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68 results for “multidimensional data”
Data from: Different phylogenetic and environmental controls of first-order root morphological and nutrient traits: evidence of multidimensional root traits
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Data from: multidimensional beta-diversity across local and regional scales in a Chinese subtropical forest: the role of forest structure
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Data for: Multidimensional stoichiometric mismatch explains differences in detritivore biomass across three forest types
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Data from: Latest Ordovician (Hirnantian) brachiopod faunal lists used for non-matric multidimensional scaling (NMDS) and network analyses
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Data from: Constructing concepts without feedback: An empirical investigation of how relational information affects multidimensional concept completion behavior in an unsupervised task
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Data from: Individual asymmetric competition responses across multidimensional niches may enable coexistence of closely related species
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Data from: Multidimensional plasticity in the Glanville fritillary butterfly: larval performance is temperature, host and family specific
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Data from: The complexity of social complexity: a quantitative multidimensional approach for studies on social organisation
<p>The rapid increase in "big data" of the post-genomic era makes it crucial to appropriately measure the level of social complexity in comparative studies. We argue that commonly-used qualitative classifications lump together species showing a broad range of social complexity, and falsely imply that social evolution always progresses along a single linear stepwise trajectory that can be deduced from comparing extant species. To illustrate this point, we compared widely-used social complexity measures in "primitively eusocial" bumble bees with "advanced eusocial" stingless bees, honey bees, and attine ants. We find that a single species can have both higher and lower levels of complexity compared to other taxa, depending on the social trait measured. We propose that measuring the complexity of individual social traits switches focus from semantic discussions and offers several directions for progress. Firstly, quantitative social traits can be correlated with molecular, developmental, and physiological processes within and across lineages of social animals. This approach is particularly promising for identifying processes that influence or have been affected by social evolution. Secondly, key social complexity traits can be combined into multidimensional lineage-specific quantitative indices enabling fine scale comparison across species that are currently bundled within the same level of social complexity.</p>
Data from: Climate and soil nutrients differentially drive multidimensional fine root traits in ectomycorrhizal‐dominated alpine coniferous forests
<ol> <li><span><span>Fine root traits vary greatly with environmental changes, but the understanding of root-trait variation and its drivers is limited over broad geographical scales, especially for ectomycorrhizal (ECM)-dominated conifers in alpine forests. Herein, the covariation patterns of and environmental controls for fine root traits among ECM-dominated conifers were examined to test whether and how climate and soil nutrients differentially affect fine root trait variations.</span></span></li> <li><span><span>Eight traits of first- and second-order roots were measured, i.e., root diameter (RD), specific root length (SRL), branching intensity (BRI), root tissue density (RTD), mycorrhizal colonization rate (MCR), and concentrations of carbon (C), nitrogen (N) and phosphorus (P), across 76 alpine coniferous populations on the eastern Tibetan Plateau, China.</span></span></li> <li><span><span>Our results showed that variations of the fine root traits fell into two major dimensions: the first dimension (32.39% of the total variance) was mainly represented by RD and SRL, potentially conveying a tradeoff between root lifespan and efficiency of resource foraging; the second dimension (23.70% of the variance) represented coordinated variation for root nutrients (i.e., N and P) and RTD, which depicts the conservation-acquisition tradeoff in resource uptake, i.e., root economic spectrum (RES). Variations in RD and SRL were mainly driven by climatic variables, characterized by a significant increase in RD and a decrease in SRL with increasing mean annual precipitation. In contrast, variations in fine root nutrients (i.e., N and P) and RTD were primarily driven by soil fertility, showing a significant increase in root N and P concentrations but a decrease in RTD with increasing soil resource levels.</span></span></li> <li><span><span><i>Synthesis. </i>Our study clearly shows two distinct dimensions of the variation of fine root traits in ECM-dominated alpine coniferous forests, providing further evidence of the inherent multidimensionality of root traits. Moreover, our findings highlight different roles of climatic and soil variables in driving the variation of fine root traits, potentially leading to the multidimensionality of root traits. This study provides new insights for understanding and predicting shifts in plant belowground strategies in climate-sensitive alpine forests worldwide.</span></span></li> </ol>
