Resultados totales (Incluyendo duplicados): 45302
Encontrada(s) 4531 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284944
Dataset. 2022

VARIATION IN DNA METHYLATION AND RESPONSE TO SHORT-TERM HERBIVORY IN THLASPI ARVENSE

  • Niloya Troyee, A.
  • Alonso, Conchita
  • Medrano, Mónica
  • Müller, Caroline
Plant metabolic pathways and gene networks involved in the response to herbivory are well-established, but the impact of epigenetic factors as modulators of those responses is less understood. Here, we studied the role of DNA cytosine methylation on phenotypic responses after short-term herbivory in Thlaspi arvense plants with two contrasting flowering phenotypes. We investigated the effect of experimental demethylation and herbivory treatments following a 2x3 factorial design. First, half the seeds were submerged in a water solution of the demethylating agent 5-azacytidine and the other half only in water, as controls. Then, we assigned control and demethylated plants to three herbivory categories (i) insect herbivory, (ii) artificial herbivory, and (iii) undamaged plants. The effects of the demethylation and herbivory treatments were assessed by quantifying genome-wide global DNA cytosine methylation, concentration of leaf glucosinolates, final stem biomass, fruit and seed production, and seed size. For most of the plant traits analysed, individuals from the two plant-types responded differently. In late-flowering plants, global DNA methylation did not differ between control and demethylated plants but it was significantly reduced by herbivory. Conversely, in early-flowering plants, demethylation at seed stage was still evident in leaf genomes of reproductive individuals whereas herbivory did not affect their global DNA methylation., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/284944
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284944
HANDLE: http://hdl.handle.net/10261/284944
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284944
PMID: http://hdl.handle.net/10261/284944
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284944
Ver en: http://hdl.handle.net/10261/284944
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284944

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284954
Dataset. 2021

SPECIATION OF IODINE IN MARINE AEROSOL

  • Gómez Martín, Juan Carlos
  • Saiz-Lopez, A.
  • Cuevas, Carlos A.
  • Baker, Alex R.
  • Fernández, Rafael P.
We have compiled a comprehensive dataset of field observations of iodine speciation and size distribution in marine aerosol (1983-2018). Since the source of iodine is mainly marine, only ship-borne campaigns (16 cruises) and coastal or insular campaigns (12 ground-based stations) have been considered. Iodine speciation measurements are heterogeneous and do not always cover the same species or group of species. The data can be classified in five groups according to the iodine species reported and their size segregation in fine and coarse aerosol: (1) total iodine (TI) and total soluble iodine (TSI) in bulk aerosol, (2) TI size distribution, (3) TSI and soluble speciation size distribution, (4) soluble speciation in fine aerosol fraction only and (5) soluble speciation in bulk aerosol only. Soluble speciation consist of iodide (I-), iodate (IO3-) and soluble organic iodine (SOI). For some of the cruises where the size distribution of soluble iodine species was reported (7 cruises) there are also measurements of major ions (MI) available. MI observations include Na+, NH4+, Mg2+, Ca2+, K+, Cl-, NO3-, SO42-, oxalate (C2O4-2), Br- and methanesulfonate (CH3SO3-), and derived quantities such as non-sea-salt (nss) K+, Ca2+ and SO42-. The associated paper discusses some aspects of data treatment and questions related to analytical methods employed to determine iodine speciation., Financial Support: J. C. G. M. acknowledges financial support from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and the Ramon y Cajal Program (RYC-2016-19570). A.S.-L. acknowledges financial support from the European Research Council Executive Agency under the European Union's Horizon 2020 Research and Innovation programme (Project 'ERC-2016-COG 726349 CLIMAHAL')., Peer reviewed

DOI: http://hdl.handle.net/10261/284954
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284954
HANDLE: http://hdl.handle.net/10261/284954
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284954
PMID: http://hdl.handle.net/10261/284954
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284954
Ver en: http://hdl.handle.net/10261/284954
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oai:digital.csic.es:10261/284954

