Massive stocking of chum salmon (Oncorhynchus keta) fry fattens non-native brown trout (Salmo trutta) in Hokkaido, Japan

Kentaro Honda; Koh Hasegawa; Masatoshi Ban; Yutaka Yano; Yuhei Ogura

doi:10.1371/journal.pone.0307552

Abstract

In Japan, stocked chum salmon (Oncorhynchus keta) fry may have become the perfect prey for non-native brown trout (Salmo trutta), which are popular targets of anglers. If this is the case, fry stocking which is intended to boost commercial fishing may be helping to sustain the populations of an invasive predator. We used dietary and biochemical analyses to examine whether brown trout quickly restore their nutritional status following wintertime declines by preying upon chum salmon fry that are stocked in spring. We targeted six rivers in Hokkaido, Japan, three with fry stocking and three without. Changes in brown trout condition factor, triglyceride contents in muscle and serum, serum insulin-like growth factor-1 (IGF-1; an indicator of short-term growth), and docosahexaenoic acid (DHA; an essential fatty acid abundant in fish) content in muscle were examined between before stocking and during the stocking period in the six rivers. Dietary analysis showed that brown trout preyed on fry during the stocking period in all stocked rivers. Their nutritional status tended to be higher during the stocking period than before stocking in stocked rivers, but not in unstocked rivers. These results suggest that the massive stocking of chum salmon fry provides brown trout with the perfect prey to quickly restore their nutritional status and fuel increased growth; this may therefore be a controversial issue among stakeholders.

Citation: Honda K, Hasegawa K, Ban M, Yano Y, Ogura Y (2024) Massive stocking of chum salmon (Oncorhynchus keta) fry fattens non-native brown trout (Salmo trutta) in Hokkaido, Japan. PLoS ONE 19(7): e0307552. https://doi.org/10.1371/journal.pone.0307552

Editor: Dharmendra Kumar Meena, CIFRI: Central Inland Fisheries Research Institute, INDIA

Received: November 24, 2023; Accepted: July 8, 2024; Published: July 19, 2024

Copyright: © 2024 Honda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its supporting information file.

Funding: 1. K. Honda, Grant number: 2021-5211-001, River Fund of The River Foundation, Japan, https://www.kasen.or.jp/ 2. K. Honda and K. Hasegawa, Grant number: JP19K06197, JSPS KAKENHI, https://www.jsps.go.jp/english/ 3. K. Hasegawa, Grant number: JP21K05760, JSPS KAKENHI, https://www.jsps.go.jp/english/ No funders play any role.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Freshwater systems are closely connected to human life. They are important places of food production and host both wild-catch and aquaculture fisheries [1‒3]. Additionally, they are popular destinations for recreation [4], with recreational fishing being one of the most popular activities worldwide, with economic impacts [5]. Consequently, both native and non-native fish species have been stocked into freshwater systems to enhance fisheries resources for both commercial and recreational purposes [1, 6, 7]. In South Africa, for example, common carp (Cyprinus carpio), salmonids, and centrarchids (all non-native to the region) have been introduced to inland waters for angling and food production since the late 1800s [8]. These stocked fishes have caused declines of populations of other sympatric species through interspecific interactions such as competition and predation [8]. Thus, conflicts have arisen between people with differing opinions on fish stocking.

Brown trout (Salmo trutta) are a popular recreational fishing target worldwide, both in and out of their native range [9]. This species is also listed on the IUCN’s “100 of the World’s Worst Invasive Alien Species” [10], and there are considerable concerns about their negative impacts on invaded regions [9]. In Japan, brown trout are believed to have been first introduced in 1892; since then, they have been widely transplanted across Hokkaido and are now found in many rivers in northern Japan [11, 12]. In the process, brown trout populations in Hokkaido have replaced native white-spotted charr (Salvelinus leucomaenis) [13, 14]. In the Falkland Islands, brown trout have been reported to expand their distribution through the movement of anadromous individuals in the ocean [15]. In Japan, the presence of anadromous individuals has been confirmed in several rivers [16, 17], and an individual with anadromous life history has recently been identified in a small river in southern Hokkaido, where the presence of brown trout had not previously been confirmed [18]. Thus, the presence and range expansion of non-native brown trout are feared to have ecosystem-level impacts [9] and to seriously affect native ecosystems in Japan [11, 12, 19].

In the North Pacific, Pacific salmon (Oncorhynchus spp.) are an important fishery resource and have economic value. They are stocked widely through stock enhancement programs, contributing greatly to commercial fisheries resources [20]. However, salmon stocking does not simply increase the abundance of the target species: It also carries the risk of negative impacts on the wider ecosystem at the stocked site, such as by reducing wild populations of the same species or populations of interacting species [21‒24]. Hasegawa et al. [25] showed that stocked chum salmon (Oncorhynchus keta) fry decreased the foraging efficiency and growth of wild native masu salmon (O. masou) fry through interspecific competition and reduced the abundance of aquatic invertebrates through predation.

Chum salmon are native to Japan; as the species most commonly stocked over a wide region, they are a significant contributor to commercial fishery resources in Japan [20, 26]. Most chum salmon fry stocked in spring migrate to the sea within a short period (mostly within a month in Japan, where the distances from stocking points to the sea are less than 100 km) [27]. Chum salmon suffer massive mortality during their early life history [26], likely including by predation in rivers [28‒30], as has been observed in salmon juveniles and fry in other regions [e.g., 31‒33]. Although reducing this predation pressure is desirable to protect stocked salmon fry, it is not realistic to artificially reduce mortality from predators that are widely distributed in both rivers and oceans, unless the removal of predators is judged to be justified.

Because brown trout prey upon chum salmon fry, local commercial fishermen consider brown trout to be harmful to their operations [19]. On the other hand, recreational anglers that target brown trout regard this predation on chum salmon fry to be an inconvenient fact that they fear could provide an excuse to justify a removal program [34]. Nevertheless, even if brown trout were eliminated, native fishes such as white-spotted charr would still prey on fry [30]. Therefore, we believe that the initial focus should not be on reducing the total number of fry preyed upon, but on building consensus between commercial fishermen and recreational anglers to properly manage rivers where hatchery-raised chum salmon and brown trout coexist [19]. To do so, understanding the predator–prey interactions between stocked chum salmon fry and introduced brown trout is essential, but little research on this has been conducted to date.

Brown trout have been observed to individually prey on >100 chum salmon fry in the Chitose River, Hokkaido, within 1 day after fry stocking [29]. Additionally, brown trout in the river do not show noticeable seasonal migration associated with chum fry stocking [29]. In many stocked rivers in Hokkaido, stocking is repeated over multiple days in spring, and the total stocking number exceeds 1 million (Fisheries Resources Institute, unpublished data). These data suggest that the consumption of stocked fry might contribute to brown trout survival and growth. In particular, because the brown trout spawning season in Hokkaido is from autumn to winter [12, 35], brown trout in spring are at their most exhausted after reproduction and overwintering. Moreover, the post-spawning period in fish is generally considered to be a period of accelerated growth [36]. Therefore, the massive stocking of fry in this season could provide brown trout with the perfect food supply in terms of both quantity and quality to restore their depleted nutritional status. If this is the case, then fry stocking which is intended to boost commercial fishing may contribute to sustaining the populations of an invasive predator. Recently, it was reported that concentrations of essential fatty acids in predatory white-spotted charr were increased by predation on stocked masu salmon fry in which the fatty acid content had been enhanced by the feeding of artificial pellets [37]. The same mechanism may be occurring in invasive brown trout. The objective of the present study was to use dietary and biochemical analysis of body tissues to test the hypothesis that brown trout quickly restore their nutritional status following wintertime declines by preying on stocked chum salmon fry.

Materials and methods

Study site

A total of six rivers in central and southern Hokkaido were selected as study sites (Fig 1). Brown trout are common in these rivers [17, 29, 35, 38]. Three of the selected rivers are regularly stocked with chum salmon fry: (1) the Hekirichi River, (2) the main stem of the Chitose River in the Ishikari River system, and (3) the Toyohata River in the Shizunai River system. In these rivers, large releases of hatchery-raised chum salmon fry are conducted multiple times over a 2-month period annually. In 2022, a total of 5.91 million fry (mean fork length [FL]: 5.2 cm) were stocked in the Hekirichi River during 10 releases between 11 March and 18 April, 30.29 million fry (4.5 cm FL) in the Chitose River during 8 releases between 3 March and 23 April, and 12.43 million fry (6.7 cm FL) in the Toyohata River during 14 releases between 11 April and 26 May (S1 Table in S1 File; Fisheries Resources Institute, unpublished data). The other three selected rivers were unstocked: (4) the Oh River in the Kunebetsu River system, (5) the Sosuke River in the Shiribetsu River system, and (6) the Mamachi River in the Chitose River system, all of which are connected to the sea and are capable of supporting wild chum salmon runs. However, no chum salmon adults or fry were observed during the study period in any of the three unstocked rivers.

