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Research on utilization conflicts of fishery resources and catch allocation methods in the Bohai Sea, China
Fisheries Research 225 (2020) 105477
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Research on utilization conflicts of fishery resources and catch allocation methods in the Bohai Sea, China
T
Qi Dinga,b, Xiujuan Shana,b, Xianshi Jina,b,*, Harry Gorfinec a Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, Shandong Provincial Key Laboratory of Fishery Resources and Ecological Environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China b Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China c School of Biosciences, The University of Melbourne, Parkville 3010, Australia
A R T I C LE I N FO
A B S T R A C T
Handled by S Xavier Cadrin
Developing equitable quota allocation schemes can contribute to achieving long-term ecological and economic sustainability of a nation’s fishery resources. Taking the Bohai Sea as a case study, we explored the biological reasons for fishery conflicts using survey data from the Yellow Sea Fisheries Research Institute, and further developed a multi-criteria allocation approach from biological, social and economic aspects and investigated eight allocation scenarios based on the national fishery statistical data. Results showed that fishery conflicts in the Bohai Sea were mainly caused by large annual variations in fish abundance, some high abundance areas occurring near jurisdictional boundaries, and biologically limited fisheries which had become overfished. Allocation approaches with multiple weighted criteria were more stable and acceptable compared with those solely based on one aspect. Percentage shares in Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality were 30.2 %, 21.0 %, 47.6 %, and 1.2 % respectively based on the application of an entropy method. Instead of base allocation schemes which rely solely on biological factors such as historical catch records, these results highlight the importance of incorporating socioeconomic factors into decisions about catch quota allocation.
Keywords: Catch shares Allocation Fishery conflicts Socio-economics Fairness and impartiality The Bohai Sea
1. Introduction Marine capture fisheries are not only an important source of food in China, but also contribute to the national economy and society by creating employment and adding economic value (Kumar, 2014; McClanahan et al., 2015). China is geographically located in Eastern Asia, bordering the Bohai Sea, the Yellow Sea, the East China Sea, and the South China Sea. The Bohai Sea is a semi-enclosed shallow sea, and it is an important spawning, nursery and feeding ground for many fish species targeted in the Yellow Sea and Bohai Sea (Jin, 2004; 2014). However, fisheries resources in the Bohai Sea have greatly decreased since the 1960s mainly due to overfishing and environmental pollution (Gao et al., 2014; Kang et al., 2018). The dominant species have changed from traditional high-value fishes to small-sized species of low value (Shan et al., 2016). Beyond the widespread depletion of marine fisheries resources, conflicts over access and allocation is a growing security concern (Hilborn, 2007; Spijkers et al., 2018; Zhang, 2018). Fisheries resources
⁎
in China are much like the commons: access is restricted, but licensed fishermen can exploit these resources relatively freely (Yu and Yu, 2008; Shen and Heino, 2014). The scarcity of fishery resources leads to increased competition, which in turn leads to fishery conflicts. In the Bohai Sea, geographic proximity and intense competition for the limited fisheries resources among fishing provinces have often caused conflicts, resulting in human casualties and destruction of fishing vessels. Fisheries management in China mainly relies on technical measures (e.g. closed areas and seasons, minimum mesh size regulation) and a range of input control measures (e.g. licensing system) (Shen and Heino, 2014). However, the Chinese government has now been paying greater attention to controlling the volume of marine catches in recent years (Cao et al., 2017; Ministry of Agriculture and Rural Affairs, 2017). Well-designed and implemented catch shares could help to prevent overfishing, promote stability and ecological stewardship (Gutiérrez et al., 2011). Furthermore, it would help to avoid the race for fish phenomenon (Birkenbach et al., 2017), which may contribute to reduce
Corresponding author at: Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China E-mail address: [email protected] (X. Jin).
https://doi.org/10.1016/j.fishres.2019.105477 Received 23 July 2019; Received in revised form 18 December 2019; Accepted 23 December 2019 0165-7836/ © 2019 Elsevier B.V. All rights reserved.
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the fishery conflicts. Allocation is an essential part of a volume control policy, and equitable allocation is a key issue in actual performance of catch share programs. Developing a reasonable allocation scheme is one way to combat the tragedy of the commons (Metzner et al., 2010). However, issues surrounding the allocation of shared fisheries resources are some of the most challenging in fisheries management (Bailey et al., 2013; Crowe et al., 2013). Currently, there are four main methods used to allocate catch shares including: (i) auctions, (ii) equal allocation, (iii) catch history, and (iv) vessel- or gear-based rules (Lynham, 2014). Nevertheless, most methods used to allocate catch shares are based solely on catch information, while socio-economic factors do not appear to influence allocation to any major extent (Metzner et al., 2010). One of the drawbacks associated with solely using catch information to allocate catch shares is that this explicitly ignores human drivers of fishing behavior and does nothing to illustrate tradeoffs in policy options (Bailey et al., 2013). Developing fair and impartial allocation schemes can make a practical contribution to more sustainable and cooperative use of fisheries resources (Cox, 2009; Metzner et al., 2010). However, to date, few studies have explored potential catch share allocation schemes in China. This analysis is the first systematic attempt to explore the quota allocation options for fisheries in the Bohai Sea. It begins with an examination of the distribution and annual variation of fisheries resources in the Bohai Sea. Beyond allocating catch shares solely on the basis of historical catch records, this study further combines historical catch with socio-economic factors in allocation schemes and discusses some of the possible outcomes from catch shares allocation scenarios. The aim of this paper is to provide a reference tool for policymakers and academics involved in future fisheries management of the Bohai Sea.
Fig. 1. Sampling stations in the Bohai Sea.
This paper deals with the allocation schemes of catch shares in the Bohai Sea. Initially, an examination of fish stock distribution was undertaken to identify possible biological factors that may induce fishery conflicts among the fishing provinces in the Bohai Sea. We analyzed the variation of relative abundance in total fish (including finfish and invertebrates), finfish, and invertebrates. In addition, by dividing the Bohai Sea in accordance with the maritime jurisdictional boundaries of Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, we further explored the distribution of its fish stocks in detail. The data employed for the present study were derived from comprehensive surveys carried out by the Yellow Sea Fisheries Research Institute. The above surveys were conducted on a fixed station grid that measured 0.5 °N × 0.5 °E, with around 50 sampling stations, that covered the entire Bohai Sea (Jin et al., 2014). The surveys were conducted using pair bottom trawlers (around 200 horsepower). The cod-end mesh size was 2 cm, the headline height was around 5−6 m, and the distance between wings was 22.6 m. Trawling speed was approximately 2.6 knots and tows were one hour in duration. All species were sorted to species level, counted and weighed on board. Only fish, crustaceans, and cephalopods were included in this study. Although there were some differences in sampling sites between years due to weather condition, the surveys covered the same broad area. For consistency, only stations that surveyed in all the study years were used (Fig. 1). Relative abundance index was calculated as follows:
swept by the trawl (km2/h). More than half of the major catch share fisheries in the world allocate a Total Allowable Catch (TAC) based solely on historical catch records (Lynham, 2014). However, incorporating socio-economic factors may offer alternative allocation possibilities that could increase the rationality in managing shared fish stocks. Therefore, this paper subsequently developed a combined socio-economic-ecological construct to discuss the possible allocation decisions. As this is the first study that specifically addresses catch share allocation in the Bohai Sea, we chose measures of its biology, society, and economy that likely best capture the properties of interest, based on the principles of fairness and impartiality, and previous studies of catch share allocation elsewhere. The biological aspect was represented using historical catch records. We used two metrics to define the social aspect: number of traditional fishers and the size of communities dependent on marine fisheries. Specifically, the former refers to the population in the marine fishing village, and the latter refers to total population who make a living on marine fisheries or related activities, including both the personnel engaged in marine fishery or related activities and their dependants (Fisheries Bureau of the Ministry of Agriculture, 2018). The economic aspect was quantified based on catch values (2016 constant price, national currency). The data on historical catch records, number of traditional fishers and human populations dependent on marine fisheries were acquired from the China Fishery Statistical Yearbook (Fisheries Bureau of the Ministry of Agriculture, 2016, 2017; 2018). Due to limited data availability, catch values were calculated based on the average price of marine capture fisheries for each fishing province and the catches reported for the Bohai Sea. Based on the third national agricultural census, the Ministry of Agriculture and Rural Affairs (MARA) in combination with the National Bureau of Statistics (NBS) adjusted the China fishery statistical data. Due to the limitation of adjusted catch data before the year of 2016 in the Bohai Sea, only catch records and its corresponding catch values in 2016–2017 were used in this study (Table 1). For other indicators, an average value for the most recent three years was used to counter interannual variability (Table 1). A synthesized catch share allocation index had been established using a weighted average method:
D = C/(q × A)
CQi = wbBi + wsSi + weEi
2. Materials and methods 2.1. Indicators and data sources
(1)
(2)
Where CQi is the synthetical value of catch quota for province i. Bi, Si, Ei are the biological (B), social (S) and economical (E) indices respectively. wb, ws, we are the weight of indicators Bi, Si, Ei respectively.
