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4 October 2010 Spatial and Temporal Variability in Atka Mackerel Female Maturity at Length and Age
Daniel W. Cooper, Susanne F. McDermott, James N. Ianelli
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Abstract

Spatial and temporal variability in maturity at length and maturity at age was examined for female Atka mackerel Pleurogrammus monopterygius in the eastern and central Aleutian Islands of Alaska. Postovulatory follicles (POFs) were evaluated as a potential character to distinguish spent mature fish from immature fish. We estimated that POFs remain in the ovaries for approximately 1 month after spawning, therefore allowing us to include some collections of recently spent fish for maturity estimates. Maturity-at-length data varied significantly among geographic areas and years, whereas maturity-at-age data failed to indicate differences. These results are probably attributable to different growth rates between the areas. An age-based model was developed to account for differences in year-class strengths, and modeling results showed that length at maturity could vary by as much as 4 cm over time because of variable recruitment. Maturity in Atka mackerel seems to be determined more by age than by somatic body size.

Maturity-at-age and maturity-at-length relationships are used in fisheries population dynamics to quantify reproductive output. Maturity at both age and length can vary spatially (Beacham 1983; Bowering 1989; Rochet 1998; Morgan and Colbourne 1999; Olsen et al. 2004) and temporally (Chen and Mello 1999; Morgan and Colbourne 1999; Barot et al. 2004; Hamatsu et al. 2004), causing error in estimates of reproductive output if a spatially and temporally fixed maturity relationship is used.

Commonly, either length or age is used to determine maturity in stock assessments. Although maturity is determined by a combination of age and length, one factor may be more influential than the other in determining maturity for a fish population (Stearns 1992). For stock assessment, selecting the determining factor (length or age) with less temporal and spatial variation would minimize error in reproductive output estimates.

Atka mackerel Pleurogrammus monopterygius currently represent the largest groundfish biomass in the Aleutian Islands, Alaska, and support a large-scale commercial trawl fishery. Atka mackerel females spawn an average of four batches per year (McDermott et al. 2007), and batches are estimated to be spawned 2–4 weeks apart (Zolotov 1993). McDermott and Lowe (1997) reported a constant age at 50% maturity (A50) of 3.6 years for Atka mackerel throughout Alaska, but they documented decreasing length at maturity from east to west, which they attributed to differential spatial growth patterns. Temporal variability in Atka mackerel maturity at age or length has not been determined. Similar to many fish species, the magnitude of the incoming year-classes (annual recruitment) of Atka mackerel is highly variable (Lowe et al. 2008); however, the effect of year-class variation on maturity has not been studied.

To study the temporal and spatial variability associated with maturity at age and length in fish, it is necessary to distinguish spent females from immature females. One ovarian structure used to distinguish spent females from immature females is the postovulatory follicle (POF). Many reports describing POF degeneration indicate that POFs persist for 3 d or less (Hunter and Goldberg 1980; Goldberg et al. 1984; Hunter et al. 1986); therefore, Hunter et al. (1992) recommended avoiding sampling after spawning begins because POFs may not be identifiable and spent mature fish will be erroneously classified as immature. However, there are reports that POFs persist for months in fish from relatively cold waters, making maturity estimates possible from collections that include spent fish (Saborido-Rey and Junquera 1998; Narimatsu et al. 2005). Typical water temperatures during and after Atka mackerel spawning are approximately 4–11°C (Lauth et al. 2007).

Our objectives for this study were to (1) evaluate the use of POFs in maturity classification for postspawning Atka mackerel females; (2) use additional years of data to re-examine the conclusions of McDermott and Lowe (1997) that maturity at age is constant across areas, whereas maturity at length varies with spatial growth differences; (3) determine whether maturity at length or maturity at age (or both) varies temporally; and (4) model the effect of variability in annual population age composition on maturity at length.