Download:

Fig 1. Map of the study site.

Red (blue) lines show rivers where chum salmon fry are stocked (unstocked). See Table 1 for detailed sampling locations in each river. River data: Reprinted under a CC BY license, with permission from Information Utilization Division, Real Estate and Construction Economy Bureau, MLIT of Japan, original copyright 2009. Maps were made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

https://doi.org/10.1371/journal.pone.0307552.g001

The introduction history of brown trout to these rivers is not clear. The year of the first recorded brown trout appearance is known in some rivers (e.g., 1984 in the Chitose River [39]), but the number of fish initially stocked and the persons who conducted brown trout stocking are unknown. Takami and Aoyama [40] have speculated that private anglers stocked brown trout into rivers in Hokkaido, but stocking of brown trout is prohibited by the Hokkaido government at present.

Fish sampling

In the Chitose and Mamachi rivers, brown trout were sampled once a month from February to June 2022, including in March and April, when chum salmon fry were stocked in the Chitose River (Table 1; S1 Table in S1 File). In other rivers, sampling was conducted once before (January‒February) and once during the peak (April‒May) of the fry stocking period in 2022. Sampling periods for each unstocked river were matched to those for the nearest stocked river. A total of 9‒15 fish were collected in each river during each sampling period by using an electrofisher (model 12B; Smith Root Co., Vancouver, WA, USA), except for 2 fish collected by angling in May in the Hekirichi River (Table 1). Although the last fry release in the Hekirichi River occurred on 18 April, sampling for the peak stocking period was delayed to 7 May because of increased snowmelt in April, which made sampling impossible. The collected fish were immediately euthanized by cranial pithing and were frozen at –30°C or below until analysis.

Download:

Table 1. Summary of brown trout sampling.

https://doi.org/10.1371/journal.pone.0307552.t001

In the Chitose and Mamachi rivers, among the fish collected, blood samples from 9‒12 fish per month were collected from the caudal peduncle on site by using a syringe (2.5 mL) for analysis of blood composition (Table 1). Blood was injected into 1.5-mL tubes without an anticoagulant, kept cold below 10°C, and brought back to the laboratory. Blood was centrifuged (1000 ×g, 15 min) on the same day, and the supernatant serum was collected and stored at –80°C until analysis.

A total of 215 brown trout were analyzed, with an FL range (mean ± SD) of 10.3‒63.5 cm (24.1 ± 10.2 cm), which was measured after thawing (Table 1; S2 Table in S1 File). In this study, we targeted brown trout of size 10 cm FL or larger because brown trout of 8.7 cm FL have been found to prey on masu salmon fry (which are very similar in body shape to chum salmon fry) in the Chitose River [41].

Dietary analysis

Brown trout were thawed and sexed and measured for FL and body weight (BW, g). Stomach contents were then removed from the excised stomachs and identified to the species level whenever possible. Classified prey items were counted and their wet weight was measured to the nearest 0.001 g. Because the main objective of the present study was to understand the effects of predation on chum salmon fry, fish were classified as either chum salmon fry or as “other fishes.” Other prey items varied and therefore were categorized mainly at the order level as fish eggs, Ezo brown frog (Rana pirica), Amphipoda, Decapoda, Ephemeroptera, Plecoptera, Megaloptera, Trichoptera, Diptera, Gastropoda, other aquatic invertebrates, terrestrial invertebrates, and others. Given the variation in body size of specimens among groups in each river and month, the mean wet weight (MWW) per 100-g converted fish for each prey taxon (excluding digestate) was determined by reference to Tadokoro et al. [42], by using the following formula: (1) where W_i is the wet weight of a prey taxon preyed upon by individual i, n is the number of predator specimens in each river and month, and BW_Ti is the true body weight of individual i, excluding the total wet weight of stomach contents. MWW was calculated for all prey taxa, and the dominance of prey taxa was compared among groups.

Biochemical analysis

Fish condition factor (CF) was determined from the following equation: (2) where BW_T is the true body weight. In fish, neutral lipids represented by triglycerides (TG) are taken up into the blood as an important energy source and subsequently stored in body tissues such as muscle and liver [43]. Therefore, TG concentrations in blood and muscle are often used as indicators of nutritional status in salmonids [44‒47]. Chum salmon fry just before stocking are reported to have higher TG values than wild fry [48]. Additionally, docosahexaenoic acid (DHA) is an n-3 polyunsaturated fatty acid that is abundant in fish, including salmonids, making it a reasonable lipid constituent for assessing the effects of predation on salmon fry [37, 49]. Freshwater salmonids retain DHA directly from their food and also synthesize it from precursors such as eicosapentaenoic acid (EPA), whereas invertebrates such as insects are rich in EPA but poor in DHA as a result of the types of food they consume and their limited ability to synthesize DHA [50]. Serum insulin-like growth factor-1 (IGF-1) is a known indicator of short-term growth and has recently been used for this purpose in salmonids [51, 52]. In the present study, muscle TG content (M-TG, mg/g), serum TG concentration (S-TG, mg/dL), muscle DHA content (mg/g), and IGF-1 concentration (ng/mL) were used as indicators of nutritional status in addition to CF.

M-TG was measured by using LabAssay Triglyceride (GPO-DAOS method; FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan) following Torao [47, 53]. About 2 g of half-thawed dorsal muscle was excised, and lipids were extracted with 10 times the volume of ethanol-ether (3:1) solution. This was followed by centrifugation (1300 ×g, 20 min) to remove foreign substances. The supernatant liquid was mixed with a chromogenic solution, soaked in 37°C water for 5 min, and measured by colorimetric analysis at a wavelength of 630 nm.

S-TG and IGF-1 were analyzed for all specimens sampled for blood in the Chitose and Mamachi rivers. For S-TG, 5 μL was taken from serum dissolved on ice and measured in the same manner as the supernatant of M-TG. IGF-1 was measured by using an IGF-1 ELISA Kit (Cusabio Technology LLC., Houston, TX, USA). Microplates coated with IGF-1 antibody were loaded with 10 μL of dissolved serum and horseradish peroxidase and allowed to react at 37°C for 1 h. A chromogenic solution was added, and the reaction was carried out at 37°C for 15 min before colorimetric analysis at a wavelength of 450 nm.

The analysis of fatty acids was conducted as described by Hasegawa et al. [37]. Seven fish each were randomly selected for analysis before stocking and during the peak of the stocking period in each river. A piece of tissue and skin was sampled from defrosted brown trout from the area between the gill cover and dorsal fin for lipid extraction. Total lipids were extracted by using the method described by Folch et al. [54]. The total lipids were quantitatively transferred to a reaction tube and added to 406 μg of docosanoic acid (22:0) as an internal standard. Fatty acid methyl esters were prepared by acid-catalyzed methylation by using the procedure described by Ichihara and Fukubayashi [55] and analyzed by using gas chromatography (8860GC; Agilent, Santa Clara, CA, USA) with an Omegawax 320 capillary column (length 30 m, internal diameter 0.32 mm, phase thickness 0.25 um) (Sigma-Aldrich Co., St. Louis, MO, USA) and a flame ionization detector. Helium was used as the carrier gas. Chromatograms were integrated by using Agilent OpenLAB data analysis software. Fatty acid methyl esters were identified by comparison of the retention times with those of known standards (Sigma-Aldrich Co.). Quantification of DHA was conducted by using the ratio of the DHA peak areas to the internal standard peak area (22:0).

Statistical analysis

Comparison between the Chitose and Mamachi rivers.

R ver. 4.2.2 [56] was used for all statistical analyses. Indices of nutritional status (CF, M-TG, S-TG, and IGF-1) obtained in each month were compared between the Chitose and Mamachi rivers. General linear models were constructed with CF or log₁₀-transformed M-TG, S-TG, or IGF-1 as objective variables and log₁₀FL (excluded from the CF model), river (Chitose or Mamachi), month (February to June, ordered as categorical variables), and the interaction of river and month as explanatory variables, as follows: (3) (4)

Model outputs were analyzed with Type III ANOVA by using the Anova function in the package “car” [57]. To determine the effect of FL on CF, we examined the relationship between FL and BW_T in each month by using a general linear model: (5)

If the interaction term log₁₀FL × river was significant (ɑ = 0.05), this was interpreted as indicating a difference in the slope of the regression line between rivers.

Comparison between pre- and peak stocking periods.

To determine if the trends observed in the Chitose and Mamachi rivers were consistent with those in other rivers, we added DHA as a factor (while excluding S-TG and IGF-1) and examined whether CF, M-TG, and DHA varied between the pre- and peak stocking periods for chum salmon fry in the six rivers. Linear mixed models with the difference between rivers as a random effect were constructed by using the package “lmerTest” [58], with CF, log₁₀-transformed M-TG, or DHA as objective variables and log₁₀FL (except in the CF model), timing (pre- or peak stocking period), river type (RT; stocked or unstocked), and the interaction of timing and RT as explanatory variables, as follows: (6) (7)

Model outputs were analyzed with Type III ANOVA. To determine the effect of FL on CF, we examined the relationship between FL and BW_T by using the following general linear model: (8)

Separate models were constructed for pre- and peak stocking periods. If the interaction term log₁₀FL × RT was significant (ɑ = 0.05), this was interpreted as indicating a difference in the slope of the regression line between river types. Finally, because DHA is a component of M-TG, correlations between the three indices (including CF) were tested by using Pearson’s correlation test (ɑ = 0.05) between stocked and unstocked rivers before and at the peak of the stocking periods.

