Springs As Models to Unveil Ecological Drivers and Responses: Perspectives for Ecosystem Theory from Neglected Ecosystems
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Springs as models to unveil ecological drivers and responses: Perspectives for ecosystem theory from neglected ecosystems Dissertation zur Erlangung des akademischen Grades Doctor rerum naturalium (Dr. rer. nat.) an der Fakultät für Biologie, Chemie und Geowissenschaften der Universität Bayreuth vorgelegt von Andreas Hubert Schweiger geboren am 11.08.1984 in Garmisch-Partenkirchen, Deutschland Bayreuth, im Februar 2016 Die vorliegende Arbeit wurde in der Zeit von Februar 2013 bis Februar 2016 in Bayreuth am Lehrstuhl für Biogeografie unter Betreuung von Herrn Professor Dr. Carl Beierkuhnlein angefertigt. Vollständiger Abdruck der von der Faklutät für Biologie, Chemie und Geowissenschaften der Universität Bayreuth genehmigten Dissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. Nat.). Dissertation eingereicht am: 05.02.2016 Zulassung durch die Promotionskommission: 17.02.2016 Wissenschaftliches Kolloqium: 15.08.2016 Amtierender Dekan: Prof. Dr. Stefan Schuster Prüfungsausschuss: Prof. Dr. Carl Beierkuhnlein (Erstgutachter) Prof. Dr. Konrad Dettner (Zweitgutachter) Prof. Dr. Stefan Peiffer (Vorsitz) PD. Dr. Gregor Aas (Drittgutachter: Prof. Dr. Holger Kreft) - ii - “Es gibt nichts Praktischeres als eine gute Theorie.” (Nothing is as practical as a good theory) Immanuel Kant - iii - - iv - Contents 1 Introduction ............................................................................................. 1 1.1 My motivation and theoretical background for this thesis ............................... 1 1.2 Structure of this thesis ....................................................................................... 3 1.3 Springs as neglected model ecosystems ........................................................... 7 1.3.1 Current knowledge about springs .................................................................................... 7 1.3.2 Springs as model ecosystems ......................................................................................... 11 1.4 The role of theory in ecology (then and now) ................................................. 18 1.5 The different theoretical perspectives in ecology ........................................... 20 1.6 Complex adaptive systems theory as holistic perspective .............................. 22 1.7 The major principles of complex adaptive systems theory in ecology ........... 24 1.7.1 Diversity and organisation of biotic system elements ................................................... 26 1.7.2 Flow, distribution and interaction of information, energy and matter ........................... 28 1.7.3 Stability and non-linearity .............................................................................................. 31 1.7.4 Scale-dependence ........................................................................................................... 34 1.7.5 Path-dependence ............................................................................................................ 38 1.8 Methodological requirements for testing the complex adaptive systems theory in ecology: The role of long-term monitoring and sampling design .................... 39 2 Synthesis ............................................................................................... 43 2.1 The manuscripts of this thesis ......................................................................... 43 2.2 Outlook on emerging research challenges ...................................................... 48 3 References in introduction and synthesis ............................................. 52 4 Declaration of own contribution to each manuscript ........................... 67 5 Manuscripts ........................................................................................... 69 5.1 Manuscript 1 .................................................................................................... 69 5.2 Manuscript 2 .................................................................................................... 87 5.3 Manuscript 3 .................................................................................................. 103 - v - 5.4 Manuscript 4 .................................................................................................. 127 5.5 Manuscript 5 .................................................................................................. 141 5.6 Manuscript 6 .................................................................................................. 159 6 Summary ............................................................................................. 183 7 Zusammenfassung .............................................................................. 185 8 Acknowledgements............................................................................. 187 9 Appendix ............................................................................................. 188 10 Declarations ...................................................................................... 191 - vi - Motivation 1 Introduction 1.1 My motivation and theoretical background for this thesis “It is important to define the central goal of ecological research before discussing how such work should be done” David Tilman (1989, p. 136). The improvement of understanding is the general goal of science (Kuhn 1962, Picket et al. 2007). The primary objective in ecology is to understand “the processes influencing the distribution and abundance of organisms, the interaction among organisms, and the interaction between organisms and the transformation and flux of energy and matter” (Likens 1992). This broad definition of ecology as a scientific discipline integrates two major perspectives, the organismal as well as the systemic perspective. Whereas the organismal perspective has a strong focus on processes acting among single organisms or species (thus system elements) (Morin 2011) the systemic perspective strongly focuses on the distribution and fluxes of material, energy and information regulated by ecosystems (Margalef 1975, Abel 1998, Beierkuhnlein 2007). Another general goal of science is consilience, meaning the synthesis of knowledge (Wilson 1998, Grace 2015). Ecology as scientific discipline has a rather broad focus which would in principle favour the integration of knowledge. However, ecological research often appears as a series of case studies in isolated sub-disciplines with loose relation to each other (Picket et al. 2007). Among all disciplines of science, biology (including ecology) is the fastest evolving science of the last two centuries (Collins 2011). Concomitant with this fast development of ecology, numerous sub-disciplines with differing perspectives, concepts and theories have emerged (McIntosh 1987, Kolasa 2011). This increasing divergence during the development of ecology led amongst others to community ecology, dealing with the interaction of organisms without considering system aspects (fluxes of information, energy and matter in systems) and systems ecology, focusing on the systems perspective but ignoring the idiosyncrasies at the organismic level (Picket et al. 2007). This divergence into sub-disciplines increases detailed understanding in the particular sub-disciplines of ecology but at the same time diminishes scientific progress towards general concepts (Marquet et al. 2014). Scientific progress leading to the overall understanding about the processes which maintains the functioning of complex ecological systems is a prerequisite when we want to pursue consilience in ecology. Although the divergence of ecology in different sub-disciplines might be a natural process related to the evolution of systems, a general, integrative understanding of ecosystem functioning is nowadays more topical than ever. Ongoing anthropogenic intervention changes ecosystem functioning and, thus, service provisioning. However, predictions about these changes, which are a prerequisite to counteract these developments, lack in generality and, thus, are characterized by high uncertainty. This high uncertainty of predictions, which impedes concrete proposals to counterbalance negative developments, can be reduced - 1 - Motivation by increasing generality in ecological understanding. When aiming for an integrative ecological understanding, combining organismal and systemic perspectives is assumed to open promising perspectives towards a truly integrative ecology (Picket et al. 2007). Already Brown (1995) suggested that community ecology and systems ecology need to be brought together. In this thesis I want to pursue this philosophy by integrating the two perspectives conceptualized in community and systems ecology. The technological progress during the last decades (e.g. next generation sequencing, high resolution remote sensing via satellites, increasing computational power) increased our ability to collect and analyse ecological data across large spatial, temporal and organismal scales. This vast amount of data, however, generates new challenges for ecology as a scientific discipline (Marquet et al. 2014). Proper theoretical frameworks are needed to prevent ecology from “drowning in [this] sea of data” (Brenner 2012, p. 461). An integrative theory is, thus, a prerequisite when aiming for a comprehensive understanding of ecological processes and patterns (Picket el al. 2007, Scheiner & Willig 2011). Searching for such kind of integrative theory, I decided to use the theory of complex adaptive systems as a theoretical framework for my thesis.