Temperature alters the toxicological impacts of plant terpenoids on the polyphagous model herbivore Vanessa cardui.

Terpenes are a major class of secondary metabolites present in all plants, and long hypothesized to have diversified in response to specific plant-herbivore interactions. Herbivory is a major biotic interaction that plays out across broad temporal and spatial scales that vary dramatically in temperature regimes, both due to climatic variation across geographic locations as well as the effect of seasonality. In addition, there is an emerging understanding that global climate change will continue to alter the temperature regimes of nearly every habitat on Earth over the coming centuries. Regardless of source, variation in temperature may influence herbivory, in particular via changes in the efficacy and impacts of plant defensive chemistry. This study aims to characterize temperature-driven variation in toxicological effects across several structural classes of terpenes in the model herbivore Vanessa cardui, the painted lady butterfly. We observed a general increase in monoterpene toxicity to larvae, pupa, and adults at higher temperatures, as well as an increase in development time as terpene concentration increased. Results obtained from this study yield insights into possible drivers of seasonal variation in plant terpene production as well as inform effects of rising global temperatures on plant-insect interactions. In the context of other known effects of climate change on plant-herbivore interactions like carbon fertilization and compensatory feeding, temperature-driven changes in plant chemical defense efficacy may further complicate the prediction of climate change impacts on the fundamental ecological process of herbivory.

Large Mammals Have More Powerful Antibacterial Defenses Than Expected from Their Metabolic Rates.

AbstractTerrestrial mammals span seven orders of magnitude in body size, ranging from the <2-g Etruscan pygmy shrew (Suncus etruscus) to the >3,900-kg African elephant (Loxodonta africana). Although body size profoundly affects the behavior, physiology, ecology, and evolution of species, how investment in functional immune defenses changes with body size across species is unknown. Here, we (1) developed a novel 12-point dilution curve approach to describe and compare antibacterial capacity against three bacterial species among >160 terrestrial species of mammals and (2) tested published predictions about the scaling of immune defenses. Our study focused on the safety factor hypothesis, which predicts that broad, early-acting immune defenses should scale hypermetrically with body mass. However, our three statistical approaches demonstrated that antibacterial activity in sera across mammals exhibits isometry; killing capacity did not change with body size across species. Intriguingly, this result indicates that the serum of a large mammal is less hospitable to bacteria than would be predicted by its metabolic rates. In other words, if metabolic rates underlie the rates of physiological reactions as postulated by the metabolic theory of ecology, large species should have disproportionately lower antibacterial capacity than small species, but they do not. These results have direct implications for effectively modeling the evolution of immune defenses and identifying potential reservoir hosts of pathogens.

Broad diversity in monoterpene-sesquiterpene balance across wild sunflowers: Implications of leaf and floral volatiles for biotic interactions.

PREMISE: As plant lineages diversify across environmental gradients, species are predicted to encounter divergent biotic pressures. This study investigated the evolution of volatile secondary metabolism across species of Helianthus. METHODS: Leaves and petals of 40 species of wild Helianthus were analyzed via gas chromatography-mass spectrometry to determine volatile secondary metabolite profiles. RESULTS: Across all species, 500 compounds were identified; 40% were sesquiterpenes, 18% monoterpenes, 3% diterpenes, 4% fatty acid derivatives, and 35% other compounds such as phenolics and small organic molecules. Qualitatively, annuals and species from more arid western climates had leaf compositions with a higher proportion of total monoterpenes, while erect perennials and species from more mesic eastern habitats contained a higher proportion of total sesquiterpenes. Among species, mass-based leaf monoterpene and sesquiterpene abundance were identified as largely orthogonal axes of variation by principal component analysis. Profiles for leaves were not strongly correlated with those of petals. CONCLUSIONS: Volatile metabolites were highly diverse among wild Helianthus, indicating the value of this genus as a model system and rich genetic resource. The independence of leaf and petal volatile profiles indicates a low level of phenotypic integration between vegetative and reproductive structures, implying vegetative defense and reproductive defense or pollinator attraction functions mediated by terpene profiles in these two organs can evolve without major trade-offs. The major biosynthetic pathways for the major terpenes in wild Helianthus are already well described, providing a road map to deeper inquiry into the drivers of this diversity.

Gene co-expression reveals the modularity and integration of C4 and CAM in Portulaca.

