Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
163
datasets available to search
ShareScore release 0.9.0
Dataset results
163 results for “plant functional trait”
Data from: Re-growing a tropical dry forest: functional plant trait composition and community assembly during succession
A longstanding goal of ecology and conservation biology is to understand the environmental and biological controls of forest succession. However, the patterns and mechanisms that guide successional trajectories, especially within tropical forests, remain unclear. We collected leaf functional trait and abiotic data across a 110-year chronosequence within a tropical dry forest in Costa Rica. Focusing on six key leaf functional traits related to resource acquisition and competition, along with measures of forest stand structure, we propose a mechanistic framework to link species composition, community trait distributions, and forest structure. We quantified the community-weighted trait distributions for specific leaf area, leaf dry matter concentration, leaf phosphorus concentration, leaf carbon to nitrogen ratio, and leaf stable isotopic carbon and nitrogen. We assessed several prominent hypotheses for how these functional measures shift in response to changing environmental variables (soil water content, bulk density and pH) across the chronosequence. Increasingly, older forests differed significantly from younger forests in species composition, above ground biomass and shifted trait distributions. Early stages of succession were uniformly characterized by lower values of community-weighted mean specific leaf area, leaf stable nitrogen isotope, and leaf phosphorus concentration. Leaf dry matter concentration and leaf carbon to nitrogen ratio were lower during earlier stages of succession, and each trait reached an optimum during intermediate stages of succession. The leaf carbon isotope ratio was the only trait to decrease linearly with increasing stand age indicating reduced water use efficiency in older forests. However, in contrast to expectations, community-weighted trait variances did not generally change through succession, and when compared to null expectations were lower than expected. The observed directional shift in community-weighted mean trait values is consistent with the 'productivity filtering' hypothesis where a directional shift in water and light availability shifts physiological strategies from 'slow' to 'fast'. In contrast to expectations arising from niche based ecology, none of the community trait distributions were over-dispersed. Instead, patterns of trait dispersion are consistent with the abiotic filtering and/or competitive hierarchy hypotheses.
Data from: Variation in plant functional traits is best explained by the species identity: stability of trait based species ranking across meadow management regimes
1. It is commonly assumed in trait-based studies that plant functional traits are species-specific, being more variable among species than among different environmental conditions. If the environment affects traits it is assumed that species react in a similar direction and conserve the functional distances. The rank of species based on the trait values is then unchanged, which justifies the use of species trait averages from database values. Such assumptions of species specificity are, however, increasingly disputed by studies showing overall high intraspecific trait variability. 2. To test the species specificity and ranking stability of functional traits we sampled plant individuals of almost all species (66 in total) within each plot of a long term (19 years) land use management experiment, which comprised a factorial combination of fertilization, mowing and removal of the dominant species Molinia caerulea in an oligotrophic wet meadow in the Czech Republic. Plant individuals were measured for eight commonly used traits: height, leaf dry matter content (LDMC), specific leaf area (SLA), leaf δ13C content, leaf carbon content, leaf δ15N content, and leaf nitrogen content. Height, LDMC, and SLA were also extracted from the LEDA trait database for comparison. 3. Species identity consistently explained the largest portion of trait variability (40%-68%). Land use managements had a considerably lower effect (0.4%-9% of explained trait variability for individual traits). The species trait averages computed for each land use management regime separately were mutually correlated, showing the stable trait-based species ranking. Ranking stability of species trait averages was observed despite land use management changing absolute trait values and despite the tremendous intraspecific trait variability (causing substantial overlap of trait values for different species). For all treatments our measured species averages for LDMC and SLA were also stably ranked with species averages from the LEDA database. 4. Synthesis. Our results showed that species conserve the functional distances in different environmental conditions from where they were measured. Species trait averages can describe general trends in functional composition, although averaging reduces the ecologically interesting information of the intraspecific trait variability.
Invasive earthworms can change understory plant community traits and reduce plant functional diversity
<p>Datasets and R script</p>
Unprocessed PROSAIL-generated datasets of plant functional traits with associated spectra
Open the record for dataset details and reuse information.
