Seed Mass and Morphology in Outcrossing and Selfing Species of Clarkia (Onagraceae): An SEM Study

Seeds from three pairs of outcrossing-selfing sister taxa from the genus Clarkia (farewell-to-spring, Onagraceae)—Clarkia unguiculata, Clarkia exilis, Clarkia xantiana ssp. xantiana and ssp. parviflora, and Clarkia concinna ssp. concinna and ssp. automixa—were studied to assess the effects of contrasting mating systems on seed mass and seed morphology. For each outcrossing-selfing comparison, the seed mass of the selfing taxon was less than that of the outcrossing taxon. Seed mass typically differed significantly among populations within a taxon. Scanning electron microscopy showed that the seeds from all these taxa share several characteristics: a bullet to shield shape, a reticulate exotesta pattern, presence of crystals in the seed coat, and a seed coat that varies in thickness over the length of the seed. No morphological feature reliably distinguished seeds of outcrossing taxa from those of selfing taxa. The lack of morphological differences in conjunction with the consistent differences in seed mass between selfing and outcrossing seeds in these taxa supports the hypothesis that evolutionary forces have acted only on seed mass and not on seed morphology

Hotter Is Better and Broader: Thermal Sensitivity of Fitness in a Population of Bacteriophages

Hotter is better is a hypothesis of thermal adaptation that posits that the rate-depressing effects of low temperature on biochemical reactions cannot be overcome by physiological plasticity or genetic adaptation. If so, then genotypes or populations adapted to warmer temperatures will have higher maximum growth rates than those adapted to low temperatures. Here we test hotter is better by measuring thermal reaction norms for intrinsic rate of population growth among an intraspecific collection of bacteriophages recently isolated from nature. Consistent with hotter is better, we find that phage genotypes with higher optimal temperatures have higher maximum growth rates. Unexpectedly, we also found that hotter is broader, meaning that the phages with the highest optimal temperatures also have the greatest temperature ranges. We found that the temperature sensitivity of fitness for phages is similar to that for insects

Erroneous Arrhenius: Modified Arrhenius Model Best Explains the Temperature Dependence of Ectotherm Fitness

The initial rise of fitness that occurs with increasing temperature is attributed to Arrhenius kinetics, in which rates of reaction increase exponentially with increasing temperature. Models based on Arrhenius typically assume single rate-limiting reaction(s) over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using datasets for microbes that have measurements of fitness (intrinsic rate of population growth) at many temperatures and over a broad temperature range, and for diverse ectotherms that have measurements at fewer temperatures. When measurements are available at many temperatures, strictly Arrhenius kinetics is rejected over the physiological temperature range. However, over a narrower temperature range, we cannot reject strictly Arrhenius kinetics. The temperature range also affects estimates of the temperature dependence of fitness. These results indicate that Arrhenius kinetics only apply over a narrow range of temperatures for ectotherms, complicating attempts to identify general patterns of temperature dependence

The Genetic Basis of Thermal Reaction Norm Evolution in Lab and Natural Phage Populations

Two major goals of laboratory evolution experiments are to integrate from genotype to phenotype to fitness, and to understand the genetic basis of adaptation in natural populations. Here we demonstrate that both goals are possible by re-examining the outcome of a previous laboratory evolution experiment in which the bacteriophage G4 was adapted to high temperatures. We quantified the evolutionary changes in the thermal reaction norms—the curves that describe the effect of temperature on the growth rate of the phages—and decomposed the changes into modes of biological interest. Our analysis indicated that changes in optimal temperature accounted for almost half of the evolutionary changes in thermal reaction norm shape, and made the largest contribution toward adaptation at high temperatures. Genome sequencing allowed us to associate reaction norm shape changes with particular nucleotide mutations, and several of the identified mutations were found to be polymorphic in natural populations. Growth rate measures of natural phage that differed at a site that contributed substantially to adaptation in the lab indicated that this mutation also underlies thermal reaction norm shape variation in nature. In combination, our results suggest that laboratory evolution experiments may successfully predict the genetic bases of evolutionary responses to temperature in nature. The implications of this work for viral evolution arise from the fact that shifts in the thermal optimum are characterized by tradeoffs in performance between high and low temperatures. Optimum shifts, if characteristic of viral adaptation to novel temperatures, would ensure the success of vaccine development strategies that adapt viruses to low temperatures in an attempt to reduce virulence at higher (body) temperatures

Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures

Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits.

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures