BUSCADOR RECOLECTA

Dataset of the scientific article "Nestling sex and behaviour determine the host preference of insect vectors in avian nests"., Peer reviewed

Figure S1 - spectrum.02623-23-s0001.docx Observed viable counts of Hp ATCC 700392 following exposure to the Hp-fld inhibitor compound IV at four times the MIC., Peer reviewed

Supplementary Figure 1. Apricot grafted onto a transgenic plum rootstock. (A) Apricot bud grafted sprouting after artificial winter. (B) Heavily infected apricot scion grafted onto the transgenic susceptible plum line St5’-7 and (C) healthy apricot grafted onto the resistant plum rootstocks. (D) Detail of an apricot grafted plant (ag) after trimming the plum rootstock (pr) where can be seen the point of chip-budding infection (cb). Supplementary Figure 2. Chip budding technique used to infect apricot scions with sharka. A cut in the apricot scion (1) allows the introduction of a piece of bark from an infected GF305 new growth (2) within the apricot scion (3). Grafting is wrapped with parafilm to avoid desiccation (4) and it is maintained until it dries out and falls (5). Supplementary Figure 3. Schematic representation of the h-UTR/P1 T-DNA showing the position of primers used in this study. Supplementary Figure 4. Electrophoretic analysis of PCR products for PPV detection. L: DNA ladder 100 pb (New England Biolabs, Cat. no. N3231L). Lanes 1-10: apricot scion grafted onto different St5’ transgenic rootstocks. Lane 1 and 2: onto St5’-7 plants. Lanes 3 and 4: onto St5’-6 plants. Lanes 5-7 onto St5’-1 plants. Lanes 5-7 onto St5’-9 plants. Lane 10 H2O, Peer reviewed

1 figure, 3 tables, Supporting information for the article https://doi.org/10.1016/j.wasman.2022.01.035, Figure S1 - Box plots and kernel density plots before and after normalization. The density plots are based on all samples. Data transformation: Log Normalization; Data scaling: Autoscaling.-- Table S1 – Amino acids content from substrates of the five study groups: control group (a), 25% replacement (b), 50% replacement (c), 75% replacement (d) and 100% replacement (e)) of expired fish feed. (g/100 g total amino acids). OHPro: hydroxyproline. Errors are the confidence intervals for n=2 (replicates of analysis) and α =0.05.-- Table S2 – Amino acids content of Black Soldier Fly larvae (g/100 g total amino acids). Errors are the confidence intervals for n=2 (replicates of analysis) and α=0.05.-- Table S3 - Fatty acid composition from substrates lipid extracts of the five study groups: control group (a), 25% replacement (b), 50% replacement (c), 75% replacement (d) and 100% replacement (e) of expired fish feed. Abundances are expressed in relative abundance (%) and values are means of five samples (n = 5) ± standard deviation, Peer reviewed

PDF file contains: Tables S1-S5 and Figures S1-S4.-- © Author(s) 2022. CC BY 4.0 License. The copyright of individual parts of the supplement might differ from the article licence., Peer reviewed