C4 photosynthesis and Crassulacean acid metabolism (CAM) have been considered as largely independent adaptations despite sharing key biochemical modules. Portulaca is a geographically widespread clade of over 100 annual and perennial angiosperm species that primarily use C4 but facultatively exhibit CAM when drought stressed, a photosynthetic system known as C4 + CAM. It has been hypothesized that C4 + CAM is rare because of pleiotropic constraints, but these have not been deeply explored. We generated a chromosome-level genome assembly of Portulaca amilis and sampled mRNA from P. amilis and Portulaca oleracea during CAM induction. Gene co-expression network analyses identified C4 and CAM gene modules shared and unique to both Portulaca species. A conserved CAM module linked phosphoenolpyruvate carboxylase to starch turnover during the day-night transition and was enriched in circadian clock regulatory motifs in the P. amilis genome. Preservation of this co-expression module regardless of water status suggests that Portulaca constitutively operate a weak CAM cycle that is transcriptionally and posttranscriptionally upregulated during drought. C4 and CAM mostly used mutually exclusive genes for primary carbon fixation, and it is likely that nocturnal CAM malate stores are shuttled into diurnal C4 decarboxylation pathways, but we found evidence that metabolite cycling may occur at low levels. C4 likely evolved in Portulaca through co-option of redundant genes and integration of the diurnal portion of CAM. Thus, the ancestral CAM system did not strongly constrain C4 evolution because photosynthetic gene networks are not co-regulated for both daytime and nighttime functions.

Genetic control of arbuscular mycorrhizal colonization by Rhizophagus intraradices in Helianthus annuus (L.).

Plant symbiosis with arbuscular mycorrhizal (AM) fungi provides many benefits, including increased nutrient uptake, drought tolerance, and belowground pathogen resistance. To develop a better understanding of the genetic architecture of mycorrhizal symbiosis, we conducted a genome-wide association study (GWAS) of this plant-fungal interaction in cultivated sunflower. A diversity panel of cultivated sunflower (Helianthus annuus L.) was phenotyped for root colonization under inoculation with the AM fungus Rhizophagus intraradices. Using a mixed linear model approach with a high-density genetic map, we identified genomic regions that are likely associated with R. intraradices colonization in sunflower. Additionally, we used a set of twelve diverse lines to assess the effect that inoculation with R. intraradices has on dried shoot biomass and macronutrient uptake. Colonization among lines in the mapping panel ranged from 0-70% and was not correlated with mycorrhizal growth response, shoot phosphorus response, or shoot potassium response among the Core 12 lines. Association mapping yielded three single-nucleotide polymorphisms (SNPs) that were significantly associated with R. intraradices colonization. This is the first study to use GWAS to identify genomic regions associated with AM colonization in an Asterid eudicot species. Three genes of interest identified from the regions containing these SNPs are likely related to plant defense.

Evolutionary trade-offs in the chemical defense of floral and fruit tissues across genus Cornus.

PREMISE: Defense investment in plant reproductive structures is relatively understudied compared to the defense of vegetative organs. Here the evolution of chemical defenses in reproductive structures is examined in light of the optimal defense, apparency, and resource availability hypotheses within the genus Cornus using a phylogenetic comparative approach in relation to phenology and native habitat environmental data. METHODS: Individuals representing 25 Cornus species were tracked for reproductive phenology over a full growing season at the Arnold Arboretum of Harvard University. Floral, fruit, and leaf tissue was sampled to quantify defensive chemistry as well as fruit nutritional traits relevant to bird dispersal. Native habitat environmental characteristics were estimated using locality data from digitized herbarium records coupled with global soil and climate data sets. RESULTS: The evolution of later flowering was correlated with increased floral tannins, and the evolution of later fruiting was correlated with increased total phenolics. Leaves were found to contain the highest tannin activity, while inflorescences contained the highest total flavonoids. Multiple aspects of fruit defensive chemistry were correlated with fruit nutritional traits. Floral and fruit defensive chemistry were evolutionarily correlated with aspects of native habitat temperature, precipitation, and soil characteristics. CONCLUSIONS: Results provide tentative support for the apparency hypothesis with respect to both flower and fruit phenology, while relative concentrations of secondary metabolites across organs provide mixed support for the optimal defense hypothesis. The evolution of reproductive defense with native habitat provides, at best, mixed support for the resource availability hypothesis.

Measuring inferential importance of taxa using taxon influence indices.

Assessing the importance of different taxa for inferring evolutionary history is a critical, but underutilized, aspect of systematics. Quantifying the importance of all taxa within a dataset provides an empirical measurement that can establish a ranking of extant taxa for ecological study and/or quantify the relative importance of newly announced or redescribed specimens to enable the disentangling of novelty and inferential influence. Here, we illustrate the use of taxon influence indices through analysis of both molecular and morphological datasets, introducing a modified Bayesian approach to the taxon influence index that accounts for model and topological uncertainty. Quantification of taxon influence using the Bayesian approach produced clear rankings for both dataset types. Bayesian taxon rankings differed from maximum likelihood (ML)-derived rankings from a mitogenomic dataset, and the highest ranking taxa exhibited the largest interquartile range in influence estimate, suggesting variance in the estimate must be taken into account when the ranking of taxa is the feature of interest. Application of the Bayesian taxon influence index to a recent morphological analysis of the Tully Monster (Tullimonstrum) reveals that it exhibits consistently low inferential importance across two recent treatments of the taxon with alternative character codings. These results lend support to the idea that taxon influence indices may be robust to character coding and therefore effective for morphological analyses. These results underscore a need for the development of approaches to, and application of, taxon influence analyses both for the purpose of establishing robust rankings for future inquiry and for explicitly quantifying the importance of individual taxa. Quantifying the importance of individual taxa refocuses debates in morphological studies from questions of character choice/significance and taxon sampling to explicitly analytical techniques, and guides discussion of the context of new discoveries.

