Increased hydralic risk in assemblages of woody plant species predicts spatial patterns of drought-induced mortality

Predicting drought-induced mortality (DIM) of woody plants remains a key research challenge under climate change. Here, we integrate information on the edaphoclimatic niches, phylogeny and hydraulic traits of species to model the hydraulic risk of woody plants globally. We combine these models with species distribution records to estimate the hydraulic risk faced by local woody plant species assemblages. Thus, we produce global maps of hydraulic risk and test for its relationship with observed DIM. Our results show that local assemblages modelled as having higher hydraulic risk present a higher probability of DIM. Metrics characterizing this hydraulic risk improve DIM predictions globally, relative to models accounting only for edaphoclimatic predictors or broad functional groupings. The methodology we present here allows mapping of functional trait distributions and elucidation of global macro-evolutionary and biogeographical patterns, improving our ability to predict potential global change impacts on vegetation

CARAMEL: results on a secure architecture for connected and autonomous vehicles detecting GPS spoofing attacks

The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine Learning techniques. As a result, CARAMEL enhances the protection against threats related to automated driving, smart charging of Electric Vehicles, and communication among vehicles or between vehicles and the roadside infrastructure. This work focuses on the latter and presents the CARAMEL architecture aiming at assessing the integrity of the information transmitted by vehicles, as well as at improving the security and privacy of communication for connected and autonomous driving. The proposed architecture includes: (1) multi-radio access technology capabilities, with simultaneous 802.11p and LTE-Uu support, enabled by the connectivity infrastructure; (2) a MEC platform, where, among others, algorithms for detecting attacks are implemented; (3) an intelligent On-Board Unit with anti-hacking features inside the vehicle; (4) a Public Key Infrastructure that validates in real-time the integrity of vehicle’s data transmissions. As an indicative application, the interaction between the entities of the CARAMEL architecture is showcased in case of a GPS spoofing attack scenario. Adopted attack detection techniques exploit robust in-vehicle and cooperative approaches that do not rely on encrypted GPS signals, but only on measurements available in the CARAMEL architecture.This work was supported by the European Union’s H2020 research and innovation programme under the CARAMEL project (Grant agreement No. 833611). The work of Christian Vitale, Christos Laoudias and Georgios Ellinas was also supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE) and from the Republic of Cyprus through the Directorate General for European Programmes, Coordination, and Development. The work of Jordi Casademont and Pouria Sayyad Khodashenas was also supported by FEDER and Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya through projects Fem IoT and SGR 2017-00376 and by the ERDFPeer ReviewedPostprint (author's final draft

Linking ecological niche models and common garden experiments to predict phenotypic differentiation in stressful environments: Assessing the adaptive value of marginal populations in an alpine plant

Environmental variation within a species’ range can create contrasting selective pressures, leading to divergent selection and novel adaptations. The conservation value of populations inhabiting environmentally marginal areas remains in debate and is closely related to the adaptive potential in changing environments. Strong selection caused by stressful conditions may generate novel adaptations, conferring these populations distinct evolutionary potential and high conservation value under climate change. On the other hand, environmentally marginal populations may be genetically depauperate, with little potential for new adaptations to emerge. Here, we explored the use of ecological niche models (ENMs) linked with common garden experiments to predict and test for genetically determined phenotypic differentiation related to contrasting environmental conditions. To do so, we built an ENM for the alpine plant Silene ciliata in central Spain and conducted common garden experiments, assessing flowering phenology changes and differences in leaf cell resistance to extreme temperatures. The suitability patterns and response curves of the ENM led to the predictions that: (1) the environmentally marginal populations experiencing less snowpack and higher minimum temperatures would have delayed flowering to avoid risks of late-spring frosts and (2) those with higher minimum temperatures and greater potential evapotranspiration would show enhanced cell resistance to high temperatures to deal with physiological stress related to desiccation and heat. The common garden experiments revealed the expected genetically based phenotypic differentiation in flowering phenology. In contrast, they did not show the expected differentiation for cell resistance, but these latter experiments had high variance and hence lower statistical power. The results highlight ENMs as useful tools to identify contrasting putative selective pressures across species ranges. Linking ENMs with common garden experiments provides a theoretically justified and practical way to study adaptive processes, including insights regarding the conservation value of populations inhabiting environmentally marginal areas under ongoing climate change

