Management Of The Scottish Inshore Fisheries; Assessing The Options For Change

An analysis of the impacts from different options for the management of the Scottish Inshore fisheries. In particular, the report provides an appraisal of scenarios related to restrictions on the use of mobile fishing gears within one and three nautical m


7 ECONOMIC DEPENDENCY ON INSHORE FISHING

It has been suggested that in a number of villages inshore fishing is critical to the economy and that any restrictions might have serious outcomes for the health of that community. For example the Scottish Executive (2005) stated that "fishing is the economic mainstay of many of our most remote and fragile coastal communities bringing them wealth and social cohesion".

Campbell et al (2010) examine the evidence using Travel to Work Areas ( TTWA). They found that crude measures of fisheries dependence can be misleading. In Scotland only three out of 38 coastal Travel to Work Areas ( TTWAs) show a level of employment dependence in excess of 10% (Fraserburgh 19.6%, Berwickshire 12.3%, and Uists and Barra 11.1%) and a further seven TTWAs over 5%. The measure of dependence is based on direct employment in fishing, fish processing and aquaculture. It excludes any multiplier to account for other local employment wholly or partly related to fishing activity (repair facilities; gear manufacture; box making; ice plants; transport firms etc .), let alone the proportion of local service sector jobs dependent on the local spending of incomes generated in the fisheries sector. Nor are there any regular, up to date, comparative data on value added revenues attributable to the local fisheries sector.

Basic data on direct employment, first hand sales value of landings and the fishing fleet are adequate. However the TWAs are too large to examine the dependence of small communities and also missing is the array of social data on demographics, housing, education, health and social exclusion that can help to describe the varying economic and social circumstances in which fisheries dependence may occur.

Fortunately, such data exist in the small area statistics but the use of these presents a further range of problems associated with defining communities. These problems are discussed in the following section before application of the Scottish Neighbourhood Statistics ( SNS) and the Business Register Employment Survey ( BRES) to our defined fishing communities.

After this work was finished, Jones (2013) also completed an analysis for the Marine Analytical Unit of Marine Scotland of the Scottish Index of Multiple Deprivation ( SIMD). This work is slightly different in that the data-zones around "Ports" were subjectively identified. Their rankings on the Index were then analysed. The results suggested that Fishing Communities were not significantly different from other Scottish communities with similar ranges of deprivation and affluence.

7.1 Definitions and Methodology

The basic unit utilised is the data-zone and there are 6,505 data-zones in Scotland. Each data-zone consists of around 250 households / 800 people, but may well be smaller if there is a strong argument for adhering to physical boundaries. For example, an island of 500 people may be treated as a single data zone.

Initially this research was to be confined to those data-zones whose centroids are within 2 km of the coast. This excluded inland processors and the jobs dependent upon them and could conceivably understate the impact in larger communities which have processing or engineering services located significantly more than 1 km away. In practice the effect of using the centroid is to expand the buffer area to an average of 2 km from the coast. 1450 data-zone centroids were within the buffer.

For this study it was believed that data-zones in cities such as Aberdeen needed to be distinguished from villages such as Carradale and indeed from larger towns such as Stornoway. The OS Gazetteer identifies cities, towns and villages. Some of these may be misleading e.g. Bridge of Don is defined as a village rather than as part of the City of Aberdeen, but to enable checking and replication the OS definition was utilised. A few data-zones could not be related directly and were added directly.

After some experimentation it was found a generic analysis of all data-zones on the coast was unwieldy and misleading. It was unclear, for example, how towns like Helensburgh, Perth or Portobello were relevant to an analysis of fishing communities. Instead the focus was shifted to the home ports of the fishing fleet as defined in Scottish Sea Fisheries Statistics (2012).This identifies the administrative and home port for all licensed vessels. For boats registered in Scotland the number associated with each home port were identified. The complete list of home ports is given in Appendix 1. Although single boats may be critical to the welfare of individual families, particularly on isolated island communities, the data cannot support such detail. For this analysis, therefore, a fishing community is defined as any area where there are at least 5 licensed fishing vessels. This gave some 72 towns and villages for analysis.

These 72 ports were then mapped. This was normally straightforward but a few such as Central Mainland or West Mainland or South Lochs were ambiguous and a best guess was implemented based on administrative port and distance from other home ports. This information was then combined with GIS information from the SNS and BRES.