R scripts showing how to use climwin package with tree-ring width and anatomy chronologies. The databases needed to use the scripts are included., [FILES] 1. climwin with dendro and anatomy.R R script in which climwin is used to study the growth/anatomy-climate relationships of 5 species with weekly time resolution. 2. climwin with the river flow.R R script in which climwin is used to study the growth-river flows relationships of 2 sites with monthly time resolution. 3. Pinus sylvestris model.R R script in which climwin is used to fit a multiple linear regression. 4. RingWidths.csv Database of detrended growths and anatomical variables needed to run the R scripts. Abbreviations: LA - lumen area CWT - cell wall thickness ew - earlywood lw - latewood Ps - Pinus sylvestris (Corbalán site) Aa - Abies alba (Paco Ezpela site) VA1 - Valdelinares (Pinus uncinata) AL - Alcalá de la Selva (Pinus sylvestris) CO - Olmedilla (Pinus nigra) AC - Alto de Cabra (Pinus pinaster) VH - Valbona (Pinus halepensis) 5. climate.rds Database of climate needed to run the R scripts. Abbreviations: T - Temperature Tmax - Maximum temperature Tmin - Minimum temperature P - Precipitation spei - Standardized Evapotranspiration Precipitation Index using a range of time scales (1, 3, 6, 9, 12, 24, 36 and 48 months) over which water deficits and surplus accumulate are considered. 6. Fraxinus.csv Database of detrended growths of Fraxinus needed to run the R scripts. 7. River flow.csv Database of river flow needed to run the R scripts. 8. readme.txt txt file explaining the details of the data. (2021-07-01), [METHODOLOGY] We aim to identify the most likely climate variables driving the growth and wood anatomy of the species using climwin package. We used the weekly resolved climate data and a randomization technique to find, for each climate variable, the most relevant period of the year in which climate was most related to growth according to climwin. To identify the most likely climate predictors of the growth and wood anatomy features and the most relevant time window (the most influential period of the year for individual climate variables), we fitted simple linear regressions with the growth/anatomy variables as the response variables and the climate variables as predictors. The mean of each factor in each time window considered was used as the aggregate statistics. For each factor all possible window lengths (periods of year) at weekly resolution (but monthly resolution for the flow river) was calculated and the one with the lowest ΔAICc compared to the null model (i.e., including the intercept only) was selected. Finally, randomization tests were calculated using 1000 repetitions to calculate pΔAICc (the likelihood that a climatic signal is real). October 1 of the previous year was established as the threshold for the beginning of the windows and November 31 of the year of growth as the limit for the end of the windows. A minimum length of two weeks was pre-defined. A multiple linear regression were fitted using P. sylvestris pine lumen area chronology, without distinguishing between earlywood and latewood, as the response variable and including the climate variables found to be statistically significant. For building the model with climwin we followed this procedure: (i) among the simple linear models calculated with climwin for the response variable, the model with the lowest ∆AICc was selected; (ii) using this model as baseline model, we introduced the rest of climatic variables one by one in order to fit all possible two-factor models, obtaining for each model ∆AICc, climate windows and p∆AICc; and (iii) the models with p∆AICc < 0.05 were selected. Finally, only a model with two climate variables met this condition. If more significant models with different climatic variables had been found, the whole process would have to be repeated including the model with two climatic factors with lower ∆AICc in the baseline model. Multicollinearity was avoided by controlling the variance inflation factor (VIF)., Ministerio de Economía y Competitividad: CGL2015-69186-C2-1-R Agencia Estatal de Investigación: RTI2018-096884-B-C31, Peer reviewed

-General information for the experimental section, crystallographic data, computational details, catalytic reaction profiles, and NMR spectra (PDF). -Cartesian coordinates of the optimized structures (XYZ)., Peer reviewed

Methionine supplementation during the suckling period of ewe lambs might program feed efficiency during the whole life time due to stable changes of epigenetic marks caused by methylation of DNA. The results of the present study revealed that methionine supplementation during the suckling period has a limited effect on epigenetic marks of DNA obtained from blood., This work was funded by Ministerio de Ciencia e Innovación (PID2021-126489OB-I00, MCIN/AEI/10.13039/501100011033, “FEDER, Una manera de hacer Europa”); ACRONYM: NUPROVI Alba Martín gratefully acknowledges receipt of a pre-doctoral grant (PRE2019-089288) from Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033, “El FSE invierte en tu futuro”); CSIC is acknowledged for supporting Open Access publication., 3_****_L001_R1_001.fastq 3_****_L001_R2_001.fastq 4_****_L001_R1_001.fastq 4_****_L001_R2_001.fastq 16_****_L001_R1_001.fastq 16_****_L001_R2_001.fastq 17_****_L001_R1_001.fastq 17_****_L001_R2_001.fastq 20_****_L001_R1_001.fastq 20_****_L001_R2_001.fastq 21_****_L001_R1_001.fastq 21_****_L001_R2_001.fastq 29_****_L001_R1_001.fastq 29_****_L001_R2_001.fastq 30_****_L001_R1_001.fastq 30_****_L001_R2_001.fastq 31_****_L001_R1_001.fastq 31_****_L001_R2_001.fastq 32_****_L001_R1_001.fastq 32_****_L001_R2_001.fastq, No

