Corresponding author: Murat Dağtekin ( muratdagtekin998@gmail.com ) Academic editor: Adnan Tokaç
© 2021 Murat Dağtekin, Devrim Selim Misir, İsa Şen, Cemil Altuntaş, Gülsüm Balçik Misir, Ali Çankaya.
This is an open access article distributed under the terms of the CC0 Public Domain Dedication.
Citation:
Dağtekin M, Misir DS, Şen İ, Altuntaş C, Balçik Misir G, Çankaya A (2021) Small-scale fisheries in the southern Black Sea: Which factors affect net profit? Acta Ichthyologica et Piscatoria 51(2): 145-152. https://doi.org/10.3897/aiep.51.62792
|
Small-scale fisheries (SSF) is a local and community-based activity that can be traced back to ancient times, and thus, closely related to the history of humankind. However, large-scale fisheries have grown tremendously, approaching an industrial sector in the last century, due to their socio-economic and political properties, including both national and international aspects. This progress towards industrial-scale fisheries led to the involvement of scientific research, first aiming to improve production efficiency, and then, to protect ecosystems as resources exploited for fisheries activity, by mitigating their adverse impacts. During this evolutionary progress, SSF was usually neglected because of their limited production ability, and thus minimal economic contribution, until the later phase when the protection of ecosystem resources gained sufficient importance. As a result of this, many countries lack data on SSF, undermining efforts for the creation of proper policies for this type of fisheries. The aim of this study was to evaluate the productivity and the effects of some demographic characteristics, boat structures, and some cost (input) items on the net profit of SSF in the Black Sea. The eligible sample for this study consisted of 5575 small-scale fishing boats in the Black Sea. The number of fishers to be surveyed was determined as 315 using the “Simple Random Sampling” method, based on operators of boats < 12 m, i.e., boats in the SSF. Questionnaires were conducted face-to-face with fishers. In this study, it was tested if six parameters were investigated to determine whether they had a significant effect on net profit in SSF. These parameters were: (1) engine power; (2) number of fishing days; (3) boat length; (4) consumption of fuel in fishing; (5) education level of fishers; and (6) overall professional experience of fishers. To do so, Simple Linear Regression Analysis was performed to determine the effect of the data considered as independent variables when the net profit was set as the dependent variable. Atlantic bonito, Sarda sarda (Bloch, 1793); whiting, Merlangius merlangus (Linnaeus, 1758); rapa whelk, Rapana venosa (Valenciennes, 1846); and turbot, Scophthalmus maximus (Linnaeus, 1758) were the most important commercial fish species for small scale fishing. When catch per boat in SSF was evaluated, Kırklareli province ranked first with 97 007 kg, with Atlantic bonito (44 778 kg) being the most common species caught. Samsun had the second-largest catch per boat with 91 761 kg. The total net profit of 303 boats was calculated as €1 794 938 and the mean net profit per boat was €5924. The highest per boat mean net profit (€25 909) was in Kırklareli. According to the results of the study, the number of days at the sea, boat length, engine power, and fuel cost had a significant effect on the net profit while education level and professional experience were not important in productivity. The economically-fragile SSF sector may need some kind of supporting subsidy. It would be beneficial to provide support to the majority of fishers active in the SSF in terms of complementary alternative employment opportunities in the regions where they are located.
Black Sea, net profit, productivity, revenue, small-scale fisheries, total cost
Small-scale fisheries (SSF) is not considered as an economic sector. In their own right since SSF tend to be closely related to local communities, traditions, and values (
The amount of main SSF marine products used for human consumption, such as fish flesh, roe, fins, etc. is around 30 million tons/year (
Due to the inherent variability, complexity, and uncertainty, it is difficult to create a consensus definition that would be applicable to all global SSFs. Therefore, sectoral-based definitions for SSF have to be general. SSF has been defined as a dynamic and developing sub-sector of fisheries, using labor-intensive catching, processing, and distribution technologies to take advantage of marine and inland fishing resources (
Fisheries, in general, is defined as an activity that involves the catching, preservation, processing, transporting, and marketing of the product. Additionally, there are bilateral related sectors, such as construction and repair/maintenance of fishing gear, boats, and engines. There is no doubt that SSF plays a prominent role in the value chain, in the fishery market as a product supplier, and in the industrial and service sectors as a dependent customer. All these associated sectors, together with fish production, create the total contribution of the fishery sector to national, regional, and local economies.
