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The capability for mapping two species of seagrass, Thalassia testudinium and Syringodium filiforme, by remote sensing using a physics based model inversion method was investigated. The model was based on a three-dimensional canopy model combined with a model for the overlying water column. The model included uncertainty propagation based on variation in leaf reflectances, canopy structure, water column properties, and the air-water interface. The uncertainty propagation enabled both a-priori predictive sensitivity analysis of potential capability and the generation of per-pixel error bars when applied to imagery. A primary aim of the work was to compare the sensitivity analysis to results achieved in a practical application using airborne hyperspectral data, to gain insight on the validity of sensitivity analyses in general. Results showed that while the sensitivity analysis predicted a weak but positive discrimination capability for species, in a practical application the relevant spectral differences were extremely small compared to discrepancies in the radiometric alignment of the model with the imagery-even though this alignment was very good. Complex interactions between spectral matching and uncertainty propagation also introduced biases. Ability to discriminate LAI was good, and comparable to previously published methods using different approaches. The main limitation in this respect was spatial alignment with the imagery with in situ data, which was heterogeneous on scales of a few meters. The results provide insight on the limitations of physics based inversion methods and seagrass mapping in general. Complex models can degrade unpredictably when radiometric alignment of the model and imagery is not perfect and incorporating uncertainties can have non-intuitive impacts on method performance. Sensitivity analyses are upper bounds to practical Hedley et al.Remote Sensing of Seagrasses capability, incorporating a term for potential systematic errors in radiometric alignment may be advisable. While T. testudinium and S. filiforme were too spectrally similar to be discriminated purely on spectral grounds, mapping of these, and other species may be achievable by exploiting co-incident factors based on ecological zonation.

Bubble size distributions ranging from 0.5 to 125 lm radius were measured optically during high winds of 13 m s 21 and large-scale wave breaking as part of the Southern Ocean Gas Exchange Experiment.Very small bubbles with radii less than 60 mm were measured at 6-9 m depth using optical measurements of the near-forward volume scattering function and critical scattering angle for bubbles (80 ). The bubble size distributions generally followed a power law distribution with mean slope values ranging from 3.6 to 4.6. The steeper slopes measured here were consistent with what would be expected near the base of the bubble plume. Bubbles, likely stabilized with organic coatings, were present for time periods on the order of 10-100 s at depths of 6-9 m. Here, relatively young seas, with an inverse wave age of approximately 0.88 and shorter characteristic wave scales, produced lower bubble concentrations, shallower bubble penetration depths, and steep bubble size distribution slopes. Conversely, older seas, with an inverse wave age of 0.70 and longer characteristic wave scales, produced relatively higher bubble concentrations penetrating to 15 m depth, larger bubble sizes, and shallower bubble size distribution slopes. When extrapolated to 4 m depth using a previously published bubble size distribution, our estimates suggest that the deeply penetrating small bubbles measured in the Southern Ocean supplied 36% of the total void fraction and likely contributed to the transfer and supersaturation of low-solubility gases.

A s the primary conduit for CO 2 and heat exchange between the atmosphere and the deep ocean, the Southern Ocean is an important part of the climate system. Approximately 40% of the ocean's inventory of anthropogenic carbon entered through the air-sea interface south of 40°S (Khatiwala et al. 2009), and the region will continue to serve as an important carbon sink into the future (Ito et al. 2015). Despite its importance, the processes controlling air-sea gas exchange in the Southern Ocean are poorly represented by models. This was highlighted in a recent comparison of models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), wherein the simulated seasonal cycles of air-sea CO 2 exchange with the Southern Ocean were widely divergent and in poor agreement with observational estimates (Anav et al. 2013;Jiang et al. 2014), suggesting possible model biases in the timing, spatial A recent Southern Ocean airborne campaign collected continuous, discrete, and remote sensing measurements to investigate biogeochemical and physical processes driving air-sea exchange of CO 2 , O 2 , and reactive biogenic gases.