The procedure followed was then as follows

  • Data-zones whose centroids were within 2 km of the coast were identified.
  • The nearest port was allocated to each data zone centroid and the distance between calculated.
  • All data zones where the distance was more than 2km were excluded. This still meant that in a city like Aberdeen there are 35 zones to consider.
  • In some cases e.g. island clusters; there was no data zone centroid within 2km of the harbour. In these cases the closest data zone was associated with the port.
  • In a few cases the data zone centroid was not within 2km of the coast. In these cases the data zone that includes the port was visually identified from the map.

Once the data-zones associated with each port have been identified it is easy to attach any data available at data-zone level.

7.2 The Socio-Economic Features of Fishing Communities

The SNS currently contains 1012 series at data-zone level. The Socio-Economic characteristics of communities are, however, neatly summarised in the construction of the Index of Multiple Deprivation. This ranks each zone from 1 to 6505 according to 9 criteria e.g. on the number of people seeking employment. The data zone with the highest unemployment rate is marked as 1. The Index of Multiple Deprivation combines these scores and then ranks them. For ease of inspection the scores have been grouped as follows.

Table 7.2.1 Deprivation Scores, Descriptions

Score Description
1:1500 "very deprived"
1500:2800 "deprived"
2800:3600 "average"
3600:4900 "well provided"
4900:6505 "very well provided"

Appendix 2 shows the results. Inspection of Appendix 2 shows that there is no such thing as a typical fishing community. Some are well above the average, some well below. Some in the same geographic area such as Methil and St Andrews are markedly different in their socio-economic status. Where data-zones are part of a larger community such as Aberdeen the results can be misleading as these tend to be clustered in the poorer industrial areas close to the harbour.

In order to summarise, for each fishing port, a score of 1 was allocated to "very well provided" down to 5 for "deprived." Appendix 3 presents the result for each port.

Analysis suggests that there is no correlation between socio-economic status, fleet size or geographical location (local authority). Two (St Andrews and Crail) are in the top 20% strata and two (Methil and Lybster) in the bottom 20% but the rest (68) are "normal".

As a general rule fishing communities appear to have poorer transport links and poorer access to facilities than the norm. However, those with particularly poor links, typically have above average ranks in education, health and housing. The Table below presents the number of ports achieving a particular deprivation ranking for each criterion.

Table 7.2.2 Number of Ports by Deprivation Ranking for each Criterion .

Very Well Provided Well Provided Average Deprived Very Deprived Mean Score
Drive Time 8 20 2 5 37 3.6
Public Transport 4 19 11 5 33 3.61
Access Overall 7 21 4 5 35 3.56
Crime 29 10 8 22 3 2.44
Education 6 23 29 12 2 2.74
Employment 10 22 24 15 1 2.65
Health 13 21 15 20 3 2.71
Housing 7 18 20 20 7 3.03
Income 6 26 23 16 1 2.72
Multiple Index 2 21 24 23 2 3.03

Given an expected mean of 2.5 it would appear that fishing communities tend to be around or just below average on most measures but significantly worse off in terms of access.

7.3 Unemployment

The measure of Unemployment used here is the Claimant Count as of October 2013. This tends to under-estimate the actual level of unemployment as it does not measure under-employment, fictitious self-employment and non-registration (or exclusion). On the other hand it does include those who might be undertaking unregistered casual work. Table x gives the results.

