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Este ítem incluye dos bases de datos en formato Excel con las descripciones analíticas de los restos arqueozoológicos y de artefactos líticos del yacimiento Lanashuaia.También contiene dibujos, fotos y listados en formato pdf de estos mismos restos., Bases de datos, álbumes de dibujos y fotografías de los objetos del yacimiento Lanashuaia., Agencias financiadoras: CSIC, CONICET, Ministerio de Educación y Ciencia (España) y Ministerio de Cultura (España)., Peer reviewed

Contiene documentos en pdf con fotografías, protocolos de excavación, topografías e inventario resultados de los trabajos realizados en el yacimiento Alashawaia en 1995., Documentos de las excavaciones arqueológicas realizadas en 1995 en el yacimiento Alashawaia., Agencias financiadoras: Unión Europea, CSIC, CONICET, Ministerio de Educación y Ciencia (España) y Ministerio de Cultura (España)., Peer reviewed

[EN] 279 .tif files: 278 color scanned prints of aerial photographs; 1 flight diagram showing the footprints of that aerial photographs. No specific software is needed to read the .tif files. [ES] 279 archivos en formato .tif : 278 corresponden a las fotografías aéreas escaneadas; 1 es el diagrama de vuelo de dichas fotografías que muestra su ubicación y las pasadas del vuelo. No se necesita ningún software específico para leer los archivos .tif. This dataset is covered by a Creative Commons Licence Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)., [EN] This dataset contains the scans of the contact prints of aerial photographs of the sections 2nd and 3rd of the first part of the Canal of Monegros, i.e. Monegros I or Monegros North, located in the Huesca province, Spain. The dataset also includes the diagram of the originating flight conducted by CETFA in 1972. The scanned contact prints are those used for soil prospection in 1975., [ES] Este conjunto de datos está formado por los escaneos de los contactos en papel de fotos aéreas del segundo y tercer tramo del Canal de Monegros en su parte norte, es decir Monegros I o Monegros Norte, en la provincial de Huesca, España. Además se incluye el diagrama de este vuelo efectuado por CETFA en 1972. Los contactos escaneados se usaron para prospectar los suelos en 1975., Proyecto PCI2018-09299 financiado por MCIN/AEI/10.13039/501100011033 y cofinanciado por la Unión Europea. Grant PCI2018-09299 funded by MCIN/AEI/10.13039/501100011033 and co-funded by the European Union, Peer reviewed

Experiment performed in the lab, following details described in the publication (http://hdl.handle.net/10261/240920 / https://doi.org/10.3390/insects12050448), Grants ICVV-CSIC: Ministry of Science and Innovation (PID2019-104112RB-I00) funded by MCIN/AEI/10.13039/501100011033. Support for researchers: 1) RCH is awarded by Ramon y Cajal contract award MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”: Grant RYC-2016-19939 from the Government of Spain 2) IVD is I.V.-D. funded by ADER I + D + i (2019) fellowship by the Rioja Agency of Economic Development (La Rioja, Spain) and by FPI-UR (2021) fellowship (Universidad de La Rioja, Spain). 4) MMGT is funded by the Program JAE-Intro CSIC call 2020 (JAEINT20_EX_0939). 5) R.B.-P. was supported by the pre-doctoral contracts CAR-2018 (Department of Economic Development and Innovation of the Government of La Rioja)., Peer reviewed

The monitoring of lizards and geckos’ community in Doñana was initiated in 2005 as part of the Monitoring Program of Natural Resources and Processes. One of the aims of this project was to obtain a temporal and continuous series of data of the presence and abundance of these species to detect changes and trends in their wild populations within the protected area. The records have been collected during spring and autumn every year between 2005-2021 by members of the monitoring team in sampling transects in different habitats (dunes and Mediterranean vegetation) when reptile activity is higher. Dataset includes species name, number of individuals, sex, life stage, behaviour, coordinates, weather description (sky conditions, temperature, rain, or wind intensity), time of the day and other remarks., The aim of this project is to provide information about the evolution of the conservation status of Doñana. To do that, it has been designed a monitoring program of the dynamic of natural processes and the distribution and abundance of species and communities. This monitoring is generating time series of data which is being used to analyzed long-term trends.