Disentangling the roles of plant functional diversity and plaint traits in regulating plant nitrogen accumulation and denitrification in freshwaters
<p>1. There is a growing recognition that functional measures of diversity, based on quantification of functionally important species traits, are useful for explaining variation in ecosystem processes. However, the mechanisms linking functional diversity to different processes remain poorly understood, hindering development of a predictive framework for ecosystem functioning based on species traits.</p> <p>2. The current understanding of how the functional traits of aquatic plants (macrophytes) affect nitrogen (N) cycling by regulating microbial communities and their activity in freshwater habitats is particularly limited. Denitrifying bacteria are typically associated with the roots of both aquatic and terrestrial plants and denitrification is the main cause of loss of N from ecosystems. Disentangling the interplay between plants and microbial denitrifiers is key to understanding variation in rates of denitrification from local to landscape scales.</p> <p>3. In a mesocosm experiment, we varied the species richness (monocultures or two- species mixtures) and composition of macrophytes. We quantified effects of both macrophyte functional diversity, quantified as functional trait dissimilarity, and functional trait composition, quantified as community weighted mean trait values, on N removal in wetlands. We used structural equation modelling to disentangle the direct and indirect influences of traits on N accumulation in plant biomass, denitrification activity and abundance of key bacterial denitrification genes (<i>nirS</i>and <i>nirK</i>).</p> <p>4. Both functional diversity and functional trait composition regulated N removal, explaining 70 – 94% variation in the underlying ecosystem processes. Increased macrophyte functional diversity increased plant N accumulation, and indirectly enhanced denitrification by increasing denitrification gene abundance. Among traits, greater plant relative growth rates, specific leaf area and aboveground biomass increased plant N accumulation. Denitrification activity increased with increasing belowground biomass but decreased with increasing root diameter.</p> <p><span><span><span><span><span><span><span><span><span><span><span>5. These findings improve our understanding of N removal in freshwater wetlands dominated by macrophytes, and have broad ecological implications for wetland management targeting enhanced ecosystem services. Our results highlight the potential for optimising denitrification and plant N accumulation in wetlands and thereby improving water purification by increasing macrophyte functional diversity and ensuring the presence of key traits in macrophyte assemblages.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Grassland management regimes alter the coordination of plant functional traits and nutrient resorption in semiarid grasslands
<p>Grazing and enclosure (grazing exclusion) are the main grassland management regimes that affect nutrient cycling and ecosystem function by altering plant traits. However, the coordination among plant functional traits and nutrient resorption under different grassland management regimes remains unclear. We examined the coordination of eight root and four leaf traits along with the nitrogen (N) and phosphorus (P) resorption efficiencies under four grazing intensities and two enclosure chronosequences in a semiarid steppe ecosystem in China. The principal components analysis (PCA) of root traits and multiple factors analysis of root and leaf traits showed two-dimensional economic spaces at the individual level. Increasing grazing intensity shifts species and community trait composition from conservative to acquisitive with increases in specific root length, specific root area, root alkaline phosphatase activity, and specific leaf area, accelerating nutrient cycling and coordination among traits. Increasing grazing intensity promoted nutrient resorption efficiency. Such adaptations optimize plant nutrient acquisition and nutrient conservation under nutrient-poor conditions. Conversely, long-term enclosure increases plant nutrient and light acquisition by promoting root tissue density, mycorrhizal colonization, and specific leaf area. The conservative (e.g., <em>Stipa grandis</em>) and acquisitive species (e.g., <em>Carex korshinskyi</em>) dominated under grazing, whereas the mid-acquisitive species, including <em>Leymus chinensis</em> and <em>Agropyron cristatum</em>,<em> </em>dominated under enclosure. The observed N and P resorption efficiencies decrease with increasing PC1 score (increase in nutrient acquisition by itself) in root PCA, indicating the trade-off between nutrient-conservative and nutrient-acquisitive strategies. Community-weighted mean traits were primarily driven by intraspecific trait variation, enhancing the adaptability of plants and communities to environmental changes and external stressors. Our study highlights the coordination among above- and below-ground traits, as well as the trade-off between root nutrient acquisition and leaf nutrient resorption under different grassland management regimes in semi-arid grassland ecosystems. From these findings, we conclude that enhancing soil nutrient availability is the most effective approach to the solution to grazing-induced grassland degradation. This knowledge is crucial for devising more effective strategies for sustainable land use and biodiversity conservation in grassland ecosystems.</p>
