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193 results for “trait analysis”
Fig. 3 in Gut-content analysis in four species, combined with comparative analysis of trophic traits, suggests an araneophagous habit for the entire family Palpimanidae (Araneae)
Fig. 3 Phylogeny of Palpimanidae plus three other families on the genus level, with estimates of the probabilities of each of five traits at nodes. The fuller the symbol, the higher the probability of a presence of the trait. For trait values at terminals see Table S7
PLATE 1 in Taxonomic Studies Using Multivariate Analysis of Eriobotrya Based on Morphological Traits
PLATE 1. Leaf morphologies of different species in Eriobotrya. Note: the number sequence is consistent with Table 1.
Data from: Independent and interactive effects of plant genotype and environment on plant traits and insect herbivore performance: a meta-analysis with Salicaceae
1. Ecological research has increasingly highlighted the importance of intraspecific variation in shaping the structure and function of communities and ecosystems. Indeed, the effects of intraspecific variation can match or exceed those of interspecific variation. Previous reviews of intraspecific variation in plant traits across heterogeneous environments have focused primarily on mean phenotypic effects. We propose that a richer and fuller understanding of the ecological causes and consequences of intraspecific variation would be provided by partitioning trait variance into its subcomponents (genetic, environment, genotype by environment interaction). 2. We used a meta-analysis of 352 sets of genetic, environment, and genotype by environment (GxE) variation estimates from 72 studies of Salicaceae to compare these sources of variation across plant traits (growth, foliar nitrogen, defense compounds), insect herbivore performance metrics (e.g., survival, growth, fecundity), and environmental conditions (e.g., soil nutrients, water, defoliation). 3. Our findings revealed that variation in levels of defense compounds (both condensed tannins and salicinoids) and insect herbivore performance were primarily genetically determined, while variation in plant growth and foliar nitrogen were more environmentally determined. 4. Plasticity in plant growth, foliar nitrogen levels, and insect herbivore performance varied substantially across different sites (year x location), and nutrient, water, and carbon dioxide environments. Plasticity was lowest for chemical defense traits and all traits in contrasting ozone and defoliation environments. 5. Our quantitative review also revealed several gaps in the literature, including a need for surveying more mature plants (>2 years-old), a wider variety of insect herbivore species (e.g., leaf-modifiers, specialist insects), and underrepresented environmental treatments (e.g., competition, defoliation, disease, light, water). This work will help to assess how the patterns within this meta-analysis may or may not be confined within particular parameters (e.g., plant maturity). 6. Findings from this analysis further highlight the importance of and patterns within intraspecific variation in shaping the evolvability and plasticity of traits and in governing plant-insect interactions.
Figure 2 in Disentangling prey-handling efficiency of larval newts through multivariate prey trait analysis
Figure 2. Biplots of handling efficiency traits ("concealment", "body shape" and "body flexibility") obtained from a fuzzy principal component analysis. See legend of Figure 1 for further explanations.
Figure 1 in Disentangling prey-handling efficiency of larval newts through multivariate prey trait analysis
Figure 1. Biplots of handling efficiency traits ("mobility", "trajectory" and "agility") obtained from a fuzzy principal component analysis. Position of species depending on the prey present in gut contents (A, C, E) and axes interpretation, including the histogram of eigenvalues (B, D, F).
Figure 3 in Disentangling prey-handling efficiency of larval newts through multivariate prey trait analysis
Figure 3. Component analysis of the scores of the eigenvalues grouped by traits ("mobility", "trajectory", "agility", "concealment", "body shape" and "body flexibility"). Eigenvalues are represented by numbers of each axis (1, 2, 3 and 4).
FIGURE. Maximum clade credibility tree of a post-burnin Bayesian analysis (100 million generations), based on nuclear (agt1, ETS, g3pdh, phyC, rpb2) and plastid (atpB–rbcL, matK, rps16, ycf1 pos. 1113-2103, ycf1 pos. 4492-5440) data. Above the branches, Bayesian posterior probabilities (PP) and maximum-likelihood bootstrap support (BS) are shown (PP/BS). The scale bar below the tree shows the branch length for 0.004 substitutions per nucleotide position. Capital letters at the branches are referred to in the tree description. in Re-evaluation of the Amazonian Hylaeaicum (Bromeliaceae: Bromelioideae) based on neglected morphological traits and molecular evidence
FIGURE. Maximum clade credibility tree of a post-burnin Bayesian analysis (100 million generations), based on nuclear (agt1, ETS, g3pdh, phyC, rpb2) and plastid (atpB–rbcL, matK, rps16, ycf1 pos. 1113-2103, ycf1 pos. 4492-5440) data. Above the branches, Bayesian posterior probabilities (PP) and maximum-likelihood bootstrap support (BS) are shown (PP/BS). The scale bar below the tree shows the branch length for 0.004 substitutions per nucleotide position. Capital letters at the branches are referred to in the tree description.