Molecular evolution of key metabolic genes during transitions to C4 and CAM photosynthesis.

PREMISE OF THE STUDY: Next-generation sequencing facilitates rapid production of well-sampled phylogenies built from very large genetic data sets, which can then be subsequently exploited to examine the molecular evolution of the genes themselves. We present an evolutionary analysis of 83 gene families (19 containing carbon-concentrating mechanism (CCM) genes, 64 containing non-CCM genes) in the portullugo clade (Caryophyllales), a diverse lineage of mostly arid-adapted plants that contains multiple evolutionary origins of all known photosynthesis types in land plants (C3 , C4 , CAM, C4 -CAM, and various intermediates). METHODS: We inferred a phylogeny of 197 individuals from 167 taxa using coalescent-based approaches and individual gene family trees using maximum likelihood. Positive selection analyses were conducted on individual gene family trees with a mixed effects model of evolution (MEME). We devised new indices to compare levels of convergence and prevalence of particular residues between CCM and non-CCM genes and between species with different photosynthetic pathways. KEY RESULTS: Contrary to expectations, there were no significant differences in the levels of positive selection detected in CCM versus non-CCM genes. However, we documented a significantly higher level of convergent amino acid substitutions in CCM genes, especially in C4 taxa. CONCLUSIONS: Our analyses reveal a new suite of amino acid residues putatively important for C4 and CAM function. We discuss both the advantages and challenges of using targeted enrichment sequence data for exploratory studies of molecular evolution.

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time-consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000-species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within-species variation, non-Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time-consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation-Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.

Importance of whole-plant biomass allocation and reproductive timing to habitat differentiation across the North American sunflowers.

Background and Aims: Trait-based plant ecology attempts to use small numbers of functional traits to predict plant ecological strategies. However, a major gap exists between our understanding of organ-level ecophysiological traits and our understanding of whole-plant fitness and environmental adaptation. In this gap lie whole-plant organizational traits, including those that describe how plant biomass is allocated among organs and the timing of plant reproduction. This study explores the role of whole-plant organizational traits in adaptation to diverse environments in the context of life history, growth form and leaf economic strategy in a well-studied herbaceous system. Methods: A phylogenetic comparative approach was used in conjunction with common garden phenotyping to assess the evolution of biomass allocation and reproductive timing across 83 populations of 27 species of the diverse genus Helianthus (the sunflowers). Key Results: Broad diversity exists among species in both relative biomass allocation and reproductive timing. Early reproduction is strongly associated with resource-acquisitive leaf economic strategy, while biomass allocation is less integrated with either reproductive timing or leaf economics. Both biomass allocation and reproductive timing are strongly related to source site environmental characteristics, including length of the growing season, temperature, precipitation and soil fertility. Conclusions: Herbaceous taxa can adapt to diverse environments in many ways, including modulation of phenology, plant architecture and organ-level ecophysiology. Although leaf economic strategy captures one key aspect of plant physiology, on their own leaf traits are not particularly predictive of ecological strategies in Helianthus outside of the context of growth form, life history and whole-plant organization. These results highlight the importance of including data on whole-plant organization alongside organ-level ecophysiological traits when attempting to bridge the gap between functional traits and plant fitness and environmental adaptation.

Likelihood-Based Parameter Estimation for High-Dimensional Phylogenetic Comparative Models: Overcoming the Limitations of "Distance-Based" Methods.

Recently, a suite of distance-based multivariate phylogenetic comparative methods has been proposed for studying the evolution of high-dimensional traits, such as morphometric coordinates, gene expression data, and function-valued traits. These methods allow for the statistical comparison of evolutionary rates, assessment of phylogenetic signal, and tests of correlated high-dimensional trait evolution. Simulations reveal that distance-based comparative methods exhibit low statistical power and high Type I error under various evolutionary scenarios. Distance-based methods are also limited to relatively simple model specification (e.g., Brownian motion evolution) due to the lack of a likelihood function for parameter estimation. Here I propose an alternative method for studying high-dimensional trait evolution which overcomes some of the statistical limitations associated with distance-based methods. This framework, based on parametric bootstrapping and maximum pseudolikelihood parameter estimation, opens up the ability to estimate alternative evolutionary models, combine multiple evolutionary hypotheses, and potentially allow missing data and within-species variation. Simulations reveal that pairwise composite likelihood methods demonstrate appropriate Type I error and high statistical power, thus providing a robust framework for studying high-dimensional trait evolution. These methods are implemented in the R package phylocurve [Covariance; distance; evolutionary rate; function-valued trait; high-dimensional; morphometric; multivariate; pairwise composite likelihood; phylogenetic comparative method; phylogenetic generalized least squares; phylogenetic signal.].

