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589 results for “Vascular Plants”
Vascular plants of Ewe-Adakplame Relic Forest at Kétou in Benin, West Africa
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Statistics for each 15 km X 15 km grid cell, for all California native vascular plants, as studied by Baldwin et al. (2017 Amer. J. Bot.), including randomization results.
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Master spatial file for native California vascular plants used by Baldwin et al. (2017 Amer. J. Bot.)
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A subset of Californian vascular plant species recognized by Baldwin et al. (2017), corresponding to to the “large and intermediate-sized genera” studied by Stebbins & Major (1965)
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Six subsets of all native vascular plant species of California used by Baldwin et al. (2017), and the R script to use to extract the subsets from the master spatial file
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Progress Towards Plant Community Transcriptomics: Pilot RNA-Seq Data from 24 Species of Vascular Plants at Harvard Forest
<p>Assembled transcriptomes of 24 vascular plant species from Harvard Forest. Transcriptomes for each species were sequenced and assembled as described below. Additional details available in the associated manuscript: https://doi.org/10.1101/2020.03.31.018945. Raw reads for each available at NCBI SRA SRP127805 and BioProject PRJNA422719.</p> <p><strong>Taxon selection and sampling </strong></p> <p>The Harvard Forest Flora <a href="https://paperpile.com/c/nMUYEV/hd5w">(Jenkins et al., 2008)</a> was used to select taxa to represent each category (native/invasive, diploid/polyploid). Invasive species status was determined from the Harvard Forest Flora Database <a href="https://paperpile.com/c/nMUYEV/g5Tw">(Jenkins and Motzkin, 2009)</a>. Putative diploids and neo-polyploid species were identified from chromosome counts obtained from the Chromosome Counts Database <a href="https://paperpile.com/c/nMUYEV/6Vzo">(Rice et al., 2015)</a>. Congeneric species pairs were selected based on their phylogenetic relatedness. The Harvard Forest Flora Database was used to assesscalculate recent encounter rates of each target species, and locate sampling sites. </p> <p>Tissue from mature leaves was collected from an individual representing each target species at two time points (July and August) during the 2016 growing season. The same individual was sampled at both time points for perennial individuals, and the same population was sampled for annuals. Field sampling for plant RNA-seq followed the protocol described in Yang et al. 2017 <a href="https://paperpile.com/c/nMUYEV/n5lK">(Yang et al., 2017)</a>. Leaf tissues were flash frozen in liquid nitrogen in the field, and shipped on dry ice to the University of Arizona for RNA extraction.</p> <p> </p> <p><strong>RNA extraction and RNA-seq</strong></p> <p>Total RNA was extracted from leaf tissue collected at each time point for all species using the Spectrum Plant Total RNA Kit (Sigma-Aldrich Co., St. Louis, MO, USA) following Protocol A. RNA was used to prepare cDNA using Nugen’s Ovation RNA-Seq System via single primer isothermal amplification (Catalogue # 7102-A01) and automated on the Apollo 324 liquid handler (Wafergen). cDNA was quantified on the Nanodrop (Thermo Fisher Scientific) and was sheared to approximately 300 bp fragments using the Covaris M220 ultrasonicator. Libraries were generated using Kapa Biosystem’s library preparation kit (KK8201). Fragments were end repaired and A-tailed, and individual indexes and adapters (Bioo, catalogue #520999) were ligated on each separate sample. The adapter ligated molecules were cleaned using AMPure beads (Agencourt Bioscience/Beckman Coulter, A63883), and amplified with Kapa’s HIFI enzyme (KK2502). Each library was then analyzed for fragment size on an Agilent’s Tapestation, and quantified by qPCR (KAPA Library Quantification Kit, KK4835) on Thermo Fisher Scientific’s Quantstudio 5 before multiplex pooling (13-16 samples per lane) and paired-end sequencing at 2x150 bp on the Illumina NextSeq500 platform at Arizona State University’s CLAS Genomics Core facility. Raw read quality was assessed using fastQC <a href="https://paperpile.com/c/nMUYEV/mvKN">(Andrews, 2010)</a>.</p> <p> </p> <p><strong><em>De novo</em> transcriptome assembly</strong></p> <p>Raw sequence reads were processed using the SnoWhite pipeline <a href="https://paperpile.com/c/nMUYEV/4el87+4OvN">(Barker et al., 2010a; Dlugosch et al., 2013)</a>, which included trimming adapter sequences and bases with a quality score below 20 from the 3' ends of all reads, removing reads that are entirely primer and/or adapter fragments using TagDust <a href="https://paperpile.com/c/nMUYEV/4I38S">(Lassmann et al., 2009)</a>, and removing polyA/T tails with SeqClean (<a href="https://sourceforge.net/projects/seqclean/">https://sourceforge.net/projects/seqclean/</a>). The cleaned reads from each sample time point were merged together by pairs, and pooled to assemble a reference de novo transcriptome for each species. All transcriptomes were assembled with SOAPdenovo-Trans v1.03 <a href="https://paperpile.com/c/nMUYEV/3Szww">(Xie et al., 2014)</a> using a k-mer of 57.</p>
Figure 1 from: Kipkoech S, Melly DK, Muema BW, Wei N, Kamau P, Kirika PM, Wang Q, Hu G (2020) An annotated checklist of the vascular plants of Aberdare Ranges Forest, a part of Eastern Afromontane Biodiversity Hotspot. PhytoKeys 149: 1-88. https://doi.org/10.3897/phytokeys.149.48042
Figure 1 The locality of Aberdare Ranges Forest. (i) Five major water catchment forests in Kenya (ii) Two sections of the Aberdare Ranges Forest with numerous watersheds.
