Assessment of the current status and effectiveness of area-based conservation measures banning trawling activities in the Adriatic Sea

The marine environment is highly stressed by anthropogenic pressures, among which fisheries, and in particular bottom trawling, are one of the main sources of impact. Area-based conservation measures can help conserve and restore ecosystems and population structures and therefore constitute a key tool to the achievement of the 14th Sustainable Development Goal, preservation of the ocean. The purpose of this paper is to provide an assessment of the compliance of area-based conservation measures. The Adriatic Sea has been selected as a case study area, as one of the most intensively trawled areas in the world where different countries share its resources and consequently different management strategies are put in place. We present a review of the marine managed areas established in the Adriatic Sea in 2019, providing information on their characteristics, temporal variabilities, and scopes. Through the processing of Automatic Identification System (AIS) data, the monthly bottom fishing activity performed within each area was inferred and the intensity was assessed. Thus, the effectiveness of trawling bans was evaluated. We demonstrated that full respect of the prohibition was effective in 73% of the areas, while trawling activity was recorded with different intensities in 149 out of 549 managed areas

La financiación de las universidades públicas españolas. Estado actual y propuestas de mejora

Como consecuencia de la crisis económica y financiera mundial, los gobiernos de todos los países europeos están reformulando las formas de financiación de los sistemas uni-versitarios públicos para garantizar su sostenibilidad financiera, eficacia y eficiencia, al tiempo que se están produciendo cambios en las universidades públicas que tendrán, sin duda, efectos importantes en las fuentes de financiación y su peso. En este artículo se analizan las distintas fuentes de financiación de las universidades públicas españolas y se proponen medidas para conseguir modelos de financiación coherentes con la situación económica actual, en donde se premie la flexibilidad y el esfuerzo de las universidades públicas en la consecución de ciertos objetivos, respe-tando la autonomía universitaria y potenciando la transparencia y rendición de cuen-tas. Así, se señalan ciertas reformas tanto para el modo de financiación pública de las universidades como, especialmente, para la financiación privada. En el primer caso, se apuesta por la extensión de los contratos programa a todo el sistema universitario. En el segundo caso, se proponen cambios en la financiación a través de precios públicos y la necesaria potenciación de la financiación filantrópica. Asimismo, se describen las sinergias que se pueden producir con la financiación de origen privado, de modo que las mejores universidades atraigan mejores estudiantes nacionales e internacionales y den un mayor impulso a la innovación y a la transferencia de conocimiento a la socie-dad. Palabr

Estimating hidden fishing activity hotspots from vessel transmitted data

Monitoring fishery activity is essential for resource planning and guaranteeing fisheries sustainability. Large fishing vessels constantly and continuously communicate their positions via Automatic Identification System (AIS) or Vessel Monitoring Systems (VMSs). These systems can use radio or Global Positioning System (GPS) devices to transmit data. Processing and integrating these big data with other fisheries data allows for exploring the relations between socio-economic and ecosystem assets in marine areas, which is fundamental in fishery monitoring. In this context, estimating actual fishing activity from time series of AIS and VMS data would enhance the correct identification of fishing activity patterns and help assess regulations' effectiveness. However, these data might contain gaps because of technical issues such as limited coverage of the terrestrial receivers or saturated transmission bands. Other sources of data gaps are adverse meteorological conditions and voluntary switch-offs. Gaps may also include hidden (unreported) fishing activity whose quantification would improve actual fishing activity estimation. This paper presents a workflow for AIS/VMS big-data analysis that estimates potential unreported fishing activity hotspots in a marine area. The workflow uses a statistical spatial analysis over vessel speeds and coordinates and a multi-source data integration approach that can work on multiple areas and multiple analysis scales. Specifically, it (i) estimates fishing activity locations and rebuilds data gaps, (ii) estimates the potential unreported fishing hour distribution and the unreported-over-total ratio of fishing hours at a 0.01° spatial resolution, (iii) identifies potential unreported fishing activity hotspots, (iv) extracts the stocks involved in these hotspots (using global-scale repositories of stock and species observation data) and raises an alert about their possible endangered, threatened, and protected (ETP) status. The workflow is also a free-to-use Web Service running on an open science-compliant cloud computing platform with a Web Processing Service (WPS) standard interface, allowing efficient big data processing. As a study case, we focussed on the Adriatic Sea. We reconstructed the monthly reported and potential unreported trawling activity in 2019, using terrestrial AIS data with a 5-min sampling period, containing ~50 million records transmitted by ~1,600 vessels. The results highlight that the unreported fishing activity hotspots especially impacted Italian coasts and some forbidden and protected areas. The potential unreported activity involved 33 stocks, four of which were ETP species in the basin. The extracted information agreed with expert studies, and the estimated trawling patterns agreed with those produced by the Global Fishing Watch

