1999 Articles

Bio-optical properties of the marine diazotrophic cyanobacteria Trichodesmium spp. II. A reflectance model for remote sensing

Subramaniam, Ajit; Carpenter, Edward J.; Falkowski, Paul G.

The spatial and temporal distribution of Trichodesmium in the world's oceans is highly variable and can potentially be assessed using satellite imagery. Distinguishing these organisms from other phytoplankton in the upper ocean using remotely sensed information, however, requires an optical model that uniquely characterizes Trichodesmium. Here, we parameterize a standard remote-sensing reflectance model using measured values of Trichodesmium's inherent optical properties, namely the spectral dependence of the chlorophyll-specific optical absorption cross-sections and the spectral dependence of the chlorophyll-specific backscatter cross-sections. Values for the chlorophyll-specific absorption cross sections are described in the previous paper. We calculated the spectral chlorophyll-specific backscattering cross-section (b*b) from measurements of the chlorophyll-specific volume-scattering function and the spectral backscatter coefficients. b*b was 0.0027 m² (mg chlorophyll a [Chl a])⁻¹ at 436 nm and 0.002 m² (mg Chl a)⁻¹ at 546 nm; these cross-sections are approximately one order of magnitude higher than those for "typical" phytoplankton. The optical model revealed that the combination of high backscatter, absorption, and fluorescence could be used to distinguish moderate to high concentrations (>1 mg Chl m⁻³)of Trichodesmium from other phytoplankton. The model also predicted that surface scum blooms of Trichodesmium would have high reflectance in the near infrared. The high reflectance feature of surface Trichodesmium blooms was used in conjunction with sea truth and data from the advanced very high resolution radiometer (AVHRR) to map a 300,000-km² Trichodesmium bloom off the Somali Coast in May 1995. The nitrogen fixed by this bloom was estimated to be 9.4 × 10⁸ gN d⁻¹. These results demonstrate the potential of using remote-sensing techniques in the estimation of nitrogen fixation and the contribution of nitrogen fixation to global biogeochemical processes.