Palmquist, Emily (2022) Climate, genetics, and river flow interact to shape riparian plant community structure. Doctoral thesis, Northern Arizona University.
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Palmquist_2022_climate_genetics_river_flow_interact_shape_riparian_pla.pdf - Published Version Download (6MB) |
Abstract
Riparian plant communities are shaped by hierarchical, interacting factors ranging from climate and river flows to plant traits shaped by genetics and the environment. As increasing temperatures, water use, and river regulation change the conditions that control riparian plant establishment, growth, and survival, a deeper understanding of the interactions between landscape-level environmental pressures and plant-level responses are needed to protect and conserve riparian areas. In this dissertation, I examine interactions among factors driving riparian plant communities at three different scales, using the Colorado River between Glen Canyon Dam and Lake Mead as the study area. In Chapter 1, I introduce the concepts behind riparian plant genetic patterns, potential links between climate adaptation and inundation response, and how river regulation and increasing temperatures could differentially impact riparian species. In Chapter 2, I use simple sequence repeat markers to examine how geography and life history are related to riparian plant population genetics in a restoration context. Here, I show that patterns of genetic variation differ across species and are related to river connectivity, mating system, clonality, and seed dispersal. In Chapter 3, I evaluate how phenotypic variability in growth and resource acquisition characteristics are related to genotype, provenance, and inundation depth using a controlled greenhouse experiment and a clonal, riparian shrub, Pluchea sericea. I show that growth characteristics are more closely related to inundation, while resource acquisition characteristics are more closely related to genotype. In Chapter 4, I examine plant responses to 12 climate, hydrology, and topographic variables and their interactions with site-specific mean annual temperature. I analyze data from a large, 5-year riparian vegetation monitoring dataset, with a focus on eight species representing four functional groups and a variety of hydrological preferences. Analyses were conducted using a Bayesian model structure that simultaneously evaluates plant species absence and cover in the same framework and adjusts for false absences associated with observer error. These results indicate that absence and cover differ in their environmental correlates, hydropower derived flows have unique impacts on riparian plants separate from other hydrological variables, and higher air temperature mediates plant responses to other environmental variables. In Chapter 5, I discuss how conclusions from these studies raise new questions and illustrate connections across multiple drivers of riparian plant responses. Taken together, these studies emphasize the need for comparing multiple riparian species responses to make informed management decisions. Additionally, they show the utility of incorporating plant genetics, river flow, and climate into understanding riparian plant responses.
Item Type: | Thesis (Doctoral) |
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Publisher’s Statement: | © Copyright is held by the author. Digital access to this material is made possible by the Cline Library, Northern Arizona University. Further transmission, reproduction or presentation of protected items is prohibited except with permission of the author. |
Keywords: | Bayesian modeling; Grand Canyon; land management; plant physiology; population genetics; riparian ecology;Climate change; Ecological restoration; Pluchea sericea; Glen Canyon Dam--Environmental impacts |
Subjects: | Q Science > QK Botany |
NAU Depositing Author Academic Status: | Student |
Department/Unit: | Graduate College > Theses and Dissertations College of the Environment, Forestry, and Natural Sciences > Biological Sciences |
Date Deposited: | 13 Jun 2023 17:28 |
Last Modified: | 04 Jan 2024 08:30 |
URI: | https://openknowledge.nau.edu/id/eprint/6011 |
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