Helgoland Marine Research

, Volume 69, Issue 3, pp 293–303 | Cite as

Interannual variations in the hatching pattern, larval growth and otolith size of a sand-dwelling fish from central Chile

  • Camilo Rodríguez-Valentino
  • Mauricio F. Landaeta
  • Gissella Castillo-Hidalgo
  • Claudia A. Bustos
  • Guido Plaza
  • F. Patricio Ojeda
Original Article

Abstract

The interannual variation (2010–2013) of larval abundance, growth and hatching patterns of the Chilean sand stargazer Sindoscopus australis (Pisces: Dactyloscopidae) was investigated through otolith microstructure analysis from samples collected nearshore (<500 m from shore) during austral late winter-early spring off El Quisco bay, central Chile. In the studied period, the abundance of larval stages in the plankton samples varied from 2.2 to 259.3 ind. 1000 m−3; larval abundance was similar between 2010 and 2011, and between 2012 and 2013, but increased significantly from 2011 to 2012. The estimated growth rates increased twice, from 0.09 to 0.21 mm day−1, between 2011 and 2013. Additionally, otolith size (radius, perimeter and area), related to body length of larvae, significantly decreased from 2010 to 2012, but increases significantly in 2013. Although the mean values of microincrement widths of sagitta otoliths were similar between 2010 and 2011 (around 0.6–0.7 μm), the interindividual variability increases in 2011 and 2013, suggesting large environmental variability experienced by larvae during these years. Finally, the hatching pattern of S. australis changed significantly from semi-lunar to lunar cycle after 2012.

Keywords

Sagitta Chile Ichthyoplankton Dactyloscopidae 

Introduction

Several species of marine fish exhibit beach-spawning behaviour, including some silversides (Atherinopsidae), certain killifish (Fundulidae), a puffer (Tetraodontidae), a few smelts (Osmeridae) and a stickleback (Gasterosteidae). Placement of eggs at higher levels in the intertidal zone seems to be a risky behaviour, but it has numerous advantages, including increased incubation temperatures, increased oxygen availability and reduced aquatic predation (Martin and Swiderski 2001). In these species, hatching may be negatively correlated with the onshore wind-induced wave action which disturbed the beach (Frank and Leggett 1981; Griem and Martin 2000). On the other hand, several species that laid eggs in subtidal sand or rocky bottom show lunar or semi-lunar spawning cycles (Hay 1990; Contreras et al. 2013; Palacios-Fuentes et al. 2014). This tendency is assumed to be related to the timing of larval hatching: benthic eggs have considerably narrow diel hatching windows, and those windows coincide with tides (i.e. during neap and/or spring tides) that are appropriate for dispersal by the strongest tidal currents only during 2 short periods in each lunar month (Yamahira 1997).

A group of fishes that inhabits sandy nearshore or estuarine environments in warm temperate to tropical waters from North and South America are the sand stargazers of the family Dactyloscopidae (Dawson 1982; Doyle 1998). This family is composed of 9 genera, with 48 species that present elongated bodies, eyes on top of the head and cryptic coloration (Hastings and Springer 2009). They frequently bury themselves in sand bottoms, similar to some trachinoids, with only the mouth and eyes exposed, making it very difficult to detect them visually, since their coloration is very similar to that of the adjacent background (Wagner et al. 1976). However, unlike virtually all other teleosts, which normally pump water over the gills by alternately expanding and contracting the buccal and opercular cavities, they have evolved a branchiostegal pump that replaces the opercular pump. Fingerlike labial and opercular fimbriae probably function to prevent particles from clogging the branchial chamber (Nelson 2006).

Sand stargazers exhibit internal fertilization as males of most species have copulatory structures derived from anterior anal fin rays. They are oviparous, laying eggs of approximately 1 mm in diameter attached to each other by filaments; they have parental care, and most males carry and incubate the eggs (Watson 1996; Teixeira et al. 2013). In the latter case, eggs are held in place between the large pectoral fins and the recurved spines in the anterior anal fin of males. Little else is known of this behaviour including how eggs are transferred from the female to the male, the number of eggs and number of clutches that are carried by males and consequently how many females mate with single males (Hastings and Petersen 2010). Hatching seems to occur around 4 mm in the species from the Gulf of California and the California region (Brogan 1992; Watson 1996) and from the Humboldt current (Herrera et al. 2007), and less than 3.6 mm in the species from Belize, Central America (Cavalluzzi 1997).