Files list: 1. Murciano-Granadina-1040F.ped: Genotypic information of 50,514 SNPs genotyped in 1,040 Murciano-Granadina female goats obtained with the Goat SNP50 BeadChip (Illumina Inc., San Diego, CA). 2. Murciano-Granadina-1040F.map: Genomic positional information of the SNPs genotyped in 1,040 Murciano-Granadina female goats. 3. Pheno_file.txt: Milk production records from 820 Murciano-Granadina goats. Milk composition traits are normalized to a lactation of 210 days. Relationship between files: “.map” and “.ped” files are complementary, “.map” contains the genomic position and name of the genotypes displayed in “.ped” file. Files can be opened and manipulated with PLINK software (https://www.cog-genomics.org/plink/)., Genotypic information from 1,040 female Murciano-Granadina goats and the phenotypic records for milk traits of 820 female Murciano-Granadina goats. The dataset includes a README file with the information about each file., This research was funded by the European Regional Development Fund (FEDER)/Ministerio de Ciencia e Innovación - Agencia Estatal de Investigación/Project Reference grant: PID2019-105805RB-I00 and by the CERCA Programme/Generalitat de Catalunya. We also acknowledge the support of the Spanish Ministerio de Ciencia e Innovación for the Center of Excellence Severo Ochoa 2020-2023 (CEX2019-000902-S) grant awarded to the Centre for Research in Agricultural Genomics (CRAG, Bellaterra, Spain). We also acknowledge the support of the CERCA programme of the Generalitat de Catalunya. Dailu Guan was funded by a PhD fellowship from the China Scholarship Council (CSC). Maria Luigi-Sierra was funded with a PhD fellowship Formación de Personal Investigador (BES-C-2017-079709) awarded by the Spanish Ministry of Economy and Competitivity., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000902-S), Peer reviewed

Download of the data available in the publisher platform., Transposon Insertion Polymorphisms (TIPs) are a significant source of genetic variation. Previous work (Castanera et al., 2021) has shown that TIPs can improve detection of causative loci on agronomic traits in rice. Here, we quantify the fraction of variance explained by Single Nucleotide Polymorphisms (SNPs) compared to TIPs, and we explore whether TIPs can improve prediction of phenotypes when compared to using only SNPs. We used eleven traits of agronomic relevance from by five different rice population groups (Aus, Indica, Aromatic, Japonica and Admixed), 738 varieties in total. We assess prediction by applying data split validation in two scenarios. In the within population scenario, we predicted performance of improved Indica varieties using the rest of Indica and additional samples. In the across population scenario, we predicted all Aromatic and Admixed samples using the rest of populations. In each scenario, Bayes C and a Bayesian reproducible kernel Hilbert space regression were compared. We find that TIPs can explain an important fraction of total genetic variance, often more than the fraction explained by SNPs, and that they also improve genomic prediction, especially in the across population prediction scenario, where TIPs outperformed SNPs in nine out of the eleven traits analyzed. In some phenotypes like leaf senescence or grain width, using TIPs increased predictive correlation by 40%. Our results evidence, for the first time, that TIPs genotyping can improve prediction on complex agronomic traits in rice, especially when samples to be predicted are less related to training samples., Dataset contains: Scripts: BayesC_PREDICTION.MODEL.R : An R script for genomic prediction within and across population analysis applying "BayesC"; RKHS_PREDICTION.MODEL.R : An R script for genomic prediction within and across population analysis applying "RKHS"; RKHS_GENETIC_VARIANCE_INFERENCE.R : An R script for genetic variance inference within and across population applying "RKHS". And Data: Accessions_Traits.csv : A csv file of the 11 traits and their corresponding phenotypic values for the 738 accessions. Data transformed as described in manuscript; snps. RData : SNPs matrix in R format; mitedtx_matrix.RData: Merged matrix of MITE and DTX TIPs in R format; rlxrix_matrix.RData: Merged matrix of RLX and RIX TIPs in R format; Additive_Matrix.RData : The three additive-relationship matrices for each marker (SNPs, MITE/DTX, RLX/RIX) to be used in RKHS method script., Peer reviewed

