BUSCADOR RECOLECTA

10 pages, 6 figures, 4 tables.-- Data availability: The code is available in the github repository of the first author as stated in the manuscript, Seabirds are bioindicators of marine ecosystems health and one of the world's most endangered avian groups. The creation of marine protected areas plays an important role in the conservation of marine environment and its biodiversity. The distributions of top predators, as seabirds, have been commonly used for the management and creation of these figures of protection.

The main objective of this study is to investigate seabirds biodiversity distribution in the Mediterranean Sea through the use of Bayesian spatial Beta regression models. We used an extensive historical database of at-sea locations of 19 different seabird species as well as geophysical, climatology variables and cumulative anthropogenic threats to model species biodiversity. We found negative associations between seabirds biodiversity and distance to the coast as well as concavity of the seabed, and positive with chlorophyll and slope. Further, a positive association was found between seabirds biodiversity and coastal impact.

In this study we define as hot spot of seabird biodiversity those areas with a posterior predictive mean over 0.50. We found potential hot spots in the Mediterranean Sea which do not overlap with the existing MPASs and marine IBAs. Specifically, our hot spots areas do not overlap with the 52.04% and 16.87% of the current MPAs and marine IBAs, respectively. Overall, our study highlights the need for the extension of spatial prioritization of conservation areas to seabirds biodiversity, addressing the challenges of establishing transboundary governance, BS was supported by Margarita Salas fellowship from Ministry of Universities-University of Valencia (MS21-013). JM-M would like to thank for the support by the Basque Government through the BERC 2018–2021 program and by the Ministry of Science, Innovation and Universities: BCAM Severo Ochoa accreditation SEV-2017-0718 and PID2020-115882RB-I00 research project. DC would like to thank the Spanish Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación for grant PID2019-106341 GB-I00 (jointly financed by the European Regional Development Fund, FEDER). MC acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869300 (FutureMares project) and No 101059407 (MarinePlan), and the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Data-based methods and statistical models are given special attention to the studyof sports injuries to gain in-depth understanding of its risk factors and mechanisms. The objective of this work is to evaluate the use of shared frailty Cox models forthe prediction of occurring sports injuries, and to compare their performance withdifferent sets of variables selected by several regularized variable selection approaches. The study is motivated by specific characteristics commonly found for sports injury data, that usually include reduced sample size and even fewer number of injuries,coupled with a large number of potentially influential variables. Hence, we conduct asimulation study to address these statistical challenges and to explore regularized Cox model strategies together with shared frailty models in different controlled situations. We show that predictive performance greatly improves as more player observations areavailable. Methods that result in sparse models and favour interpretability, e.g. best subset selection and boosting, are preferred when the sample size is small. We include a real case study of injuries of female football players of a Spanish football club., This research was supported by the Basque Government through the BERC Programme 2018–2021 by the Spanish Ministry of Science, Innovation and Universities MICINN and FEDER: BCAM Severo Ochoa excellence accreditation SEV-2017-0718, and project PID2020-115882RB-I00 funded by AEI/FEDER, UE and acronym ‘S3M1P4R’ and by the German Federal Ministry of Education and Research (BMBF) under Grant No. 01IS18036A.

Although cities globally are increasingly mobilizing re-naturing projects to address diverse urban socio-environmental and health challenges, there is mounting evidence that these interventions may also be linked to the phenomenon known as green gentrification. However, to date the empirical evidence on the relationship between greenspaces and gentrification regarding associations with different greenspace types remains scarce. This study focused on 28 mid-sized cities in North America and Western Europe. We assessed improved access to different types of greenspace (i.e. total area of parks, gardens, nature preserves, recreational areas or greenways [i] added before the 2000s or [ii] added before the 2010s) and gentrification processes (including [i] gentrification for the 2000s; [ii] gentrification for the 2010s; [iii] gentrification throughout the decades of the 2000s and 2010s) in each small geographical unit of each city. To estimate the associations, we developed a Bayesian hierarchical spatial model foreach city and gentrification time period (i.e. a maximum of three models per city). More than half of our models showed that parks-together with other factors such as proximity to the city center-are positively associated with gentrification processes, particularly in the US context, except in historically Black disinvested postindustrial cities with lots of vacant land. We also find than in half of our models newly designated nature preserves are negatively associated with gentrification processes, particularly when considering gentrification throughout the 2000s and the 2010s and in the US. Meanwhile, for new gardens, recreational spaces and greenways, our research shows mixed results (some positive, some negative and some no effect associations). Considering the environmental and health benefits of urban re-naturing projects, cities should keep investing in improving park access while simultaneously implementing anti-displacement and inclusive green policies.