Contents volume 124, 1995

Abstract

Retrospective estimates of life-history traits (e.g., growth rate, lifespan, phenology) of mollusks are valuable data for a number of fields, including paleontology, archaeology, and fisheries science. The best option for obtaining these data for species such as oysters that lack reliable morphological indicators of annual accretionary growth (e.g., growth lines) is to use time consuming and expensive stable isotope analyses. However, laser ablation analyses of Mg/Ca are faster and less expensive than stable isotope analyses, and although several studies have shown Mg/Ca ratios in bivalve shells do not reflect water temperature, there is often a weak correlation that may allow annual cycles to be detected. Here, we explore the utility of line scan analyses of Mg/Ca ratios using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) as a more rapid and less expensive method for obtaining ontogenetic age estimates of mollusk shells than more traditional oxygen stable isotope analyses. We tested this method by measuring Mg/Ca ratios from 21 fossil and modern specimens of two oyster species, Crassostrea virginica and Magallana gigas (formerly Crassostrea gigas), collected across a wide geographic area along the coast of the United States. We compared Mg/Ca growth profiles with either known lifespans or with growth characteristics estimated from δ18O profiles. These analyses showed that Mg/Ca profiles from laser ablation analyses reliably reproduced the annual features of the more widely used δ18O profiles. In total, 97% (n = 102) of all seasonal peaks and troughs, including both those from the δ18O profiles and the expected patterns in the shells of known age, were detectable in the Mg/Ca profiles. We conclude that laser ablation analysis of Mg/Ca ratios is a rapid and cost effective alternative to stable isotope analysis for retrospective estimation of the growth characteristics of oysters and potentially other taxa with shells lacking reliable annual morphological features.