Fish Sci (2010) 76:719–728 DOI 10.1007/s12562-010-0276-9 ORIGINAL ARTICLE Fisheries Evaluation of four models for estimating the population size of largemouth bass in an experimental pond Osamu Katano Received: January 2010 / Accepted: June 2010 / Published online: 13 August 2010 Ó The Japanese Society of Fisheries Science 2010 Abstract The utility of four commonly used models for estimating population size in teleosts was tested Sixty-five individually marked largemouth bass, Micropterus salmoides, were introduced into a concrete pond Fishing surveys were conducted every days for a period of 19 days The collected data were then used to estimate the population size under a variety of conditions using the following models: mark/recapture (Petersen method), DeLury (first model), and two models of the software program Capture Comparison of the actual population size with population estimates obtained using the mark/recapture method showed that the percentage of absolute error was \30% in all cases in which the number of fish caught and marked in the first survey was [30% of the population Using the DeLury method and Model of Capture, the population estimates were biased toward underestimation, but the error was \30% when the number of fish caught in all surveys was [70% In contrast, in Model of Capture, the error was relatively small when the percentage of fish caught in all surveys was \70% These conditions for minimizing errors should be taken into account by fisheries managers when estimating the population size of largemouth bass Keywords DeLury method Á Largemouth bass Á Mark and recapture Á Population estimation Á Program Capture O Katano (&) National Research Institute of Fisheries Science, Fisheries Research Agency, 1088 Komaki, Ueda, Nagano 386-0031, Japan e-mail: katano@fra.affrc.go.jp Introduction Largemouth bass Micropterus salmoides have a significant negative impact on many inland fisheries and ecosystems [1–4] Considerable effort has been devoted to the eradication of largemouth bass in ponds, lakes, and rivers in Japan However, a number of eradication programs have failed to evaluate the effectiveness of these efforts in controlling the population size Instead, most programs have focused on the number of bass that were removed To successfully evaluate an eradication program, it is critical to obtain estimates of the population size before and after each removal effort There are several methods for estimating population size in teleosts [5, 6], some of which have been applied to estimate largemouth bass populations in Japan [7–9] However, there is little basis for determining which of these methods is the most appropriate for this species Generally, the larger size classes of bass become increasingly difficult to catch under heavy fishing pressure, possibly due to learned avoidance behavior by these larger fish Individual differences in ease of capture and learning ability among largemouth bass have been documented [10] Taken together, these factors suggest that a number of the methods currently in use for estimating population size may not be applicable for this species The objective of the study reported here was to evaluate the utility of four methods that are commonly used to estimate population size In this study, 65 largemouth bass were introduced into an experimental pond, and angling surveys were conducted over a 19-day period The data were then used to estimate the population size using the following models: mark/recapture (Petersen), DeLury, and two models of the software program Capture [11–13] It was possible to calculate the exact error of the population 123 720 Fish Sci (2010) 76:719–728 Materials and methods In the evening of days when sampling was not conducted, the largemouth bass were fed with 65 live Japanese dace (7–10 cm SL) On October 2009, the pond was drained, and all 65 largemouth bass were captured No bass died during the experiment All experimental procedures were conducted with permission of the Ministry of the Environment of Japan Fishing experiment Data analysis The