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A main goal of ecological and evolutionary biology is understanding and predicting interactions between populations and both abiotic and biotic environments, the spatial and temporal variation of these interactions, and the effects on population dynamics and performance. Trait-based approaches can help to model these interactions and generate a comprehensive understanding of ecosystem functioning. A central tool is the collation of databases that include species trait information. Such centralized databases have been set up for a number of organismal groups but is lacking for one of the most important groups of predators in terrestrial ecosystems – spiders. Here we promote the collation of an open spider traits database, integrated into the global Open Traits Network. We explore the current collation of spider data and cover the logistics of setting up a global database, including which traits to include, the source of data, how to input data, database governance, geographic cover, accessibility, quality control and how to make the database sustainable long-term. Finally, we explore the scope of research questions that could be investigated using a global spider traits database.

Juniperus excelsa is one of the most common tree species and has a wide geographical and altitudinal distribution in Turkey. It is also resistant to drought and frost damages and can cope with poor soils. In this study, we explore whether there are any differences among eight J. excelsa populations from a narrow geographic region grown in a common garden test site in terms of growth and contents of photosynthetic pigments, proline and nutrients of their 10-year-old saplings. Phenotypic trait differentiation (QST) at all traits, FST at neutral SSRs among six of the populations and associations of traits with environmental conditions at provenance regions were also analysed to test for patterns of local adaptation. Sapling traits of eight J. excelsa populations of from Lakes District in Turkey at the test site showed that populations significantly differed for growth, photosynthetic pigments, proline and nutrient contents. The mean height and diameter of 10-year-old saplings were found as 94.5 cm and 41.6 mm, respectively. Egirdir-Barla and Sütçüler-Tota populations showed the highest performance for the majority of traits at age 10 compared to all other populations. Nutrient contents in leaves were generally in the sufficiency range reported for plant growth. Considering photosynthetic pigments and proline, it could be concluded that the populations were not exposed to severe stress. Among the environmental variables, the best predictors of growth were annual mean minimum temperature and soil texture at the populations’ origin, accounting for 49% of the variation in height and diameter, respectively. Also, higher phenotypic trait differentiation for most traits than genetic differentiation at neutral genetic markers suggests local adaptation at a small geographic scale. The present study revealed adaptive divergence between populations at a small geographic scale. However, environmental similarity between region of origin and test site was not a good indicator of growth-related traits. The results can be used in the early selection of provenances for J. excelsa for plantation establishment.

Increases in biodiversity can result from an increase in species richness, as well as from a higher genetic diversity within species. Intraspecific genetic diversity, measured as the number of genotypes, can enhance plant primary productivity and have cascading effects at higher trophic levels, such as an increase in herbivore and predator richness. The positive effects of genotypic mixtures are not only determined by additive effects, but also by interactions among genotypes, such as facilitation or inhibition. However, so far there has been no effort to predict the extent of such effects. In this study, we address the question of whether the magnitude of the effect of genotype number on population performance can be explained by the extent of dissimilarity in key traits among genotypes in a mixture. We examine the relative contribution of genotype number and phenotypic dissimilarity among genotypes to population performance of the soil arthropod, Orchesella cincta . Nearly homogeneous genotypes were created from inbred isofemale lines. Phenotypic dissimilarity among genotypes was assessed in terms of three life-history traits that are associated with population growth rate, i.e., egg size, egg development time, and juvenile growth rate. A microcosm experiment with genotype mixtures consisting of one, two, four, and eight genotypes, showed that genotypic richness strongly increased population size and biomass production and was associated with greater net diversity effects. Most importantly, there was a positive log-linear relationship between phenotypic dissimilarity in a mixture and the net diversity effects for juvenile population size and total biomass. In other words, the degree of phenotypic dissimilarity among genotypes determined the magnitude of the genotypic richness effect, although this relationship leveled off at higher values of phenotypic dissimilarity. Although the exact mechanisms responsible for these effects are currently unknown, similar advantages of trait dissimilarity have been found among species. Hence, to better understand population performance, genotype number and phenotypic dissimilarity should be considered collectively.

The primary objective of this study was to assess metabolomics for its capacity to discern biological variation among 10 full-sib families of a Douglas-fir tree breeding population, replicated on two sites. The differential accumulation of small metabolites in developing xylem was examined through metabolite profiles (139 metabolites common to 181 individual trees) generated by gas chromatography mass spectrometry and a series of statistical analyses that incorporated family, site, and tree growth and quantitative phenotypic wood traits (wood density, microfibril angle, wood chemistry and fiber morphology). Multivariate discriminant, canonical discriminant and factor analyses and broad-sense heritabilities revealed that metabolic and phenotypic traits alike were strongly related to site, while similar associations relating to genetic (family) structure were weak in comparison. Canonical correlation analysis subsequently identified correlations between specific phenotypic traits (i.e. tree growth, fibre morphology and wood chemistry) and metabolic traits (i.e. carbohydrate and lignin biosynthetic metabolites), demonstrating a coherent relationship between genetics, metabolism, environmental and phenotypic expression in wood-forming tissue. The association between cambial metabolites and tree phenotype, as revealed by metabolite profiling, demonstrates the value of metabolomics for systems biology approaches to understanding tree growth and secondary cell wall biosynthesis in plants.

