Selph, K. E., Landry, M. R., Taylor, A. G., Gutierrez-Rodriguez, A., Stukel, M. R., Wokuluk, J., et al. (2016). Phytoplankton production and taxon-specific growth rates in the Costa Rica Dome.
J Plankton Res, 38(2), 199–215.
Abstract: During summer 2010, we investigated phytoplankton production and growth rates at 19 stations in the eastern tropical Pacific, where winds and strong opposing currents generate the Costa Rica Dome (CRD), an open-ocean upwelling feature. Primary production (14C-incorporation) and group-specific growth and net growth rates (two-treatment seawater dilution method) were estimated from samples incubated in situ at eight depths. Our cruise coincided with a mild El Nino event, and only weak upwelling was observed in the CRD. Nevertheless, the highest phytoplankton abundances were found near the dome center. However, mixed-layer growth rates were lowest in the dome center ( approximately 0.5-0.9 day-1), but higher on the edge of the dome ( approximately 0.9-1.0 day-1) and in adjacent coastal waters (0.9-1.3 day-1). We found good agreement between independent methods to estimate growth rates. Mixed-layer growth rates of Prochlorococcus and Synechococcus were largely balanced by mortality, whereas eukaryotic phytoplankton showed positive net growth ( approximately 0.5-0.6 day-1), that is, growth available to support larger (mesozooplankton) consumer biomass. These are the first group-specific phytoplankton rate estimates in this region, and they demonstrate that integrated primary production is high, exceeding 1 g C m-2 day-1 on average, even during a period of reduced upwelling.
Stukel, M. R., Decima, M., & Kelly, T. B. (2018). A new approach for incorporating 15N isotopic data into linear inverse ecosystem models with Markov Chain Monte Carlo sampling.
PLoS One, 13(6), e0199123.
Abstract: Oceanographic field programs often use delta15N biogeochemical measurements and in situ rate measurements to investigate nitrogen cycling and planktonic ecosystem structure. However, integrative modeling approaches capable of synthesizing these distinct measurement types are lacking. We develop a novel approach for incorporating delta15N isotopic data into existing Markov Chain Monte Carlo (MCMC) random walk methods for solving linear inverse ecosystem models. We test the ability of this approach to recover food web indices (nitrate uptake, nitrogen fixation, zooplankton trophic level, and secondary production) derived from forward models simulating the planktonic ecosystems of the California Current and Amazon River Plume. We show that the MCMC with delta15N approach typically does a better job of recovering ecosystem structure than the standard MCMC or L2 minimum norm (L2MN) approaches, and also outperforms an L2MN with delta15N approach. Furthermore, we find that the MCMC with delta15N approach is robust to the removal of input equations and hence is well suited to typical pelagic ecosystem studies for which the system is usually vastly under-constrained. Our approach is easily extendable for use with delta13C isotopic measurements or variable carbon:nitrogen stoichiometry.