The members of the family Dactyloscopidae have worldwide distribution, being the southernmost distribution in the Pacific Ocean is the Chilean sand stargazer Sindoscopus australis (Fowler and Bean 1923). It is the only Dactyloscopid that inhabit cold temperate waters and is known only from coastal waters of Chile at depths of 2 m or less about 23°–36°S (Dawson 1977). Larvae are pelagic occurring in nearshore waters, and undergo notochord flexion at larger sizes compared to those of other Dactyloscopids, between 8 and 9 versus 6 mm of body length (Watson 1996; Herrera et al. 2007). Also, transformation (i.e. migration of eyes to the upper position of the head) occurs at larger sizes (Herrera et al. 2007), suggesting large pelagic duration of S. australis in relation to other Dactyloscopids; however, there is no previous information about this subject for any Dactyloscopid fish, nor about growth rates and/or hatch dates.

A useful tool to reveal early life history traits of marine fishes is through otolith microstructure analysis, because otoliths record not only age and growth patterns, but also hatching times, settlement, metamorphosis, migration and condition (Victor 1987; Folkvord et al. 1997; Landaeta et al. 2012; Plaza et al. 2013; Zenteno et al. 2014). Through diel variations in calcium and protein deposition, bipartite structures known as daily growth increments often form at microstructural level of the otolith (Campana 1984). Also, the correlation between otolith size and somatic size enables growth trajectories and histories to be back-calculated (Campana 1990; Takasuka et al. 2008).

The aim of this study was to estimate larval age and growth rates, as well as hatch date patterns of the Chilean sand stargazer (S. australis). For these purposes, the morphometrics and microstructure analysis of sagitta otoliths of S. australis were carried out throughout larval development on an interannual basis in nearshore waters of central Chile. The daily periodicity of the growth increments for S. australis has not been validated, nor for any Dactyloscopidae; however, several species of the suborder Blennioidei has been validated for daily periodicity in coastal waters of central Chile and elsewhere (Hernández-Miranda et al. 2009; Kohn and Clements 2011; Mansur et al. 2013).

Materials and methods

Fieldwork

During the late austral winter and spring of 2010, 2011, 2012 and 2013 nearshore (<500 m offshore), night-time surveys were conducted at El Quisco Bay (EQB, 33°24′S, 71°43′W), central Chile, on board of an artisanal vessel. Two hundred and sixty-four oblique hauls of a Bongo net (60 cm diameter, 300 μm mesh size) with one TSK flowmeter mounted in the frame of the net were performed for 15–20 min from a depth of 20 m (Table 1). Seawater filtered by the net ranged from 13.3 to 437.4 m3 (mean ± one standard deviation: 141.2 ± 102.5 m3). Subsequently, the nets were washed on board, and all zooplankton samples (n = 352) were initially fixed with 5 % formalin buffered with sodium borate and preserved in 96 % ethanol after 12 h. This procedure has no effect on the microstructure of the otolith (Palacios-Fuentes et al. 2012, 2014; Contreras et al. 2013).
Table 1

Summary of dates, sampling effort, number of hauls with positive presence of larval Sindoscopus australis and larval abundance (ind. 1000 m−3) for all the study period, 2010–2013