Data from: Multidimensional stable isotope analysis illuminates resource partitioning in a sub-Antarctic island bird community
1. A central theme in community ecology is understanding how similar species co-exist and how their interactions may evolve in the context of climate change. Most studies of resource partitioning among central place foragers, particularly birds, focus on the offspring-rearing period, when they are accessible, but breeding success may be determined earlier and little is known about how such species partition resources at the onset of breeding. 2. We used a non-invasive approach to evaluate resource partitioning in co-existing females at a sub-Antarctic island during their pre-laying periods. 3. Three hypotheses were tested using carbon, nitrogen and oxygen stable isotope ratios measured in shells and membranes of hatched eggs as ecological tracers: 1) resource partitioning by geographic location and trophic level will exist among the 12 bird species and will be enhanced within taxonomic groups; 2) given the absence of strong oxygen gradients in the Southern Ocean we will not detect spatial structuring based on oxygen isotopes, but differences will exist between resident and oceanic species as the former may use meteoric water; 3) capital and income breeder strategies can be differentiated using stable isotopes of egg remains. 4. Two and three dimensional isotopic data showed resource partitioning among species. As predicted, segregation was evident within the four main taxonomic groups: penguins, albatrosses, burrowing petrels and giant petrels. Unexpectedly, oxygen isotopes revealed widespread use of meteoric water among a suite of sub-Antarctic birds. Stable isotopes allowed us to identify females of most species as income breeders at the onset of breeding, with the exception of the two crested penguin females exhibiting a mix of income and capital resources use. 5. Multidimensional isotopic analyses revealed that resource partitioning exists at multiple stages of the annual cycle in ways likely to be important under global change, exhibiting wide potential for ecosystem analysis.
Data from: Individual-level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space
Global environmental change can influence ecosystem processes directly or through changes in the trait composition of natural communities. Traits are individual-level features of organisms, and theory predicts that diversity in traits should relate to ecosystem processes. Validated indices that account for both intra- and interspecific trait variation in multidimensional trait space are lacking. In this article, we highlight how an individual-level perspective requires new concepts for trait diversity (TD) and we validate a set of measures suitable to study trait richness, evenness and divergence at the individual scale. First, we tested a selection of multivariate indices for trait richness, evenness and divergence from the literature (FRic, FEve, FDis and the Rao coefficient) using simulated and real individual-level data. We compared the observed changes in the tested indices with those predicted from their expected/required behaviour (i.e. increase or decrease under specific manipulation of community trait structure) and found unsatisfactory results only for FRic and FEve, whereas FDis and the Rao coefficient showed the expected changes. Therefore, we propose two novel concepts and related indices for individual-level trait richness (TOP = trait onion peeling) and evenness (TED = trait even distribution). TOP represents the sum of all successive convex hull areas touching all individuals (points) within a multidimensional trait distribution. TED is a measure of how evenly distributed are individuals within the multidimensional trait space. It is calculated comparing the probability distributions of pairwise distances between individuals and between points of a perfectly even reference distribution. We tested TOP and TED on the same simulated and real data as above, and results indicated appropriate behaviour for TOP (trait richness) and TED (trait evenness). By validating TD indices in an individual-level context, this study contributes to the expansion of functional ecology towards individual-level dynamics. Future comprehensive investigations of individual trait differences in natural communities may improve our understanding of the pathways by which environmental changes affect ecosystem functioning through biodiversity change.