Dataset for: Temporal trajectories of plant functional traits in mediterranean grasslands under different grazing regimes
<p>The excel file contains three spreadsheets:</p> <ol> <li>the environmental and temporal information about the plot (sample)</li> <li>the plant functional traits of the species (traits)</li> <li>the species composition of the plant communities (species).</li> </ol> <p>These data have been used for the statistical analysis of the manuscript Nour et al., 2024 on Applied Vegetation Science. For more information see the manuscript "Temporal trajectories of plant functional traits in Mediterranean grasslands under different grazing regimes" (Nour et al., 2024).</p>
Plant community composition and traits modulate the impacts of drought intensity on soil microbial community composition and function
<p>Terrestrial ecosystems are increasingly threatened by extreme drought events. Soil microbial communities are central to terrestrial ecosystem function via their role in regulating biogeochemical cycling. Consequently, the impact of increasingly intense drought events on soil microbial communities will have knock-on effects for how ecosystems cope with climate change. In an outdoor grassland mesocosm experiment, we determined how increasing drought intensity affects bacterial and fungal community composition, and functioning, during and after drought. We also tested whether plant community resource acquisition strategy (fast- versus slow-strategy plant communities), plant community composition, and plant functional traits mediate soil microbial responses to increasing drought intensity. We found that increasing drought intensity markedly shifted bacterial and fungal community composition, and these effects persisted until the end of the experiment (two months after re-wetting). Bacterial and fungal communities that experienced severe droughts did not return to baseline composition, while those that experienced a mild drought did. Microbial community functioning (potential extracellular enzyme activity) was reduced at peak drought and shortly after re-wetting. While drought intensity effects on bacterial or fungal communities were insensitive to plant community resource acquisition strategy, functional group abundance (aboveground biomass of grass or forb plant species) composition (grass:forb ratio) and leaf traits (leaf dry matter content and leaf nitrogen concentration) explained significant variation in bacterial and fungal community composition during and after drought. Notably, plant community leaf dry matter content and soil nitrogen were the key factors mediating the effect of increasing drought intensity on microbial indicator taxa (ASVs). We conclude that increasing drought intensity affects grassland soil microbial communities during and after drought, and this impact is influenced by plant community composition and functional traits.</p>
Data from: Microenvironment and functional-trait context dependence predict alpine plant community dynamics
Predicting the structure and dynamics of communities is difficult. Approaches linking functional traits to niche boundaries, species co‐occurrence and demography are promising, but have so far had limited success. We hypothesized that predictability in community ecology could be improved by incorporating more accurate measures of fine‐scale environmental heterogeneity and the context‐dependent function of traits. We tested these hypotheses using long term whole‐community demography data from an alpine plant community in Colorado. Species distributions along microenvironmental gradients covaried with traits important for below‐ground processes. Positive associations between species distributions across life stages could not be explained by abiotic microenvironment alone, consistent with facilitative processes. Rates of growth, survival, fecundity and recruitment were predicted by the direct and interactive effects of trait, microenvironment, macroenvironment and neighbourhood axes. Synthesis. Context‐dependent interactions between multiple traits and microenvironmental axes are needed to predict fine‐scale community structure and dynamics.
