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Sbragaglia, Valerio . et al.-- 11 pages, 5 figures, 2 tables, supplementary information https://doi.org/10.1038/s41598-018-37954-0 ; The seasonal timing of recurring biological processes is essential for organisms living in temperate regions. While ample knowledge of these processes exists for terrestrial environments, seasonal timing in the marine environment is relatively understudied. Here, we characterized the annual rhythm of habitat use in six fish species belonging to the Sparidae family, highlighting the main environmental variables that correlate to such rhythms. The study was conducted at a coastal artificial reef through a cabled observatory system, which allowed gathering underwater time-lapse images every 30 minutes consecutively over 3 years. Rhythms of fish counts had a significant annual periodicity in four out of the six studied species. Species-specific temporal patterns were found, demonstrating a clear annual temporal niche partitioning within the studied family. Temperature was the most important environmental variable correlated with fish counts in the proximity of the artificial reef, while daily photoperiod and salinity were not important. In a scenario of human-induced rapid environmental change, tracking phenological shifts may provide key indications about the effects of climate change at both species and ecosystem level. Our study reinforces the efficacy of underwater cabled video-observatories as a reliable tool for long-term monitoring of phenological events ; VS was supported by a Leibniz-DAAD postdoctoral research fellowship (n. 91632699). [.] This work was partially funded within the framework of the RESBIO project (REdes de Sensores submarinos autónomos y cableados aplicados a la monitorización remota de indicadores BIOlógicos; Comisión Interministerial de Ciencia y Tecnología, MINISTERIO DE ECONOMÍA, INDUSTRIA Y COMPETITIVIDAD, RETOS 2017) under TEC2017-87861-R contract. The Research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2013-2017) under the grant agreement n◦ 312463, FixO3, through the TNA project FISHAUT (grant agreement n◦ FC-01) for accessing the OBSEA data ; Peer Reviewed

3 pages, 1 table ; We highlight important steps that researchers should follow when using social media data, in particular when the aim of their research is to characterize illegal fishing. Specifically, we provide a checklist of mitigation strategies focusing on data privacy concerns and ethical principles associated with human-subject research. We hope our reflections will contribute to a more responsible use of social media and other digital platforms among marine conservation scientists ; We acknowledge the constructive feedback of two anonymous reviewers. VS is supported by a "Juan de la Cierva Incorporación" research fellowship (IJC2018-035389-I) granted by the Spanish Ministry of Science and Innovation. VS also acknowledge the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation to ICM-CSIC (#CEX2019-000928-S). RAC is supported by funds from the University of Helsinki through a personal grant to EDM. EDM thanks the European Research Council for funding under the European Union's Horizon 2020 Research and Innovation Program (grant agreement #802933) ; Peer reviewed

12 pages, 8 figures, 2 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2021.768047/full#supplementary-material.-- Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation ; Social media may provide information for monitoring recreational fisheries, but several caveats prevent operationalization. Specifically, the fraction and profile of recreational fishers sharing their catches is not known. Our aim was to advance the monitoring capacities of recreational fishing using social media data. We collected data with onsite (face-to-face) survey and online (emails) questionnaires to characterize marine recreational fishers sharing catches on digital platforms ("sharers") along with other demographic or fishing information. In the online survey we found that 38% of recreational fishers share their catches using digital platforms (including the private messaging platform WhatsApp), but such proportion dropped to 12% when considering only public or semi-public social media (Instagram was the most commonly used platform, followed by Facebook, YouTube, and Twitter). A similar pattern was found with the online questionnaire where sharers represented 37% of recreational fishers (including WhatsApp), while such proportion dropped to 21% when considering only public or semi-public social media. In general, sharers were more avid (24 and 35 yearly fishing trips for onsite and online survey, respectively) compared to non-sharers (18 and 31 yearly fishing trips). Sharers also spent more money on each fishing trip (on average 26 and 31 euro for onsite and online survey, respectively) than non-sharers (on average 21 and 28 euro for onsite and online survey, respectively), but they had similar chances of catching something. However, for fishers with catches, the harvest per unit effort of sharers was higher than that of non-sharers (0.4 and 0.5 kg/h with respect to 0.3 and 0.4 kg/h, for onsite and online survey, respectively). Moreover, recreational fishers that caught trophy, iconic, or emblematic species were more inclined to share their catches. This study represents an important advancement for integrating social media data into the monitoring of recreational fishing ; GV was supported by an ERASMUS+ traineeship grant in agreement with the "School of Nature Sciences" of the University of Turin, while VS was supported by a "Juan de la Cierva Incorporación" research fellowship (IJC2018-035389-I) granted by the Spanish Ministry of Science and Innovation. VS and GV acknowledge the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation to ICM-CSIC (#CEX2019-000928-S) ; Peer reviewed