The aim of this study was to analyze the socio-economic status of the SSF in the Black Sea. A set of socio-economic indicators were investigated that enabled an estimate of their significance to net profit in the SSF so that these results can be exploited to enhance the management of fisheries in the region. The following SSF fleet composition will provide the required data and information.
Data from 2017 reported a total of 14 479 fishing boats operating in Turkey. Of these, 12 983 (89.7%) have a boat length less than 12 m and thus constitute the SSF fleet active throughout the coasts of Turkey. These proportions are similar in the Black Sea, with 5575 fishing boats, of which 5141 (88.6%) are shorter than 12 m (
These numbers indicate that the majority of boats involved in the Black Sea fishing are actually part of the Black Sea SSF, both in terms of structure and function. Although the number of boats in the SSF fleet is known, data and information concerning the socio-economic properties are scarce and limited. As result, it is almost impossible to predict their potential socio-economic performance. Such predictions are essential for developing efficient management strategies and solutions, considering both the sustainability of SSF activities and ecosystem resources and thus achieving a more rational use of resources and sustainable levels of the fishery.
The sample was drawn from the SSF in the Black Sea. These numbered 5141 (88.6%) with a boat length < 12 m of a total of 5575 fishing boats operating in the Black Sea (
The study was based on a field survey, to be conducted by face-to-face interview, in order to collect data via a specifically prepared questionnaire. The number of fishers to be surveyed was determined by using the simple random sampling method, using the following equation (
where, n is the number of boats surveyed; N refers to the total population of boats (5575); z is the standard normal distribution value corresponding to the desired confidence level (95%); C is the coefficient of variation; and d is the margin of error (±10%), accepted in the study.
In order to arrange the meetings with fishers, a series of informative meetings was first organized with the regional authorities, including the departments of Provincial Directorates of the Ministry of Agriculture and Forestry and Fisheries Cooperatives in order to prepare the work program schedule for each fishing port where the project personnel would meet with fishers who were boat owners in order to conduct the surveys.
The questionnaire forms were used to create the main data resource. The survey consists of three sections, each of which has a set of questions on: a) the social status of the boat owners; b) information on boats and fishing operations; and c) the economic features of their fishing operations.
Considering the possible variations due to demographic or technological differences which can influence the comparability of the analysis leading to bias, a set of parameters free from such bias were selected for evaluating the efficiency of SSFs in the Black Sea. Costs and revenue figures were converted to Euro equivalents (€) for standardization purposes at the exchange rate quoted by the Central Bank of the Republic of Turkey for 2015 (
There were six parameters selected to test for their influences on the net profit in SSF. These were: (1) engine power, (2) numbers of days at sea, (3) length of boat, (4) fuel costs, (5) education level, and (6) professional experience of fishers. Once these parameters were selected and the data associated was collected, collated, and compiled for analysis, a simple linear regression analysis (SLRA) was performed in SPSS, version 13.0 (IBM Inc., Armonk, NY, USA). This was done to determine the effect when data from the selected parameters were designated independent variables and the net profit was designated as the dependent variable. The SLRA is a statistical test that predicts the relations between the independent and the dependent variables and the nature of the relation (
Even though the calculated number of fishers to be surveyed was 284, face-to-face interviews were carried out with 315 boat owners from 15 provinces including (eastern) Giresun, Ordu, Artvin, Rize, Trabzon, (central) Samsun, and (western) Bartın, Zonguldak, Kastamonu, Sinop, Sakarya, Kırklareli, İstanbul, Kocaeli, and Duzce (Fig.
During the study, 32.3% of the respondents were in the age group aged 50–59 years with the mean value of 49.7 ± 11.4 years while the range was 21–78 years. Dağtekin (unpublished) in a study carried out in Trabzon province reported that 42% of the boat owners were in the 40–49 years age group. Similarly,
The fishers’ education level was predominantly primary school level (48.6%). This proportion for Turkish fishers showed a slight improvement on earlier studies. The proportion who were primary school graduates in earlier studies were: 58.44% in the Black Sea (
In the presently reported study, the mean number of years of experience of the fishers surveyed was 29.4 ± 12.7. The household population of fishers varied between 2 and 7 family members. The corresponding mean values were 3.38 in the Aegean region (
Socio-demographic characteristics of fishers on the Turkish Black Sea coasts.
