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Abstract
Life history theory seeks to explain how natural selection shapes organisms’ cycles of birth, maturation, and death to optimize lifetime fitness. Local environmental conditions often exert strong selection on life history traits like reproductive phenology. Climate change directly and indirectly shapes local environments through increased global temperatures and shifts regional precipitation patterns, altering soil water and nutrient resource availability. Climate change imposes novel selection on natural plant populations and influences eco-evolutionary dynamics. Here, I examine fitness trade-offs across and within environments, patterns of selection, and plasticity in reproductive phenology in the context of climate change using the perennial forb, Boechera stricta (Brassicaceae). I exposed 35 accessions originating from natural populations across a 1000m elevational gradient to a large-scale multifactorial greenhouse manipulation of three soil water and two nutrient resource availabilities. I quantified fitness (seed count) and four life history traits, which are often genetically-correlated: the timing of first flowering, the duration of flowering, and height and leaf number at flowering. I found clear evidence for local adaptation to drought stress. In addition, drought intensified the trade-off between reproduction and growth, suggesting drought conditions constrain adaptation despite the high heritability of these fitness-related components (chapter 2). Water and nutrient availability imposed selection on all traits. This research expands on field studies, finding persistent selection for early flowering could, in fact, represent selection for longer duration of flowering (chapter 3). Additionally, I found strong adaptive plasticity in flowering time response to nutrient manipulations, and plasticity in flowering time increased with elevation. This adaptive plasticity could enhance short-term population persistence in response to climate change in high elevation populations. My results bolster our ability to predict evolutionary responses to shifting resource availabilities under future climate change conditions.