Resultados totales (Incluyendo duplicados): 35683
Encontrada(s) 3569 página(s)
Encontrada(s) 3569 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358792
Dataset. 2024
SUPPLEMENTARY MATERIALS: ANTI-OBESITY EFFECT OF DIFFERENT OPUNTIA STRICTA VAR. DILLENII’S PRICKLY PEAR TISSUES AND INDUSTRIAL BY-PRODUCT EXTRACTS IN 3T3-L1 MATURE ADIPOCYTES
- Gómez-López, Iván
- Eseberri, Itziar
- Cano, M. Pilar
- Portillo, María P.
Table S1: HPLC retention time (Rt), maximum absorption (λmax) and m/z of the identified major bioactive compounds from Opuntia stricta var. dillenii according to Gómez-López et al. (2021) [18]; Table S2: antioxidant activities (ORAC and LOX-FL) of Opuntia stricta var. dillenii’s whole fruit, tissues (peel, and pulp) and by-product (bagasse); Table S3: effects of 10, 25, 50 and 100 µg/mL of extracts from Opuntia stricta var. dillenii whole fruit, peel, pulp and bagasse tissues on triglycerides content (%) of 3T3-L1 mature adipocytes treated for 24 h. Figure S1: HPLC-DAD chromatogram of betalains (at 480 and 535 nm) and phenolic compounds (at 280 and 370 nm) in Opuntia stricta var. dillenii from (a) whole fruit, (b) peel, (c) pulp, and (d) bagasse from the industrialisation. Numbers correspond to the identified compounds indicated in Table S1; Figure S2: structural presentation of the main betalains and phenolic compounds identified in Opuntia stricta var. dillenii., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358792
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358792
HANDLE: http://hdl.handle.net/10261/358792
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358792
PMID: http://hdl.handle.net/10261/358792
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358792
Ver en: http://hdl.handle.net/10261/358792
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358792
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358799
Dataset. 2024
OAK MORPHOLOGY DATASET FROM ITURRARÁN BOTANICAL GARDEN AND SUPPLEMENTARY FILES [DATASET]
- Martín-Sánchez, Rubén
- Sancho-Knapik, Domingo
- Alonso-Forn, David
- López-Ballesteros, Ana
- Ferrio, Juan Pedro
- Hipp, Andrew L.
- Peguero-Pina, José Javier
- Gil-Pelegrín, Eustaquio
1 zip file, containing:
-Morphological data.xlsx: Mean values of each species for the four quantitative traits (LA, LW, ILB and LMA) and the five qualitative traits (Leaf Habit, Pubescence, Shape, Apex, Margin) LA: Leaf Area, expressed in cm2. LW: Lenght-Width ratio, dimensionless. ILB: Index of Lobulation, expressed as (Perimeter/square root of Area), dimensionless. LMA: dry Leaf Mass per Area, expresed as (dry weight/leaf area), expressed in g/m2. Leaf Habit: Deciduous or Evergreen Pubescence: Glabrous, Pubescent or Densely Pubescent Shape: Elliptic, Obovate, Oblong, Lanceolate, Ovate or Circular. Apex: Acute, Acuminate, Rounded or Straight Margin: Entire, Lobated, Serrate, Dentate, Undulate, Spinose or Crenate.
-Climatic data.csv: Average Worldclim variables for each species used in the climatic PCA. See https://www.worldclim.org/data/bioclim.html for further details. "bio20" was calculated ex profeso for the paper as a result of BIO16 minus BIO17.
-Supplementary Tables.xlsx: Supplementary material containing the five supplementary tables for the main manuscript., Files in this folder include raw data as well as supplementary files corresponding to the paper: "Oak leaf morphology may be more strongly shaped by climate than by phylogeny" Rubén Martín-Sánchez, Domingo Sancho-Knapik, David Alonso-Forn, Ana López-Ballesteros, Juan Pedro Ferrio, Andrew L. Hipp, José Javier Peguero-Pina, Eustaquio Gil-Pelegrín. Annals of Forest Science. 2024. https://doi.org/10.1186/s13595-024-01232-z
In addition, you can also find the five supplementary tables generated for the same paper.
