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Increasing or decreasing? - Current status of the Japanese eel stock
Fisheries Research 220 (2019) 105348
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Increasing or decreasing? - Current status of the Japanese eel stock a,⁎
Kenzo Kaifu , Kazuki Yokouchi a b
b
T
Faculty of Law, Chuo University, 724-1 Higashinakano, Hachioji-shi, Tokyo 192-0393 Japan National Research Institute of Fisheries Science, Japan Fisheries Research and Education Agency, Yokosuka, Kanagawa 238-0316, Japan
ARTICLE INFO
ABSTRACT
Handled by: A.E. Punt
Although Japanese eel, Anguilla japonica, is listed as endangered on the International Union for Conservation of Nature Red List of Threatened Species, a previous stock assessment of the Japanese eel estimated that the age 1+ stock of the species has been recovering since 1990. To help understand the population dynamics of wild Japanese eels, eel fisheries in coastal and estuarine areas in Japan were investigated, because inland fisheries cooperative associations have conducted eel stocking that is presumed to bias the fisheries data in inland waters of Japan. We conducted a questionnaire survey of 1509 fisheries cooperative associations in coastal and estuarine areas of Japan, where the possible bias of eel stocking is expected to be relatively low. Based on the questionnaire, exploitable eel (yellow and silver eels) catch and effort data from 2003 to 2018 were obtained from six fisheries cooperative associations. A standardized catch per unit effort (CPUE) was developed using a generalized linear model for each fisheries cooperative association. The results indicated that the standardized exploitable eel CPUE was significantly lower in four of the six associations. As for the other two associations, significant relationships between CPUE and year was not found. Additionally, of the 227 fisheries cooperative associations that confirmed they catch eels, 1.3%, 5.3%, 21.6%, and 71.8% answered that the eel stock is “relatively increasing,” “stable” “relatively decreasing,” or “decreasing,” respectively, with no association stating that the eel stock is “increasing.” Moreover, reported glass eel CPUE in nine prefectures in Japan was significantly lower in both periods of 1977–2018 and 2003–2018. Because the dataset used in this study is likely to be one of the best currently available, the wild Japanese eel stock appears to be currently declining in Japanese coastal and estuarine waters, where the bias of eel stocked eels on stock dynamics is thought to be relatively low.
Keywords: Anguillid eel Conservation CPUE Fisheries questionnaire Japanese eel Stock dynamics
1. Introduction The Japanese eel, Anguilla japonica, is a catadromous fish species that spawns in waters west of the Mariana Islands, and their leaf-like leptocephalus larvae migrate to the freshwater and estuarine habitats of East Asia including Japan, China, Korea and Taiwan (Tsukamoto, 1990; Tsukamoto et al., 2011; Jacoby and Gollock, 2014). After metamorphosis into yellow eels, they spend most of their life in continental waters until the onset of sexual maturation. Sexually maturing eels start their downstream migration toward the spawning area in the open ocean as silver eels in autumn and early winter (Sudo et al., 2017). This species is commercially important, and recruiting glass eels are intensively captured for use in aquaculture (Shiraishi and Crook, 2015). Fisheries catches of recruiting glass eels and juveniles have decreased since the 1970s and are currently at historically low levels, with the species listed as endangered (EN) on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species (Jacoby and Gollock, 2014). The Japanese eel is one of the most important fish
⁎
species in Japanese inland aquaculture, with the aquaculture of this species yielding about 65 billion JPY (about 600 million USD) in 2016 (Ministry of Agriculture, Forest and Fisheries, 2018). Despite its commercial importance, only one scientific paper (Tanaka, 2014) has assessed the Japanese eel stock. Because stock assessment is crucial for stock management, further studies of Japanese eels are needed to accurately determine the stock status of this species. Tanaka (2014) estimated that the age 1+ stock of this species has been recovering since 1990 (Fig. 1). However, the red list assessments of the IUCN classified A. japonica as a threatened species (Jacoby and Gollock, 2014). Tanaka (2014) estimated the stock status and dynamics of this species mainly based on Japanese fishery data on recruiting glass eels, growth-phase yellow eels, and maturing silver eels. However, Japanese fishery statistics for glass eels are not an appropriate data source for stock assessment because non-negligible illegal and unreported glass eel catches occur in Japan (Kaifu, 2019). For example, domestic catches reported during the 2014 fishing season (1 November 2013 to 31 October 2014) totaled 8.0 t, but this was only 46.0% of the actual catch
Corresponding author. E-mail addresses: [email protected] (K. Kaifu), [email protected] (K. Yokouchi).
https://doi.org/10.1016/j.fishres.2019.105348 Received 12 April 2019; Received in revised form 17 August 2019; Accepted 20 August 2019 0165-7836/ © 2019 Elsevier B.V. All rights reserved.
Fisheries Research 220 (2019) 105348
K. Kaifu and K. Yokouchi
naturally recruited wild individuals (hereafter, ‘wild eels’) should be assessed separately from that of stocked eels. The aim of this study was to help understand the population dynamics of wild Japanese eels; whether the stock of this commercially important species is currently increasing, decreasing or stable. To achieve the aim of this study, yellow and silver eel (exploitable eel) population dynamics should be investigated where the possible bias of eel stocking is expected to be relatively low. Exploitable Japanese eels are fished in both inland and coastal waters in Japan, while eel stocking has been conducted only in inland waters. Because freshwater areas in Japan are dominated by stocked eels (Kaifu et al., 2014, 2018a; Ministry of the Environment, 2016; Itakura et al., 2018), Japanese inland waters are presumed to be ‘contaminated’ to assess the stock of this species (Kaifu, 2019). In addition, Japanese fishery statistics for glass eels can be biased by non-negligible illegal and unreported glass eel catches in Japan (Kaifu, 2019). Despite these difficulties in collecting accurate data for exploitable eel fisheries in Japanese inland waters and glass eel fisheries, coastal and estuarine areas may be relatively suitable sites for investigating the stock dynamics of wild Japanese eels, although downstream movement of eels from freshwater areas to these areas might influence on stock dynamics of wild eels to some extent. A recent case study revealed the depletion of the wild Japanese eel stock in Okayama Prefecture in Japan (Kaifu et al., 2018a). This study reported that stocked eels were dominant in freshwater areas of Okayama Prefecture, and that CPUEs of exploitable eels were significantly decreased in coastal and estuarine areas where wild eels were dominant (Kaifu et al., 2018a). In the current study, the target area was expanded to all the coastal and estuarine areas of Japan, except Hokkaido and Okinawa prefectures, that were thought to be outside of the main species distribution area (Ministry of the Environment, 2016). We first conducted a questionnaire survey of coastal and estuarine fisheries cooperative associations in Japan and then obtained exploitable eel catch and effort data from the associations that confirmed they collected such data, to estimate the current catch per unit effort (CPUE) dynamics. In addition, a part of glass eel fisheries data used in Tanaka (2014) was updated to test the consistency between the estimated CPUE dynamics of exploitable eels and glass eels.
Fig. 1. Trajectories of the size of the Japanese eel stock (1+ group) estsimated by Tanaka (2014). Solid-line and dotted-line curves Point estimate and upper and lower 95% confidence limits, respectively (modified from Tanaka, 2014).