Data from: Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change
Most phenological traits are extremely sensitive to current climate change and advances in the timing of important life-history events have been observed in many species. In birds, phenotypic plasticity in response to temperature is thought to be the main mechanism underlying yearly adjustment in the timing of breeding. However, other factors could be important and interact to affect the levels of plastic responses between and/or within-individuals. Here we use long-term individual-based data on Tree swallow (Tachycineta bicolor) to identify the spatial and environmental drivers affecting plasticity in laying date and to assess their importance at both population and individual levels. We found that laying date has advanced by 4.2 days over 10 years, and that it was mainly influenced by latitude and an interaction between spring temperature and breeder density. Analyses of individual plasticity showed that increases in temperature, but not in breeder density, resulted in within-individual advances in laying date. Our results suggest that females can adjust their laying date as a function of temperature, but that this adjustment will be partly constrained in habitats with lower breeder densities. Such potential constraint is especially worrying for the broad array of species already declining as a result of climate change.
Data from: Multidimensionality in host manipulation mimicked by serotonin injection
Manipulative parasites often alter the phenotype of their hosts along multiple dimensions. 'Multidimensionality' in host manipulation could consist in the simultaneous alteration of several physiological pathways independently of one another, or proceed from the disruption of some key physiological parameter, followed by a cascade of effects. We compared multidimensionality in 'host manipulation' between two closely related amphipods, Gammarus fossarum and Gammarus pulex, naturally and experimentally infected with Pomphorhynchus laevis (Acanthocephala), respectively. To that end, we calculated in each host–parasite association the effect size of the difference between infected and uninfected individuals for six different traits (activity, phototaxis, geotaxis, attraction to conspecifics, refuge use and metabolic rate). The effects sizes were highly correlated between host–parasite associations, providing evidence for a relatively constant 'infection syndrome'. Using the same methodology, we compared the extent of phenotypic alterations induced by an experimental injection of serotonin (5-HT) in uninfected G. pulex to that induced by experimental or natural infection with P. laevis. We observed a significant correlation between effect sizes across the six traits, indicating that injection with 5-HT can faithfully mimic the 'infection syndrome'. This is, to our knowledge, the first experimental evidence that multidimensionality in host manipulation can proceed, at least partly, from the disruption of some major physiological mechanism.
Estimating phylogenies from shape and similar multidimensional data: why it is not reliable
In recent years, there has been controversy whether multidimensional data such as geometric morphometric data or information on gene expression can be used for estimating phylogenies. This study uses simulations of evolution in multidimensional phenotype spaces to address this question and to identify specific factors that are important for answering it. Most of the simulations use phylogenies with four taxa, so that there are just three possible unrooted trees and the effect of different combinations of branch lengths can be studied systematically. In a comparison of methods, squared-change parsimony performed similarly well as maximum likelihood, and both methods outperformed Wagner and Euclidean parsimony, neighbor-joining and UPGMA. Under an evolutionary model of isotropic Brownian motion, phylogeny can be estimated reliably if dimensionality is high, even with relatively unfavorable combinations of branch lengths. By contrast, if there is phenotypic integration such that most variation is concentrated in one or a few dimensions, the reliability of phylogenetic estimates is severely reduced. Evolutionary models with stabilizing selection also produce highly unreliable estimates, which are little better than picking a phylogenetic tree at random. To examine how these results apply to phylogenies with more than four taxa, we conducted further simulations with up to eight taxa, which indicated that the effects of dimensionality and phenotypic integration extend to more than four taxa, and that convergence among internal nodes may produce additional complications specifically for greater numbers of taxa. Overall, the simulations suggest that multidimensional data, under evolutionary models that are plausible for biological data, do not produce reliable estimates of phylogeny.