where D is the relative abundance index (kg/km2). C is the total catch per hour at each sampling station. q is the catchability coefficient, which are sourced from Jin et al. (2005), and A is the sampling area 2
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Table 1 The value of four key factors for Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, average over 2015–2017. Provinces and municipalities
Marine capture fisheries in the Bohai Sea /tons
Number of traditional fishers / individual
Size of communities dependent on marine fisheries /individual
Catch values in the Bohai Sea (2016 constant price, national currency) / 10,000 RMB
Tianjin Liaoning Hebei Shandong
6764 216161 181696 311484
5660 313334 112135 375658
10318 512261 146099 930362
20921 262675 292889 493438
category). Then we conduct the normalization operation as follows:
Variables were standardized based on maximum values in our dataset and placed on a range of 0–1 using the following conversion: X/Xmax. Two indicators, the numbers of traditional fishers and the size of communities dependent on marine fisheries, were included in the society category. A social index was calculated using a weighted average, in which the corresponding weight of the two indicators were calculated using an entropy method. And the allocation proportion for each province was calculated as Eq. (3):
Pi =
CQi *100 m ∑i = 1 CQi
m
pij = x ij / ∑ x ij
Where m is the number of provinces under discussion. The decision matrix is obtained as follows:
p p ⋯ p1, j − 1 p1, j ⎡ 1, 1 1, 2 ⎤ ⎢ p2, 1 p2, 2 ⋯ p2, j − 1 p2, j ⎥ Yij = ⎢ ⋮ ⋮ ⋮ ⋮ ⎥ ⎢ ⎥ pi, 1 pi, 2 ⋯ pi, j − 1 pi, j ⎣ ⎦
(3)
And the entropy of indicator j is calculated by the following equation:
Where Pi is the proportion of catch quota allocation for province i and m is the number of provinces under discussion, which equals four in this study. In addition, different weight allocation scenarios indicated different preferences on the aspects of biology, society, and economy. In order to provide a useful reference tool for policymakers, academics, and others interested in catch shares management in the Bohai Sea, we further investigated eight allocation scenarios. Specific weight allocation schemes listed in Table 2, and the weights in Scenario 8 were computed using an entropy method.
m
Hj = −k∑ pij lnpij Where k = 1/ln m Then the final weight for indicator j is measured as Eq. 5:
wj =
3. Results Investigation of the distribution and annual variation of fish stocks revealed large inter-annual fluctuations in fish abundance in the Bohai Sea. Specifically, mean relative abundance ranged from 495 kg/km2 in 2016 to 1192 kg/km2 in 2017, with an average of 769 kg/km2 during 2015–2017 (Fig. 2). Of which, mean relative abundance of finfish fluctuated from a low of 289 kg/km2 in 2015 to a high of 906 kg/km2 in 2017, with an average of 566 kg/km2 during 2015–2017 (Fig. 3). Mean relative abundance of invertebrates varied from 116 kg/km2 in 2015 to 285 kg/km2 in 2017, with an average of 202 kg/km2 during 2015–2017 (Fig. 4). Relative abundance showed that finfish made up the highest proportion of total abundance, 72.6 %, which was almost three times of the relative abundance comprised by invertebrates. Japanese anchovy (Engraulis japonicus) made up 41.9 % of the total abundance of all species, followed by crustaceans, which accounted for 20.5 %, of which 15.3 % was Mantis shrimp (Oratosquilla oratoria). Molluscs comprised 6.9 % of the total abundance, of which 6.1 % was Beka squid (Loligo beka) (Table 3). In terms of the geographic distribution of fish abundance in the maritime jurisdictional zone of Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, the mean relative abundance in Hebei Province was highest with an average of 996 kg/ km2 during 2015–2017. Tianjin Municipality came next with 906 kg/ km2 and then Shandong Province with 818 kg/km2. However, in Liaoning Province the mean relative abundance was only about 591 kg/ km2, which was the lowest among the above four fishing provinces. From an overall perspective, some areas with highly abundant stocks occurred near the jurisdictional boundaries in the Bohai Sea (Fig. 2). In order to provide a systematic analysis of quota allocation options
Where xij represents the value of indicator j for province i (i = 1, 2, 3, 4; j = 1, 2, 3 when estimating the categories of biology, society and economy, or j = 1, 2 when calculating the two metrics in the social Table 2 Index weights under different decision preferences.
Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario
1 2 3 4 5 6 7 8
(Biology only) (Society only) (Economics only) (No decision preference) (Biological preference) (Social preference) (Economical preference) (Objective bio-socioeconomic preference)
we
1 0 0 1/3 0.5 0.25 0.25 0.29
0 1 0 1/3 0.25 0.5 0.25 0.40
0 0 1 1/3 0.25 0.25 0.5 0.31
(5) n
x x ⋯ x1, j − 1 x1, j ⎤ ⎡ 1, 1 1, 2 ⎢ x2, 1 x2, 2 ⋯ x2, j − 1 x2, j ⎥ X ij = ⎢ ⋮ ⋮ ⋮ ⋮ ⎥ ⎢x x x x ⎥ ⎣ i, 1 i, 2 ⋯ i, j − 1 i, j ⎦
ws
1 − Hj n
∑ j = 1 (1 − Hj )
Where 0 ≤ wj≤1; ∑ j = 1 wj = 1; n is the number of the index under discussion, which equals to 2 or 3 in this study.
