10:45 AM - 11:00 AM
[AOS15-07] Variability of Chlorophyll and Primary Production at Time-series Observation Sites
Keywords:marine ecosystem, plankton ecology, ecosystem modeling, adaptive response, acclimation
Introduction
Environmental gradients of light, nutrients and temperature fluctuate persistently within the marine environment, and in response phytoplankton systematically adjust their physiology and hence alter their chemical composition and pigment content. This process, termed photo-acclimation, is captured by a wide variety of phytoplankton models, which are now commonly incorporated into marine biogeochemical and even Earth System Climate Models. Including photo-acclimation in models can substantially improve the representation of key observables, by for example better capturing the observed global scale distributions of chlorophyll (chl) [2] and oceanic carbon to nitrogen ratios [3]. Understanding how such key observables depend on underlying environmental variability is important for interpreting observed patterns as well as for testing model formulations to be used for future projections and other predictive modeling, including simulations to inform the planning and design of observations.
Model
The FlexPFT model, embedded in an updated, higher-resolution version otherwise similar to a recent 3D global setup [1, 2] calculates dynamic variations in the composition of phytoplankton, quantified by the C:N:chl ratios of biomass, and their primary production. Phytoplankton growth tends to be limited by light and iron limitation at subarctic station K2, but persistent nitrogen limitation is observed (and modeled) at subtropical station S1. Results from the 3D model were extracted for stations K2 and S1, as well as for other time-series observation sites, including subarctic stations HOT and BATS. Model results are analyzed to understand how seasonal and other variations in the light and nutrient environment impact the modeled composition and productivity of phytoplankton.
Results
Modeled phytoplankton C:N ratios are higher at subtropical compared to subarctic sites, as observed, and they are more closely related to nitrate concentrations than to light levels. At low nitrate concentrations, C:N ratios are persistently high with a narrow range of variability. At higher nitrate concentrations, C:N ratios tend to be lower, but with substantially greater variability, reflecting differing degrees of light limitation (seasonally and with depth). Modeled chl:C ratios are strongly and directly related to modeled C:N ratios, because the model accounts for the use of both nitrogen and energy to synthesize chlorophyll. Modeled chlorophyll concentrations and the ratio of Chl:C in biomass both vary substantially with the seasonal variations in light and nutrient availability. Therefore, although chlorophyll observations are widely available, they are not a good proxy for phytoplankton biomass.
Net Primary Production (NPP) and Chl are positively associated, both at subarctic and subtropical sites. However, maximal NPP tends to occur near the surface during summer, whereas Chl tends to be maximal under lower-light, higher nutrient conditions, such as at the subsurface chlorophyll maxima that persistently occur in the subtropical ocean. Therefore, Chl concentration is not a good proxy for primary production.
Modelled relationships between Chl and NPP differ substantially with the degree of environmental variability among sites, and with depth. Modeled and observed patterns are broadly similar for stations BATS and HOT, but the model underestimates variability, particularly in the subsurface below the mixed layer. Likely reasons for this include: 1) the climatological forcing as applied cannot resolve interannual nor other short-term variability, 2) the model does not resolve the different trait values and responses of the different species that dominate at different depths, nor seasonal shifts in community composition. These results give some indications about the likely trends in phytoplankton response that can be expected with changing climate.
References
[1] Masuda Y. et al. (2021) Photoacclimation by phytoplankton determines the distribution of global subsurface chlorophyll maxima in the ocean. Comm. Earth Environ. 2.1 (2021): 128.
[2] Masuda Y. et al. (2023) Acclimation by diverse phytoplankton species determines oceanic carbon to nitrogen ratios. Limnol. Oceanogr. Lett. 8: 519-528.
Environmental gradients of light, nutrients and temperature fluctuate persistently within the marine environment, and in response phytoplankton systematically adjust their physiology and hence alter their chemical composition and pigment content. This process, termed photo-acclimation, is captured by a wide variety of phytoplankton models, which are now commonly incorporated into marine biogeochemical and even Earth System Climate Models. Including photo-acclimation in models can substantially improve the representation of key observables, by for example better capturing the observed global scale distributions of chlorophyll (chl) [2] and oceanic carbon to nitrogen ratios [3]. Understanding how such key observables depend on underlying environmental variability is important for interpreting observed patterns as well as for testing model formulations to be used for future projections and other predictive modeling, including simulations to inform the planning and design of observations.
Model
The FlexPFT model, embedded in an updated, higher-resolution version otherwise similar to a recent 3D global setup [1, 2] calculates dynamic variations in the composition of phytoplankton, quantified by the C:N:chl ratios of biomass, and their primary production. Phytoplankton growth tends to be limited by light and iron limitation at subarctic station K2, but persistent nitrogen limitation is observed (and modeled) at subtropical station S1. Results from the 3D model were extracted for stations K2 and S1, as well as for other time-series observation sites, including subarctic stations HOT and BATS. Model results are analyzed to understand how seasonal and other variations in the light and nutrient environment impact the modeled composition and productivity of phytoplankton.
Results
Modeled phytoplankton C:N ratios are higher at subtropical compared to subarctic sites, as observed, and they are more closely related to nitrate concentrations than to light levels. At low nitrate concentrations, C:N ratios are persistently high with a narrow range of variability. At higher nitrate concentrations, C:N ratios tend to be lower, but with substantially greater variability, reflecting differing degrees of light limitation (seasonally and with depth). Modeled chl:C ratios are strongly and directly related to modeled C:N ratios, because the model accounts for the use of both nitrogen and energy to synthesize chlorophyll. Modeled chlorophyll concentrations and the ratio of Chl:C in biomass both vary substantially with the seasonal variations in light and nutrient availability. Therefore, although chlorophyll observations are widely available, they are not a good proxy for phytoplankton biomass.
Net Primary Production (NPP) and Chl are positively associated, both at subarctic and subtropical sites. However, maximal NPP tends to occur near the surface during summer, whereas Chl tends to be maximal under lower-light, higher nutrient conditions, such as at the subsurface chlorophyll maxima that persistently occur in the subtropical ocean. Therefore, Chl concentration is not a good proxy for primary production.
Modelled relationships between Chl and NPP differ substantially with the degree of environmental variability among sites, and with depth. Modeled and observed patterns are broadly similar for stations BATS and HOT, but the model underestimates variability, particularly in the subsurface below the mixed layer. Likely reasons for this include: 1) the climatological forcing as applied cannot resolve interannual nor other short-term variability, 2) the model does not resolve the different trait values and responses of the different species that dominate at different depths, nor seasonal shifts in community composition. These results give some indications about the likely trends in phytoplankton response that can be expected with changing climate.
References
[1] Masuda Y. et al. (2021) Photoacclimation by phytoplankton determines the distribution of global subsurface chlorophyll maxima in the ocean. Comm. Earth Environ. 2.1 (2021): 128.
[2] Masuda Y. et al. (2023) Acclimation by diverse phytoplankton species determines oceanic carbon to nitrogen ratios. Limnol. Oceanogr. Lett. 8: 519-528.