Data from: Plant functional traits and environmental conditions shape community assembly and ecosystem functioning during restoration
Recovering biological diversity and ecosystem functioning are primary objectives of ecological restoration, yet these outcomes are often unpredictable. Assessments based on functional traits may help with interpreting variability in both community composition and ecosystem functioning because of their mechanistic and generalizable nature. This promise remains poorly realized, however, because tests linking environmental conditions, functional traits, and ecosystem functioning in restoration are rare. Here, we provide such a test through what is to our knowledge the first empirical application of the 'response–effect trait framework' to restoration. This framework provides a trait-based bridge between community assembly and ecosystem functioning by describing how species respond to environmental conditions based on traits and how the traits of species affect ecosystem functioning. Our study took place across 29 prairies restored from former agricultural fields in southwestern Michigan. We considered how environmental conditions affect ecosystem functioning through and independently of measured functional traits. To do so, we paired field-collected trait data with data on plant community composition and measures of ecosystem functioning and used structural equation modelling to determine relationships between environmental conditions, community-weighted means of functional traits and ecosystem functioning. Environmental conditions were predictive of trait composition. Sites restored directly from tillage (as opposed to those allowed to fallow) supported taller species with larger seeds and higher specific leaf area (SLA). Site age and fire frequency were both negatively related to SLA. We also found a positive relationship between soil moisture and SLA. Both trait composition and environmental conditions predicted ecosystem functioning, but these relationships varied among the measured functions. Pollination mode (animal pollination) increased and fire frequency decreased floral resource availability, seed mass had a negative effect on below-ground biomass production, and vegetative height increased decomposition rate. Soil moisture and fire frequency both increased while site age decreased above-ground biomass production, and site age and soil moisture both increased decomposition rate. Synthesis and applications. Our results suggest that both trait composition and environmental conditions play a role in shaping ecosystem function during restoration, and the importance of each is dependent on the function of interest. Because of this, environmental heterogeneity will be necessary to promote multiple ecosystem functions across restored landscapes. A trait-based approach to restoration can aid interpretation of variable outcomes through insights into community assembly and ecosystem functioning.
Relationships between plant-soil feedbacks and functional traits
<p>Plant-soil feedbacks (PSF) and functional traits are two active but not well theoretically integrated areas of research. However, PSF and traits are both affected by life history evolution, so the two should theoretically be related.</p> <p>We provide a conceptual framework to link plant functional traits to two types of PSF metrics, and hypothesize that individual PSF (plant performance in conspecific versus heterospecific soil) should be related to the fast-slow trait spectrum, while pairwise PSF (the sum of the individual feedbacks for two species growing in each other's soils) should be related to trait dissimilarity. We performed meta-analyses to test these hypotheses by compiling two datasets, one dataset consisting of individual PSF values and plant trait values (specific leaf area, SLA; leaf N concentration, LNC; specific root length, SRL; fine root diameter, FRD; plant height; seed mass), and the second consisting of pairwise PSF values and trait dissimilarity.</p> <p>Our meta-analyses showed that individual PSF values were more negative in faster-growing species with greater SLA, LNC and SRL, supporting the growth-defence trade-off hypothesis. Plant height was positively correlated with individual PSF, perhaps because large, long-lived plants defend against pathogens better than smaller, shorter-lived plants. We also found that larger-seeded species had more positive or less negative PSF, likely reflecting greater tolerance of soil pathogens. The direction of relationships between trait dissimilarity and pairwise PSF varied with trait identity. Dissimilarities in SRL and FRD were negatively correlated with pairwise PSF, while height dissimilarity was positively correlated with pairwise PSF. The contrasting relationships may reflect distinct links between trait dissimilarity and niche and fitness differences.</p> <p>Synthesis. Our results demonstrate how an integration of PSF and trait-based approaches can advance plant community ecology.</p>
Equilibrium in plant functional trait responses to warming is stronger under higher climate variability during the Holocene
Aim.The functional trait composition of plant communities is thought to be largely determined by climate, but relationships between contemporary trait distributions and climate are often weak. Spatial mismatches between trait and climatic conditions are commonly thought to arise from disequilibrium responses to past environmental changes. We here investigated whether current trait-climate disequilibrium were likely to emerge during plant functional responses to Holocene climate warming. Location.North America Time period.14-0Kya Major taxa studied. Terrestrial plants Methods. We joined global trait data with paleoecological time-series and climate simulations on 425 sites. We estimated plant community functional composition for three leaf traits involved in resource use. We then quantified disequilibrium in plant trait temporal responses to climate change during two contrasted periods : a period of high climate variability (14-7 Kya), and a period low climate variability (7-0 Kya). Results. Functional trait composition showed consistent deviation from climatic equilibrium during both periods. The temporal dynamics of trait composition tends to be positively correlated to climate equilibrium expectations during Holocene climate warming (14-7 Kya), but not during a following period of low climate variability (7-0 Kya). Main conclusions.Long-term functional responses of plants to climate change showed mixed evidence for both equilibrium and disequilibrium responses. Temporal trait dynamics were closer to spatial dynamics expectations under high climate variability, indicating that relevance of space-for-time substitution might be partially dependent on climate variability. Our results further suggest that current mismatches between trait and climatic conditions may arise due to a divergence of factors influencing trait dynamics during low climate variability periods. These findings provide a counterpoint to the common assumption that contemporary trait-climate mismatches result from lagged responses to past climate warming. Our study also demonstrates the need for a deeper investigation of the potential influence of non-climatic factors on functional plant community dynamics.
