Insights into the environmental conditions contributing to variability in the larval recruitment of the tropical sardine Sardinella lemuru
Introduction
The Bali sardine Sardinella lemuru dominates the small pelagic fishery in the southern Philippines and a large postharvest industry is dependent on this single species (Willette et al., 2011; Rola et al., 2018). This species is also classified under the Near Threatened status according to the IUCN (2019). In developing effective management strategies that can address threats to the sardine fishery, there is a need to understand the high variability in sardine stock population (Buchary et al., 2002; Gaol et al., 2004). Since stock variability can partially be predicted by pre-recruitment patterns (Houde, 2009; Shelton and Mangel, 2011; Gallego et al., 2012; Katara, 2014), this study aimed to establish estimates on the variability of the main environmental factors that may affect recruitment success of S. lemuru larvae.
Rooting back to Johan Hjort's critical period hypothesis (Hjort, 1914), fisheries oceanography has put forward different theories (e.g., aberrant drift, match-mismatch, stable ocean, member-vagrant, etc.) to identify the different pre-recruitment conditions and processes that could explain stock variability (Werner and Quinlan, 2002; Houde, 2008; Katara, 2014). Although these studies have demonstrated that different environmental variables contribute to varying degrees of predictability for different species and regions, it could be deduced that the key concept to recruitment success is that spawning location and timing is an adaptive strategy for larvae to experience the most optimal conditions for growth and survival. Conversely, this should result in lower mortality risks during the critical early life period in which the large variability in mortality determines recruitment variations in year classes (Miller, 2007).
Three-year reproductive biology data of S. lemuru particularly in the Bohol Sea and the southeastern portion of the Sulu Sea (Fig. 1) show that main spawning occurs during the northeast monsoon months of November to February with the maximum between December and January (De Guzman et al., 2015a and 2015b) with a markedly lower secondary spawning event between July to August (Campos and Bagarinao 2019). This is marked by increased gonadosomatic index values (Fig. 1) comparable to the western Australian population (Gaughan and Mitchell, 2000) and of the similar tropical sardine Sardinella longiceps in Oman (Al-Jufaili, 2012), along with an increase in the percentage of stage 4 mature or spawning adults (Landry and McQuinn, 1988). To understand the link between pre-recruitment processes and stock variability, the first step would be to identify what seasonally varying factors in the sardine environment coincide with the observed peak in spawning activity. Knowing these factors and how they affect larval populations, their interannual variations can then be used to surmise potential changes in the recruited stock for later months, following the subsequent maturation of larvae spawned within a particular period.
The principal factors affecting survival of larvae are predation, intra-species interactions, and environmental factors of food availability, temperature, and transport (Houde, 2008; Kuparinen et al., 2014). This study focused on the density-independent factors that dominate during the early-life stages, namely food availability, temperature, and transport or advection (Myers, 2002; Houde, 2008). The most influential density-independent factors on recruitment variability of larvae are prey abundance and temperature (Katara, 2014; Fiechter et al., 2015; Politikos et al., 2018; Sanchez-Garrido et al., 2019). Density-dependent factors are recognized to play an important role in fish population dynamics and can be mediated by food availability (Hilborn and Walters, 1992; Rose et al., 2001; Cahuin et al., 2009). However, specifying and disentangling their impact relative to density-independent factors remain controversial and challenging (Rose et al. 2001). Density-dependent factors may be more significant for the juvenile stage (Ohlberger et al., 2014), but is beyond the scope of this study.
Models on Japanese sardines have verified that sardine stock fluctuation is caused by variabilities in mortality during the pre-recruitment stages when survival is heavily dependent on larval sardine prey abundance (Suda and Kishida, 2003; Suda et al., 2005). Theories on prey abundance and timing (e.g., critical period and match-mismatch) have been given much attention as these directly affect starvation and growth trends. Correlating satellite-derived products with sardine catch in the southern Philippines (Villanoy et al., 2011) and the Bali Strait (Gaol et al., 2004; Sartimbul, 2010) have demonstrated that the increase in sardine abundance has a positive relationship with chlorophyll-a, representing the food supply for the sardine larvae (Gaol et al., 2004). Recent studies using more advanced sardine population models designate small zooplankton as larval prey (Fiechter et al., 2015; Sanchez-Garrido et al., 2019). High chlorophyll-a levels were found to correspond with high phytoplankton (Camoying, 2016; Camoying and Yñiguez, 2016) and zooplankton concentrations (Acabado et al., 2018) within the Bohol Sea, and as such, chlorophyll-a can be used as a proxy for sardine larval prey in this region.