estimated (17.4 t) (Kaifu, 2016; Gollock et al., 2018). Therefore, Japanese glass eel catch statistics are not an appropriate indicator of the actual glass eel recruitment. Yellow and silver eel (exploitable eel) abundance can be a more reliable indicator of Japanese eel stock dynamics if quantitative catch data is available because the high price and specific trading rules for glass eels appear to be driving illegal fishing and underreporting in Japan (Kaifu, 2019). In Japan, a member of a fisheries cooperative association has the right of operating a fishery. The Fisheries Act in Japan (Act No. 267 of 1949) mandates that inland-water fisheries cooperative associations that catch fish in rivers and lakes must increase their fish populations, and the associations harvesting eels typically stock eels to fulfill this obligation (Kaifu et al., 2014, 2018a). In addition, the Fisheries Agency of Japan financially supported eel farming associations that stocked eels until 2015. The primary method of eel stocking in Japan is to release small yellow eels from eel farms into rivers and lakes (Kaifu et al., 2014). Consequently, farmed and stocked individuals are commonly found in Japanese inland waters. For example, it has been suggested that most eels inhabiting Lake Mikata in Fukui Prefecture are stocked and there is little or no glass eel recruitment into the lake (Kaifu et al., 2014). A recent study that used a discrimination model based on otolith stable isotopes (Kaifu et al., 2018b) revealed that 98.1% of the 161 yellow eels captured in freshwater areas of the major rivers in Okayama Prefecture were stocked (Kaifu et al., 2018a). In another study (Itakura et al., 2018), 28.2% of the yellow eels captured in the Tone River (n = 153) were determined to be stocked. The Ministry of the Environment of Japan (2016) applied a discrimination model to 10 water systems in Japan, and 62.0% of the yellow eels were classified as stocked (n = 92) (Ministry of the Environment, 2016). According to these studies, there are considerable numbers of stocked Japanese eels in Japanese inland waters. Although stocking has the potential to enhance eel populations, assessments of the population dynamics of this species can contain biases (Kaifu, 2019). Biological characteristics such as survival rate, growth rate, and sex ratio are essential in population dynamics assessments and can be biased by stocked individuals (Kullmann et al., 2018). It is also possible that stocked eels might be abortive individuals that should not be counted in population dynamics assessments, because there is no evidence that eel stocking contributes to their reproduction. Several researchers have expressed concern that the translocation of eels from one recruited water system to another might result in an inability to migrate to spawning areas (e.g., Westin, 2003; Prigge et al., 2013). The International Council for the Exploration of the Sea (ICES) Working Group on Eel Stocking concluded that “the knowledge base for the assessment of the net benefits of stocking is extremely weak” (ICES, 2016). To develop an effective management plan for wild Japanese eels, information on the population dynamics of
2. Material and methods 2.1. Questionnaire survey The questionnaire survey was conducted in 2016 and included 1509 fisheries cooperative associations in 37 prefectures in Japan, as a part of a Japanese eel research project implemented by the Fisheries Agency of Japan. Fisheries cooperative associations are organizations of fishermen who have the right of operating a fishery and a part of the landing and effort data was recorded by these associations. The questionnaires were distributed to the fisheries cooperative associations directly by postal mail or via prefectural governments, and the fisheries cooperative associations responded by postal mail. The survey included all the Japanese fisheries cooperative associations that operated fisheries in coastal water, brackish estuary and brackish lakes, except for Hokkaido and Okinawa prefectures where fisheries on Japanese eels are not conducted. At least three species of anguillid eels, Japanese eel, giant mottled eel (A. marmorata), and the non-native European eel (A. anguilla), have been reported in the study area (Okamura et al., 2008; Mizuno and Nagasawa, 2009; Ministry of the Environment, 2016; Arai et al., 2017). However, the dominant species is Japanese eel, with the giant mottled eel distributed only in the southern part of Japan (Mizuno and Nagasawa, 2009), while the number of European eels has substantially decreased (Okamura et al., 2008; Ministry of the Environment, 2016; Arai et al., 2017). The questionnaire asked fisheries cooperative associations whether they had caught eels during the last five years. When an association answered “yes” to this initial question, they were prompted to respond 2
Fisheries Research 220 (2019) 105348
K. Kaifu and K. Yokouchi
to the next question, which asked whether they believed the eel stock is now “increasing,” “relatively increasing,” “stable,” “relatively decreasing,” or “decreasing.” The questionnaire also asked the associations whether they collected eel catch data. This was used to identify which associations could be contacted to collect eel fisheries data for the estimation of Japanese eel stock dynamics.
depth was about 10–100 m and sediment was mud. Set net fisheries in Aich were conducted in full sea water mud flat. Water depth was less than 10 m. Set net fisheries in Hyogo were conducted in brackish estuary. Water depth was less than 10 m and sediment was sand and mud. Longline fisheries in Okayama were conducted in brackish bay and estuary. Water depth was less than 10 m and sediment was sand and mud. Set net fisheries in Okayama were conducted in full sea water inland sea. Water depth was less than 10 m and sediment was sand and mud. Set net fisheries in Hiroshima were conducted in full sea water inland sea. Water depth was less than 10 m and sediment was mud.
2.2. Fisheries data for exploitable eels There were 39 fisheries cooperative associations that confirmed they collected exploitable eel catch data and we contacted all of them to obtain the data. Finally, exploitable eel catch and effort data were obtained from six fisheries cooperative associations in five prefectures. Bottom trawl-net fisheries data from 2010 to 2018 were obtained from a fisheries cooperative in Kanagawa Prefecture. Set net fisheries data from 2005 to 2018 and 2001 to 2016 were obtained from fisheries cooperative associations in Aichi and Hyogo prefectures, respectively. Longline and set-net fisheries data from 2003 to 2016 were obtained from two fisheries cooperative associations in Okayama Prefecture. Setnet fisheries data from 2011 to 2017 were obtained from a fisheries cooperative association in Hiroshima Prefecture. Set-net and longline fisheries data from Aichi and Okayama prefectures, respectively, were obtained from a single fisherman. The longline fisheries in Okayama Prefecture mainly target eels, whereas set nets and bottom trawls in the other fisheries cooperative associations target various fish species, including Japanese eel. To ensure the confidentiality of all personal information, the names of the fisheries cooperative associations that replied are not revealed and the exploitable eel catch data were shown as indices. CPUEs in Fig. 2 were indexed as CPUE in 2011 = 100 for each fisheries cooperative association because the shortest fisheries data (Hiroshima) was obtained from 2011. Mean annual catches were indexed as mean annual catch in Kanagawa = 100. Fisheries data obtained from Okayama Prefecture have already been published in a previous study (Kaifu et al., 2018a). We obtained information about the environments of the eel fishing areas of the six fisheries cooperative associations. Bottom trawl-net fisheries in Kanagawa were conducted in full sea water bay. Water
2.3. Fisheries data for glass eels Glass eel fisheries data in Japan are not appropriate for stock assessment because of non-negligible illegal and unreported glass eel catches (Kaifu, 2019). However, it could be important to test the consistency of the increase, decrease or stable trend between exploitable eel and glass eel CPUEs. Therefor glass eel fisheries data were collected to compare the CPUE trends of glass eels and exploitable eels. Tanaka (2014) used glass eel fisheries data (1977–1997) in nine prefectures in Japan; Chiba, Shizuoka, Aichi, Mie, Tokushima, Kochi, Oita, Miyazaki and Kagoshima Prefectures. Glass eel catch in these prefectures accounted 70.5% of the entire glass eel catch in Japan in 2018 fishing season (November 2017 to October 2018). Glass eel fisheries data (glass eel catch and number of fishermen) in Tanaka (2014) were updated to 2018 based on personal communication with the nine prefectures. 2.4. Data analysis A recent study has identified challenges in assessment of Japanese eel stock (Kaifu, 2019). Kaifu (2019) concluded that it is difficult to assess the stock status of Japanese eels using an age- and sex- structured population model because of non-negligible illegal and unreported glass eel catches and biases of stocked individuals. In this study, therefore, increasing/decreasing trends of CPUEs were tested instead of using a population model to examine the stock dynamics of the Japanese eels in the coastal and estuarine areas.
Fig. 2. Locations and prefectures from which eel fisheries data were obtained. a: Locations where exploitable eel fisheries data for CPUE analysis were obtained. No fisheries cooperative associations in Yamagata Prefecture responded that they catch eels during the last 5 years. Questionnaire research was not conducted for Hokkaido Prefecture and Okinawa Prefecture (out of the maps). b: Nine prefectures where glass eel fisheries data were obtained. The gray and stripe areas indicate the main and margin of ranges of natural geographic distribution of this species in Japan estimated by Yoneta et al. (2019). 3
Fisheries Research 220 (2019) 105348
K. Kaifu and K. Yokouchi
3. Results
Table 1 Questionnaire responses made by Japanese coastal fisheries cooperatives regarding the Japanese eel stock status.
number ratio (%)
increasing
relatively increasing
stable
relatively decreasing
decreasing
total
0 0.0
3 1.3
12 5.3
49 21.6
163 71.8
227 100
3.1. Questionnaire research 1,016 (67.3%) responses were obtained from the 1509 questionnaires that were distributed after removing 23 responses that did not indicate either the name of the fisheries cooperative association or the prefecture where the association was located, 993 responses were collected across all the 37 prefectures investigated. A total of 748 coastal fisheries cooperative associations responded that there has been no eel catch, including bycatch, in the last five years. Our analysis then targeted the responses of the remaining 245 fisheries cooperative associations that had caught eels in the past five years. Except for Yamagata prefecture (Fig. 2), eels were caught in the last 5 years in all the prefectures investigated. Of the 245 coastal fisheries cooperative associations that caught eels, 18 fisheries cooperative associations did not answer the question about the stock status of eels. Three (1.3%) and 12 (5.3%) of the remaining 227 fisheries cooperative associations responded that the eel stock was ‘relatively increasing” or “stable,” respectively (Table 1). The number of fisheries cooperative associations that responded that the eel stock was “relatively decreasing” or “decreasing” was 49 (21.6%) and 163 (71.8%), respectively. and no association responded that the eel stock was “increasing.”