Ethics statement

The authors obtained legal permission from the governor of Hokkaido Prefecture for fish sampling and handling (permit numbers 158, 159, 161, and 184 for sampling organisms in inland waters). Permission for animal experiments was not required from the Japan Fisheries Research and Education Agency. All methods were carried out in accordance with the ARRIVE guidelines ver. 2.0 [59]. The collected fish were immediately euthanized by cranial pithing.

Results

Dietary analysis

Chum salmon fry were detected in the stomachs of brown trout collected in all stocked rivers during the peak of the stocking period (Fig 2; S2 Table in S1 File). Fry were additionally found in March (during the stocking period) and May (after the stocking period) in the Chitose River, with particularly high MWW in March and April. Four, six, and two brown trout preyed on 1‒97 chum salmon fry in the Chitose River in March, April, and May, respectively. One and three brown trout in the Hekirichi and Toyohata rivers preyed on 1 and 1‒3 fry, respectively. Mean FL ± SD (range) of brown trout that fed on fry was 31.3 ± 14.8 cm (15.0‒62.7 cm). Predation on chum salmon fry was not observed in other rivers or months. During the peak of the stocking period in the Hekirichi and Toyohata rivers, other fishes (ice goby Leucopsarion petersii, and Gymnogobius spp.) and Amphipoda, respectively, accounted for a relatively high proportion of the stomach contents not taken up by chum salmon fry (Fig 2). Total MWW was lower in unstocked rivers, where aquatic and terrestrial invertebrates were dominant.

Download:

Fig 2. Mean wet weight per 100-g converted brown trout for each stomach content category in each river and month.

Black and white bars show stocked and unstocked rivers, respectively.

https://doi.org/10.1371/journal.pone.0307552.g002

Biochemical analysis

Comparison between the Chitose and Mamachi rivers.

In the general linear model for CF, the variables river and month were significant, showing that CF was higher in the Chitose River than in the Mamachi River and that CF increased as the months progressed (Table 2; Fig 3A). Although the interaction term was insignificant, CF had similar values between the two rivers only in February (before fry stocking). The slope of log₁₀FL relative to log₁₀BW_T did not differ between rivers in any month (i.e., log₁₀FL × river was not significant, F < 1.25, p > 0.277; S1 Fig in S2 File). River × month was significant in the M-TG model, indicating that M-TG tended to increase more over the months in the Chitose River than in the Mamachi River, reaching a maximum in May (Table 2; Fig 3B). River × month was also significant in the S-TG model, reflecting the higher S-TG in the Chitose River than in the Mamachi River during March and April (Table 2; Fig 3C). S-TG in the Chitose River then dropped sharply in May and became comparable to that in the Mamachi River. River × month had a marginal effect in the IGF-1 model, which showed a large difference between rivers in May (Table 2; Fig 3D). FL was not significant in the M-TG and IGF-1 models but had a negative effect on S-TG (estimated coefficient = –0.491; Table 2). Extremely high S-TG exceeding 1000 mg/dL was observed in a total of seven fish with relatively small FL (17.1‒22.6 cm).

Download:

Fig 3.

Box plots of (a) condition factor (CF), (b) triglyceride in muscle (M-TG) and (c) serum (S-TG), and (d) serum insulin-like growth factor-1 (IGF-1) for brown trout sampled from the Mamachi (white) and Chitose (gray) rivers from February to June 2022. Chum salmon fry were stocked in March and April in the Chitose River. Crosses and lines in the middle of boxes show means and medians. Box upper and lower boundaries show 75th and 25th percentiles, respectively. Bars extend to 1.5 times the box height above and below the boxes. Small circles show outlier data points.

https://doi.org/10.1371/journal.pone.0307552.g003

Download:

Table 2. Results of general linear models testing the effects of log₁₀-transformed fork length (log₁₀FL), river (Chitose or Mamachi), month (February‒June), and an interaction term (river × month) on brown trout condition factor (CF), triglyceride in muscle (log₁₀M-TG) and serum (log₁₀S-TG), and insulin-like growth factor-1 (log₁₀IGF-1).

https://doi.org/10.1371/journal.pone.0307552.t002

Comparison between pre- and peak stocking periods.

Timing × RT (river type) was significant in all linear mixed models for CF, M-TG, and DHA, indicating higher nutritional status during the peak stocking period than before the stocking period in stocked rivers (Table 3; Fig 4). Before the stocking period, log₁₀FL × release was not significant, meaning that there was no difference in the slope of log₁₀FL relative to log₁₀BW_T between stocked and unstocked rivers (F = 0.0007, p = 0.979; S2 Fig in S2 File). By contrast, log₁₀FL × release was significant during the peak stocking period (F = 5.228, p = 0.026; S2 Fig in S2 File), and the estimated slope in stocked and unstocked rivers was 3.07 and 2.90, respectively. FL was also significant in the M-TG and DHA models (Table 3), with higher values of both nutritional indices at larger FL (S3 Fig in S2 File). Additionally, there was a significant positive correlation between M-TG and DHA regardless of river type or timing (Table 4), and M-TG and DHA were positively correlated with CF in stocked rivers.

Download:

Fig 4.

Box plots of (a) condition factor (CF), (b) muscle triglyceride (M-TG), and (c) DHA for brown trout sampled before (white boxes) and during the peak (gray boxes) of the chum salmon fry stocking period in stocked (Hekirichi, Chitose, and Toyohata rivers; black bar) and unstocked (Oh, Sosuke, and Mamachi rivers; white bar) rivers. Crosses and lines in the middle of boxes show means and medians. Box upper and lower boundaries show 75th and 25th percentile lines, respectively. Bars extend to 1.5 times the box height above and below the boxes. Small circles show outlier data points.

https://doi.org/10.1371/journal.pone.0307552.g004

Download:

Table 3. Results of selected linear mixed models testing the effects of log₁₀-transformed fork length (log₁₀FL), timing (pre- or peak stocking period), river type (stocked or unstocked), and their interaction terms on condition factor (CF), muscle triglyceride (log₁₀M-TG), and log₁₀DHA of brown trout.

https://doi.org/10.1371/journal.pone.0307552.t003

Download:

Table 4. Coefficients and p-values of Pearson’s correlations among muscle triglyceride (M-TG), DHA, and condition factor (CF) in brown trout before chum salmon fry stocking and during the peak of fry stocking in stocked and unstocked rivers.

https://doi.org/10.1371/journal.pone.0307552.t004

Discussion

Our results indicate that brown trout at the peak of the chum salmon fry stocking period tended to be better nourished in stocked rivers than in unstocked rivers. As previously reported in a number of rivers in Hokkaido [19], predation on chum salmon fry was observed in all stocked rivers, although predation pressure may vary among the rivers depending on the biotic (e.g., prey availability) and abiotic (e.g., water temperature and stream morphology) conditions in each stream. Chum salmon fry accounted for >60% of total MWW in the Chitose River throughout the stocking period. Brown trout are widely distributed throughout the Chitose River and prey on large numbers of chum salmon fry immediately after fry stocking, with one fish reported to have preyed on 481 fry within 1 day after stocking [29]. This suggests that the massive, pulsed supply of fry released into stocked rivers is an important food resource that quickly fills the stomachs of brown trout distributed over a wide area.

In the Hekirichi River, brown trout sampling for the peak of the stocking period occurred 19 days after the last fry release of the season. Because most chum salmon fry in Hokkaido rivers after April migrate to the sea within 10 days of release [27], it is likely that few fry remained in the Hekirichi River during the brown trout sampling, which is consistent with the low fry MWW observed. Other fishes and Amphipoda accounted for relatively large proportions of the MWW during the peak of the stocking period in the Hekirichi and Toyohata rivers, respectively. Although these results provide only a snapshot of brown trout diets during the sampling periods, they may reflect variations in food niche among individual salmonids [60]. For example, in the Hekirichi River a single brown trout preyed on 77 other fishes (other brown trout preyed on three or fewer other fishes), and in the Toyohata River three brown trout preyed on more than 10 Amphipoda.

