=Ecological component

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Guest days Risør

Guest dayst Risør. Source Statistics Norway

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10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

100 000

2005 2006 2007

Guest days

Foreigners

Norw egians

Guest days Risør. Source Statistics Norway

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10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

2005 2006 2007

Hotell

Camping/cabins

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Tourist days and expenditures • Figures used by us:

• Original expenditure data: Source Statistics Norway/TØI

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Local economic benefits from expenditure

• Parameters for LEB (local economic benefits) from tourist expenditure in the different groups: i = (Local share) * (Multiplier)

(From Auno and Sørensen 2009)

Hotel

2nd Home owners

Fishing tourists

2nd home renters

Camping tourists

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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

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Factors affecting conflict levelTourist – local inhabitants

• (But… legitimacy… process... output… conflicts…)

Local economic benefits from tourism

No of tourist-daysConflict level

indicator =

No of tourist-days

Local economic benefits from tourism

”Low” conflict level

High

Med

ium

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Policy issue & examples of links

Maximise local economic benefits from tourism

Minimise impacts on local coastal cod stock

Minimise conflicts with local users

2nd homes

Tourist days

Fishing pressure

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Regulations / Governance

• Number of 2nd homes

• Habitat conservation (”MPA Habitat”)

• Cod fishing regulations (”MPA Cod”)

• Fishing tourist dedicated accomodation

• Number of – seals and comorants– Eel fishers

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Base example

Commercial fishery LEB NOK

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50 000

100 000

150 000

200 000

250 000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

• Cod numbers by age-group

• Cod biomass

• Commercial fishery LEB

Cod SumBiomass kg

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10 000

20 000

30 000

40 000

50 000

60 000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Cod population history

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

0-group

1-group

2-group

3-group

4-group

5-group

6-group

7-group

8-group

9-group

10-group

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Base example

• Tourist days

• LEB direct touristexpenditure

• Sum LEB

Tourist days

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20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

180 000

200 000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Hotel

2nd home owners

Fishing tourists

2nd home renters

Camping

LEB from direct tourist expenditure, NOK

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10 000 000

20 000 000

30 000 000

40 000 000

50 000 000

60 000 000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Hotel

2nd HO

Fishing tourists

2nd HR

Camping

Sum Local Economic benefits NOK

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50 000 000

100 000 000

150 000 000

200 000 000

250 000 000

300 000 000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

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Example 2

• No marinas/beaches• No nets or trawl-

fishing• More dedicated

fishing-touristaccomodation(80 *****)

• Leads to:– No commercial

fishing– More fishing

tourists

Cod SumBiomass kg

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10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

100 000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

Cod SumBiomass kg

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10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

100 000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49

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Example 2

• Local economicbenefits bycategory

• Bottom diagram– No nets/trawl– No habitat

destruction– More dedicated

fishing touristaccomodation

Average LEB NOK

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5 000 000

10 000 000

15 000 000

20 000 000

25 000 000

30 000 000

35 000 000

40 000 000

45 000 000

50 000 000

Hotel 2nd HO Fishing tourists 2nd HR Camping New 2nd homes Maintenance 2ndhomes

Commercial fishery

Average LEB

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5 000 000

10 000 000

15 000 000

20 000 000

25 000 000

30 000 000

35 000 000

40 000 000

45 000 000

50 000 000

Hotel 2nd HO Fishing tourists 2nd HR Camping New 2nd homes Maintenance 2ndhomes

Commercial fishery

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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)

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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

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Thank you

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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

0i i0 ij j j k k

j

T T b (A A ) 1 (b ln(A ) 1,3) /100

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Tourist days and GDP-growth Norway

y = 3,6811Ln(x) - 1,305

R2 = 0,3503

-4

-2

0

2

4

6

8

0 1 2 3 4 5 6

Growth GDP Norway

Gro

wth

sta

ys

No

rwa

y

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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

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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

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Factors for tourist days

• 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

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Tourist factors

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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

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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

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Shell-farming in Søndeledfjord