Category | Variable | [%] |
---|---|---|
Age (years) | 20–29 | 4.2 |
30–39 | 15.7 | |
40–49 | 26.2 | |
50–59 | 32.3 | |
60–69 | 18.5 | |
≥70 | 3.2 | |
Marital status | Single | 10.5 |
Married | 89.5 | |
Number of children | 0 | 13.2 |
1 | 15.8 | |
2 | 39.2 | |
3 | 21.9 | |
4 | 8.0 | |
5 | 1.9 | |
Level of education | Primary school | 48.6 |
Secondary School | 21.1 | |
High school | 25.9 | |
Associate degree | 2.6 | |
University | 1.9 | |
Social security | With social security | 78.3 |
Without social security | 21.7 | |
Second revenue | Fishing only | 56.1 |
Having a second revenue | 43.9 | |
Fishing experience (years) | 1–10 | 8.4 |
11–20 | 25.0 | |
21–30 | 24.4 | |
31–40 | 26.6 | |
41–50 | 7.5 | |
>50 | 8.1 | |
Number of children engaged in fishing profession | Yes | 19.9 |
No | 80.1 | |
Satisfaction | Satisfied | 34.8 |
No Satisfied | 13.4 | |
Moderate level satisfied | 51.8 | |
Do you plan to continue the profession in the future? | Yes | 87.7 |
No | 11.4 | |
Are you satisfied with the legal regulations? | Yes | 31.5 |
No | 68.5 |
The analyses of the distribution of catch by species, the net profit by province, and the relation between inputs and net profit of SSF were performed using data from fishing operations in one season along the Black Sea coastline of Turkey. Kırklareli, the westernmost province, was where the maximum yield (97 007 kg) of fish was caught. Atlantic bonito, Sarda sarda (Bloch, 1793), was more frequent and one of the most important species in the populations studied. The mean value of the catch of Atlantic bonito was 44 778 kg/boat in Kırklareli and 22 977 kg/boat in Samsun. Moreover, Atlantic bonito was also the top species caught by the boats in Kocaeli province (19 183 kg) whilst anchovy (10 500 kg) was the second species caught most often by boats (Table
Region | Target species | Total | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
Artvin | 2487 | 5015 | 1500 | 9029 | 6300 | 3378 | 500 | 1500 | 3437 | 3750 | 36 896 | |||
Bartın | 4820 | 8465 | 250 | 200 | 3000 | 790 | 6250 | 750 | 17 050 | 300 | 41 875 | |||
Düzce | 15 500 | 18 817 | 1602 | 3200 | 3000 | 24 000 | 10 000 | 2000 | 78 119 | |||||
Giresun | 1656 | 4642 | 200 | 21 552 | 2025 | 2640 | 2850 | 235 | 1500 | 10 000 | 2000 | 49 300 | ||
İstanbul | 4332 | 9573 | 3831 | 3900 | 3875 | 4750 | 300 | 1917 | 26 000 | 18 112 | 76 590 | |||
Kastamonu | 2252 | 13 732 | 3308 | 1150 | 5475 | 1588 | 683 | 325 | 993 | 250 | 10 200 | 3972 | 43 928 | |
Kırklareli | 19 857 | 44 778 | 10 643 | 750 | 3360 | 2950 | 700 | 100 | 1483 | 5486 | 6900 | 97 007 | ||
Kocaeli | 10 050 | 1399 | 19 183 | 3439 | 8833 | 8950 | 5350 | 750 | 8000 | 6583 | 2333 | 74 870 | ||
Ordu | 2225 | 13 905 | 34 911 | 6190 | 7291 | 1010 | 5360 | 4600 | 3000 | 78 492 | ||||
Rize | 2672 | 4638 | 1375 | 6000 | 839 | 1995 | 500 | 150 | 3451 | 3417 | 3500 | 28 537 | ||
Sakarya | 1710 | 11 800 | 5540 | 1500 | 2733 | 550 | 8775 | 3300 | 35 908 | |||||
