BUSCADOR RECOLECTA

Urbanization affects ecosystems by reducing biodiversity and displacing species from native habitats. While some suffer, others, like urban wildlife, adapt through innovative feeding and behaviours that improve their fitness in human-altered settings. Despite research on wildlife in urban areas, the development of foraging behaviour in urban species is still understudied. Here, we examined the age-related differences in the foraging behaviour of yellow-legged gulls (Larus michahellis) in Barcelona (Spain), a densely populated coastal urban ecosystem. Using biologging technologies and trophic markers, we compared the foraging strategies, habitat use, human interactions, and trophic niches of juvenile, immature, and adult yellow-legged gulls over three breeding seasons. The results showed age-related differences in spatial distribution and foraging behaviour in this opportunistic species. Juveniles and immatures mainly foraged in ports and at sea, while adults favoured urban habitats. These patterns likely stem from reproductive constraints in adults and lower foraging efficiency in younger birds. Adults’ primary use of urban habitats also explains their higher trophic niche. Furthermore, fishing activity significantly influenced yellow-legged gull foraging across age groups, with strong associations between gulls and fishing vessels. By studying how age and life stage influence habitat use and behaviour, this research provides insights to guide targeted management strategies for this species, This study is part of the projects BCNGulls, Aliats and Intramural CSIC Project “Opportunistic gulls as sentinel species to monitor urban marine ecosystems”. VMV was supported by a Juan de la Cierva fellowship from the Spanish Government (JDC2022-049638-I). This work acknowledges the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI), Age: age group (juveniles, immatures or adults); Latitude: latitude coordinates in degrees; Longitude: longitude coordinates in degrees, Peer reviewed

[Description of methods used for collection/generation of data] Costovertebral material belonging to the fossil specimen and the reference H. sapiens individuals was surface scanned., [Methods for processing the data] First, we calculated the vector of change between each mean H. sapiens metamer as the increment of 3D coordinates between each costovertebral level and the subsequent one. This vector was added or subtracted to the best-preserved costovertebral levels of Shanidar 3, depending on whether we wanted to estimate missing elements below or above the level, respectively. The obtained coordinates were morphed, and the final meshes were obtained. Eventually, the 3D model of Shanidar 3’s ribcage was reconstructed using these meshes., Reconstructed ribcage belonging to Shanidar 3, a Levantine Neanderthal specimen dated circa 45-60 ky BP. Final 3D models were statistically obtained by original fossil material through a statistical study of costovertebral metameric variation in H. sapiens., This reconstruction has been possible thanks to grant PRE2021-097584 to J.M.L.-R. and grant PID2020-115854GB-I00 to M.B., both funded by MCIN/AEI/10.13039/501100011033 of the Spanish Ministry of Science and Innovation and the European Union., Peer reviewed

The Appendices E to H with Tables E.1 and E.2, F.1 and F.2, G.1 to G.5, and Figures H.1 to H.19., Peer reviewed

Under a Creative Commons license BY-NC 4.0, https://creativecommons.org/licenses/by-nc/4.0/, Elemental analysis standards deviations: Table S1. Standard deviations of C, H, O, Co, Ni and Mo for each sample. List of identified compounds: Table S2. Identified compounds in liquid and gas products by gas chromatography and their respective standard deviations. XRD pattern of Co-Mo/Al2O3: In Fig. S1, peaks correlated to the support γ-Al2O3 (2θ = 39.5° [111], 45.9° [200], 25.3° and 66.9° [220]) and MoO3 (2θ = 46.2° [220] and 67.5° [400]) were found overlapped [22]. Moreover, peaks of MoO2 (2θ = 37.1°) and hydrated Co2Mo3O8 (2θ = 39.8° [204]) were also observed. TEM: Fig. S2. TEM images of MoO2 inside the tube in Ni-Mo/CNTox. STEM: Fig.S3. STEM of Co-Mo/CNTox (a) and Ni-Mo/CNTox (b, c and d). Isotherms: Fig. S4. N2 adsorption-desorption isotherms of the catalysts and supports., This work was supported by national funds through FCT/MCTES (PIDDAC): LSRE-LCM, UIDB/50020/2020 (DOI: 10.54499/UIDB/50020/2020) and UIDP/50020/2020 (DOI: 10.54499/UIDP/50020/2020); and ALiCE, LA/P/0045/2020 (DOI: 10.54499/LA/P/0045/2020). The authors are grateful for the financial support from the I + D + i project PID2020-115053RB-I00, funded by Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033). The authors also thank Gobierno de Aragón (DGA) for the financial support to Grupo de Conversión de Combustibles (T06_23). K. K. Ferreira acknowledges her Ph.D. scholarship (2022.12949.BD) from FCT. C.D.S is grateful for the Juan de la Cierva (JdC) fellowship (Grant Number: JDC2022-048765-I) funded by MICIU/AEI/10.13039/501100011033 and by FSE+., Peer reviewed