Methods

Collection methods

During 2002–2004, ovaries were collected aboard the National Marine Fisheries Service chartered vessel F/T Seafisher by using bottom trawl gear in the eastern Aleutian Islands (Seguam Pass) and the central Aleutian Islands (Tanaga Pass and near Amchitka Island; Figure 1). All cruises were conducted in October, coinciding with the end of the Atka mackerel spawning season (McDermott and Lowe 1997). Five females were randomly sampled from each trawl haul. Total weight (±2 g) and fork length (±1 cm) were recorded, and ovaries were removed and preserved in 10% formalin in seawater buffered with sodium bicarbonate. Otoliths were removed and stored in a 50% solution of ethanol. In addition to the samples collected for this study, the maturity data collected from both study areas in 1993 and 1994 by McDermott and Lowe (1997) were used to examine temporal variability in maturity (Table 1).

Histology

After storage for 1–2 years, ovaries were removed from formalin and were soaked in freshwater for a minimum of 4 h before additional handling. The presence of residual unspawned ova within individual ovaries was observed macroscopically and was recorded. Residual unspawned ova are the few ova that were ready to be spawned but were not successfully expelled from the female. Residual unspawned ova are easily identified by the naked eye because they are relatively large (∼2 mm) and blackish brown in color (compared with the rest of the ovary, which is pink or gray). They remain identifiable for a long period, and some persist in the ovaries for at least 1 year postspawning (McDermott and Lowe 1997).

A cross section was taken from the middle of one ovary, embedded in paraffin, sectioned at 4 μm, mounted on a slide, and stained with hematoxylin and eosin (McDermott and Lowe 1997). Ovary cross sections were examined at 40× and 100× magnification. Oocyte stages were determined, and the presence of POFs was recorded.

Maturity classification and postovulatory follicle evaluation

Oocyte stages and maturity stages were defined by McDermott and Lowe (1997), and three stages of POFs were determined on the basis of descriptions by Hunter and Goldberg (1980). Spent females did not contain developing oocytes and were classified as mature based on presence of residual unspawned ova, POFs, or both. Residual unspawned ova are a reliable character for maturity, but they are not present in all mature females; therefore, they could not be used as a sole character to differentiate spent females from immature females. In females without residual unspawned ova, maturity determination was based solely on the presence of POFs. Because POFs are more ephemeral than residual ova, there is the potential for mature fish to have reabsorbed POFs and be erroneously assigned as immature fish. To reduce the magnitude of this error and to test the validity of POF presence as a maturity character, POF presence was examined in fish that were known to be mature based on the presence of residual unspawned ova. Ovary collections from a given year and area were considered suitable for maturity analysis when the percentage of known mature females (residual ova present) with identifiable POFs was high. It was assumed that these ovary collections were made soon enough after spawning so that the POFs were still present and identifiable within the ovaries of mature fish that did not contain residual unspawned ova.

Age determination

Ages were assigned by the Alaska Fisheries Science Center's Age and Growth Program, which used otoliths according to the procedures outlined by Anderl et al. (1996).

Statistical analysis

Generalized linear models (GLM) with binomial error distributions were applied to the proportion of females mature at each length and age, with geographic area and time period as factors. The geographic areas were the eastern Aleutian Islands (Seguam Pass) and the central Aleutian Islands (Tanaga Pass and Amchikta Island). In most cases, each year represents a separate time period; however, 1993 and 1994 data were combined into one time period for the central Aleutian Islands as was done by McDermott and Lowe (1997). We tested the significance of the GLM terms by using the chi-square (χ2) approximation test (Venables and Ripley 1997). The expected proportion of mature females at each length or age was determined by fitting the following logistic model to the observed data by using SPLUS (Insightful Corp., Seattle):

where Y = proportion mature at length or age x, α and β = parameters to be estimated, e = the base of natural logarithms, and x = fork length (cm) or age (years).