Date

No. of hauls

No. of positive hauls

Total abundance

02/09/2010

12

1

5.06

09/09/2010

10

10

445.22

04/10/2010

16

8

83.93

08/09/2011

15

5

170.94

15/09/2011

16

12

63.90

18/10/2011

9

4

72.31

18/11/2011

16

0

23/11/2011

16

0

08/10/2012

16

8

393.71

13/11/2012

16

3

86.09

27/11/2012

16

4

84.95

05/12/2012

16

1

9.51

11/12/2012

16

2

39.35

24/10/2013

16

13

1116.65

28/11/2013

12

7

271.51

05/12/2013

15

8

502.61

12/12/2013

15

7

184.56

17/12/2013

16

4

63.27

Laboratory work

In the laboratory, all larval fish were separated, counted and identified into the lowest possible taxon. Sand stargazer larvae, S. australis, were identified on the basis of the criteria described by Herrera et al. (2007) (Fig. 1a), i.e. the absence of dorsal cephalic pigmentation and short and compact gut with short preanal distance, and separated into pre- and post-flexion stages (flexion and post-flexion were pooled together). Larval abundance was standardized to individuals (ind.) 1000 m−3 utilizing the flowmeter counts. The body length (BL), which corresponded to the notochord length (from the tip of the snout to the tip of the notochord in pre-flexion larvae) or the standard length (from the tip of the snout to the base of the hypural bones in flexion and post-flexion larvae), was measured to the nearest 0.01 mm under an Olympus SZ-61 stereomicroscope with a Moticam 2500 (5.0 M Pixel) video camera connected to a PC with the Moticam Image Plus 2.0 software. The larval measurements were not corrected for shrinkage.
Fig. 1

a Larval stage of the sand stargazer Sindoscopus australis; b, c sagitta otolith of the larva, indicating nucleus (N), hatch mark (HM) and microincrements (MI)

The left and right sagitta otoliths were removed from well-preserved 174 larvae (3.93–18.21 mm SL) (Fig. 1b, c). The otoliths were embedded in epoxy resin on a glass slide. The daily age was estimated by counting the number of otolith increments with a Motic BA310 light microscope at 1000× magnification under oil immersion. The longest radius of a sagitta was measured three times, and the average was used. The perimeters and areas of the otoliths were then measured once using the Moticam Image Plus 2.0 software.

Three independent counts were performed on both the right and left sagittae. The counts were performed after a prominent hatch mark (HM, Fig. 1b). When the coefficient of variation (CV = standard deviation/mean × 100) of the increment counts among the three readings was <10 %, the arithmetic mean of the three counts was calculated and utilized for the analysis. When the CV was >10 %, the otolith reading was discarded (n2010 = 2; n2011 = 4; n2012 = 5; n2013 = 1). Once selection of the values was done, comparison of readings was carried out with a Wilcoxon matched-pairs test, testing the hypothesis that reading of the left sagitta is the same that right sagitta. Because null hypothesis of the same lecture in both otoliths cannot be rejected (W = 71.5; P = 0.512), we assume that both otoliths can be utilized for analyses.

Microincrement widths were measured for the older/larger individuals from each sampling year. For these individuals, each microincrement was measured three times and the average was utilized for further analysis.

Data analysis

Larval abundance was compared among years with nonparametric tests (Kruskal–Wallis H test) because the data departed for a normal distribution (Shapiro–Wilk test, W = 0.682, P < 0.001). Post hoc comparisons were made with mean ranks for all groups.

Least-squares linear regression analyses were performed between the sagittae morphometry (radius and perimeter) and body length, and exponential models were fitted between the sagitta area and larval length. Linear models among years (2010–2013) were compared with a one-way ANCOVA and multiple slope test (Zar 1999). For comparisons of the relationship between otolith area and larval length among years, data were ln-transformed, and then, linear regression models were fitted. Additionally, linear regressions between the microincrement counts (age) and larval lengths were adjusted. In this case, the slope corresponded to the population growth rate, and the intercept corresponded to the estimated hatch size. To compare the population growth rate during 2010–2013, the slopes were compared with one-way ANCOVA (Zar 1999), utilizing the same size range for all years (from 4.76 to 17.38 mm BL).

Comparisons in the microincrement width (MIW) between individuals and among days were carried out with repeated-measures ANOVA (RM ANOVA). The analysis was a mixed two-factor design, with year as an independent factor and increment width at the third, 10th, 20th and 40th days as a repeated levels (n = 14 for 40th day; for the rest, n = 20). All RM ANOVAs were achieved on balanced set of levels over age.