Temperature is pinpointed to be the most associated factor to recruitment even in the tropics where there is a narrow range of surface ocean temperatures (Houde, 2009). Temperature is most influential on the early-life stages (Haslob et al., 2012), acting indirectly as a driver for variations in hydrography and as an indicator of optimal conditions (e.g., upwellings and blooms) (Katara, 2014); but more importantly, as a direct factor affecting metabolism and growth rates (Houde, 2009), egg buoyancy (Ospina-Alvarez et al., 2012a; Ospina-Alvarez et al., 2012b), and ovarian maturation (Ganias et al., 2014).
Much of early-life mortality is due to transport or advective loss (Peck and Hufnagl, 2012). Retention of larvae can significantly contribute to recruitment (Brochier et al., 2011) such that spawning grounds have evolved to be in areas that increase the likelihood of stock integrity (Fogarty and O'Brien, 2009). Measuring larval advective loss and retention within the southern Philippines should take into account its complex geomorphology consisting of multiple bays, islands, and relatively deep basins and its dynamic circulation patterns driven by monsoonal and El Niño Southern Oscillation (ENSO)-related climate variations (Gordon et al., 2011; Lermusiaux et al., 2011).
Because of the practical challenges to studying larvae in situ (Staaterman et al., 2012) the emergence of coupled biophysical models (CBPMs) has opened up an opportunity to identify advective losses from natural mortality (Paris, 2009), providing a mechanistic understanding of early-life history at spatial and temporal scales that is difficult to capture by conventional field methods (Werner et al., 2007; Lett et al., 2008). Such CBPMs have been successfully used to understand the population dynamics of small pelagics in temperate areas using detailed individual-based representations of various life history components (e.g., Suda and Kishida, 2003; Le Fur and Simon, 2009; Okunishi et al., 2009; García-García et al., 2016; Politikos et al., 2018). Ideally, a more complete life cycle model would be used, however, due to limited information on the necessary biological parameters to construct such models for the tropical sardine S. lemuru, we opted to use a simpler CBPM with less uncertainty. Using a CBPM, this study investigates the range of early-life conditions that Sardinella lemuru larvae are exposed to in the southern Philippines to give insights to the following questions: (1) What are the conditions experienced by larvae spawned at different months and are there distinct conditions characterizing the peak spawning period? (2) How does the interannual variability in these conditions affect larval recruitment and potentially account for observed stock population variability?
Section snippets
Methods
The CBPM was developed by linking offline daily velocity outputs from the global Hybrid Coordinate Ocean Model (HYCOM) (Chassignet et al., 2007) dataset with a particle dispersal model using MASON, which is a simulation toolkit written in Java (Luke et al., 2005), as platform. The 1/12° global HYCOM model was shown to sufficiently reproduce pertinent features of the Bohol Sea (Hurlburt et al., 2011). The purpose of the model is to enable Lagrangian tracking of sardine larvae and their
Results
Between replicate differences in all measured variables (retention, experienced chlorophyll-a, and experienced temperature) were very minimal with no significant differences, but these variables were significantly correlated with depth. Since chlorophyll-a and sea surface temperature were assumed to be homogeneous from surface to 30 m depth, the differences in experienced conditions between depths are explained only by variations in horizontal transport per simulated depth layer and not due to
Discussion
The conditions experienced by the recruited sardines demonstrated considerable sensitivity to the circulation patterns determining the larval tracks, evidenced by both temporal and depth variability of the results. Apparent highs and lows in median experienced conditions are observed seasonally (Fig. 3) and interannually (Fig. 4) but occasions of abrupt changes for particular batches of larvae spawned at least 5 days apart are common as marked by wide ranges and numerous outlier values. With
Summary and Recommendations
Short-lived small pelagics such as S. lemuru are highly affected by regional weather patterns (Houde, 2009) which heighten the risk from present and future stressors to recruitment (Katara, 2014). Similar to the S. lemuru population in Indonesia (Sartimbul et al., 2010; Sambah et al., 2012), the variability in the southern Philippines stock is related to productivity in the area. The modeled trends in environmental conditions imply that the spawning patterns observed are adaptations to maximize
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors would like to thank Dr. Wilfredo Campos, Luke Felix, Dr. Rio Naguit, Denmark Recamara, and the Research for Sardines Volunteer Program (RSVP) volunteers for sharing sardine fisheries data; Arjay Cayetano for helping start the model used; and Iris Salud Bollozos for useful insights on larval ecology. This study was fully funded by the Department of Science and Technology–Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development (DOST-PCAARRD) under
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