Estimating contributions from nursery areas to fish stocks in freshwater systems using otolith fingerprints: The case of the streaked prochilod in the La Plata Basin (South America)

Abstract

Stock composition studies using otolith fingerprints have scarcely been developed in freshwater systems. In this context, the La Plata Basin is the second largest fluvialmarine system of South America, where Prochilodus lineatus is the most important fishery resource. Despite the basin importance, estimation of mixed stock composition has not been explored yet. In this paper, the contribution of the two main nursery areas to two fishing stocks (Uruguay and Paraná rivers) of P. lineatus was evaluated using otolith's core microchemistry, considering two groups: subadult (2 years) and adult (4 years). Estimates were made using two maximum likelihood methods. Chemical composition of young-of-year fish caught in nursery areas in 2010 was used as baseline of the models, whereas chemical composition of the core of subadult and adult otoliths was used as sample of unknown origin. Results suggest that the subadult stock from Paraná was not mixed (contribution~100%), whereas the stock from Uruguay had a contribution from the Paraná nursery (1.5 ± 1.2-17.9 ± 3.96%). For the adults, the degree of mixing increased and the contribution from both nursery areas to the Paraná and Uruguay stocks varied between 14.8 ± 4.18% and 85.2 ± 4.18%, respectively. The potential application of otolith fingerprints and maximum likelihood mixture models is here highlighted for determining the relative importance of recruitment sources of fish in the La Plata Basin. Because the contributions of the different nursery areas shared among several nations in turn affect the composition of internationally shared stocks, comprehensive management agreements at the basin level are necessary.

Mixed-stock and discriminant models use for assessing recruitment sources of estuarine fish populations in La Plata Basin (South America)

“…Several authors have employed both MLE and MLC methods (Fraile et al, 2014;Rooker et al, 2014;Avigliano et al, 2018b), while others have used MLE (Crook & Gillanders, 2006) or MCL (Lazartigues et al, 2016(Lazartigues et al, , 2017, separately. Discriminant analysis models have been less used because it is necessary to know the prior probabilities of classification to each group, these being rarely known in nature (Millar, 1990;Gillanders, 2005).…”

“…For example, to assume equal probabilities of classification could tend to under-estimate the misclassification probabilities, especially when the size of the baseline is very small (Millar, 1990). In this regard, recent authors have preferred to used maximum likelihood estimators (Fraile et al, 2014;Rooker et al, 2014;Lazartigues et al, 2017;Avigliano et al, 2018b), although these methods in combination with discriminant analysis have also been used (Fraile et al, 2014). Avigliano et al (2018b) have assessed the contribution from nursery areas to freshwater stocks of P. lineatus in the La Plata Basin using otolith chemistry and maximum classification-likelihood models (MLE and MLC methods) simultaneously.…”

“…A 193 nm ArF Excimer laser ablation system (Photon Machines Analyte G2) coupled to an ICP-QMS Agilent 7700 (Santa Clara, USA) was used for the analysis. Analytical conditions were configured according to Avigliano et al (2018aAvigliano et al ( , 2018b. Radial line-scans of ∼190 µm length were carried out from core to the first annuli ( Figure 2) using a circular aperture at scanning speed of 5 µm s −1 (spot diameter: 85 µm; crater depth: 160 µm).…”

“…Standard deviations of the maximum likelihood methods estimates were calculated by running the HISEA program in simulation mode (bootstrap) using 1000 simulations (Millar, 1990;DeVries et al, 2002;Rooker et al, 2008Rooker et al, , 2014Rooker et al, , 2016Avigliano et al, 2018b).…”

Unravelling the stock structure of the Persian brown trout by otolith and scale shape

“…More research is necessary to reveal the existence of connectivity between the study sites. Other methodologies such as otolith element–calcium ratios (Avigliano et al ., ), genetics (Vignon & Morat, ), scale microchemistry (Eek & Bohlin, ) and otolith strontium isotopes (Zimmerman, ) could contribute to unravel displacements and connectivity. Scale shape could provide a non‐lethal alternative to otoliths for studying vulnerable species, such as Persian brown trout, while the use of otoliths could be a more conservative method because these are inert structures and do not get damaged or lost.…”