All nutrient indices tended to be higher in the Chitose River than in the Mamachi River after March, when fry stocking began. CF also increased in the Mamachi River after March, but CF in the Mamachi River in May was at the same level as that in the Chitose River in March, and CF in the Mamachi River in June was at the same level as that in the Chitose River in April (Fig 3A). If we assume that the results from the Mamachi River reflect the normal recovery of CF among brown trout in unstocked rivers, brown trout in the Chitose River appear to have recovered their CF 2 months earlier than normal. Although salmonids are generally considered to be in good condition once their CF exceeds 14 [61], the mean and median CF in the present study exceeded 14 only in May and June in the Chitose River and during the peak of the stocking period in the Hekirichi and Toyohata rivers, suggesting faster recovery in stocked rivers.

During the stocking period, both M-TG and S-TG tended to be higher in stocked rivers than in unstocked rivers. The whole-body TG content of a well-fed chum salmon fry is 14‒23 mg/g [53], and the high TG observed in brown trout in the present study is likely to reflect the absorption of a large amount of TG from salmon fry. In particular, S-TG in March and April was much higher in the Chitose River than in the Mamachi River. Extremely high S-TG values (>1000 mg/dL) were observed in some relatively small individuals, possibly explaining the negative FL effect in the model. In wild brown trout from other regions, blood TG levels rarely exceed 500 mg/dL [e.g., 62‒64]. Our results suggest that S-TG increased rapidly in the Chitose River owing to heavy predation on chum salmon fry once stocking began in March and remained very high as stocking continued into April. M-TG increased further after May in the Chitose River, suggesting that TG eventually accumulated in the muscles. Moreover, the elevated IGF-1 in the Chitose River in May indicates that stored nutrients were being invested into growth, as has been suggested for white-spotted charr preying on masu salmon fry [65]. Increased DHA is also considered to be an effective indicator of nutritional improvement by predation on salmon fry [37, 50]; in the present study, this was especially notable in the Chitose and Toyohata rivers, where there was a large difference between pre- and peak stocking period samples. The positive correlation between M-TG and DHA suggests that M-TG was increased by predation on DHA-rich salmon fry in the stocked rivers rather than on aquatic insects or other invertebrates. In general, there is a positive correlation between muscle lipid content and CF in fish [66, 67]. In the present study, M-TG was correlated with CF in stocked rivers, indicating that CF improved for individuals that accumulated M-TG by preying on salmon fry. However, the observed trends were not consistent in all rivers (i.e., M-TG in the Toyohata River and DHA in the Hekirichi River) and showed considerable variation (Fig 4). These variations could reflect differences in seasonal prey availability among rivers and in the food niches of individual brown trout.

In the comparison of the six rivers, FL significantly affected multiple nutritional indices, likely because larger brown trout had a higher proportion of salmon fry in their diet during the stocking period. Piscivory in brown trout increases with body size [33, 68, 69], and in this study salmon fry were detected more often in the stomachs of large individuals. On the other hand, comparisons between the Chitose and Mamachi rivers showed no significant effect of FL for many indices. This could be because of the relatively small body size variance among the compared groups (range of mean FL: 19.9‒28.6 cm). Further study, including with captive experiments, is needed to determine how each index is affected by body size.

Our results demonstrate that brown trout restore their nutritional status through predation on stocked chum salmon fry. This suggests that chum salmon stocking may be helping to sustain brown trout populations to some extent by improving survival and growth. Not only non-native salmonids but also stocked hatchery salmonids are known to alter stream ecosystems [7, 24]. It would be interesting to investigate how the predator–prey relationship between non-native brown trout and stocked chum salmon fry modifies each impact on stream ecosystems. Meanwhile, our results highlight the potential for controversy among commercial fishermen and recreational anglers because valuable fisheries resources are being preyed upon by non-native species—prime targets of anglers—that are being fattened up as a result. At the very least, brown trout in stocked rivers can be considered more likely to maintain their populations through this predation; these rivers would therefore need to be given high priority as the targets of any brown trout removal programs.

To further clarify the interaction between the two species, it is necessary to determine whether the restoration of nutritional status observed in the present study leads to increased brown trout growth (as suggested by the IGF-1 results) and survival and ultimately to increased investment in reproduction as a “carry-over effect” [70]. In the Trinity River in the United States, non-native brown trout have been shown to prey on large numbers of stocked salmon juveniles, and it appears that the brown trout population there increased substantially after hatchery releases of salmon juveniles began in the 20th century [33]. In addition, brown trout with poor nutritional status are more likely to take on the anadromous form [46, 62, 63, 71], and the presence of suitable habitats in the Kerguelen Islands has been linked to a lack of range expansion via the ocean by brown trout there [72]. These reports suggest that massive stocking of salmon fry might even affect life history selection in brown trout, reducing the incidence of the anadromous form. Therefore, further research is required to elucidate the effects of massive stocking of chum salmon fry on brown trout at the population level. Such knowledge will be indispensable in developing more comprehensive river management measures, including hatchery programs and invasive species management.

Supporting information

S1 File. Supporting information—contains the supporting S1 and S2 Tables.

https://doi.org/10.1371/journal.pone.0307552.s001

(XLSX)

S2 File. Supporting information—contains the supporting S1‒S3 Figs.

https://doi.org/10.1371/journal.pone.0307552.s002

(DOCX)

Acknowledgments

We thank Asami Fukuda of the Fisheries Resources Institute for her assistance with the biochemical analysis.

