Otolith microchemistry to identify sources of larval yellow perch in a fluvial lake: an approach towards freshwater fish management

Abstract

The study aims at determining which spawning sites are contributing to yellow perch (Perca flavescens) juveniles’ recruitment in Lake Saint-Pierre (St. Lawrence River, Canada). We expect to highlight new management perspectives. Thus, we investigated both natal origin and connectivity processes for young of the year prior to their first winter. Otolith chemical composition was measured at larval and juvenile stages using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Five spawning sites were sampled and discriminated using a three-elemental model (manganese, barium, strontium). Results showed that (i) all within-lake sites contributed similarly to juvenile production and (ii) production results from both local recruitment and lake-wide connectivity processes. The study suggests fish management should include an overall evaluation of the lake-wide recruitment. Both local and widespread actions are required, depending on the level of connectivity in the lake, which plays a central role in shaping the spatial pattern of recruitment. Finally, otolith microchemistry proves to be an efficient tool for freshwater fish managers to evaluate both natal origin and connectivity in heterogeneous aquatic ecosystems.

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.…”

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)

“…It was also documented that the nursery area located upstream of Salto Grande Dam (Uruguay River) has a different chemical signature to that located downstream (Avigliano, Fortunato, et al, ). On the other hand, the segregation of fish of the same origin could affect the estimates (Lazartigues et al, ).…”

“…At this point, defining which method is most suitable for the base matrix could be questionable. Some authors used both methods (Rooker et al, ), whereas others directly used MLE (Crook & Gillanders, ) or MCL (Lazartigues et al, , ). Both estimators show an increase in the mix for 2014 and a greater contribution to each stock from the nursery areas of the same region.…”

Paths to the unknown: dispersal during the early life of fishes

“…Moreover, environmental factors, such as temperature, salinity, bottom depth, and density gradient, were important explanatory variables for the probability of occurrence and abundance of eggs. Lazartigues et al (2018) used biochemical analysis of otoliths to measure the contribution of different spawning areas to the yearly production of a species of high fisheries importance. This study provides, for the first time, detailed, qualitative, and quantitative information on the recruitment process with regard to the connectivity of spawning areas and nurseries in a large fluvial lake system.…”