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Climate forcing of phytoplankton dynamics in Chesapeake Bay

dc.contributor.advisorHarding, Jr., Lawrence Wen_US
dc.contributor.authorMiller, William Daviden_US
dc.date.accessioned2006-09-12T05:33:25Z
dc.date.available2006-09-12T05:33:25Z
dc.date.issued2006-05-23en_US
dc.identifier.urihttp://hdl.handle.net/1903/3705
dc.description.abstractClimate has long been recognized as an important driver of phytoplankton dynamics. In Chesapeake Bay, climate variability is manifest as differences in timing and magnitude of freshwater flow. Interannual differences of freshwater flow influence phytoplankton through effects on light and nutrient distributions. Understanding how climate forces temporal and spatial patterns of phytoplankton biomass (Chla) and primary productivity (PP) is an important area of research as we attempt to predict effects of climate change and nutrient enrichment on estuarine ecosystems. This Dissertation describes climate forcing of Chla and PP using a synoptic climatology to quantify climate variability and ocean color remote sensing to assess phytoplankton variability. I developed a synoptic climatology using surface sea-level pressure data for the eastern United States to characterize regional climate because large-scale climate indices are not strongly expressed in this region. The long time series (1989-2004) of remotely sensed ocean color measurements provided high spatial and temporal resolution that allowed me to resolve interannual differences of Chla and PP. I show that the frequency-of-occurrence of synoptic-scale weather patterns during winter explained 54% of the variance in spring freshwater flow to Chesapeake Bay through interannual differences in precipitation and water storage in the basin as snow and ice. Winter weather patterns were also linked to interannual variability of several characteristics of the spring phytoplankton bloom (timing, position, magnitude) through their effects on precipitation and freshwater flow. Multiple linear regression models of winter weather pattern frequencies on regional Chla explained between 23-89% of the variance of the time series. Climate variability in winter-spring also influenced summer and annual integral production through nutrient loading associated with the spring freshet, explaining between 43-62% of the variance of integral production. Finally, I quantified the effects of Hurricane Isabel on Chesapeake Bay phytoplankton dynamics and showed that event-scale climate perturbations can have significant impacts on ecosystem dynamics as well as seasonal and regional carbon cycling. Together these analyses highlight the importance of climate forcing of Chla and PP in Chesapeake Bay and support predictive models that explain significant amounts of the variance of these important ecosystem properties.en_US
dc.format.extent4963439 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleClimate forcing of phytoplankton dynamics in Chesapeake Bayen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentMarine-Estuarine-Environmental Sciencesen_US
dc.subject.pqcontrolledBiology, Oceanographyen_US
dc.subject.pqcontrolledBiology, Ecologyen_US
dc.subject.pqcontrolledRemote Sensingen_US
dc.subject.pquncontrolledphytoplanktonen_US
dc.subject.pquncontrolledclimateen_US
dc.subject.pquncontrolledremote sensingen_US
dc.subject.pquncontrolledChesapeake Bayen_US


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