Corresponding author: Rubén Martín Sánchez (rmartin@cita-aragon.es), Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358799
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358799
HANDLE: http://hdl.handle.net/10261/358799
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358799
PMID: http://hdl.handle.net/10261/358799
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358799
Ver en: http://hdl.handle.net/10261/358799
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358799
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358807
Dataset. 2021
PROTEOMIC CHARACTERIZATION OF BACTERIOPHAGE PEPTIDES FROM MASTITIS PRODUCER STAPHYLOCOCCUS AUREUS BY LC-ESI-MS/MS AND THE BACTERIOPHAGE PHYLOGENOMIC ANALYSIS [DATASET]
- Carrera, Mónica
21 files, The present work describes LC-ESI-MS/MS analyses of tryptic digestion peptides from phages that infect Staphylococcus aureus-causing mastitis, and isolated from dairy products. A total of 1935 non-redundant peptides belonging to 1282 proteins were identified and analyzed. Among them, 80 staphylococcal peptides from phages were confirmed. These peptides belong to proteins such as phage repressors, structural phage proteins, uncharacterized phage proteins and complement inhibitors. Moreover, of the phage origin peptides found, eighteen of them were specific to S. aureus strains. These diagnostic peptides could be useful for the identification and characterization of S. aureus strains that cause mastitis. Furthermore, a study of bacteriophage phylogeny and the relationship among the identified phage peptides and the bacteria they infect was also performed. The results show the specific peptides which are present in closely related phages, and the existing links between bacteriophage phylogeny and the respective Staphylococcus spp. infected, Excel_dataset_in_Supplemental_Data.xlsx.-- README.txt.-- SA_41_mcarrera_O1205_343.RAW.-- SA_92_mcarrera_O1205_192.RAW.-- SA_280_mcarrera_O1205_190.RAW.-- SA_286_mcarrera_O1205_188.RAW.-- SA_507_mcarrera_O1205_345.RAW.-- SA_587_mcarrera_O1205_184.RAW.-- SA_617_mcarrera_O1205_335.RAW.-- SA_640_mcarrera_O1205_337.RAW.-- SA_700_mcarrera_O1205_182.RAW.-- SA_844_mcarrera_O1205_196.RAW.-- SA_894_mcarrera_O1205_347.RAW.-- SA_ATCC9144_mcarrera_O1205_200.RAW.-- SA_ATCC29213_mcarrera_O1205_333.RAW.-- SA_ATCC35845_mcarrera_O1205_194.RAW.-- SA_CA19_mcarrera_O1205_341.RAW.-- SA_GP2_mcarrera_O1205_349.RAW.-- SA_GP17_mcarrera_O1205_351.RAW.-- SA_OV18_mcarrera_O1205_339.RAW.-- SA_PE1_mcarrera_O1205_198.RAW.-- SA_U17_mcarrera_O1205_186.RAW, Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358807, https://doi.org/10.20350/digitalCSIC/16328
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358807
HANDLE: http://hdl.handle.net/10261/358807, https://doi.org/10.20350/digitalCSIC/16328
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358807
PMID: http://hdl.handle.net/10261/358807, https://doi.org/10.20350/digitalCSIC/16328
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358807
Ver en: http://hdl.handle.net/10261/358807, https://doi.org/10.20350/digitalCSIC/16328
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358807
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358810
Dataset. 2024
SUPPLEMENTARY MATERIALS: ASSESSMENT OF NOVEL PROTEINS TRIGGERING CELIAC DISEASE VIA DOCKING-BASED APPROACH
- Atanasova, Mariyana
- Dimitrov, Ivan
- Fernández, Antonio
- Moreno, F. Javier
- Koning, Frits
- Doytchinova, Irini