The hatching days were back-calculated and related to the lunar cycle. In order to compare distribution patterns, hatch day frequencies for each year (2010–2013) were converted to Julian days and then converted to angles (°) by dividing by 365 and then multiplying by 360° so that the data could be analysed using circular statistics. Similarly, for each sampling date, the days since the new moon were counted (DNM), and thereby assigned DNM values from 0 to 29 for each date, in which 0 represented the new moon. The DNM values were converted to angles (°) by dividing by 29 (the length, in days, of the lunar cycle) and then multiplying by 360°. To assess whether the hatching events showed lunar periodicity, the data were analysed using the Rao’s spacing test (Batschelet 1981). The Rao’s spacing test is more powerful and robust than many other circular goodness-of-fit tests and is able to analyse bi- and multimodal distributions, whereas other tests cannot, such as the Rayleigh test and Watson’s U2 (Bergin 1991). The Rao’s spacing test is robust even for small sample sizes but also shows a low frequency of type I errors when analysing data that display no pattern. The null hypothesis that the hatching events would be equally or randomly spaced throughout the lunar cycle was tested for each data set. Finally, comparisons between the annual and lunar hatching distributions among years were conducted using the nonparametric Mardia–Watson–Wheeler test (W) for equal distributions (Mardia 1972).

Results

Temporal variability of larval abundance

The abundance of larval stages of sand stargazer in the plankton samples collected in nearshore waters (<30 m depth) varied from 2.2 to 259.3 ind. 1000 m−3 (mean ± standard deviation, median; 37.1 ± 46.6 ind. 1000 m−3, 20.1 ind. 1000 m−3) (Table 1). At interannual scale, larval abundance of S. australis varied significantly among years off El Quisco Bay (Kruskal–Wallis test, H = 22.78, P < 0.001). Larval abundance was similar between 2010 and 2011, and between 2012 and 2013, but increased significantly from 2011 to 2012 (P = 0.001) (Fig. 2).
Fig. 2

Interannual variation in the abundance (ind. 1000 m−3) of larval Sindoscopus australis during 2010–2013, indicating median, quartiles and min–max values

Otolith morphometry and its interannual variation

Morphometric measurements of sagitta otoliths during the larval development of sand stargazer showed significant relationships with the body length (Table 2; Fig. 3). These patterns strongly suggest that sagitta otolith can be a good proxy of growth of larval length. Nonetheless, these relationships varied at interannual scale (Figs. 3, 4). All three parameters, radius, perimeter and area, decreased significantly from 2010 to 2012, and then, they increased significantly in 2013 (one-way ANCOVA, radius: F = 36.84, P = 1.07 × 10−8; perimeter: F = 47.63, P = 7.9 × 10−23; ln area: F = 38.57, P = 5.45 × 10−19, Fig. 4). Therefore, sagitta otoliths of larval S. australis showed a decreasing trend from 2010 to 2012, and then, they increase its size during 2013.
Table 2

Linear regression models between body length (BL, mm) and sagitta otolith size parameters

Year

Model

α

SE

β

SE

R2

F

2010

R versus BL

−5.99

2.24

8.07

0.33

0.907

587.65

 

P versus BL

−27.91

12.96

45.33

1.91

0.902

557.83

 

ln A versus BL

6.65

0.12

0.27

0.01

0.786

220.88

2011

R versus BL

23.07

7.03

4.66

0.92

0.401

25.53

 

P versus BL

134.91

36.55

26.76

4.79

0.451

31.21

 

ln A versus BL

7.83

0.21

0.15

0.02

0.451

31.21

2012

R versus BL

−3.65

4.29

5.44

0.37

0.858

211.55

 

P versus BL

10.36

20.11

27.96

1.75

0.878

254.24

 

ln A versus BL

6.87

0.11

0.17

0.01

0.911

362.28

2013

R versus BL

−8.16

7.94

8.14

0.65

0.764

155.64

 

P versus BL

−12.94

38.07

43.55

3.12

0.801

193.73

 

ln A versus BL

7.73

0.18

0.17

0.01

0.727

127.93

R radius (μm), P perimeter (μm), ln A natural logarithm of the area, SE standard error. All models were statistically significant at P < 0.001

Fig. 3

Interannual variation in morphometric relationships (radius, perimeter and area) of sagitta otoliths and larval length during 2010–2013. Lines indicate linear regression models, and dotted lines correspond to 95 % confidence intervals

Fig. 4

Comparison of adjusted mean size (radius, perimeter and area) of sagittal otoliths from larval Sindoscopus australis collected at El Quisco Bay, central Chile, during 2010–2013

