Fines de la escritura, tanto en la enseñanza como en el aprendizaje

Otoliths are hard calcium carbonate structures found in pairs within the heads of all teleosts, and are employed for balance, orientation and hearing (e.g., Campana and Neilson 1985; Campana 1999). The main interest that otoliths hold for biologists and fishery scientists lies in the fact that these structures store valuable information on age of fishes and the

environment within which they lived at different ages throughout life, facilitating

understanding of population dynamics, stock identity, fish systematics and evolution (Popper et al. 2005). The use of otoliths as indicators of fish age began with Reibisch’s (1899)

observations of otolith annuli in Pleuronectes platessa. Since then, interest in otolith microstructure as a metabolically-inert timekeeper and environmental recorder has grown exponentially, with close to a million fish aged each year worldwide (Campana et al. 2000; Campana and Thorrold 2001; Campana 2005).

The information related to growth and environment contained within the otolith

microstructure and chemistry at different temporal scales is important for the management of fisheries and protected fish species around the world (Kalish 1989; Campana 1999). This information, which is employed in studies of age, growth, movement patterns and habitat interactions, makes these biological structures highly valuable to fishery scientists. Through records of daily events stored within their structure and chemical composition, otoliths can assist in elucidating the effects of changes in the environment on growth and survival in the early life stages of fish, thus resulting in an improved understanding of factors affecting recruitment success (Jones 1992). For adult fish, counts of the annuli that form in otoliths at

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annual intervals are used to determine the ages individual fish for estimating growth, longevity, and mortality rates in fish populations (e.g., Campana 2001; Wilson and Nieland 2001; Laidig et al. 2003). This understanding of fish population biology is vital for producing reliable fish stock assessments required for determining effective management strategies to allow fish harvesting whilst ensuring that the risk of such harvesting to the long term

sustainability of the stock remains at an appropriate level (Jones 1992; Campana 2001; Begg et al. 2005).

Somatic growth rate is calculated from growth models, which are fitted to lengths at capture using ages derived by examining the microstructure of otoliths (Campana and Jones 1992). The diversity of growth models available in the literature and their interpretation make the determination of the most appropriate model to describe length-at-age data for a species difficult (Ricker 1979). Thus, for example, a number of alternative curves have been used to describe growth rates of individuals at early life history stages, e.g., linear (e.g., Townsend and Graham 1981; Jones 1986; Victor 1987), exponential (e.g., Struhsaker and Uchiyama 1976), and Gompertz (e.g., Laroche et al. 1982; Lough et al. 1982; Warlen and Chester 1985; McGurk 1987) models. The von Bertalanffy growth curve (von Bertalanffy 1938) has also been employed to describe the growth of young fish (e.g., Ralston 1976; Wild and Foreman 1980; Laroche et al. 1982), but to a much lesser extent than for adult fish (Ricker 1979; Campana and Jones 1992; Jones 1992), largely due to its inability to represent sigmoidal growth data. Before selecting the final form of curve to be employed, the fit to length-at-age data provided by alternative growth curves should, therefore, be explored. The growth models should also be able to account for both accelerated growth at the juvenile stage and decelerated growth during the adult stage, when individuals approach a final size (Schnute 1981). To address this, Schnute (1981) proposed a comprehensive growth model, which

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includes several historical models as special cases, and which can be related to both accelerated and decelerated growth.

A prominent application of otolith microstructure examination is growth back- calculation, which involves estimating the length of individual fish at successive ages throughout life (e.g., Francis 1990; Campana and Jones 1992). Back-calculation is an invaluable analytical method widely used in fisheries science and ecology around the world for reconstructing individual growth histories of teleosts (e.g., Francis 1990; Campana 2005; Vigliola and Meekan 2009). The most common application of back-calculation is that of complementing the observations of lengths at the ages of capture with estimates of lengths at age for younger fish. Curves are then fitted to the combined set of observations and estimates to determine values of key growth parameters (e.g., the asymptotic length or the growth coefficient of the von Bertalanffy growth function) and to compare, describe or predict growth variations among individuals (e.g., Shafi and Jasim 1982; Jones 2000; Colloca et al. 2003; Lorance et al. 2003; Ballagh et al. 2011). For some species, growth histories within bony structures, such as otoliths, become particularly useful when samples sizes are small or information on life history at earlier ages is lacking (e.g., Campana 1989; Meekan et al. 1998a; Vigliola and Meekan 2009). Growth curves derived from back-calculated data have been used to compare growth rates between sexes, cohorts and populations of the same species (e.g., Frost and Kipling 1980; Thorrold and Williams 1989; Sirois et al. 1998;

Goldman and Musick 2006). Back-calculated lengths at age have also been used in models to account for individual variability in growth, thereby facilitating improvement of fish stock assessments (e.g., Pilling et al. 2002; Santiago and Arrizabalaga 2005). Other developments, which use the results of growth back-calculations, involve relating environmental conditions from a specific time period to estimates of length at age (e.g., Dutil et al. 1999). Back- calculation has also led to significant progress in assessment of the influence of year-to-year

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variation of size-selective mortality on previous life history stages (e.g., Grønkjær and Schytte 1999; Good et al. 2001; Sinclair et al. 2002a).

Another common application of information from otoliths is the use of otolith microchemistry for discriminating fish stocks and understanding population connectivity (e.g., Gillanders 2002; Rooker et al. 2003; Fowler et al. 2005; Stransky et al. 2005; Thresher and Proctor 2007). Environmental histories and migration patterns and/or habitat shifts throughout the lives of individual fish have been reconstructed from otolith elemental concentrations, which change in a predictable manner with environmental variables (e.g., Elsdon and Gillanders 2004; Daverat et al. 2005; Dorval et al. 2005; Hobbs et al. 2005). Furthermore, techniques developed initially for analysing tree-ring data (i.e.,

dendrochronology) have been employed to describe the long-term relationships between trends exhibited by otolith growth and aspects of environmental variability (e.g., water temperature) (e.g., Black 2009; Neuheimer et al. 2011; Gillanders et al. 2012; Black et al. 2013). Sclerochronology, or the study of calcified structures to reconstruct the past history of living organisms, which employs these relationships to predict the effects of climate change from otolith biochronologies, is becoming an important aspect of fisheries management (e.g., Panfili et al. 2002; Matta et al. 2010; Gillanders et al. 2012).