CPUE for exploitable eels were estimated based on fisheries data collected from six fisheries cooperative associations. Considering the sedentary behavior of Japanese eels inhabiting continental waters (Itakura et al., 2017), exploitable eels caught by different fisheries cooperative associations were treated as different local stocks, although they shared the same spawning population (Han et al., 2010; Minegishi et al., 2012). Therefore, CPUEs were analyzed separately for each fisheries cooperative association. This also helped to avoid the influence of associations with a large catch on the CPUE analysis. Exploitable eel CPUEs were standardized to account for the different numbers of fishermen. However, CPUEs were not standardized by either number or differences in fisheries for the Aichi and Okayama longline fisheries, because the data obtained were collected from a single fisherman. Exploitable eel catch data were analyzed using a generalized linear model (GLM), with a gaussian distribution. Data obtained from Kanagawa Prefecture were analyzed with a log link function. The response variable was the annual exploitable eel catch and the explanatory variable was the year, while the offset function was the logarithmic number of fishermen. Data obtained from Aichi Prefecture were analyzed with a log link function. The response variable was the annual exploitable eel catch and the explanatory variable was the year. Data obtained from Hyogo Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were the year and fishermen, because the catches of each fisherman were identified. For longline eel fisheries data obtained from Okayama Prefecture, the start and end dates of longline fishing activities varied from year to year and did not occur on exactly the first and last days of the month. To avoid any possible bias from the variation in the number of fishing days in the first and last months, the fishing data from these two months were omitted from the analysis (see Kaifu et al. [2018a] for details). The longline fisheries data were analyzed with a log link function. The response variable was the annual exploitable eel catch, except for that of the first and last month, and the explanatory variable was year, while the offset function was the logarithmic number of fishing months less 2 (i.e., the first and last months). Set net eel catch data obtained from Okayama Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were year and fishermen, because the catches of each fisherman were identified. Eel catch data obtained from Hiroshima Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were year and fishermen, because the catches of each fisherman were identified. Glass eel fisheries data were analyzed using a GLM with a gaussian distribution and log link function. The response variable was the annual glass eel catch of each prefecture and the explanatory variable was the year and prefecture, while the offset function was the logarithmic number of fishermen in each prefecture. Because the period of the glass eel fisheries data (1977–2018) differs substantially from that of exploitable eel fisheries data (2003–2018), both periods of 1977–2018 and 2003–2018 were analyzed to test the consistency between CPUE dynamics of exploitable eels and glass eels. R software version 3.0.2 (R Core Team) was used for all data analysis, with the glm function used for GLM analysis.
3.2. GLM analysis of exploitable eel CPUE Annual eel catch per fisherman in the six coastal fisheries cooperative associations of the five prefectures in Japan is indicated in Fig. 3, and the results of the GLM analysis are shown in Table 2. The coefficients for the relationship between year and annual eel catch were significantly negative for four of the six fisheries cooperative associations: Aichi (GLM; coefficient ± SE = −0.09327 ± 0.03925, t = −2.376, p< 0.05), Hyogo (GLM; coefficient ± SE = −0.0288 ± 0.0097, t = −2.967, p < 0.01), Okayama longline (GLM; coefficient ± SE = −0.1134 ± 0.0168, t = −6.762, p < 0.001), and Okayama set net (GLM; coefficient ± SE = −3.0426 ± 0.9945, t = −3.059, p < 0.01). In the two other associations, the year was not significantly correlated with the annual catch of eels, with the coefficient being negative in one association, Kanagawa (GLM; coefficient ± SE = −0.1422 ± 0.1040, t = −1.693, p = 0.134). One of the six fisheries cooperative associations analyzed, Hiroshima, had a positive coefficient for the relationship between year and annual eel catch, although it was not significant (GLM; coefficient ± SE = 0.1299 ± 0.0869, t = 1.494, p = 0.149). 3.3. GLM analysis of glass eel CPUE Annual glass eel catch per fisherman in the nine prefectures in Japan is indicated in Fig. 4. The coefficients for the relationship between year and annual eel catch were significantly negative for both periods of 1977–2018 (GLM; coefficient ± SE = −0.021206 ± 0.003944, t = −5.377, p < 0.0001) and 2003–2018 (GLM; coefficient ± SE = −0.10094 ± 0.01801, t = −5.604, p < 0.0001). 4. Discussion This study collected eel fisheries data from six fisheries cooperative associations that harvest eels in the Japanese coastal and estuarine areas and showed that the CPUE was significantly decreasing for four of the six associations. The time period covered by the dataset and over which this significant decrease occurred was longer (14–16 years) in the Aichi, Hyogo, and Okayama longline and Okayama set net associations, compared with the other two associations; i.e., Kanagawa (9 years) and Hiroshima (7 years). The reason why this study could not find significant relationships between catch and year for the Kanagawa 4
Fisheries Research 220 (2019) 105348
K. Kaifu and K. Yokouchi
Fig. 3. CPUE obtained from six fisheries cooperatives. CPUEs are estimated as annual catch per number of fishermen and indexed as CPUE = 100 in 2011. Numbers under prefecture names indicate mean annual catch index (Kanagawa = 100).
Japan is not inconsistent with other results obtained in this study at least. Based on these results, the Japanese eel population in Japanese coastal and estuarine areas appears to be currently decreasing. For the Japanese eel, fishery-independent eel-monitoring data for the East Asia region are particularly sparse. Consequently, the IUCN Red List (Jacoby and Gollock, 2014) is informed predominantly by fisheries data from Japan, where such data are relatively more abundant (Jacoby et al., 2015). However, in Japan, non-negligible illegal and unreported glass eel catches occur, which affects the glass eel fisheries statistics (Kaifu, 2016, 2019; Gollock et al., 2018). Moreover, yellow and silver eel fisheries data in Japanese inland water might be biased by stocked individuals (Kaifu et al., 2018a). It is therefore difficult to collect accurate data for yellow and silver eel fisheries in Japanese inland waters and glass eel fisheries in Japan, whereas relatively accurate information regarding the stock dynamics of wild Japanese eels can be obtained from coastal and estuarine areas, where wild eels are dominant (Kaifu et al., 2018a). The dataset used in this study is likely to be one of the best currently available because catch and effort data were collected from the coastal and estuarine area, where the bias of stocked eels on stock dynamics is thought to be relatively low (Kaifu et al., 2018a), and the CPUE dataset was based on a broad questionnaire survey that targeted 1509 coastal and estuary fisheries cooperative associations. This study geographically covered only some parts of Japan, while Japanese eels are distributed throughout East Asia, including Korea, Mainland China and Taiwan. A recent study used otolith 87Sr/86Sr reported that otolith Sr stable isotope ratios of spawning adult Japanese eels that had been captured at spawning area were similar to 87Sr/86Sr of Japanese water rather than that of Korea, Mainland China and Taiwan water (Otake et al., 2019). This suggests that abundance indices (CPUE) of Japanese eels in Japan might be an
Table 2 Results of a generalized linear model (GLM) analysis on the eel fisheries data of six fisheries cooperatives. prefecture
Kanagawa Aichi Hyogo Okayama Okayama Hiroshima
fishing gear
period
bottom trawl set net set net long line set net set net
GLM results coefficient of year (standard error)
t value
p value
2010–2018
−0.1422 (0.1040)
−1.693
0.134
2005–2018 2001–2016 2003–2016 2003–2016 2011–2017
−0.0933 (0.0393) −0.0288 (0.0097) −0.1134 (0.0168) −3.0426 (0.9945) 0.1299 (0.0869)
−2.376 −2.967 −6.762 −3.059 1.494
< 0.05 < 0.01 < 0.001 < 0.01 0.149
and Hiroshima fisheries cooperative associations might be due to the short time period covered by the fisheries data. The result that CPUE for the four of the nine fisheries cooperative associations is significantly decreasing is consistent with the results of the questionnaire survey; 93.4% of fisheries cooperative associations believing that the Japanese eel stock is decreasing or relatively decreasing. Although it is possible that this belief might be biased by media reporting that this species is listed as Endangered on the IUCN Red List of Threatened Species (Jacoby and Gollock, 2014), the local knowledge of fishermen should not be ignored. Moreover, reported glass eel CPUE in nine prefectures in Japan was also significantly decreased for both periods of 1977–2018 and 2003–2018. It is difficult to estimate whether glass eel recruitment is increasing, decreasing or stable based on the reported glass eel CPUE in Japan because of non-negligible illegal and unreported glass eel catch in Japan. However, the significant decrease of glass eel CPUE in 5
Fisheries Research 220 (2019) 105348
K. Kaifu and K. Yokouchi
Fig. 4. Glass eel CPUE in nine prefectures in Japan (Chiba, Shizuoka, Aichi, Mie, Tokushima, Kochi, Oita, Miyazaki and Kagoshima Prefectures). CPUEs are estimated as annual glass eel catch (kg) per number of fishermen based on Tanaka (2014) updated with personal communication with the nine prefectures.