Data from: Nitrogen addition and warming modulate the pathogen impact on plant biomass by shifting intraspecific functional traits and reducing species richness
<p><span>1. </span><span>Foliar fungal pathogens can substantially reduce plant biomass. This effect can be modulated by environment conditions, such as soil nitrogen availability and air temperature. The ongoing global changes are altering these variables and thus interact with pathogens to influence plant biomass, but experimental test of their interactions is scarce. </span></p> <p><span>2. </span><span>We conducted a 4-year field experiment in a Tibetan alpine meadow to examine the interactive effects of nitrogen addition, warming and foliar pathogens (via fungicide application) on plant biomass. We also measured plant functional traits, species richness and abundance to test the possible mechanisms underlying these interactions. </span></p> <p><span>3. </span><span>Our results showed that foliar fungal pathogens reduced plant community biomass under nitrogen addition, which in turn weakened the positive nitrogen effect on community biomass. Mechanistically, nitrogen addition shifted the plant communities towards fast-growing traits; this happened predominantly because of changes in within-species trait values, including an increase in specific leaf area and height. These trait changes resulted in greater suppression of plant biomass by pathogens, likely because of the trade-offs associated with the allocation of resources to plant growth and defense. Moreover, the reduction in species richness amplified the pathogen effect under nitrogen addition due to the increased density and susceptibility of the most dominant species (i.e. Kobresia capillifolia). Furthermore, warming did not interact with pathogens and nitrogen addition to influence plant community biomass, but their three-way interaction modified the biomass of K. capillifolia. Specifically, warming enhanced the positive effect of nitrogen addition on the biomass of K. capillifolia in the fungicide, low infection plots, while it weakened the nitrogen effect in the no fungicide, high infection plots.</span></p> <p><span>4. </span><span>Synthesis:</span> <span>Our results demonstrate how pathogens interact with nitrogen addition and warming to influence the biomass of dominant species and the whole plant community. Our study highlights the importance of considering foliar fungal pathogens when assessing ecosystem responses to multiple global change factors.</span></p>
Data and code from: The functional trait distinctiveness of plant species is scale dependent
<p>Beyond the local abundance of species, their functional trait distinctiveness is now recognized as a key driver of community dynamics and ecosystem functioning. Yet, since the functional distinctiveness of a species is always relative to a given species pool, a species distinct at the regional scale might not necessarily be distinct at the local or community scale, and reciprocally. To assess the importance of scale (i.e the definition of a species pool) when quantifying the functional distinctiveness of species, and how it might distort the ecological conclusions derived from it, we quantified trait distinctiveness of 1,350 plant species at regional, local, and community scales over ca. 88 000 grassland plots in France. We measured differences in functional distinctiveness of species between regional, local and community scales and tested the influence of environmental predictors (climate and nitrogen input) and contexts (environmental distinctiveness, frequency, and heterogeneity) on these variations. In line with theoretical expectations, we found large variations of functional distinctiveness (in particular between regional and community scales) for many species, with a general tendency of lower distinctiveness at smaller scales. We also showed that nitrogen input – a key aspect of high land use intensity – and environmental frequency partly explained the differences between local and regional scales only. These results suggest the role played by environmental filtering on species' distinctiveness at the local scale, but the determinant of distinctiveness variations at the community scale still needs to be elucidated. Our study provides robust empirical evidence that measures of ecological originality are strongly scale-dependent. We urge ecologists to carefully consider the scale at which they measure distinctiveness, as ignoring scale dependencies could lead to biased (or even entirely wrong) conclusions when not considered at the scale of interest for the respective research question.</p>