experiments were conducted at the National Research Institute of Fisheries Science in the city of Ueda, Nagano Prefecture, Japan The largemouth bass were captured from ponds and lakes near Ueda City and acclimated for [30 days before the experiments were initiated The experimental pond (length 40.0 m, width 5.3 m) was constructed of concrete [10] River water was pumped (3.3 l/s) into the upper end of the pond and exited from the lower end The water depth was maintained at 75–80 cm Nine refuges for the fish, each consisting of four concrete blocks (39 cm long, 18 cm wide, 15 cm high) were constructed These refuges were placed at equal intervals (approx 4.9 m) along the center of the pond At the beginning of the experiment, the fish (n = 65) were anesthetized using 2-phenoxyethanol, and the standard length and body weight were recorded to the nearest 0.1 cm and 0.1 g, respectively Each fish was marked with a unique combination of fin marks by cutting two or three small sections of the dorsal, caudal, ventral, or anal fins The bass were then introduced into the experimental pond on September 2007 The water temperature was measured at three sites in the pond at the same time on each day (1500 hours) The temperature ranged from 21.0 to 25.6°C throughout the study There was no rainfall on any of the survey days Angling surveys were conducted using bait or lures every days between 11 and 29 September 2007 (i.e., 10 surveys) The surveys were conducted during a 6-h period between 0900 and 1700 hours For bait fishing, an 8.5-m rod (model H80-85ZT; Shimano, Keihou, Japan) and a 0.205-mm-diameter line with a small float were used The bait consisted of either live worms or shrimps For lure fishing, a 1.98-m rod (model 662MRS-S; Daiwa, Tokyo, Japan) with a reel (model Emblem-S 2000iA; Daiwa) and a 0.235-mm-diameter line were used A soft plastic worm (3.500 Kut Tail Worm J7S-10-229 10; Gary Yamamoto Custom Baits, Milam, TX) was attached to a single hook (Dream hook 15-2; Decoy, Japan) A live Japanese dace Tribolodon hakonensis [7–10 cm standard length (SL)] was sometimes attached to this fishing tackle as a bait fish Each of these methods was used on each survey day to determine the most effective method, which was then used until the catch rate declined All fish were released back into the pond after the fin clip pattern was recorded The following methods were used to estimate the population size: mark and recapture, DeLury, and the program Capture In each instance, the simplest method to derive a population estimate was used To evaluate the mark/recapture model, the Petersen method [5, 6] was applied The population size was estimated using the formula: estimates because the actual population size was known The results of this paper may be used by fisheries managers and other interest groups for evaluating the success of efforts to eradicate largemouth bass 123 N ¼ ðn=mÞM ð1Þ where N is the estimated population size, M is the number of marked fish, m is the number of recaptured fish, and n is the total number of fish captured in the angling surveys In this study, all of the bass were marked prior to the experiment Therefore, to estimate population size using the Petersen method, individuals captured at the time of the first survey were considered to be the marked individuals in subsequent recapture surveys Sampling days used for the first survey were varied, as shown in Table The recapture rates for these individuals were then calculated based on this assumption When the number of fish recaptured (m) was \10, the following formula [6, 14, 15] was used to calculate the population size: N ¼ ½ðM þ 1Þðn þ 1Þ=ðm þ 1ފ À ð2Þ When m C 10, 95% confidence limits were calculated according to DeLury [16] When m \ 10, it is difficult to calculate 95% confidence limits exactly, and for pffiffiffi convenience the limits were calculated as N Æ 1:96 v [15] v ¼ ðM þ 1Þðn þ 1ÞðM À mÞðn À mÞ=ðm þ 1Þ2 ðm þ 2Þ ð3Þ To estimate the population size using the DeLury method, the angling effort was divided equally among the survey days (6 h/day) Therefore, the