References

1. Cowx IG. Stocking strategies. Fish Manage Ecol 1994;1: 15–30.
- View Article
- Google Scholar
2. Welcomme RL, Cowx IG, Coates D, Béné C, Funge-Smith S, Halls A, et al. Inland capture fisheries. Philos Trans R Soc Lond B Biol Sci. 2010;365: 2881–2896. pmid:20713391
- View Article
- PubMed/NCBI
- Google Scholar
3. Rath RK. Freshwater aquaculture (3rd ed.). Jodhpur: Scientific publishers. 2018.
4. Postel SL, Carpenter SR (1997): Freshwater ecosystem services. In: Daily G, editor. Nature’s services. Washington: Island Press; 1997. pp 195–214.
5. Arlinghaus R, Tillner R, Bork M. Explaining participation rates in recreational fishing across industrialized countries. Fish Manag Ecol. 2015;22: 45–55.
- View Article
- Google Scholar
6. Welcomme RL, Bartley DM. Current approaches to the enhancement of fisheries. Fish Manage Ecol. 1998;5: 351–382.
- View Article
- Google Scholar
7. Eby LA, Roach WJ, Crowder LB, Stanford JA. Effects of stocking-up freshwater food webs. Trends Ecol Evol. 2006;21: 576–584. pmid:16828522
- View Article
- PubMed/NCBI
- Google Scholar
8. Ellender BR, Woodford DJ, Weyl OLF, Cowx IG. Managing conflicts arising from fisheries enhancement based on non-native fishes in southern Africa. J Fish Biol. 2014; 85: 1890–1906.
- View Article
- Google Scholar
9. Hansen MJ, Guy CS., Budy P, McMahon TE. Trout as native and non-native species: A management paradox. In: Kershner JL, Williams JE, Gresswell RE, Lobon-Cervia J, editors. Trout and char of the world. Bethesda: American Fisheries Society; 2019. pp. 645–684.
10. Lowe S, Browne M, Boudjelas S, De Poorter M. 100 of the world’s worst invasive alien species: a selection from the global invasive species database. Auckland: Invasive Species Specialist Group. 2000.
11. Morita K. Trout and char of Japan. In: Kershner JL, Williams JE, Gresswell RE, Lobon-Cervia J, editors. Trout and char of the world. Bethesda: American Fisheries Society; 2019. pp. 487‒515.
12. Hasegawa K. Invasions of rainbow trout and brown trout in Japan: a comparison of invasiveness and impact on native species. Ecol Freshw Fish. 2020;29: 419‒428.
- View Article
- Google Scholar
13. Takami T, Yoshihara T, Miyakoshi Y, Kuwabara R. 2002. Replacement of white-spotted charr Salvelinus leucomaenis by brown trout Salmo trutta in a branch of the Chitose River, Hokkaido. 2002. Nippon Suisan Gakkaishi. 2002;68: 24–28 (in Japanese with English abstract).
- View Article
- Google Scholar
14. Morita K. Assessing the long-term causal effect of trout invasion on a native charr. Ecol Indic. 2018;87: 189‒192.
- View Article
- Google Scholar
15. McDowall RM, Allibone RM, Chadderton WL. Issues for the conservation and management of Falkland Islands freshwater fishes. Aquat Conserv: Mar Freshw. 2001;11: 473‒486.
- View Article
- Google Scholar
16. Arai T, Kotake A, Aoyama T, Hayano H, Miyazaki N. Identifying sea-run brown trout, Salmo trutta, using Sr:Ca ratios of otolith. Ichthyol Res. 2002;49: 380‒383.
- View Article
- Google Scholar
17. Honda K, Arai T, Kobayashi Y, Tsuda Y, Miyashita K. Migratory patterns of exotic brown trout Salmo trutta in south-western Hokkaido, Japan, on the basis of otolith Sr: Ca ratios and acoustic telemetry. J Fish Biol. 2012;80: 408‒426.
- View Article
- Google Scholar
18. Goto A, Kuroki M, Morita K. Invasion through the sea of a brown trout Salmo trutta in a small river, southern Hokkaido. Jpn J Ichthyol. 2020;67: 241–245 (in Japanese with English abstract).
- View Article
- Google Scholar
19. Shimoda K. Alien fish problems in Hokkaido (introduced Salmonidae fishes). Nippon Suisan Gakkaishi. 2012;78: 754‒757 (in Japanese).
- View Article
- Google Scholar
20. North Pacific Anadromous Fish Commission. The status and trends of Pacific salmon and steelhead trout stocks with linkages to their ecosystem. NPAFC Tech Rep. 2023;19.
21. Araki H, Schmid C. Is hatchery stocking a help or harm? Evidence, limitations and future directions in ecological and genetic surveys. Aquaculture. 2010;308: S2‒S11.
- View Article
- Google Scholar
22. Economic Kitada S., ecological and genetic impacts of marine stock enhancement and sea ranching: a systematic review. Fish Fish. 2018;19: 511‒532.
- View Article
- Google Scholar
23. Kitada S. Lessons from Japan marine stock enhancement and sea ranching programmes over 100 years. Rev Aquac. 2020;12: 1944‒1969.
- View Article
- Google Scholar
24. Terui A, Urabe H, Senzaki M, Nishizawa B. Intentional release of native species undermines ecological stability. PNAS. 2023;120: e2218044120. pmid:36749724
- View Article
- PubMed/NCBI
- Google Scholar
25. Hasegawa K, Ohta T, Takahashi S. Are hatchery chum salmon fry a native invader? Direct and indirect effects of stocking salmon fry on stream organisms. Hydrobiologia. 2018;806: 111–121.
- View Article
- Google Scholar
26. Urawa S, Beacham TD, Fukuwaka M, Kaeriyama M. Ocean ecology of chum salmon. In: Beamish RJ, editor. Ocean ecology of Pacific salmon and trout. Bethesda: American Fisheries Society; 2018. pp. 161–317.
27. Kasugai K, Torao M, Nagata M, Irvine JR. The relationship between migration speed and release date for chum salmon Oncorhynchus keta fry exiting a 110-km northern Japanese river. Fish Sci. 2013;79: 569–577.
- View Article
- Google Scholar
28. Morita K, Nakashima A, Kikuchi M. River temperature drives salmon survivorship: is it determined prior to ocean entry? R Soc Open Sci. 2015;2: 140312. pmid:26064583
- View Article
- PubMed/NCBI
- Google Scholar
29. Honda K, Hasegawa K, Ono I, Miyashita K. Piscivorous brown trout Salmo trutta does not migrate from distant downstream habitats to a massive release site for chum salmon Oncorhynchus keta fry in the Chitose River, northern Japan. Environ Biol Fish. 2023;106: 707‒715.
- View Article
- Google Scholar
30. Okado J, Hasegawa K. Exploring predators of Pacific salmon throughout their life history: the case of Japanese chum, pink, and masu salmon. Rev Fish Biol Fisheries. 2024; Online first: https://doi.org/10.1007/s11160-024-09858-y
- View Article
- Google Scholar
31. Jepsen N, Aarestrup K, Økland F, Rasmussen G. Survival of radio-tagged Atlantic salmon (Salmo salar L.) and trout (Salmo trutta L.) smolts passing a reservoir during seaward migration. Hydrobiologia. 1998;371:347–353.
- View Article
- Google Scholar
32. Henderson JN, Letcher BH. Predation on stocked Atlantic salmon (Salmo salar) fry. Can J Fish Aquat Sci. 2003;60: 32–42.
- View Article
- Google Scholar
33. Alvarez JS, Ward DM. Predation on wild and hatchery salmon by non-native brown trout (Salmo trutta) in the Trinity River, California. Ecol Freshw Fish. 2019;28: 573–585.
- View Article
- Google Scholar
34. Takeuchi K. Introduced brown trout in southern Hokkaido. Shiken kenkyu wa ima. 2016; no. 804 (in Japanese). Available from: https://www.hro.or.jp/list/fisheries/marine/att/ima804.pdf
- View Article
- Google Scholar
35. Shimoda K, Aoyama T, Sakamoto H, Ohkubo S, Hatakeyama M, Takeuchi K. Growth and sexual maturity of brown trout in ten rivers in Hokkaido, Japan (Note). Sci Rep Hokkaido Fish Res Inst. 2017;92: 65‒77 (in Japanese).
- View Article
- Google Scholar
36. Pauly D, Froese R, Liang C, Müller J, Sorensen P. Post-spawning growth acceleration in fish as a result of reduced live weight and thus, increased food conversion efficiency. Environ Biol Fish. 2023;106: 2031‒2043.
- View Article
- Google Scholar
37. Hasegawa K, Yano Y, Honda K, Ogura Y. DHA and EPA levels in a piscivorous fish changed by preying upon stocked salmon fry. Sci Rep. 2023;13: 15278. pmid:37714890
- View Article
- PubMed/NCBI
- Google Scholar
38. Hasegawa K. Population densities of masu salmon and white-spotted charr in the tributaries of Shiribetsu River, southwestern Hokkaido, Japan. Nippon Suisan Gakkaishi.2018;84: 728‒730 (in Japanese).
- View Article
- Google Scholar
39. Urawa S. Seasonal occurrence of Microsporidium takedai (Microsporida) infection in masu salmon, Oncorhynchus masou, from the Chitose River. Physiol Ecol Japan. 1989;1: 587‒598.
- View Article
- Google Scholar
40. Takami T, Aoyama T. Distributions of rainbow trout and brown trout in Hokkaido, northern Japan. Wildlife Conservation Japan. 1999;4: 41–48 (in Japanese with English abstract).
- View Article
- Google Scholar
41. Mayama H. Predation of juvenile masu salmon (Oncorhynchus masou) and brown trout (Salmo trutta) on newly emerged masu salmon fry in the Chitose River. Bulletin of the National Salmon Resources Center. 1999;2: 21‒27 (in Japanese with English abstract).
- View Article
- Google Scholar
42. Tadokoro K, Ishida Y, Davis ND, Ueyanagi S, Sugimoto T. Change in chum salmon (Oncorhynchus keta) stomach contents associated with fluctuations of pink salmon (O. gorbuscha) abundance in the central subarctic Pacific and Bering Sea. Fish. Oceanogr. 1996;5: 89–99.
- View Article
- Google Scholar
43. McClelland G, Zwingelstein G, Weber J, Brichon G. Lipid composition off tissue and plasma in two mediterranean fishes, the gilt-head sea bream (Chrysophyrys auratus) and the European seabass (Dicentratchus labrx). Can J Fish Aquat Sci. 1995;52: 161‒170.
- View Article
- Google Scholar
44. Ando S, Hatano M, Zama K. A composition of muscle lipid during spawning migration of chum salmon Oncorhynchus keta. Bulletin of the Japanese Society of Scientific Fisheries. 1985;51: 1817–1824.
- View Article
- Google Scholar
45. Congleton JL, Wagner T. Blood-chemistry indicators of nutritional status in juvenile salmonids. J Fish Biol. 2006;69: 473‒490.
- View Article
- Google Scholar
46. Bordeleau X, Davidsen JG, Eldøy SH, Sjursen AD, Whoriskey FG, Crossin GT. Nutritional correlates of spatiotemporal variations in the marine habitat use of brown trout (Salmo trutta) veteran migrants. Can J Fish Aquat Sci. 2018;75: 1744‒1754.
- View Article
- Google Scholar
47. Torao M. Effect of water temperature on the feed intake, growth, and feeding efficiency of juvenile chum salmon Oncorhynchus keta after seawater transfer. Aquac Sci. 2022;70: 97‒106.
- View Article
- Google Scholar
48. Shimizu T, Ban M, Miyauchi Y, Umeda K, Nakano K, Fujii M, et al. Nutritional condition of hatchery and wild chum salmon Oncorhynchus keta fry migrating down the Chitose River. J Fish Tech. 2016;8: 89–94 (in Japanese with English abstract).
- View Article
- Google Scholar
49. Tacon AG, Metian M. Fish matters: Importance of aquatic foods in human nutrition and global food supply. Rev Fish Sci. 2013;21, 22–38.
- View Article
- Google Scholar
50. Twining CW, Brenna JT, Hairston NG, Flecker AS. Highly unsaturated fatty acids in nature: What we know and what we need to learn. Oikos. 2016;125: 749–760.
- View Article
- Google Scholar
51. Beckman BR, Shimizu M, Gadberry BA, Cooper KA. Response of the somatotropic axis of juvenile coho salmon to alterations in plane of nutrition with an analysis of the relationships among growth rate and circulating IGF-I and 41 kDa IGFBP. Gen Comp Endocrinol. 2004;135: 334‒344. pmid:14723885
- View Article
- PubMed/NCBI
- Google Scholar
52. Izutsu A, Tadokoro D, Habara S, Ugachi Y, Shimizu M. Evaluation of circulating insulin-like growth factor (IGF)-I and IGF-binding proteins as growth indices in rainbow trout (Oncorhynchus mykiss). Gen Comp Endocrinol. 2022;320: 114008.
- View Article
- Google Scholar
53. Torao M. Validity of fish triglyceride content and liver glycogen content as indicators of nutritional status in chum salmon Oncorhynchus keta fry. Sci Rep Hokkaido Fish Res Inst. 2020;97: 29‒36 (in Japanese with English abstract).
- View Article
- Google Scholar
54. Folch J, Lees M, Slone-Stanley GH. A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem. 1957;226: 497–509.
- View Article
- Google Scholar
55. Ichihara K, Fukubayashi Y. Preparation of fatty acid methyl esters for gas-liquid chromatography. J Lipid Res. 2010;51: 635–640. pmid:19759389
- View Article
- PubMed/NCBI
- Google Scholar
56. R Core Team. R: A language and environment for statistical computing (version 4.2.2). Vienna, Austria. R Foundation for Statistical Computing. 2022.
57. Fox J, Weisberg S. An R companion to applied regression, Third Edition. Thousand Oaks, CA, SAGE Publications; 2019. Available from: https://socialsciences.mcmaster.ca/jfox/Books/Companion/
58. Kuznetsova A, Brockhoff PB, Christensen RHB (2017) lmerTest package: Tests in linear mixed effects models. A Stat Softw. 2017;82: 1‒26.
- View Article
- Google Scholar
59. Percie du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M. et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol. 2020;18: e3000410. pmid:32663219
- View Article
- PubMed/NCBI
- Google Scholar
60. Iguchi K, Matsubara N, Yodo T, Maekawa K. Individual food niche specialization in stream-dwelling charr. Ichthyol Res. 2004;51: 321–326.
- View Article
- Google Scholar
61. Barnham C, Baxter A. Condition factor, K, for salmonid fish. Fish. Notes. 2003;5: 1‒3.
- View Article
- Google Scholar
62. Birnie-Gauvin K, Larsen MH, Aarestrup K. Energetic state and the continuum of migratory tactics in brown trout (Salmo trutta). Can J Fish Aquat Sci. 2021;78: 1435‒1443.
- View Article
- Google Scholar
63. Eldøy SH, Bordeleau X, Lawrence MJ, Thorstad EB, Finstad AG, Whoriskey FG, et al. The effects of nutritional state, sex and body size on the marine migration behaviour of sea trout. Mar Ecol Prog Ser. 2021;665: 185–200.
- View Article
- Google Scholar
64. Mikołajczak Z, Rawski M, Mazurkiewicz J, Kierończyk B, Kołodziejski P, Pruszyńska-Oszmałek E, et al. The first insight into black soldier fly meal in brown trout nutrition as an environmentally sustainable fish meal replacement. Animal. 2022;16: 100516. pmid:35468507
- View Article
- PubMed/NCBI
- Google Scholar
65. Hasegawa K, Fukui S. Pulsed supplies of small fish facilitate time-limited intraguild predation in salmon-stocked streams. R Soc Open Sci. 2022;9: 220127. pmid:36147937
- View Article
- PubMed/NCBI
- Google Scholar
66. Schloesser RW, Fabrizio MC. Condition indices as surrogates of energy density and lipid content in juveniles of three fish species. Trans Am Fish Soc. 2017;146: 1058–1069.
- View Article
- Google Scholar
67. Hards AR, Gray MA, Noël SC, Cunjak RA. Utility of Condition Indices as Predictors of Lipid Content in Slimy Sculpin (Cottus cognatus). Diversity. 2019;11:71.
- View Article
- Google Scholar
68. L’Abée‐Lund JH, Langeland A, Sægrov H. Piscivory by brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus L. in Norwegian lakes. J Fish Biol. 1992;41: 91–101.
- View Article
- Google Scholar
69. Jensen H, Kiljunen M, Amundsen PA. Dietary ontogeny and niche shift to piscivory in lacustrine brown trout Salmo trutta revealed by stomach content and stable isotope analyses. J Fish Biol. 2012;80: 2448‒2462.
- View Article
- Google Scholar
70. Harrison XA, Blount JD, Inger R, Norris DR, Bearhop S. Carry-over effects as drivers of fitness differences in animals. J Anim Ecol. 2011;80: 4–18. pmid:20726924
- View Article
- PubMed/NCBI
- Google Scholar
71. Boel M, Aarestrup K, Baktoft H, Larsen T, Madsen SS, Malte H, et al. The physiological basis of the migration continuum in brown trout (Salmo trutta). Physiol Biochem Zool. 2014;87: 334‒345.
- View Article
- Google Scholar
72. Davidsen JG, Bordeleau X, Eldøy SH, Whoriskey F, Power M, Crossin GT, et al. (2021) Marine habitat use and feeding ecology of introduced anadromous brown trout at the colonization front of the sub-Antarctic Kerguelen archipelago. Sci Rep. 2021;11: 11917.
- View Article
- Google Scholar