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284971
Dataset. 2019

DATA FROM: A CLOCKWORK FISH. AGE-PREDICTION USING DNA METHYLATION-BASED BIOMARKERS IN THE EUROPEAN SEABASS

  • Anastasiadi, Dafni
  • Piferrer, Francesc
[Methods] Overall design: We used multiplexed bisulfite sequencing (MBS) to measure the DNA methylation of specific regions in tissues of sea bass from different age classes. Two MBS libraries were prepared and sequenced. In all cases, each tissue and age class were represented by 4 replicate fish. The first MBS library consisted of 22 valid amplicons amplified in ovary, testis and muscle of 1.28, 3.07 and 10.5 years sea bass. The second MBS library consisted of 4 valid amplicons amplified in muscle of a) 0.55, 0.96, 1, 1.1, 1.37, 1.64, 4.17, 5.83 and 6.75 years old sea bass reared at natural (low-17ºC) temperature and b) 0.48, 0.55, 0.82, 0.96, 1.1, 1.37 years old sea bass reared at high (21ºC) temperature from 7 to 68 days post fertilization. Description of protocols: Fish were raised at the Aquarium facilities of the Institute of Marine Sciences or the Institute of Aquaculture Torre de La Sal (Spanish National Research Council, CSIC) following standard procedures until sampling. Samples were snap frozen in liquid nitrogen and kept at -80ºC until DNA extraction. Genomic DNA was extracted by the Phenol/Chlorofom/Isoamyl-alcohol (25:24:1) extraction protocol. MBS libraries were prepared as described in Anastasiadi et al 2018 (https://doi.org/10.1080/15592294.2018.1529504). Briefly, 2 μg of DNA were bisulfite-converted and PCRs with primers targeting specific bisulfite-converted regions were performed. Bead-based normalization of DNA quantities was followed by pooling of amplicons per sample. Indices were added to samples following a dual-index strategy by PCRs. Equal quantities of samples were pooled into a single final library and sequenced in an Illumina MiSeq using the 300 bp paired-end protocol. Description of data processing: Raw reads were quality trimmed by the Trim Galore for MBS 1 and Trimmomatic for MBS 2 Trimmed reads were aligned to the reference genome dicLab (v1.0c, June 2012; http://seabass.mpipz.mpg.de/) using Bismark with --non_directional --phred33-quals --score_min L,0,-0.6. For samples of 1.28, 3.07 and 10.5 years alignments were performed in three steps: 1) paired reads were aligned, 2) unmapped reads from the first step were aligned as single reads, and 3) unpaired reads from the first step of trimming were aligned like the unmapped reads. Paired-end and single-end alignments are provided as .bam files. Methylation calling was performed by the bismark_methylation_extractor. For samples of 1.28, 3.07 and 10.5 years extraction was performed separately for paired-end and for single-end reads. Methylation files were merged into a single file containing all samples. Methylation values were read into R. CpGs with less than 5 coverage were eliminated. In this data package, two types of data are included per sample: alignmnet files (.bam) and methylation value of each CpG (.txt). For the MBS1, paired-end and single-end alignments (.bam) are provided. The processed data files are tab-delimited and contain: 1) the name of the sample, 2) the genomic position of the CpG (in the format chr, cpg start.cpg end), 3) the percent methylation and 4) the age in years. [Usage Notes] A spreadsheet is included in this data package. It includes as columns the name of each sample, the age, tissue, developmental temperature, sex and the names of the corresponding alignment (for MBS1, both paired-end and single-end) and methylation values files., Age-related changes in DNA methylation do occur. Taking advantage of this, mammalian and avian epigenetic clocks have been constructed to predict age. In fish, studies on age-related DNA methylation changes are scarce and no epigenetic clocks are available. However, in fisheries and population studies there is a need for accurate estimation of age, something that is often impossible for some economically important species with the currently available methods. Here, we used the European sea bass, a marine fish where age can be known with accuracy, to construct a piscine epigenetic clock, the first one in a cold-blooded vertebrate. We used targeted bisulfite sequencing to amplify 48 CpGs from four genes in muscle samples and applied penalized regressions to predict age. We, thus, developed an age predictor in fish that is highly accurate (0.824) and precise (2.149 years of error). In juvenile fish, accelerated growth due to elevated temperatures had no effect in age prediction, indicating that the clock is able to predict the chronological age independently of environmentally-driven perturbations. An epigenetic clock developed using muscle samples accurately predicted age in samples of testis but not ovaries, possibly reflecting the reproductive biology of fish. In conclusion, we report the development of the first piscine epigenetic clock, paving the way for similar studies in other species. Piscine epigenetic clocks should be of great utility for fisheries management and conservation purposes, where age determination is of crucial importance., Ministerio de Economía, Industria y Competitividad, Gobierno de España, Award: AGL2016–78710–R .Ministerio de Economía, Industria y Competitividad, Gobierno de España, Award: BES–2011–044860., Peer reviewed