Data for: Comparing the effect of landscape context on vascular plant and bryophyte communities in a human-dominated landscape
<p><b>Aims:</b> It is important to understand the effect of landscape context on biological communities to predict how biodiversity will be affected on human-dominated landscapes. While many studies have tested the effects of landscape context on the species richness and composition of vascular plants, few have compared the responses of vascular plants and bryophytes on the same landscape. We sampled non-epiphytic bryophytes and vascular plants in 184 plots to test whether three landscape context factors measured four years or four decades previously could predict bryophyte or vascular plant species richness and composition after accounting for local factors.</p> <p><b>Location:</b> Temperate forests and oak savannahs, Vancouver Island, British Columbia, Canada.</p> <p><b>Methods: </b>We used model selection and comparisons to test the effects of<b> </b>surrounding road density, total amount of forest, and distance to the nearest forest edge on species richness, species richness of non-disturbance-associated species, and community composition after controlling for important local predictors including substrate availability and topography.</p> <p><b>Results:</b> The species richness of non-disturbance-associated vascular plants was lower in plots with greater surrounding historical road density, and perennial stayer bryophyte richness declined with increasing historical road density and lower historical forest amount, suggesting a potential extinction debt. Landscape context significantly affected total species richness and community composition of vascular plants, but not bryophytes.</p> <p><b>Conclusion:</b> While bryophytes appear to be less sensitive overall to landscape context than vascular plants, disturbance-intolerant perennial stayer bryophytes may decline in the future in response to the increased road density and loss of forest cover that has occurred over the past four decades.</p>
Figure 8 from: Jamilah MS, Lee GE, Salam MR, Shahimi S, Pesiu E, Jani JM, Horsali NAI, Shahrudin R, Nor SMM, Chong JL, Mohamad F, Raffi A, Nikong D (2020) A checklist of vascular plants and uses of some species for livelihood-making in Setiu Wetlands, Terengganu, Malaysia. PhytoKeys 160: 7-43. https://doi.org/10.3897/phytokeys.160.52946
Figure 8 Utilisation of Lepironia articulata (A1–3), Pandanus tectorius (B1–3), and Nypa fruticans (C1–3ii) in Setiu Wetlands. From left to right 1 Harvesting 2 Part used 3 Finished products.
Figure 4 from: Jamilah MS, Lee GE, Salam MR, Shahimi S, Pesiu E, Jani JM, Horsali NAI, Shahrudin R, Nor SMM, Chong JL, Mohamad F, Raffi A, Nikong D (2020) A checklist of vascular plants and uses of some species for livelihood-making in Setiu Wetlands, Terengganu, Malaysia. PhytoKeys 160: 7-43. https://doi.org/10.3897/phytokeys.160.52946
Figure 4 A selection of Orchidaceae species from Setiu Wetlands. AAnia penangianaBThrixspermum amplexicauleCPinalia atrovinosaDPapilionanthe hookerianaEPhalaenopsis pulcherrimaFCymbidium finlaysonianumGGrammatophyllum speciosumHStrongyleria panneaICallostylis pulchellaJBromheadia finlaysonianaKVanilla griffithiiLArachnis flos-aerisMDendrobium secundumNBulbophyllum trigonopusODendrolirium lasiopetalum.
Figure 1 from: Jamilah MS, Lee GE, Salam MR, Shahimi S, Pesiu E, Jani JM, Horsali NAI, Shahrudin R, Nor SMM, Chong JL, Mohamad F, Raffi A, Nikong D (2020) A checklist of vascular plants and uses of some species for livelihood-making in Setiu Wetlands, Terengganu, Malaysia. PhytoKeys 160: 7-43. https://doi.org/10.3897/phytokeys.160.52946
Figure 1 The boundaries (red line) of the forest to be gazetted in Setiu Wetlands as state park. Map courtesy of the Terengganu State Parks.
