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Utilizing holistic ecosystem indices to explore ecosystem structure and function and improve fisheries management strategies

  • Author(s): Schlenger, Adam James
  • Advisor(s): Ballance, Lisa
  • Leichter, James
  • et al.

The extent of anthropogenic impact on the world has reached has reached the point where humans are fundamentally disrupting the natural structure and function of entire ecosystems. The need to mitigate, restore, and protect natural ecosystems has become a critical issue throughout the world. However, the sheer scale and complexity of ecosystems makes this a difficult problem to solve. Over the past few decades, modern ecology has risen to the challenge by adopting a holistic approach to the study of ecosystems. This holistic perspective incorporates the nonlinear processes, indirect effects, and emergent properties that play a major role in ecosystem behavior. Ecosystems are hierarchal, self-organizing networks, driven by the flow of energy and material. A central focus of this viewpoint emphasizes the philosophy that the whole is more than the sum of its parts and this depiction of ecosystems has shed light on the existence of a general set of driving principles amongst a seemingly endless sea of variables and unknowns. A holistic approach to ecology simplifies the challenges of scale and complexity to allow scientists and managers to tackle ecological issues around the globe.

Chapter 1 of this dissertation constitutes a literature review synthesizing some of the major advancements of modern ecology and the development of a holistic approach to ecosystem research. Ecosystems were placed in the context of complex adaptive systems, focusing on the important structural, functional, and mathematic properties that lead to a set of common emergent properties. The role of thermodynamics in driving ecosystem behavior is then presented along with the application of information theory to develop a conceptual framework for the interactions between components of an ecosystem and how that influences their holistic behavior. Finally, a wide variety of mathematically derived indices of ecosystem structure, function, and organizational complexity are presented. These indices represent approaches from a number of different disciplines that have been applied to the development of modern ecological theory.

Chapter 2 outlines a study aimed at identifying the major drivers of ecosystem structure and function. We used 24 synthetic ecosystem-level indices derived from trophic models, and independently-derived data for net primary productivity, to investigate drivers of ecosystem structure and function for 43 marine ecosystems distributed in all oceans of the world and including coastal, estuaries, mid-ocean islands, open-ocean, coral reef, continental shelf, and upwelling ecosystems. Of these indices, ecosystem Biomass, Primary Production, Respiration, the ratio of Biomass to Total System Throughput (sum of total energy flow into and out of an ecosystem as well as between ecosystem components), the ratio of Production to Biomass, Residence Time (mean time that a unit of energy remains in the ecosystem), Average Trophic Level, and Relative Ascendency (index of organization and complexity of a food web) displayed relationships with measures of net primary productivity (NPP). Across all ecosystems, relationships were stronger with seasonal and interannual variability of NPP as compared to mean NPP. Both measures of temporal variability were combined into multivariate predictive relationships for each ecosystem index, with r2 values ranging from 0.14 to 0.49 and Akaike’s Information Criteria values from -8.44 to 3.26. Our results indicate that despite large geographical and environmental differences, temporal variability of NPP is strongly linked to the structure and function of marine ecosystems.

Chapter 3 builds off of chapter 2 by utilizing the multi-dimensional relationship between variability in NPP and biomass to predict future changes in global biomass distributions under future climate change scenarios. Estimates of variability in NPP were calculated using output from three earth system models (ESMs) to quantify historic distributions of biomass. Similarly, these ESMs were used to quantify future estimates of NPP and subsequent biomass predicted under Representative Concentrations Pathways (RCPs) 4.5 and 8.5. Biomass anomalies between historic estimates and future predictions show very little change in mean global Biomass, but much larger localized anomalies were observed of approximately -200% to 200%. Locations displaying large regional changes include the north Atlantic, Arctic, and eastern tropical Pacific. These results provide useful information concerning which areas of the world that might be the most vulnerable at an ecosystem scale.

Chapter 4 constitutes a heuristic approach to bioeconomic modeling to optimize fishery management strategies in the eastern tropical Pacific. Linking the economic and biological components of human interactions with natural systems is a vital part of effective fisheries management. This study utilized a trophic network model of the eastern tropical Pacific to compare multi-species fishery management strategies by varying the efforts of individual fleets to optimize specific policy objectives. This approach highlights the cascading, indirect effects of fishing across an entire ecosystem and incorporates a holistic perspective to quantify their economic and ecosystem health impacts. Results of this study showed that varying management scenarios can lead to a diverse combination of economic and ecosystem health effects. This study also highlighted the potential for different management strategies to achieve similar economic results, but through alternative mechanisms with significantly different ecosystem-level impacts.

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