Abstract
Seasonal responses in estuarine metabolism (primary production, respiration, and net metabolism) were examined using two complementary approaches. Total ecosystem metabolism rates were calculated from dissolved oxygen time series using Odum's open water method. Water column rates were calculated from oxygen-based bottle experiments. The study was conducted over a spring-summer season in the Pensacola Bay estuary at a shallow seagrass-dominated site and a deeper bare-bottomed site. Water column integrated gross production rates more than doubled (58.7 to 130.9 mmol O(2) m(-2) d(-1)) from spring to summer, coinciding with a sharp increase in water column chlorophyll-a, and a decrease in surface salinity. As expected, ecosystem gross production rates were consistently higher than water column rates, but showed a different spring-summer pattern, decreasing at the shoal site from 197 to 168 mmol O(2) m(-2) d(-1) and sharply increasing at the channel site from 93.4 to 197.4 mmol O(2) m(-2) d(-1). The consistency among approaches was evaluated by calculating residual metabolism rates (ecosystem - water column). At the shoal site, residual gross production rates decreased from spring to summer from 176.8 to 99.1 mmol O(2) m(-2) d(-1), but were generally consistent with expectations for seagrass environments, indicating that the open water method captured both water column and benthic processes. However, at the channel site, where benthic production was strongly light-limited, residual gross production varied from 15.7 mmol O(2) m(-2) d(-1) in spring to 86.7 mmol O(2) m(-2) d(-1) in summer. The summer rates were much higher than could be realistically attributed to benthic processes, and likely reflected a violation of the open water method due to water column stratification. While the use of sensors for estimating complex ecosystem processes holds promise for coastal monitoring programs, careful attention to the sampling design, and to the underlying assumptions of the methods, is critical for correctly interpreting the results. This study demonstrated how using a combination of approaches yielded a fuller understanding of the ecosystem response to hydrologic and seasonal variability.