Estimating the effect of spatial growth differences on maturity at length

The A50 was obtained from the combined data for both study areas. Using separate growth parameters for each area, the lengths at A50 were estimated for each area by using the von Bertalanffy growth equation (von Bertalanffy 1938). The difference in these values was assumed to approximate the effect of spatial growth differences on maturity at length, and these values were compared with the lengths at 50% maturity (L50) estimated from the maturity data for each area. The von Bertalanffy growth parameters were obtained from Lowe et al. (2008) and were estimated independently with data from fishery observers.

Maturity-at-length modeling

A model was developed to determine the effect of population age composition on the maturity-at-length relationship (Table 2, Table 3). This approach was designed simply to evaluate the extent to which a variable population age structure affects the observed maturity at length (under the assumption that growth and maturity at age were constant). The growth rate and the population age composition estimates used were from the Atka mackerel stock assessment by Lowe et al. (2005). The mean and variance of lengths given ages were used to produce a transition matrix where expected population length frequencies could be computed given estimated population numbers at age. Similarly, applying a maturity-at-age schedule (as from Lowe et al. 2005), the proportion of mature fish at each centimeter length increment could be calculated.

Results

Postovulatory Follicles

Three stages of POFs were described (Table 4; Figure 2). Atka mackerel oocytes contain oil droplets, which appear as clear, spherical objects when stained with hematoxylin and eosin

(McDermott and Lowe 1997); these oil droplets persist in vitellogenic oocytes undergoing beta-stage atresia. Postovulatory follicles do not contain oil droplets and can therefore be distinguished from advanced atretic oocytes. All three POF stages were present in some females (Figure 1d), indicating that POFs persist for at least two intervals between spawning events. Based on a reported interval of 2–4 weeks between batch spawning events (Zolotov 1993), POFs are estimated to be present for at least 4 weeks after spawning.

Postovulatory follicles were present in only 70% of females with residual eggs in samples taken from the central Aleutian Islands in 2004, indicating that sampling occurred too long after spawning to use POFs for reliable determination of maturity; consequently, these data were excluded from the analysis. Aside from the 2004 central Aleutian Islands data, POFs were present in 94–100% of known mature females in both areas during all years (Table 5), and these data were used in the maturity analysis.

Spatial Variability in Maturity

Maturity at age did not significantly vary between the study areas (P = 0.40), and a model was fitted to the combined data from both areas (Table 6; Figure 3a). Maturity at age was estimated to be 3.47 years (Table 7). Maturity at length did vary significantly by area (P < 0.0001; Table 8; Figure 3b). The L50 was estimated at 34.9 cm in the eastern Aleutian Islands and 32.8 cm in the central Aleutian Islands (Table 7). These L50 values were similar to the L50 values estimated from the von Bertalanffy equation using a combined A50 for both areas and area-specific growth parameters (L50 of 35.2 cm for the eastern Aleutian Islands and 32.5 cm for the central Aleutian Islands), indicating that spatial growth differences are great enough to cause the observed spatial differences in maturity at length.

Temporal Differences in Maturity

Estimates of A50 ranged from 3.2 years in 2003 to 3.8 years in 2002; however, time period was not a statistically significant factor in maturity at age (P = 0.053; Table 6).

Length at 50% maturity varied significantly over time (P < 0.0001; Table 8); L50 was lowest in 2003 in both areas and was highest in 2002 (Figure 4).

Age Composition of Maturity Samples

The sampled Atka mackerel populations transitioned from immature to mature between 30 and 40 cm; in other words, females within this size range could be immature or mature. Females smaller than 30 cm were always immature, and females larger than 40 cm were almost always mature (Figure 3b). The age composition of 30–40-cm females varied with year-class strength (Figure 5). The relatively high percentage of age-3 fish collected in 2002 (Figure 5b) corresponded with the highest L50 values in both areas (Figure 4). In 2003, the relatively low percentage of age-3 fish (Figure 5c) corresponded with the lowest L50 values in both areas (Figure 4).

Length-at-Maturity Model

The model of the effect of year-class strength on maturity at length indicated that fluctuations in year-class strength can cause L50 to fluctuate over time by as much as 4 cm, even if age at maturity and growth remain constant (Figure 6).

