The Pennsylvania State University The Graduate School Department of Geosciences HOW LANDSCAPE DYNAMICS CAN ALTER THE PRESERVATION AND INTERPRETATION OF PALEOENVIRONMENTAL SIGNALS IN FLUVIODELTAIC ENVIRONMENTS A Dissertation in Geosciences by Sheila M. Trampush © 2017 Sheila M. Trampush Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy December 2017 The dissertation of Sheila M. Trampush was reviewed and approved* by the following: Elizabeth Hajek Assistant Professor of Geosciences Dissertation Adviser Chair of Committee Lee Kump Professor of Geosciences Mark Patzkowsky Professor of Geosciences Benjamin Shaby Assistant Professor of Statistics Demien Saffer Professor of Geosciences Head of Graduate Programs and Research in the Department of Geosciences *Signatures are on file in the Graduate School iii ABSTRACT Fluviodeltaic environments are some of the most dynamic sedimentary systems on Earth. They are highly sensitive to changes in external boundary conditions, such as sea level, sediment supply, and climate. In addition, they have a wide range of internally generated (autogenic) sediment transport processes that control where sediment is deposited or eroded over short to intermediate timescales (up to ~105 years). Example of these autogenic processes include channel avulsion or bifurcation. Because of the highly dynamic nature of fluviodeltaic environments, it is hard to predict how they will respond to future changes in sea level and climate. However, they are critical environments for society, and so efforts have focused on better understanding how they have responded to perturbations in the stratigraphic record in order to better predict the future. The challenge of directly applying analyses of the stratigraphic record is that the very landscape dynamics that make it hard to predict delta behavior in the future, complicate the preservation and interpretation of past paleoenvironmental signals of all sorts. The autogenic processes in particular cause sediment to be unevenly deposited in both time and space. This means that the stratigraphic record of paleoenvironmental signals is likely to have large amounts of missing time at any given study location within a fluviodeltaic system. Previous work has demonstrated that autogenic processes, and the gaps in the record caused by autogenic processes, can expand, condense, or remove entire portions of paleoenvironmental signals if they occur at timescales less than the longest timescale autogenic processes. In this dissertation, I use a combination of numerical models and field datasets to explore how landscape dynamics control signal preservation and how we can use landscape dynamics to improve the uncertainties related to reconstructing paleoenvironmental signals in dynamic landscapes. iv In the first project of this dissertation, I investigate how to measure the scale of landscape dynamics using depositional patterns preserved in outcrops that are limited in spatial extent or resolution. To accomplish this I used synthetic stratigraphy from a physical delta experiment to test the sensitivity of a proposed tool to identify the maximum autogenic scale, called the compensation statistic. I also applied this analysis to four field fluviodeltaic datasets. In the second project, I demonstrate the effect of stochastic sedimentation from landscape dynamics on the probability of preservation and the accuracy of reconstructions of paleoenvironmental signals from geochemical paleoenvironmental proxies. To this end, I compiled sedimentation event magnitudes and frequencies from published data from modern and ancient river, delta, and shallow shelf environments. Based on this compilation, I wrote a stochastic sedimentation model that tracked the preservation of an input proxy signal. In the third project, I investigate how autogenic landscape dynamics control the spatiotemporal distribution of erosion and deposition across a fluviodeltaic system using a numerical delta evolution model. I then used multiple models to predict how these landscape dynamics control how many samples are needed to reconstruct complete and accurate reconstructions of paleoenvironmental signals of different durations. Finally, I applied the concepts developed in the first three projects to a case of the preservation of the Paleocene-Eocene Thermal Maximum, a rapid global warming event ~56 Ma, within deltaic and shelf deposits from the Mid-Atlantic. Overall, this dissertation demonstrates that rapid paleoenvironmental signals can be reconstructed even in highly dynamic sedimentary system when the system is sampled sufficiently to overcome the combined effects of landscape dynamics. Additionally, my analyses demonstrate that under-sampled fluviodeltaic systems are highly likely to significantly bias reconstructions of the original signal. v TABLE OF CONTENTS List of Figures .......................................................................................................................... viii List of Tables ........................................................................................................................... x Acknowledgements .................................................................................................................. xi Chapter 1 Introduction to landscape dynamics and the stratigraphic record ........................... 1 1.1 Distinguishing Climate Change from Landscape Dynamics ..................................... 3 1.2 Dissertation Goals and Approach ............................................................................... 6 1.3 Summary of Dissertation Chapters ............................................................................ 7 Chapter 2: Identifying autogenic sedimentation in fluvial-deltaic stratigraphy: evaluating the effect of outcrop-quality data on the compensation statistic ..... 7 Chapter 3: Preserving proxy records in dynamic landscapes: Modeling and examples from the Paleocene-Eocene Thermal Maximum .............................. 8 Chapter 4: Exploring how landscape dynamics influence the sampling of paleoenvironmental signals .............................................................................. 8 Chapter 5: Characterizing landscape dynamics and variability in sedimentation on the Mid-Atlantic shelf during the Paleocene-Eocene Thermal Maximum .. 9 1.4 References .................................................................................................................. 10 Chapter 2 Identifying autogenic sedimentation in fluvial-deltaic stratigraphy: evaluating the effect of outcrop-quality data on the compensation statistic ...................................... 13 Key Points ........................................................................................................................ 13 Abstract ............................................................................................................................ 13 2.1 Introduction ................................................................................................................ 14 2.2 Background ................................................................................................................ 17 2.2.1 Identifying autogenic scales and organization using the compensation statistic .............................................................................................................. 20 2.3 Effects of dataset resolution on autogenic scales and organization estimates ........... 24 2.3.1 Dataset extent .................................................................................................. 25 2.3.2 Dataset resolution ............................................................................................ 27 2.3.3 Implications ..................................................................................................... 28 2.4 Identifying autogenic scales and organization in ancient fluvial and deltaic deposits ..................................................................................................................... 30 2.4.1 Fluvial case studies .......................................................................................... 31 2.4.2 Deltaic case studies ......................................................................................... 37 2.5 Discussion .................................................................................................................. 44 2.6 Conclusions ................................................................................................................ 48 Acknowledgments and Data ............................................................................................ 49 References ........................................................................................................................ 50 2.7 Figures and Tables ..................................................................................................... 56 vi Chapter 3 Preserving proxy records in dynamic landscapes: Modeling and examples from the Paleocene-Eocene Thermal Maximum ...................................................................... 69 Abstract ............................................................................................................................ 69 3.1 Introduction ................................................................................................................ 70 3.2 Stochastic Sedimentation Model ...............................................................................