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opencc-zeroOct 2020View details →

Quantifying the effects of species traits on predation risk in nature: a comparative study of butterfly wing damage

1) Evading predators is a fundamental aspect of the ecology and evolution of all prey animals. In studying the influence of prey traits on predation risk, previous researchers have shown that crypsis reduces attack rates on resting prey, predation risk increases with increased prey activity, and rapid locomotion reduces attack rates and increases chances of surviving predator attacks. However, evidence for these conclusions is nearly always based on observations of selected species under artificial conditions. In nature, it remains unclear how defensive traits such as crypsis, activity levels, and speed influence realized predation risk across species in a community. Whereas direct observations of predator-prey interactions in nature are rare, insight can be gained by quantifying bodily damage caused by failed predator attacks. 2) We quantified how butterfly species traits affect predation risk in nature by determining how defensive traits correlate with wing damage caused by failed predation attempts, thereby providing the first robust multi-species comparative analysis of predator-induced bodily damage in wild animals. 3) For 34 species of fruit-feeding butterflies in an African forest, we recorded wing damage and quantified crypsis, activity levels, and flight speed. We then tested for correlations between damage parameters and species traits using comparative methods that account for measurement error. 4) We detected considerable differences in the extent, location, and symmetry of wing surface loss among species, with smaller differences between sexes. We found that males (but not females) of species that flew faster had substantially less wing surface loss. However, we found no correlation between cryptic colouration and symmetrical wing surface loss across species. In species in which males appeared to be more active than females, males had a lower proportion of symmetrical wing surface loss than females. 5) Our results provide evidence that activity greatly influences the probability of attacks and that flying rapidly is effective for escaping pursuing predators in the wild, but we did not find evidence that cryptic species are less likely to be attacked while at rest. 15-Oct-2019

opencc-zeroJan 2021View details →

Trait-fitness associations do not predict within-species phenotypic evolution over 2 million years

Long-term patterns of phenotypic change are the cumulative results of tens of thousands to millions of years of evolution. Yet, empirical and theoretical studies of phenotypic selection are largely based on contemporary populations. The challenges in studying phenotypic evolution, in particular trait-fitness associations in the deep past, are barriers to linking micro- and macroevolution. Here, we capitalize on the unique opportunity offered by a marine colonial organism commonly preserved in the fossil record to investigate trait-fitness associations over 2 million years. We use the density of female polymorphs in colonies of Antartothoa tongima as a proxy for fecundity, a fitness component, and investigate multivariate signals of trait-fitness associations in six time intervals on the backdrop of Pleistocene climatic shifts. We detect negative trait-fitness associations for feeding polymorph (autozooid) sizes, positive associations for autozooid shape but no particular relationship between fitness and brood chamber size. In addition, we demonstrate that long-term trait patterns are explained by palaeoclimate and to a lesser extent by ecological interactions. Our analyses show that macroevolutionary outcomes of trait evolution are not a simple scaling-up from the trait-fitness associations.

Elevation filters seed traits and germination strategies in the eastern Tibetan Plateau

Seeds are the colonizing propagules for many plants and may therefore contribute to the filtering of species during the process of colonization and community assembly. Environmental filtering of seed traits may occur among species and influence community composition, or within species and influence the environmental breadth that a given species inhabits. To test for evidence of such filtering of seed traits, we measured morphological and germination traits of seeds of 408 angiosperm species collected across an elevational gradient in the eastern Tibetan Plateau grasslands. We tested for elevational filtering of traits at the species level, as well as within 22 of those species that occurred at different elevations, in order to test whether within-species variation reflected among-species patterns. Elevational patterning occurred in both seed morphology and seed germination. Seeds were smaller, more elongated, and had a higher surface area:volume ratio and shorter germination times at higher elevation. Seed morphology was associated with germination such that more elongated and smaller seeds with a higher surface area:volume ratio germinated faster, leading to earlier germination in seeds from high elevation. Within species, elevational variation in seed traits was observed in several species, but species differed in how those traits were distributed across elevation. These results suggest that taxonomic differences in seed traits may contribute to elevational variation in the species composition of plant communities, but that seed traits may be variably selected by elevation within species.

A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. Many of these methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.