References
appropriate indicator of the whole population dynamics of this species. In this study, however, the period of the dataset was not long enough to cover multiple generation lengths (10 years according to the IUCN assessment; Jacoby and Gollock, 2014). Future studies should analyze eel CPUE at larger temporal scales to better understand the stock dynamics of the Japanese eel. A previous stock assessment of the Japanese eel (Tanaka, 2014) estimated that the age 1+ stock of the species has been recovering since 1990 (Fig. 1). The conclusion of Tanaka (2014) is inconsistent with that of this study. One of the reasons for this inconsistency might be the differences in the time frames of these studies. Tanaka (2014) used a data series from 1903 to 2010, whereas this study used a dataset from 2003 to 2018. Another possible reason could be a bias of stocked individuals. Tanaka (2014) estimated the stock dynamics of Japanese eels based on glass eels and exploitable eels (yellow and silver eels) fisheries data in Japan and their biological characteristics, such as survival rate, growth rate, and sex ratio. Tanaka (2014) collected yellow and silver eel fisheries data in Japan from inland waters where fisheries cooperative associations have been stocking eels (Kaifu, 2019). The yellow and silver eel catch data and biological parameters used by Tanaka (2014) may have been affected by the stocked populations in Japanese inland waters. A recent study (Kullmann et al., 2018), moreover, revealed that stress-related annulus-like rings that form during the farming process cannot be distinguished from true annuli formed under natural conditions, and therefore stocking-related aging errors can strongly affect the estimates of biomass. To obtain an accurate understanding of the Japanese eel population, fisheries independent monitoring should be conducted to enable appropriate stock assessments in the future.
Arai, K., Itakura, H., Yoneta, A., Yoshinaga, T., Shirotori, F., Kaifu, K., Kimura, S., 2017. Discovering the dominance of the non-native European eel in the upper reaches of the Tone River system. Japan. Fish. Sci 83, 735–742 https://idp.springer.com/authorize/ casa?redirect_uri=https://link.springer.com/article/10.1007/s12562-017-1107-z& casa_token=nW3h2JC-urIAAAAA:RMlmrZDSMqFYeZQXKwjAdM9KcO7ffwCtFEsN wYDQz4JG9t0YnTdiZkKZ9eMva53QjAWzFs4SFr4Ej5k. Gollock, M., Shiraishi, H., Carrizo, S., Crook, V., Levy, E., 2018. Status of non-CITES Listed Anguillid Eels. CITES AC30 Document 18.1 Annex 2. https://cites.org/sites/ default/files/eng/com/ac/30/E-AC30-18-01-A2.pdf. Han, Y.S., Hung, C.L., Tzeng, W.N., 2010. Population genetic structure of the Japanese eel Anguilla japonica: panmixia at spatial and temporal scales. Mar. Ecol. Prog. Ser. 401, 221–232. https://www.int-res.com/abstracts/meps/v401/p221-232/. ICES, 2016. Report of the Workshop on Eel Stocking (WKSTOCKEEL) 21. ICES CM 2016/ SSGEPD, Toomebridge, Northern Ireland, UK, pp. 75. http://ices.dk/sites/pub/ Publication%20Reports/Expert%20Group%20Report/SSGEPD/2016/01% 20WKSTOCKEEL%20-%20Report%20of%20the%20Workshop%20on%20Eel %20Stocking.pdf. Itakura, H., Arai, K., Kaifu, K., Shirai, K., Yoneta, A., Miyake, Y., Secor, D.H., Kimura, S., 2018. Distribution of wild and stocked Japanese eels in the Tone River watershed revealed by otolith stable isotopic ratios. J. Fish Biol. 93, 805–813. https:// onlinelibrary.wiley.com/doi/abs/10.1111/jfb.13782?casa_token= PNx5KFly7doAAAAA:6f-aPJGwdL-b77vGLm5dGUm_ Uu5SmfAiCiuTIJziOcoDCJFbUdoLLlTyQ1S9pws8-1HBHe26ADVoGQ. Itakura, H., Miyake, Y., Kitagawa, T., Kimura, S., 2017. Site fidelity, diel and seasonal activities of yellow-phase Japanese eels (Anguilla japonica) in a freshwater habitat as inferred from acoustic telemetry. Ecol. Freshw. Fish 27, 737–751. https:// onlinelibrary.wiley.com/doi/abs/10.1111/eff.12389?casa_token=s0_ lOI2UQJ0AAAAA:3CMbBaNLDQj0EQDkxfCRI2Pjf8qKbQLv6P30ibYNkHURd_ GVPVnvizby1pvu0cA-SpgVfIZmG4EHIw. Jacoby, D., Gollock, M., 2014. Anguilla japonica. The IUCN Red List of Threatened Species. Version 2014.3. https://www.iucnredlist.org/species/166184/1117791. Jacoby, D.M.P., Casselman, J.M., Crook, V., De Lucia, M.B., Ahn, H., Kaifu, K., Kurwie, T., Sasal, P., Silfvergrip, A.M., Smith, K.G., Uchida, K., Walker, A.M., Gollock, M.J., 2015. Synergistic patterns of threat and the challenges facing global anguillid eel conservation. Glob. Ecol. Cons 4, 321–333. https://www.sciencedirect.com/science/ article/pii/S2351989415000827. Kaifu, K., 2016. Conservation Ecology of Eel. Kyoritu Shuppan, Tokyo (in Japanese). Kaifu, K., 2019. Challenges in assessments of Japanese eel stock. Mar. Policy 102, 1–4. https://www.sciencedirect.com/science/article/pii/S0308597X18308169. Kaifu, K., Itakura, H., Amano, Y., Shirai, K., Yokouchi, K., Wakiya, R., MurakamiSugihara, N., Washitani, I., Yada, T., 2018b. Discrimination of wild and cultured Japanese eels based on otolith stable isotope ratios. ICES J. Mar. Sci. 75, 719–726. https://academic.oup.com/icesjms/article-abstract/75/2/719/4159462. Kaifu, K., Maeda, H., Yokouchi, K., Sudo, R., Miller, M.J., Aoyama, J., Yoshida, T., Tsukamoto, K., Washitani, I., 2014. Do Japanese eels recruit into the Japan Sea coast?: a case study in the Hayase River system, Fukui Japan. Environ. Biol. Fish 97, 921–928. https://link.springer.com/article/10.1007/s10641-013-0193-8. Kaifu, K., Yokouchi, K., Higuchi, T., Itakura, H., Shirai, K., 2018a. Depletion of naturally recruited wild Japanese eels in Okayama, Japan, revealed by otolith stable isotope ratios and abundance indices. Fish. Sci. 84, 757–763. https://idp.springer.com/
Acknowledgements We are grateful to all the fisheries cooperative associations that responded to the questionnaire survey. Support from prefectural governments for the questionnaire survey is also highly appreciated. This study was funded through the Japanese eel research project, implemented by the Fisheries Agency of Japan, Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number JP18H02225, and the Chuo University Joint Research Grant. 6