[Description of methods used for collection/generation of data] Data was collected using the DJI Matrice 300 RTK quadcopter equipped with the DJI Zenmuse L2 sensor. This sensor integrates a LiDAR system capable of detecting up to 5 returns within a range of 2 to 450 meters (with 50% reflectivity and 0 klx), as well as a 20 MP RGB mapping camera featuring a 4/3" CMOS sensor. This data was collected at an altitude of 80 meters and reprojected to the ETRS89 / UTM Zone 30N reference system, with the geoid configured to the Alicante height., [Methods for processing the data] Data was processed using DJI Terra v.4.3.0 software. During processing, the point cloud was generated with a resolution of 20 cm and an effective range of 40 to 200 meters. The DEM was generated at a scale of 1:500. Additionally, the flights were not conducted under RTK conditions due to connection difficulties, so the positioning information was corrected using the central point data from the base station, derived from the EMLID REACH 2 antenna., This repository contains the topographic products generated from Unmanned Aerial Vehicle (UAV) flights equipped with an LiDAR sensor, conducted over the Poyo´s Gully on November 10, 2024, after 12 days of the Cut-Off Low that occurred in Valencia on October 29, 2024. This repository includes a LiDAR point cloud and a centimeter-resolution Digital Elevation Model (DEM), covering the gully course from El Boni area at the Albufera (Latitude: 39.384528º; Longitude: -0.359503°) up to Torrent village (Latitude: 39.442071°; Longitude: -0.455153°). The equipment used were a DJI Zenmuse L2 sensor mounted on the DJI Matrice 300 RTK multirotor UAV, supported by positioning information provided by the EMLID Reach 2 antenna used as a base station. This information is useful for quickly assessing damage of infrastructures or the amount of sediment accumulated along the couser of the Gully, among others. The data will help technicians and managers in assisting in decision-making for restoration and prevention., Grupo de Asesoramiento en Desastres y Emergencias (GADE-CSIC)., 3 files: F20241110_BarrancoPoyo_DEM_L2_ICMAN-CSIC.tif (DEM model); F20241110_BarrancoPoyo_PointCloud_L2_ICMAN (Point Cloud model); F20241110_BarrancoPoyo_NotaProcesamiento_L2_ICMAN-CSIC.pdf (Processing note pdf), Peer reviewed

Esta publicación es parte del proyecto de I+D+i Escritores latinoamericanos en los países socialistas europeos durante la Guerra Fría (PID2020-113994GB-I00), financiado por MCIN/ AEI/10.13039/501100011033/., Recopilación hemerográfica de textos relativos a la literatura latinoamericana. Para más detalles, véase el fichero Readme adjunto. Material procedente de la biblioteca de la Universidad del Oeste de Timisoara: https://bcut.ro/, Collection of periodicals on Latin American literature. For more details, see the attached Readme file. Material from the Library of the West University of Timisoara: https://bcut.ro/, Esta publicación es parte del proyecto de I+D+i Escritores latinoamericanos en los países socialistas europeos durante la Guerra Fría (PID2020-113994GB-I00), financiado por MCIN/ AEI/10.13039/501100011033/., No

Supplementary Table S1: composition of the experimental control (C) and cocoa–carob-rich (CC) diets (g/kg dry weight). Supplementary Table S2: body weight data, food intake, and food efficiency of rats fed with standard (ZL and ZDF) and cocoa–carob-rich (ZDF-CC) diets, and treated with metformin and fed with standard (ZDF-M) and cocoa–carob-rich diets (ZDF-CC + M)., Peer reviewed

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Figure S1. Flow diagram of the participants included in the GREENCOF study, based on the CONSORT 2010 (Consolidated Standards of Reporting Randomized Crossover Trials) guidelines. Figure S2. Changes in body fat percentage segmented by sex (women data are colored in red, while men in blue) and by type of coffee. Each dot represents an individual participant’s value. Figure S3. Changes in visceral fat area (in cm2) segmented by sex (women data are colored in red, while men in blue) and by type of coffee. Each dot represents an individual participant’s value. Figure S4. Changes in skeletal muscle mass percentage segmented by sex (women data are colored in red, while men in blue) and by type of coffee. Each dot represents an individual participant’s value. Table S1. CONSORT checklist of information to include when reporting randomized crossover trials., Peer reviewed

[Description of methods used for collection/generation of data] Handheld camera (APEMAN A60), [Methods for processing the data] The images are ortho-rectified using a vertical plane through calculation of a homography matrix, supported with the RANSAC algorithm (Vincent and Laganiére, 2001). Vincent, E. and R. Laganiére. 2001. Detecting planar homographies in an image pair. In Image and Signal Processing and Analysis ISPA 2001. Proceedings of the 2nd International Symposium on, pp. 182–187. IEEE., Orthorectified images of Poaceae species, specifically Lolium perenne L. (perennial ryegrass) and Phleum pratense L. (timothy grass), are presented in this dataset. The original images were captured using high-resolution RGB cameras, yielding an average size of 2736 x 2736 pixels per image. To correct for the “fisheye” distortion introduced by the APEMAN 60 camera and to ensure accurate spatial representation, the images underwent an orthorectification process, resulting in a standardized size of 912 x 912 pixels. This dataset is designed for use in deep learning applications, such as the classification and detection of weeds within Poaceae grass species., This research was funded by Grant PID2020-113229RBC43/AEI/https://doi.org/10.13039/501100011033., Ortho_rye, Ortho_timothy, Peer reviewed