Seema Sheth

Background: Evaluating how climate alters demographic rates is crucial for understanding current population dynamics and predicting population trajectories and species distributions in response to climate change. Yet, many gaps remain in our understanding of how historical and contemporary patterns of climate adaptation shape population dynamics. Our overarching goal is to understand how spatiotemporal variation in climatic drivers affects population stability and persistence by evaluating the following objectives over the next ten years. First, we will compare how vital rates (e.g., survival, growth, fecundity) respond to spatial and temporal environmental gradients. Second, we will test whether responses of vital rates to environmental variation promote demographic buffering or demographic lability. Third, we will assess the contributions of phenotypic plasticity and genetic adaptation to demographic stability. To address these objectives, we will continue building a large-scale, long-term demographic data set from Mimulus cardinalis, a widespread perennial herb that spans a broad latitudinal and climatic gradient in western North America. This species is an ideal model for understanding population persistence in a rapidly changing climate because we can leverage an already extensive spatial and temporal demographic dataset (10-21 years of demographic data from 21 populations, Table 1), experimental work in greenhouse and field common gardens, and ongoing genomic studies to investigate adaptation to climate across the species’ range. The combination of observational and experimental data makes this a particularly powerful study system for dissecting how historical and contemporary climate adaptation shape distribution and abundance. Aim 1: Compare responses of vital rates to environmental variation across spatial and temporal gradients. Though researchers often rely on inferences from spatial proxies to forecast population dynamics under climate change, a major knowledge gap is whether spatial gradients in climate can give accurate windows into temporal demographic trajectories within a site. The climate envelope hypothesis postulates that space-for-time substitutions can reveal likely temporal trajectories because they reflect species-level, range-wide tolerance. Alternatively, the local adaptation hypothesis proposes that space-for-time substitutions cannot reveal temporal trajectories because local adaptation yields distinct temporal responses across sites. To distinguish between these contrasting hypotheses, we need demographic time series of long enough duration to model vital rates as functions of weather, assembled across many climatically distinct sites. Aim 2: Test whether responses of vital rates to environmental variation promote demographic buffering or demographic lability. Theory predicts that natural selection favors a reduction in temporal variation of population growth rates by minimizing inter-annual variation in highly sensitive vital rates (demographic buffering hypothesis). In contrast, the demographic lability hypothesis posits that natural selection has favored traits that capitalize on temporal variation in population growth rate when gains in good years outweigh losses in bad years. These hypotheses are not mutually exclusive, and determining which vital rates are buffered and labile is key to better understanding of life history evolution. Aim 3: Assess the contributions of plasticity and adaptation to demographic stability. Demographic stability over time can arise from a combination of adaptive evolution (evolutionary rescue hypothesis) and phenotypic plasticity (plastic rescue hypothesis), whereby populations with the greatest magnitudes of trait evolution (or changes in allele frequency at climate-associated loci) and/or adaptive trait plasticity show the smallest declines or quickest rebounds during extreme climate perturbations, respectively. We will integrate the demographic time series with information about adaptive potential, local adaptation, and phenotypic plasticity from

Overview: Climate change is exposing natural systems to novel climatic regimes and biotic interactions, altering natural selection, and disrupting local adaptation. Populations across the range of a species likely vary in their migratory and adaptive potential under climate change. Nevertheless, very few studies to-date have examined quantitative genetic variance in traits, adaptive potential, or the degree of plasticity across populations, nor has there been a robust effort to dissect the consequences of ignoring range-wide variation in these processes for the accuracy of models that forecast species’ responses to future climate change. Most approaches aimed at predicting population persistence under climate change involve simplifying assumptions around plasticity, adaptation, and gene flow that are virtually always violated in natural systems. Here, we combine approaches from evolutionary biology, field ecology, and population genomics in a broadly distributed native plant species experiencing rapid environmental change (Chamaecrista fasciculata, Fabaceae) to forecast population dynamics range-wide under climate change. To evaluate genetic variation range-wide (Aim 1), we will first evaluate the migratory potential of populations under climate change using population genomic estimators of historical rates of gene flow. Gene flow could facilitate adaptive responses to climate change by redistributing adaptive alleles across populations and introducing alleles that confer thermal tolerance from low into high latitude populations. Population genomic studies will quantify variation in inbreeding, genetic drift, and genetic load in 60 populations across the range, which is crucial for predicting adaptive potential under climate change, especially in range-edge populations where deleterious mutations can accumulate. To estimate the adaptive potential of populations (Aim 2), proposed field studies will expose pedigreed lines from 12 populations across the range to contemporary conditions and simulated climate change in common gardens located in trailing edge, central, leading edge, and beyond-range sites. This range-wide manipulative experiment will: (a) evaluate if elevated temperatures reduce additive genetic variance in fitness, and test whether climate change diminishes adaptive potential to a greater extent in small than in large populations; (b) test key hypotheses about the consequences of climate change for population growth rates in different parts of the distribution; and (c) examine whether plasticity could buffer some populations from decline in the short-term. Finally, we will forecast range-wide eco-evolutionary dynamics under climate change using models that differ in the degree to which they incorporate data on species occurrence, quantitative genetic estimates for fitness in response to climate, trait expression under climate change, sequence variation, and gene flow (Aim 3). Intellectual merit: Genomic and quantitative genetic field studies will evaluate population-level variation in genetic diversity, rates of gene flow, phenotypic plasticity and additive genetic variance in traits and fitness. We will then integrate eco-evolutionary processes into models that predict range-wide fitness and occurrence as functions of climate, and contrast basic species distribution models with sophisticated models that incorporate empirical estimates of gene flow and data on trait and fitness responses to climatic variation from multiple common gardens. By comparing the predictive accuracy of alternative modeling approaches, we seek to identify the data required to forecast range-wide responses to climate change. The primary objective is to determine the type and amount of data necessary to generate robust and reliable predictions about range dynamics and adaptive potential, based on standard cross validation and independent validation approaches. Chamaecrista fasciculata is an exemplary case study to evaluate how and why alternative modeling approaches differ. This approach will generate robust forecasts of rang

Throughout history, humans have relied on understanding the evolution and ecology of plants, which form the basis of all life on Earth. Climate change is threatening plants across the planet. One way that plants can persist in the face of changing climate is by adapting to new conditions. Understanding the abilities of plant populations to adapt to environmental change can improve our ability to prioritize biological groups of conservation concern, forecast vulnerability to climate change, and predict the rate of spread of invasive species. This project focuses on the processes that facilitate or constrain adaptation to novel conditions such as those beyond species geographic range edges or those that have arisen due to climatic changes. Specifically, this work will examine rapid adaptation to climate change within multiple populations across the scarlet monkeyflower’s (Mimulus cardinalis) geographic range. Aside from providing a comprehensive understanding of constraints to adaptation, this work will provide numerous training and mentoring opportunities for undergraduates, graduate students, and postdoctoral associates.