Using AIS to Attempt a Quantitative Evaluation of Unobserved Trawling Activity in the Mediterranean Sea

In the past decades, the Automatic Identification System (AIS) has been employed in numerous research fields as a valuable tool for, among other things, Maritime Domain Awareness and Maritime Spatial Planning. In contrast, its use in fisheries management is hampered by coverage and transmission gaps. Transmission gaps may be due to technical limitations (e.g., weak signal or interference with other signals) or to deliberate switching off of the system, to conceal fishing activities. In either case such gaps may result in underestimating fishing effort and pressure. This study was undertaken to map and analyze bottom trawler transmission gaps in terms of duration and distance from the harbor with a view to quantifying unobserved fishing and its effects on overall trawling pressure. Here we present the first map of bottom trawler AIS transmission gaps in the Mediterranean Sea and a revised estimate of fishing effort if some gaps are considered as actual fishing

Few and nonsevere adverse infusion events using an automated method for diluting and washing before unrelated single cord blood transplantation

Graft dilution and DMSO washing before cord blood (CB) administration using an automated system may offer low incidence of adverse infusion events (AIE), ensuring reproducible cell yields. Hence, we analyzed the incidences and significance of immediate AIE, cellular yield, and engraftment after single CB infusion. One hundred and fifty-seven patients (median age, 20 years; range, 1 to 60) received a single CB unit for treatment of hematologic and nonhematologic malignancies with myeloablative conditioning after graft dilution and washing. The median total nucleated cell (TNC) doses was 3.4× 10/kg (range, 2 to 26) and the median post-thaw recovery was 84% (range, 45 to 178). The cumulative incidence of neutrophil engraftment at 50 days was 84% (95% confidence interval [CI], 83 to 93). A total of 118 immediate AIE were observed in fifty-two (33%) patients. All reported AIE were transient, graded from 1 to 2 by Common Terminology Adverse Events version 4. The most frequent toxicity was cardiovascular but without any life-threatening reaction. Infused TNC, recipient's weight, and rate of infusion per kilogram were risk factors associated with cardiovascular AIE in multivariate analysis (odds ratio [OR], 1.2 (95% CI, 1.1 to 1.4); P <.001; OR,.94 (95% CI,.9 to.97); P <.001; and OR, 1.5 (95% CI, 1.2 to 1.8); P <.001; respectively). In summary, use of an automated method for graft washing before CB administration showed low incidence of AIE without compromising cell yields and engraftment. Infused TNC dose, recipient's weight, and rate of infusion per kilogram were risk factors associated with infusion reactions

Cumulative and average beam and pelagic trawling fishing hours in the Adriatic Sea for the period 2015-2022

An enhanced version of the R4AIS workflow (Galdelli et al., 2021) was used to process T-AIS data, with a poll frequency of 5 min, of fishing vessels operating in the Adriatic Sea during 8 years (2015-2022). Data of vessels categorized as beam trawlers and pelagic trawlers were aggregated to obtain cumulative (fahs) and average (mfahs) fishing hours by fishing category at 0.1°. Maps of beam and pelagic trawling fishing activity were created at 0.1°