Fine root tradeoffs between nitrogen concentration and xylem vessel traits preclude unified whole-plant resource strategies in Helianthus.

Recent work suggests variation in plant growth strategies is governed by a tradeoff in resource acquisition and use, ranging from a rapid resource acquisition strategy to a resource-conservative strategy. While evidence for this tradeoff has been found in leaves, knowledge of root trait strategies, and whether they reflect adaptive differentiation across environments, is limited. In the greenhouse, we investigated variation in fine root morphology (specific root length and tissue density), chemistry (nitrogen concentration and carbon:nitrogen), and anatomy (root cross-sectional traits) in populations of 26 Helianthus species and sister Phoebanthus tenuifolius. We also compared root trait variation in this study with leaf trait variation previously reported in a parallel study of these populations. Root traits varied widely and exhibited little phylogenetic signal, suggesting high evolutionary lability. Specific root length and root tissue density were weakly negatively correlated, but neither was associated with root nitrogen, providing little support for a single axis of root trait covariation. Correlations between traits measured in the greenhouse and native site characteristics were generally weak, suggesting a variety of equally viable root trait combinations exist within and across environments. However, high root nitrogen was associated with lower xylem vessel number and cross-sectional area, suggesting a tradeoff between nutrient investment and water transport capacity. This led to correlations between root and leaf traits that were not always consistent with an acquisition-conservation tradeoff at the whole-plant level. Given that roots must balance acquisition of water and nutrients with functions like anchorage, exudation, and microbial symbioses, the varied evidence for root trait covariation likely reflects the complexity of interacting selection pressures belowground. Similarly, the lack of evidence for a single acquisition-conservation tradeoff at the whole-plant level likely reflects the vastly different selection pressures shaping roots and leaves, and the resources they are optimized to obtain.

Phylogenetic structural equation modelling reveals no need for an 'origin' of the leaf economics spectrum.

The leaf economics spectrum (LES) is a prominent ecophysiological paradigm that describes global variation in leaf physiology across plant ecological strategies using a handful of key traits. Nearly a decade ago, Shipley et al. (2006) used structural equation modelling to explore the causal functional relationships among LES traits that give rise to their strong global covariation. They concluded that an unmeasured trait drives LES covariation, sparking efforts to identify the latent physiological trait underlying the 'origin' of the LES. Here, we use newly developed phylogenetic structural equation modelling approaches to reassess these conclusions using both global LES data as well as data collected across scales in the genus Helianthus. For global LES data, accounting for phylogenetic non-independence indicates that no additional unmeasured traits are required to explain LES covariation. Across datasets in Helianthus, trait relationships are highly variable, indicating that global-scale models may poorly describe LES covariation at non-global scales.

Phylogenetic Comparative Methods for Evaluating the Evolutionary History of Function-Valued Traits.

Phylogenetic comparative methods offer a suite of tools for studying trait evolution. However, most models inherently assume fixed trait values within species. Although some methods can incorporate error around species means, few are capable of accounting for variation driven by environmental or temporal gradients, such as trait responses to abiotic stress or ontogenetic trajectories. Such traits, often referred to as function-valued or infinite-dimensional, are typically expressed as reaction norms, dose-response curves, or time plots and are described by mathematical functions linking independent predictor variables to the trait of interest. Here, I introduce a method for extending ancestral state reconstruction to incorporate function-valued traits in a phylogenetic generalized least squares (PGLS) framework, as well as extensions of this method for testing phylogenetic signal, performing phylogenetic analysis of variance (ANOVA), and testing for correlated trait evolution using recently proposed multivariate PGLS methods. Statistical power of function-valued comparative methods is compared to univariate approaches using data simulations, and the assumptions and challenges of each are discussed in detail.

Acute and chronic effects of diphenhydramine and sertraline mixtures in Ceriodaphnia dubia.

Ceriodaphnia dubia were tested to evaluate the acute and chronic interactive effects of diphenhydramine and sertraline. Observed effects were compared with 2 reference toxicity models, the concentration addition model and the independent action model. Results indicate that the 2 drugs exhibit additive toxicity in C. dubia. In some cases, individually sublethal concentrations of the chemicals resulted in 100% mortality when combined, demonstrating the potentially severe impact of trace environmental contaminants.