First Faculty Advisor
First Faculty Reader
Samuel St. Clair
Quantifying the environmental and physiological niches of plant species is crucial to predicting their sensitivity to global change, and aggregating plant species by functional type is fundamental both to ecological theory and to the practicality of large-scale efforts to predict the consequences of global change. However, traditional functional types are not always predictive of individual species’ responses to change. Here, an inverse species distribution modeling approach is used to identify functionally similar species based on physiological niche in order to better anticipate the consequences of climate change on the Colorado Plateau, USA. The Colorado Plateau is a semiarid region particularly sensitive to climate change and represents the intersection of several different ecosystems with overlapping plant functional types. While seeing evidence for similarities within traditional functional groups defined by growth form and photosynthetic pathway, we identified revised functional groupings which more precisely reflect differences in tolerance of key environmental variables relevant to climate change sensitivity, including soil moisture, maximum temperature threshold, and minimum temperature threshold. One group is sensitive to high maximum temperature and can tolerate very low soil moisture conditions. The projected ranges of these low-temperature species are small and often overlap considerably with the Colorado Plateau, but they have recently declined on the Plateau with warming temperatures. Another group includes species which have recently increased on the Colorado Plateau, and is largely unconstrained by maximum temperature and soil moisture. These results support the idea that the historical Colorado Plateau specialist niche may be threatened by warming temperatures.
BYU ScholarsArchive Citation
Thomas, Anne, "Plant Functional Groups and Success in a Changing Environment: Modeling Physiological Niches of Colorado Plateau Plants" (2018). Undergraduate Honors Theses. 32.