Colorful traits in avian females, individual condition, reproductive performance, and male mate preferences: A meta-analytic approach

Colorful ornaments in females are suggested to have evolved and be maintained by sexual selection. Although several studies have evaluated this idea evidence is still equivocal. Results from empirical studies have been compilated in reviews, but quantitative analyses have seldom been performed. Here, using a meta-analytic approach, we show that evidence from empirical studies conducted in birds, supports the ideas that colorful female ornaments are positively associated with individual condition, reproductive performance, and male-mate preferences. Hence, females' colorful traits, in birds, likely evolved and are maintained by sexual selection.

opencc-zeroJan 2020View details →

Data from: Trait-based formal definition of plant functional types and functional communities in the multi-species and multi-traits context

The concepts of traits, plant functional types (PFT), and functional communities are effective tools for the study of complex phenomena such as plant community assembly. Here, we (1) suggest a procedure formalising the classification of response traits to construct a PFT system; (2) integrate the PFT, and species compositional data to formally define functional communities; and, (3) identify environmental drivers that underpin the functional-community patterns.A species–trait data set featuring species pooled from two study sites (Eneabba and Cooljarloo, Western Australia), both supporting kwongan vegetation (sclerophyllous scrub and woodland communities), was subjected to classification to define PFTs. Species of both study sites were replaced with the newly derived PFTs and projected cover abundance-weighted means calculated for every plot. Functional communities were defined by classifications of the abundance-weighted PFT data in the respective sites. Distance-based redundancy analysis (using the abundance-weighted community and environmental data) was used to infer drivers of the functional community patterns for each site.A classification based on trait data assisted in reducing trait-space complexity in the studied vegetation and revealed 26 PFTs shared across the study sites. In total, seven functional communities were identified. We demonstrate a putative functional-community pattern-driving effect of soil-texture (clay—sand) gradients at Eneabba (42% of the total inertia explained) and that of water repellence at Cooljarloo (36%). Synthesis. This paper presents a procedure formalising the classification of multiple response traits leading to the delineation of PFTs and functional communities. This step captures plant responses to stresses and disturbance characteristic of kwongan vegetation, including low nutrient status, water stress, and fire (a landscape-level disturbance factor). Our study is the first to introduce a formal procedure assisting their formal recognition. Our results support the role of short-term abiotic drivers structuring the formation of fine-scale functional community patterns in a complex, species-rich vegetation of Western Australia.

Predicting amphibian intraspecific diversity with machine learning: Challenges and prospects for integrating traits, geography, and genetic data

The growing availability of genetic datasets, in combination with machine learning frameworks, offer great potential to answer long-standing questions in ecology and evolution. One such question has intrigued population geneticists, biogeographers, and conservation biologists: What factors determine intraspecific genetic diversity? This question is challenging to answer because many factors may influence genetic variation, including life history traits, historical influences, and geography, and the relative importance of these factors varies across taxonomic and geographic scales. Furthermore, interpreting the influence of numerous, potentially correlated variables is difficult with traditional statistical approaches. To address these challenges, we analyzed repurposed data using machine learning and investigated predictors of genetic diversity, focusing on Nearctic amphibians as a case study. We aggregated species traits, range characteristics, and >42,000 genetic sequences for 299 species using open-access scripts and various databases. After identifying important predictors of nucleotide diversity with random forest regression, we conducted follow-up analyses to examine the roles of phylogenetic history, geography, and demographic processes on intraspecific diversity. Although life history traits were not important predictors for this dataset, we found significant phylogenetic signal in genetic diversity within amphibians. We also found that salamander species at northern latitudes contain lower genetic diversity. Data repurposing and machine learning provide valuable tools for detecting patterns with relevance for conservation, but concerted efforts are needed to compile meaningful datasets with greater utility for understanding global biodiversity.

Population genetic structure and classification of cultivated and wild pea (Pisum sp.) based on morphological traits and SSR markers

Pea (Pisum sativum L.) is an important legume crop that is widely grown worldwide for human consumption and livestock feed. Despite extensive studies, the population genetic structure and classification of cultivated and wild pea (Pisum sp.) are remaining controversial. To characterize patterns of genetic and morphological variation and investigate the classification of Pisum, we conducted comprehensive population genetic analyses for 323 accessions from cultivated and wild pea representing three species of Pisum utilizing 34 morphological traits and 87 polymorphic SSR markers. First, we identified three distinct genetic groups among all samples. Group I was primarily composed of Pisum fulvum, Pisum abyssinicum and some wild P. sativum accessions, whereas groups II and III consisted of the two genetic groups under P. sativum representing different geographic distributions of cultivated pea. Analyses of morphological variation revealed significant differences among the three species. Second, among pea germplasms representing eight taxa of Pisum, P. fulvum and P. abyssinicum possessed unique genetic backgrounds and morphological characteristics, corroborating their independent species status. The intraspecific subdivisions of P. sativum described by some authors were not supported in this study, with the exception of several genotypes of P. sativum subsp. elatius that were clustered with P. fulvum and P. abyssinicum. Finally, we confirmed that the Chinese pea germplasm was genetically distinct and could be divided into two genetic groups, each of which included both spring-sowing and autumn-sowing ecotypes. These results provide a robust foundation for understanding pea domestication and the utilization of wild genetic resources of pea.

