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Otolith elemental tags

Elemental composition assumptions, what affects elemental tags, types of fingerprinting and the demand for new software.

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Elemental composition assumptions

To the extent that populations or stocks of fish inhabit different environments, the otolith elemental composition should serve as a proxy for population identity.

To use otolith elemental composition as a stock discriminator we use 2 assumptions.

Elements under strong physiological regulation (Na, K, S, P and Cl) are of limited value for stock identification studies as they don’t meet the second assumption.

However, both assumptions appear to be met with respect to elements such as:

These have ambient element Ca concentrations and the temperature produces significant effects on otolith composition.

These environmental responses are recorded permanently in the otolith. They imply that we can use the otolith concentrations of selected elements and isotopes as a biological tag. This helps us to discriminate among groups of fish which have spent at least part of their lives in different environments.

Treating the selected elements as a group, using multivariate statistics, rather than individually, increases discriminatory power. Hence the term elemental fingerprint.

An appealing feature of this application is that the elemental fingerprint need not be linked to potential sources or locations in the environment. Rather, the presence of significant differences in the fingerprints of 2 or more groups of fish implies that the groups can’t all be random samples from the same population. This deduction holds even if physiological effects have influenced elemental composition, since random samples from the same population would have experienced the same mean physiological effects.

Of course, the presence of different fingerprints can’t be used to infer the length of time that the groups of fish remained separate. Even occasional residency in a different environment has the potential to introduce a detectable difference in the elemental composition.

By corollary, the absence of differences doesn’t necessarily imply that the groups of fish are of common origin.

As a result, it’s fair to categorize otolith elemental fingerprints as powerful discriminators when differences exist. However, fingerprints are of negligible value when differences can’t be detected.

Different environments

Genetic differences aren’t implied in elemental fingerprinting. Spatial heterogeneity in the stock environment can result in different fingerprints for different stock components. This makes it inappropriate to refer to the use of elemental fingerprinting as stock discriminators.

In addition, ontogenetic effects and age-related differences in exposure history can result in very different fingerprints for fish of different size classes from the same population. Nevertheless, the presence of different fingerprints among matched groups of fish necessarily implies different environmental histories.

Accordingly, the elemental fingerprint would appear to be an excellent biological tracer of groups of fish. This application of elemental fingerprinting has been met with success in both freshwater and saltwater.

Types of elemental fingerprinting

Our 2 forms of elemental fingerprinting are based on:

Advantages of whole-otolith assays include:

The major disadvantage is associated with the inability to take advantage of the chronological growth sequence recorded in the otolith.

The techniques we’ve used to analyze otoliths include:

However, ICPMS is the preferred choice for such assays. This is due largely to its capability for rapid and accurate isotopic and elemental assays over a wide range of elements and concentrations.

Isotope dilution ICPMS (ID-ICPMS) is a variant of ICPMS often used to certify reference materials. It’s the most accurate of the otolith analytical techniques currently available. Sample sizes required for most of the above assays are on the order of 5 to 10 mg of otolith material. However, ICPMS units outfitted with high efficiency nebulizers are capable of handling otolith weights as low as 0.3 mg.

Maximum-likelihood based software

There is increasing demand for the maximum-likelihood based software to separate mixtures of fish coming from different sources.

Discriminant analysis isn’t a good option here, since the 'priors' parameter is unknown. We've released a working copy of the Integrated Stock Mixture Analysis (ISMA) program  (written for the S-Plus environment). It’s available for use in separating stock mixtures based on elemental fingerprints or other continuous or categorical variables.

We’ve devoted much effort to the study and application of otolith elemental fingerprints, both with respect to stock identification and to factors influencing trace element uptake into the otolith.

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