Predator prey dynamics under the influence of exogenous and endogenous regulation [Elektronische Ressource] : a data based modeling study on spring plankton with respect to climate change / Katrin Tirok

Katrin Tirok

Sujets

• Biologie

Informations

• Publié par: universitat_potsdam
• Publié le: 01 janvier 2008
• Nombre de lectures: 13
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Predator preydynamics under the influence
of exogenous and endogenous regulation
A data based modeling study on spring plankton
with respect to climate change
Ph.D. Thesis
Katrin Tirok
Dept. of Ecology and Ecosystem Modelling
University of Potsdam
2008Institut für Biochemie und Biologie
Arbeitsgruppe Ökologie und Ökosystemmodellierung
Predator prey dynamics under the influence of exogenous and endogenous
regulation: A data based modeling study on spring plankton with respect
to climate change
Dissertation
zur Erlangung des akademischen Grades
„doctor rerum naturalium“
(Dr. rer. nat.)
in der Wissenschaftsdisziplin „Ökologie“
eingereicht an der
Mathematisch Naturwissenschaftlichen Fakultät
der Universität Potsdam
von
Katrin Tirok
Potsdam, den 30. Juni 2008













































Online published at the
Institutional Repository of the Potsdam University:
http://opus.kobv.de/ubp/volltexte/2008/2452/
urn:nbn:de:kobv:517-opus-24528
[http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-24528] Contents
Contents i
General Introduction v
1 The effect of irradiance, vertical mixing and temperature on spring
phytoplankton dynamics under climate change: long term obser-
vations and model analysis 1
1.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.7 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
1.8 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
1.9 Appendix: model equations . . . . . . . . . . . . . . . . . . . . 35
2 Spring phytoplankton dynamics depend on temperature, cloudi
ness, grazing and overwintering biomasses - a process oriented
modeling study based on mesocosm experiments 39
2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
2.6 Acknowldedgments . . . . . . . . . . . . . . . . . . . . . . . . 56
2.7 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
iii CONTENTS
2.8 Appendix: model equations . . . . . . . . . . . . . . . . . . . . 63
3 Regulation of planktonic ciliate dynamics and functional composi
tion during spring in Lake Constance 69
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.3 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . 74
3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 85
3.7 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.8 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4 Endogenous alternation of functional traits yields compensatory
dynamics in a multi species predator prey system 97
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
4.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
4.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 118
4.7 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
4.8 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
4.9 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5 Reflecting functional diversity and adaptability in dynamic models
modifies predator prey dynamics 131
5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
5.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
5.6 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
5.7 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
5.8 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
General Discussion 163iii
Summary 167
Bibliography 169
Declaration 183
Danksagung 185General Introduction
Understanding the interactions of predators and their prey is one of the striking
features of ecological research until today. Predator prey interactions are the ba
sis of food webs which are influenced by exogenous and endogenous regulation.
For example, resource limitation which reduces the production of a prey commu
nity and thus, also that of the predator community represents exogenous regula
tion. On the other hand, regulation mechanisms act within a single predator prey
relationship and shape this relationship, here referred to as endogenous regula
tion.
In this thesis, I considered the spring dynamics of phytoplankton and its con
sumers, zooplankton, in dependence on environmental conditions in a large deep
lake (Lake Constance) and in mesocosms resembling a shallow marine water
(Kiel Bight, Baltic Sea). Spring plankton development is known to be closely
linked to abiotic variables such as global irradiance and temperature (Tilzer et al.,
1986, Straile, 2000), and in deep waters, additionally, wind induced vertical mix
ing intensity (Gaedke et al., 1998b, Waniek, 2003). In contrast, the termination
of the spring bloom, resulting in a so called “clear water phase”, is often caused
by increased grazing of zooplankton (protozoans, rotifers, crustaceans) (Sommer
et al., 1986, Lampert et al., 1986, Talling, 2003, Tirok and Gaedke, 2006). Pro
tozoans are among the most important grazers of phytoplankton (Müller et al.,
1991, Gaedke and Straile, 1994, Neuer and Cowles, 1994) and remineralizers of
nutrients (Sonntag et al., 2006) in marine and freshwater ecosystems. In Lake
Constance, ciliates dominate the herbivorous zooplankton in spring, when crus
taceans are still hampered by low temperatures (Müller et al., 1991, Weisse and
Müller, 1998). In the mesocsom experiments from shallow Kiel Bight, ciliates
and copepods exert a decisive grazing pressure on phytoplankton during spring
(Aberle et al., 2007, Sommer et al., 2007, Sommer and Lengfellner, 2008).
To conclude, the beginning and the end of the spring bloom typically undergoes
vvi GENERAL INTRODUCTION
exogenous regulation, whereas during the spring bloom endogenous processes
drive the dynamics of phytoplankton and zooplankton (mainly ciliates). The
timing, duration, and interplay of the different periods depend on environmental
drivers and thus, are supposed to be affected by the ongoing climate change.
Climate Change
We anticipate that climate change will have far reaching consequences for the
functioning of planktonic food webs, which are currently poorly understood. Cli
◦mate models predict substantial warming during the winter and spring (1–5.5 C),
increasing storm activity, and decreasing cloudiness during the years 2070–2100
as compared to 1960–1990 in Western and Central Europe (IPCC, 2001, Giorgi
et al., 2004, Leckebusch and Ulbrich, 2004). Higher air temperatures imply
higher water temperatures (George and Hewitt, 1999, Straile, 2000), which will
directly enhance heterotrophic processes such as zooplankton activity and algal
respiration, but may leave others undisturbed, e.g., primary production, which
is primarily regarded as light limited in spring (Tilzer et al., 1986). This may
lead to changed synchronies in the growth and activity patterns of the differ-
ent components of the plankton community and to a potential mismatch in the
demand supply relationship between consumers and their food organisms.
This thesis aims to entangle the different effects driving the spring dynamics
of phytoplankton and zooplankton using statistically based data analyses and
process oriented simulation models to get detailed insight into the exogenous
and endogenous regulation mechanisms.
Modeling plankton food webs
With the help of mathematical models, it is possible to enhance our insights into
ecological mechanisms, and to predict responses to environmental changes, e.g.,
climate change. However,