Table 7.3. Claimant Count for Coastal Communities

Community Claimants Rate Community Claimants Rate
SCOTLAND 144257 4.4% ALL FISHING 6031 4.1%
ABERDEEN 735 3.6% LOCHINVER 10 3.0%
ANSTRUTHER 67 2.9% LUING 7 1.3%
ARBROATH 304 6.0% LYBSTER 27 7.0%
ARISAIG 15 3.0% MACDUFF 164 3.5%
AYR 659 6.6% MALLAIG 12 2.5%
BALLANTRAE 22 5.6% METHIL 518 7.2%
BENBECULA 21 4.4% MONTROSE 263 4.0%
BERNERA 16 4.3% OBAN 140 3.5%
BROADFORD 34 3.0% PETERHEAD 323 4.0%
BUCKIE 198 4.6% PITTENWEEM 15 1.4%
BUTE 191 6.2% PORTREE 50 3.5%
CAMPBELTOWN 141 5.0% PORTSOY 29 3.0%
CARRADALE 13 2.9% ROSEHEARTY 19 2.4%
CASTLEBAY 17 5.1% SANDAY 14 2.6%
CENTRAL SHETLAND 7 1.1% SCALLOWAY 10 2.0%
CRAIL 24 2.3% SCALPAY 13 2.4%
DRUMMORE 15 3.7% SCRABSTER 61 3.6%
DUNROSSNESS 7 1.2% SOUTH HARRIS 28 5.0%
DUNVEGAN 13 2.6% SOUTH LOCHS 11 2.4%
EYEMOUTH 99 5.2% SOUTH RONALDSAY 5 1.1%
FORT WILLIAM 134 3.6% SOUTH UIST/ERISKAY 3 1.0%
FRASERBURGH 206 4.0% ST ANDREWS 32 0.5%
GARDENSTOWN 3 0.8% STORNOWAY 158 4.1%
GIRVAN 233 6.0% STROMNESS 23 2.1%
GOURDON 18 1.3% TARBERT 24 2.8%
GRIMSAY 17 3.3% TINGWALL 5 1.1%
HOY 9 1.4% TOBERMORY 18 2.7%
ISLAY 14 2.7% TORRIDON 13 2.8%
JOHN O'GROATS 8 1.8% TROON 201 4.8%
JOHNSHAVEN 20 3.8% ULLAPOOL 19 2.2%
KINLOCHBERVIE 6 2.0% WEST MAINLAND 0 0.0%
KIRKCUDBRIGHT 85 3.9% WESTRAY 7 1.4%
KIRKWALL 49 1.6% WHALSAY 0 0.0%
KYLE 27 6.9% WHITEHILLS 14 2.1%
LERWICK 98 2.2% WICK 240 6.6%
LOCH SCRIDAIN 10 2.5% YELL 20 4.1%

The results again suggest that fishing communities around Scotland are not developing in any specific way. Some towns with a declining industrial heritage such as Methil and Campbeltown have high levels of unemployment as do some of the remote rural villages such as Barra and South Harris. However these are contrasted by high levels of employment in oil towns like Aberdeen and in remote areas like South Uist and South Ronaldsay. The rates in Ayr, Ballantrae, Bute and Girvan may be related to the economic situation in the west of Scotland in general and to early voluntary retirement/release rather than any specific decline in fishing. In the next section we examine the industrial structure of the fishing communities.

7.4 Community Dependence on the Fishing Sector

The BRES publishes employee and employment estimates at detailed geographical and industrial levels. It collects comprehensive employment information from businesses in England, Scotland and Wales representing the majority of the GB economy. BRES is regarded as the definitive source of official government employee and employment statistics by industry. Employment is obtained by adding the number of working owners to the number of employees employed by a business where working owners include sole traders, sole proprietors and partners who receive drawings and/or a share of profits, but are not paid via PAYE.

In terms of data, the survey sample of approximately 80,000 businesses is weighted up to represent the GB economy covering all sectors. One of the strengths of BRES is that estimates are provided at detailed geographical and industrial levels (down to a lower super output geography at a 5-digit Standard Industrial Classification ( SIC)). No other Office of National Statistics employment survey output provides such information at these low levels and this enables a detailed analysis of employment at low level geographies and industries.

It should be noted BRES is a sample survey and produces estimated employment figures. These estimates are of a good quality at higher levels of geography (for example region). The quality of the estimates deteriorates as the geographies get smaller and this should be taken into account when considering the quality of sub-national estimates.

Agriculture is not collected or published at DZ level in the survey and consequently estimates of employment identified as Agriculture, Forestry and Fishing in practice only relate to Forestry and Fishing. Even then it appears that the coverage of employment in Fishing is spasmodic. Whilst the larger deep sea vessels operating from Peterhead, Buckie and Fraserburgh are included, fishermen working on small trawlers and creel boats should have but have not been identified.