The entropy approach is an objectively weighted method which is commonly used in multi-objective optimization strategies (Sun et al., 2013; Zhang et al., 2014; Cheng et al., 2015). Entropy is a method to measure the uncertainty or disorder in an information set. Specifically, the uncertainty and entropy will be smaller (larger) if the information content is larger (smaller) (Shannon, 1948). Based on the concept of entropy, we can examine the discrete degree of the involved indicators. According to the entropy method, first, we develop a decision-making matrix X for the above three aspects of the three provinces and one municipality.
wb
(4)
i=1
2.2. Entropy method used to allocate catch quotas
Scenarios
(3)
i=1
3
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Fig. 2. The distribution of total fisheries stock abundance in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
influence differed among the four fishing provinces. Under Scenario 4, we placed equal weights on biology, society, and economy. Results showed that Shandong Province had the largest proportional catch quota which was 47.1 %, and the allocation proportion for Liaoning Province, Hebei Province, and Tianjin Municipality were 29.8 %, 21.9 %, 1.2 % respectively. If we placed emphasis on the biological aspect (Scenario 5), the allocation proportion for Liaoning Province and Hebei Province slightly increased to 29.9 % and 22.8 %, while the quota distribution fractions for Shandong Province and Tianjin Municipality decreased to 46.1 % and 1.1 %. Under the scenario of Social preference (Scenario 6), the allocation proportions for Shandong Province and Liaoning Province increased to 48.3 % and 31.1 % due to the large numbers of traditional fishers and size of the associated fisheries-dependent community. In contrast, these populations were relatively smaller in Hebei Province and Tianjin Municipality, which lead to the proportions of these two areas decreasing to 19.5 % and 1.1 %. However, under the scenario of Economic preference (Scenario 7), the higher average fish prices in Tianjin Municipality and Hebei Province resulted in the percentage shares increasing to 23.3 % and 1.4 % in these two fishing provinces, while they decreased to 46.8 % and 28.5 % in Shandong Province and Liaoning Province. In order to provide a more objective and comprehensive analysis, this study further used the entropy method to allocate catch shares
in the Bohai Sea, this study developed a bio-socioeconomic allocation approach and examined eight allocation scenarios (Table 2). The allocation of catch quota proportions showed obvious differences under different scenarios (Fig. 5). In most cases, allocations have generally been decided based on historical catch records (Scenario 1). If we use Scenario 1 as a reference, results showed that allocation proportions under single factor scenarios (Scenario 2, 3) showed larger variations than that under multi-factor scenarios (Scenario 4–8). Specifically, when we only considered the biological (catch) aspect, the allocation proportions for Shandong Province, Liaoning Province, Hebei Province, and Tianjin Municipality were 43.5 %, 30.2 %, 25.4 % and 0.9 % respectively. However, the allocation proportion for Shandong and Liaoning provinces increased to 52.4 % and 35.4 %, while Hebei Province and Tianjin Municipality decreased to 11.5 % and 0.7 %, if only social factors were taken into consideration (Scenario 2). In contrast, under the scenario of Economics only (Scenario 3), the catch quota proportion for Liaoning Province decreased to 24.5 %, whereas Shandong and Hebei provinces and Tianjin Municipality increased to 46.1 %, 27.4 % and 2.0 % (Fig. 5). In general, allocation proportions exhibited relatively low variation under multi-factor scenarios, making them more viable and acceptable to policy makers (Fig. 5). The preference on different aspects by decision makers had effects on the quota allocation, and the degree of 4
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Fig. 3. The abundance of fin-fish in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
among fishing provinces and compared it with the results using the equal weight distribution. Under Scenario 8, the weight of society was significantly higher than the other two indices. Consequently, in comparison with Scenario 4, the allocation proportion in both Liaoning Province and Shandong Province increased 2 % and 1 %, while the ratio in Hebei Province and Tianjin Municipality slightly decreased 4 % and 3 %. The Ministry of Agriculture and Rural Affairs of the People's Republic of China (MARA) announced plans in 2017 to reduce the total domestic marine catch to 10 million tonnes by 2020. Catches in the Bohai Sea have accounted for about 6 % of total domestic marine catches in recent years. In other words, total catch from the Bohai Sea approximated 600 thousand tonnes in 2020. Based on the allocated proportion under the scenario of objective bio-socioeconomic preference (Scenario 8), catch quotas for Shandong Province, Liaoning Province, Hebei Province, and Tianjin Municipality were 285, 182, 126 and 7 thousand tonnes respectively in 2020.
and specific attention has increasingly been paid to volume control in Chinese fisheries management (Cao et al., 2017). However, limited research has been conducted on the allocation schemes for shared fisheries resources in China which play a pivotal role in the actual performance of catch share programs (Montero et al., 2002; Anderson et al., 2011; Lynham, 2014). The combined socio-economic-ecological framework presented in this study of catch quota allocation in the Bohai Sea, is an effort to enhance the objectivity for fair and impartial allocation of catches among fishing provinces. Through a general comparison of eight allocation scenarios, our analysis suggests that the allocation approaches with multiple weighted criteria would be more stable compared with those solely based on one aspect. Furthermore, the chosen multi-criteria could insure the catch information and socioeconomic factors will be both considered in permits allocation. As mentioned above, when considering the social and economic affairs, fisheries resource management is a very complex decisionmaking process. Therefore, the entropy method has been introduced into this study as a measurement of system inequality of catch allocation based on multi-criteria among fishing provinces. Percentage shares in Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality were 30.2 %, 21.0 %, 47.6 %, and 1.2 % respectively based on the entropy method. A reduction in conflict and increase in fishery resources are
4. Discussion Catch-share fishery reforms can provide incentives for sustainable exploitation (Costello et al., 2008; Heal and Schlenker, 2008; Birkenbach et al., 2017). China is the world's largest fishing country, 5
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Fig. 4. The abundance of invertebrates in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
measure in fisheries management. Quota allocation is an important topic in total catch control among all the stakeholders (Sanchirico et al., 2006; Villasante et al., 2011; Lynham, 2014). Historical criteria are easiest to use as a basis for allocation mainly because this is the simplest measure to objectively quantify when compared with more subjective criteria (McClanahan et al., 2011). By comparing historical catch allocation criteria with other allocation scenarios, we found that the percentage shares increased in Shandong Province under all other allocation scenarios. For the case of Tianjin Municipality, percentage shares
expected to reduce negative effects on ecosystems and fisheries (Pomeroy et al., 2007; Hendrix and Glaser, 2011; McClanahan et al., 2011). From a biological perspective, fishery conflicts in the Bohai Sea may occur for the following reasons: (i) fisheries resources are mainly composed by small pelagic fishes which have large annual variations; (ii) a few high abundance areas occurred near the jurisdictional boundaries; and (iii) limited but overfished fisheries resources. Conflicts are likely to be reduced by reasonable allocation schemes (Cox, 2009). Total allowable catch is a common and efficient policy
Table 3 Major species and their percentage in fish abundance in the Bohai Sea during.2015–2017. Species
2015 /%
2016 /%
2017 /%
Average over 2015–2017 /%
Japanese Anchovy (Engraulis japonicus) Mantis Shrimp (Oratosquilla oratoria) Beka Squid (Loligo beka) Hairfin Anchovy (Setipinna taty) Dotted Gizzard Shad (Konosirus punctatus) Silver Pomfret (Pampus argenteus) Rednose Anchovy (Thrissa kammalensis) Branded Goby (Chaeturichthys stigmatias) Sappa (Sardinella zunasi) Spanish mackerel (Scomberomorrus niphonius)
66.4 9.1 3.9 0.8 0.7 0.2 0.6 1.2 1.5 0.4
22.4 22.3 11.4 10.8 9.4 0.3 2.8 0.8 0.4 0.3
36.9 14.5 2.9 4.0 4.9 4.5 1.7 2.5 1.4 1.4
41.9 15.3 6.1 5.2 5.0 1.7 1.7 1.5 1.1 0.7
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increasingly emphasized in Chinese fisheries development (Cao et al., 2017). Overcapacity is a fundamental problem in China (Szuwalski et al., 2017), but the rising demand for fishery products and limited employment opportunities add the pressure in marine ecosystem and the frequency of fishery conflicts (Zhang et al., 2018). Effective management measures are essential for the sustainability of domestic marine capture fisheries. Possible approaches that may facilitate fisheries sustainability whilst delivering stable or improved socioeconomic outcomes could include: (i) using government financial support to remove excessive fishing capacity by buying a certain amount of catch quotas from fishing provinces to enhance the success of output control measures rather than current investment of large subsidies for license holders; (ii) further developing alternative sources of employment and conducting workforce training to reduce the dependency of fishing communities on marine capture fisheries; (iii) developing environmentally friendly mariculture that has demonstrated promise as an approach to increase seafood production, which in turn could balance ecological benefits with socioeconomic needs.
