Methodology And Case Studies Of Fish Otolith Morphology And Microchemistry Analysis In Stock Discrimination

Otoliths are calcified structures that exist in most teleost. Otolith informationanalysis technique has been used to solve many problems in fishery ecology, forexample, species and stock discrimination, spawning ground and migration habits.However, in otolith morphology analyses, too many variables are used to express otolithmorphological characteristics, and the effective characteristics and category of thosevariables have not been well investigated. The characteristics of various kinds ofvariables, their applications and the pros and cons of the commonly used size removalmethods have not been stuied, either. In otolith elemental fingerprinting by LA-ICPMS,the methods of precisey laser ablating, validation of ablation spots and effectivelychoosing elemental data are still not standardized and thus need to be furtherinvestigated. In this study, we investigate the methods of otolith morphometrics andelemental fingprinting and their applications in stock discrimination of fish thatcommonly inhabit Chinese coastal waters. These fish include anadromous Coilia nasus,estuarine Coilia mystus and five highly localized gobies (Ctenotrypauchen chinensis,Odontamblyopus lacepedii, Amblychaeturichthys hexanema, Chaeturichthysstigmatias and Acanthogobius hasta). The main findings are as follows:1) Because there are too many otolith morphological variables that can be used inotolith morphology analysis, reasonable classification of the variables is essentialwhen applying them to stock discrimination. In this study, we classified the otolithmorphological variables into size variables and shape variables (i.e. Fouriercoefficients and shape indices), which were used for discriminating among stocksof Coilia nasus (the Liaohe River Estuary, the Qinhuang Island, the Yellow Riverestuary and the Yangtze River estuary). The results showed that the overallclassification success was moderate (<60%), with the lowest (34-39.5%) inQinhuang Island stock (slightly better than randomly assigned) and the highest (64-90%) in the Yangtze River estuary stock.2) Selecting the appropriate morphological variables in stock discrimination is a keytechnique in otolith morphology analysis. From the results of discriminating amongstocks of C. nasus and C. mystus in this study, some basic principles for selectingotolith morphological variable were suggested. Firstly, the variables should strictlymeet the corresponding statistic assumptions and have potentials for discrimination among stocks. Secondly, when the number of variables is relatively small, effectivevariables can be selected according to step-by-step statistics. However, when thereare too many variables, principle components analysis should be first applied to geteffective variables from the original ones before they are run for further statisticalanalyses such as discrimination analysis.3) The nonparametric test is an option when the data assumptions for parametric testare not met, while most parametric tests undergo the corresponding procedures fornonparametric tests. Comparisons between parametric tests and nonparametrictests running on the otolith morphometrics of four C. mystus stocks (the LiaodongBay, the Bohai Bay, the Jiaozhou Bay and the Yangtze River estuary) wereinvestigated. Results of the stock discrimination using the combination of shapeindices and elliptic Fourier coefficients showed that nonparametric tests could keepmore effective morphological variables for stock discrimination, which producedhigher overall classification success (68.2%) than parametric tests (46.2%).4) Size adjustment is another important technique in otolith morphology analysis.Three methods (ANCOVA adjustment, residual adjustment and allometricadjustment) were compared to remove fish length effects, which were applied tostock discrimination of C. nasus and C. mystus (the Liaodong Bay, the Bohai Bay,the Yellow River Estuary, the Jiaozhou Bay and the Yangtze River Estuary). Theresults showed that the fitting effects of the models in the three methods weresimilar. The allometric adjustment obtained the highest classification success(70.7%) in C. nasus, while the ANCOVA adjustment got the highest classificationsuccess (58.9%) in C. mystus. This suggested that the effectiveness of each sizeadjustment might be species-specific. Moreover, a procedure that can improve thestatistical process in comparing otolith morphology analysis was proposed in thisstudy.5) It is of interest to fishery researchers how to identify effective otolithmorphological variables and apply them to species and stock discrimination. Thisstudy compared the shape indices and elliptic Fourier coefficients as well as theirapplications to species and stock discrimination in five goby species that inhabitedin the Liaodong Bay, the Bohai Bay, the Yellow River estuary and the JiaozhouBay (Ctenotrypauchen chinensis, Odontamblyopus lacepedii,Amblychaeturichthys hexanema, Chaeturichthys stigmatias and Acanthogobiushasta). The results showed that the classification success of species discrimination (83.7-98.6%) were significantly higher than stock discrimination (50-75.8%). Theelliptic Fourier coefficients performed better in improving classification successthan shape indices in stock discrimination.6) Accurately locating otolith nuclei and ensuring the effectiveness of laser ablationsare key techniques to acquire reliable LA-ICPMS analysis. The traditional singlelaser ablating of otolith nuclei may weaken the reliability of elementalfingerprinting due to the unicity and bias of the ablating spots. A multi-ablatingotolith nuclei technique for elemental fingerprint was established and was appliedto discriminating among stocks of C. nasus that were collected from the LiaodongBay, the Bohai Bay, the Yellow River estuary, the Jiaozhou Bay and the YangtzeRiver estuary. The results showed that Sr:Ca and Ba:Ca ratios were effective atelementally fingerprinting the stocks. The overall classification success was at arelatively high rate of72.7%, indicating that this technique could ensure highquality of laser ablating and thus improve the efficiency and precision of the stockdiscrimination.In conclusion, a number of methods of otolith morphology analysis and elementalfingerprinting for species or stock discrimination were compared and investigated inthis study. These included size adjustment, selection of effective morphologicalvariables, nonparametric test versus parametric test, shape or size variables versuselliptic Fourier analysis and multi-laser ablating in otolith nuclei for otolithfingerprinting etc.. A case study was conducted to validate each methodology, whichsuggested that each appropriate analysis methods could improve the effectiveness ofotolith analysis for species or stock discrimination. This study could help betterunderstand the fundamental theories of otolith information analysis and theirapplications in fishery ecology.