3 tables, 30 figures, Supplementary Material for the article https://doi.org/10.1016/j.ecolind.2020.107141, Table S1. Summary of the model structure fitted to each species’ body size data.-- Table S2. Summary table indicating the body size reference points and source of information for each species’ length at maturity.-- Figure S1. Percentage of annual change for the body size of each species at catch for the period 2000-2018 in ICES division 9.a (lower panel) and ICES division 8.c (upper panel).-- Figure S2. Time series of the estimated indices of abundance for the 20 species analysed from 2000 to 2018 in the Galician coast (NE Atlantic) taken from Alonso-Fernández et al. (2019) and updated up to year 2018.-- Figure S3. Percentage of change by year for each species index of abundance for the period 2000-2018 in ICES division 9.a (lower panel) and ICES division 8.c (upper panel).-- Figure S4. Time series of the skewness of the body size frequency distribution for the 20 species analysed over the period 2000 to 2018.-- Figure S5. Slope of the linear trend of body size skewness for each species in ICES division 9.a (lower panel) and ICES division 8.c (upper panel).-- Figure S6. Residual check for the model fitted to Trisopterus luscus body size data.-- Figure S7. Residual check for the model fitted to Pollachius pollachius body size data.-- Figure S8. Residual check for the model fitted to Mullus surmuletus body size data.-- Figure S9. Residual check for the model fitted to Dicentrarchus labrax body size data.-- Figure S10. Residual check for the model fitted to Conger conger body size data.-- Figure S11. Residual check for the model fitted to Labrus bergylta body size data.-- Figure S12. Residual check for the model fitted to Diplodus sargus body size data.-- Figure S13. Residual check for the model fitted to Scophthalmus maximus body size data.-- Figure S14. Residual check for the model fitted to Scophthalmus rhombus body size data.-- Figure S15. Residual check for the model fitted to Solea solea body size data.-- Figure S16. Residual check for the model fitted to Solea senegalensis body size data.-- Figure S17. Residual check for the model fitted to Pegusa lascaris body size data.-- Figure S18. Residual check for the model fitted to Platichthys flesus body size data.-- Figure S19. Residual check for the model fitted to Scyliorhinus canicula body size data.-- Figure S20. Residual check for the model fitted to Raja undulata body size data.-- Figure S21. Residual check for the model fitted to Sepia officinalis body size data.-- Figure S22. Residual check for the model fitted to Octopus vulgaris body size data.-- Figure S23. Residual check for the model fitted to Loligo vulgaris body size data.-- Figure S24. Residual check for the model fitted to Maja brachydactyla body size data.-- Figure S25. Residual check for the model fitted to Necora puber body size data.-- Table S3. Values for all explanatory variables used for predictions for each species' model (Fig. 4 and Fig. 5 in the main text and Fig. S26).-- Figure S26. Estimated (±95 C.I.) variation in body size at catch with depth for the 20 species.-- Figure S27. Plots of the DFA model fitted to the predicted body size at catch for each species in ICES division 8.c in the Galician coast (NE Atlantic).-- Figure S28. Plots of the DFA model fitted to the predicted body size at catch for each species in ICES division 9.a in the Galician coast (NE Atlantic).-- Figure S29. Relationship between (a) the rate of change in body size (% · year-1) and (b) the rate of change in relative abundance (% · year-1) with the average proportion of immature individuals caught (in number, ImC).-- Figure S30. Relationship between the rate of change in body size (% · year-1) with the time trend of body size skewness, Peer reviewed

Supporting Information includes Table S1 and Figures S1–S5 containing the NMR signals of flazin and HPLC and HPLC-MS chromatograms of flazin in the reactions and foods., Peer reviewed