[ref1] 1. Cowx IG. Stocking strategies. Fish Manage Ecol 1994;1: 15–30.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Welcomme RL, Cowx IG, Coates D, Béné C, Funge-Smith S, Halls A, et al. Inland capture fisheries. Philos Trans R Soc Lond B Biol Sci. 2010;365: 2881–2896. pmid:20713391
View Article
PubMed/NCBI
Google Scholar

[5] View Article

[6] PubMed/NCBI

[7] Google Scholar

[ref3] 3. Rath RK. Freshwater aquaculture (3rd ed.). Jodhpur: Scientific publishers. 2018.

[ref4] 4. Postel SL, Carpenter SR (1997): Freshwater ecosystem services. In: Daily G, editor. Nature’s services. Washington: Island Press; 1997. pp 195–214.

[ref5] 5. Arlinghaus R, Tillner R, Bork M. Explaining participation rates in recreational fishing across industrialized countries. Fish Manag Ecol. 2015;22: 45–55.
View Article
Google Scholar

[11] View Article

[12] Google Scholar

[ref6] 6. Welcomme RL, Bartley DM. Current approaches to the enhancement of fisheries. Fish Manage Ecol. 1998;5: 351–382.
View Article
Google Scholar

[14] View Article

[15] Google Scholar

[ref7] 7. Eby LA, Roach WJ, Crowder LB, Stanford JA. Effects of stocking-up freshwater food webs. Trends Ecol Evol. 2006;21: 576–584. pmid:16828522
View Article
PubMed/NCBI
Google Scholar

[17] View Article

[18] PubMed/NCBI

[19] Google Scholar

[ref8] 8. Ellender BR, Woodford DJ, Weyl OLF, Cowx IG. Managing conflicts arising from fisheries enhancement based on non-native fishes in southern Africa. J Fish Biol. 2014; 85: 1890–1906.
View Article
Google Scholar

[21] View Article

[22] Google Scholar

[ref9] 9. Hansen MJ, Guy CS., Budy P, McMahon TE. Trout as native and non-native species: A management paradox. In: Kershner JL, Williams JE, Gresswell RE, Lobon-Cervia J, editors. Trout and char of the world. Bethesda: American Fisheries Society; 2019. pp. 645–684.

[ref10] 10. Lowe S, Browne M, Boudjelas S, De Poorter M. 100 of the world’s worst invasive alien species: a selection from the global invasive species database. Auckland: Invasive Species Specialist Group. 2000.

[ref11] 11. Morita K. Trout and char of Japan. In: Kershner JL, Williams JE, Gresswell RE, Lobon-Cervia J, editors. Trout and char of the world. Bethesda: American Fisheries Society; 2019. pp. 487‒515.

