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42 results for “plant species abundance”
Plant–hummingbird pollination networks exhibit limited rewiring after experimental removal of a locally abundant plant species
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Data from: Plant community responses to long-term fertilization: changes in functional group abundance drive changes in species richness
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Data from: Species abundance fluctuations over 31 years are associated with plant-soil feedback in a species-rich mountain meadow
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The proportion of low abundance species is a key predictor of plant β-diversity across the latitudinal gradient
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Plant functional traits of the 100 most abundant species in the Pasoh forest reserve 50-ha forest dynamics plot, Malaysia
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Space resource utilization of dominant species integrates abundance- and functional-based processes for better predictions of plant diversity dynamics
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Data from: Global warming will affect the maximum potential abundance of boreal plant species
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Plant species percent cover data: The Diversity and Abundance of Prairie Plant Communties
This study is divided into six experiments that test the influence of many factors on the diversity and abundance of prairie plant communities. Each "community" is a 2.25 meter square plot seeded with the same amount of seeds from 59 different species of plants. The first experiment is a nitrogen-fire-water factorial. The second experiment is a nitrogen-pH factorial. The third experiment is a nitrogen gradient and the fourth experiment is a nitrogen gradient with a diversity of seeds added each year. The fifth experiment is a disturbance gradient and the last experiment has three levels of soil heterogeneity (variance from the mean) for both nitrogen and pH. See trmte86, trmte103, trmte104, trmte105, trmte106, trmte107 for plot layout.
Data from msGBS: A new high-throughput approach to quantify the relative species abundance in root samples of multi-species plant communities
<p>Plant interactions are as important belowground as aboveground. Belowground plant interactions are however inherently difficult to quantify, as roots of different species are difficult to disentangle. Although for a couple of decades molecular techniques have been successfully applied to quantify root abundance, root identification and quantification in multi-species plant communities remains particularly challenging.</p> <p><span><span><span><span><span><span><span><span><span><span><span>Here we present a novel methodology, multi-species Genotyping By Sequencing (msGBS), as a next step to tackle this challenge. First, a multi-species meta-reference database containing thousands of gDNA clusters per species is created from GBS derived High Throughput Sequencing (HTS) reads. Second, GBS derived HTS reads from multi-species root samples are mapped to this meta-reference which, after a filter procedure to increase the taxonomic resolution, allows the parallel quantification of multiple species. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>The msGBS signal of 111 mock-mixture root samples, with up to 8 plant species per sample, was used to calculate the within-species abundance. Optional subsequent calibration yielded the across-species abundance. The within- and across-species abundances highly correlated (R<sup>2 </sup>range 0.72-0.94 and 0.85-0.98, respectively) to the biomass-based species abundance. Compared to a qPCR based method which was previously used to analyze the same set of samples, msGBS provided similar results. Additional data on 11 congener species groups within 105 natural field root samples showed high taxonomic resolution of the method. </span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><a>msGBS is highly scalable in terms of sensitivity and species numbers within samples, which is a major advantage compared to the qPCR method and advances our tools to reveal hidden belowground interactions.</a></span></span></span></span></span></span></span></span></span></span></span></p> <p>This dataset belongs to the article "<span><span><span><span><span><span><span><span><span><span><span><b>msGBS: A new high-throughput approach to quantify the relative species abundance in root samples of multi-species plant communities</b>". </span></span></span></span></span></span></span></span></span></span></span>msGBS is a technique that uses Genotyping By Sequencing on mixed plant species root samples which, after a filtering step to increase the taxonomic resolution and calibration, is able to estimate plant species abundances. </p> <p>The article uses data of two different experiment:</p> <ol> <li>the Jena field survay (13 plant species) and</li> <li>the Dutch field survay (120 plant species).</li> </ol>
Data from: Species traits and abundances predict metrics of plant–pollinator network structure, but not pairwise interactions
Plant–pollinator mutualistic networks represent the ecological context of foraging (for pollinators) and reproduction (for plants and some pollinators). Plant–pollinator visitation networks exhibit highly conserved structural properties across diverse habitats and species assemblages. The most successful hypotheses to explain these network properties are the neutrality and biological constraints hypotheses, which posit that species interaction frequencies can be explained by species relative abundances, and trait mismatches between potential mutualists respectively. However, previous network analyses emphasize the prediction of metrics of qualitative network structure, which may not represent stringent tests of these hypotheses. Using a newly documented temporally explicit alpine plant–pollinator visitation network, we show that metrics of both qualitative and quantitative network structure are easy to predict, even by models that predict the identity or frequency of species interactions poorly. A variety of phenological and morphological constraints as well as neutral interactions successfully predicted all network metrics tested, without accurately predicting species observed interactions. Species phenology alone was the best predictor of observed interaction frequencies. However, all models were poor predictors of species pairwise interaction frequencies, suggesting that other aspects of species biology not generally considered in network studies, such as reproduction for dipterans, play an important role in shaping plant–pollinator visitation network structure at this site. Future progress in explaining the structure and dynamics of mutualistic networks will require new approaches that emphasize accurate prediction of species pairwise interactions rather than network metrics, and better reflect the biology underlying species interactions.