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K. Kaifu and K. Yokouchi authorize/casa?redirect_uri=https://link.springer.com/article/10.1007/s12562018-1225-2&casa_token= 08kKE3USwoEAAAAA:pS7YVHD2kv5d0nADJAWjhuAmdbtylTqoXAeRCzGYo fyW7fpDn_WhqKgYcgnk4pQekj4VN2EnTxe_stM. Kullmann, B., Pohlmann, J.D., Freese, M., Keth, A., Wichmann, L., Neukamm, R., Thiel, R., 2018. Age-based stock assessment of the European eel (Anguilla anguilla) is heavily biased by stocking of unmarked farmed eels. Fish. Res. 208, 258–266. https://www. sciencedirect.com/science/article/pii/S0165783618302303. Minegishi, Y., Aoyama, J., Yoshizawa, N., Tsukamoto, K., 2012. Lack of genetic heterogeneity in the Japanese eel based on a spatiotemporal sampling. Coast. Mar. Sci. 35, 269–276. Ministry of Agriculture, Forest and Fisheries, 2018. Fishery Production (in Japanese). Ministry of Agriculture, Forest and Fisheries, Tokyo. https://www.e-stat.go.jp/statsearch/files?page=1&layout=datalist&toukei=00500208&tstat=000001015664& cycle=7&year=20160&month=0&tclass1=000001036597&tclass2= 000001115243. Ministry of the Environment of Japan, 2016. Report of Commissioned Affairs to Consider Conservation Measures for Japanese Eel in Heisei 27. Ministry of the Environment of Japan, Tokyo (in Japanese). Mizuno, K., Nagasawa, K., 2009. The current status of the geographical distribution of the giant mottled eel Anguilla marmorata (Anguilliformes, Anguillidae) in Japan. Bull. Biogeogr. Soc. Jpn. 64, 79–87 (in Japanese with English abstract). Okamura, A., Zhang, H., Mikawa, N., Kotake, A., Yamada, Y., Utoh, T., Horie, N., Tanaka, S., Oka, H.P., Tsukamoto, K., 2008. Decline in non-native freshwater eels in Japan: ecology and future perspectives. Environ. Biol. Fish 81, 347–358. https://idp. springer.com/authorize/casa?redirect_uri=https://link.springer.com/article/10. 1007/s10641-007-9205-x&casa_token=aA4pcGQELcAAAAA:JI8QAGOKokeMiH3s7GJB0-_ WLVm18ERUE9Tnl9uGv7jh0M8NSewSJyUzKrovJeAFHDXzsSslnaH5QlM. Otake, T., Amano, Y., Shirai, K., Mochioka, N., Takahashi, T., Chow, S., Kurogi, H., Dou, S., Yamaguchi, A., Tsukamoto, K., 2019. Evaluation from otolith Sr stable isotope ratios of possible juvenile growth areas of Japanese eels collected from the West Mariana ridge spawning area. Fish. Sci. 85, 483–493. https://link.springer.com/
article/10.1007/s12562-019-01304-4. Prigge, E., Marohn, L., Hanel, R., 2013. Tracking the migratory success of stocked European eels Anguilla in the Baltic Sea. J. Fish Biol. 82, 686–691. https:// onlinelibrary.wiley.com/doi/full/10.1111/jfb.12032. Shiraishi, H., Crook, V., 2015. Eel Market Dynamics: An Analysis of Anguilla Production, Trade and Consumption in East Asia. TRAFFIC, Tokyo. https://www.traffic.org/ publications/reports/eel-market-dynamics-an-analysis-of-anguilla-production-tradeand-consumption-in-east-asia/. Sudo, R., Okamura, A., Fukuda, N., Miller, M.J., Tsukamoto, K., 2017. Environmental factors affecting the onset of spawning migrations of Japanese eels (Anguilla japonica) in Mikawa Bay Japan. Environ. Biol. Fish 100, 237–249. https://idp.springer.com/ authorize/casa?redirect_uri=https://link.springer.com/article/10.1007/s10641017-0575-4&casa_token=qgAj_ AckNc4AAAAA:CORSSeIJco9sqNwGXl4dXOL3ZD4mkyjjThsEkCam_ NoTwhjMcPX3ujEnZfMZiRCAA5M1JgaHSB4ZWc4. Tanaka, E., 2014. Stock assessment of Japanese eels using Japanese abundance indices. Fish. Sci. 80, 1129–1144. https://link.springer.com/article/10.1007/s12562-0140807-x. Tsukamoto, K., 1990. Recruitment mechanism of the eel, Anguilla japonica, to the Japanese coast. J. Fish Biol. 36, 659–671. https://doi.org/10.1111/j.1095-8649. 1990.tb04320.x. Tsukamoto, K., Chow, S., Otake, T., Kurogi, H., Mochioka, N., Miller, M.J., Aoyama, J., Kimura, S., Watanabe, S., Yoshinaga, T., Shinoda, A., Kuroki, M., Oya, M., Watanabe, T., Hata, K., Ijiri, S., Kazeto, Y., Nomura, K., Tanaka, H., 2011. Oceanic spawning ecology of freshwater eels in the western North Pacific. Nat. Com. 2, 1–9. https:// www.nature.com/articles/ncomms1174. Westin, L., 2003. Migration failure in stocked eels Anguilla anguilla. Mar. Ecol. Prog. Ser. 254, 307–311. https://www.int-res.com/abstracts/meps/v254/p307-311/. Yoneta, A., Itakura, H., Arai, K., Kaifu, K., Yoshinaga, T., Miyake, Y., Shirai, K., Kimura, S., 2019. Distribution of naturally recruited wild Japanese eels in Japan revealed by otolith stable isotopic ratios and document investigation. Nippon. Suisan Gakkaishi 85, 150–161 (in Japanese with English abstract.
7
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Increasing or decreasing? - Current status of the Japanese eel stock a,⁎
Kenzo Kaifu , Kazuki Yokouchi a b
b
T
Faculty of Law, Chuo University, 724-1 Higashinakano, Hachioji-shi, Tokyo 192-0393 Japan National Research Institute of Fisheries Science, Japan Fisheries Research and Education Agency, Yokosuka, Kanagawa 238-0316, Japan
ARTICLE INFO
ABSTRACT
Handled by: A.E. Punt
Although Japanese eel, Anguilla japonica, is listed as endangered on the International Union for Conservation of Nature Red List of Threatened Species, a previous stock assessment of the Japanese eel estimated that the age 1+ stock of the species has been recovering since 1990. To help understand the population dynamics of wild Japanese eels, eel fisheries in coastal and estuarine areas in Japan were investigated, because inland fisheries cooperative associations have conducted eel stocking that is presumed to bias the fisheries data in inland waters of Japan. We conducted a questionnaire survey of 1509 fisheries cooperative associations in coastal and estuarine areas of Japan, where the possible bias of eel stocking is expected to be relatively low. Based on the questionnaire, exploitable eel (yellow and silver eels) catch and effort data from 2003 to 2018 were obtained from six fisheries cooperative associations. A standardized catch per unit effort (CPUE) was developed using a generalized linear model for each fisheries cooperative association. The results indicated that the standardized exploitable eel CPUE was significantly lower in four of the six associations. As for the other two associations, significant relationships between CPUE and year was not found. Additionally, of the 227 fisheries cooperative associations that confirmed they catch eels, 1.3%, 5.3%, 21.6%, and 71.8% answered that the eel stock is “relatively increasing,” “stable” “relatively decreasing,” or “decreasing,” respectively, with no association stating that the eel stock is “increasing.” Moreover, reported glass eel CPUE in nine prefectures in Japan was significantly lower in both periods of 1977–2018 and 2003–2018. Because the dataset used in this study is likely to be one of the best currently available, the wild Japanese eel stock appears to be currently declining in Japanese coastal and estuarine waters, where the bias of eel stocked eels on stock dynamics is thought to be relatively low.
