Resultados de investigación

These are the data to produce the results and figures found in the paper "Impacts of canopy disturbances by tree logging on soil biota increase with organism size", Peer reviewed

1) Climate_2022_2024.xlsx Five columns: Date : date, in format %d-%m%-%Y TempAvg.C : average daily temperature [°C] Precip.mm : daily precipitation sum [mm] PET.mm : daily Potential Evapotranspiration (Penman-Monteith method) [mm] CWB.mm : Climatic Water Balance [mm] = Precip.mm - PET.mm, 2) Raw Data Dendrometers (Basal Area).xlsx Data sheet with tree sizes recorded by each date (every column), from which the cumulative basal area growth curves were derived, and finally, the phenological events (48 columns). TREE : A unique tree number SP : Species of each tree PLOT: A unique sample plot number Columns 18.05.2022 - 28.08.2024 (45 columns) : basal area of each tree [mm^2], attained by a date = column name., 3) Phenol. Events Reference.xlsx Data sheet containing phenological events identified a vista (DOY - day of year), used as reference in the article (6 columns,). TREE : A unique tree number YEAR : Year during which the phenological events were recognized Growth_onset : Spring onset of growth Summer_cessation : Summer cessation of growth Autumn_onset : Autumn onset of growth Year_cessation : Cessation of the yearly growth., 4) 2STA_v.02_R R script, with the body of the function implementing 2STA method, as described in the article., European Commission Skill-For.Action - Skill-For.Action956355 Agencia Estatal de Investigación BEGINPINEPID2022-136906OB-C21, Peer reviewed

Additional file 2. Macroscopic lesions, histopathology and parasite DNA detection in lymph nodes draining the small intestine., Ministerio de Ciencia e Innovación; Comunidad de Madrid; H2020 European Institute of Innovation and Technology, Peer reviewed

Additional file 4. βAPP immunolabelling in foetal brains. For each foetal brain, 4 different areas were studied., Ministerio de Ciencia e Innovación; Comunidad de Madrid; H2020 European Institute of Innovation and Technology, Peer reviewed

Additional file 5. βAPP staining of foetal brains. Representative images of the two different labelling patterns observed: i) staining of areas of variable size in the white matter (A, foetus from sheep 3.1) and ii) sparse areas where the cytoplasm of different cell types in foetal brains from infected sheep was labelled (B, D and F, corresponding to foetuses from sheep 3.4, 1.2 and 1.1, respectively), as opposed to those from the uninfected controls (C, E and G, corresponding to foetuses from sheep 5.2, 4.3 and 5.3, respectively). Neurons (B–C), microglia (D–E), and Purkinje cells in the cerebellum (F–G). Magnification: 40x (A) and 400x (B–G)., Ministerio de Ciencia e Innovación; Comunidad de Madrid; H2020 European Institute of Innovation and Technology, Peer reviewed

This dataset is a unique, highly detailed, spatially-explicit database of trophic interactions of brown bear across Europe and Türkiye. It contains six files: Supplementary Tables 1-4 (Trophic Database); Supplementary Table 5 which shows a list of species in the diet; Supplementary Table 27, summarizing the relative energy contribution of each food item (rEDEC) for each species by subpopulation., Peer reviewed

We used 10 different sources of historical data for brown bear, below we report the area of study, the map/figure/data within the publication and the century: for Spain we used data obtained from “Anotaciones al “Libro de la Montería” del Rey Alfonso XI. “(Valverde 2009) (XIV Century), for North West of Spain (Galicia) the figure 1 from “A conservación do oso pardo en Galicia” (Naves & Fernández-Gil 2017) (XVIII Century), for North of Spain (Cantabrian Mountains) the figure 6.16 from “Bears. Status Survey and Conservation Action Plan” (Servheen et al. 1999) (XIX Century), for Portugal we used figure 1 from “Research trends and geographical distribution of mammalian carnivores in Portugal” (SW Europe) (Bencatel et al. 2018) (XVII Century), for Portugal we also used the figure 1 from “Historical presence of Brown bear in Portugal and evidence of its relation with human communities” (Álvares & Domingues 2010) (XVI-XVIII Centuries), for France we used the data from figure “Répartition de lÓurs brun en France” from the “Encyclopédie des carnivores de France”(Parde & Camarra 1992) (XV-XVI Centuries), figure 1 from “A habitat model for brown bear conservation and land use planning in the central Apennines” (Posillico et al. 2004) (XVI-XVIII Centuries), for the former Yugoslavian countries from figure 6.19 from “Bears. Status Survey and Conservation Action Plan” (Servheen et al. 1999) (XIX Century), for Greece from figure 6.8 from “Bears. Status Survey and Conservation Action Plan” (Servheen et al. 1999) (II Century), and the historical distribution for brown bear for Eurasia from the IUCN Red List (McLellan et al. 2017) (XVI-XX Centuries)., The Range Database contains data, at a low spatial resolution (50 x 50 km), on the Eurasian historical distribution of brown bear, areas of current presence and areas which were occupied in the past but where the species has been extirpated., Peer reviewed

