Achieving societal well-being goals is inextricably linked to the preservation of many ecosystem functions. This dissertation adopts a plant lens, to contribute to our understanding of sustainable ecosystem functioning. Specifically, it sheds light on some plant physiology, phenology, and ecology processes, which matter for sustainable development: tree growth response to high temperatures, annual fluctuations in the timing of plant flowering, and ecological benefits of crop diversity that translate into economic returns. In addition, it illustrates how large-scale data proxies can be used to document large scale patterns that arise from individual plant processes.
Chapter 1 documents a new methodology for estimating tree-level temperature response curves, using tree ring data and a degree-day framework. It uses those curves to document harmful impacts of high temperatures for tree growth across the US, and shows that there is limited acclimatization, but some adaptation to those high temperatures in a sample of climate sensitive and long-lived trees. Chapter 2 shows that satellite imagery and deep learning tools can be leveraged, to monitor interannual variations in the timing of plant flowering at large scales. It documents the predictive performance of two models: one adapted to monitoring crop flowering, the other adapted to monitoring shifts in the onset of spring flowering. Finally, chapter 3 highlights remaining gaps between empirical evidence of crop diversity benefits, and portrayal of those benefits in economic models of optimal crop diversity choice. Together, these chapters illustrate that bridging scales and disciplines is a difficult task, although it is necessary for understanding the sustainability of the human environmental footprint.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-dbx3-0v07 |
| Date | January 2021 |
| Creators | Gantois, Josephine |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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