Human genetics has been haunted by the mystery of \"missing heritability\" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator—that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating \"phantom heritability.\" Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.

Stay-green (sometimes staygreen) refers to the heritable delayed foliar senescence character in model and crop plant species. In a cosmetic stay-green, a lesion interferes with an early step in chlorophyll catabolism. The possible contribution of synthesis to chlorophyll turnover in cosmetic stay-greens is considered. In functional stay-greens, the transition from the carbon capture period to the nitrogen mobilization (senescence) phase of canopy development is delayed, and/or the senescence syndrome proceeds slowly. Yield and composition in high-carbon (C) crops such as cereals, and in high-nitrogen (N) species such as legumes, reflect the source–sink relationship with canopy C capture and N remobilization. Quantitative trait loci studies show that functional stay-green is a valuable trait for improving crop stress tolerance, and is associated with the domestication syndrome in cereals. Stay-green variants reveal how autumnal senescence and dormancy are coordinated in trees. The stay-green phenotype can be the result of alterations in hormone metabolism and signalling, particularly affecting networks involving cytokinins and ethylene. Members of the WRKY and NAC families, and an ever-expanding cast of additional senescence-associated transcription factors, are identifiable by mutations that result in stay-green. Empirical selection for functional stay-green has contributed to increasing crop yields, particularly where it is part of a strategy that also targets other traits such as sink capacity and environmental sensitivity and is associated with appropriate crop management methodology. The onset and progress of senescence are phenological metrics that show climate change sensitivity, indicating that understanding stay-green can contribute to the design of appropriate crop types for future environments.

Epigenetics is receiving growing attention in the plant science community. Epigenetic modifications are thought to play a particularly important role in fluctuating environments. It is hypothesized that epigenetics contributes to plant phenotypic plasticity because epigenetic modifications, in contrast to DNA sequence variation, are more likely to be reversible. The population of decrease in DNA methylation 1-2 (ddm1-2)-derived epigenetic recombinant inbred lines (epiRILs) in Arabidopsis thaliana is well suited for studying this hypothesis, as DNA methylation differences are maximized and DNA sequence variation is minimized. Here, we report on the extensive heritable epigenetic variation in plant growth and morphology in neutral and saline conditions detected among the epiRILs. Plant performance, in terms of branching and leaf area, was both reduced and enhanced by different quantitative trait loci (QTLs) in the ddm1-2 inherited epigenotypes. The variation in plasticity associated significantly with certain genomic regions in which the ddm1-2 inherited epigenotypes caused an increased sensitivity to environmental changes, probably due to impaired genetic regulation in the epiRILs. Many of the QTLs for morphology and plasticity overlapped, suggesting major pleiotropic effects. These findings indicate that epigenetics contributes substantially to variation in plant growth, morphology, and plasticity, especially under stress conditions.

What is the nature of the genetic changes underlying phenotypic evolution? We have catalogued 1008 alleles described in the literature that cause phenotypic differences among animals, plants, and yeasts. Surprisingly, evolution of similar traits in distinct lineages often involves mutations in the same gene (\"gene reuse\"). This compilation yields three important qualitative implications about repeated evolution. First, the apparent evolution of similar traits by gene reuse can be traced back to two alternatives, either several independent causative mutations or a single original mutational event followed by sorting processes. Second, hotspots of evolution—defined as the repeated occurrence of de novo mutations at orthologous loci and causing similar phenotypic variation—are omnipresent in the literature with more than 100 examples covering various levels of analysis, including numerous gain-of-function events. Finally, several alleles of large effect have been shown to result from the aggregation of multiple small-effect mutations at the same hotspot locus, thus reconciling micromutationist theories of adaptation with the empirical observation of large-effect variants. Although data heterogeneity and experimental biases prevented us from extracting quantitative trends, our synthesis highlights the existence of genetic paths of least resistance leading to viable evolutionary change.

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays 'Fernandez') plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.

Examining biological diversity in an explicitly evolutionary context has been the subject of research for several decades, yet relatively recent advances in analytical techniques and the increasing availability of species-level phylogenies, have enabled scientists to ask new questions. One such approach is to quantify phylogenetic signal to determine how trait variation is correlated with the phylogenetic relatedness of species. When phylogenetic signal is high, closely related species exhibit similar traits, and this biological similarity decreases as the evolutionary distance between species increases. Here, we first review the concept of phylogenetic signal and suggest how to measure and interpret phylogenetic signal in species traits. Second, we quantified phylogenetic signal in primates for 31 variables, including body mass, brain size, life-history, sexual selection, social organization, diet, activity budget, ranging patterns and climatic variables. We found that phylogenetic signal varies extensively across and even within trait categories. The highest values are exhibited by brain size and body mass, moderate values are found in the degree of territoriality and canine size dimorphism, while low values are displayed by most of the remaining variables. Our results have important implications for the evolution of behaviour and ecology in primates and other vertebrates.