13 pages, 6 figures, 2 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2021.802235/full#supplementary-material.-- Data Availability Statement: The datasets analyzed for this study can be found in the GBIF (www.gbif.org, accessed in June 2021) through different queries. Details on each query and associated DOIs are included in the article/Supplementary Table 1. Further inquiries can be directed to the corresponding author ; The ongoing contemporary biodiversity crisis may result in much of ocean's biodiversity to be lost or deeply modified without even being known. As the climate and anthropogenic-related impacts on marine systems accelerate, biodiversity knowledge integration is urgently required to evaluate and monitor marine ecosystems and to support suitable responses to underpin a sustainable future. The Census of Marine Life (CoML, 2000–2010) was the largest global research program on marine biodiversity. A decade after, and coinciding with the steep increase of digitalization of our society, we review existing findability, accessibility, interoperability, and reusability (FAIR) biodiversity data coming from one of the most reliable online information systems: the Global Biodiversity Information Facility (GBIF). We evaluate the completeness of available datasets with respect to the CoML benchmark, along with progresses in understanding spatial–temporal patterns of marine biodiversity in the European Seas in the last decades. Overall, we observe severe biases in available biodiversity data toward the north-western marine regions (particularly around the United Kingdom and the North Sea), the most recent years (with a peak in the number of reported occurrences in the 2010s) and the most conspicuous, abundant, and likely "appealing" taxa (e.g., crustaceans, echinoderms or fish). These biases may hamper research applications, but also global-scale data needs and integrative assessments required to support cost-effective progresses toward global biodiversity conservation. National to international joint efforts aimed at enhancing data acquisition and mobilization from poorly known regions, periods, and taxa are desirable if we aim to address these potential biases for the effective monitoring of marine ecosystems and the evaluation of ongoing impacts on biogeographic patterns and ecosystem functioning and services ; This work has been co-funded by the H2020 MINKE (Metrology for Integrated Marine Management and Knowledge-Transfer Network; grant agreement No. 101008724), the H2020 Cos4Cloud (co-designed citizen observatories for the European Open Science Cloud EOSC – Cos4Cloud; grant agreement No. 863463), and H2020-FutureMares (Climate Change and Future Marine Ecosystem Services and Biodiversity; grant agreement No. 869300), and the Spanish government through the "Severo Ochoa Center of Excellence" accreditation (grant agreement No. CEX2019-000928-S, hereafter SO). FR was supported by SO and VS by a "Juan de la Cierva Incorporación" research fellowship (grant agreement No. IJC2018-035389-I) granted by the Spanish Ministry of Science and Innovation ; Peer reviewed

12 pages, 5 figures, 4 tables, 1 video, supplementary material https://dx.doi.org/10.1038/s41598-018-32089-8 ; Marine cabled video-observatories allow the non-destructive sampling of species at frequencies and durations that have never been attained before. Nevertheless, the lack of appropriate methods to automatically process video imagery limits this technology for the purposes of ecosystem monitoring. Automation is a prerequisite to deal with the huge quantities of video footage captured by cameras, which can then transform these devices into true autonomous sensors. In this study, we have developed a novel methodology that is based on genetic programming for content-based image analysis. Our aim was to capture the temporal dynamics of fish abundance. We processed more than 20,000 images that were acquired in a challenging real-world coastal scenario at the OBSEA-EMSO testing-site. The images were collected at 30-min. frequency, continuously for two years, over day and night. The highly variable environmental conditions allowed us to test the effectiveness of our approach under changing light radiation, water turbidity, background confusion, and bio-fouling growth on the camera housing. The automated recognition results were highly correlated with the manual counts and they were highly reliable when used to track fish variations at different hourly, daily, and monthly time scales. In addition, our methodology could be easily transferred to other cabled video-observatories ; The Research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2013-2017) under the grant agreement n° 312463, FixO3, through the TNA project FISHAUT (grant agreement n° FC-01) for accessing the OBSEA data ; Peer Reviewed