DOI: http://hdl.handle.net/10261/284971
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284971
HANDLE: http://hdl.handle.net/10261/284971
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284971
PMID: http://hdl.handle.net/10261/284971
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284971
Ver en: http://hdl.handle.net/10261/284971
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/284971

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285045
Dataset. 2021

CT-EBM-SP - CORPUS OF CLINICAL TRIALS FOR EVIDENCE-BASED-MEDICINE IN SPANISH

  • Campillos-Llanos, Leonardo
  • Valverde Mateos, Ana
  • Capllonch Carrión, Adrián
  • Moreno Sandoval, Antonio
A collection of 1200 texts (292 173 tokens) about clinical trials studies and clinical trials announcements in Spanish: - 500 abstracts from journals published under a Creative Commons license, e.g. available in PubMed or the Scientific Electronic Library Online (SciELO). - 700 clinical trials announcements published in the European Clinical Trials Register and Repositorio Español de Estudios Clínicos. Texts were annotated with entities from the Unified Medical Language System semantic groups: anatomy (ANAT), pharmacological and chemical substances (CHEM), pathologies (DISO), and lab tests, diagnostic or therapeutic procedures (PROC). 46 699 entities were annotated (13.98% are nested entities). 10% of the corpus was doubly annotated, and inter-annotator agreement (IAA) achieved a mean F-measure of 85.65% (±4.79, strict match) and a mean F-measure of 93.94% (±3.31, relaxed match)., European Commission: InterTalentum - Programme for Post-Doctoral Talent Attraction to CEI UAM+CSIC (713366), Peer reviewed

Proyecto: EC/H2020/713366
DOI: http://hdl.handle.net/10261/285045
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285045
HANDLE: http://hdl.handle.net/10261/285045
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285045
PMID: http://hdl.handle.net/10261/285045
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285045
Ver en: http://hdl.handle.net/10261/285045
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285045

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285075
Dataset. 2022

DISTANCIA-COVID CONTACT ESTIMATES FOR SPAIN

  • Palmer, John R. B.
  • Ottow, Ramona
  • Bartumeus, Frederic
File Descriptions - distancia_covid_contact_estimates_spain_metadata_dictionary: Data dictionary - distancia_covid_contact_estimates_spain.csv: Contact estimates - distancia_covid_instrument_wave_1.xlsx: Survey instrument used in Wave 1 - distancia_covid_instrument_wave_2.xlsx: Survey instrument used in Wave 2 - distancia_covid_instrument_wave_3_4.xlsx: Survey instrument used in Waves 3 and 4 - CITATION.cff: Citation information, Estimates of age-specific contact patterns in Spain during the Covid-19 pandemic. This data was generated from the CSIC Distancia-Covid survey (https://distancia-covid.csic.es/). It includes estimated mean numbers of coresidents and non-coresident contacts by age group during 2020 and 2021, for all of Spain and disaggregated by autonomous community. (See `data/distancia_covid_contact_estimates_spain_metadata_dictionary.csv` for variable descriptions.) This repository also includes the survey instrument used in each wave., This data was generated from the survey implemented through the project "Impacto de las medidas de distanciamiento social sobre la expansión de la epidemia de Covid-19 en España," funded by the Spanish National Research Council (Consejo Superior de Investigaciones Científicas, CSIC). Processing and analysis was done with support from the Human-Mosquito Interaction Project (H-MIP) funded by European Research Council Starting Grant No. 853271, and the Versatile emerging infectious disease observatory (VEO) funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 874735., Peer reviewed

DOI: http://hdl.handle.net/10261/285075
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285075
HANDLE: http://hdl.handle.net/10261/285075
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285075
PMID: http://hdl.handle.net/10261/285075
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285075
Ver en: http://hdl.handle.net/10261/285075
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285075