Table 7.4.1 BRES Employment Data

District Regularly Employed Irregularly Employed Crofters Total BRES
Aberdeen 78 34 - 112 18
Anstruther 114 51 - 165 12
Buckie 136 48 - 184 170
Eyemouth 116 50 - 166 19
Fraserburgh 643 154 - 797 548
Peterhead 347 31 - 378 315
Scrabster 111 - - 111 26
Total East Coast 1,545 368 - 1,913 1108
Orkney 235 119 - 354 48
Shetland 231 201 - 432 211
Stornoway 298 56 17 371 50
Total Islands 764 376 17 1,157 309
Ayr 507 74 - 581 109
Campbeltown 279 44 - 323 29
Kinlochbervie 39 - 1 40 38
Lochinver 19 2 2 23 1
Mallaig 92 7 - 99 64
Oban 231 - - 231 28
Portree 152 34 34 220 31
Ullapool 124 36 - 160 3
Total West Coast 1,443 197 37 1,677 303
All districts 3,752 941 54 4,747 1,720

Despite the limitations relating to numbers of fishermen, data on the static industries, fish processing, net making and repair and boat repair should be accurate.

The Table below compares the employment in these fishing industries with employment in the tourist industries.

Table 7.4.2 Employment in Tourism and Fishing Compared

Fishing Industries Tourist Industries Difference
Marine Fishing Processing Ropes and Nets Boat Repair All Accomm. Catering Sport & Recreation All
SCOTLAND 0.1% 0.3% 0.0% 0.3% 0.7% 2.4% 4.6% 1.7% 8.6% 7.9%
ALL FISHING 1.1% 2.0% 0.0% 0.3% 3.4% 4.0% 6.2% 2.1% 12.2% 8.8%
Aberdeen 0.0% 1.0% 0.0% 0.1% 1.1% 2.6% 8.8% 1.8% 13.3% 12.2%
Anstruther 0.8% 0.2% 0.0% 1.2% 2.2% 8.1% 14.7% 1.3% 24.1% 21.9%
Arbroath 0.0% 0.0% 0.0% 0.0% 0.0% 0.6% 6.2% 1.0% 7.9% 7.8%
Arisaig 0.4% 0.0% 0.0% 0.0% 0.4% 25.4% 4.5% 0.0% 29.9% 29.5%
Ayr 0.0% 0.0% 0.0% 0.0% 0.0% 5.3% 7.0% 2.1% 14.5% 14.5%
Ballantrae 0.0% 0.0% 0.0% 0.0% 0.0% 20.2% 1.6% 0.0% 21.9% 21.9%
Benbecula 0.0% 0.0% 0.0% 0.0% 0.0% 1.7% 6.1% 0.7% 8.5% 8.5%
Bernera 14.0% 0.7% 0.0% 0.0% 14.7% 6.3% 0.7% 0.0% 7.0% -7.7%
Broadford 1.6% 0.0% 0.0% 0.0% 1.6% 14.7% 5.0% 0.4% 20.2% 18.6%
Buckie 6.2% 7.7% 0.0% 0.3% 14.2% 2.2% 4.1% 3.7% 10.1% -4.2%
Bute 0.2% 0.0% 0.0% 0.0% 0.2% 2.9% 2.9% 2.5% 8.3% 8.2%
Campbeltown 0.6% 0.0% 0.0% 0.0% 0.7% 3.4% 2.3% 4.5% 10.2% 9.5%
Carradale 3.9% 0.0% 0.0% 0.0% 3.9% 9.3% 0.0% 0.8% 10.1% 6.2%
Castlebay 1.9% 0.0% 0.0% 0.0% 1.9% 15.4% 2.7% 0.4% 18.5% 16.6%
Central Shetland 0.2% 0.0% 0.0% 0.0% 0.2% 13.1% 12.5% 3.9% 29.6% 29.4%
Crail 0.0% 0.0% 0.0% 0.0% 0.0% 27.7% 4.0% 12.1% 43.8% 43.8%
Drummore 0.0% 0.0% 0.0% 0.0% 0.0% 10.4% 11.9% 0.0% 22.4% 22.4%