Data and code for "Tree species abundance changes at the edges of their climatic distribution: an interplay between climate change, plant traits, and forest management"
<p>## Secondary data and code to accompany the research entitled "Tree species abundance changes at the edges of their climatic distribution: an interplay between climate change, plant traits, and forest management" by Padullés Cubino et al. (2024).</p> <p># There are four folders with (1) "raw data", (2) "processed data", (3) "results", and (4) "scripts".</p> <p># The raw and processed data folders contain the CSV and XLSX files with all the data used for analysis and produced from them</p> <p># The "results" folder contains the figures and table presented in the manuscript.</p> <p># The "scripts" folder contains four scripts for the analyses described in the manuscript:</p> <p> 01_preparation_ClimEdge.R -> data cleaning and processing</p> <p> 02_script_Fig1.R -> code to produce Fig1</p> <p> 03_script_Fig2.R -> code to produce Fig2</p> <p> 04_script_Table1_Fig3.R -> code to produce Table 1 and Fig3</p> <p># If anything is unclear, please contact the corresponding author for clarification (padullesj@gmail.com).</p>
F in Host plant utilization and population abundance of three tropical species of Cassidinae (Coleoptera: Chrysomelidae)
F. 2. Population abundance of Stolas chalybea, S. areolata and Anacassis phaeopoda at different life stages at Serra do Japi, SP.
F in Host plant utilization and population abundance of three tropical species of Cassidinae (Coleoptera: Chrysomelidae)
F. 1. Climatic diagram of Jundiaí (where Serra do Japi is located), in São Paulo state, during the years 1997 and 1998 (according to Walter and Lieth, 1960). Original data were collected in a station at 715 m and temperature data were corrected to 1170 m (data provided by Instituto Agronômico de Campinas). Dotted region represents dry periods and dark region represents super-humid periods.
Data from: Species traits and abundances predict metrics of plant–pollinator network structure, but not pairwise interactions
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Data from: Disentangling the relative importance of species occurrence, abundance and intraspecific variability in community assembly: a trait-based approach at the whole-plant level in Mediterranean forests
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Data from msGBS: A new high-throughput approach to quantify the relative species abundance in root samples of multi-species plant communities
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Data from: Species abundance, not diet breadth, drives the persistence of the most linked pollinators as plant-pollinator networks disassemble
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Data from: Duration of propagule pressure affects non-native plant species abundances
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Data from: Dominant bee species and floral abundance drive parasite temporal dynamics in plant-pollinator communities
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Introduced honey bees increase host plant abundance but decrease native bumble bee species richness and abundance
<p>Long-term variation in the population density of introduced honey bees (<em>Apis mellifera)</em> has been shown to be associated with variations in floral traits in alpine lotus (<em>Saussurea nigrescens</em>). However, it remains to be determined whether a high density of honey bees affects the abundance of nectariferous plants and the species richness and abundance of native bumble bees. We predicted that a high density of introduced honey bees lasting three decades would decrease the species richness and abundance of native bumble bees but increase the abundance of honeybee host plant species. Here, the field experiments were conducted to examine the diversity of nectariferous plants and native bumble bees along the typical gradients of honey bee density (high density of honey bee at close apiary and low density of honey bee at distant of apiary). We investigated nectariferous plant abundance, floral and seed traits, bumble bee species richness and abundance at sites with either a high or low honey bee density in an alpine meadow. Our results demonstrated that an increased population of introduced honey bees was associated with increased host plant abundance and flower/capitula number per plant but decreased nectar volume per flower, seed mass, species richness and abundance of native bumble bees. The bumble bee visitation rate was positively correlated with nectar volume per flower at sites close to and far from apiaries. The honey bee visitation rate was positively correlated with flower/capitula number per plant at sites close to apiaries and nectar volume per flower at sites far from apiaries. Seed mass was negatively correlated with nectariferous plant abundance. Our findings showed that introduced honey bees decreased the species richness and abundance of native bumble bees, attributed to evolutionary decrease nectar resources among honey bee host plant species, but increased the abundance of nectariferous plants, attributed to the production of many small seeds by plants. This suggests that long-term high-density beekeeping affects the biodiversity of honey bee host plants and native bumble bees. Our results provide new insights into the mechanisms of maintaining the biodiversity of nectariferous plants and native bumble bees.</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.