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691 results for “plant traits”
Data from: Environmental modulation of plant mycorrhizal traits in the global flora
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Data from: Leaf functional traits predict timing of nutrient resorption and carbon depletion in deciduous subarctic plants
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Data from: Leaf metabolic traits reveal hidden dimensions of plant form and function
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Data for a global meta-analysis of passive experimental warming effects on plant traits and community properties
This database contains the data used in a global meta-analysis of warming effects on plants. L0 data are available upon request; they include the raw data from 126 warming experiments. The L1 data are the result of merged L0 data and are cleaned for typos and are standardized names. L1 data contain plant trait and community property measurements in both warmed and ambient conditions. L2 data contain the effect sizes of warming for each study. These data came from 126 warming experiments across the globe.
Measurement of Plant Traits on Hylocomium splendens Samples Collected at Sites within the Bonanza Creek LTER Regional Site Network in Interior Alaska, 2019
This dataset contains measurements of plant traits on Hylocomium splendens species collected at a subset of sites from the Regional Site Network (n = 26). The two species, Hylocomium splendens and Vaccinium uliginosum, are the two most ubiquitous nonvascular and vascular species at these sites. The traits measured on these species relate to the fire ecology of each species. Traits measured for Hylocomium splendens include: length, width, aspect ratio (width/length), specific leaf area (SLA) and moisture content % at maximum water retention capacity. There is a corresponding dataset with trait data for Vaccinium uliginosum.
Measurement of Plant Traits on Vaccinium uliginosum Samples Collected at Sites within the Bonanza Creek LTER Regional Site Network in Interior Alaska, 2019
This dataset contains measurements of plant traits on Vaccinium uliginosum species collected at a subset of sites from the Regional Site Network (n = 26). The two species, Hylocomium splendens and Vaccinium uliginosum, are the two most ubiquitous nonvascular and vascular species at these sites. The traits measured on these species relate to the fire ecology of each species. Traits measured for Vaccinium uliginosum include: rhizome depth, number of rhizomes, plant height, moisture content % of aboveground tissues, aboveground tissue ratios and dry mass of leaves. There is a corresponding dataset with trait data for Hylocomium splendens.
Species composition and plant functional traits on Hog and Metompkin Islands, VA 2016-2017
Physical characteristics (soil salinity, elevation, distance from shoreline) and biological parameters (species composition, cover, biomass, and functional traits) were measured for plants on Hog Island (Northampton Co. VA) and Metompkin Island (Accomack County, VA). Physical parameters were measured during 2016. Plant biomass, species composition, percent cover, and functional traits were measured in 2017. Data Table 1: Environmental and geographic data on Hog and Metompkin Islands, VA 2016 Data Table 2: Species composition and aboveground plant functional traits on Hog and Metompkin Islands, VA 2017 Data Table 3: Vegetative biomass on Hog and Metompkin Islands, VA 2017 Data Table 4: Plot-level root functional traits on Hog and Metompkin Islands, VA 2017 Data Table 5: Latitude-longitude coordinates of plots on Hog and Metompkin Islands, VA 2016-2017
Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits
<p>Data for the preprint "Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits.”, by Legay N. , Grassein F., Arnoldi C., Segura R., Laîné P., Lavorel S., Clément J.C.</p>
Data from: The effect of root-associated microbes on plant growth and chemical defence traits across two contrasted elevations,
<p>1. Ecotypic differences in plant growth and anti-herbivore defence phenotypes are determined by the complex interactions between the abiotic and the biotic environment.</p> <p>2. Root-associated microbes (RAMs) are pervasive in nature, vary over climatic gradients, and have been shown to influence the expression of multiple plant functional traits related to biomass accumulation and biotic interactions. We addressed how variation in climatic conditions between lowland and sub-alpine habitats in the Alps and RAMs can independently or interactively affect plant growth and anti-herbivore defence trait expression.</p> <p>3. To address the contribution of climate and RAMs on growth and chemical defences of high- and low-elevation Plantago major ecotypes, we performed a full-factorial reciprocal transplant field experiment at two elevations. We coupled it with plant functional trait measurements and metabolomics analyses.