Keywords: Anguillid eel Conservation CPUE Fisheries questionnaire Japanese eel Stock dynamics
1. Introduction The Japanese eel, Anguilla japonica, is a catadromous fish species that spawns in waters west of the Mariana Islands, and their leaf-like leptocephalus larvae migrate to the freshwater and estuarine habitats of East Asia including Japan, China, Korea and Taiwan (Tsukamoto, 1990; Tsukamoto et al., 2011; Jacoby and Gollock, 2014). After metamorphosis into yellow eels, they spend most of their life in continental waters until the onset of sexual maturation. Sexually maturing eels start their downstream migration toward the spawning area in the open ocean as silver eels in autumn and early winter (Sudo et al., 2017). This species is commercially important, and recruiting glass eels are intensively captured for use in aquaculture (Shiraishi and Crook, 2015). Fisheries catches of recruiting glass eels and juveniles have decreased since the 1970s and are currently at historically low levels, with the species listed as endangered (EN) on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species (Jacoby and Gollock, 2014). The Japanese eel is one of the most important fish
⁎
species in Japanese inland aquaculture, with the aquaculture of this species yielding about 65 billion JPY (about 600 million USD) in 2016 (Ministry of Agriculture, Forest and Fisheries, 2018). Despite its commercial importance, only one scientific paper (Tanaka, 2014) has assessed the Japanese eel stock. Because stock assessment is crucial for stock management, further studies of Japanese eels are needed to accurately determine the stock status of this species. Tanaka (2014) estimated that the age 1+ stock of this species has been recovering since 1990 (Fig. 1). However, the red list assessments of the IUCN classified A. japonica as a threatened species (Jacoby and Gollock, 2014). Tanaka (2014) estimated the stock status and dynamics of this species mainly based on Japanese fishery data on recruiting glass eels, growth-phase yellow eels, and maturing silver eels. However, Japanese fishery statistics for glass eels are not an appropriate data source for stock assessment because non-negligible illegal and unreported glass eel catches occur in Japan (Kaifu, 2019). For example, domestic catches reported during the 2014 fishing season (1 November 2013 to 31 October 2014) totaled 8.0 t, but this was only 46.0% of the actual catch
Corresponding author. E-mail addresses: [email protected] (K. Kaifu), [email protected] (K. Yokouchi).
https://doi.org/10.1016/j.fishres.2019.105348 Received 12 April 2019; Received in revised form 17 August 2019; Accepted 20 August 2019 0165-7836/ © 2019 Elsevier B.V. All rights reserved.
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naturally recruited wild individuals (hereafter, ‘wild eels’) should be assessed separately from that of stocked eels. The aim of this study was to help understand the population dynamics of wild Japanese eels; whether the stock of this commercially important species is currently increasing, decreasing or stable. To achieve the aim of this study, yellow and silver eel (exploitable eel) population dynamics should be investigated where the possible bias of eel stocking is expected to be relatively low. Exploitable Japanese eels are fished in both inland and coastal waters in Japan, while eel stocking has been conducted only in inland waters. Because freshwater areas in Japan are dominated by stocked eels (Kaifu et al., 2014, 2018a; Ministry of the Environment, 2016; Itakura et al., 2018), Japanese inland waters are presumed to be ‘contaminated’ to assess the stock of this species (Kaifu, 2019). In addition, Japanese fishery statistics for glass eels can be biased by non-negligible illegal and unreported glass eel catches in Japan (Kaifu, 2019). Despite these difficulties in collecting accurate data for exploitable eel fisheries in Japanese inland waters and glass eel fisheries, coastal and estuarine areas may be relatively suitable sites for investigating the stock dynamics of wild Japanese eels, although downstream movement of eels from freshwater areas to these areas might influence on stock dynamics of wild eels to some extent. A recent case study revealed the depletion of the wild Japanese eel stock in Okayama Prefecture in Japan (Kaifu et al., 2018a). This study reported that stocked eels were dominant in freshwater areas of Okayama Prefecture, and that CPUEs of exploitable eels were significantly decreased in coastal and estuarine areas where wild eels were dominant (Kaifu et al., 2018a). In the current study, the target area was expanded to all the coastal and estuarine areas of Japan, except Hokkaido and Okinawa prefectures, that were thought to be outside of the main species distribution area (Ministry of the Environment, 2016). We first conducted a questionnaire survey of coastal and estuarine fisheries cooperative associations in Japan and then obtained exploitable eel catch and effort data from the associations that confirmed they collected such data, to estimate the current catch per unit effort (CPUE) dynamics. In addition, a part of glass eel fisheries data used in Tanaka (2014) was updated to test the consistency between the estimated CPUE dynamics of exploitable eels and glass eels.
Fig. 1. Trajectories of the size of the Japanese eel stock (1+ group) estsimated by Tanaka (2014). Solid-line and dotted-line curves Point estimate and upper and lower 95% confidence limits, respectively (modified from Tanaka, 2014).
estimated (17.4 t) (Kaifu, 2016; Gollock et al., 2018). Therefore, Japanese glass eel catch statistics are not an appropriate indicator of the actual glass eel recruitment. Yellow and silver eel (exploitable eel) abundance can be a more reliable indicator of Japanese eel stock dynamics if quantitative catch data is available because the high price and specific trading rules for glass eels appear to be driving illegal fishing and underreporting in Japan (Kaifu, 2019). In Japan, a member of a fisheries cooperative association has the right of operating a fishery. The Fisheries Act in Japan (Act No. 267 of 1949) mandates that inland-water fisheries cooperative associations that catch fish in rivers and lakes must increase their fish populations, and the associations harvesting eels typically stock eels to fulfill this obligation (Kaifu et al., 2014, 2018a). In addition, the Fisheries Agency of Japan financially supported eel farming associations that stocked eels until 2015. The primary method of eel stocking in Japan is to release small yellow eels from eel farms into rivers and lakes (Kaifu et al., 2014). Consequently, farmed and stocked individuals are commonly found in Japanese inland waters. For example, it has been suggested that most eels inhabiting Lake Mikata in Fukui Prefecture are stocked and there is little or no glass eel recruitment into the lake (Kaifu et al., 2014). A recent study that used a discrimination model based on otolith stable isotopes (Kaifu et al., 2018b) revealed that 98.1% of the 161 yellow eels captured in freshwater areas of the major rivers in Okayama Prefecture were stocked (Kaifu et al., 2018a). In another study (Itakura et al., 2018), 28.2% of the yellow eels captured in the Tone River (n = 153) were determined to be stocked. The Ministry of the Environment of Japan (2016) applied a discrimination model to 10 water systems in Japan, and 62.0% of the yellow eels were classified as stocked (n = 92) (Ministry of the Environment, 2016). According to these studies, there are considerable numbers of stocked Japanese eels in Japanese inland waters. Although stocking has the potential to enhance eel populations, assessments of the population dynamics of this species can contain biases (Kaifu, 2019). Biological characteristics such as survival rate, growth rate, and sex ratio are essential in population dynamics assessments and can be biased by stocked individuals (Kullmann et al., 2018). It is also possible that stocked eels might be abortive individuals that should not be counted in population dynamics assessments, because there is no evidence that eel stocking contributes to their reproduction. Several researchers have expressed concern that the translocation of eels from one recruited water system to another might result in an inability to migrate to spawning areas (e.g., Westin, 2003; Prigge et al., 2013). The International Council for the Exploration of the Sea (ICES) Working Group on Eel Stocking concluded that “the knowledge base for the assessment of the net benefits of stocking is extremely weak” (ICES, 2016). To develop an effective management plan for wild Japanese eels, information on the population dynamics of
2. Material and methods 2.1. Questionnaire survey The questionnaire survey was conducted in 2016 and included 1509 fisheries cooperative associations in 37 prefectures in Japan, as a part of a Japanese eel research project implemented by the Fisheries Agency of Japan. Fisheries cooperative associations are organizations of fishermen who have the right of operating a fishery and a part of the landing and effort data was recorded by these associations. The questionnaires were distributed to the fisheries cooperative associations directly by postal mail or via prefectural governments, and the fisheries cooperative associations responded by postal mail. The survey included all the Japanese fisheries cooperative associations that operated fisheries in coastal water, brackish estuary and brackish lakes, except for Hokkaido and Okinawa prefectures where fisheries on Japanese eels are not conducted. At least three species of anguillid eels, Japanese eel, giant mottled eel (A. marmorata), and the non-native European eel (A. anguilla), have been reported in the study area (Okamura et al., 2008; Mizuno and Nagasawa, 2009; Ministry of the Environment, 2016; Arai et al., 2017). However, the dominant species is Japanese eel, with the giant mottled eel distributed only in the southern part of Japan (Mizuno and Nagasawa, 2009), while the number of European eels has substantially decreased (Okamura et al., 2008; Ministry of the Environment, 2016; Arai et al., 2017). The questionnaire asked fisheries cooperative associations whether they had caught eels during the last five years. When an association answered “yes” to this initial question, they were prompted to respond 2
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to the next question, which asked whether they believed the eel stock is now “increasing,” “relatively increasing,” “stable,” “relatively decreasing,” or “decreasing.” The questionnaire also asked the associations whether they collected eel catch data. This was used to identify which associations could be contacted to collect eel fisheries data for the estimation of Japanese eel stock dynamics.
depth was about 10–100 m and sediment was mud. Set net fisheries in Aich were conducted in full sea water mud flat. Water depth was less than 10 m. Set net fisheries in Hyogo were conducted in brackish estuary. Water depth was less than 10 m and sediment was sand and mud. Longline fisheries in Okayama were conducted in brackish bay and estuary. Water depth was less than 10 m and sediment was sand and mud. Set net fisheries in Okayama were conducted in full sea water inland sea. Water depth was less than 10 m and sediment was sand and mud. Set net fisheries in Hiroshima were conducted in full sea water inland sea. Water depth was less than 10 m and sediment was mud.
