Particles, prey, and purse seines: A data-driven investigation into the impacts of climate on biological processes across the global ocean

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Leung, Shirley Wing

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In this dissertation, I use existing large-scale public datasets to examine how climate variability and change affect ecosystem processes throughout the global oceans, with some emphasis on the Tropical Pacific because of the abundance of culturally and economically important top pelagic predator species such as tuna and billfish here. The objectives of this work are to illuminate the effects of climate on marine ecosystems, as well as to quantify and reduce uncertainties in current stock assessment and global ocean models. In Chapter 2, I use an empirically-constrained 3-D global ocean model to show that more detailed modeling of phytoplankton sizes and sinking particles can have a considerable effect on the accuracy of climate change-driven projections of particulate carbon export, which can in turn greatly affect projections of future carbon storage, mesopelagic biomass availability, and subsurface oxygen concentrations. In Chapter 3, I use in situ measurements of oxygen and temperature to show that El Niño-Southern Oscillation (ENSO) is the primary driver of large variations in upper-ocean oxygen content on interannual time scales in the Tropical Pacific. Oxygen therefore likely plays an important role in altering tuna habitat quality and available vertical habitat space between different phases of ENSO here. In Chapter 4, I show that of all global ocean regions, climate warming-driven deoxygenation over the next century will most greatly affect species residing in the temperate North Pacific (including swordfish and yellowfin, bigeye, Pacific bluefin, and albacore tunas), where projected decreases in oxygen concentrations between 200-700 m depth are greatest and most certain. Conversely, the smallest and least certain projections of subsurface oxygen concentration changes and effects occur within the tuna-rich Tropical Pacific, where more attention should be focused on improving model representations of underlying ocean circulation dynamics. In Chapter 5, I analyze purse seine catch and effort data to determine where and when fishers targeting fish aggregating device (FAD)-associated skipjack tuna can most effectively reduce incidental juvenile bigeye tuna catches. Though FAD-associated skipjack and bigeye tend to strongly co-occur, there are significant variations in their lateral separability over both space and time, especially between different phases of ENSO. El Niño lowers fractional incidental bigeye catch east of ~170°E and raises it to the west, while La Niña has the opposite effect. Spatial patterns in sea surface height anomalies, which also vary greatly with ENSO, may be useful in separating different habitats preferred by skipjack and bigeye throughout the Western Tropical Pacific. In Appendix A, I show that ENSO also drives sizable variations in micronektonic prey availability and diel vertical migration depths throughout the Tropical Pacific. As was the case with subsurface oxygen concentrations, these variations in prey availability likely substantially alter tuna habitat quality between different ENSO phases and should therefore be considered in temporally-resolved habitat and stock assessment models. Collectively, this body of work has demonstrated the following three points: Firstly, climate variability and change can have profound effects on marine ecosystem processes on all scales, from the size and sinking speed of particles to the spatial distributions of top pelagic predators and their relationships with other species, including humans. Secondly, there are many ways to improve the accuracy of models, including better accounting for small-scale processes with large effects, better constraining difficult-to-parameterize relationships with observational data, and better resolving biologically relevant environmental conditions. Finally, many important and interesting research questions can be answered using already-existing public domain data analyzed in new and creative ways.

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Thesis (Ph.D.)--University of Washington, 2020

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