Evolutionary responses to global change: an experimental test of the effect of altered precipitation on hybridization rates in sunflower (Helianthus)

Climate change is rapidly altering natural ecosystems. Plastic and adaptive responses to climate change (i.e., range shifts and phenology) have been widely noted across taxa. However, the effects of climate change on evolutionary processes such as interspecific gene flow (hybridization) are less well known. In this study, we quantified hybridization rates in response to experimental manipulations of rainfall, an important dimension of global change. We used rain-out shelters in the field and quantified rates of hybridization between two congeners, Helianthus annuus (common sunflower) and H. petiolaris (prairie sunflower). We found that H. annuus maternal plants produced hybrid progeny more than H. petiolaris maternal plants, with a trend for decreased rates of hybridization with increased soil moisture (when rain-out shelters were absent). The relative number of open inflorescences of each species predicted hybridization rates. Thus, this study demonstrates how changing environmental conditions, specifically precipitation, could influence hybridization rates

The Effect of Altered Soil Moisture on Hybridization Rate in a Crop-Wild System (<i>Raphanus spp</i>.)

<div><p>Since plant mating choices are flexible and responsive to the environment, rates of spontaneous hybridization may vary across ecological clines. Developing a robust and predictive framework for rates of plant gene flow requires assessing the role of environmental sensitivity on plant reproductive traits, relative abundance, and pollen vectors. Therefore, across a soil moisture gradient, we quantified pollinator movement, life-history trait variation, and unidirectional hybridization rates from crop (<i>Raphanus sativus</i>) to wild (<i>Raphanus raphanistrum</i>) radish populations. Both radish species were grown together in relatively dry (no rain), relatively wet (double rain), or control soil moisture conditions in Ohio, USA. We measured wild and crop radish life-history, phenology and pollinator visitation patterns. To quantify hybridization rates from crop-to-wild species, we used a simply inherited morphological marker to detect F₁ hybrid progeny. Although crop-to-wild hybridization did not respond to watering treatments, the abundance of hybrid offspring was higher in fruits produced late in the period of phenological overlap, when both species had roughly equal numbers of open flowers. Therefore, the timing of fruit production and its relationship to flowering overlap may be more important to hybrid zone formation in <i>Raphanus</i> spp. than soil moisture or pollen vector movements.</p></div

Results from generalized linear mixed effects models of the frequency of hybridization (0/1), abundance of hybrid offspring, life-history, phenology and pollinator visitation patterns in wild and crop radish (Species) grown under four watering treatments (Watering Treatment), with phenological overlap (Timing) sampled across the growing season (Date) performed using SAS PROC GLIMMIX.

<p>Results from generalized linear mixed effects models of the frequency of hybridization (0/1), abundance of hybrid offspring, life-history, phenology and pollinator visitation patterns in wild and crop radish (Species) grown under four watering treatments (Watering Treatment), with phenological overlap (Timing) sampled across the growing season (Date) performed using SAS PROC GLIMMIX.</p

Models predicting hybridization rate between <i>Raphanus raphanistrum</i> and <i>R</i>. <i>sativus</i> based on plot-level soil moisture, relative flowering intensity, and the relative frequency that insect visitors switched from foraging on <i>R</i>. <i>raphanistrum</i> and went to <i>R</i>. <i>sativus</i> as predictors (for clarity the intercept (α) and error (ε) are included in all models).

<p>Models predicting hybridization rate between <i>Raphanus raphanistrum</i> and <i>R</i>. <i>sativus</i> based on plot-level soil moisture, relative flowering intensity, and the relative frequency that insect visitors switched from foraging on <i>R</i>. <i>raphanistrum</i> and went to <i>R</i>. <i>sativus</i> as predictors (for clarity the intercept (α) and error (ε) are included in all models).</p

The effect of watering treatment (NR = No Rain, CU = Control Unsheltered, CS = Control Sheltered, DR = Double Rain) on relative flowering intensity (average number of open flowers per plot across a maximum of 12 sampling dates) of <i>Raphanus raphanistrum</i> compared to <i>R</i>. <i>sativus</i> across nine experimental blocks (grey dots).

<p>Values above 1 indicate more <i>R</i>. <i>raphanistrum</i> flowers relative to <i>R</i>. <i>sativus</i> flowers, whereas values below 1 indicate more <i>R</i>. <i>sativus</i> flowers relative to <i>R</i>. <i>raphanistrum</i> flowers. Least squares mean values (±95% CI) across plots within a watering treatment are represented by black dots.</p

Testing the roles of vertical transmission and drought stress in the prevalence of heritable fungal endophytes in annual grass populations

Beneficial inherited symbionts are expected to reach high prevalence in host populations, yet many are observed at intermediate prevalence. Theory predicts that a balance of fitness benefits and efficiency of vertical transmission may interact to stabilize intermediate prevalence. We established populations of grass hosts (Lolium multiflorum) that varied in prevalence of a heritable fungal endophyte (Epichloё occultans), allowing us to infer long-term equilibria by tracking change in prevalence over one generation. We manipulated an environmental stressor (elevated precipitation), which we hypothesized would reduce the fitness benefits of symbiosis, and altered the efficiency of vertical transmission by replacing endophyte-positive seeds with endophyte-free seeds. Endophytes and elevated precipitation both increased host fitness, but symbiont effects were not stronger in the drier treatment, suggesting that benefits of symbiosis were unrelated to drought tolerance. Reduced transmission suppressed the inferred equilibrium prevalence from 42.6% to 11.7%. However, elevated precipitation did not modify prevalence, consistent with the result that it did not modify fitness benefits. Our results demonstrate that failed transmission can influence the prevalence of heritable microbes and that intermediate prevalence can be a stable equilibrium due to forces that allow symbionts to increase (fitness benefits) but prevent them from reaching fixation (failed transmission).Fil: Cavazos, Brittany R.. Rice University; Estados UnidosFil: Bohner, Teresa F.. Rice University; Estados UnidosFil: Donald, Marion L.. Rice University; Estados UnidosFil: Sneck, Michelle E.. Rice University; Estados UnidosFil: Shadow, Alan. United States Department of Agriculture; Estados UnidosFil: Omacini, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Rudgers, Jennifer A.. University of New Mexico; Estados UnidosFil: Miller, Tom E. X.. Rice University; Estados Unido

Data from: The effect of demographic correlations on the stochastic population dynamics of perennial plants

Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-to-year variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (λS)? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from -1% to +22%. However, vital rate correlations caused virtually no change in the estimates of λS (mean effects ranging from -0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data-intensive and technically challenging

Data from: The effect of demographic correlations on the stochastic population dynamics of perennial plants

Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-to-year variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (λS)? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from -1% to +22%. However, vital rate correlations caused virtually no change in the estimates of λS (mean effects ranging from -0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data-intensive and technically challenging

DataScriptsResults

This file contains the data and R scripts to: 1. fit vital rate models, 2. build population projection models, and 3. run stochastic simulations. The 'Results' directory also reports the results of vital rate models and simulations. Readme and metadata files are provided within the main, and 'Data' folders, respectively