25 files, Alignment of orthologous chromosomes of the two European hake chromosome-level genomes using Minimap2 and pafr package from R, Peer reviewed

[Code availability] All the scripts used for the processing and analyses of the sequencing data are openly available to ensure full reproducity of the workflow. This includes scripts for the quality control and filtering of Illumina (MiSeq) reads, processing of ASV tables for both bacterial and fungal datasets, and formatting of data into DarwinCore Archive structure for integration into GBIF. The full workflow is documented and hosted in a GitHub repository (https://anitalasa.github.io/Psylvestris_DataPaper/), and permanently archived in Zenodo44. By providing a fully documented and reproducible workflow, this dataset complies with FAIR principles45 and facilitates its application in microbial ecology, forest health monitoring, and biodiversity research. Furthermore, all the repositories are under license CC BY., Forest decline is a worldwide phenomenon affecting many species such as Pinus sylvestris. Although it is driven by multiple stressors, the role of tree associated microorganisms remains still unclear. To reduce this knowledge gap we obtained amplicon sequences of the microbiota inhabiting the rhizosphere soil and root endosphere (bacterial 16S rRNA and fungal ITS2) of decline-affected and asymptomatic P. sylvestris trees in spring and summer. The dataset comprised a total of 384 samples from three mountainous areas which yielded an average of 59,592.3 ± 7,371 and 56,894.3 ± 12,983.5 (spring and summer) bacterial and 74,827.9 ± 12,095.4 and 85,363.9 ± 14,199.3 (spring and summer) fungal raw reads, resulting in 23,982.4 ± 11,312.4 (spring) and 17,921.8 ± 10,802.7 (summer) bacterial and 50,571.1 ± 10,499.5 (spring) and 49,509.4 ± 12,673.8 (summer) fungal quality-filtered sequences. These data and the corresponding metadata could be used to identify pine decline bioindicators, to develop novel diagnosis tools of specific microorganisms and could serve as reference against which to compare other microbial communities., This work was supported by the MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-13, POPE 2014-2020]. AVL is hired under the Generation D initiative, promoted by Red.es, an organisation attached to the Ministry for Digital Transformation and the Civil Service, for the attraction and retention of talent through grants and training contracts, financed by the Recovery, Transformation and Resilience Plan through the European Union’s Next Generation funds. AJPL is currently funded by MCIN/AEI/10.13039/ 501100011033 and by “European Union NextGenerationEU/PRTR” with a “Juan de la Cierva” fellowship programme (Grant JDC2022- 050056-I). We also thank to Katia Cezón (Spanish GBIF node-CSIC) for technical support in the data integration in GBIF., Peer reviewed

Agriculture needs to mitigate its impacts and adapt to new environmental conditions. To this end, communicating climate change to farmers is essential but remains a challenge, since many stakeholders (e.g. public administration, sectoral stakeholders, environmentalists) engage with farmers, conveying diverse messages about climate change and the role of agriculture. Here we aim to analyse farmers’ perceptions of climate change and how these relate to their trust in different stakeholders. We conducted a survey with 167 livestock farmers across Spain, gathering data about their perceptions on climate change severity and origin, and to what extent its importance has been exaggerated. We also analysed farmers’ trust in different information sources, including farmers associations (i.e. breed associations, farmer organisations and cooperatives), agricultural organisations, technical publications, veterinarians, agricultural firms, government agencies, scientists, environmentalists, animal activists, and the media. Our results show that farmers believe climate change exists but a high proportion are sceptical about its origin and severity. Farmers’ trust in information sources influences their perception of climate change. Farmers who trust public institutions, environmentalists, animal activists, and the media are more likely to view climate change as human-driven and perceive its impacts as severe, rejecting claims of exaggeration. In contrast, those who trust veterinarians, cooperatives, agricultural firms, and farmer organisations tend to see climate change as a hybrid human-natural process and believe its impacts are overstated. The results highlight the need to improve the science-policy-farmers dialogue to make farmers more aware of the potential consequences of climate change on farming and trigger adaptation. Many farmers (∼60%) are sceptical about climate change origin Farmers trust sectoral stakeholders and scientists, and mistrust public administration, the media, and environmental activists Farmers mistrust in public administration, the media, and environmental activists is linked to scepticism about climate change Many farmers (∼60%) are sceptical about climate change origin Farmers trust sectoral stakeholders and scientists, and mistrust public administration, the media, and environmental activists Farmers mistrust in public administration, the media, and environmental activists is linked to scepticism about climate change, Peer reviewed