Samsun | 2592 | 22 977 | 4862 | 3100 | 11 312 | 4500 | 1687 | 6967 | 2718 | 3000 | 23 225 | 4821 | 91 761 | |
Sinop | 400 | 14 723 | 3933 | 9583 | 2887 | 4570 | 762 | 1208 | 2818 | 150 | 1717 | 1150 | 43 901 | |
Trabzon | 187 | 1910 | 8485 | 2934 | 11 572 | 3144 | 2998 | 700 | 1804 | 1325 | 200 | 16 900 | 2192 | 54 351 |
Zonguldak | 1039 | 5962 | 2992 | 4267 | 16 667 | 7927 | 7877 | 500 | 2250 | 10 230 | 12 740 | 72 451 |
The total and mean net profits of the 303 boats surveyed were, respectively, €1 794 938.00 and €5924.00. Total catch earnings of the 10 active boats in one year in Kırklareli amounted to €259 090. Fishers from Kırklareli reported both the highest revenue and the highest mean net profit among the provinces included in this study. However, many provinces had comparatively low net profit in one season: the mean were €1124 in Rize; €1833 in Trabzon, and €2185 in Giresun per boat (Table
Total and mean revenue, net profit, and total costs of boats by provinces.
Province | Number of total boats | Interviews number of boats | Total net profit [€] | Mean net profit [€] | Mean total revenue [€] | Mean total costs |
---|---|---|---|---|---|---|
Artvin | 233 | 13 | 111 341 | 8565 | 11 596 | 3031 |
Bartın | 180 | 12 | 36 766 | 3064 | 5458 | 2394 |
Düzce | 67 | 7 | 78 271 | 11 182 | 15 618 | 4436 |
Giresun | 514 | 27 | 58 988 | 2185 | 6184 | 3999 |
İstanbul | 214 | 21 | 108 035 | 5145 | 8791 | 3646 |
Kastamonu | 208 | 16 | 128 899 | 8056 | 10 928 | 2872 |
Kırklareli | 85 | 10 | 259 090 | 25 909 | 30 703 | 4794 |
Kocaeli | 134 | 19 | 189 101 | 9953 | 12 832 | 2879 |
Ordu | 401 | 20 | 200 855 | 10 043 | 19 007 | 8964 |
Rize | 915 | 39 | 43 835 | 1124 | 4573 | 3449 |
Sakarya | 57 | 7 | 89 215 | 12 745 | 18 501 | 5756 |
Samsun | 398 | 23 | 173 980 | 7564 | 11 850 | 4286 |
Sinop | 364 | 23 | 103 244 | 4489 | 7938 | 3449 |
Trabzon | 974 | 46 | 84 323 | 1833 | 6626 | 4793 |
Zonguldak | 397 | 20 | 128 994 | 6450 | 10 605 | 4155 |
Total | 5141 | 303 | 1 794 938 | 5924 | 10 108 | 4184 |
The reported boat engine power was highly variable, ranging from only 2.98 kW to 261 kW, with a mean value of 45.54 kW. The number of days at sea also varied widely, from 10 to 310 days, with a mean of 159 days. The length of boats ranged between 4.4 to 12 m, with a mean of 7.47 m. Fuel cost varied, as expected by both engine power and the number of days of fishing, with a mean of €1325 (Table
Parameters | Min. | Max. | Mean | SD |
---|---|---|---|---|
Engine power [kW] | 2.98 | 261.00 | 45.54 | 42.50 |
Number of days at sea | 10.00 | 310.00 | 159.08 | 79.06 |
Length of boat [m] | 4.40 | 12.00 | 7.47 | 1.63 |
Fuel costs [€] | 66.00 | 9917.00 | 1482.50 | 1325.28 |
Age of boat | 1.00 | 45.00 | 14.95 | 9.89 |
Each of the six selected parameters had some effect on net profit, with the exceptions of professional experience and education level (see Table
Relations between engine power, number of fishing days, fuel consumption, boat size, and net profit.