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285257
Dataset. 2022

RECONSTRUCTING THE IBERIAN SALT-BEARING RIFTED MARGIN OF THE SOUTHERN PYRENEES: INSIGHTS FROM THE ORGANYÀ BASIN

  • Casini, Giulio
  • Vergés, Jaume
  • Drzewiecki, Peter A.
  • Ford, Mary
  • Cruset, David
  • Wright, Wayne
  • Hunt, David W.
File List: Dips_fieldwork.dat; Dips_remote_sensing.dat, Description of methods used for collection/generation of data: fieldwork (compass), remote sensing (Equinor propietary software Outcrop Digitizer and GoogleEarth), Fieldwork was integrated with remote sensing on satellite and drone derived 3D virtual outcrops to study the geometries of the Jurassic to Late Cretaceous sedimentary sequences belonging to the Organyà Basin, Catalunya, Spain. A total of 329 dips were measured in the field and 433 dips were extracted from the interpretation of virtual outcrops., This research was funded by Equinor Research Centre, Bergen (Norway), by the Spanish Ministry of Economy and Competitiveness Projects ALORBE (PIE-CSIC-202030E310), with additional support from the Generalitat de Catalunya grant AGAUR 2017 SGR 847. David Cruset acknowledges MCIN/AEI /10.13039/501100011033 and European Union NextGenerationEU/PRTR (Juan de la Cierva Formación fellowship FJC2020-043488-I), Peer reviewed

DOI: http://hdl.handle.net/10261/285257, https://doi.org/10.20350/digitalCSIC/14862
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285257
HANDLE: http://hdl.handle.net/10261/285257, https://doi.org/10.20350/digitalCSIC/14862
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285257
PMID: http://hdl.handle.net/10261/285257, https://doi.org/10.20350/digitalCSIC/14862
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285257
Ver en: http://hdl.handle.net/10261/285257, https://doi.org/10.20350/digitalCSIC/14862
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285257

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285087
Dataset. 2022

DISTANCIA-COVID INDIVIDUAL CONTACT ESTIMATES FOR SPAIN

  • Palmer, John R. B.
  • Ottow, Ramona
  • Bartumeus, Frederic
This dataset contains the following files: distancia_covid_individual_contact_estimates_metadata_dictionary.csv: Variable definitions distancia_covid_individual_contact_estimates_spain_cores_wave1.csv.gz: Estimates of coresidents during wave 1 of the Distancia-Covid survey (14 May 2020 through 10 June 2020) distancia_covid_individual_contact_estimates_spain_cores_wave2.csv.gz: Estimates of coresidents during wave 2 of the Distancia-Covid survey (24 July 2020 through 31 August 2020) distancia_covid_individual_contact_estimates_spain_cores_wave3.csv.gz: Estimates of coresidents during wave 3 of the Distancia-Covid survey (14 December 2020 through 10 January 2021) distancia_covid_individual_contact_estimates_spain_noncores_wave1.csv.gz: Estimates of non-coresident contacts during wave 1 of the Distancia-Covid survey (14 May 2020 through 10 June 2020) distancia_covid_individual_contact_estimates_spain_noncores_wave2.csv.gz: Estimates of non-coresident contacts during wave 2 of the Distancia-Covid survey (24 July 2020 through 31 August 2020) distancia_covid_individual_contact_estimates_spain_noncores_wave3.csv.gz: Estimates of non-coresident contacts during wave 3 of the Distancia-Covid survey (14 December 2020 through 10 January 2021) CITATION.cff: Citation file., Individual estimates of age-specific contact patterns in Spain during the Covid-19 pandemic. This data was generated from the CSIC Distancia-Covid survey (https://distancia-covid.csic.es/). It includes estimated numbers of coresidents and non-coresident contacts for each individual represented in the Spanish Labor Force Survey during 2020 and 2021. These estimates do not relate to any identifiable person; rather they provide information about the overall distribution of contacts across the population. These individual estimates have been used to calculate the mean age-specific contacts provided in https://doi.org/10.5281/zenodo.5983902., This data was generated from the survey implemented through the project "Impacto de las medidas de distanciamiento social sobre la expansión de la epidemia de Covid-19 en España," funded by the Spanish National Research Council (Consejo Superior de Investigaciones Científicas, CSIC). Processing and analysis was done with support from the Human-Mosquito Interaction Project (H-MIP) funded by European Research Council Starting Grant No. 853271, and the Versatile emerging infectious disease observatory (VEO) funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 874735., Peer reviewed

