Scenario 1: Model equations and parameter values

Fisheries are the dominant sector, both in terms of production and employment.

The following equations and parameters have been built into the VENSIM model to determine the allocation of workers between tourism and fishery activities for scenario 1. Initially there are seventy workers with seventy per cent allocated to fisheries and thirty per cent to tourism. The initial number of hotels is one and the maximum capacity is five hotels. The maximum fish harvest per worker is one tonne (1000kg) per month. The initial harvest per worker is 120kg/ month. There is also a total of 28.13 hectares of mangrove area for the community and the simulation is run for 120 months.

The simulation equations for scenario 1 are:

Employment (N)

Total employment N 70

Tourism employment (1 )

2 d

N_T N

Fish employment (1 )

2 d

N_F N

Tourism (T)

Intrinsic growth rate of tourism r_T 0.05 Maximum tourism (hotels) T 5

Tourism (hotels) T Tdt

Growth of tourism N T T

T r r

T _T ^T 0.0001 _T

(Expected) tourism wage W_T 0.2T(400 5T_T)

Fish harvest per worker (F)

Intrinsic growth rate of fish r_F 0.01 0.00155T 0.01F harvest/worker

Maximum fish harvest/worker F = 1 (ton/month)

Growth of fish harvest/worker

F F F r

F _F 1

Fish harvest/worker (ton/month) F Fdt Fish cost per ton C_F 500 F Fish price per ton P_F 3500 0.05F

Profit (net earnings)

Fish profit Y_F (P_F C_F)F Total earnings B Y_F W_T Relative earnings difference

B W d Y^{F T}

Initial Conditions

Tourism T 1 Fisheries F 0.12 8.4.2.1 Discussions of results

Fisheries are the dominant sector in terms of labour and production for the Pangaimotu community. Figure 8.1 shows the initial allocation of workers. At present, most workers are engaged in fisheries and only thirty per cent in the tourism industry. However, once tourism activity picks up, the number of workers in tourism also increases. In fact, the number of workers in tourism increases exponentially from twelve workers initially in the first six years and then levelling

off to thirty three workers after that. Correspondingly, in the face of increased tourism activity, fisheries workers declined dramatically over the same period.

That is, increased tourism activity resulted in a decline of fisheries workers from fifty eight workers initially, levelling off at thirty seven workers after seventy-two months (six years). According to the simulation, after almost ten years of operation, the labour allocation would almost be equally split between tourism and fisheries industries (see Figure 8.1).

Figure 8.1: Labour Allocation

An increase in the number of tourism resorts would also mean reclaiming more mangrove areas for tourism development. Land reclamation would have a direct impact on mangrove areas that would otherwise be available as nursery grounds for fisheries, which, in turn, would mean a decline in fish stocks for the community. Therefore, an important decision the community would have to make is how much of their mangrove areas should be allowed to be reclaimed for further tourism development, that is, how much mangrove clearance is sustainable in relation to the food security of the community that derives from fisheries activities?

The simulation model seeks to highlight salient issues once the status quo changes for the community. Indeed, the model presented here seeks to demonstrate that increasing the number of tourism resorts will also increase job opportunities in a complementary approach to maintaining a sustainable level of fisheries for the Number of workers

60 48 36 24 12 0

0 12 24 36 48 60 72 84 96 108 120

months

Fish employment workers

Tourism employment workers

community due to the transfer of workers from fishing to tourism. In other words, the labour transfer from fishing to tourism (especially to obtain higher paid jobs) should be seen as an incentive to the community, given the benefits such as a better standard of living, a higher income to buffer external shocks, and better access to infrastructure and social development. That is, migrating to tourism work (if there is an expansion of the current level of tourism development) may enhance the living standards of the community. The variables in the simulation model are included to allow us to explore the linkages and interactions between the movements of fisheries labour into the tourism sector. In Figure 8.2, through the cause and effect flows in the model, we can study the proposition that job creation in the tourism sector, together with the growth of the tourism industry, would continue to maintain a sustainable level of fisheries for the community due to the transfer of workers from fishing to tourism. The number of hotels grows rapidly in the first nineteen months (see Figure 8.2), with the establishment of another tourism related hotel. The maximum capacity for the community reaches its peak after 100 months, with around five hotels built and then levelling off.