[ref12] 12. Hasegawa K. Invasions of rainbow trout and brown trout in Japan: a comparison of invasiveness and impact on native species. Ecol Freshw Fish. 2020;29: 419‒428.
View Article
Google Scholar

[27] View Article

[28] Google Scholar

[ref13] 13. Takami T, Yoshihara T, Miyakoshi Y, Kuwabara R. 2002. Replacement of white-spotted charr Salvelinus leucomaenis by brown trout Salmo trutta in a branch of the Chitose River, Hokkaido. 2002. Nippon Suisan Gakkaishi. 2002;68: 24–28 (in Japanese with English abstract).
View Article
Google Scholar

[30] View Article

[31] Google Scholar

[ref14] 14. Morita K. Assessing the long-term causal effect of trout invasion on a native charr. Ecol Indic. 2018;87: 189‒192.
View Article
Google Scholar

[33] View Article

[34] Google Scholar

[ref15] 15. McDowall RM, Allibone RM, Chadderton WL. Issues for the conservation and management of Falkland Islands freshwater fishes. Aquat Conserv: Mar Freshw. 2001;11: 473‒486.
View Article
Google Scholar

[36] View Article

[37] Google Scholar

[ref16] 16. Arai T, Kotake A, Aoyama T, Hayano H, Miyazaki N. Identifying sea-run brown trout, Salmo trutta, using Sr:Ca ratios of otolith. Ichthyol Res. 2002;49: 380‒383.
View Article
Google Scholar

[39] View Article

[40] Google Scholar

[ref17] 17. Honda K, Arai T, Kobayashi Y, Tsuda Y, Miyashita K. Migratory patterns of exotic brown trout Salmo trutta in south-western Hokkaido, Japan, on the basis of otolith Sr: Ca ratios and acoustic telemetry. J Fish Biol. 2012;80: 408‒426.
View Article
Google Scholar

[42] View Article

[43] Google Scholar

[ref18] 18. Goto A, Kuroki M, Morita K. Invasion through the sea of a brown trout Salmo trutta in a small river, southern Hokkaido. Jpn J Ichthyol. 2020;67: 241–245 (in Japanese with English abstract).
View Article
Google Scholar

[45] View Article

[46] Google Scholar

[ref19] 19. Shimoda K. Alien fish problems in Hokkaido (introduced Salmonidae fishes). Nippon Suisan Gakkaishi. 2012;78: 754‒757 (in Japanese).
View Article
Google Scholar

[48] View Article

[49] Google Scholar

[ref20] 20. North Pacific Anadromous Fish Commission. The status and trends of Pacific salmon and steelhead trout stocks with linkages to their ecosystem. NPAFC Tech Rep. 2023;19.

[ref21] 21. Araki H, Schmid C. Is hatchery stocking a help or harm? Evidence, limitations and future directions in ecological and genetic surveys. Aquaculture. 2010;308: S2‒S11.
View Article
Google Scholar

[52] View Article

[53] Google Scholar

[ref22] 22. Economic Kitada S., ecological and genetic impacts of marine stock enhancement and sea ranching: a systematic review. Fish Fish. 2018;19: 511‒532.
View Article
Google Scholar

[55] View Article

[56] Google Scholar

[ref23] 23. Kitada S. Lessons from Japan marine stock enhancement and sea ranching programmes over 100 years. Rev Aquac. 2020;12: 1944‒1969.
View Article
Google Scholar

[58] View Article

[59] Google Scholar

[ref24] 24. Terui A, Urabe H, Senzaki M, Nishizawa B. Intentional release of native species undermines ecological stability. PNAS. 2023;120: e2218044120. pmid:36749724
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref25] 25. Hasegawa K, Ohta T, Takahashi S. Are hatchery chum salmon fry a native invader? Direct and indirect effects of stocking salmon fry on stream organisms. Hydrobiologia. 2018;806: 111–121.
View Article
Google Scholar

[65] View Article

[66] Google Scholar

[ref26] 26. Urawa S, Beacham TD, Fukuwaka M, Kaeriyama M. Ocean ecology of chum salmon. In: Beamish RJ, editor. Ocean ecology of Pacific salmon and trout. Bethesda: American Fisheries Society; 2018. pp. 161–317.

[ref27] 27. Kasugai K, Torao M, Nagata M, Irvine JR. The relationship between migration speed and release date for chum salmon Oncorhynchus keta fry exiting a 110-km northern Japanese river. Fish Sci. 2013;79: 569–577.
View Article
Google Scholar

[69] View Article

[70] Google Scholar

[ref28] 28. Morita K, Nakashima A, Kikuchi M. River temperature drives salmon survivorship: is it determined prior to ocean entry? R Soc Open Sci. 2015;2: 140312. pmid:26064583
View Article
PubMed/NCBI
Google Scholar

[72] View Article

[73] PubMed/NCBI

[74] Google Scholar

[ref29] 29. Honda K, Hasegawa K, Ono I, Miyashita K. Piscivorous brown trout Salmo trutta does not migrate from distant downstream habitats to a massive release site for chum salmon Oncorhynchus keta fry in the Chitose River, northern Japan. Environ Biol Fish. 2023;106: 707‒715.
View Article
Google Scholar

[76] View Article

[77] Google Scholar

[ref30] 30. Okado J, Hasegawa K. Exploring predators of Pacific salmon throughout their life history: the case of Japanese chum, pink, and masu salmon. Rev Fish Biol Fisheries. 2024; Online first: https://doi.org/10.1007/s11160-024-09858-y
View Article
Google Scholar

[79] View Article

[80] Google Scholar

[ref31] 31. Jepsen N, Aarestrup K, Økland F, Rasmussen G. Survival of radio-tagged Atlantic salmon (Salmo salar L.) and trout (Salmo trutta L.) smolts passing a reservoir during seaward migration. Hydrobiologia. 1998;371:347–353.
View Article
Google Scholar

[82] View Article

[83] Google Scholar

[ref32] 32. Henderson JN, Letcher BH. Predation on stocked Atlantic salmon (Salmo salar) fry. Can J Fish Aquat Sci. 2003;60: 32–42.
View Article
Google Scholar

[85] View Article

[86] Google Scholar

[ref33] 33. Alvarez JS, Ward DM. Predation on wild and hatchery salmon by non-native brown trout (Salmo trutta) in the Trinity River, California. Ecol Freshw Fish. 2019;28: 573–585.
View Article
Google Scholar

[88] View Article

[89] Google Scholar

[ref34] 34. Takeuchi K. Introduced brown trout in southern Hokkaido. Shiken kenkyu wa ima. 2016; no. 804 (in Japanese). Available from: https://www.hro.or.jp/list/fisheries/marine/att/ima804.pdf
View Article
Google Scholar

[91] View Article

[92] Google Scholar

[ref35] 35. Shimoda K, Aoyama T, Sakamoto H, Ohkubo S, Hatakeyama M, Takeuchi K. Growth and sexual maturity of brown trout in ten rivers in Hokkaido, Japan (Note). Sci Rep Hokkaido Fish Res Inst. 2017;92: 65‒77 (in Japanese).
View Article
Google Scholar

[94] View Article

[95] Google Scholar

[ref36] 36. Pauly D, Froese R, Liang C, Müller J, Sorensen P. Post-spawning growth acceleration in fish as a result of reduced live weight and thus, increased food conversion efficiency. Environ Biol Fish. 2023;106: 2031‒2043.
View Article
Google Scholar

[97] View Article

[98] Google Scholar

[ref37] 37. Hasegawa K, Yano Y, Honda K, Ogura Y. DHA and EPA levels in a piscivorous fish changed by preying upon stocked salmon fry. Sci Rep. 2023;13: 15278. pmid:37714890
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref38] 38. Hasegawa K. Population densities of masu salmon and white-spotted charr in the tributaries of Shiribetsu River, southwestern Hokkaido, Japan. Nippon Suisan Gakkaishi.2018;84: 728‒730 (in Japanese).
View Article
Google Scholar

[104] View Article

[105] Google Scholar

[ref39] 39. Urawa S. Seasonal occurrence of Microsporidium takedai (Microsporida) infection in masu salmon, Oncorhynchus masou, from the Chitose River. Physiol Ecol Japan. 1989;1: 587‒598.
View Article
Google Scholar

[107] View Article

[108] Google Scholar

[ref40] 40. Takami T, Aoyama T. Distributions of rainbow trout and brown trout in Hokkaido, northern Japan. Wildlife Conservation Japan. 1999;4: 41–48 (in Japanese with English abstract).
View Article
Google Scholar

[110] View Article

[111] Google Scholar

[ref41] 41. Mayama H. Predation of juvenile masu salmon (Oncorhynchus masou) and brown trout (Salmo trutta) on newly emerged masu salmon fry in the Chitose River. Bulletin of the National Salmon Resources Center. 1999;2: 21‒27 (in Japanese with English abstract).
View Article
Google Scholar

[113] View Article

[114] Google Scholar

[ref42] 42. Tadokoro K, Ishida Y, Davis ND, Ueyanagi S, Sugimoto T. Change in chum salmon (Oncorhynchus keta) stomach contents associated with fluctuations of pink salmon (O. gorbuscha) abundance in the central subarctic Pacific and Bering Sea. Fish. Oceanogr. 1996;5: 89–99.
View Article
Google Scholar

[116] View Article

[117] Google Scholar

[ref43] 43. McClelland G, Zwingelstein G, Weber J, Brichon G. Lipid composition off tissue and plasma in two mediterranean fishes, the gilt-head sea bream (Chrysophyrys auratus) and the European seabass (Dicentratchus labrx). Can J Fish Aquat Sci. 1995;52: 161‒170.
View Article
Google Scholar

[119] View Article

[120] Google Scholar

[ref44] 44. Ando S, Hatano M, Zama K. A composition of muscle lipid during spawning migration of chum salmon Oncorhynchus keta. Bulletin of the Japanese Society of Scientific Fisheries. 1985;51: 1817–1824.
View Article
Google Scholar

[122] View Article

[123] Google Scholar

[ref45] 45. Congleton JL, Wagner T. Blood-chemistry indicators of nutritional status in juvenile salmonids. J Fish Biol. 2006;69: 473‒490.
View Article
Google Scholar

