BUSCADOR RECOLECTA

Dataset S1: USDA and NIH online freely accessible information about TBD; Dataset S2: CDC online information on TBD surveillance; Dataset S3: Tick-borne pathogens identified in ticks from Central America; Dataset S4: Distribution of ticks and tick-borne pathogens worldwide., Peer reviewed

Supplementary Material 1: Supplementary Table S1. Data from sampled tortoises, their morphologic characteristics and identification of PCR-positive results. Supplementary Table S2. Tick infestation in Testudo graeca populations through their distribution range: infestation prevalence (%), infestation intensity (tick/infected tortoise) and host density (tortoise/ha)., Peer reviewed

Experimental chronogram: Figure S1: Chronogram of the glutathione manipulation. BSO = buthionine sulfoximine. From (Romero Haro and Alonso-Alvarez 2015). DNA extraction protocol. Supplementary statistical analyses. Supplementary Results: Table S1; Table S2; Table S3; Table S4; Table S5; Figure S2; Figure S3; Figure S4; Figure S5; Figure S6; Figure S7; Figure S8. Interaction between early glutathione levels and telomere length on longevity, Peer reviewed

Comprises 3 sheets: 1. Growth and grain yield. 2. Leaf nutrient content. 3. Grain quality. – All data refers to the same experimental plots. – Description of methods used for collection/generation of data: (a) growth and grain yield: Plant height was measured as the length from the base of the stem to the tip of the top leaf. (b) chemical analyses: For mineral elements analysis, samples were calcined at 450 °C for 8 h and the ashes dissolved in HCl:HNO3:H2O (1:1:8). The concentrations of P, K, Ca, Mg, S, Mn, Fe, Cu and Zn were determined by inductively coupled plasma atomic emission spectroscopy (ICP-OES, Varian 720-ES). Protein was determined as nitrogen using a C/H/N analyzer (LECO CN628). The fiber content was determined by analysing neutral detergent fiber (NDF), acid detergent fiber (ADF) and lignin using the filter bag technique with an automated fiber analyzer (Ankom A2000). Trolox equivalent antioxidant capacity (TEAC) was determined in lyophilized plant material using the oxygen radical absorbance capacity (ORAC) method described (Gillespie et al., 2007) with some modifications (Mellado-Ortega et al., 2017) Grain protein fractions, gliadins and glutenins, were quantified by HPLC as described by Marín-Sanz et al. (2020). Soluble sugars were quantified by HPLC according to the standard Association of Official Analytical Chemists method 2000.17 (AOAC, 2009). The starch content of whole flour was determined according to standard International Association for Cereal Chemistry method no. 123/1 (ICC, 1994). References are listed in the publication, In this study, we tested whether fungal strains in symbiotic interaction with roots of Celtica gigantea, a wild grass adapted to nutrient-poor soils in semiarid habitats, could improve the field performance of the agricultural cereal tritordeum (Triticum durum x Hordeum chilense). Seedlings of tritordeum were inoculated with 12 different fungal strains isolated from roots of Celtica gigantea. The inoculated seedlings were transplanted to field plots at two locations belonging to different climatic zones in terms of mean temperatures and precipitation in the Iberian Peninsula (Salamanca and Córdoba). Both experiments were conducted under rainfed conditions. Plant height, measured as the length from the base of the stem to the tip of the top leaf, and tiller number were recorded when plants were at a growth stage equivalent to stage 5 on the Feekes scale for wheat. When plants had five leaves fully expanded, a sample was collected for nutrient analysis. Plants were harvested at maturity and the number of heads per plant, grain weight, and 1000 grain weight were determined. Several grain quality parameters were analyzed, RTC2014-3112-2 funded by AEI and FEDER, grant PID2019-109133RB-I00 funded by MCIN/AEI/10.13039/50110001103, Project CLU2019-05-IRNASA/CSIC Unit of Excellence funded by the Junta de Castilla y León and co-financed by EU (ERDF Europe drives our growth), No

