BUSCADOR RECOLECTA

Index of supplemental materials: Table S1. Species information and accession number for sequences retrieved from public databases included in phylogenetic analysis. Table S2. Uricase (urate oxidase) partial sequences for YLS obtained from C. brasiliensis and C. orchidearum, and four Fulgoroidea species samples in Costa Rica. Table S3. Ant species associated with colonies of Cerataphis spp. and plant host combinations observed in Costa Rica and/or reported worldwide., Peer reviewed

1 vídeo., Monitoring water systems under extreme conditions or in remote areas poses a risk to scientists and staff involved, and can also result in disturbances to the local flora and fauna. In order to overcome these limitations, new techniques are being developed with the aim to gain more insight into how geochemical pathways of trace elements regulate the functioning of the ocean. Here, we present the first trace metals and inorganic nutrients concentrations measured in dissolved (<0.22 µm) surface water samples collected in the Antarctic by using an Automatic Water Autosampler (AWA) system onboard an unmanned aerial vehicle (UAV). The AWA system has been used to chemically quantify the composition of the water masses (lake and coastal water) of Deception Island (South Shetland Islands, Antarctica), with, for example, Pb values ranging from 0.01 to 0.25 nM in seawater and 1.20 to 2.11 nM in lake water. The results demonstrate the effectiveness of the AWA system in environmental studies that require the sampling of trace metals and nutrients without sample contamination., Peer reviewed

Plasmid maps and full sequences of Lit2C-PK2 and HomA-PK2; and plate images of plaque assay comparing P2 infection in ΔwaaC and BW25113 bacterial strains (−3 to −8)., Peer reviewed

Consellería do Medio Rural (Xunta de Galicia) supported the establishment of the trial network. Planting was carried out by Grupo Tragsa.Tree measurements were done by the MBG-CSIC under the project “RESILPINE” (RTI2018-094691-B-C33) funded by the Spanish Government., 1. Number of variables: 9 2. Number of cases/rows: 8400 3. Variable List: S X Y G ID B H SUR Section, Peer reviewed

Supplementary Table 1 | List of (A) transcriptomics, (B) metabolomics, (C) proteomics, and (D) ionomics studies retrieved from the literature., Peer reviewed

Table S1. Sex- and age-related differences in the wing patch size across the Stonechat population when all birds of known age were examined (e.g., age 0, juveniles; age 1, first-year adults; and so on). The mean, standard error (SE), degrees of freedom (df), and 95% coefficient intervals (CI) for each category are shown. Table S2. Pairwise differences in wing patch size between males and females of the same age-class, and across the age of individuals when all birds of known age were examined (e.g., age 0, juveniles; age 1, first-year adults; and so on). Note that, for the single adult male captured with an age-class of 5 years, comparisons between sexes cannot be made. For each comparison, estimate, standard error (SE), degrees of freedom (df), t-ratio and p-value adjusted by Tukey method are shown. Significant differences are in bold. Table S3. Total number of measurements obtained from the white wing patch of adult males (1) and females (2) during the study period. Only birds measured two or more times are shown. The data are grouped by plumage-year, so that they correspond to the year in which the measured plumage was moulted. For example, a bird with a "2" in 2008 was captured and measured twice between the moult of 2008 and the moult of 2009, i.e. between June 2008 and June 2009. Table S4. The three top-ranked candidate models (< 2 AICc points) resulting from the analysis performed to identify the source of variation of the wing patch size in common stonechat males. The number of identifiable parameters (K), the AICc value, the difference in AICc with respect to the highest-ranked model (ΔAICc), the maximized value of the log-likelihood function (LL), and the models with uninformative parameters (UP) are shown. Table S5. The six top-ranked models (< 2 AICc points) resulting from the analysis performed to identify the source of variation of the wing patch size in common stonechat females. The number of identifiable parameters (K), the AICc value, the difference in AICc with respect to the highest-ranked model (ΔAICc), the maximized value of the log-likelihood function (LL), and the models with uninformative parameters (UP) are shown. Table S6. Baseline and adjusted repeteabilities (R) of wing patch size in male and female stonechats. Baseline repeatabilities were calculated from models including the random effect alone (1|identity), while adjusted repeatabilites were obtained from models fitted with significant fixed effects (age, month, and year). To test the effect of intra-individual consistency within the same plumage-year, here we removed repeated measurements within the same plumage-year (only first measurement taken was kept). Figure S1. Wing plumage photos showing the white patch on a juvenile (top), a female (middle) and a male (bottom) of European Stonechat, Saxicola rubicola rubicola, from our study population. Figure S2. Individual variation in wing patch size within a plumage-year in males (top) and females (bottom). Dots represent individual wing patch measurements, while lines connect measurements from the same individual and plumage-year. Note that two different lines do not necessarily represent measurements from different individuals, if not they can have been taken in a different plumage-year. Annex I. Preliminary analyses conducted to select the effect of mean temperature of May for each sampling year (from 2006 to 2012)., Peer reviewed

Appendix A. Supplementary data: The Supplementary data to this article: Multimedia component 1. Multimedia component 2., Peer reviewed

The raw data presented in this study are available in the NCBI repository (BioProject PRJNA684483). Processed data to replicate the analysis are in the Supplementary material., Peer reviewed

Supplementary Text 1: Characterization of phenotypic effects of infection in the 21 A. thaliana genotypes used. Supplementary Fig. S1. Supplementary Fig. S2. Supplementary Text 2: ANOVA-like analysis of the infection matrix. Supplementary Table S1. Supplementary Fig. S3. Supplementary Table S2., Peer reviewed

Supplementary Material 1: List of variables used for the selection of factors conditioning wild lentil species distribution in Europe and Turkey., Crop wild relatives are species related to cultivated plants, whose populations have evolved in natural conditions and confer them valuable adaptive genetic diversity, that can be used in introgression breeding programs. Targeting four wild lentil taxa in Europe, we applied the predictive characterization approach through the filtering method to identify populations potentially tolerant to drought, salinity, and waterlogging. In parallel, the calibration method was applied to select wild populations potentially resistant to lentil rust and broomrape, using, respectively, 351 and 204 accessions evaluated for these diseases. An ecogeographic land characterization map was used to incorporate potential genetic diversity of adaptive value. We identified 13, 1, 21, and 30 populations potentially tolerant to drought, soil salinity, waterlogging, or resistance to rust, respectively. The models targeting broomrape resistance did not adjust well and thus, we were not able to select any population regarding this trait. The systematic use of predictive characterization techniques may boost the efficiency of introgression breeding programs by increasing the chances of collecting the most appropriate populations for the desired traits. However, these populations must still be experimentally tested to confirm the predictions., Peer reviewed