| one publication added to basket [304215] | Optimizing models for remotely estimating primary production in Antarctic coastal waters
In: Antarctic Science. Cambridge University Press: Oxford. ISSN 0954-1020; e-ISSN 1365-2079, more |  |
| Authors | | Top | - Dierssen, H.M., more
- Vernet, M.
- Smith, R.C.
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| Abstract | Primary productivity and associated biogeochemical fluxes within the Southern Ocean are globally significant, sensitive to change and poorly known compared to temperate marine ecosystems. We present seasonal time series data of chlorophyll a, primary productivity and in-water irradiance measured in the coastal waters of the Western Antarctica Peninsula and build upon existing models to provide a more optimum parameterization for the estimation of primary productivity in Antarctic coastal waters. These and other data provide strong evidence that bio-optical characteristics and phytoplankton productivity in Antarctic waters are different from temperate waters. For these waters we show that over 60% of the variability in primary production can be explained by the surface chlorophyll a concentration alone, a characteristic, which lends itself to remote sensing models. If chlorophyll a concentrations are accurately determined, then the largest source of error (13–18%) results from estimates of the photoadaptive variable (PBopt). Further, the overall magnitude of PBopt is low (median 1.09 mg C mg chl−1 h−1) for these data compared to other regions and generally fits that expected for a cold water system. However, the variability of PBopt over the course of a season (0.4 to 3 mg C mg chl−1 h−1) is not consistently correlated with other possible environmental parameters, such as chlorophyll, sea surface temperature, incident irradiance, day length, salinity, or taxonomic composition. Nonetheless, by tuning a standard depth-integrated primary productivity model to fit representative PBopt values and the relatively uniform chlorophyll-normalized production profile found in these waters, we can improve the model to account for approximately 72–73% variability in primary production both for our data as well as for independent historic Antarctic data. |
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