2.2. Fisheries data for exploitable eels There were 39 fisheries cooperative associations that confirmed they collected exploitable eel catch data and we contacted all of them to obtain the data. Finally, exploitable eel catch and effort data were obtained from six fisheries cooperative associations in five prefectures. Bottom trawl-net fisheries data from 2010 to 2018 were obtained from a fisheries cooperative in Kanagawa Prefecture. Set net fisheries data from 2005 to 2018 and 2001 to 2016 were obtained from fisheries cooperative associations in Aichi and Hyogo prefectures, respectively. Longline and set-net fisheries data from 2003 to 2016 were obtained from two fisheries cooperative associations in Okayama Prefecture. Setnet fisheries data from 2011 to 2017 were obtained from a fisheries cooperative association in Hiroshima Prefecture. Set-net and longline fisheries data from Aichi and Okayama prefectures, respectively, were obtained from a single fisherman. The longline fisheries in Okayama Prefecture mainly target eels, whereas set nets and bottom trawls in the other fisheries cooperative associations target various fish species, including Japanese eel. To ensure the confidentiality of all personal information, the names of the fisheries cooperative associations that replied are not revealed and the exploitable eel catch data were shown as indices. CPUEs in Fig. 2 were indexed as CPUE in 2011 = 100 for each fisheries cooperative association because the shortest fisheries data (Hiroshima) was obtained from 2011. Mean annual catches were indexed as mean annual catch in Kanagawa = 100. Fisheries data obtained from Okayama Prefecture have already been published in a previous study (Kaifu et al., 2018a). We obtained information about the environments of the eel fishing areas of the six fisheries cooperative associations. Bottom trawl-net fisheries in Kanagawa were conducted in full sea water bay. Water
2.3. Fisheries data for glass eels Glass eel fisheries data in Japan are not appropriate for stock assessment because of non-negligible illegal and unreported glass eel catches (Kaifu, 2019). However, it could be important to test the consistency of the increase, decrease or stable trend between exploitable eel and glass eel CPUEs. Therefor glass eel fisheries data were collected to compare the CPUE trends of glass eels and exploitable eels. Tanaka (2014) used glass eel fisheries data (1977–1997) in nine prefectures in Japan; Chiba, Shizuoka, Aichi, Mie, Tokushima, Kochi, Oita, Miyazaki and Kagoshima Prefectures. Glass eel catch in these prefectures accounted 70.5% of the entire glass eel catch in Japan in 2018 fishing season (November 2017 to October 2018). Glass eel fisheries data (glass eel catch and number of fishermen) in Tanaka (2014) were updated to 2018 based on personal communication with the nine prefectures. 2.4. Data analysis A recent study has identified challenges in assessment of Japanese eel stock (Kaifu, 2019). Kaifu (2019) concluded that it is difficult to assess the stock status of Japanese eels using an age- and sex- structured population model because of non-negligible illegal and unreported glass eel catches and biases of stocked individuals. In this study, therefore, increasing/decreasing trends of CPUEs were tested instead of using a population model to examine the stock dynamics of the Japanese eels in the coastal and estuarine areas.
Fig. 2. Locations and prefectures from which eel fisheries data were obtained. a: Locations where exploitable eel fisheries data for CPUE analysis were obtained. No fisheries cooperative associations in Yamagata Prefecture responded that they catch eels during the last 5 years. Questionnaire research was not conducted for Hokkaido Prefecture and Okinawa Prefecture (out of the maps). b: Nine prefectures where glass eel fisheries data were obtained. The gray and stripe areas indicate the main and margin of ranges of natural geographic distribution of this species in Japan estimated by Yoneta et al. (2019). 3
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3. Results
Table 1 Questionnaire responses made by Japanese coastal fisheries cooperatives regarding the Japanese eel stock status.
number ratio (%)
increasing
relatively increasing
stable
relatively decreasing
decreasing
total
0 0.0
3 1.3
12 5.3
49 21.6
163 71.8
227 100
3.1. Questionnaire research 1,016 (67.3%) responses were obtained from the 1509 questionnaires that were distributed after removing 23 responses that did not indicate either the name of the fisheries cooperative association or the prefecture where the association was located, 993 responses were collected across all the 37 prefectures investigated. A total of 748 coastal fisheries cooperative associations responded that there has been no eel catch, including bycatch, in the last five years. Our analysis then targeted the responses of the remaining 245 fisheries cooperative associations that had caught eels in the past five years. Except for Yamagata prefecture (Fig. 2), eels were caught in the last 5 years in all the prefectures investigated. Of the 245 coastal fisheries cooperative associations that caught eels, 18 fisheries cooperative associations did not answer the question about the stock status of eels. Three (1.3%) and 12 (5.3%) of the remaining 227 fisheries cooperative associations responded that the eel stock was ‘relatively increasing” or “stable,” respectively (Table 1). The number of fisheries cooperative associations that responded that the eel stock was “relatively decreasing” or “decreasing” was 49 (21.6%) and 163 (71.8%), respectively. and no association responded that the eel stock was “increasing.”
CPUE for exploitable eels were estimated based on fisheries data collected from six fisheries cooperative associations. Considering the sedentary behavior of Japanese eels inhabiting continental waters (Itakura et al., 2017), exploitable eels caught by different fisheries cooperative associations were treated as different local stocks, although they shared the same spawning population (Han et al., 2010; Minegishi et al., 2012). Therefore, CPUEs were analyzed separately for each fisheries cooperative association. This also helped to avoid the influence of associations with a large catch on the CPUE analysis. Exploitable eel CPUEs were standardized to account for the different numbers of fishermen. However, CPUEs were not standardized by either number or differences in fisheries for the Aichi and Okayama longline fisheries, because the data obtained were collected from a single fisherman. Exploitable eel catch data were analyzed using a generalized linear model (GLM), with a gaussian distribution. Data obtained from Kanagawa Prefecture were analyzed with a log link function. The response variable was the annual exploitable eel catch and the explanatory variable was the year, while the offset function was the logarithmic number of fishermen. Data obtained from Aichi Prefecture were analyzed with a log link function. The response variable was the annual exploitable eel catch and the explanatory variable was the year. Data obtained from Hyogo Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were the year and fishermen, because the catches of each fisherman were identified. For longline eel fisheries data obtained from Okayama Prefecture, the start and end dates of longline fishing activities varied from year to year and did not occur on exactly the first and last days of the month. To avoid any possible bias from the variation in the number of fishing days in the first and last months, the fishing data from these two months were omitted from the analysis (see Kaifu et al. [2018a] for details). The longline fisheries data were analyzed with a log link function. The response variable was the annual exploitable eel catch, except for that of the first and last month, and the explanatory variable was year, while the offset function was the logarithmic number of fishing months less 2 (i.e., the first and last months). Set net eel catch data obtained from Okayama Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were year and fishermen, because the catches of each fisherman were identified. Eel catch data obtained from Hiroshima Prefecture were analyzed with an identity link function. The response variable was the annual exploitable eel catch of each fisherman and the explanatory variables were year and fishermen, because the catches of each fisherman were identified. Glass eel fisheries data were analyzed using a GLM with a gaussian distribution and log link function. The response variable was the annual glass eel catch of each prefecture and the explanatory variable was the year and prefecture, while the offset function was the logarithmic number of fishermen in each prefecture. Because the period of the glass eel fisheries data (1977–2018) differs substantially from that of exploitable eel fisheries data (2003–2018), both periods of 1977–2018 and 2003–2018 were analyzed to test the consistency between CPUE dynamics of exploitable eels and glass eels. R software version 3.0.2 (R Core Team) was used for all data analysis, with the glm function used for GLM analysis.
