Age and Growth
Age and growth were assessed by three approaches; direct measurement of growth in confinement by continuous monitoring, modal progression analysis of length frequency data (LFD) of fishes caught in commercial fishing and interpretation of microstructures on otoliths.
The oil sardines reared in open sea cages on natural food, exhibited almost uniform growth throughout the period and attained 166 mm size (TL) in 275 days (Table 1; Fig. 1). Size of the juveniles at start of the trial was 74-77 mm with mean size of 75 mm, indicating all from a single brood. Considering 3 mm as size of the oil sardine larvae at hatching (Nair 1959), interpretation of growth curve developed by growth data from the rearing trial, juveniles were two-plus month old at the start of trial. This suggested a total growth of 163 mm in 11 months under captive condition. The growth obtained in the rearing trial is much higher, compared to earlier reports of 100-160 mm growth in a year in natural condition (Hornell and Nayudu, 1924; Balan 1964; Antony Raja 1969;1970; Annigeri et al. 1992; Yohannan 1998; Nair et al. 2016).
Modal progression analysis
Growth parameters for age and growth estimations were derived from length frequency data of the species by modal progression analysis. The von Bertalanffy growth curve fitted from these parameters provided a growth of 193 mm TL at the end of first years (Table 2, 3, Fig. 2). This growth is much higher compared to 166 mm in 11 months obtained in the present rearing trial and the growth ranges of 100-175 mm in one year reported by earlier researchers (Hornell and Nayudu 1924; Balan 1964; Antony Raja 1969; 1970; Annigeri et al. 1992; Yohannan 1998; Rohit and Bhat 2003; Nair et al. 2016) but is comparable to the growth reported for the species by Rohit et al., 2018. In Oman waters, they are reported to attain 191 mm TL at the end of one year and 222 mm by second year (Jayabalan et al. 2014), which is almost same as the present estimate. The wide variation in the growth estimates by different researchers could be attributed to the individual bias in sampling, the complexities in the size frequency data used for analysis owing to their continuous spawning and recruitment in to the fishery and the estimation procedures employed. Partly it can be attributed to the variation in habitat environment, especially sea surface temperature (SST) which persists along the regions where study was undertaken as opined by Ganga and Pillai (2006).
Hard part analysis
The microstructures on hard parts appear as alternate dark and light bands under microscope in transmitted light (Fig. 3). Diurnal variations in growth of the animals are expected to produce similar variations in growth of hard part also and which appears as dark and light bands due to differential rates of minerals deposits. For ease of enumeration, generally dark bands were considered as daily rings. Campana and Nelson (1985) described the impact of day/night cycles on the growth of the fishes and its resultant impact on hard parts as formation of growth rings. Al-Anbouri et al. (2011) also considered such microstructures on hard parts as daily rings, while ageing IOS from Oman waters. In the present study microstructure formation over time on hard parts viz, scales, vertebrae and sagittal otoliths of fishes reared in cages were monitored regularly. Their increment was more frequent in scales and otoliths, whereas, it is very rare or in most cases no increments were observed on vertebrae (Table 1). Though microstructure formation on scales were more frequent during initial periods of growth, did not follow any definite time scale and that it almost ceases to form after certain period. However, their formation on sagittal otoliths were regular at one dark and light band a day throughout the period of growth, irrespective of size, sex and age of the fish. The uniformity of microstructure formation on otoliths established their suitability for age determination to day’s precision and were considered most reliable. So, otoliths alone were used for further studies. A variety of hard parts were in use across the globe for age and growth studies in fishes (Green et al. 2009; Abdussamad et al. 2019). Sardine (Sardinella Spp.) ageing in India and other areas were attempted by earlier researchers using otoliths (Nair 1949; Al-Anbouri et al. 2011; Dehghani et al. 2015) and scales (Balan 1959; 1964). Though types of hard parts were tested for their reliability in age determination of oil sardine except otolith, others were found extremely unreliable as microstructure formation on them are highly inconsistent.
Age determination of wild population
The microstructures on otoliths from wild caught fishes covering all size groups were analysed for the period and converted to length at age data. The plots and growth curve derived from the pooled age length data for the periods produced two distinct clusters and growth curves (Fig 4). The higher cluster and the corresponding growth curve indicate faster growth and the lower one indicates slow growth. Those constructed separately for males and females, however produced almost identical plots and curves for both sexes as of unsorted sample and thus rejected the hypothesis on operation of sexual divergence in growth in the species. The plots and curves for annually segregated age at length data produced higher cluster for the period 2011-13 and lower cluster for 2014-17. This suggested operation of temporal growth variation in the species with normal growth during 2011-13 and slow growth during 2014-2017 (Table 4). Same magnitude of temporal growth variation was also evident for both males and females.