</p> <p>4. We found that local growing climatic conditions mostly influenced how the ecotypes grew, but we also found that the high- and low-elevation ecotypes improved biomass accumulation if in the presence of their own-elevation RAMs. Second, we found that while chemical defence expression was affected by climate, they were also more highly expressed when plants were inoculated with low elevation RAMs.</p> <p>5. Synthesis – Our research demonstrated that RAMs from contrasted elevations impact how plants grow or synthesize toxic secondary metabolites. At low elevation, where biotic interactions are stronger, RAMs enhance plant biomass accumulation and the production of toxic secondary metabolites.</p>
Independent evolutionary changes in fine-root traits among main clades during the diversification of seed plants
<p><b>Rationale</b>: Changes in fine-root morphology are typically associated with transitions from the ancestral arbuscular mycorrhizal (AM) to the alternative ectomycorrhizal (ECM) or non-mycorrhizal (NM) associations. However, the modifications in root morphology may also coincide with new modifications in leaf hydraulics and growth habit during angiosperm diversification. These hypotheses have not been evaluated concurrently, which limits our understanding of the causes of fine-root evolution.</p> <p><b>Methods</b>: To explore the evolution of fine-root systems, we assembled a 600+ species database to reconstruct historical changes in seed plants over time. We utilize ancestral reconstruction approaches together with phylogenetically informed comparative analyses to test whether changes in fine-root traits were most strongly associated with mycorrhizal affiliation, leaf hydraulics or growth form.</p> <p><b>Key Results</b>: Our findings show significant shifts in root diameter, specific root length and root tissue density as angiosperms diversified, largely independent from leaf changes or mycorrhizal affiliation. Growth form was the only factor associated with fine-root traits in statistical models including mycorrhizal association and leaf venation, suggesting substantial modifications in fine-root morphology during transitions from woody to non-woody habits.</p> <p><b>Conclusion</b>: Divergences in fine-root systems were crucial in the evolution of seed plant lineages, with important implications for ecological processes in terrestrial ecosystems.</p>
Data from: Drivers of plant traits that allow survival in wetlands
<ol> <li>Plants have developed a suite of traits to survive the anaerobic and anoxic soil conditions in wetlands. Previous studies on wetland plant adaptive traits have focused mainly on physiological aspects under experimental conditions, or compared the trait expression of the local species pool. Thus, a comprehensive analysis of potential factors driving wetland plant adaptive traits under natural environmental conditions is still missing.</li> <li>In this study, we analysed three important wetland adaptive traits, i.e. root porosity, root/shoot ratio and underwater photosynthetic rate, to explore driving factors using a newly compiled dataset of wetland plants. Based on 21 studies at 38 sites across different biomes, we found that root porosity was affected by an interaction of temperature and hydrological regime; root:shoot ratio was affected by temperature, precipitation and habitat type; and underwater photosynthetic rate was affected by precipitation and life form. This suggests that a variety of driving mechanisms affect the expression of different adaptive traits.</li> <li>The quantitative relationships we observed between the adaptive traits and their driving factors will be a useful reference for future global methane and denitrification modelling studies. Our results also stress that besides the traditionally emphasized hydrological driving factors, other factors at several spatial scales should also be taken into consideration in the context of future functional wetland ecology.</li> </ol>
Data from: Addition of nitrogen to canopy versus understory has different effects on leaf traits of understory plants in a subtropical evergreen broad–leaved forest
