DIPLOMARBEIT Titel der Diplomarbeit Climatic thresholds for ecosystem stability: The case of the Western Congolian Lowland Rainforest Verfasser Johannes Elias Bednar angestrebter akademischer Grad Magister der Naturwissenschaft (Mag.rer.nat) Wien, 2011 Studienkennzahl lt. Studienblatt: A 411 Studienrichtung lt. Studienblatt: Physik Betreuerin / Betreuer: Univ. Prof. Dipl.-Ing. Dr. Hubert Hasenauer Abstract The heterogeneity in the composition of species and the mix of forest ecosystems of the present tropical flora in western Central Africa has been subject of many publications. Most of the authors agree on the idea that changing climatic conditions in the past have led to disturbances that subsequently caused different stages in plant succession in the present picture. This work's aim is to find out which climatic parameters have a significant impact on the stability of tropical forest ecosystems, such as the showcase biome of the Western Congolian Lowland Rainforest (WCLR). Using the stochastic weather generator MarkSim, climate time series with quantified meteorological parameters, such as the amount and year-to-year variation of annual rainfall, the distribution of rainfall within the year and the quality of the cloud cover, are generated. For this reason MarkSim is adapted and validated for sites in Gabon where the WCLR-biome is native. The mechanistic ecosystem model Biome-BGC, parametrized for the WCLR-biome, simulates the cycling of water, energy, carbon and nitrogen through different plant compartments and is applied to asses tropical forest ecosystem stability, based on the climate time series generated with MarkSim. The methods developed in the course of this work are applicable to other forest ecosystems and can be regarded as an innovative approach to assess the impact of climatic change. I Zusammenfassung Die Heterogenität der Artenzusammensetzung, sowie der Waldökosystemgefüge der heutigen tropischen Flora im westlichen Zentralafrika ist Thema vieler Publikationen. Ein Großteil der Autoren gibt Veränderungen des Klimas, welche in Folge zu Störungen dieser Systeme führten, die Verantwortung für die heute bestehenden unterschiedlichen sukzessionalen Stadien tropischer Wälder. Zielsetzung dieser Arbeit ist es, anhand des Beispielbioms Westkongolesischer Tieflandregenwald (WCLR) den Einfluss klimatischer Parameter auf die Stabilität tropischer Waldökosysteme zu untersuchen. Der stochastische Wettergenerator MarkSim wird benutzt um Klimazeitserien mit quantifizierten klimatischen Parametern, wie die Gesamtniederschlagsmenge, die jährliche Variation des Niederschlags, die Verteilung des Niederschlags über das Jahr sowie die Art der Wolkendecke, zu generieren. Zu diesem Zeck wird MarkSim für Gabun, welches das WCLR-Biom beheimatet, adaptiert und validiert. Das für das WCLR-Biom parametrisierte mechanistische Ökosystemmodell Biome-BGC simuliert die Kreisläufte von Wasser, Energie, Kohlenstoff und Stickstoff durch unterschiedliche Bestandteile eines Waldökosystems, und wird zur Abschätzung der Stabilität solcher Systeme basierend auf den zuvor generierten Klimaten herangezogen. Die im Zuge dieser Arbeit entwickelten Methoden lassen sich auch auf andere Typen von Waldökosystemen übertragen und können als innovativer Ansatz zur Bewertung des Einflusses klimatischer Veränderungen auf diese Systeme erachtet werden. II Acknowledgement I would like to show my sincere gratitude to Dr. Stephan Pietsch for his inspiration and enthusiasm and his great efforts to explain things clearly and simply which helped a lot to enter a new field of science. Throughout my thesis-writing period he provided excellent ideas and most of all, good company. It was a honor for me to travel with him and get to know his lovely family. I am very grateful to Prof. Hubert Hasenauer who's motivation, and advice in structural questions helped me in all the time of research and writing of this thesis. This work would not have been possible without the support of Dr. Richard Petritsch, who provided aid to solve countless computational tasks. I would have been lost without his advice. Besides my advisors at the Boku University, I would like to thank the rest of my Professors at the University of Vienna, I owe special thanks to Prof. Helmuth Horvath who agreed to join my board of examiners. I am indepted to my fellow students and friends Martin Diermaier, who has found a research group for me, and Lukas Pichelstorfer, flatmate and close friend for many years. I wish to thank my entire extended family for providing a loving environment for me. My girlfriend Miriam Bammer, my half-sister Katharina Urbanek, and her mother Lisa Urbanek were particularly supportive. Most importantly I want to thank my parents, Waltraud Bednar and Hans Bednar. They bore me, raised me, taught me, and loved me. To them I dedicate this thesis. It is a pleasure to thank the many people who made this thesis possible. III Table of Contents 1 Introduction...................................................................................................................................1 1.1 Background...........................................................................................................................1 1.2 Availability of climate records in Gabon ................................................................................3 2 Goals............................................................................................................................................4 3 Methods.......................................................................................................................................6 3.1 Weather generators.............................................................................................................6 3.1.1 Why to use weather generators?...................................................................................6 3.1.2 MarkSim: A probabilistic weather generator...................................................................7 3.2 Biome-BGC: A biogeochemical ecosystem model................................................................8 4 Data............................................................................................................................................10 5 Analysis and improvements........................................................................................................15 5.1 Validating and correcting stochastic climate for Gabon.......................................................15 5.1.1 Comparison of international tropical sites with sites in Gabon.....................................15 5.1.2 Correction of daily solar radiation and maximum temperature.....................................20 5.1.3 Validation of generated climate using data from three weather stations .....................21 5.1.4 Evaluating the distribution of annual rainfall................................................................32 5.2 Customizing climate for BGC-simulations ..........................................................................33 5.2.1 Customizing dry season and annual rainfall................................................................34 5.2.2 Climate for Biome-BGC simulations............................................................................36 5.2.3 Climatic parameters and varieties for BGC-simulations...............................................42 6 Results.......................................................................................................................................43 6.1 Testing ecosystem stability under different climatic conditions............................................43 6.1.1 Methodical approach...................................................................................................44 6.1.2 Two concepts to approach a stable state.....................................................................45 6.1.3 Spinup simulations......................................................................................................46 6.1.4 Spindown simulations..................................................................................................64 6.1.5 Hysteresis (spinup vs. spindown)................................................................................80 7 Discussion..................................................................................................................................83 8 Bibliography................................................................................................................................85 APPENDIX A - MarkSim file structure.............................................................................................89 APPENDIX B - Statistical methods ................................................................................................91 B.1 Test for normality.................................................................................................................91 B.2 Testing predicted vs. observed............................................................................................91 Confidence (CI) and prediction-interval (PI) for residuals......................................................91 Pearson's linear correlation coefficient & sample mean error................................................92 B.3 Box-and-whiskers plot.........................................................................................................93 IV B.4 Logistic regression analysis.................................................................................................93