Fig. 5. The percentage shares for Tianjin Municipality, Hebei Province, Liaoning Province, Shandong Province under different allocation scenarios.
also showed an increasing trend except for Scenario 2. However, the proportions of quota in Liaoning Province and Hebei Province showed the opposite trend. Specifically, for Hebei Province, its quota proportion only increased under Scenario 3; similarly, the quota proportion in Liaoning Province merely increased under Scenario 2 and Scenario 6. Indeed, the number of traditional fishers and the size of communities dependent on marine fisheries progressively decreased in Shandong, Liaoning, and Hebei provinces and in Tianjin Municipality. To be specific, the proportions of traditional fishers were 46.6 %, 38.8 %, 13.9 % and 0.7 %, and the percentage of fisheries-dependent community were 58.2 %, 32.0 %, 9.1 %, 0.7 % for the above four provinces in past three years. From an economic point of view, the national fish price averaged over 2016–2017 for marine capture fisheries was 13.9 Yuan/kg. However, this average fish price reached 29.7 Yuan/kg in Tianjin Municipality, followed by Hebei Province and Shandong Province which were 15.7 Yuan/kg and 15.3 Yuan/kg respectively, but only 12.0 Yuan/kg in Liaoning Province. Furthermore, the proportion of agricultural output value for fisheries in 2017 was only 3.6 % in Hebei Province, whereas the above percentage values were much higher in Liaoning Province, Shandong Province, and Tianjin Municipality in the same year, being 15.4 %, 16.1 % and 18.3 % respectively (Fisheries Bureau of the Ministry of Agriculture, 2018). Through a general comparison of these scenarios and overall consideration of these statistics in combination suggest that in comparison with Scenario 4, the allocation plan of Scenario 8 would be preferable. While the right to choose allocation plan is still in the hand of policymakers. The allocation of catch quotas among fishing provinces is a pillar of China’s nation-wide catch output control management strategy. Developing a fair and impartial allocation scheme can promote sustainable fisheries (Bailey et al., 2013). Considering that most fish species in the Bohai Sea are migratory and fish stocks exhibited extreme annual variation in both abundance and geographic distribution, we did not include it as a biological variable in the catch shares allocation models. Despite some limitations, the results of this study do provide a usable framework to evaluate quota allocation strategies in the Bohai Sea and may provide insightful reference for decision makers to allocate catch quotas in China. Allocations in some catch share fisheries are quantified in absolute terms of tonnes. Instead, explicitly allocating quotas as a proportion of a total allowable catch which might change every few years depending on exploitation status of fish stocks may be more reasonable (Cox, 2009). In addition, allowing quota to be traded is one option to pave the way for new entrants to buy their way into fisheries or for existing fishing provinces to expand their quota holdings, which may improve not only the economic efficiency but also the incentives for stable cooperative arrangements (Metzner et al., 2010; Call and Lew, 2015). In an effort to reconcile economic development with environmental quality and human well-being, the concept of eco-civilization is
5. Conclusion Catch quota allocation among fishing provinces in the Bohai Sea may be the first step toward a nation-wide quota control management strategy and a key approach for equitably controlling total catch output. China’s national government emphasizes fairness and impartiality in the resource allocation process, while the framework based on multiobjective decision-making techniques considers not only fairness and impartiality but also efficiency. By comparing the allocation results under different scenarios, we found that allocation approaches with multiple weighted criteria were more reasonable and suitable for an allocation policy design than alternatives. The entropy method has been adopted into our research as a measure of system inequality of quota allocation among fishing provinces. Percentage shares among Shandong, Liaoning, Hebei provinces, and Tianjin Municipality were 47.6 %, 30.2 %, 21.0 %, and 1.2 % respectively based on the entropy method. Most current allocation decisions are based solely on biological information, without consideration of economic or social factors. Therefore, this study provides important information about policy implications for decision-makers and offers insights into the future of fisheries management in China. Declaration of Competing Interest None. Acknowledgment This work was supported by the National Key R&D Program of China (Grant No. 2017YFE0104400), the National Natural Science Foundation of China (Grant No. 31872692), the Special Funds for Taishan Scholars Project of Shandong Province and the AoShan Talents Cultivation Program Supported by Qingdao National Laboratory for Marine Science and Technology (Grant No. 2017ASTCP-ES07). We also thank two anonymous reviewers for constructive comments that improved this manuscript. References Anderson, T., Arnason, R., Libecap, G.D., 2011. Efficiency advantages of grandfathering in rights-based fisheries management. Annu. Rev. Resour. Econ. 3 (1), 159–179. Bailey, M., Ishimura, G., Paisley, R., Sumaila, U.R., 2013. Moving beyond catch in allocation approaches for internationally shared fish stocks. Mar. Policy 40, 124–136. Birkenbach, A.M., Kaczan, D.J., Smith, M.D., 2017. Catch shares slow the race to fish. Nature 544 (7649), 223. Costello, C., Gaines, S.D., Lynham, J., 2008. Can catch shares prevent fisheries collapse? Science 321 (5896), 1678–1681. Cox, A., 2009. Quota Allocation in International Fisheries. OECD Food, Agriculture and Fisheries Papers, No. 22. OECD Publishing, Paris, pp. 1–61.