Figure 8.2: Tourism growth

From Figure 8.2, it can be seen that growth in the number of tourism resorts will increase job opportunities, see Figure 8.1 (hence fisheries workers will move from fisheries into tourism). This increase in tourism also, however, implies that more mangrove land will be cleared. An increase in the number of tourist activities will

Number of

have flow on effects so far as fish profit and the amount of fish harvest per worker are concerned (see Figure 8.4).

Since the model is also simulating a labour out-migration from the fisheries to tourism sector, variables related to the tourism sector are also included. The effects are modelled because we would like to include the effects of a reduction in fish catch (assuming workers shift from fishing to tourism jobs) and growth in tourism over time. Changes in the tourism sector then affect sector profit. This is shown in the simulation model.

Figure 8.3: Expected tourism income (wage)

The expected income of the tourism sector in turn affects inter-sectoral profit differences (relative profit). Given a change in relative profits in favour of tourism, for example, as workers migrate from fisheries to the tourism sector, the tourism sector expands. An expansion in employment in tourism will therefore reduce fish harvest per worker. Hence, the simulation model links all the causes and effects of the complementary approach proposed.

From Figure 8.3, it cam be seen that tourism income increases with the increase in tourism employment, from an initial income of T$81 per month to around T$450 per month after approximately 100 months. During this time a shift in workers from fishing to tourism occurs, given the relative wage difference.

T$

While there is a growth in the tourism sector, the opposite is happening in the fisheries sector. From Figure 8.1, it can be seen that fish employment falls from an initial labour allocation of fifty eight workers to thirty seven workers, with a general increase in fish harvest per worker from 120kg per worker per month to level off at 150kg per worker after about six and a half years (see Figure 8.4).

Figure 8.4: Fish harvest per worker (ton/month)

Net fish earnings per worker, on the other hand, generally increased at a much slower pace, from just over $360/worker/month to level off at almost

$454/worker/month after about six and a half years (see Figure 8.5).

Figure 8.5: Fish Earnings (T$/worker/month)

While there is a general increase in fish harvest per worker (Figure 8.4), intrinsic growth and fish growth were greatly affected indicating a fast crash of the system (see Figure 8.6). This is further affected by the growth in the tourism sector, which leads to an increase in reclaimed mangrove areas, hence a decrease in the breeding grounds available for fisheries.

An increase in the growth of the tourism sector will see workers moving from fishing to tourism. The expected income from tourism will also see an increase in total earnings for the community. With more workers moving to the tourism sector, there will be a decrease in the intrinsic growth rate of the fish harvest due to the lack of protection for the juvenile fish (see Figure 8.6). This happens because mangroves will have been cleared to meet the growth of the tourism industry (involving increased reclamation of mangrove land for tourism development).

Figure 8.6: Intrinsic growth of fish harvest (ton//worker/month)

But as Figure 8.5 suggests, fish earnings per worker can rise (and eventually stabilise), despite the adverse impact of tourism on mangrove breeding grounds.

Nevertheless, earnings are sensitive to the destruction of mangroves. With a twenty per cent increase in the adverse impact of tourism on mangroves (implying a reduction in the intrinsic growth rate of the fish harvest from rF = 0.01 - Tons

0.008 0.006 0.004 0.002 0

0 12 24 36 48 60 72 84 96 108 120

Time (month)

ton/worker Intrinsic growth rate of fish harvest

0.00155T - 0.01F to r_F = 0.01 - 0.00186T - 0.01F, we note a resulting decline in fish harvest, see Figure 8.7 and net earnings (profits) per worker see Figure 8.8 . Figure 8.7: Fish harvest per worker