Interannual variability in larval growth rates

Linear regression models estimated growth rates between 0.095 and 0.214 mm day−1, from the 2011 and 2013 cohorts, respectively (Fig. 5; Table 3). One-way ANCOVA for the same size range (4.76–17.38 mm BL) detected significant differences in the size-at-age among years (one-way ANCOVA, F = 36.44, P = 1.01 × 10−17) as well as differences in the growth rates among years (homogeneity of slopes, F = 9.71, P = 6.96 × 10−6). Nonetheless, no significant differences were detected in the size-at-age (F = 0.212, P = 0.646) or growth rates (F = 3.412, P = 0.068) between 2010 and 2011 cohorts, and in growth rates between 2012 and 2013 cohorts (F = 1.103, P = 0.297). Then, between 2011 and 2012 occurred a significant increase in the growth rate of larval S. australis (F = 12.85, P = 0.0006), but also the size-at-age increased as well (F = 58.43, P = 8.25 × 10−11).
Fig. 5

Linear regression models of relationships between body length and microincrement counts (age) for larval Sindoscopus australis collected during 2010–2013

Table 3

Linear regression models between microincrement counts (age, in days) and body length (mm)

Year

N

Hatch size (mm)

SE

Growth rate (mm day−1)

SE

R2

F

2010

47

3.267

0.283

0.127

0.008

0.837

232.53

2011

40

4.084

0.658

0.095

0.017

0.431

28.73

2012

34

4.251

0.802

0.191

0.020

0.737

90.11

2013

41

2.259

0.835

0.214

0.016

0.805

161.57

SE standard error. All models were statistically significant at P < 0.001

Microincrement width variations

Microincrement widths (MIW) were very narrow, varying from 0.440 to 0.987 μm, in individuals up to 81 days old. During 2013, nonetheless, the range of the MIW increased between 0.480 and 2.25 μm (Fig. 6). During 2010 and 2011, larvae have a similar trend in the MIW throughout the early development, but in 2011 there was a larger interindividual variability (Fig. 6). During the study period, MI showed a similar width up to 30–35 days old (around 0.6–0.7 μm). After this period, MIW increased smoothly all years, but being more steep in 2013 (Fig. 6). MIW was compared across years using a repeated-measures ANOVA. This analysis did not detect significant differences in MIW over age across years (Wilks’ Lambda 12,35P = 0.844).
Fig. 6

Average (and one SD) of microincrement widths of sagitta otoliths from individuals collected during 2010–2013 off central Chile

Hatch date distributions

Hatch date distributions among years were similar, but not the same for the studied period (Fig. 7). During 2010, hatch distributed between 06 July and 24 September; in 2011, hatching occurred from 09 July to 18 September; in 2012, hatching days were between 10 August and 21 November; finally, in 2013, hatching period occurred from 04 August to 7 October (Fig. 7). Circular statistics showed similar hatching period during 2010–2011 (W = 0.07, P = 0.963), but they differ significantly among other years. Although almost the 70 % of the larvae from 2012 hatched in a similar period than those from the other years, distributions were different (Table 4).
Fig. 7

Back-calculated hatch day distribution of sand stargazer Sindoscopus australis on an annual basis, 2010–2013

Table 4

Summary of statistic results (W, Mardia–Watson–Wheeler test for equal distribution) of comparison of the hatching day distributions of Sindoscopus australis during 2010–2013 off central Chile

 

2010

2011

2012

2010

2011

0.074 (0.963)

2012

11.837 (0.002)

15.814 (<0.001)

2013

28.847 (<0.001)

25.180 (<0.001)

9.651 (0.008)

In parenthesis, the P value is indicated; bold numbers indicate significant differences (significance at 0.05)

