Spatial and temporal variation in C:N:P ratios, delta N-15 and delta C-13 of eelgrass Zostera marina as indicators of ecosystem processes, Tomales Bay, California, USA

The nutrient content, delta(15)N, and delta(13)C of seagrasses in Tomales Bay (California, USA) vary in both space and time. The variations in these measurements were not random, but followed spatial and seasonal patterns that provide insight into the sources and processing of nutrients in the Tomales Bay ecosystem. Wide ranges of carbon, nitrogen, and phosphorus content of green leaves of Zostera marina were found in 72 samples collected over the 2 yr of sampling. Carbon content varied from 29.0 to 40.9% of dry weight, nitrogen from 1.13 to 3.79%, and phosphorus from 0.11 to 0.90%. Stable isotopic composition was variable as well: the mean delta(15)N for all samples collected was 9.7 +/- 0.3 parts per thousand with a range of 6.2 parts per thousand. Carbon isotopic content had a range of 7.5 parts per thousand, with a mean delta(13)C Of -9.6 +/- 0.2 parts per thousand. There was a strong spatial trend in the N content, but not the P content, of Z. marina leaves from Tomales Bay. The C:N ratio was around 15 near the mouth of the bay and increased Linearly with distance into the bay to similar to 25 near the head of the bay; there was a concomitant pattern of increasing delta(15)N Of seagrass leaves, from 7 parts per thousand near the mouth of the bay to near 12 parts per thousand at the head of the bay. The spatial pattern in N content was only present during summer months, but the spatial pattern in stable isotopic composition was present in both summer and winter. The patterns in the N and delta(15)N content of the seagrasses indicate the importance of denitrification in the C and N cycles in Tomales Bay. The analysis of patterns in variation of elemental content and isotopic composition of seagrasses is a powerful tool for investigating ecosystem-scale processes in coastal marine systems. Similar analyses of seagrasses from less well studied ecosystems should provide data to generate hypotheses about spatial and temporal variation in processes in these other systems.