Data from: Victims of ancient hyperthermal events herald the fates of marine clades and traits under global warming

Organismic groups vary non-randomly in their vulnerability to extinction. However, it is unclear whether the same groups are consistently vulnerable, regardless of the dominant extinction drivers, or whether certain drivers have their own distinctive and predictable victims. Given the challenges presented by anthropogenic global warming, we focus on changes in extinction selectivity trends during ancient hyperthermal events: geologically rapid episodes of global warming. Focusing on the fossil record of the last 300 million years, we identify clades and traits of marine ectotherms that were more prone to extinction under the onset of six hyperthermal events than during other times. Hyperthermals enhanced the vulnerability of marine fauna that host photosymbionts, particularly zooxanthellate corals, the reef environments they provide, and genera with actively burrowing or swimming adult life-stages. The extinction risk of larger-sized fauna also increased relative to non-hyperthermal times, while genera with a poorly buffered internal physiology did not become more vulnerable on average during hyperthermals. Hyperthermal-vulnerable clades include rhynchonelliform brachiopods and bony fish, whereas resistant clades include cartilaginous fishes, and ostreid and venerid bivalves. These extinction responses in the geological past mirror modern responses of these groups to warming, including range shift magnitudes, population losses, and experimental performance under climate-related stressors. Accordingly, extinction mechanisms distinctive to rapid global warming may be indicated, including sensitivity to warming-induced seawater deoxygenation. In anticipation of modern warming-driven marine extinctions, the trends illustrated in the fossil record offer an expedient preview.

Plant size and leaf traits for epiphyte species found in flooded gallery forests and non-flooded gallery forests in Central Brazil

Despite their unique adaptations to thrive in canopy environments without access to soil resources, epiphytes are underrepresented in studies of functional traits and of functional composition of tropical plant communities. We investigated functional traits of spermatophytic (seed-bearing) C3 and CAM epihyte communities in flooded and non-flooded gallery forests in Central Brazil. The two forest types differ in floristic, structure, microclimate and edaphic conditions. We studied plant size, leaf thickness, leaf dry matter content, leaf area, specific leaf area, leaf C, N, P, K, Mg, Ca and C and N stable isotope ratios. Because photosynthetic pathway (C3 or CAM) is an important aspect of ecologial differentiation of spermatophytic epiphytes, we expected that functional trait syndromes in a multivariate space would be more associated with photosynthetic pathway than forest type and changes in abundance of C3 and CAM epiphytes would drive functional trait composition at the community level. C3 and CAM epiphytes segregated in the multivariate trait space, however more complex functional typologies were also evident. Despite lower light levels, CAM epiphytes were more abundant in the flooded gallery forest. There, they accounted for 80% of all individuals, whereas C3 epiphytes dominated in the non-flooded forest. These large differences in the proportion of C3 and CAM epiphytes strongly affected functional trait values at the community level, despite very little intraspecfic variation in trait values between forest types for species that occurred in both forests.

opencc-by-4.0Nov 2020View details →

Quantile regression in genomic selection for oligogenic traits in autogamous plants: a simulation study

This study assessed the efficiency of Genomic selection (GS) or genome‐wide selection (GWS), based on Regularized Quantile Regression (RQR), in the selection of genotypes to breed autogamous plant populations with oligogenic traits. To this end, simulated data of an F2 population were used, with traits with different heritability levels (0.10, 0.20 and 0.40), controlled by four genes. The generations were advanced (up to F6) at two selection intensities (10% and 20%). The genomic genetic value was computed by RQR for different quantiles (0.10,0.50 and 0.90), and by the traditional GWS methods, specifically RR-BLUP and BLASSO. A second objective was to find the statistical methodology that allows the fastest fixation of favorable alleles. In general, the results of the RQR model were better than or equal to those of traditional GWS methodologies, achieving the fixation of favorable alleles in most of the evaluated scenarios. At a heritability level of 0.40 and a selection intensity of 10%, RQR (0.50) was the only methodology that fixed the alleles quickly, i.e., in the fourth generation. Thus, it was concluded that the application of RQR in plant breeding, to simulated autogamous plant populations with oligogenic traits, could reduce time and consequently costs, due to the reduction of selfing generations to fix alleles in the evaluated scenarios.