<p>Atmospheric nitrogen (N) deposition has substantial effects on forest ecosystems. The effects of N deposition on understory plants have been simulated by spraying N on the forest floor. Such understory addition of N (UAN) might simulate atmospheric N deposition in a biased manner, because it bypasses the canopy.</p> <p>We compared the effects of UAN and canopy addition of N (CAN) at 0, 25, and 50 kg N ha<sup>–1</sup> year<sup>–1</sup> on specific leaf area (SLA), leaf construction costs (CC), concentrations of leaf carbon ([C]), nitrogen ([N]), phosphorus ([P]), minerals ([Mineral]), nitrate ([NO<sub>3</sub><sup>-</sup>]), lignin ([Lignin]), lipids ([Lipid]), organic acids ([OA]), soluble phenolics ([SP]), total non-structural carbohydrates ([TNC]), and total structural carbohydrates ([TSC]) in six dominant understory species in a subtropical evergreen forest after five years of N treatments.</p> <p>We found that leaf CC, [C], [Lignin], [OA], [TNC] and [TSC] were significantly affected by N-addition approach and rate, but leaf [P] and [Lipid] were affected by N-addition approach and N-addition rate, respectively; leaf CC, [C], [P], [OA], and [TNC] were significantly lower under UAN than under CAN, but leaf [TSC] and [Lignin] were significantly higher and lower, respectively, under UAN than under CAN at 50 kg N ha<sup>–1</sup> year<sup>–1</sup>; the decline of leaf [C] and [Lignin] contributed to the significantly lower leaf CC under UAN than under CAN.</p> <p><em>Synthesis</em>. We show that canopy and understory N addition exerted significantly different effects on leaf traits of understory plants. The results indicate that understory plants in subtropical forest respond differently to understory addition of N from those to atmospheric deposition of N. Further studies are warranted to evaluate the unbiased ecological processes and functions of forest ecosystem responding to atmospheric N deposition via both canopy and understory N addition experiments over a longer term.</p>
Data from: Plant trait response of tundra shrubs to permafrost and nutrient addition
<p>Plants may alter their strategies, such as growth and resource acquisition, as a result of climate change, especially in areas like the Arctic. These changes might affect in turn ecosystem functions and vegetation-climate interactions. Plant traits reflect both strategies and plant trade-offs in response to environmental conditions. In combination with observational data, experiments mimicking future climate conditions and data involving multiple leaf and stem traits, can contribute to a better mechanistic understanding of feedbacks between shrub growth strategies, permafrost thaw and carbon and energy fluxes.</p> <p>This dataset contains both metadata and plant trait data measured in individuals of four arctic shrub species under experimental conditions. The permafrost thaw and fertilization experiment (Peng et al., 2017) ran for four years (2011-2014) in the nature reserve of Kytalyk, north-eastern Siberia (70°49'N, 147°28'E). The shrub species, dominant at the research site, were the deciduous species <em>Betula nana</em> ssp. <em>exilis</em> (Sukazcev) Hultén and <em>Salix pulchra</em> Cham., and the evergreen species <em>Ledum palustre</em> ssp. <em>decumbens</em> (Aiton) Hultén and <em>Vaccinium vitis-idaea</em> L.</p>
Data from: Trait matching and phenological overlap increase the spatio-temporal stability and functionality of plant-pollinator interactions
<p>Morphology and phenology influence plant-pollinator network structure, but whether they generate more stable pairwise interactions with higher pollination success is unknown. Here we evaluate the importance of morphological trait matching, phenological overlap and specialisation for the spatio-temporal stability (measured as variability) of plant-pollinator interactions and for pollination success, while controlling for species abundance. To this end, we combined a six-year plant-pollinator interaction dataset, with information on species traits, phenologies, specialisation, abundance and pollination success, into structural equation models. Interactions among abundant plants and pollinators with well-matched traits and phenologies formed the stable and functional backbone of the pollination network, whereas poorly-matched interactions were variable in time and had lower pollination success. We conclude that phenological overlap could be more useful for predicting changes in species interactions than species abundances, and that non-random extinction of species with well-matched traits could decrease the stability of interactions within communities and reduce their functioning.</p>
Below- and aboveground traits explain local abundance, and regional, continental and global occurrence frequencies of grassland plants