Figure 5 from: Jamilah MS, Lee GE, Salam MR, Shahimi S, Pesiu E, Jani JM, Horsali NAI, Shahrudin R, Nor SMM, Chong JL, Mohamad F, Raffi A, Nikong D (2020) A checklist of vascular plants and uses of some species for livelihood-making in Setiu Wetlands, Terengganu, Malaysia. PhytoKeys 160: 7-43. https://doi.org/10.3897/phytokeys.160.52946
Figure 5 Different plant communities in Setiu Wetlands. A Mangrove plants B Nipa palm (Nypa fruticans) population CCeriops zippelianaDPandanus tectoriusE Ant plant, Hydnophytum formicarum attached to Bruguiera hainesiiFNepenthes ampullariaGHoya coronariaHPloiarium alternifolia.
Figure 2 from: Kiew R, Chung-Lu L (2020) Checklist of vascular plants of Klang Gates Quartz Ridge, Malaysia, a 14-km long quartz dyke. PhytoKeys 166: 57-77. https://doi.org/10.3897/phytokeys.166.55778
Figure 2 View of the eastern ridge of Klang Gates Quartz Ridge from summit of western ridge, the summit (foreground) dominated by 2–3 m tall Baeckea frutescens.
Figure 3 from: Kiew R, Chung-Lu L (2020) Checklist of vascular plants of Klang Gates Quartz Ridge, Malaysia, a 14-km long quartz dyke. PhytoKeys 166: 57-77. https://doi.org/10.3897/phytokeys.166.55778
Figure 3 Endemic species in Klang Gates Quartz Ridge: Eulalia milsumi (left) and Aleisanthia rupestris.
The list of vascular plants for the city of Toronto
<p>Urban areas have become epicenters for applied ecological and conservation research and policy. Yet, most urban areas have surprisingly little consolidated information about their biota, including species-at-risk and invasive species.</p> <p>I used multiple data sources to compile a list of vascular plants for the greater metropolitan Toronto region. This data not only includes taxonomic information, but also global and national status ranks, growth from, native status, threatened status, abundance estimates and year of first observation for non-indigenous species.</p> <p>The list includes 1937 taxa from 146 families, of which 822 are non-indigenous. The majority of native species were ranked as abundant and widespread both globally and provincially. However, non-indigenous species ranks were bimodal, likely to be either extremely restricted in the province, or very widespread.</p> <p>This database provides a robust list of plant taxa in Canada's largest city. It will inform global urban ecology analyses and local and regional management and policy.</p>
Supplementary material 2 from: Márquez-García F, García-Alonso D, Guerra-Barrena MJ, Vázquez-Pardo FM (2021) Vascular plants dataset of the herbarium (HSS) of Agrarian Research Institute Finca "La Orden-Valdesequera" (CICYTEX), Extremadura, Spain. PhytoKeys 171: 47-59. https://doi.org/10.3897/phytokeys.171.58900
Types HSS Herbarium
Figure 1 from: Márquez-García F, García-Alonso D, Guerra-Barrena MJ, Vázquez-Pardo FM (2021) Vascular plants dataset of the herbarium (HSS) of Agrarian Research Institute Finca "La Orden-Valdesequera" (CICYTEX), Extremadura, Spain. PhytoKeys 171: 47-59. https://doi.org/10.3897/phytokeys.171.58900
Figure 1 Families with greatest number of specimens in the HSS Herbarium (A) Genera represented by the highest number of specimens in the HSS Herbarium (B).
Supplementary material 1 from: Márquez-García F, García-Alonso D, Guerra-Barrena MJ, Vázquez-Pardo FM (2021) Vascular plants dataset of the herbarium (HSS) of Agrarian Research Institute Finca "La Orden-Valdesequera" (CICYTEX), Extremadura, Spain. PhytoKeys 171: 47-59. https://doi.org/10.3897/phytokeys.171.58900
Taxonomic coverage of the HSS Herbarium
Figure 5 from: Márquez-García F, García-Alonso D, Guerra-Barrena MJ, Vázquez-Pardo FM (2021) Vascular plants dataset of the herbarium (HSS) of Agrarian Research Institute Finca "La Orden-Valdesequera" (CICYTEX), Extremadura, Spain. PhytoKeys 171: 47-59. https://doi.org/10.3897/phytokeys.171.58900
Figure 5 Collection points of the HSS Herbarium in Extremadura (Note: 1 southern slope of the Gredos Mountain range 2 Gata Mountain range 3 Villuercas Mountain range 4 Guadiana River valley 5 Badajoz Mountain range 6 foothills of Sierra Morena).
Figure 2 from: Márquez-García F, García-Alonso D, Guerra-Barrena MJ, Vázquez-Pardo FM (2021) Vascular plants dataset of the herbarium (HSS) of Agrarian Research Institute Finca "La Orden-Valdesequera" (CICYTEX), Extremadura, Spain. PhytoKeys 171: 47-59. https://doi.org/10.3897/phytokeys.171.58900
Figure 2 Genera with greatest number of species and infraespecific taxa (subspecies and varieties) in the HSS Herbarium.
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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)
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DANDI Archive for NWB datasets
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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
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