A standard protocol for reporting species distribution models

Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready-to-use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservation and management, and for quantifying impacts from global change. However, models must be fit for purpose, with all important aspects of their development and applications properly considered. Despite the widespread use of SDMs, standardisation and documentation of modelling protocols remain limited, which makes it hard to assess whether development steps are appropriate for end use. To address these issues, we propose a standard protocol for reporting SDMs, with an emphasis on describing how a study's objective is achieved through a series of modeling decisions. We call this the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol, as its components reflect the main steps involved in building SDMs and other empirically-based biodiversity models. The ODMAP protocol serves two main purposes. First, it provides a checklist for authors, detailing key steps for model building and analyses, and thus represents a quick guide and generic workflow for modern SDMs. Second, it introduces a structured format for documenting and communicating the models, ensuring transparency and reproducibility, facilitating peer review and expert evaluation of model quality, as well as meta-analyses. We detail all elements of ODMAP, and explain how it can be used for different model objectives and applications, and how it complements efforts to store associated metadata and define modelling standards. We illustrate its utility by revisiting nine previously published case studies, and provide an interactive web-based application to facilitate its use. We plan to advance ODMAP by encouraging its further refinement and adoption by the scientific community

Impact of Diabetes on 10‐Year Outcomes Following ST‐Segment–Elevation Myocardial Infarction: Insights From the EXAMINATION‐EXTEND Trial

BACKGROUND: Long-term outcomes of ST-segment-elevation myocardial infarction in patients with diabetes have been barely investigated. The objective of this analysis from the EXAMINATION-EXTEND (10-Years Follow-Up of the EXAMINATION trial) trial was to compare 10-year outcomes of patients with ST-segment-elevation myocardial infarction with and without diabetes. METHODS AND RESULTS: Of the study population, 258 patients had diabetes and 1240 did not. The primary end point was patient-oriented composite end point of all-cause death, any myocardial infarction, or any revascularization. Secondary end points were the individual components of the primary combined end point, cardiac death, target vessel myocardial infarction, target lesion revascularization, and stent thrombosis. All end points were adjusted for potential confounders. At 10 years, patients with diabetes showed a higher incidence of patient-oriented composite end point compared with those without (46.5% versus 33.0%; adjusted hazard ratio [HR], 1.31 [95% CI, 1.05-1.61]; P=0.016) mainly driven by a higher incidence of any revascularization (24.4% versus 16.6%; adjusted HR, 1.61 [95% CI, 1.19-2.17]; P=0.002). Specifically, patients with diabetes had a higher incidence of any revascularization during the first 5 years of follow-up (20.2% versus 12.8%; adjusted HR, 1.57 [95% CI, 1.13-2.19]; P=0.007) compared with those without diabetes. No statistically significant differences were found with respect to the other end points. CONCLUSIONS: Patients with ST-segment-elevation myocardial infarction who had diabetes had worse clinical outcome at 10 years compared with those without diabetes, mainly driven by a higher incidence of any revascularizations in the first 5 years

Introducció a les Xarxes Telemàtiques: problemes amb solució

Col·lecció de problemes resolts d'IXT (Introducció a les Xarxes Telemàtiques) amb solució, 1er curs dels graus de l'ETSETB.2022/20232n quadrimestr

Introducció a les Xarxes Telemàtiques: problemes amb solució

Col·lecció de problemes resolts d'IXT (Introducció a les Xarxes Telemàtiques) amb solució, 1er curs dels graus de l'ETSETB2022/20232n quadrimestr