Level-3 daily merged Copernicus-GlobColour multi-sensor Remote Sensing Reflectance (Rrs(λ)) from the Copernicus Marine Environmental Monitoring Service (CMEMS) is used as data source. The aCDOM(443) was estimated using the gsmA parametrizations for the southern Beaufort Sea (Matsuoka et al., 2013) with some modifications; while DOC was retrieved using an empirical aCDOM(443)-DOC relationship developed by Juhls et al. (2022), valid across the fluvial-marine transition zone of the Mackenzie River–Beaufort Sea region, Level-4 daily maps of aCDOM(443) and DOC for the Mackenzie River-Beaufort Sea region (122-142ºW and 68-73ºN) are distributed in the regular latitude–longitude grid at a spatial resolution of 4 km. The data is available from 1st January 2002 to 31st October 2023. Additionally, 8-day means, and monthly mean data are also provided. The dataset consists of four variables: (i) Chromophoric Dissolved Organic Matter at 443 nm (aCDOM(443) [m-1]) (ii) Dissolved Organic Carbon (DOC [µM]) (iii) water type mask (coastal/oceanic) (iv) model relative error for Rrs(443) (∆Rrs(443) [%]) (v) aCDOM(443) uncertainty (σaCDOM [m-1]) (vi) DOC uncertainty (σDOC [µM]), YYYYMMDD_aCDOM443_DOC_l4_4km_P1D.nc (This dataset contains daily Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region) YYYYMMDD_YYYYMMDD_aCDOM443_DOC_l4_4km_P8D.nc (This dataset contains daily Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region) YYYYMMDD_YYYYMMDD_aCDOM443_DOC_l4_4km_P1M.nc (This dataset contains monthly Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region), In the regime-shifting Arctic, organic carbon export from river watersheds is expected to increase due to changes in hydrological regimes and permafrost thawing. Given the impact these changes have on the biogeochemical cycles of coastal and shelf areas, robust monitoring of major Arctic rivers is needed. During ice-free season, ocean color remote sensing has shown to be an effective monitoring tool for remote, under-sampled areas with limited access such as the Beaufort Sea region. It offers synoptic spatio-temporal coverage, filling in the gaps among the scarce in situ data and improving our knowledge of land-to-ocean transport pathways and coastal ocean dynamics near riverine zones. Remote sensing of Chromophoric Dissolved Organic Matter (CDOM) and Dissolved Organic Carbon (DOC) has proven to be a valuable approach for assessing variations in terrestrial carbon export. However, seasonal fluctuations and diverse vegetation and soil conditions of each river watershed make it difficult to establish a single retrieval method for the entire Arctic. This complexity has led to a development of several regional algorithms, yet accessible long-term series remain a challenge. We present the first long-term satellite-derived dataset quantifying the absorption coefficient of CDOM at 443 nm and DOC concentrations in the Mackenzie River–Beaufort Sea region (122–142ºW and 68–73ºN) from 1st January 1998 to 31st October 2023. We employed a modified version of the GIOP (Generalized Inherent Optical Properties) algorithm to retrieve CDOM(443) for the southern Beaufort Sea; DOC was then derived using a region-specific relationship between aCDOM(443) and DOC. The product has been validated using in situ observations from several field campaigns conducted in the area. We provide a consistent dataset that can be used to assess DOM spatial and temporal variability, trends, and export to the coastal seas, This work has been carried out as part of the ARCTIC-MON project (Advances in monitoring sea ice thickness and snow depth, ocean dynamics, and freshwater content in the Arctic using remote sensing data), funded through the Consejo Superior de Investigaciones Científicas (CSIC) (grant no. PID2021-125324OB-I00), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Level-4 daily maps of aCDOM(443) and DOC for the Mackenzie River-Beaufort Sea region (122-142ºW and 68-73ºN) are distributed in the regular latitude–longitude grid at a spatial resolution of 4 km. The data is available from 1st January 2002 to 31st October 2023. Additionally, 8-day means, and monthly mean data are also provided. The dataset consists of four variables: (i) Chromophoric Dissolved Organic Matter at 443 nm (aCDOM(443) [m-1]) (ii) Dissolved Organic Carbon (DOC [µM]) (iii) water type mask (coastal/oceanic) (iv) model relative error for Rrs(443) (∆Rrs(443) [%]) (v) aCDOM(443) uncertainty (σaCDOM [m-1]) (vi) DOC uncertainty (σDOC [µM]), Peer reviewed

S1 Appendix. PRISMA figure depicting the flow of documents obtained for each of the steps in the literature review in the database SCOPUS., S1 Data. Excel spreadsheet including, in separate sheets, all numerical values used for Figs 1, 2, 3, 4 and S1., S1 Fig. Regional distribution of autochthonous Leishmania infantum infections in humans and/or animals in European countries reported in the scientific literature and by the ministries of health of some countries, between 2009 and 2020., S1 Table. Number and cumulative incidence per 100,000 population of cutaneous and visceral leishmaniasis in European countries between 2005 and 2020 as reported in the WHO-GHOD., S2 Table. Geographical references of reported autochthonous symptomatic and asymptomatic infections by Leishmania infantum in animals and/or humans in European countries, between 2009 and 2020., Peer reviewed

Here you can find the SPSS data used for the manuscript titled "The role of implicit theories about climate change malleability in the prediction of pro-environmental behavioral intentions" accepted on 2022, June, in The Environment, Development and Sustainability. In this research, we analyze how the sense of responsibility toward climate change and implicit theories about climate change (ITCC) interact to condition individual pro-environmental intention in a pretest–posttest experiment., Peer reviewed

Monitoring compliance with environmental laws is essential to overcoming possible implementation shortfalls jeopardizing their effectiveness. Besides improving our ecological understanding of wildlife, remote tracking technologies also allow us to take advantage of such ecological knowledge to use wildlife as sentinels of compliance with law. We illustrate this sentinel potential of wildlife using GPS-tracking of large scavengers with complementary functional traits (i.e., 21 griffon vultures and 13 wolves) to assess compliance with EU sanitary regulations allowing livestock carcass disposal in the field. Wildlife sentinels allowed the systematic evaluation of 489 livestock carcasses left in the field, which revealed an important mismatch between on-paper and in-reality implementation of these regulations. While <45 % of the carcasses were placed in authorized areas, compliance with all the criteria required by the regulations on livestock carcass disposal (e.g., from carcass characteristics such as species, age, or production system to its location far away from water, buildings, or roads) ranged from 0 to 4.2%, with no major differences between regions with uneven implementation. Major gaps in compliance pointed towards insufficient and over-bureaucratized designation of Scavenger Feeding Zones (SFZs), where livestock carcass disposal is authorized. The indiscriminate nature of distance criteria from carcasses to watercourses, buildings, and infrastructure further affected compliance. Synthesis and applications: GPS-tagged scavengers allow the on-ground monitoring of carcasses, the addressing of potential risks for wildlife, livestock, and human health, the quantitative assessment of compliance with the law and would improve estimates of carcass availability, substantially contributing to more effective legislation enforcement. Our results show the huge potential of GPS-tagged wildlife as sentinels for monitoring compliance to enhance the environmental rule of law., Ministry of Economy, Industry and Competitiveness. Fundación BBVA. Gobierno del Principado de Asturias. Ministerio de Ciencia e Innovación. Fundación Biodiversidad. Ministério do Ambiente e da Ação Climática, Peer reviewed

Peer reviewed

Tabla Suplementaria 1. Detalles de las organizaciones contactadas y la información proporcionada., Peer reviewed