Table S1. Docking-based quantitative matrix for α-gliadin peptide library docked in HLA-DQ2.5; Table S2. Docking-based quantitative matrix for non-gliadin peptide library docked in HLA-DQ2.5; Table S3. Docking-based quantitative matrix for α-gliadin peptide library docked in HLA-DQ8.1. Figure S1a. Accuracy of predictions by the QMs for α-gliadin peptide (blue curve) and non-gliadin peptide (orange curve) at different cutoffs between binders and non-binders to HLA-DQ2.5. Figure S1b. Accuracy of predictions by the QM for HLA-DQ8.1 at different cutoffs between binders and non-binders. Figure S2. Intermolecular interactions between the most positively/negatively contributing peptide residues from α-gliadin and non-gliadin peptides binding into the corresponding pockets of HLA-DQ2.5 and HLA-DQ8.1. The hydrogen bonds are presented as orange discontinued lines; π-π-stacking with red or pale pink for weaker contacts, hydrophobic interactions with green or pale green for weaker interactions. The peptide backbone and sidechains are coloured in cyan. Hydrogens are not presented., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358810
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358810
HANDLE: http://hdl.handle.net/10261/358810
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358810
PMID: http://hdl.handle.net/10261/358810
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358810
Ver en: http://hdl.handle.net/10261/358810
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358810
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/359411
Dataset. 2023
HERBICOLIN A PRODUCTION AND ITS MODULATION BY QUORUM SENSING IN A PANTOEA AGGLOMERANS RHIZOBACTERIUM BIOACTIVE AGAINST A BROAD SPECTRUM OF PLANT-PATHOGENIC FUNGI [DATASET]
- Matilla, Miguel A.
- Evans, T.J.
- Martín, J.
- Udaondo, Zulema
- Lomas-Martínez, C.
- Rico-Jiménez, Miriam
- Reyes, F.
- Salmond, G.P.C.
Supplementary material table and figures, Table S1. Bacteria, oomycete, fungi, phages, plasmids and oligonucleotides used in this study.
Figure S1. Halos of antibiosis of filter-sterilized supernatants of Pantoea agglomerans 9Rz4 grown in different culture media. Growth inhibition of the ascomycete yeast Schizosaccharomyces pombe (herbicolin A sensitive) with culture supernatants of P. agglomerans 9Rz4 and the herbicolin A deficient mutant NB1 grown overnight in LB, minimal medium (MM), YE and Strobel medium (Strobel et al., 1999) at 25 ºC. For the bioassays, a S. pombe top agar lawn was prepared in YE-agar and 300 µl of filter-sterilized supernatants were added to holes punched in the S. pombe bioassay plates. The size of the inhibition halos is indicative of the susceptibility of S. pombe to herbicolin A. The bioassays were repeated three times and representative pictures are shown. Picture were taken after 48 h of incubation at 30 ºC. The radius of the halos from three biological replicas is 7.0 ± 0.2 mm (LB), 4.1 ± 0.1 (MM), 6 ± 0.1 mm (YE) and 1.8 ± 0.05 mm (Strobel medium). Bars, 5 mm.
Figure S2. Pantoea agglomerans 9Rz4 maize root colonization and its effect on plant growth. A, Maize plants 10 days after inoculation with 9RZ4. Non-inoculated plants were included as control. B, Root weight of maize plants shown in Fig. S2A. Shown are mean and standard deviation of six different plants. No statistically significant differences in root weight were observed between inoculated and non-inoculated plants. C, Maize root colonization assays of P. agglomerans 9Rz4 and its mutant strain NB1. Shown are mean and standard deviation of six different plants. In A-C, sterilization, germination and inoculation of maize seeds was carried out as described previously (Matilla et al., 2007), with minor modifications. Briefly, sterile maize seeds were incubated for 45 min at 30 ºC with a 107 CFU/mL of Pantoea agglomerans 9Rz4 strains. Thereafter, seeds were rinsed with sterile deionized water and planted in 50 mL tubes containing 40 g of sterile washed silica sand and 10% (v/w) plant nutrient solution supplemented with Fe-EDTA and micronutrients, as described previously (Matilla et al., 2007). Plants were maintained at 24 ºC with a daily light period of 16 h for 10 days.