Dunrossness 0.7% 0.0% 0.0% 0.0% 0.7% 9.3% 0.0% 0.4% 9.7% 9.0%
Dunvegan 0.0% 0.0% 0.0% 0.0% 0.0% 12.7% 16.4% 0.7% 29.9% 29.9%
Eyemouth 2.2% 12.0% 0.0% 0.0% 14.2% 1.1% 6.6% 2.2% 9.9% -4.3%
Fort William 0.1% 0.0% 0.0% 0.0% 0.1% 9.6% 8.6% 1.8% 20.0% 19.9%
Fraserburgh 7.2% 18.9% 0.4% 0.4% 26.9% 0.0% 3.2% 1.7% 5.0% -21.9%
Gardenstown 60.3% 0.0% 0.0% 0.0% 60.3% 0.0% 2.6% 0.0% 2.6% -57.7%
Girvan 0.2% 0.0% 0.0% 0.0% 0.2% 0.7% 8.1% 0.8% 9.6% 9.3%
Gourdon 0.0% 0.0% 0.0% 0.0% 0.0% 4.1% 6.3% 0.0% 10.3% 10.3%
Grimsay 2.3% 0.4% 0.0% 0.0% 2.7% 29.1% 0.0% 0.0% 29.1% 26.4%
Hoy 1.8% 0.0% 0.0% 0.0% 1.8% 0.4% 5.5% 2.6% 8.5% 6.6%
Islay 0.0% 0.0% 0.0% 0.0% 0.0% 5.8% 0.9% 6.3% 13.0% 13.0%
John O'groats 0.0% 0.0% 0.0% 0.0% 0.0% 10.6% 0.0% 0.0% 10.6% 10.6%
Johnshaven 5.0% 0.0% 0.0% 0.0% 5.0% 6.9% 1.3% 0.0% 8.2% 3.1%
Kinlochbervie 15.7% 0.0% 0.0% 0.0% 15.7% 5.7% 0.0% 2.9% 8.6% -7.1%
Kirkcudbright 0.8% 14.3% 0.0% 0.0% 15.1% 3.5% 1.9% 3.0% 8.4% -6.7%
Kirkwall 0.5% 0.0% 0.0% 0.0% 0.5% 4.1% 3.0% 1.9% 9.0% 8.5%
Kyle 1.8% 0.0% 0.0% 0.5% 2.3% 4.8% 8.6% 1.8% 15.2% 12.9%
Lerwick 2.4% 3.4% 0.0% 0.9% 6.7% 2.1% 4.9% 2.7% 9.7% 3.0%
Loch Scridain 3.1% 0.0% 0.0% 0.0% 3.1% 33.7% 8.2% 0.0% 41.8% 38.8%
Lochinver 0.4% 0.0% 0.0% 0.0% 0.4% 19.8% 5.8% 5.1% 30.7% 30.4%
Luing 0.8% 0.0% 0.0% 0.0% 0.8% 0.0% 4.0% 2.4% 6.3% 5.6%
Lybster 1.5% 0.0% 0.0% 0.0% 1.5% 3.7% 0.0% 0.0% 3.7% 2.2%
Macduff 1.6% 0.0% 0.3% 3.4% 5.4% 1.1% 2.5% 2.1% 5.7% 0.3%
Mallaig 15.2% 7.3% 0.0% 0.0% 22.5% 4.8% 10.4% 0.0% 15.2% -7.3%
Methil 0.0% 0.0% 0.0% 2.7% 2.7% 0.6% 2.0% 4.0% 6.6% 3.9%
Montrose 0.1% 0.0% 0.0% 0.0% 0.1% 3.3% 6.8% 3.1% 13.3% 13.2%
Oban 0.5% 0.0% 0.0% 0.0% 0.5% 8.4% 5.1% 1.8% 15.3% 14.8%
Peterhead 4.4% 5.2% 0.1% 0.2% 10.0% 2.7% 4.0% 1.5% 8.2% -1.8%
Pittenweem 2.5% 0.0% 0.0% 0.0% 2.5% 0.0% 14.7% 0.5% 15.2% 12.7%
Portree 0.4% 0.0% 0.0% 0.0% 0.4% 11.5% 4.3% 0.7% 16.5% 16.1%
Portsoy 0.8% 8.2% 0.0% 0.0% 9.0% 3.8% 6.0% 0.0% 9.9% 0.8%
Rosehearty 6.1% 0.0% 0.0% 6.1% 12.3% 9.6% 1.8% 5.3% 16.7% 4.4%
Sanday 1.3% 0.0% 0.0% 0.0% 1.3% 6.0% 0.0% 0.0% 6.0% 4.6%
Scalloway 0.0% 13.2% 0.0% 0.2% 13.4% 4.7% 1.4% 0.0% 6.1% -7.3%
Scalpay 0.9% 0.0% 0.0% 1.5% 2.4% 15.4% 1.5% 0.0% 16.9% 14.5%
Scrabster 0.2% 0.0% 0.0% 0.0% 0.2% 10.6% 0.3% 0.0% 10.9% 10.7%
South Harris 0.0% 0.0% 0.0% 0.0% 0.0% 9.3% 3.9% 0.0% 13.2% 13.2%
South Lochs 4.1% 0.0% 0.0% 0.0% 4.1% 4.7% 6.8% 0.0% 11.5% 7.4%
South Ronaldsay 1.3% 0.0% 0.0% 0.0% 1.3% 12.6% 24.5% 0.0% 37.1% 35.8%