The number of tree species on Earth

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.Additional co-authors: Junho Lee, Jun Zhu, Jinyun Fang, Douglass F. Jacobs, Bryan Pijanowski, Arindam Banerjee, Robert A. Giaquinto, Giorgio Alberti, Angelica Maria Almeyda Zambrano, Esteban Alvarez-Davila, Alejandro Araujo-Murakami, Valerio Avitabile, Gerardo A. Aymard, Radomir Balazy, Chris Baraloto, Jorcely G. Barroso, Meredith L. Bastian, Philippe Birnbaum, Robert Bitariho, Jan Bogaert, Frans Bongers, Olivier Bouriaud, Pedro H. S. Brancalion, Francis Q. Brearley, Eben North Broadbent, Filippo Bussotti, Wendeson Castro da Silva, Ricardo Gomes César, Goran Češljar, Víctor Chama Moscoso, Han Y. H. Chen, Emil Cienciala, Connie J. Clark, David A. Coomes, Selvadurai Dayanandan, Mathieu Decuyper, Laura E. Dee, Jhon Del Aguila Pasquel, Géraldine Derroire, Marie Noel Kamdem Djuikouo, Tran Van Do, Jiri Dolezal, Ilija Đ. Đorđević, Julien Engel, Tom M. Fayle, Ted R. Feldpausch, Jonas K. Fridman, David J. Harris, Andreas Hemp, Geerten Hengeveld, Bruno Herault, Martin Herold, Thomas Ibanez, Andrzej M. Jagodzinski, Bogdan Jaroszewicz, Vivian Kvist Johannsen, Tommaso Jucker, Ahto Kangur, Victor N. Karminov, Kuswata Kartawinata, Deborah K. Kennard, Sebastian Kepfer-Rojas, Gunnar Keppel, Mohammed Latif Khan, Pramod Kumar Khare, Timothy J. Kileen, Hyun Seok Kim, Henn Korjus, Amit Kumar, Ashwani Kumar, Diana Laarmann, Nicolas Labrière, Mait Lang, Simon L. Lewis, Natalia Lukina, Brian S. Maitner, Yadvinder Malhi, Andrew R. Marshall, Olga V. Martynenko, Abel L. Monteagudo Mendoza, Petr V. Ontikov, Edgar Ortiz-Malavasi, Nadir C. Pallqui Camacho, Alain Paquette, Minjee Park, Narayanaswamy Parthasarathy, Pablo Luis Peri, Pascal Petronelli, Sebastian Pfautsch, Oliver L. Phillips, Nicolas Picard, Daniel Piotto, Lourens Poorter, John R. Poulsen, Hans Pretzsch, Hirma Ramírez-Angulo, Zorayda Restrepo Correa, Mirco Rodeghiero, Rocío Del Pilar Rojas Gonzáles, Samir G. Rolim, Francesco Rovero, Ervan Rutishauser, Purabi Saikia, Christian Salas-Eljatib, Dmitry Schepaschenko, Michael Scherer-Lorenzen, Vladimír Šebeň, Marcos Silveira, Ferry Slik, Bonaventure Sonké, Alexandre F. Souza, Krzysztof Jan Stereńczak, Miroslav Svoboda, Hermann Taedoumg, Nadja Tchebakova, John Terborgh, Elena Tikhonova, Armando Torres-Lezama, Fons van der Plas, Rodolfo Vásquez, Helder Viana, Alexander C. Vibrans, Emilio Vilanova, Vincent A. Vos, Hua-Feng Wang, Bertil Westerlund, Lee J. T. White, Susan K. Wiser, Tomasz Zawiła-Niedźwiecki, Lise Zemagho, Zhi-Xin Zhu, Irié C. Zo-Bi, and Jingjing Lian

Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis

Metabolic syndrome (MetS) is one of the most important medical problems around the world. Identification of patient ' s singular characteristic could help to reduce the clinical impact and facilitate individualized management. This study aimed to categorize MetS patients using phenotypical and clinical variables habitually collected during health check-ups of individuals considered to have high cardiovascular risk. The selected markers to categorize MetS participants included anthropometric variables as well as clinical data, biochemical parameters and prescribed pharmacological treatment. An exploratory factor analysis was carried out with a subsequent hierarchical cluster analysis using the z-scores from factor analysis. The first step identified three different factors. The first was determined by hypercholesterolemia and associated treatments, the second factor exhibited glycemic disorders and accompanying treatments and the third factor was characterized by hepatic enzymes. Subsequently four clusters of patients were identified, where cluster 1 was characterized by glucose disorders and treatments, cluster 2 presented mild MetS, cluster 3 presented exacerbated levels of hepatic enzymes and cluster 4 highlighted cholesterol and its associated treatments Interestingly, the liver status related cluster was characterized by higher protein consumption and cluster 4 with low polyunsaturated fatty acid intake. This research emphasized the potential clinical relevance of hepatic impairments in addition to MetS traditional characterization for precision and personalized management of MetS patients