DOI: http://hdl.handle.net/10261/285087
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285087
HANDLE: http://hdl.handle.net/10261/285087
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285087
PMID: http://hdl.handle.net/10261/285087
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285087
Ver en: http://hdl.handle.net/10261/285087
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285087

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285101
Dataset. 2022

CONTENTS OF SOIL ORGANIC MATTER FRACTIONS AS AFFECTED BY WARMING AND RAIN EXCLUSION AT A SEMIARID MEDITERRANEAN SITE

  • Plaza de Carlos, César
  • Maestre, Fernando T.
Data and metadata of total, free, intra-aggregate, and mineral-associated organic C and N contents of soils from a dryland ecosystem warming experiment established in Aranjuez, Central Spain., European Commission: BIODESERT - Biological feedbacks and ecosystem resilience under global change: a new perspective on dryland desertification (647038) VULCAN - Vulnerability of soil organic carbon to climate change in permafrost and dryland ecosystems (654132), Peer reviewed

DOI: http://hdl.handle.net/10261/285101
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285101
HANDLE: http://hdl.handle.net/10261/285101
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285101
PMID: http://hdl.handle.net/10261/285101
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285101
Ver en: http://hdl.handle.net/10261/285101
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285101

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285142
Dataset. 2021

H2020 PROJECT CAPTOR: RAW DATA COLLECTED BY LOW-COST MOX OZONE SENSORS IN A REAL AIR POLLUTION MONITORING NETWORK

  • Barceló-Ordinas, José María
  • Ferrer-Cid, Pau
  • García Vidal, Jorge
  • Viana, Mar
  • Ripoll, Anna
The H2020 CAPTOR project deployed three testbeds in Spain, Italy and Austria with low-cost sensors for the measurement of tropospheric ozone (O3). The aim of the H2020 CAPTOR project was to raise public awareness in a project focused on citizen science. Each testbed was supported by an NGO in charge of deciding how to raise citizen awareness according to the needs of each country. The data presented here correspond to the raw data captured by the sensor nodes in the Spanish testbed using SGX Sensortech MICS 2614 metal-oxide sensors. The Spanish testbed consisted of the deployment of twenty-five nodes. Each sensor node included four SGX Sensortech MICS 2614 ozone sensors, one temperature sensor and one relative humidity sensor. Each node underwent a calibration process by co-locating the node at a reference station, followed by a deployment in a non-urban area in Catalonia, Spain. All nodes spent two to three weeks co-located at a reference station in Barcelona, Spain (urban area), followed by two to three weeks co-located at three non-urban reference stations near the final deployment site. The nodes were then deployed in volunteers' homes for about two months and, finally, the nodes were co-located again at the non-urban reference stations for two weeks. All data presented in this repository are raw data taken by the sensors that can be used for scientific purposes such as calibration studies using machine learning algorithms, or once the concentration values of the nodes are obtained, they can be used to create tropospheric ozone pollution maps with heterogeneous sources (reference stations and low-cost sensors)., Peer reviewed

Proyecto: EC/H2020/688110
DOI: http://hdl.handle.net/10261/285142
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285142
HANDLE: http://hdl.handle.net/10261/285142
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285142
PMID: http://hdl.handle.net/10261/285142
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285142
Ver en: http://hdl.handle.net/10261/285142
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285142