13 pages, 2 figures, supporting information https://doi.org/10.1371/journal.pbio.3000935 ; The ongoing digital revolution in the age of big data is opening new research opportunities. Culturomics and iEcology, two emerging research areas based on the analysis of online data resources, can provide novel scientific insights and inform conservation and management efforts. To date, culturomics and iEcology have been applied primarily in the terrestrial realm. Here, we advocate for expanding such applications to the aquatic realm by providing a brief overview of these new approaches and outlining key areas in which culturomics and iEcology are likely to have the highest impact, including the management of protected areas; fisheries; flagship species identification; detection and distribution of threatened, rare, and alien species; assessment of ecosystem status and anthropogenic impacts; and social impact assessment. When deployed in the right context with awareness of potential biases, culturomics and iEcology are ripe for rapid development as low-cost research approaches based on data available from digital sources, with increasingly diverse applications for aquatic ecosystems ; This work was supported by J. E. Purkyně Fellowship of the Czech Academy of Sciences (https://www.avcr.cz) (IJ), Helsinki Institute of Sustainability Science and the University of Helsinki (https://www.helsinki.fi/en/helsinki-institute-of-sustainability-science) (RAC), EU Horizon 2020 research and innovation programme funding (project grant No. 677039) (https://ec.europa.eu/programmes/horizon2020/en) (ATS), European Regional Development Fund / European Social Fund (ERDF/ESF) funding (CZ.02.1.01/0.0/0.0/16_025/0007417) (https://ec.europa.eu/regional_policy/en/funding/erdf/; https://ec.europa.eu/esf/home.jsp) (ATS), Austrian Science Foundation FWF (grant I 3757-B29) (https://www.fwf.ac.at) (FE), EU and the State of Mecklenburg-Vorpommern (Germany, grant MV-I.18-LM-004, B 730117000069) (https://www.government-mv.de/Mecklenburg%E2%80%93Vorpommern) (RA), German Federal Ministry for Education and Research (BMBF) (https://www.bmbf.de) with the grants 01LC1826D and 033W046A (RA) and the "GLANCE" project (Global Change Effects in River Ecosystems; 01 LN1320A) (SCJ, GK), Czech Science Foundation (grant 19-05510S) (https://gacr.cz) (KD), Israel Science Foundation (grant No. 406/19) (https://www.isf.org.il) (UR), Foundation for Science and Technology (FCT) strategic project UID/MAR/04292/2013 (https://www.fct.pt) (RR), Norwegian Research Council (https://www.forskningsradet.no) (RJL), Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Incorporación; grant IJC2018-035389-I) (http://www.ciencia.gob.es) (VS), Social Sciences and Humanities Research Council of Canada (grant 435-2018-1018) (https://www.sshrc-crsh.gc.ca) (YC), Nova Scotia Graduate Scholarship (https://www.dal.ca/faculty/gradstudies/funding/appprocres/scholarshiprefs/nsgs.html) (YC), grant NAKI II DG18P02OVV057 (https://starfos.tacr.cz) (LK), TACR ZÉTA project (No. TJ02000012 (https://starfos.tacr.cz) (MŠ) ; Peer reviewed

In late 2019, an outbreak caused by a novel coronavirus started in China (Graham and Baric, 2020; Hu et al., 2020; Maxmen, 2021). A global pandemic was declared in March 2020, as COVID-19, the disease caused by the coronavirus (World Health Organization, 2020b), escalated outside China (World Health Organization, 2020a). In mid-2021, when vaccination campaigns began to show positive effects on the control of the disease in several countries (Kaur and Gupta, 2020), the COVID-19 pandemic caused millions of deaths and hundreds of millions of infections (Dong et al., 2020). To fight the pandemic, governments reacted with measures designed to contain the spread of the virus, especially through measures aimed to reduce social interactions, including lockdowns (Wilder-Smith and Freedman, 2020), travel restrictions (Chinazzi et al., 2020), and limiting people's access to non-essential activities (Storr et al., 2021). Humanity suffered a notable impact as a result of the pandemic, including losses of jobs and an abrupt disruption in global demand of goods and services (Barua, 2020; McKibbin and Fernando, 2020; Nicola et al., 2020). The pandemic further degraded the quality of life of the most vulnerable people, particularly those with mental health problems (Brooks et al., 2020), victims of domestic violence (Usher et al., 2020), children (Singh et al., 2020), or indigenous populations (Lane, 2020). As a result, an increase in economic inequality and worldwide poverty is expected, especially in developing countries (World Bank, 2020), and a peak in the suicide rate (Kawohl and Nordt, 2020). On the other hand, global reduction of human activities has had some positive effects on the global environment, especially for air and water quality (Rutz et al., 2020), and noise reduction (Zambrano-Monserrate et al., 2020). Marine ecosystems for example experienced less impacts derived from commercial fishing due to disruptions in large markets such as the United States (White et al., 2021a) or the European Union (Prellezo and ...