| Summary: | Thesis (Ph.D.)--University of Washington, 2016-12 Ecologists have long been striving to learn what drives the productivity of populations, communities, and ecosystems. Such an understanding can contribute to both basic science and the practical management of renewable resources, where measuring and detecting changes in productivity is still an important but challenging component of understanding and managing natural resources. Productivity integrates several basic natural processes acting on a population: mortality, growth, reproduction, and migration. This makes measuring productivity a useful tool to guide management advice and to serve as an indicator of ecological changes. However, because productivity integrates so many diverse processes, separating out contributions of different sources of variability is quite difficult, especially in large complex ecosystems. In this dissertation, I pursue four distinct lines of research related to these themes, taking a broad approach and utilizing a variety of quantitative tools. The first three chapters examine how predation influences population productivity of exploited fish populations, both exploring the performance of established methods to detect the effect of size-structured predation, while also developing novel methods and applying considerations of size-structured predation in targeted fisheries. Chapter 1 is an extensive simulation study testing detectability of a predation signal in productivity time series, the second chapter attempts to conduct a meta-analysis of predation on mid-trophic level species across the North Atlantic and North Pacific, and the third chapter uses deterministic age-structured models to examine predation by lingcod on rockfish in the California Current. The fourth chapter explores natural abiotic drivers of productivity while carefully propagating all sources of measurement error in coastal temperate rainforests of Southeast Alaska, using an exceptional dataset on forest growth following logging. These chapters all emphasize the ...
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