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Crowe, F.M., Longson, I.G., Joll, L.M., 2013. Development and implementation of allocation arrangements for recreational and commercial fishing sectors in Western Australia. Fish. Manag. Ecol. 20 (2–3), 201–210. Call, I.L., Lew, D.K., 2015. Tradable permit programs: What are the lessons for the new Alaska halibut catch sharing plan? Mar. Policy 52, 125–137. Cao, L., Chen, Y., Dong, S., Hanson, A., Huang, B., Leadbitter, D., Little, D.C., Pikitch, E.K., Qiu, Y., Mitcheson, Y.S., Sumaila, U.R., Williams, M., Xue, G., Ye, Y., Zhang, W., Zhou, Y., Zhuang, P., Naylor, R.L., 2017. Opportunity for marine fisheries reform in China. Proc. Natl. Acad. Sci. U. S. A. 114 (3), 435–442. Cheng, K., Fu, Q., Chen, X., Li, T., Jiang, Q., Ma, X., Zhao, K., 2015. Adaptive allocation modeling for a complex system of regional water and land resources based on information entropy and its application. Water Resour. Manag. 29 (14), 4977–4993. Fisheries Bureau of the Ministry of Agriculture, 2016. China Fisheries Statistical Yearbook 2015. China Agricultural Press, Beijing. Fisheries Bureau of the Ministry of Agriculture, 2017. China Fisheries Statistical Yearbook 2016. China Agricultural Press, Beijing. Fisheries Bureau of the Ministry of Agriculture, 2018. China Fisheries Statistical Yearbook 2017. China Agricultural Press, Beijing. Gutiérrez, N.L., Hilborn, R., Defeo, O., 2011. Leadership, social capital and incentives promote successful fisheries. Nature 470 (7334), 386. Gao, X., Zhou, F., Chen, C.T.A., 2014. Pollution status of the Bohai Sea: an overview of the environmental quality assessment related trace metals. Environ. Int. 62, 12–30. Hilborn, R., 2007. Defining success in fisheries and conflicts in objectives. Mar. Policy 31, 153–158. Heal, G., Schlenker, W., 2008. Economics: sustainable fisheries. Nature 455 (7216), 1044. Hendrix, C.S., Glaser, S.M., 2011. Civil conflict and world fisheries, 1952–2004. J. Peace Res. 48 (4), 481–495. Jin, X., 2004. Long-term changes in fish community structure in the Bohai Sea, China. Estuar. Coast. Shelf Sci. 59 (1), 163–171. Jin, X., Zhao, X., Meng, T., Cui, Y., 2005. Biological Resources and Habitat in the Yellow Sea and Bohai Sea. Science Press, Beijing. Jin, X., Qiu, S., Liu, X., Wang, J., Zhang, B., Shan, X., 2014. The Foundation and Perspective of Stock Enhancement in the Bohai Sea and Yellow Sea. Science Press, Beijing. Kumar, M.S., 2014. Sustainable management of fisheries and aquaculture for food security and nutrition: policies requirements and actions. Agr. Res. 3 (2), 97–103. Kang, B., Liu, M., Huang, X.X., Li, J., Yan, Y.R., Han, C.C., Chen, S.B., 2018. Fisheries in Chinese seas: What can we learn from controversial official fisheries statistics? Rev. Fish Biol. Fish. 28 (3), 503–519. Lynham, J., 2014. How have catch shares been allocated? Mar. Policy 44, 42–48. Montero, J.P., Sanchez, J.M., Katz, R., 2002. A market-based environmental policy
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Fisheries Research journal homepage: www.elsevier.com/locate/fishres
Research on utilization conflicts of fishery resources and catch allocation methods in the Bohai Sea, China
T
Qi Dinga,b, Xiujuan Shana,b, Xianshi Jina,b,*, Harry Gorfinec a Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, Shandong Provincial Key Laboratory of Fishery Resources and Ecological Environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China b Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China c School of Biosciences, The University of Melbourne, Parkville 3010, Australia
A R T I C LE I N FO
A B S T R A C T
Handled by S Xavier Cadrin
Developing equitable quota allocation schemes can contribute to achieving long-term ecological and economic sustainability of a nation’s fishery resources. Taking the Bohai Sea as a case study, we explored the biological reasons for fishery conflicts using survey data from the Yellow Sea Fisheries Research Institute, and further developed a multi-criteria allocation approach from biological, social and economic aspects and investigated eight allocation scenarios based on the national fishery statistical data. Results showed that fishery conflicts in the Bohai Sea were mainly caused by large annual variations in fish abundance, some high abundance areas occurring near jurisdictional boundaries, and biologically limited fisheries which had become overfished. Allocation approaches with multiple weighted criteria were more stable and acceptable compared with those solely based on one aspect. Percentage shares in Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality were 30.2 %, 21.0 %, 47.6 %, and 1.2 % respectively based on the application of an entropy method. Instead of base allocation schemes which rely solely on biological factors such as historical catch records, these results highlight the importance of incorporating socioeconomic factors into decisions about catch quota allocation.
Keywords: Catch shares Allocation Fishery conflicts Socio-economics Fairness and impartiality The Bohai Sea
1. Introduction Marine capture fisheries are not only an important source of food in China, but also contribute to the national economy and society by creating employment and adding economic value (Kumar, 2014; McClanahan et al., 2015). China is geographically located in Eastern Asia, bordering the Bohai Sea, the Yellow Sea, the East China Sea, and the South China Sea. The Bohai Sea is a semi-enclosed shallow sea, and it is an important spawning, nursery and feeding ground for many fish species targeted in the Yellow Sea and Bohai Sea (Jin, 2004; 2014). However, fisheries resources in the Bohai Sea have greatly decreased since the 1960s mainly due to overfishing and environmental pollution (Gao et al., 2014; Kang et al., 2018). The dominant species have changed from traditional high-value fishes to small-sized species of low value (Shan et al., 2016). Beyond the widespread depletion of marine fisheries resources, conflicts over access and allocation is a growing security concern (Hilborn, 2007; Spijkers et al., 2018; Zhang, 2018). Fisheries resources
⁎
in China are much like the commons: access is restricted, but licensed fishermen can exploit these resources relatively freely (Yu and Yu, 2008; Shen and Heino, 2014). The scarcity of fishery resources leads to increased competition, which in turn leads to fishery conflicts. In the Bohai Sea, geographic proximity and intense competition for the limited fisheries resources among fishing provinces have often caused conflicts, resulting in human casualties and destruction of fishing vessels. Fisheries management in China mainly relies on technical measures (e.g. closed areas and seasons, minimum mesh size regulation) and a range of input control measures (e.g. licensing system) (Shen and Heino, 2014). However, the Chinese government has now been paying greater attention to controlling the volume of marine catches in recent years (Cao et al., 2017; Ministry of Agriculture and Rural Affairs, 2017). Well-designed and implemented catch shares could help to prevent overfishing, promote stability and ecological stewardship (Gutiérrez et al., 2011). Furthermore, it would help to avoid the race for fish phenomenon (Birkenbach et al., 2017), which may contribute to reduce
Corresponding author at: Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China E-mail address: [email protected] (X. Jin).
https://doi.org/10.1016/j.fishres.2019.105477 Received 23 July 2019; Received in revised form 18 December 2019; Accepted 23 December 2019 0165-7836/ © 2019 Elsevier B.V. All rights reserved.
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the fishery conflicts. Allocation is an essential part of a volume control policy, and equitable allocation is a key issue in actual performance of catch share programs. Developing a reasonable allocation scheme is one way to combat the tragedy of the commons (Metzner et al., 2010). However, issues surrounding the allocation of shared fisheries resources are some of the most challenging in fisheries management (Bailey et al., 2013; Crowe et al., 2013). Currently, there are four main methods used to allocate catch shares including: (i) auctions, (ii) equal allocation, (iii) catch history, and (iv) vessel- or gear-based rules (Lynham, 2014). Nevertheless, most methods used to allocate catch shares are based solely on catch information, while socio-economic factors do not appear to influence allocation to any major extent (Metzner et al., 2010). One of the drawbacks associated with solely using catch information to allocate catch shares is that this explicitly ignores human drivers of fishing behavior and does nothing to illustrate tradeoffs in policy options (Bailey et al., 2013). Developing fair and impartial allocation schemes can make a practical contribution to more sustainable and cooperative use of fisheries resources (Cox, 2009; Metzner et al., 2010). However, to date, few studies have explored potential catch share allocation schemes in China. This analysis is the first systematic attempt to explore the quota allocation options for fisheries in the Bohai Sea. It begins with an examination of the distribution and annual variation of fisheries resources in the Bohai Sea. Beyond allocating catch shares solely on the basis of historical catch records, this study further combines historical catch with socio-economic factors in allocation schemes and discusses some of the possible outcomes from catch shares allocation scenarios. The aim of this paper is to provide a reference tool for policymakers and academics involved in future fisheries management of the Bohai Sea.
Fig. 1. Sampling stations in the Bohai Sea.