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285150
Dataset. 2020

DATA FROM: MEGAFAUNA BIOGEOGRAPHY EXPLAINS PLANT FUNCTIONAL TRAIT VARIATION IN THE TROPICS

  • Dantas, Vinícius de L.
  • Pausas, J. G.
[Methods] We compiled data on the presence of spines, SLA, WD, HMax and presence of spines for Afrotropical and Neotropical savanna and forest woody species (trees and shrubs), from literature and herbarium sources (a list of the data sources is found in Appendix 1). We first compiled SLA and WD data from the primary literature and calculated species means at the biogeographic scale. Then, for Afrotropical species, we searched for HMax and spine data in JSTOR Global Plant (http://plants.jstor.org/) and in the African Plant Database of the Conservatoire et Jardin botaniques de la Ville de Genève and South African National Biodiversity Institute, using the list of species for which we obtained SLA and WD data as reference. For Neotropical species we obtained HMax and presence of spine information from the NeoTropTree dataset (Oliveira-filho, 2017) and Flora do Brasil (2020) for all the available species recorded in Brazilian savanna (Cerrado) and forest (Amazon and Atlantic forest) biomes. For spinescence, we only considered species with detailed descriptions of stem and branch features. We classified species as savanna, forest, or generalist (occurring in both savanna and forest) species, based on the study site descriptions reported in the literature sources from which the data were acquired, and on Mendonça et al. (2008). We only considered species that were consistently classified as forest or savanna, excluding species reported to occur in both ecosystem types, to better pinpoint the patterns and simplify the results. We also classified species according to the biogeographic region in which they occur as Afrotropical or Neotropical species (based on the data reference sources). Introduced species were also excluded using occurrence information from the flora websites and datasets used to compile height and spine data. We obtained data for number and proportion of African geoxylic plants from Maurin et al., (2014). This data is based on the flora of the Zambesian region, a savanna dominated region that includes 12 African countries. Maurin et al., (2014) present two datasets, a sampled dataset, with 53 geoxyles out of the 1400 woody species, and a provisional list of 266 African geoxylic suffrutices taxa occurring south of the Equator. We did not use the latter because an accurate quantification of the southern African flora was not provided. However, a preliminary estimate based on Germishuizen et al. (2003) indicates a total of 8169 woody taxa for southern Africa (including trees, shrubs, dwarf shrubs, subshrubs and suffrutex, but excluding scrumbers, as the proportion of woody stems was not reported). Based in these figures, we found that the first and second datasets represent a similar proportion of geoxyles for African woody species (4 and 3 %, respectively), and would provide very similar results in the statistical analyses. Thus, we only report the results for the sampled species of Maurin et al., (2014). For the Neotropical savanna region, we searched for information on stem and underground organs for subshrub species in the checklist of Mendonça et al. (1998). The list comprises 6429 savanna plant species from the Cerrado region (the largest Neotropical savanna-dominated region) and represents an older version of a more recent checklist with almost twice the number of plant species (but more difficult to work with because only the printed version is available; Mendonça et al., 2008). We then searched for information in plant species descriptions compiled by the Rio de Janeiro Botanical garden and publicly available in Portuguese at the Flora do Brasil (2020) website. We only considered information for species containing detailed descriptions of aerial and underground structures. We found information of this sort for 220 subshrubs out of the 816 subshrub species in the checklist, of which 101 were geoxyles (according to the definition used by Maurin et al., 2014). Based in the observed proportion (46%), we estimated the number of geoxyles among the 816 subshrubs to be 376 species, from a total of 3599 woody species. Thus, the comparison is between savanna regions, not actual savanna or forest vegetation (unlike the comparison for other traits), and only includes subshrub geoxyles, to match the criteria used by Maurin et al., (2014). [Environmental Data] We obtained decimal geographic coordinates for the species for which we obtained WD, SLA and HMax in GBIF.org (28 February 2020; see reference list for doi) and the R package “rgbif”. In order to exclude very close occurrences and, thus, match the resolution of the available satellite-derived environmental data (see below), we rounded the decimal coordinates to include only three decimal digits and then remove repeated species occurrences. We also excluded coordinates falling outside Africa, South and Central Americas, and outside the following biomes (according to Dinerstein et al. 2017): Tropical and Subtropical Moist and Dry Broadleaf Forests; Tropical and Subtropical Grasslands, Savannas and Shrublands; Montane Grasslands and Shrublands; Tropical and Subtropical