Data Files Description: NPC_XL_Identification_Inter_Crosslinked.csv: Inter-protein cross-links identified by pLink 2; NPC_XL_spectra.mgf: MS2 spectra data for the identified cross-links; NPC_XL_proteins.fasta : Protein sequences used for search., This repository contains chemical cross-linking mass spectrometry data of affinity-purified Yeast nuclear pore complexes., [Sample Processing] NPCs were immuno-purified from Mlp1 tagged S. cerevisiae strains (Kim et al., 2018). After native elution, 1.0 mM disuccinimidyl suberate (DSS) was added and the sample was incubated at 25ºC for 40 min with shaking (1,200 rpm). The reaction was quenched by adding a final concentration of 50 mM freshly prepared ammonium bicarbonate and incubating for 20 min with shaking (1,200 rpm) at 25ºC. The sample (50 µg) was then concentrated and denatured at 98ºC for 5 min in a solubilization buffer (10% solution of 1-dodecyl-3-methylimidazolium chloride (C12-mim-Cl) in 50 mM ammonium bicarbonate, pH 8.0, 100 mM DTT). After denaturation, the sample was centrifuged at 21,130 g for 10 min and the supernatant was transferred to a 100 kDa MWCO ultrafiltration unit (MRCF0R100, Microcon). The sample was quickly spun at 1,000 g for 2 min and washed twice with 50 mM ammonium bicarbonate. After alkylation (50 mM iodoacetamide), the cross-linked NPC in-filter was digested by trypsin and lysC O/N at 37ºC. After proteolysis, the sample was recovered by centrifugation and peptides were fractionated into 10-12 fractions by using a stage tip self-packed with basic C18 resins (Dr. Masch GmbH). Fractionated samples were pooled prior to LC/MS analysis. Desalted cross-link peptides were dissolved in the sample loading buffer (5% Methanol, 0.2% FA), separated with an automated nanoLC device (nLC1200, Thermo Fisher), and analyzed by an Orbitrap Q Exactive HFX (Pharma mode) mass spectrometer (Thermo Fisher) as previously described (Xiang et al., 2020; Xiang et al., 2021). Briefly, peptides were loaded onto an analytical column (C18, 1.6 μm particle size, 100 Å pore size, 75 μm × 25 cm; IonOpticks) and eluted using a 120-min liquid chromatography gradient. The flow rate was approximately 300 nl/min. The spray voltage was 1.7 kV. The QE HF-X instrument was operated in the data-dependent mode, where the top 10 most abundant ions (mass range 380 – 2,000, charge state 4 - 8) were fragmented by high-energy collisional dissociation (HCD). The target resolution was 120,000 for MS and 15,000 for tandem MS (MS/MS) analyses. The quadrupole isolation window was 1.8 Th; the maximum injection time for MS/MS was set at 200 ms., [Data processing] The raw data were searched with pLink2 (Chen et al., 2019b). An initial MS1 search window of 5 Da was allowed to cover all isotopic peaks of the cross-linked peptides. The data were automatically filtered using a mass accuracy of MS1 ≤ 10 ppm (parts per million) and MS2 ≤ 20 ppm of the theoretical monoisotopic (A0) and other isotopic masses (A+1, A+2, A+3, and A+4) as specified in the software. Other search parameters included cysteine carbamidomethyl as a fixed modification and methionine oxidation as a variable modification. A maximum of two trypsin missed-cleavage sites was allowed. The initial search results were obtained using a default 5% false discovery rate (FDR) expected by the target-decoy search strategy. Spectra were manually verified to improve data quality (Kim et al., 2018; Shi et al., 2014). Cross-linking data were analyzed and plotted with CX-Circos (http://cx-circos.net)., No

Zip file including raw trait, environmental, and community data, code for conducting analyses, and a spreadsheet summarizing model selection., Peer reviewed

