abstract: Functional traits research has improved our understanding of how plants respond to their environments, identifying key trade-offs among traits. These studies primarily rely on correlative methods to infer trade-offs and often overlook traits that are difficult to measure (e.g., root traits, tissue senescence rates), limiting their predictive ability under novel conditions. I aimed to address these limitations and develop a better understanding of the trait space occupied by trees by integrating data and process models, spanning leaves to whole-trees, via modern statistical and computational methods. My first research chapter (Chapter 2) simultaneously fits a photosynthesis model to measurements of fluorescence and photosynthetic response curves, improving estimates of mesophyll conductance (gm) and other photosynthetic traits. I assessed how gm varies across environmental gradients and relates to other photosynthetic traits for 4 woody species in Arizona. I found that gm was lower at high aridity sites, varied little within a site, and is an important trait for obtaining accurate estimates of photosynthesis and related traits under dry conditions. Chapter 3 evaluates the importance of functional traits for whole-tree performance by fitting an individual-based model of tree growth and mortality to millions of measurements of tree heights and diameters to assess the theoretical trait space (TTS) of “healthy” North American trees. The TTS contained complicated, multi-variate structure indicative of potential trade-offs leading to successful growth. In Chapter 4, I applied an environmental filter (light stress) to the TTS, leading to simulated stand-level mortality rates up to 50%. Tree-level mortality was explained by 6 of the 32 traits explored, with the most important being radiation-use efficiency. The multidimentional space comprising these 6 traits differed in volume and location between trees that survived and died, indicating that selective mortality alters the TTS. / Dissertation/Thesis / Doctoral Dissertation Biology 2017
| Identifer | oai:union.ndltd.org:asu.edu/item:43988 |
| Date | January 2017 |
| Contributors | Fell, Michael (Author), Ogle, Kiona (Advisor), Barber, Jarrett (Committee member), Hultine, Kevin (Committee member), Franklin, Janet (Committee member), Day, Thomas (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 246 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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