FIGURE 2 in Morphological traits and molecular analysis for two new Chrysosporium species from Fujian Province, China
FIGURE 2. Colony and conidiogenous structures of Chrysosporium laterisporum (GZUIFR-G310, holotype). A, B. Conidiogenous structures. C. Conidia. D, E. Colony (top and reverse) on PDA. Bars A–C = 10 μm, D–E = 10 mm.
FIGURE 1 in Morphological traits and molecular analysis for two new Chrysosporium species from Fujian Province, China
FIGURE 1. Phylogenetic tree of Chrysosporium spp. constructed from ITS-5.8S rDNA sequences. Statistical support values (Bayesian posterior probability/ML/MP) are shown at the nodes. The tree was rooted using Myceliophthora thermophila as outgroup.
FIGURE 3 in Morphological traits and molecular analysis for two new Chrysosporium species from Fujian Province, China
FIGURE 3. Colony and conidiogenous structures of Chrysosporium ovalisporum (GZUIFR-G446, holotype). A–C. Conidiogenous structures. D. Conidia. E–F. Colonies (reverse and top) on PDA. Bars A–D = 10 µm, E–F. = 10 mm.
Data and scripts from: Exploratory analysis of multi-trait coadaptations in the light of population history
<p><span>During the process of range expansion, populations encounter a variety of environments. They respond to the local environments by modifying their mutually interacting traits. Common approaches of landscape analysis include first focusing on the genes that undergo diversifying selection or directional selection in response to environmental variation. To understand the whole history of populations, it is ideal to capture the history of their range expansion with reference to the series of surrounding environments and to infer the multi-trait coadaptation. To this end, we propose a complementary approach; it is an exploratory analysis using up-to-date methods that integrates population genetic features and features of selection on multiple traits. First, we conduct correspondence analysis of site frequency spectra, traits and environments with auxiliary information of population-specific fixation index (FST). This visualizes the structure and the ages of populations and helps infer the history of range expansion, encountered environmental changes and selection on multiple traits. Next, we further investigate the inferred history using an admixture graph that describes the population split and admixture. Finally, principal component analysis of the </span><span>selection on edge-by-trait (SET) matrix identifies multi-trait coadaptation and the associated edges of the admixture graph. We introduce a newly defined factor loadings of environmental variables in order to identify the environmental factors that caused the coadaptation. A numerical simulation of one-dimensional stepping-stone population expansion showed that the exploratory analysis reconstructed the pattern of the environmental selection that was missed by analysis of individual traits. Analysis of a public dataset of natural populations of black cottonwood in northwestern America identified the first principal component (PC) coadaptation of photosynthesis- vs growth-related traits responding to the geographical clines of temperature and daylength. The second PC coadaptation of volume-related traits suggested that soil condition was a limiting factor for above-ground environmental selection.</span></p>
Fig. 3 in Fatty acids as chemotaxonomic and ecophysiological traits in green microalgae (desmids, Zygnematophyceae, Streptophyta): A discriminant analysis approach
Fig. 3. Linear discriminant analysis based on fatty acid profiles of desmid strains belonging to the time-isolation group. (a) Discrimination of the clusters ("very old", "old" and "new") at the start of cultivation (2 days). (b) Discrimination of the clusters at the end of cultivation (24 days). DF1 – the first discrimination function 1; DF2 – the second discrimination function; red triangles – strains cultivated> 35 years ("very old"); green quadrangles – strains cultivated between 15 and 35 years ("old"); blue circles – strains cultivated ≤ 15 years ("new"). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Fatty acids as chemotaxonomic and ecophysiological traits in green microalgae (desmids, Zygnematophyceae, Streptophyta): A discriminant analysis approach
Fig. 2. Linear discriminant analysis based on fatty acid profiles of desmid strains belonging to the trophic-preference group. (a) Discrimination of the clusters (oligotrophic, meso-oligotrophic, meso-eutrophic, and eutrophic) at the start of cultivation (2 days). (b) Discrimination of the clusters at the end of cultivation (24 days). DF1 – the first discrimination function 1; DF2 – the second discrimination function; red triangles – eutrophic strains; orange quadrangles – meso-eutrophic strains; green pentangles – meso-oligotrophic strains; blue circles – oligotrophic strains. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Data from: Selection analysis on the rapid evolution of a secondary sexual trait
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Quantitative trait locus analysis of parasitoid counteradaptation to symbiont-conferred resistance
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Data from: Comparative analysis of ear-hole closure identifies epimorphic regeneration as a discrete trait in mammals
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Data from: Quantifying the effects of ecological constraints on trait expression using novel trait-gradient analysis parameters
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Data from: Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants
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Data from: Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations
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Data from: Trait-dependant tolerance of bats to urbanisation: a global meta-analysis
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.