Dataset from: Functional traits explain both seedling and adult plant spatial patterns in gypsum annual species
<p><span>1. </span><span>Ecological processes such as seed dispersal or plant–plant interactions and environmental constraints such as climate or soil heterogeneity are known to influence establishment, and thus the spatial patterns of plant communities and populations. In this study, we hypothesized that key functional traits such as the specific leaf area (SLA), reproductive ratio (reproductive/vegetative biomass), seed mass, and maximum plant height would influence the spatial patterns of individual species in annual, gypsophilous plant communities, and that these effects would be modulated by both the soil surface structure (biocrust) and climate (precipitation) conditions. </span></p> <p><span>2. </span><span>We mapped the spatial patterns of all plants found in six 1 </span><span>x</span><span> 1 m plots (more than 1000 individuals per plot) in both the seedling (autumn) and adult stages (spring) under two biocrust experimental conditions (intact vs disturbed biocrust) during two consecutive years which were contrasted in term of precipitation (dry year and wet year). To assess the spatial patterns of seedlings and adults, we fitted four different spatial point pattern models (i.e., Poisson, inhomogeneous Poisson, Poisson cluster, and inhomogeneous Poisson cluster processes) to each of the 242 populations of the 27 most abundant species that had more than 15 individuals per plot.</span></p> <p><span>3. </span><span>Most seedling populations exhibited clustered spatial patterns that persisted in the adult stage, which suggests that short-distance dispersal is an adaptive trait for soil specialists such as gypsophilous plants. One-third of the populations fitted an inhomogeneous model best, but the physical structure of the biocrust was not related to them. More importantly, we found a connection between the functional strategies of species and the spatial distribution of plants. In particular, during the dry year, irrespective of the biocrust conditions, species with a high SLA and high Rep/Veg mainly exhibited clustered spatial patterns, whereas low SLA and low Rep/Veg were associated with random distributions. Species with heavy and light seed masses had random and clustered patterns, respectively. In both the dry and wet years, species with lower maximum heights had clustered patterns, whereas taller species exhibited random patterns. In addition, species with heavier seeds and greater maximum heights had the largest cluster sizes.</span></p> <p><span>4. </span><span>Our results confirm that the spatial patterns of seedlings and adult plants are significantly determined by the functional strategy of each species.</span></p>
Functional traits trade-offs define plant population stability worldwide
<p>Metrics (aggregated data) used in "Functional traits trade-offs define plant population stability worldwide" by Conti et al. For access to the datasets in full please refer to<a href="https://lotvs.csic.es/"> https://lotvs.csic.es/</a></p> <p>The new version of the dataset includes phylogenetic axes used in the final version of the manuscript published in Proceedings B. Conti et al. 2023 "Functional traits trade-offs define plant population stability across different biomes" DOI: 10.1098/rspb.2023.0344</p>
Data from: Plant functional traits and environmental conditions shape community assembly and ecosystem functioning during restoration
Open the record for dataset details and reuse information.
Data from: Microenvironment and functional-trait context dependence predict alpine plant community dynamics
Open the record for dataset details and reuse information.
Data from: More for less: sampling strategies of plant functional traits across local environmental gradients
Open the record for dataset details and reuse information.
Dataset from: Functional traits explain both seedling and adult plant spatial patterns in gypsum annual species
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.