Combined Effect of Length and Age on Maturity

To examine the combined effects of age and length on maturation, a logistic model was fitted to observed maturity-at-length data for age-3 females. The proportion of mature fish increased with length for age-3 females (Figure 7).

Discussion

Atka mackerel maturity can be assigned on the basis of POF presence after some females are spent. Such a finding is important for this species because some mature females cannot be distinguished from immature females until June or July, and the earliest-spawning females are spent in August. By taking advantage of an extended POF persistence time in ovaries, samples for maturity can be collected as late as October, although October was too late in the central Aleutian Islands in 2004. The ability to determine maturity based on POF presence is important for this relatively remotely located species with limited sampling opportunities, and it may be important for other similar species. Postovulatory follicle duration seems to be closely related to water temperature. Fitzhugh and Hettler (1995) observed that POF duration in Atlantic menhaden Brevoortia tyrannus increased from 1.5 to 5.0 d when water temperature decreased from 19–20°C to 15°C, and there may be a general relationship with temperature among species as well. Published reports of POF duration indicated negative relationships with temperature and positive relationships with latitude, which is presumably related to temperature (Table 9).

Atka mackerel maturity seems to be more dependent on fish age than on fish length. Maturity at age did not vary temporally or spatially, whereas maturity at length was both spatially and temporally variable. These data support the conclusions of McDermott and Lowe (1997) that maturity at age is spatially constant, whereas maturity at length varies spatially with differential growth patterns. We confirmed that spatial growth differences are great enough to cause the observed differences in maturity at length between Atka mackerel females in the central and eastern Aleutian Islands.

Examination of maturity at length for age-3 females (Figure 7) may explain why maturity seems fixed with age, even though life history theory predicts that both age and length at maturity should vary with growth changes (Stearns 1992). Although length did affect the probability of maturity, the observed spatial length differences caused only small changes in the proportion of mature age-3 females (0.08 is the expected fraction). It seems likely that the observed spatial and temporal growth differences would cause small differences in maturity at age, but the differences were probably too small to be detected by our methodology.

The Atka mackerel stock assessment assumes that maturity at age is temporally and spatially constant (Lowe et al. 2008). This assumption seems robust within the observed ranges of growth rates in this study. For this species, age is a better (i.e., less temporally and spatially variable) predictor of maturity than is length, and a fixed maturity-at-age estimate used for stock assessment will cause less error in spawning biomass estimates over time than a fixed maturity-at-length estimate. It seems that variation in Atka mackerel maturity at length is at least partly due to the relative age composition of the population. Females mature between 30 and 40 cm; depending on year-class strength, this length range could be dominated by either age-3 fish or age-4 fish. Because age-4 females are more likely to be mature than age-3 females, maturity at length shifts over time with changes in year-class strength caused by recruitment variability. For assessment purposes, it seems prudent to account for population maturity based on age. In many settings, length-based stock assessments assume that maturity is based on length independent of age (e.g., Thompson et al. 2007). Doing so for Atka mackerel would create bias in estimates of spawning stock biomass, which are critical for conservation and management recommendations. This is clearly a potential problem for similar species if similar length-based stock assessments are applied.

Acknowledgments

We thank Kimberly Rand and Sandi Neidetcher (Alaska Fisheries Science Center) for assistance with ovary collections, and we thank Martin Dorn (Alaska Fisheries Science Center) for discussions of the effects of length and age on maturity. Sandra Lowe, Dan Nichol, and Libby Logerwell (Alaska Fisheries Science Center) improved this article with thoughtful reviews. This study was partially funded by a grant from the North Pacific Research Board (Project Number 522).

References

1.

D. M. Anderl, A. Nishimura, and S. A. Lowe . 1996. Is the first annulus on the otolith of the Atka mackerel, Pleurogrammus monopterygius, missing? U.S. National Marine Fisheries Service Fishery Bulletin 94:163–169. Google Scholar

2.