Figure S3. Effect of plasmid carriage on the antifungal properties of P. agglomerans 9Rz4. Bioactivity against Verticillium dahliae of 9Rz4 and a 9Rz4 variant (9Rz4-W) lacking plasmid p9Rz4_1. Pictures were taken after 96 h of incubation at 25 °C.
Figure S4. Herbicolins A and B production is reduced in the quorum sensing mutant defective in the acyl-homoserine lactone synthase PagI. Abundance of herbicolins A and B relative to the wild type 9Rz4 in the supernatants of the P. agglomerans 9Rz4 strains. Data are the mean and standard deviations from three biological replicates and correspond to the intensity (area under the peak) of “extracted ion chromatograms” (EIC) shown in Fig. 6B. Note that the areas derived from the EICs are not comparable between compounds (e.g. herbicolin A vs herbicolin B) as these areas depend on the ionization efficiency of each compound. As shown in Fig. 1A, herbicolin B is found at trace levels in the 9Rz4 supernatants based on LC-HRMS analyses.
Figure S5: Complementation of herbicolins A and B production in the quorum sensing mutant defective in the acyl-homoserine lactone synthase PagI. A, Growth inhibition of Schizosaccharomyces pombe with culture supernatants of Pantoea agglomerans strains. For the assays, P. agglomerans strains were inoculated at an initial OD660 of 0.05 in 10 mL of LB medium containing 1 mL supernatants of overnight cultures of P. agglomerans NB1 (herbicolin A defective; wild type in acyl-homoserine lactone production) or P. agglomerans PagI (defective in the synthesis of acyl-homoserine lactones) grown in LB medium. Then, bacterial cultures were grown overnight at 25 ºC, at which time the supernatants were collected, filter-sterilized and characterized chemically and biologically. For the bioassays, a Schizosaccharomyces pombe top agar lawn was prepared and 300 µL of filter-sterilized supernatants were added to holes punched in the S. pombe bioassay plates. Pictures were taken after 48 h of incubation at 30 ºC. Numerical values indicate the mean and standard deviation of the radius of the inhibition halo of three biological replicates. Bars, 5 mm. B, Extracted ion chromatograms (EIC) corresponding to an m/z of 659.385 ± 0.005 (theoretical value for [M+2H]2+ in herbicolin A) and to an m/z of 569.845 ± 0.005 (theoretical value for [M+2H]2+ in herbicolin B). C, Abundance of herbicolins A and B relative to the wild type strain 9Rz4 in the supernatants of the P. agglomerans 9Rz4 strains through the measurement of peak areas in the EICs shown in Fig. S5B. In B and C, note that the areas derived from the EICs are not comparable between compounds (e.g. herbicolin A vs herbicolin B) as these areas depend on the ionization efficiency of each compound. As shown in Fig. 1A, herbicolin B is found at trace levels in the 9Rz4 supernatants based on LC-HRMS analyses., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/359411, https://doi.org/10.20350/digitalCSIC/16335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/359411
HANDLE: http://hdl.handle.net/10261/359411, https://doi.org/10.20350/digitalCSIC/16335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/359411
PMID: http://hdl.handle.net/10261/359411, https://doi.org/10.20350/digitalCSIC/16335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/359411
Ver en: http://hdl.handle.net/10261/359411, https://doi.org/10.20350/digitalCSIC/16335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/359411
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358839
Dataset. 2024
SUPPORTING INFORMATION: CRANBERRY POLYPHENOLS AND PREVENTION AGAINST URINARY TRACT INFECTIONS: NEW FINDINGS RELATED TO THE INTEGRITY AND FUNCTIONALITY OF INTESTINAL AND URINARY BARRIERS
- González de Llano, Dolores
- Roldán García, Mikel
- Taladrid, Diego
- Relaño de la Guía, Edgard
- Moreno-Arribas, M. Victoria
- Bartolomé, Begoña
