Numerical model exploration of climate-linked drivers and pathways driving phytoplankton bloom in Puget Sound fjord

Phytoplankton spring blooms fertilize the highly productive Puget Sound fjord. However, the mechanism of phytoplankton spring bloom in Puget Sound is not yet fully understood. The main basin of Puget Sound fjord has been undergoing environmental changes to which climate change is one of the major causes. Climate change has been shown to have a prominent influence on altering the timing and magnitude of phytoplankton blooms. Thus, it is important to understand the response of phytoplankton to changes in climate. The study, first, identifies an adequate biophysical model for the main basin Puget Sound (1-D NPZD model). Then, the study employs the model to explore and classify possible climate-induced drivers and pathways that effect main basin Puget Sound phytoplankton spring blooms. The study investigates phytoplankton spring blooms in metrics of (i) annual primary production, (ii) bloom date. The study also examines (iii) phytoplankton concentration during juvenile salmon (chinook and steelhead) outmigration, and (iv) duration nutrient limitation in summer as part of Puget Sound marine survival rate decline hypotheses. Previous studies in Puget Sound plankton suggested that phytoplankton spring blooms are controlled by light environment. Thus, to describe underwater light field, the study analyses two light-related data sets: Secchi disk depth and beam transmissometer. The analysis results in similar regressions of light attenuation (kd) and phytoplankton concentration (Chla). The regression that uses Secchi disk depth yields slightly better model good fit to observations. The regressions obtained from both Secchi disk depth and beam transmissometer could not distinguish effect of river inputs (represented by salinity) and background water on total underwater light attenuation. This is probably due to rivers run into Puget Sound basin come from diverse watersheds with distinctive sediment properties. Undefined biological parameters in the Puget Sound biophysical model are identified by using parameterisation and sensitivity approaches. Particle swarm optimizer, an opimisation algorithms, proposes numerous parameter sets that produce equal model goodness-of-fit. Among these parameter sets, there are some with contrasting dynamics. Sensitivity analysis is then carried out to classify parameters into the most, moderate and minor impact on model performance. The sensitivity analysis also compares model good fit produced by optimized parameter sets and existing parameters to conclude the new biological parameter set for Puget Sound plankton. Once the Puget Sound biophysical model defined, it is used to explore all possible climate-induced drivers-pathways which are selected based on previous studies of Puget Sound plankton. The study’s outcomes highlight the predominant role of light limitation over nutrient limitation driving spring bloom timings and magnitude. Cloud cover (via light intensity) and riverflow (via mixing mediated by stratification, and also via light attenuation) are suggested to be the first and second order climate drivers of Puget Sound phytoplankton production and bloom date. Processes influencing duration nutrient limitation in summer, however, are more complex. To this metric, nutrient limitation via mixing caused by stratification and riverflow is the major leading mechanism. Moreover, there is a large number of mechanistic pathways (e.g., light limitation via cloud cover, light intensity, via riverflow, stratification, mixing, via riverflow, light attenuation; nutrient limitation via exchange flow, vertical advection) producing the same scale of variation in number of days nutrient is limited in summer.Phytoplankton spring blooms fertilize the highly productive Puget Sound fjord. However, the mechanism of phytoplankton spring bloom in Puget Sound is not yet fully understood. The main basin of Puget Sound fjord has been undergoing environmental changes to which climate change is one of the major causes. Climate change has been shown to have a prominent influence on altering the timing and magnitude of phytoplankton blooms. Thus, it is important to understand the response of phytoplankton to changes in climate. The study, first, identifies an adequate biophysical model for the main basin Puget Sound (1-D NPZD model). Then, the study employs the model to explore and classify possible climate-induced drivers and pathways that effect main basin Puget Sound phytoplankton spring blooms. The study investigates phytoplankton spring blooms in metrics of (i) annual primary production, (ii) bloom date. The study also examines (iii) phytoplankton concentration during juvenile salmon (chinook and steelhead) outmigration, and (iv) duration nutrient limitation in summer as part of Puget Sound marine survival rate decline hypotheses. Previous studies in Puget Sound plankton suggested that phytoplankton spring blooms are controlled by light environment. Thus, to describe underwater light field, the study analyses two light-related data sets: Secchi disk depth and beam transmissometer. The analysis results in similar regressions of light attenuation (kd) and phytoplankton concentration (Chla). The regression that uses Secchi disk depth yields slightly better model good fit to observations. The regressions obtained from both Secchi disk depth and beam transmissometer could not distinguish effect of river inputs (represented by salinity) and background water on total underwater light attenuation. This is probably due to rivers run into Puget Sound basin come from diverse watersheds with distinctive sediment properties. Undefined biological parameters in the Puget Sound biophysical model are identified by using parameterisation and sensitivity approaches. Particle swarm optimizer, an opimisation algorithms, proposes numerous parameter sets that produce equal model goodness-of-fit. Among these parameter sets, there are some with contrasting dynamics. Sensitivity analysis is then carried out to classify parameters into the most, moderate and minor impact on model performance. The sensitivity analysis also compares model good fit produced by optimized parameter sets and existing parameters to conclude the new biological parameter set for Puget Sound plankton. Once the Puget Sound biophysical model defined, it is used to explore all possible climate-induced drivers-pathways which are selected based on previous studies of Puget Sound plankton. The study’s outcomes highlight the predominant role of light limitation over nutrient limitation driving spring bloom timings and magnitude. Cloud cover (via light intensity) and riverflow (via mixing mediated by stratification, and also via light attenuation) are suggested to be the first and second order climate drivers of Puget Sound phytoplankton production and bloom date. Processes influencing duration nutrient limitation in summer, however, are more complex. To this metric, nutrient limitation via mixing caused by stratification and riverflow is the major leading mechanism. Moreover, there is a large number of mechanistic pathways (e.g., light limitation via cloud cover, light intensity, via riverflow, stratification, mixing, via riverflow, light attenuation; nutrient limitation via exchange flow, vertical advection) producing the same scale of variation in number of days nutrient is limited in summer