Relation of variables with net profit | Model summary table | Coefficient table | |||
---|---|---|---|---|---|
R 2 | F | Sig. | β | Sig. | |
Engine power [kW] | 0.084 | 20.180 | P < 0.05 | 547.520 | P < 0.05 |
Number of days at sea | 0.030 | 9.309 | P < 0.05 | 322.161 | P < 0.05 |
Length of boat [m] | 0.196 | 73.371 | P < 0.05 | 16.179 | P < 0.05 |
Fuel costs [€] | 0.109 | 36.832 | P < 0.05 | 29.657 | P < 0.05 |
Professional experience of fishers | 0.010 | 0.290 | P > 0.05 | ||
Education level | 0.010 | 0.198 | P > 0.05 |
The management of SSF is important not only for the protection of natural resources but also for the sustainable living standards of the citizens whose subsistence is dependent on this activity. We estimate that a total of 26 800 people are reliant on the Black Sea SSF made up of approximately 6700 crew, who are directly dependent on fishing, on the Black Sea coastline of Turkey on 3372 active boats, and including the number of people in their households. Thus, it would be reasonable to assume that the numbers reliant to some extent on the Black Sea SSF will exceed 100 000 when the sectors related to the fishery, such as wholesalers and retailers, equipment manufacturers of engines and the fishing gear are also considered. Nonetheless, the focus of this study was to analyze only the profitability of fishing performance of the boats smaller than 12 m, as they compose the core of the SSF fleets. A further aim was to raise awareness of the sustainable use of fishing resources as a social responsibility, which goes far beyond simple environmental issues
The number of days that the boats of SSF fleet spend at sea is low. According to FAO criteria, the boat is considered active when it is at sea fishing even for one day. Therefore, when the mean revenue and catch per boat is reported, it is unlikely to reflect the status of the active boats throughout the year.
The mean age of fishers in this study was late middle age. As SSF is an active form of artisanal fishing, if this sector is to be encouraged then it will be necessary to provide support to attract younger people into the SSF, as has been reported previously (
The majority of the fishers were primary school graduates. When the reasons for practicing SSF were examined, it was found that this job was sought around 20% of the time as either a hobby or as a post-retirement activity. This finding would also explain why some of the boats reported relatively few active days. The mean net profit was €5924 per fisher per season. This figure will have been influenced by the fifth of respondents who considered their activity in the SSF as part-time. However, it would be beneficial to provide support to the majority of fishers active in the SSF in terms of complementary alternative employment opportunities in the regions where they are located.
Almost all settlements along the Black Sea coast have traditional shipbuilders who build, repair the boats, and provide maintenance services. With an investor group of at least two people in a fishing port and shelter, a new employment opportunity can be created for the fishing sector, so that coastal fishers will be able to access services for boat maintenance, repair and construction works with less cost in their local settlements. There are some examples that have been applied and successfully managed around the Gulf of Gökova, in the Aegean Sea SSF (
Within the value chain, different systems should be investigated to increase the fisher’s revenue. With cooperation, all scenarios can be developed, including e-commerce, which has come to the fore during the recent pandemic. Moreover, any changes to the legal standards for fishing gear may cause an acute increase in overall operational costs for SSF fishers who are not able to adapt due to their vulnerable economic status. Thus, a subsidy program will be needed and recommended when such changes in the legal standard for fishing gear are proposed and implemented. The overall evaluation of the results suggests that the Black Sea SSF in Turkey is not sustainable under current circumstances, like many other countries.
Recently, marine cage culture systems have been increasing in the Black Sea. It is very likely to pose some potential conflicts with the capture fisheries sectors. These include over-exploitation of marine areas as well as supply to local markets. Nevertheless, a well-designed marine spatial planning program can result in a symbiotic existence for the SSF and aquaculture, large-scale fisheries, ports and shipping in the Black Sea, instead of destructive competition.
This study was funded by the General Directorate of Agricultural Research and Policies. The data were collected within the framework of TAGEM /HAYSUD/2015/A11/P-09/02 “Investigation of Gillnets and Effects in Black Sea Fisheries” project. The authors are grateful to the anonymous referee for the valuable input on an earlier version of the article and to Ass. Prof. Kemal Can Bizsel for his linguistic corrections.