South Uist/Eriskay 14.0% 2.3% 0.0% 0.0% 16.3% 53.5% 0.0% 0.0% 53.5% 37.2%
St Andrews 0.0% 0.0% 0.0% 0.0% 0.0% 6.1% 10.3% 4.2% 20.7% 20.7%
Stornoway 0.1% 1.6% 0.0% 0.0% 1.7% 2.9% 3.0% 0.6% 6.6% 4.8%
Stromness 0.1% 1.9% 0.0% 1.4% 3.4% 6.7% 4.9% 3.5% 15.1% 11.7%
Tarbert 3.2% 5.0% 0.0% 0.0% 8.2% 3.2% 9.4% 0.0% 12.6% 4.4%
Tingwall 0.5% 0.0% 2.8% 0.0% 3.3% 0.5% 0.5% 7.5% 8.5% 5.2%
Tobermory 1.3% 0.9% 0.0% 0.0% 2.2% 16.8% 4.6% 0.2% 21.6% 19.4%
Torridon 1.7% 0.0% 0.0% 0.0% 1.7% 37.3% 3.0% 6.0% 46.3% 44.7%
Troon 4.3% 0.0% 0.0% 0.3% 4.7% 5.3% 9.9% 3.5% 18.7% 14.0%
Ullapool 0.4% 0.0% 0.0% 0.0% 0.4% 17.0% 9.6% 2.2% 28.8% 28.4%
West Mainland 4.3% 0.0% 0.0% 0.0% 4.3% 0.0% 0.0% 0.0% 0.0% -4.3%
Westray 4.1% 2.1% 0.0% 0.0% 6.2% 5.8% 0.0% 0.8% 6.6% 0.4%
Whalsay 16.9% 18.2% 0.0% 0.0% 35.1% 0.0% 0.0% 1.3% 1.3% -33.8%
Whitehills 12.7% 30.5% 0.0% 0.0% 43.2% 0.0% 5.1% 0.0% 5.1% -38.1%
Wick 0.8% 0.0% 0.0% 0.0% 0.8% 2.2% 1.9% 0.3% 4.3% 3.6%
Yell 0.0% 0.0% 0.0% 0.0% 0.0% 4.2% 0.0% 4.6% 8.8% 8.8%

The communities where employment in fishing related industries exceeds 20% are marked in yellow. With the exception of Gardenstown, all these communities have processing plants. In general, employment in tourist industries substantially exceeds that in fishing related industries. This is illustrated by the final column of the table. Where tourism employment does not exceed fishing sector employment is marked in red type. Where this exceeds 10% (marked by a yellow background) it could be argued that there was economic fragility. However Whalsay, Whitehills and Gardenstown all have low or very low unemployment; only Fraserburgh might be classified as a fragile fish based economy.

In summary, it would appear to be difficult to argue that fishing communities face exceptional problems and are unhealthily dependent upon a sustained supply of fish. Clearly difficulties would arise if vessels left the industry because of a steep rise in costs or exceptional restrictions but these would appear to be no more extreme than problems regularly faced by their urban compatriots.

If it became clear that a policy would lead to redundancy in the fishing sector but an overall rise in welfare for the people of Scotland there is nothing exceptional within the communities that would justify an exceptional response.

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