Research data supporting: "Extended sampling of macromolecular conformations from uniformly distributed points on multidimensional normal mode hyperspheres"
<p>This repository contains protein structures generated by the approach "distributed points Molecular Dynamics using Normal Modes" (dpMDNM). dpMDNM is an enhanced-sampling approach that allows large protein conformational sampling based on normal mode (NM) vector combinations.</p> <p>Input parameter and equilibrated files for Lysozyme and CYP3A4 are provided, including their respective ensemble of structures after conformational exploration combining from 2 to 8 NMs.</p> <p>For more information, please visit the <a href="https://github.com/antonielgomes/dpMDNM">dpMDNM GitHub repository</a>.</p>
Data for: New insights into multi-component atmospheric wet deposition across China: A multidimensional analysis
<p>Atmospheric wet deposition has attracted much attention because of its removal function of aerosol particles and impact on ecosystem. It is a complex multi-component process due to various pollutants emission sources and reaction processes. However, traditional studies have focused on single components, ignoring the internal relationships and the comprehensive wet deposition level; this has hindered the comprehensive understanding and the assessment of ecological effects of deposition. Here, based on the monitoring of wet deposition across 52 stations during 2013–2018 in China, we used two novel multidimensional methods to investigate multi-component atmospheric wet deposition: network analysis and comprehensive index. Network analysis is a new method that can help us better explore the overall relationship between multiple components. The tighter deposition networks, the stronger relationship between different components, meaning that their source are more similar. We find that with the improvement of human development level and the diversification of energy structure, the deposition relationship networks will become looser. Comprehensive index is a method to realize the fusion of multiple parameters, which can help us explore the comprehensive effect of multi-component atmospheric deposition on ecosystem. We calculated the deposition comprehensive index for different ecological regions and found that it was strongly influenced by human activities (energy consumption, fertilization, and vehicle ownership) and precipitation. The findings presented here provide a new perspective for understanding multi-component atmospheric deposition and potential suggestions for evaluating its comprehensive ecological effects. </p>
Data from: Specialization: a multidimensional and integrative perspective
<p><strong>Netwotk_information: </strong>Information of every interacting network for which the different specialization metrics were estimated from the repository <a href="https://www.web-of-life.es/">https://www.web-of-life.es/</a> (except data of lichens). Contains the number of species of both classes of organisms, the total number of species of each networks, the country and the coordinates. </p> <p><strong>Lichen_networks: </strong>Information of every interacting network for mycobiont species and <em>Nostoc</em> phylogroups of 9 forests across a latitudinal gradient in Chile. Each sheet of the Excel document shows the incidence matrix of each of the forest.</p> <p><strong>Abstract:</strong> Specialization remains as a controversial and ambiguous term in ecology. Although it has been usually measured using a dichotomic and simplified classification of <em>specialists</em> and <em>generalists</em>, its nature is by far more complex. In the case of biotic interactions, the assignation of these two labels, is usually based on the number of interacting partners (one or few versus many). Here we provide a more precise, quantitative, and objective interpretation of the specialization phenomenon combining three different dimensions and metrics (partner richness, Simpson’s evenness, and d’-index) that offer complementary information to quantify specialization. Hence, partner richness is a metric associated with the <em>specificity</em>, Simpson’s evenness is related with the <em>preference</em> and d’ index with the <em>selectivity</em> of the biotic interactions. Consequently, we propose a 3D specialization space combining these three metrics which allows to identify the degree of biotic specialization fleeing from its simplified historical interpretation. The proposed space was subsequently evaluated in five natural interacting systems (host-parasite, plant-ant, plant-pollinator, plant-disperser, and mycobiont-cyanobacteria) using available data comprising 116 networks with quantitative observations. The results indicate the prevalence of a lax specialization, where most organisms tended to show low values in at least one of the metrics. Predominantly, observations showed high values of specificity and low values of preference and selectivity. This relaxed specialization may provide advantages of being specialized, without sentencing specialization to its limitations when being too tight. The implementation of this framework provides a useful tool that allows to identify specialization in a more objective, integrative, and universal way for future specialization studies.</p>
Data from: Multidimensional stable isotope analysis illuminates resource partitioning in a sub-Antarctic island bird community
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Data from: Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change
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Data from: Individual-level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space
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ScienceDex guides
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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.