Quantity (ng/μL) and quality assurance (ratio 260/280) of extracted RNA (Table S1); primer sequences and melting temperature (Tmelting) used for TJ protein quantification by qRT-PCR (Table S2); data (mean ± standard deviation) of transepithelial electrical resistance (TEER) (Ω cm2) from samples and control, before (t = 0 h) and after treatments (t = 4 h), and for Caco-2 and T24 cells; calculation of ΔTEER with respect to control is also included (Table S3); and PCR data of TJ proteins (occludin, Z0–1, and claudin-2) expression as fold change (mean ± standard deviation) with respect to the noninfected control (C), the effluent Ef, the infected control (UPEC), the effluent Ef in the infected model (UPEC + Ef), or urine (Urine) (Table S4)., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358839
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358839
HANDLE: http://hdl.handle.net/10261/358839
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358839
PMID: http://hdl.handle.net/10261/358839
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358839
Ver en: http://hdl.handle.net/10261/358839
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358839
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358877
Dataset. 2021
CLIMATE, VEGETATION AND FIRE HISTORY DURING THE PAST 18,000 YEARS, RECORDED IN SEDIMENTS OF THE SANETTI PLATEAU, BALE MOUNTAINS (ETHIOPIA) [DATASET]
- Mekonnen, Betelhem
- Glaser, Bruno
- Zech, Roland
- Zech, Michael
- Schlütz, Frank
- Bussert, Robert
- Addis, Agerie
- Gil-Romera, Graciela
- Nemomissa, Sileshi
- Bekele, Tamrat
- Bittner, Lucas
- Solomon, Dawit
- Manhart, Andreas
- Zech, Wolfgang
XRF, biogeochemical and pollen results of B4 depression sediments, Sanetti Plateau (Bale Mountains, Ethiopia), Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358877
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358877
HANDLE: http://hdl.handle.net/10261/358877
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358877
PMID: http://hdl.handle.net/10261/358877
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358877
Ver en: http://hdl.handle.net/10261/358877
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358877
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358881
Dataset. 2021
DISENTANGLING RESPONSES TO NATURAL STRESSOR AND HUMAN IMPACT GRADIENTS IN RIVER ECOSYSTEMS ACROSS EUROPE [DATASET]
- Stubbington, Rachel
- Sarremejane, Romain
- Laini, Alex
- Cid, Núria
- Csabai, Zoltán
- England, Judy
- Munné, Antoni
- Aspin, Thomas
- Bonada, Núria
- Bruno, Daniel
- Cauvy-Fraunie, Sophie
- Chadd, Richard
- Dienstl, Claudia
- Fortuño, Pau
- Graf, Wolfram
- Gutiérrez-Cánovas, Cayetano
- House, Andy
- Karaouzas, Ioannis
- Kazila, Eleana
- Millán, Andrés
- Morais, Manuela
- Pařil, Petr
- Pickwell, Alex
- Polášek, Marek
- Sánchez-Fernández, David
- Tziortzis, Iakovos
- Várbíró, Gábor
- Voreadou, Catherina
- Walker-Holden, Emma
- White, James
- Datry, Thibault
All_region_-_community_-_familes_by_samples.xlsx = The sample-by-taxa spreadsheet used in the all-region whole community analysis, i.e. "taxaxsamples" in the Dryad file "Example script to calculate biological metrics in biomonitoR.R", All_region_-_community_-_env._variables_and_bio._metrics.xlsx = A spreadsheet listing - for all samples used in the all-region whole community analysis - methods details, environmental variables and biological response variables, the latter calculated in biomonitoR, All_region_-_highRR_-_familes_by_samples.xlsx = The sample-by-taxa spreadsheet used in the all-region 'high RR' analysis, All_region_-_highRR_-_env._variables_and_bio._metrics.xlsx = A spreadsheet listing - for all samples used in the all-region 'high RR' analysis - methods details, environmental variables and biological response variables, All_region_-_community_-_STAR_ICMi_only.xlsx = A spreadsheet listing - for East Mediterranean samples used in the whole community analyses - the region-specific biomonitoring indices STAR_ICMi and its ASPT (average score per taxon) as calculated following Buffagni et al. (2006), All_region_-_highRR_-_STAR_ICMi_only.xlsx = A spreadsheet listing - for East Mediterranean samples used in the 'high RR' analyses - the region-specific biomonitoring indices STAR_ICMi and its ASPT (average score