Hatch date distributions in the lunar cycle of S. australis departed for uniformity during most years (2010: Rao’s U = 164.3, P = 0.006; 2011: Rao’s U = 166.2, P = 0.009; 2013: Rao’s U = 189, P = 0). During 2010, the most frequent hatch days occurred during full moon (15.2 %) and last quarter (17.4 %) (Fig. 8); during 2011, the largest frequencies of hatching occurred during first (12.8 %) and last quarter moon (17.9 %) (Fig. 8); therefore, during 2010 and 2011, S. australis showed a semi-lunar hatch pattern. During 2012, S. australis hatched with no directionality in the lunar month (Rao’s U = 109.1, P = 0.908). Finally, during 2013, hatch days were more frequent around new moon (22.5 %, lunar hatch pattern, Fig. 8). The Mardia–Watson–Wheeler test for equal distribution showed significant differences in the hatching pattern between 2010 and 2013 (W = 6.403, P = 0.041), and between 2011 and 2013 (W = 6.642, P = 0.036). Therefore, the hatching pattern of S. australis varied significantly after 2012, changing from semi-lunar to lunar (new moon) pattern.
Fig. 8

Back-calculated hatch day distribution of sand stargazer Sindoscopus australis on a lunar cycle, 2010–2013

Discussion

The early life traits of the sand stargazer S. australis, namely hatch patterns, larval abundance and growth rates, showed large variability at interannual scale off central Chile. During 2010–2011, sand stargazer showed a semi-lunar hatching pattern, slow larval growth rates and low larval abundance. The following year 2012, larval hatch occurred uniformly throughout the lunar month, and the larval abundance and its growth increased twofold, but it sagitta otoliths were the smallest of the time series. Finally, in 2013, hatch patterns changed to a lunar cycle with its peak near new moon (i.e. spring tides), the otolith increased it size (radius, perimeter and area), as well as the larval growth rates.

During this study, larval abundances were estimated for the upper 30 m depth of the water column during night sampling in nearshore waters. Larval sand stargazers are scarcely or completely absent in deeper waters of the shelf and slope off central Chile (Landaeta et al. 2008), but they are collected in low abundance during daytime off central Chile (7.96 ± 4.97 ind. 1000 m−3, Landaeta et al. unpublished results). Therefore, it is plausible that night sampling in nearshore waters may be a good predictor of larval S. australis abundance.

Semi-lunar and lunar hatching patterns have been recently described for other criptobenthic marine fishes from central Chile, such as clingfishes (Gobiesox marmoratus, Sicyases sanguineus, Contreras et al. 2013) and Chilean triplefin blennies (Helcogrammoides chilensis, Palacios-Fuentes et al. 2014). A hatching pattern related to first and/or last quarter moon (estimated for 2010 and 2011 for S. australis) is associated with neap tides, which implicate the reduced effects of tidal export from coastal waters to offshore (Robertson et al. 1990). Later, during 2013, the hatching pattern was more frequent near new moon, i.e. during spring tides, which may increase dispersion and population connectivity. This different temporal hatching pattern may be forced by some environmental stress. Similarly, interannual variations in the hatching pattern during the lunar month have been described in rockfish from Japan, which hatch around the new and full moon (Plaza et al. 2003).

Large variations in the estimated larval growth rates as well as larval density occurred among years. This result may be due to differences in the back-calculated hatch distribution, around winter in 2010 and 2011, and during late winter-early spring 2012 and 2013, which can trigger differences in the main growth controllers (i.e. temperature and productivity). Because all years the sampling design was the same (oblique tows from 20 m depth to surface), interannual variations in larval density may obey to a combination of differences in larval survival and meteorological/oceanographic forcing. At El Quisco bay, it occurs an increase in seawater temperature and chlorophyll concentration in subsurface waters from austral winter to spring (Hernández-Miranda et al. 2003), which may partially explain the detected differences between 2011 (large otoliths, slow growth) and 2012 (small otoliths, fast growth), but it does not explain differences in larval traits from individuals hatched during 2012 and 2013 (large otoliths, fast growth).

Uncoupling between otolith and somatic growth rates may occur (Hare and Cowen 1995). The effects of somatic growth rates on the otolith and somatic size relationships (the ‘growth effect’), if it exists, could be a possible source of bias in the back-calculation and somatic size estimation procedures (Takasuka et al. 2008). Also, slow-growing fish tend to have larger otoliths than fast-growing ones of the same length (Wright et al. 1990; Francis et al. 1993). On the other hand, Munk (1993), Folkvord et al. (2000) found no differences in the otolith size–fish size relationship estimated for larvae characterized by different growth rates. Fey (2001) suggested that in hyperoptimal temperatures or conditions of significant temperature fluctuations, otolith growth and increment widths are related more closely to temperature-affected metabolic rate than to somatic growth. Then, during the studied period, it could be occurred a period with uncoupled growth of otolith and soma in larval S. australis (2010–2011) and a period of coupling between otolith and somatic growth during 2012 and 2013.

