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87 results for “plant species composition”
Supplementary material 2 from: Huang J, Guo Z, Tang S, Ren W, Chu G, Wang L, Zhao L, Yu R, Xu Y, Ding Y, Zang R (2020) Floristic composition and plant diversity in distribution areas of native species congeneric with Betula halophila in Xinjiang, northwest China. Nature Conservation 42: 1-17. https://doi.org/10.3897/natureconservation.42.54735
Figure S2. The distribution frequency of Betula species varies with the environment gradients
Intraspecific trait variation and species turnover mediate grazing impacts on above- and below-ground functional trait composition of plant communities
<ol> <li>Although grazing has significant impacts on plant functional traits and community composition in grasslands, few studies have simultaneously explored how plant above- and below-ground traits and community functional composition respond to grazing.</li> <li>Using a grazing manipulation experiment with seven levels of grazing intensity (0, 1.5, 3.0, 4.5, 6.0, 7.5, and 9 sheep ha<sup>-1</sup>) in the Inner Mongolia grassland, we partitioned the roles of intraspecific trait variation (ITV) and species turnover underlying the grazing induced changes in above- and below-ground functional trait composition of plant communities. Six aboveground traits (i.e. plant height, plant aboveground biomass, plant density, leaf area, specific leaf area (SLA) and leaf density) and three root traits (average root diameter, ARD; specific root length, SRL; and root tissue density, RTD) of the first-, second- and third-order roots (1<sup>st</sup>-, 2<sup>nd</sup>-, and 3<sup>rd</sup>-) were measured at the plant individual level. </li> <li>At the community level, plant above-ground traits shifted towards grazing avoidance strategy (e.g. plant height and leaf area decreased), and below-ground traits shifted towards conservative strategy (i.e. 1<sup>st</sup>-SRL and 2<sup>nd</sup>-SRL decreased, 1<sup>st</sup>-RTD and 2<sup>nd</sup>-ARD increased) with increasing grazing intensity. Functional tradeoffs were found between plant individual biomass and plant density, and between leaf area and leaf density under grazing. However, community-weighted mean SRL (SRL<sub>CWM</sub>) and ARD (ARD<sub>CWM</sub>) of different root orders exhibited functional coordination under grazing pressure. SLA<sub>CWM</sub> and SRL<sub>CWM</sub> also showed synergistic responses to grazing.</li> <li> The ITV plays a predominant for the changes in above- and below-ground functional trait composition at the community level. However, changes in mean trait values among plant species with different resource use strategies were mainly triggered by species turnover. For species with different resource use strategies, grazing exhibited a coordinated effects on ITV but an offset effect on species turnover.</li> <li> <i>Synthesis.</i> Our results demonstrate that both the above- and below-ground trait composition of plant communities shifted toward conservative strategy under long-term grazing. This study highlights the effects of ITV and species turnover that govern the grazing-induced changes in functional trait composition of plant communities, and has important implications for grazing management in semiarid grasslands.</li> </ol>
Intraspecific trait variation and species turnover mediate grazing impacts on above- and below-ground functional trait composition of plant communities
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Data from: Species pools and environmental sorting control different aspects of plant diversity and functional trait composition in recovering grasslands
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BOREAS TGB-03 Plant Species Composition Data over the NSA Fen
The BOREAS TGB-03 team collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the NSA. This data set contains information about the composition of plant species that were within the collars used to measure NEE. The species composition was identified to understand the differences in NEE among the various plant communities in the NSA fen. The data were collected in July of 1994 and 1996.
Data and R code for: "Nineteenth-century land use shape the current occurrence of some plant species, but weakly affects richness and total composition of Central European grasslands"'
<ol> <li> <p><strong><code>IndVal.all.habitats.csv</code></strong>: the results of the IndVal statistics (<a href="https://doi.org/10.1111/j.1600-0706.2010.18334.x">De Cáceres et al. 2013</a>) for 1,498 species for the historical land use categories calculated across the entire dataset;</p> </li> <li> <p><code><strong>IndVal.separate.habitats.csv</strong></code>: the results of the IndVal statistics for 1,498 species for the historical land use categories calculated for each habitat type (dry grasslands, mesic grasslands, wet grasslands) separately;</p> </li> <li> <p><code><strong>ecological.and.disturbance.values.csv</strong></code>: the original Ellenberg-type and disturbance indicator values, and the varimax-rotated components (‘RC’) used in the analysis (data obtained from <a href="https://doi.org/10.1111/jvs.13168">Tichý et al. 2023</a> and <a href="http://dx.doi.org/10.1111/geb.13603">Midolo et al. 2023</a>; accessible at the FloraVeg.eu website <a href="https://floraveg.eu/download/" target="_new" rel="noreferrer">https://floraveg.eu/download/</a>);</p> </li> <li> <p><strong>R code and data for reproducibility</strong>. The R code is for illustration purposes only and is based on a subset of 1,184 mesic grassland vegetation plots located in the Czech Republic and in the study area. This is part of the Czech National Phytosociological Database (<a href="https://www.preslia.cz/article/387">Chytrý & Rafajová 2003</a>) and the European Vegetation Archive (<a href="https://doi.org/10.1111/avsc.12191">Chytrý et al. 2016</a>). The data includes the following:</p> <ul> <li> <p> <code>data</code> folder:</p> </li> </ul> </li> </ol> <ul> <li> <ul> <li> <ul> <li>i. <code>indicator.values.csv</code>: the original indicator values for 831 species;</li> <li>ii. <code>plot.data.csv</code>: data for each of the 1,184 vegetation plots, including their historical land use, plot size, bioclimatic variables (‘bio’; <a href="http://dx.doi.org/10.1038/sdata.2017.122">Karger et al. 2017</a>), and soil pH (<a href="https://doi.org/10.1371%2Fjournal.pone.0169748">Hengl et al. 2017</a>);</li> <li>iii. <code>species.matrix.csv</code>: community matrix reporting the relative abundance of species (columns) and plot sites (rows).</li> </ul> </li> <li>R scripts for species richness, species composition, and species indicator analyses. R script are also rendered in .html with R Markdown.</li> </ul> </li> </ul>
Figure 7 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 7. The percentage of singleton and doubleton species from the sampling period spring 2001 that are common in other locations (ground fauna, introduced species, another habitat), or during another sampling period (season, previous spring). Unknown fauna cannot be allocated an origin because they are never abundant in the total dataset (>29,000 specimens).
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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.