per taxon) as calculated following Buffagni et al. (2006), Fuzzy_coding_of_traits.csv = A spreadsheet showing the calculation of fuzzy-coded scores for each trait. The final column for each trait (e.g. G for "Maximum potential size") is based on the preceding columns for that trait (e.g. E and F for "Maximum potential size"). For example, in row 10, no individuals have a maximum potential size ≤ .25 cm (0*4, where 4 is the trait weight shown in row B) and 75% of individuals have a maximum potential size > 0.25-0.5 cm (0.75*4); therefore (0*4)+(0.75*4)=3., Genus-level_analyses.xlsx = A multi-tab spreadsheet showing the sample-by-taxa matrix and community metrics for each region/dataset used in the genus-level analyses described in Appendix S1.4, 1. Rivers are dynamic ecosystems in which both human impacts and climate-driven drying events are increasingly common. These anthropogenic and natural stressors interact to influence the biodiversity and functioning of river ecosystems. Disentangling ecological responses to these interacting stressors is necessary to guide management actions that support ecosystems adapting to global change., 2. We analysed the independent and interactive effects of human impacts and natural drying on aquatic invertebrate communities—a key biotic group used to assess the health of European freshwaters. We calculated biological response metrics representing communities from 406 rivers in eight European countries: taxonomic richness, functional richness and redundancy, and two biomonitoring indices that indicate ecological status. We analysed metrics based on the whole community and a group of taxa with traits promoting resistance and/or resilience (‘high RR’) to drying. We also examined how responses vary across Europe in relation to climatic aridity., 3. Most community metrics decreased independently in response to impacts and drying. A richness-independent biomonitoring index (the average score per taxon; ASPT) showed particular potential for use in biomonitoring, and should be considered alongside new metrics representing high RR diversity, to promote accurate assessment of ecological status., 4. High RR taxonomic richness responded only to impacts, not drying. However, these predictors explained little variance in richness and other high RR metrics, potentially due to low taxonomic richness. Metric responsiveness could thus be enhanced by developing region-specific high RR groups comprising sufficient taxa with sufficiently variable impact sensitivities to indicate ecological status., 5. Synthesis and applications. Our results inform recommendations guiding the development of metrics to assess the ecological status of dynamic river ecosystems—including those that sometimes dry—thus identifying priority sites requiring further investigation to identify the stressors responsible for environmental degradation. We recommend concurrent consideration of richness-independent biomonitoring indices (such as an ASPT) and new high RR richness metrics that characterize groups of resistant and resilient taxa for region-specific river types. Interactions observed between aridity, impacts and drying evidence that these new metrics should be adaptable, promoting their ability to inform management actions that protect river ecosystems responding to climate change., European Cooperation in Science and Technology, Award: CA15113, Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358881
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358881
HANDLE: http://hdl.handle.net/10261/358881
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358881
PMID: http://hdl.handle.net/10261/358881
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358881
Ver en: http://hdl.handle.net/10261/358881
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358881
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358909
Dataset. 2022
SUPPORTING INFORMATION: DISENTANGLING RESPONSES TO NATURAL STRESSOR AND HUMAN IMPACT GRADIENTS IN RIVER ECOSYSTEMS ACROSS EUROPE
- Stubbington, Rachel
- Sarremejane, Romain