Coniferous Forests; and, Deserts and Xeric Shrublands. This was directed at minimizing errors, standardizing the latitude ranges and biomes considered for each biogeographic regions, and to exclude flooded ecosystems in which plant relationships with climate and soil are likely different. Thus, from the initial approximately 2,8 million occurrences, we only used 87,739 occurrences, and the number of coordinates per species varied from 1 to 1432. Based on these coordinates, we obtained climate, soil and fire data for each occurrence location from global datasets. We obtained climate data from WorldClim 2 (Fick & Hijmans, 2017), soil data from SoilGrid (250 m of spatial resolution; Hengl et al. 2017), and fire data from the MODIS product MCD14ML collection 6 v.3 (Giglio et al., 2018). We used mean annual precipitation and temperature, as well as rainfall seasonality for the years 1970-2000, as climate variables; cation exchange capacity, organic carbon content, weight percentages of clay (<0.0002 mm), silt (0.0002–0.05 mm), and sand particles (0.05–2 mm), as well as the volumetric percentage of coarse fragments (>2 mm), as soil variables; and fire count per area (as a proxy for fire frequency) and radiative power (a proxy for fire intensity) as fire variables. Soil variables were the averages between two depth, 0.05 and 2 m. Fire data was obtained from a circular area of 5 km centered on the occurrence coordinates between the years 2000 and 2019 (both included). For each species and biogeographic region, we calculated the overall means as an indicator of species habitat preferences as defined by their average position in environmental niche space. [Usage Notes] The dataset that is made available here cosists of two files in .csv format. The first is the complete trait dataset for specific leaf area (sla; mm2.mg-1), wood density (woo; g.cm-3), HMax (m) and Spines (yes/no). The list of reference sources for trait data is presentes in the end of this note. Other abreviations in this file are: ref.sla: reference sources for sla data; ref.woo: reference sources for wood density data; ref.hmax: reference sources for hmax data; mat: mean annual temperature; map: mean annual precipitation; rs: rainfall seasonality; nfires5: number of fires per 5 km area (our proxy for fire frequency); avgfrp: average fire radiative power (our proxy for fire intensity); cec: soil cation exchange capacity; orc: soil organic carbon content; cly: weight percentage of clay particles (<0.0002 mm) in the soil; slt: weight percentage of silt particles (0.0002–0.05 mm) in the soil; snd: weight percentage of the sand particles (0.05–2 mm) in the soil; crf: volumetric percentage of coarse fragments (>2 mm) in the soil. The second file attached is a dataset of Geoxyle species (geox; y(yes)/n(no)) for a subset of the Brazilian Cerrado species., [Aim] Biomes can diverge substantially in plant functional traits and disturbance regimens among regions. Given that Neotropical and Afrotropical regions have contrasting histories of the megafauna (because of the Holocene megafaunal extinction in the Neotropics), we hypothesize that they should harbour plants with different traits in relationship to herbivory and fire, especially in savannas. We predicted that herbivory resistance traits should be more prominent in Afrotropical savanna plants and fire resistance in Neotropical savanna plants., [Location] Tropics., [Time period] Not applicable., [Major taxa studied] Angiosperms (woody)., [Methods] We compiled data for five key plant functional traits (wood density, specific leaf area, maximum tree height, spinescence and proportion of geoxyles) for forest and savanna woody species from the two distant regions (Afrotropics and Neotropics). We related these data to climate, soil and fire variables and tested predictions for megafauna selection., [Results] Spines and high wood density were more common among Afrotropical than Neotropical savanna species and species from the two forests. Moreover, the Neotropical savanna region contained more geoxyles than the Afrotropical savanna region. Finally, Afrotropical species were taller than Neotropical species. These differences were consistent with our predictions for trait selection by the megafauna, and these patterns did not change when considering climate, soil and fire regimens in the models., [Main conclusions] Our results highlight the great potential of these traits for summarizing disturbance strategy axes in tropical woody species and suggest that global variation in plant traits is unlikely to be understood fully without consideration of historical factors, especially the direct and indirect impacts of megafauna., Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) (Finance Code 001), Award: 88887.311538/2018-00., Peer reviewed

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DOI: http://hdl.handle.net/10261/285150
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285150
HANDLE: http://hdl.handle.net/10261/285150
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285150
PMID: http://hdl.handle.net/10261/285150
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285150
Ver en: http://hdl.handle.net/10261/285150
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285150

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