This paper deals with the allocation schemes of catch shares in the Bohai Sea. Initially, an examination of fish stock distribution was undertaken to identify possible biological factors that may induce fishery conflicts among the fishing provinces in the Bohai Sea. We analyzed the variation of relative abundance in total fish (including finfish and invertebrates), finfish, and invertebrates. In addition, by dividing the Bohai Sea in accordance with the maritime jurisdictional boundaries of Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, we further explored the distribution of its fish stocks in detail. The data employed for the present study were derived from comprehensive surveys carried out by the Yellow Sea Fisheries Research Institute. The above surveys were conducted on a fixed station grid that measured 0.5 °N × 0.5 °E, with around 50 sampling stations, that covered the entire Bohai Sea (Jin et al., 2014). The surveys were conducted using pair bottom trawlers (around 200 horsepower). The cod-end mesh size was 2 cm, the headline height was around 5−6 m, and the distance between wings was 22.6 m. Trawling speed was approximately 2.6 knots and tows were one hour in duration. All species were sorted to species level, counted and weighed on board. Only fish, crustaceans, and cephalopods were included in this study. Although there were some differences in sampling sites between years due to weather condition, the surveys covered the same broad area. For consistency, only stations that surveyed in all the study years were used (Fig. 1). Relative abundance index was calculated as follows:
swept by the trawl (km2/h). More than half of the major catch share fisheries in the world allocate a Total Allowable Catch (TAC) based solely on historical catch records (Lynham, 2014). However, incorporating socio-economic factors may offer alternative allocation possibilities that could increase the rationality in managing shared fish stocks. Therefore, this paper subsequently developed a combined socio-economic-ecological construct to discuss the possible allocation decisions. As this is the first study that specifically addresses catch share allocation in the Bohai Sea, we chose measures of its biology, society, and economy that likely best capture the properties of interest, based on the principles of fairness and impartiality, and previous studies of catch share allocation elsewhere. The biological aspect was represented using historical catch records. We used two metrics to define the social aspect: number of traditional fishers and the size of communities dependent on marine fisheries. Specifically, the former refers to the population in the marine fishing village, and the latter refers to total population who make a living on marine fisheries or related activities, including both the personnel engaged in marine fishery or related activities and their dependants (Fisheries Bureau of the Ministry of Agriculture, 2018). The economic aspect was quantified based on catch values (2016 constant price, national currency). The data on historical catch records, number of traditional fishers and human populations dependent on marine fisheries were acquired from the China Fishery Statistical Yearbook (Fisheries Bureau of the Ministry of Agriculture, 2016, 2017; 2018). Due to limited data availability, catch values were calculated based on the average price of marine capture fisheries for each fishing province and the catches reported for the Bohai Sea. Based on the third national agricultural census, the Ministry of Agriculture and Rural Affairs (MARA) in combination with the National Bureau of Statistics (NBS) adjusted the China fishery statistical data. Due to the limitation of adjusted catch data before the year of 2016 in the Bohai Sea, only catch records and its corresponding catch values in 2016–2017 were used in this study (Table 1). For other indicators, an average value for the most recent three years was used to counter interannual variability (Table 1). A synthesized catch share allocation index had been established using a weighted average method:
D = C/(q × A)
CQi = wbBi + wsSi + weEi
2. Materials and methods 2.1. Indicators and data sources
(1)
(2)
Where CQi is the synthetical value of catch quota for province i. Bi, Si, Ei are the biological (B), social (S) and economical (E) indices respectively. wb, ws, we are the weight of indicators Bi, Si, Ei respectively.
where D is the relative abundance index (kg/km2). C is the total catch per hour at each sampling station. q is the catchability coefficient, which are sourced from Jin et al. (2005), and A is the sampling area 2
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Table 1 The value of four key factors for Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, average over 2015–2017. Provinces and municipalities
Marine capture fisheries in the Bohai Sea /tons
Number of traditional fishers / individual
Size of communities dependent on marine fisheries /individual
Catch values in the Bohai Sea (2016 constant price, national currency) / 10,000 RMB
Tianjin Liaoning Hebei Shandong
6764 216161 181696 311484
5660 313334 112135 375658
10318 512261 146099 930362
20921 262675 292889 493438
category). Then we conduct the normalization operation as follows:
Variables were standardized based on maximum values in our dataset and placed on a range of 0–1 using the following conversion: X/Xmax. Two indicators, the numbers of traditional fishers and the size of communities dependent on marine fisheries, were included in the society category. A social index was calculated using a weighted average, in which the corresponding weight of the two indicators were calculated using an entropy method. And the allocation proportion for each province was calculated as Eq. (3):
Pi =
CQi *100 m ∑i = 1 CQi
m
pij = x ij / ∑ x ij
Where m is the number of provinces under discussion. The decision matrix is obtained as follows:
p p ⋯ p1, j − 1 p1, j ⎡ 1, 1 1, 2 ⎤ ⎢ p2, 1 p2, 2 ⋯ p2, j − 1 p2, j ⎥ Yij = ⎢ ⋮ ⋮ ⋮ ⋮ ⎥ ⎢ ⎥ pi, 1 pi, 2 ⋯ pi, j − 1 pi, j ⎣ ⎦
(3)
And the entropy of indicator j is calculated by the following equation:
Where Pi is the proportion of catch quota allocation for province i and m is the number of provinces under discussion, which equals four in this study. In addition, different weight allocation scenarios indicated different preferences on the aspects of biology, society, and economy. In order to provide a useful reference tool for policymakers, academics, and others interested in catch shares management in the Bohai Sea, we further investigated eight allocation scenarios. Specific weight allocation schemes listed in Table 2, and the weights in Scenario 8 were computed using an entropy method.
m
Hj = −k∑ pij lnpij Where k = 1/ln m Then the final weight for indicator j is measured as Eq. 5:
wj =
3. Results Investigation of the distribution and annual variation of fish stocks revealed large inter-annual fluctuations in fish abundance in the Bohai Sea. Specifically, mean relative abundance ranged from 495 kg/km2 in 2016 to 1192 kg/km2 in 2017, with an average of 769 kg/km2 during 2015–2017 (Fig. 2). Of which, mean relative abundance of finfish fluctuated from a low of 289 kg/km2 in 2015 to a high of 906 kg/km2 in 2017, with an average of 566 kg/km2 during 2015–2017 (Fig. 3). Mean relative abundance of invertebrates varied from 116 kg/km2 in 2015 to 285 kg/km2 in 2017, with an average of 202 kg/km2 during 2015–2017 (Fig. 4). Relative abundance showed that finfish made up the highest proportion of total abundance, 72.6 %, which was almost three times of the relative abundance comprised by invertebrates. Japanese anchovy (Engraulis japonicus) made up 41.9 % of the total abundance of all species, followed by crustaceans, which accounted for 20.5 %, of which 15.3 % was Mantis shrimp (Oratosquilla oratoria). Molluscs comprised 6.9 % of the total abundance, of which 6.1 % was Beka squid (Loligo beka) (Table 3). In terms of the geographic distribution of fish abundance in the maritime jurisdictional zone of Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality, the mean relative abundance in Hebei Province was highest with an average of 996 kg/ km2 during 2015–2017. Tianjin Municipality came next with 906 kg/ km2 and then Shandong Province with 818 kg/km2. However, in Liaoning Province the mean relative abundance was only about 591 kg/ km2, which was the lowest among the above four fishing provinces. From an overall perspective, some areas with highly abundant stocks occurred near the jurisdictional boundaries in the Bohai Sea (Fig. 2). In order to provide a systematic analysis of quota allocation options
Where xij represents the value of indicator j for province i (i = 1, 2, 3, 4; j = 1, 2, 3 when estimating the categories of biology, society and economy, or j = 1, 2 when calculating the two metrics in the social Table 2 Index weights under different decision preferences.
Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario
1 2 3 4 5 6 7 8
(Biology only) (Society only) (Economics only) (No decision preference) (Biological preference) (Social preference) (Economical preference) (Objective bio-socioeconomic preference)
we
1 0 0 1/3 0.5 0.25 0.25 0.29
0 1 0 1/3 0.25 0.5 0.25 0.40
0 0 1 1/3 0.25 0.25 0.5 0.31
(5) n
x x ⋯ x1, j − 1 x1, j ⎤ ⎡ 1, 1 1, 2 ⎢ x2, 1 x2, 2 ⋯ x2, j − 1 x2, j ⎥ X ij = ⎢ ⋮ ⋮ ⋮ ⋮ ⎥ ⎢x x x x ⎥ ⎣ i, 1 i, 2 ⋯ i, j − 1 i, j ⎦
ws
1 − Hj n
∑ j = 1 (1 − Hj )
Where 0 ≤ wj≤1; ∑ j = 1 wj = 1; n is the number of the index under discussion, which equals to 2 or 3 in this study.
The entropy approach is an objectively weighted method which is commonly used in multi-objective optimization strategies (Sun et al., 2013; Zhang et al., 2014; Cheng et al., 2015). Entropy is a method to measure the uncertainty or disorder in an information set. Specifically, the uncertainty and entropy will be smaller (larger) if the information content is larger (smaller) (Shannon, 1948). Based on the concept of entropy, we can examine the discrete degree of the involved indicators. According to the entropy method, first, we develop a decision-making matrix X for the above three aspects of the three provinces and one municipality.
wb
(4)
i=1
2.2. Entropy method used to allocate catch quotas
Scenarios
(3)
i=1
3
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Fig. 2. The distribution of total fisheries stock abundance in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
influence differed among the four fishing provinces. Under Scenario 4, we placed equal weights on biology, society, and economy. Results showed that Shandong Province had the largest proportional catch quota which was 47.1 %, and the allocation proportion for Liaoning Province, Hebei Province, and Tianjin Municipality were 29.8 %, 21.9 %, 1.2 % respectively. If we placed emphasis on the biological aspect (Scenario 5), the allocation proportion for Liaoning Province and Hebei Province slightly increased to 29.9 % and 22.8 %, while the quota distribution fractions for Shandong Province and Tianjin Municipality decreased to 46.1 % and 1.1 %. Under the scenario of Social preference (Scenario 6), the allocation proportions for Shandong Province and Liaoning Province increased to 48.3 % and 31.1 % due to the large numbers of traditional fishers and size of the associated fisheries-dependent community. In contrast, these populations were relatively smaller in Hebei Province and Tianjin Municipality, which lead to the proportions of these two areas decreasing to 19.5 % and 1.1 %. However, under the scenario of Economic preference (Scenario 7), the higher average fish prices in Tianjin Municipality and Hebei Province resulted in the percentage shares increasing to 23.3 % and 1.4 % in these two fishing provinces, while they decreased to 46.8 % and 28.5 % in Shandong Province and Liaoning Province. In order to provide a more objective and comprehensive analysis, this study further used the entropy method to allocate catch shares
in the Bohai Sea, this study developed a bio-socioeconomic allocation approach and examined eight allocation scenarios (Table 2). The allocation of catch quota proportions showed obvious differences under different scenarios (Fig. 5). In most cases, allocations have generally been decided based on historical catch records (Scenario 1). If we use Scenario 1 as a reference, results showed that allocation proportions under single factor scenarios (Scenario 2, 3) showed larger variations than that under multi-factor scenarios (Scenario 4–8). Specifically, when we only considered the biological (catch) aspect, the allocation proportions for Shandong Province, Liaoning Province, Hebei Province, and Tianjin Municipality were 43.5 %, 30.2 %, 25.4 % and 0.9 % respectively. However, the allocation proportion for Shandong and Liaoning provinces increased to 52.4 % and 35.4 %, while Hebei Province and Tianjin Municipality decreased to 11.5 % and 0.7 %, if only social factors were taken into consideration (Scenario 2). In contrast, under the scenario of Economics only (Scenario 3), the catch quota proportion for Liaoning Province decreased to 24.5 %, whereas Shandong and Hebei provinces and Tianjin Municipality increased to 46.1 %, 27.4 % and 2.0 % (Fig. 5). In general, allocation proportions exhibited relatively low variation under multi-factor scenarios, making them more viable and acceptable to policy makers (Fig. 5). The preference on different aspects by decision makers had effects on the quota allocation, and the degree of 4
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Fig. 3. The abundance of fin-fish in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
among fishing provinces and compared it with the results using the equal weight distribution. Under Scenario 8, the weight of society was significantly higher than the other two indices. Consequently, in comparison with Scenario 4, the allocation proportion in both Liaoning Province and Shandong Province increased 2 % and 1 %, while the ratio in Hebei Province and Tianjin Municipality slightly decreased 4 % and 3 %. The Ministry of Agriculture and Rural Affairs of the People's Republic of China (MARA) announced plans in 2017 to reduce the total domestic marine catch to 10 million tonnes by 2020. Catches in the Bohai Sea have accounted for about 6 % of total domestic marine catches in recent years. In other words, total catch from the Bohai Sea approximated 600 thousand tonnes in 2020. Based on the allocated proportion under the scenario of objective bio-socioeconomic preference (Scenario 8), catch quotas for Shandong Province, Liaoning Province, Hebei Province, and Tianjin Municipality were 285, 182, 126 and 7 thousand tonnes respectively in 2020.
and specific attention has increasingly been paid to volume control in Chinese fisheries management (Cao et al., 2017). However, limited research has been conducted on the allocation schemes for shared fisheries resources in China which play a pivotal role in the actual performance of catch share programs (Montero et al., 2002; Anderson et al., 2011; Lynham, 2014). The combined socio-economic-ecological framework presented in this study of catch quota allocation in the Bohai Sea, is an effort to enhance the objectivity for fair and impartial allocation of catches among fishing provinces. Through a general comparison of eight allocation scenarios, our analysis suggests that the allocation approaches with multiple weighted criteria would be more stable compared with those solely based on one aspect. Furthermore, the chosen multi-criteria could insure the catch information and socioeconomic factors will be both considered in permits allocation. As mentioned above, when considering the social and economic affairs, fisheries resource management is a very complex decisionmaking process. Therefore, the entropy method has been introduced into this study as a measurement of system inequality of catch allocation based on multi-criteria among fishing provinces. Percentage shares in Liaoning Province, Hebei Province, Shandong Province, and Tianjin Municipality were 30.2 %, 21.0 %, 47.6 %, and 1.2 % respectively based on the entropy method. A reduction in conflict and increase in fishery resources are
4. Discussion Catch-share fishery reforms can provide incentives for sustainable exploitation (Costello et al., 2008; Heal and Schlenker, 2008; Birkenbach et al., 2017). China is the world's largest fishing country, 5
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Fig. 4. The abundance of invertebrates in the Bohai Sea in August (a) 2015, (b) 2016, (c) 2017, (d) average over 2015–2017, (the A, B, C, D in the figure represent the maritime jurisdictional zone of Liaoning Province, Hebei Province, Tianjin Municipality, and Shandong Province respectively).