number of bass captured for the first time on day t was represented by (c/f)t (catch per unit effort at time t) [5, 6, 16, 17] Nt represents the number of bass that were not captured from time to time t - and is expressed as follows: Nt ¼ N0 À Kt ð4Þ where N0 is the total number of bass, and Kt is the total number of bass caught between time and time t - The Fish Sci (2010) 76:719–728 721 Table Population estimates derived using the mark/recapture model First survey 1st day 1st and 2nd day 3rd day Number of fish caught in the first survey (%) Recapture trials Number of fish caught in the recapture trials (%) Number of fish recaptured 21 (32.3) 2nd–10th day 57 (87.7) 17 70.4b 50.1–118.6 2nd–9th day 53 (81.5) 17 65.5b 46.8–109.1 2nd–8th day 53 (81.5) 17 65.5b 46.8–109.1 2nd–7th day 51 (78.5) 16 66.9b 47.3–114.3 b 35 (53.8) 13 (20.0) 39 (60.0) 48 (73.8) 16 63.0 44.7–106.5 39 (60.0) 16 51.2a 37.0–83.1 2nd–4th day 34 (52.3) 14 51.0a 36.2–86.4 2nd–3rd day 29 (44.6) 11 55.4a 37.5–105.5 2nd day 20 (30.8) 65.0b 34.2–95.8 3rd–10th day 55 (84.6) 29 66.4b 52.9–89.2 3rd–9th day 48 (73.8) 26 64.6b 51.1–88.0 b 3rd–8th day 46 (70.8) 24 67.1 52.3–93.5 3rd–7th day 43 (66.2) 22 68.4b 52.7–97.4 3rd–6th day 38 (58.5) 20 66.5b 50.8–96.1 3rd–5th day 27 (41.5) 18 52.5a 41.3–72.1 3rd–4th day 20 (30.8) 14 50.0a 38.7–70.7 3rd day 13 (20.0) 49.4a 37.1–64.1 b 4th–10th day 52 (80.0) 10 67.6 43.1–156.7 4th–9th day 45 (69.2) 10 58.5b 37.6–132.4 4th–8th day 42 (64.6) 59.2b 42.5–75.9 4th–7th day 37 (56.9) 65.5b 40.2–90.8 4th–6th day 29 (44.6) 83.0a 33.8–132.2 4th–5th day 15 (23.1) 111.0 b 1.2–220.8 (12.3) 62.0 32.3–91.8 4th–10th day 52 (80.0) 30 67.6b 54.6–88.6 4th–9th day 45 (69.2) 27 65.0b 52.3–85.9 4th–8th day 42 (64.6) 24 68.3b 53.8–93.2 4th–7th day 37 (56.9) 20 72.2a 55.4–103.5 4th–6th day 29 (44.6) 15 75.4a 55.5–117.6 15 (23.1) 10 b 58.5 42.9–92.1 (12.3) 50.4a 35.1–65.7 5th–10th day 48 (73.8) 87.2 42.6–131.8 5th–9th day 41 (63.1) 74.6a 36.8–112.5 5th–8th day 38 (58.5) 69.2b 34.2–104.2 5th–7th day 33 (50.8) 60.2b 30.1–90.4 5th–6th day 22 (33.8) 102.5 3.8–201.2 (12.3) 39.5 3.9–75.2 4th day (12.3) 95% Confidence limit 2nd–5th day 4th–5th day 4th day Number 2nd–6th day 4th day 1st–3rd day Population estimate 5th day The day on which data were first collected was varied a Error \30% of the actual number b Error \10% fishing efficiency is represented by q, and (c/f)t is expressed as qNt Based on these relationships, the following formula was used to estimate the population size level The 95% confidence limits were calculated following DeLury [16] The second model of DeLury is expressed as follows ðc=f Þt ¼ qN0 À qKt : lnðc=f Þt ¼ ln qN0 À qEt ð5Þ The total number of bass in the pond (N) was calculated when the regression equation was significant at the 5% ð6Þ where Et is the total effort from time to time t [5, 6, 16, 17] In this study, the second model was not used because 123 722 Results The total number of bass caught tended to decrease on later sampling days (Fig 1) However, the number of bass caught for the first time increased on days and 10 The number of times an individual bass was caught ranged between zero and eight (Fig 2) Four individuals were not caught throughout the experiment The results of population estimation using the mark/ recapture method are shown in Table When the number 123 30 Number of bass newly caught Number of bass caught 25 Number of bass recaptured 20 15 10 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th Day of sampling Fig Number of largemouth bass that were caught for the first time and recaptured on each day of sampling When the same individuals were caught twice on day, the second capture was ignored 25 20 Number of bass (c/f) equaled on the 9th day in the dataset and, therefore, N0 could not be calculated Capture is an interactive software program developed by the Patuxent Wildlife Research Center (PWRC) of the United States Geological Survey (USGS) [11–13] The program (release date: 16 May 1994) includes a maximum likelihood estimation [18] and is available at http://www mbr-pwrc.usgs.gov/software/capture.html