[125] View Article

[126] Google Scholar

[ref46] 46. Bordeleau X, Davidsen JG, Eldøy SH, Sjursen AD, Whoriskey FG, Crossin GT. Nutritional correlates of spatiotemporal variations in the marine habitat use of brown trout (Salmo trutta) veteran migrants. Can J Fish Aquat Sci. 2018;75: 1744‒1754.
View Article
Google Scholar

[128] View Article

[129] Google Scholar

[ref47] 47. Torao M. Effect of water temperature on the feed intake, growth, and feeding efficiency of juvenile chum salmon Oncorhynchus keta after seawater transfer. Aquac Sci. 2022;70: 97‒106.
View Article
Google Scholar

[131] View Article

[132] Google Scholar

[ref48] 48. Shimizu T, Ban M, Miyauchi Y, Umeda K, Nakano K, Fujii M, et al. Nutritional condition of hatchery and wild chum salmon Oncorhynchus keta fry migrating down the Chitose River. J Fish Tech. 2016;8: 89–94 (in Japanese with English abstract).
View Article
Google Scholar

[134] View Article

[135] Google Scholar

[ref49] 49. Tacon AG, Metian M. Fish matters: Importance of aquatic foods in human nutrition and global food supply. Rev Fish Sci. 2013;21, 22–38.
View Article
Google Scholar

[137] View Article

[138] Google Scholar

[ref50] 50. Twining CW, Brenna JT, Hairston NG, Flecker AS. Highly unsaturated fatty acids in nature: What we know and what we need to learn. Oikos. 2016;125: 749–760.
View Article
Google Scholar

[140] View Article

[141] Google Scholar

[ref51] 51. Beckman BR, Shimizu M, Gadberry BA, Cooper KA. Response of the somatotropic axis of juvenile coho salmon to alterations in plane of nutrition with an analysis of the relationships among growth rate and circulating IGF-I and 41 kDa IGFBP. Gen Comp Endocrinol. 2004;135: 334‒344. pmid:14723885
View Article
PubMed/NCBI
Google Scholar

[143] View Article

[144] PubMed/NCBI

[145] Google Scholar

[ref52] 52. Izutsu A, Tadokoro D, Habara S, Ugachi Y, Shimizu M. Evaluation of circulating insulin-like growth factor (IGF)-I and IGF-binding proteins as growth indices in rainbow trout (Oncorhynchus mykiss). Gen Comp Endocrinol. 2022;320: 114008.
View Article
Google Scholar

[147] View Article

[148] Google Scholar

[ref53] 53. Torao M. Validity of fish triglyceride content and liver glycogen content as indicators of nutritional status in chum salmon Oncorhynchus keta fry. Sci Rep Hokkaido Fish Res Inst. 2020;97: 29‒36 (in Japanese with English abstract).
View Article
Google Scholar

[150] View Article

[151] Google Scholar

[ref54] 54. Folch J, Lees M, Slone-Stanley GH. A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem. 1957;226: 497–509.
View Article
Google Scholar

[153] View Article

[154] Google Scholar

[ref55] 55. Ichihara K, Fukubayashi Y. Preparation of fatty acid methyl esters for gas-liquid chromatography. J Lipid Res. 2010;51: 635–640. pmid:19759389
View Article
PubMed/NCBI
Google Scholar

[156] View Article

[157] PubMed/NCBI

[158] Google Scholar

[ref56] 56. R Core Team. R: A language and environment for statistical computing (version 4.2.2). Vienna, Austria. R Foundation for Statistical Computing. 2022.

[ref57] 57. Fox J, Weisberg S. An R companion to applied regression, Third Edition. Thousand Oaks, CA, SAGE Publications; 2019. Available from: https://socialsciences.mcmaster.ca/jfox/Books/Companion/

[ref58] 58. Kuznetsova A, Brockhoff PB, Christensen RHB (2017) lmerTest package: Tests in linear mixed effects models. A Stat Softw. 2017;82: 1‒26.
View Article
Google Scholar

[162] View Article

[163] Google Scholar

[ref59] 59. Percie du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M. et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol. 2020;18: e3000410. pmid:32663219
View Article
PubMed/NCBI
Google Scholar

[165] View Article

[166] PubMed/NCBI

[167] Google Scholar

[ref60] 60. Iguchi K, Matsubara N, Yodo T, Maekawa K. Individual food niche specialization in stream-dwelling charr. Ichthyol Res. 2004;51: 321–326.
View Article
Google Scholar

[169] View Article

[170] Google Scholar

[ref61] 61. Barnham C, Baxter A. Condition factor, K, for salmonid fish. Fish. Notes. 2003;5: 1‒3.
View Article
Google Scholar

[172] View Article

[173] Google Scholar

[ref62] 62. Birnie-Gauvin K, Larsen MH, Aarestrup K. Energetic state and the continuum of migratory tactics in brown trout (Salmo trutta). Can J Fish Aquat Sci. 2021;78: 1435‒1443.
View Article
Google Scholar

[175] View Article

[176] Google Scholar

[ref63] 63. Eldøy SH, Bordeleau X, Lawrence MJ, Thorstad EB, Finstad AG, Whoriskey FG, et al. The effects of nutritional state, sex and body size on the marine migration behaviour of sea trout. Mar Ecol Prog Ser. 2021;665: 185–200.
View Article
Google Scholar

[178] View Article

[179] Google Scholar

[ref64] 64. Mikołajczak Z, Rawski M, Mazurkiewicz J, Kierończyk B, Kołodziejski P, Pruszyńska-Oszmałek E, et al. The first insight into black soldier fly meal in brown trout nutrition as an environmentally sustainable fish meal replacement. Animal. 2022;16: 100516. pmid:35468507
View Article
PubMed/NCBI
Google Scholar

[181] View Article

[182] PubMed/NCBI

[183] Google Scholar

[ref65] 65. Hasegawa K, Fukui S. Pulsed supplies of small fish facilitate time-limited intraguild predation in salmon-stocked streams. R Soc Open Sci. 2022;9: 220127. pmid:36147937
View Article
PubMed/NCBI
Google Scholar

[185] View Article

[186] PubMed/NCBI

[187] Google Scholar

[ref66] 66. Schloesser RW, Fabrizio MC. Condition indices as surrogates of energy density and lipid content in juveniles of three fish species. Trans Am Fish Soc. 2017;146: 1058–1069.
View Article
Google Scholar

[189] View Article

[190] Google Scholar

[ref67] 67. Hards AR, Gray MA, Noël SC, Cunjak RA. Utility of Condition Indices as Predictors of Lipid Content in Slimy Sculpin (Cottus cognatus). Diversity. 2019;11:71.
View Article
Google Scholar

[192] View Article

[193] Google Scholar

[ref68] 68. L’Abée‐Lund JH, Langeland A, Sægrov H. Piscivory by brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus L. in Norwegian lakes. J Fish Biol. 1992;41: 91–101.
View Article
Google Scholar

[195] View Article

[196] Google Scholar

[ref69] 69. Jensen H, Kiljunen M, Amundsen PA. Dietary ontogeny and niche shift to piscivory in lacustrine brown trout Salmo trutta revealed by stomach content and stable isotope analyses. J Fish Biol. 2012;80: 2448‒2462.
View Article
Google Scholar

[198] View Article

[199] Google Scholar

[ref70] 70. Harrison XA, Blount JD, Inger R, Norris DR, Bearhop S. Carry-over effects as drivers of fitness differences in animals. J Anim Ecol. 2011;80: 4–18. pmid:20726924
View Article
PubMed/NCBI
Google Scholar

[201] View Article

[202] PubMed/NCBI

[203] Google Scholar

[ref71] 71. Boel M, Aarestrup K, Baktoft H, Larsen T, Madsen SS, Malte H, et al. The physiological basis of the migration continuum in brown trout (Salmo trutta). Physiol Biochem Zool. 2014;87: 334‒345.
View Article
Google Scholar

[205] View Article

[206] Google Scholar

[ref72] 72. Davidsen JG, Bordeleau X, Eldøy SH, Whoriskey F, Power M, Crossin GT, et al. (2021) Marine habitat use and feeding ecology of introduced anadromous brown trout at the colonization front of the sub-Antarctic Kerguelen archipelago. Sci Rep. 2021;11: 11917.
View Article
Google Scholar

[208] View Article

[209] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Study site

Fish sampling

Dietary analysis

Biochemical analysis

Statistical analysis

Comparison between the Chitose and Mamachi rivers.

Comparison between pre- and peak stocking periods.

Ethics statement

Results

Dietary analysis

Biochemical analysis

Comparison between the Chitose and Mamachi rivers.

Comparison between pre- and peak stocking periods.

Discussion

Supporting information

S1 File. Supporting information—contains the supporting S1 and S2 Tables.

S2 File. Supporting information—contains the supporting S1‒S3 Figs.

Acknowledgments

References