<p>1. Plants vary widely in how common or rare they are, but whether commonness of species is associated with functional traits is still debated. This might partly be because commonness can be measured at different spatial scales, and because most studies focus solely on aboveground functional traits.</p> <p>2. We measured five root traits and seed mass on 241 Central European grassland species, and extracted their specific leaf area, height, mycorrhizal status and bud-bank size from databases. Then we tested if trait values are associated with commonness at seven spatial scales, ranging from abundance in 16-m² grassland plots, via regional and European-wide occurrence frequencies, to worldwide naturalization success.</p> <p>3. At every spatial scale, commonness was associated with at least three traits. The traits explained the greatest proportions of variance for abundance in grassland plots (42%) and naturalization success (41%), and the least for occurrence frequencies in Europe and the Mediterranean (2%). Low root tissue density characterized common species at every scale, whereas other traits showed directional changes depending on the scale. We also found that many of the effects had significant non-linear effects, in most cases with the highest commonness-metric value at intermediate trait values. Across scales, belowground traits explained overall more variance in species commonness (19.4%) than aboveground traits (12.6%).</p> <p>4. The changes we found in the relationships between traits and commonness, when going from one spatial scale to another, could at least partly explain the maintenance of trait variation in nature. Most importantly, our study shows that within grasslands, belowground traits are at least as important as aboveground traits for species commonness. Therefore, belowground traits should be more frequently considered in studies on plant functional ecology.</p>
Data from: Integration and harmonization of trait data from plant individuals across heterogeneous sources
<p>Trait data represent the basis for ecological and evolutionary research and have relevance for biodiversity conservation, ecosystem management and earth system modelling. The collection and mobilization of trait data has strongly increased over the last decade, but many trait databases still provide only species-level, aggregated trait values (e.g. ranges, means) and lack the direct observations on which those data are based. Thus, the vast majority of trait data measured directly from individuals remains hidden and highly heterogeneous, impeding their discoverability, semantic interoperability, digital accessibility and (re-)use. Here, we integrate quantitative measurements of verbatim trait information from plant individuals (e.g. lengths, widths, counts and angles of stems, leaves, fruits and inflorescence parts) from multiple sources such as field observations and herbarium collections. We develop a workflow to harmonize heterogeneous trait measurements (e.g. trait names and their values and units) as well as additional information related to taxonomy, measurement or fact and occurrence. This data integration and harmonization builds on vocabularies and terminology from existing metadata standards and ontologies such as the Ecological Trait-data Standard (ETS), the Darwin Core (DwC), the Thesaurus Of Plant characteristics (TOP) and the Plant Trait Ontology (TO). A metadata form filled out by data providers enables the automated integration of trait information from heterogeneous datasets. We illustrate our tools with data from palms (family Arecaceae), a globally distributed (pantropical), diverse plant family that is considered a good model system for understanding the ecology and evolution of tropical rainforests. We mobilize nearly 140,000 individual palm trait measurements in an interoperable format, identify semantic gaps in existing plant trait terminology and provide suggestions for the future development of a thesaurus of plant characteristics. Our work thereby promotes the semantic integration of plant trait data in a machine-readable way and shows how large amounts of small trait data sets and their metadata can be integrated into standardized data products.</p>
Data from: Trait-based formal definition of plant functional types and functional communities in the multi-species and multi-traits context
<p>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.</p>
Plant size and leaf traits for epiphyte species found in flooded gallery forests and non-flooded gallery forests in Central Brazil
<p>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) C<sub>3</sub> 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 (C<sub>3</sub> 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 C<sub>3</sub> and CAM epiphytes would drive functional trait composition at the community level. C<sub>3</sub> 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 C<sub>3</sub> epiphytes dominated in the non-flooded forest. These large differences in the proportion of C<sub>3</sub> 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. </p>
Quantile regression in genomic selection for oligogenic traits in autogamous plants: a simulation study
<p>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 F<sub>2</sub> 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 F<sub>6</sub>) 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.</p>
Estimating individual level plant traits at scale: input data
<p>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.</p>
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.