DEVELOPMENT, CALIBRATION AND APPLICATION OF A 3-D INDIVIDUAL-BASED GAP MODEL FOR IMPROVED CHARACTERIZATION OF EURASIAN BOREAL FORESTS IN RESPONSE TO HISTORICAL AND FUTURE CHANGES IN CLIMATE KSENIA BRAZHNIK CHARLOTTESVILLE,VIRGINIA B.A. CHEMISTRY,VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY, 2002 ADISSERTATION PRESENTED TO THE GRADUATE FACULTY OF THE UNIVERSITY OF VIRGINIA IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ENVIRONMENTAL SCIENCES UNIVERSITY OF VIRGINIA DECEMBER, 2015 Abstract Climate change is altering forests globally, some in ways that may promote further warming at the regional and even continental scales. The dynamics of complex systems that occupy large spatial domains and change on the order of decades to centuries, such as forests, do not lend themselves easily to direct observation. A simulation model is often an appropriate and attainable approach toward understanding the inner workings of forest ecosystems, and how they may change with imposed perturbations. A new spatially-explicit model SIBBORK has been developed to understand how the Siberian boreal forests may respond to near-future climate change. The predictive capabilities of SIBBORK are enhanced with 3-dimensional representation of terrain and associated environmental gradients, and a 3-D light ray-tracing subroutine. SIBBORK’s outputs are easily converted to georeferenced maps of forest structure and species composition. SIBBORK has been calibrated using forestry yield tables and validated against multiple independent multi- dimensional timeseries datasets from southern, middle, and northern taiga ecotones in central Siberia, including the southern and northern boundaries of the boreal forest. Model applications simulating the vegetation response to cli- mate change revealed significant and irreversible changes in forest structure and composition, which are likely to be reached by mid-21st century. These changes in land cover will inevitably result in changes in the biodiversity, carbon storage, and the ecosystem services provided by the Siberian boreal forest. Acknowledgements First and foremost, I would like to thank my husband, Luke, for putting up with me while I learned to program. This was a journey that involved a myriad of emotions and a whole lot of chocolate. I am grateful to my advisor Hank Shugart, who had provided guidance, encouragement, funding and a productive environment for this project. I would also like to thank my brother, Konstantin, who has supported me in finding creative ways to communicate about my research and played an integral role in the creation of the SIBBORK introduction video. Furthermore, I’d like to thank Charlie Hanley, who spent a semester working with me on developing a fire subroutine for SIBBORK. I am thankful to my committee - Stephan F. J. de Wekker, Paolo D’Odorico and Jennie Chiu - for their guidance. I thank K. Holcomb for programming consultation, D. Ershov for facilitating the Usolsky forest dataset, J. Weishampel for providing a reference 3-D light subroutine, D. Urban and J. Holm for ZELIG v1.0 code and documentation, O. Krankina for fruitful conversation and access to some hard-to-find Russian literature, and Dr. C. Huttig for provid- ing the dataset "Hybrid Biomass and Land Cover Map for Central Siberia", portions of which were used in model validation and generation of several figures in this dissertation. This research was supported and funded by the Environmental Sciences Department at the University of Virginia, the Virginia Space Grant Consortium Graduate Fellowship grant, a NASA grant (NNX11AE39G) to Hank Shugart, and a NASA grant (UM-3002295358) to the University of Michigan subcontracted to Hank Shugart. CONTENTS Abstract..................................................... ii Acknowledgements............................................... iii 1 Numerical modeling Approach to Predicting Ecosystem Change1 1.1 Introduction...............................................1 1.2 Forest modeling.............................................5 1.3 Advantages of Spatially-Explicit Forest Models.............................8 1.4 Motivation................................................ 11 1.5 Objectives and Hypotheses........................................ 12 2 SIBBORK: Model Development 17 2.1 Environment............................................... 20 2.2 Vegetation Processes........................................... 43 2.3 Allometry................................................. 49 2.4 Environmental Effects on Vegetation Processes............................. 60 3 Model Calibration and Testing 67 3.1 Introduction............................................... 67 3.2 Methodology............................................... 68 3.3 Results.................................................. 