- Laini, Alex
- Cid, Núria
- Csabai, Zoltán
- England, Judy
- Munné, Antoni
- Aspin, Thomas
- Bonada, Núria
- Bruno, Daniel
- Cauvy-Fraunie, Sophie
- Chadd, Richard
- Dienstl, Claudia
- Fortuño, Pau
- Graf, Wolfram
- Gutiérrez-Cánovas, Cayetano
- House, Andy
- Karaouzas, Ioannis
- Kazila, Eleana
- Millán, Andrés
- Morais, Manuela
- Pařil, Petr
- Pickwell, Alex
- Polášek, Marek
- Sánchez-Fernández, David
- Tziortzis, Iakovos
- Várbíró, Gábor
- Voreadou, Catherina
- Walker-Holden, Emma
- White, James
- Datry, Thibault
This file contains Appendix S1 (including Figure A1 and Tables A1–A4), Appendix S2 (including Table A5), Appendix S3 and Appendix S4 (including Figures S1–S2 and Tables S1–S18) followed by supporting references., Contents: APPENDIX S1 Supporting analyses validating the analytical approaches.-- S1.1 Inclusion versus exclusion of samples taken in ponded conditions.-- S1.2 Spring and autumn versus all seasons.-- S1.3 Inclusion versus exclusion of perennial sites.-- S1.4 Genus and mixed subfamily-level analyses S1.5 Abundance versus presence–absence data.-- S1.6 Performance of biomonitoring indices in the all-region models.-- APPENDIX S2 Calculation of functional redundancy and richness.-- APPENDIX S3 Description of environmental conditions and communities in each dataset.-- APPENDIX S4 Supporting figures and tables.-- FIGURE S1 The contribution of 14 datasets to 16 models.-- FIGURE S2 NMDS ordinations of variability in community composition in each region.-- TABLE S1 Characteristics of each dataset.-- TABLE S2 Statements used to calculate the level of human impacts at each site.-- TABLE S3 Environmental variables included and excluded based on VIF analysis.-- TABLE S4 Rationale for inclusion of each biological trait.-- TABLE S5 Rationale for inclusion/exclusion of taxa in the trait assignment process.-- TABLE S6 Resistance/resilience scores of the top-33% ranked taxa in each dataset.-- TABLE S7 Summary of the invertebrate community in each dataset.-- TABLE S8 Model results – Atlantic region.-- TABLE S9 Model results – West Mediterranean region.-- TABLE S10 Model results – East Mediterranean region.-- TABLE S11 Model results – ES_S dataset.-- TABLE S12 Model results – ES_E dataset.-- TABLE S13 Model results – ES_NE2 dataset.-- TABLE S14 Model results – CY dataset.-- TABLE S15 The proportion of variance explained for each response metric.-- TABLE S16 Comparison of metric responses at family and genus level.-- TABLE S17 Summary of family-level community and high RR metric responses.-- TABLE S18 Model results – all-region model high RR group.-- References cited in the Supporting Information, Peer reviewed
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DOI: http://hdl.handle.net/10261/358909
Digital.CSIC. Repositorio Institucional del CSIC
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HANDLE: http://hdl.handle.net/10261/358909
Digital.CSIC. Repositorio Institucional del CSIC
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PMID: http://hdl.handle.net/10261/358909
Digital.CSIC. Repositorio Institucional del CSIC
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Ver en: http://hdl.handle.net/10261/358909
Digital.CSIC. Repositorio Institucional del CSIC
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358910
Dataset. 2022
SUPPLEMENTARY INFORMATION: DISENTANGLING THE LEGACIES OF CLIMATE AND MANAGEMENT ON TREE GROWTH
- Marqués, Laura
- Peltier, Drew M. P.
- Camarero, Jesús Julio
- Zavala, Miguel A.
- Madrigal-González, Jaime
- Sangüesa-Barreda, G.
- Ogle, K.
PDF file contains: Appendix S1-S10., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/358910
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358910
HANDLE: http://hdl.handle.net/10261/358910
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358910
PMID: http://hdl.handle.net/10261/358910
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358910
Ver en: http://hdl.handle.net/10261/358910
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/358910
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