The estimated larval growth rates (0.09–0.21 mm day−1) were similar to those estimated for other nearshore benthic fishes from central Chile such as clingfishes Gobiesox marmoratus (0.24 mm day−1) and Sicyases sanguineus (0.14 mm day−1, Contreras et al. 2013) and triplefin blennies (0.14–0.16 mm day−1, Palacios-Fuentes et al. 2014). Hence, it has been accumulating evidences that slow larval growth seems to be a generalized process for littoral fishes in the south-eastern Pacific Ocean, an ecosystem that is characterized by low temperatures associated with the cold-water Humbold Current System (HCS) but also characterized by a high productivity due the occurrence of upwelling events. Hence, it is reasonable to hypothesize that small variations in any of growth controllers would trigger great variations in growth rates in these fishes, triggering great changes in survival as well, such as it has been suggested for a number of studies for teleost marine fishes (Shepherd and Cushing 1980; Chambers and Leggett 1987; Miller et al. 1988; Leggett and DeBlois 1994; Takasuka et al. 2003; Hawn et al. 2005; Plaza and Ishida 2008). In the case of Chilean sand stargazer (S. australis), the higher growth rates particularly in 2012 and 2013 matched with the higher abundances. A similar pattern was detected in demersal and pelagic fish species from the Barents Sea (cod, haddock and herring, Ottersen and Loeng 2000), in Japanese mackerel (Scomberemorus niphonius) larvae in the Seto Inland Sea, Japan (Shoji and Tanaka 2003), and the sablefish off Oregon affected by extreme El Niño and La Niña events (Sogard 2011).

Natural hypoxic events may affect population dynamics of nearshore fishes in coastal waters of Chile, as it has been detected in toadfish Aphos porosus (Hernández-Miranda et al. 2012a). An intense event of natural hypoxia in January 2008 affected the entire resident community of shallow Coliumo Bay, causing widespread mortality of organisms and a mass stranding event, with fish being one of the most affected groups (Hernández-Miranda et al. 2010, 2012b). These authors reported a recovery in richness of the fish assemblage in a timescale of only 3 months; nevertheless, densities reached only about half their previous level after 2 years of the event. At a longer timescale, negative effects on the total density of the fish assemblage, including A. porosus, were also detected (Hernández-Miranda et al. 2012a), similarly to the reduction in larval abundance of the sand stargazer observed from 2010 to 2012.

Therefore, such event may have modified the population parameters of the sand-dwelling fish S. australis in central Chile, reducing its larval supply (i.e. density). Nonetheless, the sand stargazer showed a relatively rapid recovery after 3 years, increasing twice its larval growth, its otolith size and changing the hatching patterns in the lunar cycle.

Notes

Acknowledgments

We thank the field work of J.E. Contreras, F. Salas-Berríos, M.J. Ochoa-Muñoz, P. Palacios-Fuentes, C. González-Erazo and Dr. Randy Finke. Two anonymous reviewers improved with their comments and suggestions an early version of the ms. This research was funded by project Fondecyt Grant No 1100424, adjudicated to FPO, GP and MFL.

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Copyright information

© Springer-Verlag Berlin Heidelberg and AWI 2015

Authors and Affiliations

  • Camilo Rodríguez-Valentino
    • 1
  • Mauricio F. Landaeta
    • 1
  • Gissella Castillo-Hidalgo
    • 1
  • Claudia A. Bustos
    • 1
  • Guido Plaza
    • 2
  • F. Patricio Ojeda
    • 3
  1. 1.Laboratorio de Ictioplancton (LABITI), Facultad de Ciencias del Mar y de Recursos NaturalesUniversidad de ValparaísoViña del MarChile
  2. 2.Laboratorio de Esclerocronología, Escuela de Ciencias del MarPontificia Universidad Católica de ValparaísoValparaisoChile
  3. 3.Departamento de Ecología, Facultad de Ciencias BiológicasPontificia Universidad Católica de ChileSantiagoChile

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