Where are the fishing dependent areas in West Sumatra?

indicates the percentage of fishers in a district that are poor compared to the provincial average black bars. 4.3.2 Where are the fishing dependent areas in West Sumatra? Sub-districts scoring negatively for the fishing dependency index were classified as non-fishing dependent locations and those scoring positively as fishing dependent locations. Fishing dependent sub-districts were further categorised into highly fishing dependent locations dependency index 0.50, and fishing dependent locations fishing dependency index 0 - 0.50. The highly fishing dependent group included the six sub-districts Sei Beremas, Sasak Ranah Pasisie, Tarusan, Sutera, Linggo Sari Baganti, Bungus Teluk Kabang Figure 4.2. In these districts, percentage employment in sea fishing ranged between 9.1 Linggo Sari Baganti and 33.5 Sei Beremas. Sei Beremas and Sasak Ranah Pasisie are the most highly fishing dependent areas. Not only are at least one in four of the workforce there employed as fishers, together these two sub-districts are responsible for landing 45 of the total catch from all six districts 71,191 tons. The fishing dependent group comprised five sub-districts; Lengayang and Batang Kapas from Pesisir Selatan, Sungai Limau from Padang Pariaman, Tanjung Mutiara from Agam and Koto Tangah from Padang. Ten of the eleven fisheries dependent sub-districts in West Sumatra have employment in fisheries of more than 5. The one exception to this was Koto Tangah. For Koto Tangah, the geographical area of the sub-district is so large that the coastal fishing population is dwarfed by a large working population 54,654, which reduced the proportion of employment in fishing to 3.2. For this reason Koto Tangah is an example of the necessity of using a composite measure to calculate fishing dependence that incorporates total fishers and production rather than relying solely on the percentage of fishers in an area. Together these eleven fishing dependent sub- districts included 70 of the total fishers and 73 of total production in the six districts. Figure 4.2: Fishing dependent sub-districts and highly fishing dependent sub-districts in mainland West Sumatra. District names are shown in italics. The sensitivity analysis demonstrated that possible inaccuracies in the fishing production data did not affect the identification of the fishing dependent communities. When the fishing index was calculated with and without the production data, no sub-district moved between the two categories of fishing dependent and non-fishing dependent and the six most highly fishing dependent sub-districts remained unchanged. The eleven fishing dependent sub-districts from the 20102011 analysis also demonstrated fishing dependency using data from 2008. The main difference observed in the 2008 data was the inclusion of four new sub-districts in the fishing dependent category. Of these IV Jurai has simply migrated from just below the average to just above the average. The movement of the remaining three sub-districts can be explained by the difference in survey technique between the DKP surveys which documented the total fishers including those that may seldom fish and the 2010 census which forced interviewees to choose their main source of livelihood. Both of these sensitivity analyses demonstrated robustness of this method and the veracity of the underlying data. Non-fishing dependency at the district level can mask pockets of high fishing dependency at the sub-district level. Using disaggregated data available from 2008 it was possible to run the analysis to the village level. While most of the fisheries dependent villages could be predicted on their location within a fisheries dependent sub-district there were two exceptions. Both Kinali in Pasaman Barat and Lubuk Begalung in Padang contained highly fishing dependent villages with 25 and 19 employment in fishing respectively. Similarly, until the analysis moved to an increasingly detailed spatial scale it was not obvious how fishing dependent certain pockets of the sub-district of Tarusan are. Sungai Pinang is a clear example of this. Sungai Pinang is an isolated village in Tarusan surrounded by jungle with a total population of 1396. Although the 415 fishers are fewer than some other villages, 47 of the total workforce are employed in fishing. Sungai Pinang was chosen as one of the two sites for more detailed analysis in chapter 6. Highly fishing dependent areas such as Sungai Pinang only begin to emerge as the level of spatial resolution became increasingly detailed and these village examples provide powerful evidence for poverty and fisheries dependency to be viewed at multiple spatial scales. 4.3.3 What is the relationship between Fisheries dependence and poverty?