S. Barot, M. Heino, L. O'Brien, and U. Dieckmann . 2004. Long-term trend in the maturation reaction norm of two cod stocks. Ecological Applications 14:1257–1271. Google Scholar

3.

W. A. Barr 1963. The endocrine control of the sexual cycle in the plaice, Pleuronectes platessa (L) I: cyclical changes in the normal ovary. General and Comparative Endocrinology 3:197–204. Google Scholar

4.

T. D. Beacham 1983. Variability in median size and age at sexual maturity of Atlantic cod, Gadus morhua, on the Scotian shelf in the northwest Atlantic Ocean. U.S. National Marine Fisheries Service Fishery Bulletin 81:303–321. Google Scholar

5.

W. R. Bowering 1989. Witch flounder distribution off southern Newfoundland, and changes in age, growth, and sexual maturity patterns with commercial exploitation. Transactions of the American Fisheries Society 1118:659–669. Google Scholar

6.

S. L. Brouwer and M. H. Griffiths . 2005. Reproductive biology of carpenter seabream (Argyrozona argyrozona) (Pisces: Sparidae) in a marine protected area. U.S. National Marine Fisheries Service Fishery Bulletin 103:258–269. Google Scholar

7.

Y. Chen and L. G. S. Mello . 1999. Growth and maturation of cod (Gadus morhua) of different year classes in the Northwest Atlantic, NAFO subdivision 3Ps. Fisheries Research 42:87–101. Google Scholar

8.

T. A. Clarke 1987. Fecundity and spawning frequency of the Hawaiian anchovy or nehu, Encrasicholina purpurea. U.S. National Marine Fisheries Service Fishery Bulletin 85:127–138. Google Scholar

9.

G. R. Fitzhugh and W. F. Hettler . 1995. Temperature influence on postovulatory follicle degeneration in Atlantic menhaden, Brevoortia tyrannus. U.S. National Marine Fisheries Service Fishery Bulletin 93:568–572. Google Scholar

10.

K. Ganias, S. Somarkis, A. Machias, and A. J. Theodorou . 2003. Evaluation of spawning frequency in a Mediterranean sardine population (Sardina pilchardus sardina). Marine Biology 142:1169–1179. Google Scholar

11.

S. R. Goldberg, V. H. Alarcon, and J. Alheit . 1984. Postovulatory follicle histology of the Pacific sardine, Sardinops sagax, from Peru. U.S. National Marine Fisheries Service Fishery Bulletin 82:443–445. Google Scholar

12.

T. Hamatsu, K. Yabuki, and K. Watanabe . 2004. Decadal changes in reproduction of walleye pollock (Theragra chalcogramma) off the Pacific coast of northern Japan. Fisheries Oceanography 13 (Supplement 1):74–83. Google Scholar

13.

J. R. Hunter and S. R. Goldberg . 1980. Spawning incidence and batch fecundity in northern anchovy, Engraulis mordax. U.S. National Marine Fisheries Service Fishery Bulletin 77:641–652. Google Scholar

14.

J. R. Hunter, B. J. Macewicz, N. C. Lo, and C. A. Kimbrell . 1992. Fecundity, spawning, and maturity of female Dover sole, Microstomus pacificus, with an evaluation of assumptions and precision. U.S. National Marine Fisheries Service Fishery Bulletin 90:101–128. Google Scholar

15.

J. R. Hunter, B. J. Macewicz, and J. R. Sibert . 1986. The spawning frequency of skipjack tuna, Katsuwonus pelamis, from the South Pacific. U.S. National Marine Fisheries Service Fishery Bulletin 84:895–903. Google Scholar

16.

P. A. Janssen, J. G. D. Lambert, and H. J. Goos . 1995. The annual ovarian cycle and the influence of pollution on vitellogenesis in the flounder, Pleuronectes flesus. Journal of Fish Biology 47:509–523. Google Scholar

17.

R. Lauth, S. McEntire, and H. Zenger . 2007. Geographic distribution, depth range, and description of Atka mackerel Pleurogrammus monopterygius nesting habits in Alaska. Alaska Fishery Research Bulletin 12 (2):165–186. Google Scholar

18.

