Spatio-Temporal Dynamics Of Phytoplankton Biomass From Ocean Color Remote Sensing And Cmip5 Model Suites

• Main Author: Sharma, Priya
• Format: Text
• Language: English
• Published: ScholarlyCommons 2018
• Subjects: ENSO; Long-term Trend; Phytoplankton Biomass; Phytoplankton Functional Types; Seasonality; Spatio-temporal; Climate; Ecology and Evolutionary Biology; Environmental Indicators and Impact Assessment; Environmental Sciences; Pacific; North Atlantic
• Online Access: https://repository.upenn.edu/edissertations/3307; https://repository.upenn.edu/cgi/viewcontent.cgi?article=5093&context=edissertations

Phytoplankton are the base of the marine food web, and, importantly, drive the biological carbon pump, the combination of photosynthesis, organic carbon sinking and subsurface decomposition of organic matter which effectively sequesters carbon away from the atmosphere. Our knowledge of phytoplankton activity is currently advancing fast through developments of multiple ocean-color remote sensing algorithms and via developments in ecological modules incorporated in climate models. While climate models are projecting relatively clear trends in ocean ecology over the next century, distinguishing between interannual variability and ocean biology trends from satellite observations is difficult. Short record length, satellite data continuity issues and strong interannual variability all impact quantified trends. Additionally, commonly observed chlorophyll-a is not strictly indicative of underlying phytoplankton biomass because of phytoplankton adaptation. This thesis investigates the trends, interannual variability and seasonality in new size-partitioned phytoplankton biomass products, with a focus on the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) mission period (1997-2010). In Chapter 2 we found phytoplankton biomass increases in the warm ocean regions over this period, opposing common expectations of decreases in warming oceans. Biomass increases are due to increased physical mixing of the watercolumn and are partially attributed to the large scale El Nino Southern Oscillation (ENSO) phenomenon. Recent studies have highlighted the emergence of different types of ENSO, with a shift towards more Central Pacific ENSO events. Chapter 3 uses statistical techniques (agglomerative hierarchical clustering (AHC), empirical orthogonal functional analysis (EOF)) on phytoplankton biomass to characterize ENSO “flavors” in the tropical Pacific. For the first time, we empirically derive biological indices for different ENSO types and show high correlations with existing climate indices. In Chapter 4 we examine in depth seasonal in phytoplankton ecology between the North Eastern Pacific subpolar region and contrast it with North Atlantic subpolar ecology. We discuss drivers of biological changes (iron, nutrients, light, mixing). We reveal large differences between biological variables across ocean-color algorithms, as well as across the latest generation Earth System model suite (Carbon Model Intercomparison Project, CMIP5). Chapter 5 summarizes our findings and future work suggestions. Future work should link surface phytoplankton ecology to ocean-atmosphere carbon fluxes and ocean carbon pump efficiency.