The growth curve for 2011-13 is almost identical as that from modal progression analysis for entire the period (Table 3, Fig. 4). However, the former shows much faster growth, 154, 201 and 221mm respectively at the end of 6, 12, and 18 months compared to 144, 193 and 216 mm of latter. The estimate of annual growth constant (K) was larger (1.76 year-1) for the growth curve based on hard part analysis when compared with 1.57 year-1 from modal progression analysis. This indicated much higher growth potential in the species, which is not discernible from the routine modal progression analysis. The underestimates in the modal progression analysis can be attributed to the interference by different modes representing multiple cohorts in the population selectivity of the fishing gear and sampling bias.
A perusal of environmental and oceanographic dynamics exhibited wide inter-annual fluctuations in magnitude and pattern of major parameters during the period. The SST of the coastal waters varied between 27.8 and 28.7oC (Fig. 6). The coastal waters were relatively cooler with small SST during 2011-13, which gradually increased thereafter and remained warmer during rest of the period. Likewise, ONI was small during 2011-13 and high during the latter period. They were subjected to detailed statistical interpretation to assess the influence of ecological parameters on the temporal growth variation in the species. The prominent variables, viz. sea surface temperature (SST), dissolved oxygen (DO), chlorophyll-a (Chl-a) coastal currents (CC), upwelling and El Niño southern oscillation (ENSO) and also the biomass of the species were tested for significance, which throws light on their interaction on growth (Fig. 5). SST and ONI exerted significant (P<0.05), but inverse impacts on growth. The inverse relationship observed in the analysis indicates small values of SST and ONI favored good growth, whereas large values have adverse impacts. The positive correlation between the growth and biomass (P<0.01) is a natural indication of prevalence of ideal condition for growth always ensure successful recruitment and large biomass. Since the small SST and ONI values linked to La Nina and larger values with El Nino phases of ENSO, it can be concluded that it may the ENSO induced environmental modifications that produce growth variation in the species.
Antony Raja (1970) reported growth variation in the species during 1961-65 and attributed it to population density. However, the alternating phases of El Nino and La Nina that prevailed during the period suggested that it might have the habitat environment that produced growth variation, as observed in the present study. Ganga and Pillai (2006) also discussed role of prevailing SST on growth rates in the species. The present findings explain how the age and growth information derived from hard part analysis aids in understanding growth and its temporal spread in the species, which is not distinguishable from other routine length frequency analysis and more so when data for several years are clubbed for analysis.
The maximum life span, age of the largest fish (221 mm TL) observed in the study estimated by VBGF growth equation using growth parameters from modal progression analysis of LF data and age at length data from otolith microstructure interpretation. It is 1.7 years (20.6 months) by the former method and 1.5 years (18 months) by latter. Earlier estimates of their life span from the region were 2 years (Hornell and Nayudu 1924) and 2.5-2.6 years (Nair et al 2016; Rohit and Bhat, 2003; Ganga and Pillai, 2006; Abdussamad et. al., 2010), following modal progression analysis of LF data. Devanesan (1943), estimated it as 14 years from the microstructures on scales, whereas Nair (1949,1960) estimated it as 3-4 years from otolith analysis. Jayabalan et al. (2014) reported their longevity as 2.5 years in the Oman waters. The present study highlighted a much faster growth in the species and consequently had a much shorter life span than earlier estimates.
The estimate of their size obtained from otolith analysis is 201 mm at the end of one year (Table 3, Fig. 7). It is evident from the pooled length frequency plot that nearly 99.5% of the stock was succumbed to fishing or natural causes during their first year of life. Despite this, their rapid growth, early maturity, high fecundity and moderate to high resilience, would continue to support good fishery year after year under normal conditions (Rohit et al. 2018). However, being a short lived, prolonged unfavorable conditions may elicit undesirable changes like spawning and recruitment failures and may result in possible setback to fishery during the subsequent years even under normal fishing. This finding can be used to explain the frequent inter-annual fluctuations in their landings.
Their spawning periodicity was monitored directly by biological observations and back calculations from the date of fishing and age at length data from hard part analysis. The biological observation suggested prolonged spawning during April-September along the coast with peak in May and June. Earlier reports also point out the spread of peak spawning activity during pre-monsoon and monsoon months (Hornell and Nayudu 1924; Nair and Chidambaram 1951; Bensam 1964; Prabhu and Dhulkhed 1967; Sarang and Sundaram 2010). Irrespective of the wide spread in spawning activity, earlier reports suggested peak spawning during monsoon months along the region (Devanesan 1943; Nair 1959; Balan 1959, 1964; Antony Raja 1970; Kumar and Balasubramanian 1987; Shah et al. 2018).
The spawning periodicity portrayed by back tracing age and date of fishing data indicates year-round spawning in the species with two peaks, major during pre-monsoon (April-June) and minor during post-monsoon (August-November) period (Fig. 8). This is in contrary to the present biological observations and earlier reports of their spawning periodicity. This indicates that major part of their landing was supported by pre-monsoon/monsoon recruits of the region itself. The other part of the landing which was by post-monsoon recruits might have migrated in from adjacent regions, highlighting the occurrence of inter-regional movement in the stock. Such inter-regional movement of the species and the possible drivers were described by earlier workers (Krishnakumar et al. 2006; Jayaprakash 2007) and according to them there is no physical barriers which restrict such movements.