opencc-zeroDec 2020View details →

The timing of leaf senescence relates to flowering phenology and functional traits in 17 herbaceous species along elevational gradients

1. Leaf senescence is a major event in a plant's life history as autumn marks the end of the growing season. The optimal timing of leaf senescence is crucial to both, minimize risks of low temperature events and maximize carbon gain during the growing season. As abiotic conditions are currently changing at unprecedented rates, it is important to study how leaf senescence of different species is responding to these changes in order to forecast future growing season length and carbon sequestration potentials. In contrast to flowering phenology, data on autumn events is scarce and even more so for herbaceous than for woody plants, thus more information on this phenological stage is urgently needed. 2. We studied leaf senescence of 632 populations from 17 herbaceous species located along elevational gradients. We focussed on the beginning (5% of the population senesce, LS5) and peak (50% senesce, LS50) of leaf senescence. To see whether we can predict species-specific changes, we studied the link between LS5 and LS50 and flowering phenology as well as leaf functional traits related to plant performance. We looked at first and last flowering day and flowering duration as well as the traits specific leaf area, leaf dry matter content, area based leaf nitrogen and carbon content, carbon isotope discrimination (Δ13C), and the stomatal pore area index. 3. We found species-specific slopes of the beginning of leaf senescence along the elevational gradient. The peak of leaf senescence was uniformly delayed with increasing elevation across all species. Flowering phenology as well as leaf functional traits had a close relationship with leaf senescence and thus can be used to forecast species-specific responses to changes in abiotic conditions. High SLA and high leaf nitrogen were related to earlier senescence while high LDMC, high Δ13C and high SPI to later senescence. 4. Synthesis: The link between senescence, flowering phenology and plant functional traits will help to fine-tune predictions of future growing season length and ecosystem function. To date, most analyses are based on spring phenology and traits, for which data is more abundant than data on autumn senescence.

opencc-by-4.0Dec 2020View details →

Homozygosity mapping reveals population history and trait architecture in self- incompatible pear (Pyrus spp.)

opencc-by-4.0Dec 2020View details →

Homozygosity mapping reveals population history and trait architecture in self- incompatible pear (Pyrus spp.)

Runs of homozygosity (ROH) are successive homozygous segments of the genome where the two haplotypes inherited from the parents are identical-by-descent. A key focus of this project is to investigate ROH distribution patterns in the genomes of outbred fruit crops using pear as a study caseRuns of homozygosity (ROH) are successive homozygous segments of the genome where the two haplotypes inherited from the parents are identical-by-descent. A key focus of this project is to investigate ROH distribution patterns in the genomes of outbred fruit crops using pear as a study case

opencc-by-4.0Dec 2020View details →

Homozygosity mapping reveals population history and trait architecture in self- incompatible pear (Pyrus spp.)

opencc-zeroDec 2020View details →

Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: lessons from natural assemblages

1. Functional diversity assessments are crucial and increasingly used for understanding ecological processes and managing ecosystems. The functional diversity of a community is assessed by sampling traits at one or more scales (individuals, populations, species) and calculating a summary index of the variation in trait values. However, it remains unclear how the scale at which traits are sampled and the indices used to estimate functional diversity may alter the patterns observed and inferences about ecological processes. 2. For 40 plant and 61 ant communities, we assess functional diversity using six methods – encompassing various mean-based and probabilistic methods – chosen to reflect common scenarios where different levels of detail are available in trait data. We test whether including trait variability at different scales (from individuals to species) alter functional diversity values calculated using volume-based and dissimilarity-based indices, Functional Richness (FRic) and Rao, respectively. We further test whether such effects alter the functional diversity patterns observed across communities and their relationships with environmental drivers such as abiotic gradients and occurrences of invasive species. 3. Intraspecific trait variability strongly determined FRic and Rao. Methods using only species' mean trait values to calculate FRic (convex hulls) and Rao (Gower-based dissimilarity) distorted the patterns observed when intraspecific trait variability was considered. These distortions generated Type I and Type II errors for the effects of environmental factors structuring the plant and ant communities. 4. The high sensitivity of FRic to individuals with extreme trait values was revealed in comparisons of different probabilistic methods including among-individual and among-population trait variability in functional diversity. By contrast, values and ecological patterns in Rao were consistent among methods including different scales of intraspecific trait variability. 5. Decisions about where traits are sampled and how trait variability is included in functional diversity can drastically change the patterns observed and conclusions about ecological processes. We recommend sampling the traits of multiple individuals per species and capturing their intraspecific trait variability using probabilistic methods. We discuss how intraspecific trait variability can be reasonably estimated and included in functional diversity in the common circumstance where only limited trait data are available.