Capture is commonly used to investigate animal abundance [19, 20] Two models of Capture were used in this study by inputting ‘‘task read population removal’’ in the first column The same effort needs to be made in each survey, and the numbers of newly caught individuals are input The first (Model 1, mbh) is based on Otis et al [11], and its result is output first In the first step of this program, the simplest model, which assumes that all members of the population are equally at risk of capture on every survey, is examined This is the null model with no time, behavior, or heterogeneity effects When this model does not fit the data, the next model is applied with assumptions that (q1 = q2 = q3…) where qk is the average probability of capture of all individuals in the kth survey This procedure is continued until the data fit the model However, population estimation is not possible when data are poor or inadequate The second model of Capture (Model 2, mbh-Pollock) uses the generalized jackknife statistics [13] and includes behavior or heterogeneity effects Using specific assumptions, population estimation using the second model is possible for any set of data if the number of investigations is[1, even when the number of animals captured increases in the later investigations In calculations using Capture, to equalize fishing efforts in each survey, when the number of newly caught bass on the first and second day was the first input, the second to third input included data obtained on the following days (3rd and 4th day, 5th and 6th day, 6th and 7th day, and 8th and 9th day) Similarly, when the number on the first to third day was the first input, the second and third day input included data on the following days (4th–6th day and 7th–9th day) Fish Sci (2010) 76:719–728 15 10 0 Number of times an individual bass was caught Fig Number of times an individual bass was caught during the experiment of bass marked ranged between 12.3 and 60.0% of the total number, and the number of recaptured fish ranged between 12.3 and 87.7%, the estimated population size varied between 39.5 and 111.0 The actual number of bass was within the 95% confidence limits in 36 (97.3%) of 37 cases In the estimates that used DeLury’s first model (Table 2), the regression equation was not significant and the population size was not estimated in 15 (38.5%) of 39 cases When the proportion of bass caught in the first survey ranged between 12.3 and 60.0%, and the proportion of bass caught in all surveys ranged between 41.5 and Fish Sci (2010) 76:719–728 723 Table Population estimates derived using the DeLury model First survey 1st day 2nd day 1st and 2nd day 3rd day 1st–3rd day 4th day Number of fish caught in the first survey (%) 21 (32.3) 20 (30.8) 35 (53.8) 13 (20.0) 39 (60.0) (12.3) Number of surveys (n) Number of fish caught in all surveys (%) Regression equation Population estimate r Number P 95% Confidence limit 39 (60.0) 0.977 NS – 41 (63.1) 0.984 0.0163 44.4 23.4–65.4 44 (67.7) 53 (81.5) 0.984 0.893 0.0024 0.0164 45.5 52.2a 23.1–67.9 27.8–76.6 56 (86.2) 0.891 0.0071 55.3a 29.4–81.3 a 57 (87.7) 0.903 0.0021 56.4 29.8–83.0 57 (87.7) 0.915 0.0050 56.4a 29.7–83.1 10 61 (93.8) 0.897 0.0004 59.0b 31.5–86.5 34 (52.3) 0.999 0.0303 38.0 20.7–55.3 39 (60.0) 0.985 0.0145 41.7 21.8–61.6 48 (73.8) 0.862 NS – 51 (78.5) 0.886 0.0186 54.6a 30.1–79.1 53 (81.5) 0.905 0.0051 55.6a 30.3–81.0 53 (81.5) 0.922 0.0011 54.8a 29.5–80.2 60 (92.3) 0.856 0.0032 60.2b 33.5–86.9 41 (63.1) 1.000 0.0163 44.6 23.1–66.1 44 (67.7) 0.995 0.0051 46.3a 24.1–68.5 53 (81.5) 56 (86.2) 0.846 0.848 NS 0.0328 – 58.6b 33.3–83.9 57 (87.7) 0.868 0.0112 58.8b 33.0–84.6 57 (87.7) 0.885 0.0035 58.5b 32.6–84.4 b 34.7–87.9 61 (93.8) 0.859 0.0030 61.3 27 (41.5) 0.939 NS – 38 (58.5) 0.405 NS – 43 (66.2) 0.663 NS – 46 (70.8) 0.786 NS – 48 (73.8) 0.843 0.0172 60.8b 37.1–84.5 a 46.1–97.3 55 (84.6) 0.754 0.0308 71.7 44 (67.7) 0.992 NS – 53 (81.5) 0.742 NS – 56 (86.2) 0.778 NS – 57 (87.7) 0.818 0.0468 65.5b 40.4–90.6 b 57 (87.7) 0.842 0.0174 63.1 38.0–88.2 61 (93.8) 29 (44.6) 0.815 