85 3.4 Discussion................................................ 91 3.5 Conclusions............................................... 95 4 Structure and Dynamics in Complex Terrain and in a Changing Climate 97 4.1 Introduction............................................... 98 4.2 Methods................................................. 99 i 4.3 Results.................................................. 106 4.4 Discussion................................................ 109 4.5 Conclusions............................................... 115 5 Model Sensitivity 117 5.1 Does spatial-explicity matter?...................................... 118 5.2 Model sensitivity to spatial resolution.................................. 125 5.3 Climate Sensitivity Analysis: spatially-explicit forest responses to climate change in central Siberia. 136 6 Current and Future Developments 143 6.1 Disturbances and Mitigation....................................... 143 6.2 Landscape Fragmentation and Edge Effects............................... 153 6.3 Synthetic data generation for Synthetic Aperture Radar calibration and validation........... 157 7 Conclusions 159 8 References 161 ii CHAPTER ONE NUMERICAL MODELING APPROACH TO PREDICTING ECOSYSTEM CHANGE “Technical skill is mastery of complexity, while creativity is mastery of simplicity.” - Sir E. C. Zeeman (1977) 1.1 Introduction This work serves to introduce the dynamic gap model SIBBORK (SIBerian BOReal forest simulator, pronounced “cyborg” but with a “k” at the end) as a robust tool for predicting ecosystem change. This contribution estimates changes in the boreal ecosystem, which (1) represents the largest terrestrial biome, (2) contains a disproportionate amount of carbon compared to other terrestrial ecosystems, (3) exchanges carbon with the atmosphere, and (4) has been experiencing accelerated climate change over the last three decades. Boreal forests occupy one sixth of the land cover, yet contain one third of the terrestrial carbon stores (Shugart et al., 1986; Bolin, 1986, as referenced in Bonan, 1988a; Conard et al., 2002; Bonan, 2008). Although most of the carbon in boreal forests is stored in soils and permafrost (Tarnocai et al., 2009), carbon dynamics within the ecosystem depend on the structure and composition of the above-ground vegetation community. Additionally, boreal forests are floristically simple, which renders their species diversity, biomass, and carbon dynamics more susceptible to perturbations, such as climate change (Shugart et al., 1992a; Bonan, 2008; Anderegg et al., 2012). Changes in forest composition and dynamics may propagate regional and global warming of ambient air and soil temperatures through a complex system of vegetation- atmosphere feedbacks (Bonan et al., 1992; Betts, 2000; Denman et al., 2007; Bonan, 2008; Shugart and Woodward, 2011). Due to its rich carbon stores and low biodiversity, the boreal ecosystem may play a substantial role in the planetary carbon cycle, as the warming predicted and already observed in Eurasian boreal forests is likely to shift their function toward acting as a net source of atmospheric carbon. Predicting future changes in the Eurasian boreal 1 Modeling Boreal Forests in 3-D forest is intrinsically a modeling issue, as the spatial expanse of this ecosystem and the temporal scale of patterns and processes do not lend themselves to direct measurement or observation. Furthermore, models allow us to infer long- term dynamics in hypothetical or potential future environmental conditions (Busing and Mailly, 2004 ). This thesis details the development and application of SIBBORK in a spatially-explicit model-based synthesis of forest dynamics to investigate the structure and processes of this vast boreal landscape on multiple scales of time and geography, and includes an exploration of forest response to climate change with the purpose of understanding how changes in this ecosystem may affect global carbon dynamics. Complex internal interactions within the boreal ecosystem can amplify climate change at regional and continental levels. Field studies have shown that alterations in land cover, such as shifts in tree line position and forest composi- tion, and changes in vegetation processes, including regeneration and seed dispersal, are already occurring within the Siberian boreal forest (Tretyakova and Noskova, 2004; Soja et al., 2006; Noskova and Tretyakova, 2006; Tretyakova, 2006; Kharuk et al., 2009; Noskova et al., 2009; Barchenkov, 2010; Kharuk et al., 2013a,b). These physical changes in forest structure coincide with measurements of greater warming than has been observed elsewhere or predicted by global climate models (Hansen et al., 1999; Serreze et al., 2000; Soja et al., 2007; Shkol’nik et al.,