opencc-zeroApr 2020View details →

C4 photosynthesis and the economic spectra of leaf and root traits independently influence growth rates in grasses

Photosynthetic pathway is an important cause of growth rate variation between species, such that the enhanced carbon uptake of C4 species leads to faster growth than their C3 counterparts. Leaf traits that promote rapid resource acquisition may further enhance the growth capacity of C4 species. However, how root economic traits interact with leaf traits, and the different growth strategies adopted by plants with C3 and C4 photosynthetic pathways is unclear. Plant economic traits could interact with, or act independently of, photosynthetic pathway in influencing growth rate, or C3 and C4 species could segregate out along a common growth rate-trait relationship. We measured leaf and root traits on 100+ grass species grown from seeds in a controlled, common environment to compare with relative growth rates (RGR) during the initial phase of rapid growth, controlling for phylogeny and allometric effects. Photosynthetic pathway acts independently to leaf and root functional traits in causing fast growth. Using C4 photosynthesis, plants can achieve faster growth than their C3 counterparts (by an average 0.04 g g-1 day-1) for a given suite of functional trait values, with lower investments of leaf and root nitrogen. Leaf and root traits had an additive effect on RGR, with plants achieving fast growth by possessing resource-acquisitive leaf traits (high specific leaf area and low leaf dry matter content) or root traits (high specific root length and area, and low root diameter), but having both leads to an even faster growth rate (by up to 0.06 g g-1 day-1). C4 photosynthesis can provide a greater relative increase in RGR for plants with a 'slow' ecological strategy than in those with fast growth. However, aboveground and belowground strategies are not coordinated, so that species can have any combination of 'slow' or 'fast' leaf and root traits. Synthesis: C4 photosynthesis increases growth rate for a given combination of economic traits, and significantly alters plant nitrogen economy in the leaves and roots. However, leaf and root economic traits act independently to further enhance growth. The fast growth of C4 grasses promotes a competitive advantage under hot, sunny conditions.

opencc-zeroJan 2021View details →

Weak genetic signal for phenotypic integration implicates developmental processes as major regulators of trait covariation

Phenotypic integration is an important metric that describes the degree of covariation among traits in a population, and is hypothesized to arise due to selection for shared functional processes. Our ability to identify the genetic and/or developmental underpinnings of integration is marred by temporally overlapping cell-, tissue-, and structure-level processes that serve to continually 'overwrite' the structure of covariation among traits through ontogeny. Here we examine whether traits that are integrated at the phenotypic level, also exhibit a shared genetic basis (e.g., pleiotropy). We micro-CT scanned two hard tissue traits, and two soft tissue traits (mandible, pectoral girdle, atrium, and ventricle respectively) from an F5 hybrid population of Lake Malawi cichlids, and used geometric morphometrics to extract 3D shape information from each trait. Given the large degree of asymmetric variation that may reflect developmental instability, we separated symmetric- from asymmetric-components of shape variation. We then performed quantitative trait loci (QTL) analysis to determine the degree of genetic overlap between shapes. While we found ubiquitous associations among traits at the phenotypic level, except for a handful of notable exceptions, our QTL analysis revealed few overlapping genetic regions. Taken together, this indicates developmental interactions can play a large role in determining the degree of phenotypic integration among traits, and likely obfuscate the genotype to phenotype map, limiting our ability to gain a comprehensive picture of the genetic contributors responsible for phenotypic divergence.

opencc-by-4.0Jan 2021View details →

Estimating individual level plant traits at scale: input data

This dataset includes the input data to ensure replicability of the results. This dataset include the (1) reflectance for individual tree crowns, extracted from field and algorithmically delineated crowns in 2 NEON sites (OSBS and TALL); (2) the associated measures of tree traits (N%, C%, P%, LMA). The folder should be decompressed inside of the root directory of the project in https://github.com/MarconiS/Estimating-individual-level-plant-traits-at-scale/ for correctly replicate the analysis.