On the Influence of Landscape-Scale Factors On
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On the influence of landscape-scale factors on stream ecosystems and macroinvertebrate assemblages in the southeastern USA: an examination of alternative statistical methods and case studies. by Brad Patrick Schneid A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Copyright 2015 by Brad Patrick Schneid Approved by John W. Feminella, Chair, Professor and Chair, Department of Biological Sciences Christopher Anderson, Co-chair, Associate Professor, School of Forestry and Wildlife Sciences Ash Abebe, Associate Professor, Department of Mathematics and Statistics Brian Helms, Assistant Research Professor, Department of Biological Sciences Abstract The influence of land cover on stream ecosystems has increasingly been the focus of research in a variety of fields, including ecology, hydrology, and engineering. Human-altered land cover can increase overland storm runnoff and be a source of nutrients, chemicals and sediment to streams, which can negatively affect biota. Urbanization has been recognized as a particularly influential form of land cover, and low levels of urban development (e.g., suburban land) has become the focus of an increasing number of studies, as it is predicted to be a more prevalent form of land-cover change over the next century. The coastal plains of the southeastern US are a relatively understudied region; however, some research has indicated that these lowland streams may be influenced by land cover to a lesser degree than those from more frequently studied and higher gradient landscapes. Current trends and predictions in land-cover change and human population growth suggest that streams and rivers will become increasingly influenced by human activity. Thus, research is warranted to further investigate the influence of low levels of urban development on streams and how this influence may vary regionally. Studies on the influence of land cover on stream ecosystems are complicated by multiple issues, including the following: 1) experimental manipulation of whole watersheds is generally impractical, therefore most studies have been observational, 2) land cover is generally expressed as proportions; thus, land-cover classes are likely to be correlated, 3) whole-watershed replication is frequently low relative to the number of variables considered, thus constraining statistical analyses, 4) land cover is typically not the direct cause of biological degradation, and 5) real-world data are not ideal and anomalies (outliers) are generally present and not always ii realized by the investigator. Some of the above issues are problematic when using traditional statistical methods, including ordinary least-squares (OLS) regression. Small sample sizes, correlated predictor variables, and outliers separately and in combination contribute to unreliable estimation and prediction by OLS regression. Whereas no true solution to these problems exists, most ecologists often do not consider alternatives that may, to some degree, address or alleviate these analytical challenges. Overall, my dissertation provides important information regarding appropriate statistical choices for analyzing real-world data which usually should not be assumed to conform to assumptional requirements of traditional methods. Nowhere are these issues more evident than in land-cover or ecological studies in general where small sample sizes are commonplace, predictor variables are frequently highly correlated, and outliers are likely present. In addition, my dissertation contributes to research on the influence of land cover on stream ecosystems in the understudied southeastern coastal plains, suggesting that impervious surface cover ≤ 11% likely influences hydrology and physicochemistry of streams. This information is particularly important because low-levels of urban development are predicted to be the most prevalent of land-cover change along the Gulf Coast in the foreseeable future. Last, my dissertation importantly highlights specific differences in macroinvertebrate taxonomic and trait composition that exist in lowland coastal plains versus those in highland regions. Macroinvertebrates are the most frequently used taxonomic group in stream biomonitoring, and my research reinforces the body of literature suggesting that regional bioassessment metrics are needed to accurately identify impairment specific to each region. iii Acknowledgements I must thank my parents from the bottom of my heart. Joseph and Sandra Schneid provided a loving, caring environment to grow up in and instilled me with an important moral base that has proven invaluable. My parents encouraged and supported my inquisitiveness and ever-changing interests as I attempted to find myself. I also thank my entire family, but especially my older brother Matt for helping me and attempting on multiple occasions to steer me towards success and my younger brother Drew for being one of my best friends and helping me in more ways than he will ever know. I thank Drs. Jack Feminella, Christopher Anderson, Ash Abebe and Brian Helms for their guidance, support, and understanding as committee members. Specifically, I would like to thank my co-advisors, Jack and Chris, for inviting me to join their labs and providing many years of sound advice and generous support. I thank Ash for also being an an excellent M.P.S. advisor and for truly fostering my interest in statistics (and for bringing me to Zimbabwe!). I also must thank Brian for his mentorship, endless help in the field and lab, and for being a good friend. I thank Dr. Latif Kalin for serving as my outside reader and whose Advanced Forest Hydrology course made me 1st realize that I actually liked mathematics. I also must thank Dr. Nedret Billor for being an excellent teacher; it is your fault that I became obsessed with statistics. I must sincerely thank Stephen Sefick for joining the Feminella lab and being there to laugh with and answer my seemingly endless questions about computers, statistics and ecology. I would also like to thank Molli Newman, Emily Hartfield-Kirk, Brian Lowe, Susan Riethel Colvin, iv Flynt Barksdale, Diane Alix and many others for their friendship and help in the field and lab. Last, but not least, I would also like to thank Dr. Alexis M. Janosik for her friendship, loving support, and understanding; meeting you made graduate school worth the trouble. v Table of Contents Abstract ........................................................................................................................................ ii Acknowledgments........................................................................................................................ iv List of Tables ................................................................................................................................ x List of Figures .............................................................................................................................. xi Chapter 1: Introduction to-use effects on streams and related analytical issues. ....................... 1 1.1 Introduction ............................................................................................................... 1 1.2. References ................................................................................................................ 8 Chapter 2: Small sample sizes, collinear predictors and linear modeling: a simulation study comparing alternative methods and a case study on landscape-stream ecosystem research ...... 14 2.1 Introduction ............................................................................................................ 14 2.2 Methods .................................................................................................................. 21 2.2.1 Simulation study .......................................................................................... 21 2.2.2 Case study .................................................................................................... 25 2.3 Results .................................................................................................................... 26 2.3.1 Omitted variable bias ................................................................................... 26 2.3.2 Simulation study .......................................................................................... 27 2.3.3 Case study .................................................................................................... 29 vi 2.4 Discussion . ……………………………………………………………………….31 2.4.1 Simulation study . ………………………………………………………….31 2.4.2 Case study . ………………………………………………………………...33 2.4.3 Concluding remarks . ………………………………………………………33 2.5 References . ……………………………………………………………………….37 Chapter 3: Influence of low-intensity watershed development on small coastal Alabama streams: an analysis using partial least-squares ........................................................................................ 56 3.1 Introduction . ……………………………………………………………………….56 3.2 Methods ..... ……………………………………………………………………….59 3.2.1 Study area ..... ………………………………………………………………59 3.2.2 Instream sampling and response variables ................................................... 60 3.2.3 Statistical analysis ........................................................................................ 65 3.3 Results ...................................................................................................................