S. Lowe, J. Ianelli, M. Wilkins, K. Aydin, R. Lauth, and I. Spies . 2008. Stock Assessment of Bering Sea/Aleutian Islands Atka Mackerel. Pages. 1119–1198. in. Stock assessment and fishery evaluation report for the groundfish resources of the Bering Sea/Aleutian Islands regions. North Pacific Fishery Management Council. Anchorage, Alaska. Google Scholar

19.

S. Lowe, J. Ianelli, H. Zenger, K. Aydin, and R. Lauth . 2005. Stock assessment of Bering Sea/Aleutian Islands Atka mackerel. Pages. 757–820. in. Stock assessment and fishery evaluation report for the groundfish resources of the Bering Sea/Aleutian Islands regions. North Pacific Fishery Management Council. Anchorage, Alaska. Google Scholar

20.

S. F. McDermott and S. A. Lowe . 1997. The reproductive cycle and sexual maturity of Atka mackerel, Pleurogrammus monopterygius, in Alaska waters. U.S. National Marine Fisheries Service Fishery Bulletin 95:321–333. Google Scholar

21.

S. F. McDermott, K. P. Maslenikov, and D. R. Gunderson . 2007. Annual fecundity, batch fecundity, and oocyte atresia of Atka mackerel (Pleurogrammus monopterygius) in Alaskan waters. U.S. National Marine Fisheries Service Fishery Bulletin 105:19–29. Google Scholar

22.

M. Morgan and E. B. Colbourne . 1999. Variation in maturity-at-age and size in three populations of American plaice. ICES Journal of Marine Science 56:673–688. Google Scholar

23.

Y. Narimatsu, D. Kitagawa, T. Hattori, and H. Onodera . 2005. Reproductive biology of female Rikuzen sole (Dexistes rikuzenius). U.S. National Marine Fisheries Service Fishery Bulletin 103:635–647. Google Scholar

24.

E. M. Olsen, M. Heino, G. R. Lilly, M. J. Morgan, J. Brattey, B. Ernande, and U. Dieckmann . 2004. Maturation trends indicative of rapid evolution preceded the collapse of northern cod. Nature (London) 428:932–935. Google Scholar

25.

M. Rochet 1998. Short-term effects of fishing on life history traits of fishes. ICES Journal of Marine Science 55:371–391. Google Scholar

26.

F. Saborido-Rey and S. Junquera . 1998. Histological assessment of variations in sexual maturity of cod (Gadus morhua L.) at the Flemish Cap (northwest Atlantic). ICES Journal of Marine Science 55:515–521. Google Scholar

27.

K. M. Schaefer 1996. Spawning time, frequency, and batch fecundity of yellowfin tuna, Thunnus albacares, near Clipperton Atoll in the eastern Pacific Ocean. U.S. National Marine Fisheries Service Fishery Bulletin 94:98–112. Google Scholar

28.

S. C. Stearns 1992. The evolution of life histories. Oxford University Press. New York. Google Scholar

29.

B. Stequert, F. Menard, and E. Marchal . 2003. Reproductive biology of Vinciguerria nimbaria in the equatorial waters of the eastern Atlantic Ocean. Journal of Fish Biology 62:1116–1136. Google Scholar

30.

G. Thompson, J. Ianelli, M. Dorn, D. Nichol, S. Gaichas, and K. Aydin . 2007. Assessment of the Pacific cod stock in the Eastern Bering Sea and Aleutian Islands area. Pages. 209–328. in. Stock assessment and fishery evaluation report for the groundfish resources of the Bering Sea/Aleutian Islands regions. North Pacific Fishery Management Council. Anchorage, Alaska. Google Scholar

31.

W. N. Venables and B. D. Ripley . 1997. Modern applied statistics with S-PLUS, 2nd edition. Springer-Verlag. New York. Google Scholar

32.