measure in fisheries management. Quota allocation is an important topic in total catch control among all the stakeholders (Sanchirico et al., 2006; Villasante et al., 2011; Lynham, 2014). Historical criteria are easiest to use as a basis for allocation mainly because this is the simplest measure to objectively quantify when compared with more subjective criteria (McClanahan et al., 2011). By comparing historical catch allocation criteria with other allocation scenarios, we found that the percentage shares increased in Shandong Province under all other allocation scenarios. For the case of Tianjin Municipality, percentage shares
expected to reduce negative effects on ecosystems and fisheries (Pomeroy et al., 2007; Hendrix and Glaser, 2011; McClanahan et al., 2011). From a biological perspective, fishery conflicts in the Bohai Sea may occur for the following reasons: (i) fisheries resources are mainly composed by small pelagic fishes which have large annual variations; (ii) a few high abundance areas occurred near the jurisdictional boundaries; and (iii) limited but overfished fisheries resources. Conflicts are likely to be reduced by reasonable allocation schemes (Cox, 2009). Total allowable catch is a common and efficient policy
Table 3 Major species and their percentage in fish abundance in the Bohai Sea during.2015–2017. Species
2015 /%
2016 /%
2017 /%
Average over 2015–2017 /%
Japanese Anchovy (Engraulis japonicus) Mantis Shrimp (Oratosquilla oratoria) Beka Squid (Loligo beka) Hairfin Anchovy (Setipinna taty) Dotted Gizzard Shad (Konosirus punctatus) Silver Pomfret (Pampus argenteus) Rednose Anchovy (Thrissa kammalensis) Branded Goby (Chaeturichthys stigmatias) Sappa (Sardinella zunasi) Spanish mackerel (Scomberomorrus niphonius)
66.4 9.1 3.9 0.8 0.7 0.2 0.6 1.2 1.5 0.4
22.4 22.3 11.4 10.8 9.4 0.3 2.8 0.8 0.4 0.3
36.9 14.5 2.9 4.0 4.9 4.5 1.7 2.5 1.4 1.4
41.9 15.3 6.1 5.2 5.0 1.7 1.7 1.5 1.1 0.7
6
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increasingly emphasized in Chinese fisheries development (Cao et al., 2017). Overcapacity is a fundamental problem in China (Szuwalski et al., 2017), but the rising demand for fishery products and limited employment opportunities add the pressure in marine ecosystem and the frequency of fishery conflicts (Zhang et al., 2018). Effective management measures are essential for the sustainability of domestic marine capture fisheries. Possible approaches that may facilitate fisheries sustainability whilst delivering stable or improved socioeconomic outcomes could include: (i) using government financial support to remove excessive fishing capacity by buying a certain amount of catch quotas from fishing provinces to enhance the success of output control measures rather than current investment of large subsidies for license holders; (ii) further developing alternative sources of employment and conducting workforce training to reduce the dependency of fishing communities on marine capture fisheries; (iii) developing environmentally friendly mariculture that has demonstrated promise as an approach to increase seafood production, which in turn could balance ecological benefits with socioeconomic needs.
Fig. 5. The percentage shares for Tianjin Municipality, Hebei Province, Liaoning Province, Shandong Province under different allocation scenarios.
also showed an increasing trend except for Scenario 2. However, the proportions of quota in Liaoning Province and Hebei Province showed the opposite trend. Specifically, for Hebei Province, its quota proportion only increased under Scenario 3; similarly, the quota proportion in Liaoning Province merely increased under Scenario 2 and Scenario 6. Indeed, the number of traditional fishers and the size of communities dependent on marine fisheries progressively decreased in Shandong, Liaoning, and Hebei provinces and in Tianjin Municipality. To be specific, the proportions of traditional fishers were 46.6 %, 38.8 %, 13.9 % and 0.7 %, and the percentage of fisheries-dependent community were 58.2 %, 32.0 %, 9.1 %, 0.7 % for the above four provinces in past three years. From an economic point of view, the national fish price averaged over 2016–2017 for marine capture fisheries was 13.9 Yuan/kg. However, this average fish price reached 29.7 Yuan/kg in Tianjin Municipality, followed by Hebei Province and Shandong Province which were 15.7 Yuan/kg and 15.3 Yuan/kg respectively, but only 12.0 Yuan/kg in Liaoning Province. Furthermore, the proportion of agricultural output value for fisheries in 2017 was only 3.6 % in Hebei Province, whereas the above percentage values were much higher in Liaoning Province, Shandong Province, and Tianjin Municipality in the same year, being 15.4 %, 16.1 % and 18.3 % respectively (Fisheries Bureau of the Ministry of Agriculture, 2018). Through a general comparison of these scenarios and overall consideration of these statistics in combination suggest that in comparison with Scenario 4, the allocation plan of Scenario 8 would be preferable. While the right to choose allocation plan is still in the hand of policymakers. The allocation of catch quotas among fishing provinces is a pillar of China’s nation-wide catch output control management strategy. Developing a fair and impartial allocation scheme can promote sustainable fisheries (Bailey et al., 2013). Considering that most fish species in the Bohai Sea are migratory and fish stocks exhibited extreme annual variation in both abundance and geographic distribution, we did not include it as a biological variable in the catch shares allocation models. Despite some limitations, the results of this study do provide a usable framework to evaluate quota allocation strategies in the Bohai Sea and may provide insightful reference for decision makers to allocate catch quotas in China. Allocations in some catch share fisheries are quantified in absolute terms of tonnes. Instead, explicitly allocating quotas as a proportion of a total allowable catch which might change every few years depending on exploitation status of fish stocks may be more reasonable (Cox, 2009). In addition, allowing quota to be traded is one option to pave the way for new entrants to buy their way into fisheries or for existing fishing provinces to expand their quota holdings, which may improve not only the economic efficiency but also the incentives for stable cooperative arrangements (Metzner et al., 2010; Call and Lew, 2015). In an effort to reconcile economic development with environmental quality and human well-being, the concept of eco-civilization is
5. Conclusion Catch quota allocation among fishing provinces in the Bohai Sea may be the first step toward a nation-wide quota control management strategy and a key approach for equitably controlling total catch output. China’s national government emphasizes fairness and impartiality in the resource allocation process, while the framework based on multiobjective decision-making techniques considers not only fairness and impartiality but also efficiency. By comparing the allocation results under different scenarios, we found that allocation approaches with multiple weighted criteria were more reasonable and suitable for an allocation policy design than alternatives. The entropy method has been adopted into our research as a measure of system inequality of quota allocation among fishing provinces. Percentage shares among Shandong, Liaoning, Hebei provinces, and Tianjin Municipality were 47.6 %, 30.2 %, 21.0 %, and 1.2 % respectively based on the entropy method. Most current allocation decisions are based solely on biological information, without consideration of economic or social factors. Therefore, this study provides important information about policy implications for decision-makers and offers insights into the future of fisheries management in China. Declaration of Competing Interest None. Acknowledgment This work was supported by the National Key R&D Program of China (Grant No. 2017YFE0104400), the National Natural Science Foundation of China (Grant No. 31872692), the Special Funds for Taishan Scholars Project of Shandong Province and the AoShan Talents Cultivation Program Supported by Qingdao National Laboratory for Marine Science and Technology (Grant No. 2017ASTCP-ES07). We also thank two anonymous reviewers for constructive comments that improved this manuscript. References Anderson, T., Arnason, R., Libecap, G.D., 2011. Efficiency advantages of grandfathering in rights-based fisheries management. Annu. Rev. Resour. Econ. 3 (1), 159–179. Bailey, M., Ishimura, G., Paisley, R., Sumaila, U.R., 2013. Moving beyond catch in allocation approaches for internationally shared fish stocks. Mar. Policy 40, 124–136. Birkenbach, A.M., Kaczan, D.J., Smith, M.D., 2017. Catch shares slow the race to fish. Nature 544 (7649), 223. Costello, C., Gaines, S.D., Lynham, J., 2008. Can catch shares prevent fisheries collapse? Science 321 (5896), 1678–1681. Cox, A., 2009. Quota Allocation in International Fisheries. OECD Food, Agriculture and Fisheries Papers, No. 22. OECD Publishing, Paris, pp. 1–61.
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