No abstract

The proportion of living microbial biomass relative to total organic carbon is poorly constrained in the global ocean, as is the variability of these parameters over seasonal to multiyear times scales. Yet, such knowledge is key to understanding the pathways and fate of organic matter in the sea. Our use of combined discrete bottle and high resolution optical data allowed us to not only characterize for the first time the variability in the proportion of living and detrital carbon in surface waters of an oligotrophic site over 15+ years, but also to constrain estimates of living particle growth rates that drive the daily cycle of carbon production and loss within the ocean mixed layer. These observations may prove crucial to support mass-balance biogeochemical models aiming to understand particle transformation processes between the well-lit surface and the deep ocean environments.

The index of refraction (n) of particles is an important parameter in optical models that aims to extract particle size and carbon concentrations from light scattering measurements. An inadequate choice of n can critically affect the characterization and interpretation of optically-derived parameters, including those from satellite-based models which provide the current view of how biogeochemical processes vary over the global ocean. Yet, little is known about how n varies over time and space to inform such models. Particularly, in situ estimates of n for bulk water samples and at diel-resolving time scales are rare. Here, we demonstrate a method to estimate n using simultaneously and independently collected particulate beam attenuation coefficients, particle size distribution data, and a Mie theory model. We apply this method to surface waters of the North Pacific Subtropical Gyre (NPSG) at hourly resolution. Clear diel cycles in n were observed, marked by minima around local sunrise and maxima around sunset, qualitatively consistent with several laboratory-based estimates of n for specific phytoplankton species. A sensitivity analysis showed that the daily oscillation in n amplitude was somewhat insensitive to broad variations in method assumptions, ranging from 11.3 ± 4.3% to 16.9 ± 2.9%. Such estimates are crucial for improvement of algorithms that extract the particle size and production from bulk optical measurements, and could potentially help establish a link between n variations and changes in cellular composition of in situ particles.