0.768 0.0136 NS 66.5b – 40.8–92.2 37 (56.9) 0.144 NS – 42 (64.6) 0.318 NS – 45 (69.2) 0.556 NS – 52 (80.0) 0.509 NS – The day on which data were first collected was varied NS not significant at the 5% level, – calculation was not possible a Error \30% of the actual number b Error \10% 93.8%, the population estimates ranged between 38.0 and 71.7, and the actual population size was within the 95% confidence limits in 22 (91.7%) of 24 cases The population estimates calculated by Model of program Capture ranged between 37 and 110 in 28 cases, but calculation was not possible in two cases (Table 3) 123 724 Fish Sci (2010) 76:719–728 Table Population estimates derived using the Capture model First survey 1st day 2nd day 1st and 2nd day 3rd day 1st–3rd day 4th day Number of fish caught in the first survey (%) Number of surveys (n) Number of fish captured in all surveys (%) Population estimate Model Model Number 95% Confidence limit Number 95% Confidence limit 39 (60.0) 43 40–58 47a 42–63 41 (63.1) 42 42–51 47a 43–65 44 (67.7) 45 45–53 56a 48–82 53 (81.5) 68b 56–134 98 76–143 56 (86.2) 67b 59–108 74a 62–111 57 (87.7) 57a 57–57 64b 59–95 57 (87.7) 57 a 57–57 57a 57–57 10 61 (93.8) 65b 62–89 97 75–156 34 (52.3) 37 35–51 44 38–61 39 (60.0) 42 40–57 54a 45–77 48 (73.8) 61b 52–96 84a 66–120 51 (78.5) 72 a 55–176 66b 56–97 53 (81.5) 63b 56–102 65b 57–98 53 (81.5) 60 (92.3) 53a 76a 53–53 64–131 53a 116 53–53 87–179 53 (81.5) 59b 55–76 77a 66–100 57 (87.7) 73 a 59–190 69b 62–91 61 (93.8) 62b 62–75 77a 67–105 27 (41.5) 37 29–84 41 33–60 38 (58.5) 110 46–748 71b 56–102 43 (66.2) 74a 50–202 63b 51–93 46 (70.8) 62 b 50–109 61 b 51–92 48 (73.8) 57a 51–83 60b 52–93 55 (84.6) 74a 61–125 104 78–160 39 (60.0) 57 (87.7) 58a 58–66 65b 60–81 (12.3) 29 (44.6) – 57a 44–81 b 49–88 21 (32.3) 20 (30.8) 35 (53.8) 13 (20.0) 37 (56.9) – 42 (64.6) 46a 43–68 62b 61 50–92 45 (69.2) 52 (80.0) 48a 72a 46–61 55–226 60b 94 50–91 72–142 The day on which data were first collected was varied – calculation was not possible a Error \30% of the actual number b Error \10% The actual number of bass was within the 95% confidence limits in 19 (67.9%) of 28 cases The population estimates calculated by Model of Capture ranged between 41 and 116 (Table 3) The actual number of bass lay within the 95% confidence limits in 17 (56.7%) of 30 cases When the first survey was on the first, second, third, or fourth day and the last survey was on the tenth day, the population estimated by Model ranged from 94 to 116, which is larger than the estimates produced by Model and the DeLury model These estimates were 123 34–63 larger than the estimate obtained when the last survey was on the ninth day The population estimates by the four methods exactly predicted the actual number of fish in five (4.2%) cases, overestimated it in 44 cases (37.0%), and underestimated it in 70 cases (58.8%) (Table 4) The ratio of over- to underestimates differed significantly among the four methods (chi-square test, df = 3, v2 = 12.51, P = 0.0058) Most of the estimates (21/24) by the DeLury method were lower than the actual population size Underestimates Fish Sci (2010) 76:719–728 725 Table Numbers of overestimates and underestimates obtained using the four methods of population estimation listed in Tables 1, and Method Number of cases (%) Overestimation Mark/recapture Total Underestimation Exact estimation 20 (54.1) 15 (40.5) (5.4) 37 (100) DeLury (12.5) 21 (87.5) (0.0) 24 (100) Capture (Model 1) (32.1) 18 (64.3) (3.6) 28 (100) Capture (Model 2) 12 (40.0) 16 (53.3) (6.7) 30 (100) Figures in parentheses indicate percentages exceeded overestimates by a factor of two when model of the Capture program was used In contrast, no clear tendency was detected using the mark/recapture method and model of Capture The error of estimation was compared among the four methods (Fig 3) All data are shown in the figure with the percentages of fish captured in the first survey (X axis) and the percentage of fish captured in recapture trials or in all surveys (Y axis) In the mark and recapture method, the percentage of