L. von Bertalanffy 1938. A quantitative theory of organic growth (inquiries on growth law, II). Human Biology 10:181–213. Google Scholar

33.

O. G. Zolotov 1993. Notes on the reproductive biology of Pleurogrammus monopterygius in Kamchatkan waters. Journal of Ichthyology 33 (4):25–37. Google Scholar

Figure 1.

Map of the study area, showing Atka mackerel female collection sites at Amchitka Island and Tanaga Pass (central Aleutian Islands [AI]) and Seguam Pass (eastern AI). National Marine Fisheries Service statistical area boundaries for the central and eastern AI are shown in green.

Figure 2.

Histological sections of Atka mackerel ovary, showing (a) an early stage postovulatory follicle (POF); (b) a middle-stage POF; (c) a late-stage POF; and (d) POFs of all three stages (scale bar = 1,000 μm; GR = granulosa; TH = theca; L = lumen).

Figure 3.

Female Atka mackerel (a) maturity at age and (b) maturity at length for all time periods combined in two Aleutian Islands (AI) areas (black diamonds = eastern area; blue triangles = central area). The solid black line in (a) represents generalized linear model (GLM) results for both areas combined. The dashed blue line and the solid black line in (b) represent GLM model results for the central AI and eastern AI, respectively.

Figure 4.

Expected maturity at length in 1993–1994 (red line), 2002 (solid black line), 2003 (blue line), and 2004 (dashed black line) for Atka mackerel females in (a) the eastern Aleutian Islands and (b) the central Aleutian Islands.

Figure 5.

Age composition of sampled female Atka mackerel within the fork length range (30–40 cm) encompassing the transition from immature to mature for the Aleutian Islands, Alaska, population: (a) 1993–1994, (b) 2002, (c) 2003, and (d) 2004.

Figure 6.

Model results describing the effect of Atka mackerel year-class strength on the proportion of mature females at length in 1984–2005.

Figure 7.

Proportion of age-3 female Atka mackerel that were mature at each length; data are from the central and eastern Aleutian Islands (AI) areas (all time periods combined). Data points are denoted by black diamonds, and the solid line represents a logistic regression fit to the data. Arrows indicate the mean lengths of females collected in the central and eastern AI; the delta symbol (Δ) represents the difference in proportion mature between these lengths.

Table 1.

Number of female Atka mackerel used in the maturity analysis by time period and Aleutian Islands (AI) area.

Table 2.

Schedule of female Atka mackerel mean fork length (cm) at age (La), standard deviation of length at age (σa), and maturity at age (ϕa) used for the model (from Lowe et al. 2005).

Table 3.

Equations used to generate the maturity at length shown in Figure 6a = standard deviation of length at age [La]).

Table 4.

Description of postovulatory follicle (POF) degeneration categories for Atka mackerel.

Table 5.

Number and percent of ovaries of known spent Atka mackerel females containing identifiable postovulatory follicles (POFs) by collection date and Aleutian Islands area (eastern or central).

Table 6.

Analysis of deviance from the generalized linear model of Atka mackerel female maturity at age for both Aleutian Islands areas and all time periods.

Table 7.

Maturity at length and maturity at age for female Atka mackerel in the eastern and central Aleutian Islands (AI) for all time periods combined (α, β = parameters from equation 1, sα = standard error of α, sβ = standard error of β, A50 = age [years] at 50% maturity, L50 = fork length [cm] at 50% maturity).

Table 8.

Analysis of deviance from the generalized linear model of Atka mackerel female maturity at length for both Aleutian Islands areas and all time periods.

Table 9.

Postovulatory follicle (POF) reported durations for various species in relation to latitude and temperature (temp).

Daniel W. Cooper, Susanne F. McDermott, and James N. Ianelli "Spatial and Temporal Variability in Atka Mackerel Female Maturity at Length and Age," Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 2010(2010), 329-338, (4 October 2010). https://doi.org/10.1577/C09-045.1
Received: 10 August 2009; Accepted: 16 October 2009; Published: 4 October 2010
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