Daily growth rates in shells of Arctica Islandica: assessing Sub-seasonal environmental controls on a long-lived bivalve mollusk

Shells of the extremely long-lived bivalve mollusk Arctica islandica (Linnaeus 1767) provide century-long, multi-proxy records of inter-annual environmental variability in middle- to high-latitude marine settings. Reliable interpretation of these climate archives, however, requires exact knowledge of the length and timing of the growing season and which environmental parameters control shell growth rate during the year. Here, intra-annual growth microstructures, delta(18)O-derived ambient water temperatures, and delta(13)C from A. islandica shells collected from the southern and central North Sea are studied. Such data were analyzed in conjunction with observational sea-surface temperature and primary productivity data. Arctica islandica produces circadian growth increments in its shell (on average 31.5 mum per day during age four, measured along the outer shell surface), which allow assignment of calendar dates to each shell portion. The growing season of A. islandica in the upper mixed layer of the ocean (here 25 m water depth) is not continuous over an eight-month period as previously suggested. Rather, it is interrupted during spawning between early September and mid-November. In addition, shell production ceases or is strongly retarded due to food scarcity between mid-December and mid-February. Water temperatures derived from oxygen-isotope ratios are in good accord with observed sea-surface temperatures. In specimens at 25 m water depth, abrupt changes in shell delta(18)O-derived temperature (T-delta18O) were interpreted to represent vertical displacements of the seasonal thermocline. Daily shell growth is controlled by temperature and food availability. Up to 58% of the variation in daily growth rate is explained by these environmental parameters. This study demonstrates that A. islandica can provide seasonal to subseasonal, precisely dated proxies of environmental variables. Such data are of increasing importance for climate models