absolute error was \30% in all cases in which the percentage of fish caught and marked in the first survey exceeded 30% Errors[30% occurred when the percentage of fish marked was B20% even when the number of fish caught in the recapture trials exceeded 70% In the DeLury method, estimation was not possible in most of the cases (9/11) in which the percentage of fish caught in the first survey was B20% The error of estimation was\30% in all cases in which the number of fish caught in all surveys was [70%, but the error increased when the proportion decreased to \65% The same tendency was seen in model of Capture The error was \30% in all cases in which the number of fish caught in all surveys exceeded 70% In contrast, the magnitude of the error was not predictable in model of Capture The error was \30% in all four cases in which the percentage of fish caught in the first survey exceeded 50% When the proportion of fish caught in the first survey was B20%, the error was small compared with Model 1, but the error increased when the data on the tenth sampling day were added to the analysis Discussion All models for estimating population size have specific assumptions As no bass died in the experimental pond and there were no immigrants or emigrants, the four models used in this study could be applied for the population estimation The most appropriate method likely varies depending on the species of interest In this study, the behavior of largemouth bass appeared to change over time First, the number of fish caught on a given day decreased with time However, there was also a marked increase in the contribution of previously uncaught individuals during the later angling surveys The reason for this increase is unclear, but such changes can be common in field investigations Second, variation in catchability between individual bass was noted The number of times an individual was caught ranged between zero and eight throughout the experiment Four bass were not captured on any sampling day In a previous paper [10], 34 of the 65 largemouth bass could be classified, according to their catchability, as careful (8), learnable (10), or fishable (16) Fishable bass were caught repeatedly, whereas careful and learnable bass were rarely caught or recaptured Individual differences in catchability have been noted previously in some fish species, including bass [21–24] Such differences may be related to the ability to learn and the awareness of individuals These differences appear to be common in animals as individual behavioral differences or personalities are now recognized in a variety of species [25–28] The existence of learning and individual differences in behavior may invalidate the assumptions of the method, increasing the error and bias of the estimates However, it is generally unknown whether learning and/or individual differences exist in a population It is therefore important to test population estimates against the actual population size and to clarify the conditions necessary to minimize errors In this study, the error of estimation was calculated by comparing the population estimates with the actual population size The population estimates output by the four methods are summarized in Table Population estimates were least biased in terms of over- and underestimation in the mark/ recapture method and Model of Capture In contrast, in the DeLury method and Model of Capture, the outputs were biased to underestimates The tendency for underestimation in the DeLury method has been pointed by Braaten [29] and Otis et al [11] Such underestimations might occur because the catch per unit effort (CPUE) of new bass decreased on later sampling days more than predicted for random processes The actual population size generally lay within the 95% confidence limits of the mark/recapture and DeLury 123 726 Fish Sci (2010) 76:719–728 % of fish caught in all surveys % of fish caught in the recapture trials error < 10% 10% error[...]... No catch No catch Depth (750 m) Depth (900 m) 1 26. 9 No catch 28.9 No catch No catch 1 76. 