3.2. GLM analysis of exploitable eel CPUE Annual eel catch per fisherman in the six coastal fisheries cooperative associations of the five prefectures in Japan is indicated in Fig. 3, and the results of the GLM analysis are shown in Table 2. The coefficients for the relationship between year and annual eel catch were significantly negative for four of the six fisheries cooperative associations: Aichi (GLM; coefficient ± SE = −0.09327 ± 0.03925, t = −2.376, p< 0.05), Hyogo (GLM; coefficient ± SE = −0.0288 ± 0.0097, t = −2.967, p < 0.01), Okayama longline (GLM; coefficient ± SE = −0.1134 ± 0.0168, t = −6.762, p < 0.001), and Okayama set net (GLM; coefficient ± SE = −3.0426 ± 0.9945, t = −3.059, p < 0.01). In the two other associations, the year was not significantly correlated with the annual catch of eels, with the coefficient being negative in one association, Kanagawa (GLM; coefficient ± SE = −0.1422 ± 0.1040, t = −1.693, p = 0.134). One of the six fisheries cooperative associations analyzed, Hiroshima, had a positive coefficient for the relationship between year and annual eel catch, although it was not significant (GLM; coefficient ± SE = 0.1299 ± 0.0869, t = 1.494, p = 0.149). 3.3. GLM analysis of glass eel CPUE Annual glass eel catch per fisherman in the nine prefectures in Japan is indicated in Fig. 4. The coefficients for the relationship between year and annual eel catch were significantly negative for both periods of 1977–2018 (GLM; coefficient ± SE = −0.021206 ± 0.003944, t = −5.377, p < 0.0001) and 2003–2018 (GLM; coefficient ± SE = −0.10094 ± 0.01801, t = −5.604, p < 0.0001). 4. Discussion This study collected eel fisheries data from six fisheries cooperative associations that harvest eels in the Japanese coastal and estuarine areas and showed that the CPUE was significantly decreasing for four of the six associations. The time period covered by the dataset and over which this significant decrease occurred was longer (14–16 years) in the Aichi, Hyogo, and Okayama longline and Okayama set net associations, compared with the other two associations; i.e., Kanagawa (9 years) and Hiroshima (7 years). The reason why this study could not find significant relationships between catch and year for the Kanagawa 4
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Fig. 3. CPUE obtained from six fisheries cooperatives. CPUEs are estimated as annual catch per number of fishermen and indexed as CPUE = 100 in 2011. Numbers under prefecture names indicate mean annual catch index (Kanagawa = 100).
Japan is not inconsistent with other results obtained in this study at least. Based on these results, the Japanese eel population in Japanese coastal and estuarine areas appears to be currently decreasing. For the Japanese eel, fishery-independent eel-monitoring data for the East Asia region are particularly sparse. Consequently, the IUCN Red List (Jacoby and Gollock, 2014) is informed predominantly by fisheries data from Japan, where such data are relatively more abundant (Jacoby et al., 2015). However, in Japan, non-negligible illegal and unreported glass eel catches occur, which affects the glass eel fisheries statistics (Kaifu, 2016, 2019; Gollock et al., 2018). Moreover, yellow and silver eel fisheries data in Japanese inland water might be biased by stocked individuals (Kaifu et al., 2018a). It is therefore difficult to collect accurate data for yellow and silver eel fisheries in Japanese inland waters and glass eel fisheries in Japan, whereas relatively accurate information regarding the stock dynamics of wild Japanese eels can be obtained from coastal and estuarine areas, where wild eels are dominant (Kaifu et al., 2018a). The dataset used in this study is likely to be one of the best currently available because catch and effort data were collected from the coastal and estuarine area, where the bias of stocked eels on stock dynamics is thought to be relatively low (Kaifu et al., 2018a), and the CPUE dataset was based on a broad questionnaire survey that targeted 1509 coastal and estuary fisheries cooperative associations. This study geographically covered only some parts of Japan, while Japanese eels are distributed throughout East Asia, including Korea, Mainland China and Taiwan. A recent study used otolith 87Sr/86Sr reported that otolith Sr stable isotope ratios of spawning adult Japanese eels that had been captured at spawning area were similar to 87Sr/86Sr of Japanese water rather than that of Korea, Mainland China and Taiwan water (Otake et al., 2019). This suggests that abundance indices (CPUE) of Japanese eels in Japan might be an
Table 2 Results of a generalized linear model (GLM) analysis on the eel fisheries data of six fisheries cooperatives. prefecture
Kanagawa Aichi Hyogo Okayama Okayama Hiroshima
fishing gear
period
bottom trawl set net set net long line set net set net
GLM results coefficient of year (standard error)
t value
p value
2010–2018
−0.1422 (0.1040)
−1.693
0.134
2005–2018 2001–2016 2003–2016 2003–2016 2011–2017
−0.0933 (0.0393) −0.0288 (0.0097) −0.1134 (0.0168) −3.0426 (0.9945) 0.1299 (0.0869)
−2.376 −2.967 −6.762 −3.059 1.494
< 0.05 < 0.01 < 0.001 < 0.01 0.149
and Hiroshima fisheries cooperative associations might be due to the short time period covered by the fisheries data. The result that CPUE for the four of the nine fisheries cooperative associations is significantly decreasing is consistent with the results of the questionnaire survey; 93.4% of fisheries cooperative associations believing that the Japanese eel stock is decreasing or relatively decreasing. Although it is possible that this belief might be biased by media reporting that this species is listed as Endangered on the IUCN Red List of Threatened Species (Jacoby and Gollock, 2014), the local knowledge of fishermen should not be ignored. Moreover, reported glass eel CPUE in nine prefectures in Japan was also significantly decreased for both periods of 1977–2018 and 2003–2018. It is difficult to estimate whether glass eel recruitment is increasing, decreasing or stable based on the reported glass eel CPUE in Japan because of non-negligible illegal and unreported glass eel catch in Japan. However, the significant decrease of glass eel CPUE in 5
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Fig. 4. Glass eel CPUE in nine prefectures in Japan (Chiba, Shizuoka, Aichi, Mie, Tokushima, Kochi, Oita, Miyazaki and Kagoshima Prefectures). CPUEs are estimated as annual glass eel catch (kg) per number of fishermen based on Tanaka (2014) updated with personal communication with the nine prefectures.
References
appropriate indicator of the whole population dynamics of this species. In this study, however, the period of the dataset was not long enough to cover multiple generation lengths (10 years according to the IUCN assessment; Jacoby and Gollock, 2014). Future studies should analyze eel CPUE at larger temporal scales to better understand the stock dynamics of the Japanese eel. A previous stock assessment of the Japanese eel (Tanaka, 2014) estimated that the age 1+ stock of the species has been recovering since 1990 (Fig. 1). The conclusion of Tanaka (2014) is inconsistent with that of this study. One of the reasons for this inconsistency might be the differences in the time frames of these studies. Tanaka (2014) used a data series from 1903 to 2010, whereas this study used a dataset from 2003 to 2018. Another possible reason could be a bias of stocked individuals. Tanaka (2014) estimated the stock dynamics of Japanese eels based on glass eels and exploitable eels (yellow and silver eels) fisheries data in Japan and their biological characteristics, such as survival rate, growth rate, and sex ratio. Tanaka (2014) collected yellow and silver eel fisheries data in Japan from inland waters where fisheries cooperative associations have been stocking eels (Kaifu, 2019). The yellow and silver eel catch data and biological parameters used by Tanaka (2014) may have been affected by the stocked populations in Japanese inland waters. A recent study (Kullmann et al., 2018), moreover, revealed that stress-related annulus-like rings that form during the farming process cannot be distinguished from true annuli formed under natural conditions, and therefore stocking-related aging errors can strongly affect the estimates of biomass. To obtain an accurate understanding of the Japanese eel population, fisheries independent monitoring should be conducted to enable appropriate stock assessments in the future.
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