These data are part of a publication on avian seed dispersal and climate change accepted by Global Ecology and Biogeograpy. -- The file includes 3 tables. -- Methods: S1 Plant species: Minimum and maximum elevation (m a.s.l.) were compiled from Brako, L. & Zarucchi, J.L. (1993). Catalogue of the flowering plants and Gymnosperms of Peru. Catálogo de las Angiospermas y Gimnospermas del Perú. Monogr. Syst. Bot. from Missouri Bot. Gard. 45; Growth form has been defined during field surveys; Fruit width (mm) was measured on fruits collected during the field surveys on 20 fruits per plant species; given are species mean values; Plant height (m) was measured during the field surveys on all individuals in the plots; given are species' mean values; Source indicates if trait values are species mean values based on data from our own field surveys, species mean values based on data from Ecuador or genus mean values. -- S2 Bird species: Minimum and maximum elevation (m a.s.l.) were compiled from Merkord, C.L. (2010). Seasonality and elevational migration in an Andean bird community. University of Missouri-Columbia; Walker, B., Stotz, D.F., Pequeño, T. & Fitzpatrick, J.W. (2006). Birds of the Manu Biosphere Reserve. Fieldiana Zool., 23–49 and complemented by Dehling, D.M., Sevillano, C.S. & Morales, L.V. (2013). Upper and lower elevational extremes of Andean birds from south-east Peru. Boletín Inf., 8, 32–38; Body mass (g) was compiled from Dunning, J.B. (2007). CRC Handbook of Avian Body Masses. CRC Press, Boca Raton; Bill width (mm) was measured on museum specimens (at least two adult males and females) according to measurement protocols from Eck, S., Töpfer, T., Fiebig, J., Heynen, I., Fiedler, W., Nicolai, B., et al. (2011). Measuring birds. Christ Media Natur, Minden; Kipp's index equals the Kipp's distance (mm) divided by the wing length (mm), which were both measured on museum specimens (at least two adult males and females) according to measurement protocols from Eck, S., Töpfer, T., Fiebig, J., Heynen, I., Fiedler, W., Nicolai, B., et al. (2011). Measuring birds. Christ Media Natur, Minden. -- S3 Projections: LDD (m) was simulated based on three trait-matching parameter values representing a low, an intermediate and a high degree of trait matching (s = 0.5, 1.5, 5.0, respectively), and estimated as the 95th and the 99th percentile of the simulated 10000 dispersal distances per plant species (95% and 99% LDD ability, respectively); given are mean, standard deviation and coefficient of variation across 10 independent iterations of the simulations; MAX (m) was simulated based on three trait-matching parameter values representing a low, an intermediate and a high degree of trait matching (s = 0.5, 1.5, 5.0, respectively), and was estimated as the maximum of the simulated 10000 dispersal distances per plant species; given are the mean and standard deviation across 10 independent iterations of the simulations; Vertical temperature shift (m) by 2070 was projected according to three future greenhouse gas emission scenarios (RCP 2.6, 4.5 and 8.5) and five general circulation models (GCMs; cc = CCSM4, he = HadGEM2-ES, mc = MIROC 5, mg = MRI-CGCM and no = NorESM1-M). Data on current and projected mean annual temperature along the Manú gradient was derived from Worldclim (Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol., 25, 1965–1978). Data on tropospheric lapse rate for our study regions was compiled from Mokhov, I.I. & Akperov, M.G. (2006). Tropospheric lapse rate and its relation to surface temperature from reanalysis data. Izv. Atmos. Ocean. Phys., 42, 430–438. Given are mean and standard deviation of the projected vertical distances across species' elevational range as well as mean and standard deviation across general circulation models; Required horizontal dispersal distance (m) considering an average slope of 11.45° is computed as vertical temperature shift (m) divided by the sine of the mean slope (°). This approximates the distance by which a plant species would have to disperse horizontally to shift its range upslope by a given vertical distance considering a mean slope of 11.45 °; Number of required LDD events by 2070 equals the projected number of LDD events plant species' would require to fully track projected vertical temperature shifts until 2070. This was computed as LDD ability (m)/ Required horizontal dispersal distance (m) for each plant species., [Aim] Climate change causes species’ range shifts globally. Terrestrial plant species often lag behind temperature shifts, and it is unclear to what extent animal-dispersed plants can track climate change. Here, we estimate the ability of bird-dispersed plant species to track future temperature change on a tropical mountain., [Location] Tropical elevational gradient (500–3500 m a.s.l.) in the Manú biosphere reserve, Peru, [Time period] 1960–1990 to 2061–2080, [Taxa] Fleshy-fruited plants, avian frugivores., [Methods] Using simulations based on the functional traits of avian frugivores and fruiting plants, we quantified the number of long-distance dispersal (LDD) events that woody plant species would require to track projected temperature shifts on a tropical mountain by the year 2070 under different greenhouse gas emission scenarios (RCP 2.6, 4.5 and 8.5). We applied this approach to 343 bird-dispersed woody plant species., [Results] Our simulations reveal that bird-dispersed plants differ in their climate-tracking ability, with large-fruited and canopy plants exhibiting a higher climate-tracking ability. Our simulations also suggest that even under scenarios of strong and intermediate mitigation of greenhouse gas emissions (RCP 2.6 and 4.5), sufficient upslope dispersal would require several LDD events by 2070, which is unlikely for the majority of woody plant species. Furthermore, the ability of plant species to track future temperature changes increased in simulations with a low degree of trait matching between plants and birds, suggesting that plants in generalised seed-dispersal systems may be more resilient to climate change., [Main conclusion] Our study illustrates how plant and animal functional traits can inform predictive models of species dispersal and range shifts under climate change and suggests that the biodiversity of tropical mountain ecosystems is highly vulnerable to future warming. The increasing availability of functional trait data for plants and animals globally will allow parameterisation of similar models for many other seed-dispersal systems., S1_Plant_traits_elevation, S2_Bird_traits_elevation, S3_Projections, Peer reviewed