9 199.0 49.5 45.4 No catch No catch No catch No catch Water temperature -5.1 2.5 Salinity 4.1 -6. 3 n = 6, 1 9 1, AIC = 6 5 ,6 24 -8.3 4.8 – – n = 70 4, AIC = 7,3 82 – – 114 .6 n = 10 8, AIC = 1,2 25 56. 4 6. 5 4.4 -140.1 52.7 n = 50 1, AIC = 5,2 41 -3.5 1 .6 – – n = 2,5 3 0, AIC = 2 5,4 87 – indicates an explanatory variable that was... interpolated, and the areas covered by K Minami Á Y Ito Graduate School of Environmental Science, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido 041- 861 1, Japan H Yasuma Fisheries Technology Department, Kyoto Prefectural Agriculture, Forestry and Fisheries Technology Center, 1 061 Odashukuno, Miyazu, Kyoto 62 6-005 2, Japan N Tojo Field Science Center for Northern Biosphere, Hokkaido University, Aikappu,... catch 96. 6 25.5 24.0 14 .6 Depth (350 m) 80.1 26. 3 149.1 51.2 212 .6 64.4 1 26. 1 31.7 49.0 14.5 Depth (410 m) 100.4 26. 9 127.4 50.9 234.1 63 .8 No catch 75 .6 14 .6 Depth (450 m) 101.1 27.0 178.1 47.9 231.9 53.8 No catch 69 .9 14.9 Depth (510 m) 107.4 26. 8 160 .8 49.3 228.4 59.8 No catch 64 .2 16. 9 Depth (550 m) 89.9 26. 7 281.3 49 .6 237.9 55.3 No catch 60 .7 23.2 Depth (65 0 m) 99.4 27.2 300.7 52.1 225.2 49 .6 No... Flathead flounder 16 Kamchatka flounder 12 2003 8 6 0 16 0 12 2004 0.5 0 12 2005 6 8 0 16 6 8 0 16 6 8 0 16 0 12 2007 0 4 2008 0 12 2008 6 0.5 2 6 0 0 0 0 0 2008 150 210 250 310 350 410 450 510 550 65 0 750 900 150 210 250 310 350 410 450 510 550 65 0 750 900 8 150 210 250 310 350 410 450 510 550 65 0 750 900 2007 6 2 0 1 2008 20 06 6 0 4 2007 0.5 0 12 2008 0 12 20 06 2 0 1 2007 2005 6 0 4 20 06 0.5 0 12 2007... (2004) 6. 4 6. 9 25.3 24 .6 4.9 21.1 20 .6 13.8 23.8 7 .6 Year (2005) 8.5 6. 7 -19.3 19.4 23.2 24.9 54.5 16. 8 34.0 7.2 Year (20 06) 11.5 6. 7 -45.8 17.5 - 26. 9 32.1 29.7 15.4 33.4 7.5 Year (2007) 21 .6 7.0 -15.0 19.0 54.8 25.3 26. 8 14 .6 44.8 7.8 Year (2008) 29 .6 6.9 -32.5 19.3 -21.3 24.7 53.0 15.2 45.3 7.9 Line (B) 9.8 11.3 -0.5 17 .6 – – -2 .6 14.7 6. 7 8.2 Line (C) Line (D) -23.8 6. 5 10.7 7.8 23.7 -1.7 16. 7 20.3... Aikappu, Akkeshi-cho, Akkeshi-gun, Hokkaido 088-111 3, Japan S Fukui Á K Miyashita Field Science Center for Northern Biosphere, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido 041- 861 1, Japan T Nobetsu Shiretoko Nature Foundation, Shiretoko National Park Nature Center, 531 Iwaobetsu, Shari-cho, Hokkaido 099-435 6, Japan Present Address: K Minami (&) Field Science Education and Research Center, Kyoto... glycogen, lipid and protein reserves in body composition During starvation, energy reserves were mobilized for survival and W Liu Key Laboratory of Marine Bio-resources Sustainable Utilization, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 51030 1, China Q Li (&) Á F Gao Á L Kong Fisheries College, Ocean University of China, Qingdao 266 00 3, China e-mail: qili 66@ ouc.edu.cn... 0.351 0.274 Line (E) -0.532 0.255 -1.008 0. 760 – – 0.430 0.429 -1.1 56 0.281 Line (F) -0. 161 0.2 56 -1.249 0.444 – – 0.128 0.519 -1.3 46 0.339 Line (G) -1 .64 5 0.295 -1.311 0.494 – – 1.279 0.381 -1 .66 3 0.401 Line (H) 0.305 0. 265 -1 .61 6 1.425 – – 0.438 0.514 0 .68 8 0.271 Depth (210 m) 0.152 0. 564 -0 .62 0 0. 469 – – -1.297 0.290 0.511 0.350 – 0. 468 SE Depth (250 m) 0.399 0.558 -2.111 0.500 – Depth (310 m) 0.950... 0. 06 0.49 ± 0.04 0 .63 ± 0.07 0.55 ± 0.03 # 0.52 ± 0.05 0 .66 ± 0.07 0 .68 ± 0.09 0.47 ± 0.05 0 .62 ± 0.05 0. 56 ± 0. 06 60 $ 0.55 ± 0.04 0.70 ± 0. 06 0.82 ± 0.07 0. 46 ± 0.02 0.57 ± 0. 06 0.51 ± 0.04 90 # $ 0.54 ± 0.03 0.58 ± 0.07 0 .69 ± 0.10 0.71 ± 0.12 0.79 ± 0.08 0.90 ± 0.10 0.43 ± 0.03 0.41 ± 0.05 0.58 ± 0.08 0.50 ± 0.04 0.50 ± 0.03 0.44 ± 0.05 # 0.57 ± 0.05 0.70 ± 0.09 0.89 ± 0. 06 0.40 ± 0.04 0.49 ± 0. 06. .. oyster Crassostrea gigas in Northland, New Zealand Aquaculture 64 :65 – 76 22 Albentosa MM, Ferna´ndez-Reiriz J, Labarta U, Pe´rez-Camacho A (2007) Response of two species of clams, Ruditapes decussatus and Venerupis pullastra, to starvation: physiological and biochemical parameters Comp Biochem Physiol B 1 46: 241–249 Fish Sci (2010) 76: 737–745 23 Li Y, Qin JG, Li XX, Benkendorff K (2009) Spawning-dependent