Fishing activity hotspots in case study areas of the Mediterranean, Black and Atlantic Seas at 0.1°

Statistically significant hotspots of fishing activities in specific case study areas (Adriatic Sea, Aegean Sea, Balearic Sea, Baltic Sea, Bay of Biscay, Black Sea, Levantine Sea and North Sea) were identified by the application of the Getis-Ord Gi statistic (Getis and Ord 2010) though the statistical software R using the globalG.test function (spdep package). The function computes a global test for spatial autocorrelation using a Monte Carlo simulation approach. It tests the null hypothesis of no autocorrelation against the alternative hypothesis of positive spatial autocorrelation. Then the local spatial autocorrelation was tested calculating the Gi statistic, using the local_g_perm function (dfdep package), which indicates the strength of the clustering. Categorization of hotspots was performed, according to the Gi value and the p-value of a folded permutation test obtained for each grid cell, as follows: Gi>0 and p_value <=0.01 as Very hot Gi>0 and p_value <=0.05 as Hot Gi>0 and p_value <=0.1 as Somewhat hot Gi<0 and p_value <=0.1 as Somewhat cold Gi<0 and p_value <=0.05 as Cold Gi<0 and p_value <=0.01 à Very cold Grid cells with a p-value > 0.1 were categorized as Insignificant. The analyses were performed on cumulative fishing activity data at 0.1° resolution of nine different gears separately for the eight case study areas. Trawling hotspot cells categorized as “Very hot” (highly pressured) and “Hot” and “Somewhat hot” (medium pressured) were intersected with repositories of stocks and species-observation data (Coro et al., 2023) in order to retrieve information of species potentially caught by those fishing activities. The dataset presented includes for each case study area tables of species potentially caught within the trawling hotspots, maps of each gear hotspot, spatial layers of the gears hotspots (.shp; .csv

Fishing activity hotspots in the Mediterranean and Atlantic Seas at 0.5°

Statistically significant hotspots of fishing activities in the Mediterranean and Atlanti Seas were identified by the application of the Getis-Ord Gi statistic (Getis and Ord 2010) though the statistical software R using the globalG.test function (spdep package). The function computes a global test for spatial autocorrelation using a Monte Carlo simulation approach. It tests the null hypothesis of no autocorrelation against the alternative hypothesis of positive spatial autocorrelation. Then the local spatial autocorrelation was tested calculating the Gi statistic, using the local_g_perm function (dfdep package), which indicates the strength of the clustering. Categorization of hotspots was performed, according to the Gi value and the p-value of a folded permutation test obtained for each grid cell, as follows: Gi>0 and p_value <=0.01 as Very hot Gi>0 and p_value <=0.05 as Hot Gi>0 and p_value <=0.1 as Somewhat hot Gi<0 and p_value <=0.1 as Somewhat cold Gi<0 and p_value <=0.05 as Cold Gi<0 and p_value <=0.01 à Very cold Grid cells with a p-value > 0.1 were categorized as Insignificant. The analyses were performed on cumulative fishing activity data at 0.5° resolution of seven different gears separately for the two macroareas. The dataset presented includes for each area maps of each gear hotspot and spatial layers of the gears hotspots (.shp; .csv

Cumulative and average bottom trawling fishing hours in the Mediterranean Sea for the period 2015-2022

An enhanced version of the R4AIS workflow (Galdelli et al., 2021) was used to process T-AIS data, with a poll frequency of 5 min, of fishing vessels operating in the Mediterranean Sea during 8 years (2015-2022). Data of vessels categorized as bottom trawlers were aggregated to obtain cumulative (fahs) and average (mfahs) fishing hours by fishing category at 0.1° and 0.5° resolution. Maps of bottom trawling fishing activity were created for four main areas at 0.1° (Adriatic Sea, Aegean Sea, Balearic Sea and Levantine Sea) and at 0.5° for the Mediterranean basin