Monash University
Browse

Restricted Access

Reason: Access restricted by the author. A copy can be requested for private research and study by contacting your institution's library service. This copy cannot be republished

Energy in ecology: merging theory and data

thesis
posted on 2017-02-24, 01:57 authored by Louey Yen, Jian David
A challenge for ecology is to understand the structure and function of ecological communities. While studies of particular species and ecosystems underpin much of ecology, a deeper understanding requires knowledge of processes that are common to all ecological communities. I consider whether a fundamental understanding of ecology might be achieved through a focus on energy, which is common to all ecological systems. I use theory to predict the structure and function of ecological communities from thermodynamic first principles and I use data to determine whether ecological communities respond predictably to local environmental conditions. Much of my work considers the individual size distribution (ISD), which is the distribution of organism sizes in a community, irrespective of species identities. ISDs contain information on energy and resource use but also contain information on abundances and size diversity, which is considered to be a proxy for morphological and physiological trait diversity. For this reason, ISDs are suited to studying both the structure and function of ecological communities. I reviewed existing thermodynamic approaches to ecology and identified several theories but few empirical studies. I developed a broad thermodynamic principle that encompassed existing thermodynamic theories and I used this principle to generate predictions of ISDs. I extended this analysis to predict how organism and community energy use would scale with biomass. This analysis identified density-dependent energy use as a possible mechanism for many observed scaling relationships and generated predictions that were consistent with data on metabolic scaling relationships in organisms and communities. The study of links between ISDs and their local environmental conditions required statistical approaches that could incorporate functions as a response variable (function regression). I developed software for several function regression analyses and used this software to study ISDs along environmental gradients and through time. ISDs changed predictably along environmental gradients and through time, which suggests that consistent ecological rules might regulate ISDs. Changes in ISDs were compared to changes in species abundance distributions (SADs), which measure relative species abundances. ISDs changed more rapidly than SADs, which suggests that size diversity might respond more closely than species diversity to environmental conditions or to stochastic changes in species composition. Although a focus on body size might uncover important ecological processes, many applied ecologists are interested primarily in species-based measures (e.g., species richness). I extended the function regression analyses to test whether ISDs could predict variation in species richness and found strong links between species richness and ISDs. A species richness-ISD relationship suggests that changes in size diversity might underlie changes in species diversity. The results presented in this thesis support a greater focus on size-based measures alongside species-based measures in ecology. The inclusion of body size revealed links between community structure and function and highlighted that size-based measures might reflect changes in ecological communities that are missed by species-based measures. Rebuilding ecology around ISDs would bring together organism, population, community and ecosystem ecology and potentially may move ecologists closer to a fundamental and general understanding of the functioning of ecological systems.

History

Campus location

Australia

Principal supervisor

David Paganin

Additional supervisor 1

Ralph Mac Nally

Additional supervisor 2

James Thomson

Additional supervisor 3

Jonathan Keith

Year of Award

2016

Department, School or Centre

Physics and Astronomy

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Science

Usage metrics

    Faculty of Science Theses

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC