Environmental Influence on the Occurrence of Multi-Organ Cystic Echinococcosis Infection in a Patient from Sardinia, Italy

An uncommon clinical case of an adult woman who was referred to the hospital with severe symptoms attributable to cystic echinococcosis (CE) is described in this report. According to a questionnaire, the subject was exposed to a high risk of infection since she was employed on a farm about 20 years before diagnosis. She lived close to several animal species and handled vegetables in inadequate hygienic conditions. Medical and laboratory investigations confirmed the presence of massive echinococcal cystic lesions in each lung and in the liver. Given the peculiarity of the case, pharmacological and surgical treatments were the only conceivable option. The association of pharmacological treatment, surgery, and interventional radiology procedure represented a reliable and effective way to handle a complex case of human hydatidosis. A multi-disciplinary approach was mandatory, resulting in a clear and conclusive diagnosis of CE caused by the zoonotic parasite E. granulosus sensu stricto of the G1 genotype

Scientific, Technical and Economic Committee for Fisheries (STECF) - Stock Assessments: demersal stocks in the western Mediterranean Sea (STECF-19-10)

615 pagesCommission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, p. 4–10. The Commission may consult the group on any matter relating to marine and fisheries biology, fishing gear technology, fisheries economics, fisheries governance, ecosystem effects of fisheries, aquaculture or similar disciplines. This reportis from STECF Expert Working Group19-10: 2019stock assessments ofdemersal stocks in the western Mediterranean Seafrom the meeting in Arona Italy from 9thto 15rdSeptember 2019. A total of 19 fish stocks were evaluated. The EWG reports age based assessments and short term forecasts for 15 of the 19 stocks. Catch advice for the other four stocks was based on ICES category 3 evaluations of biomass indices. The content of the report gives the STECF terms of reference, the basis of the evaluationsand advice, summaries of state of stock and advised based on either the MSY approach for assessed stocks or the precautionary approachfor category 3 based advice. Thereport contains the full stock assessment reports for the 15 assessments, one full category3 evaluation and briefre-evaluations and validations of the 2018 results for the final three stocks for which two year’sadvice was given in 2018.The report also contains the STECF observations and conclusions on the assessment report. These conclusionscome from the STECF Plenary meeting November 201

Correction: Large-Scale Diversity of Slope Fishes: Pattern Inconsistency between Multiple Diversity Indices.

[This corrects the article DOI: 10.1371/journal.pone.0066753.]

Modelling of European hake nurseries in the Mediterranean Sea: an ecological niche approach

An ecological niche modelling (ENM) approach was developed to model the suitable habitat 36 for the 0-group European hake, Merluccius merluccius L., 1758, in the Mediterranean Sea. 37 The ENM was built combining knowledge on biological traits of hake recruits (e.g. growth, 38 settlement, mobility and feeding strategy) with patterns of selected ecological variables 39 (chlorophyll-a fronts and concentration, bottom depth, sea bottom current and temperature) 40 to highlight favourable nursery habitats. The results show that hake nurseries require stable 41 bottom temperature (11.8-15.0oC), low bottom currents (< 0.034 m.s-1) and a frequent 42 occurrence of productive fronts in low chlorophyll-a areas (0.1-0.9 mg.m-3) to support a 43 successful recruitment. These conditions mostly occur recurrently in outer shelf and shelf 44 break areas. The prediction explains the relative balance between biotic and abiotic drivers 45 of hake recruitment in the Mediterranean Sea and the primary role of unfavourable 46 environmental conditions on low recruitment in specific years (i.e. 2011). The ENM outputs 47 particularly agree spatially with biomass data of recruits, although processes such as fishing 48 and natural mortality are not accounted for. The seasonal mapping of suitable habitats 49 provides information on potential nurseries and recruitment carrying capacity which are 50 relevant for spatial fisheries management of hake in the Mediterranean Sea

Scientific, Technical and Economic Committee for Fisheries (STECF) - Evaluation of fishing effort regime in the Western Mediterranean - Part IV (STECF-19-14)

130 pagesCommission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, p. 4–10. The Commission may consult the group on any matter relating to marine and fisheries biology, fishing gear technology, fisheries economics, fisheries governance, ecosystem effects of fisheries, aquaculture or similar disciplines. This report is the fourth of a suite of STECF EWG reports dedicated to the fishing effort regime in the Western Mediterranean Sea, following EWG reports 18-09, 18-13 and 19-01. The group wasrequested toprogress on an operational mixed-fisheries model for Effort Management Unit 1 (i.e. GSAs 1-2-5-6-7), to update mixed fisheries models and F-E analyses with the most recent data and the most recent stock assessments., and to draft amixed-fisheries advice including relevant scenarios and displays. In EMU 1, good progresses were achieved in combining effort and catch data from both France and Spain into the bioeconomic multifleet model IAM. The model is now able to run and perform management simulations on the stock of hake (combined assessment in GSAs 1-2-5-6-7). Time did not allow to include additional stocks at this stage, but the required elements are now in place and adding these should be fairly straightforward in the future.The updates of the F-E analyses performed in EWG 18-09 and 18-13 with the most recent time series did not change the perception of the lack of relationship between fishing effort and fishing mortality. For many stocksand fleet segments, the relationship using effort expressedas fishing days has no obvious slope, indicating that the limited reduction of effort observed in the recent years did not have any visible effect on reducing fishing mortality yet.Supplementary analyses were performed using effort expressed in hours instead of days, which improved the relationship to some extent. This is consistent with previous statements in previous reports that fishing effort would be best expressed and managed in terms of fishing hours than fishing days:Extended simulation work was performed regarding management scenarios, especially in EMU 2 (GSAs 8-9-10-11). The multi-fleet BEMTOOL model was updated and extended, and 6 scenarios involving effort reductions, sometimes combined with spatial closures, were simulated in a stochastic approach. Also, the individual-based spatial model SMART was updated, and the outcomes of the spatial closures scenarios was used to parameterise the spatial scenarios in BEMTOOL. Finally, the simpler NIMED model was also updated and run, but its results were not compared to the two other models. In EMU 1, the IAM model (hake alone) was used to perform 3 runs of effort reduction, one of them including a French proposal for a spatial closure in the Gulf of Lion. Finally, a 3-pages synthetic advice is proposed, summarising the key findings of the simulations. A key outcome is that the proposed closure of the coastal zone down to 100 m deep, max 6nm from the shore, is unlikely to contribute to reducing hake catches. Rather, it can have an adverse effect if the fleets reallocate their effort further away where important concentrations of juvenile exists. In the light of the F-E relationships analyses, all results presented in this report are considered to be overoptimistic since they assume a true reduction in F if effort decreases, which may in reality be limited during the first years of effort reduction

Do changes in environmental and fishing pressures impact marine communities? An empirical assessment. Journal of Applied Ecology

The development of ecosystem approaches to environmental management implies the need to account for multiple pressures on ecosystems. Trends in multiple metrics that respond differently to changes in major environmental pressures need to be combined to evaluate the impacts of fishing and environmental changes on fish communities. 2. An exploited fish community is viewed as a three-level food chain in which the two upper levels, or functional groups, are targeted by fishing fleets, while the lowest level is subject to environmental variation. Qualitative modelling is used to predict changes at the two upper levels, that is, top-down vs. bottom-up perturbations. Abundance and length metrics are calculated from survey data for 14 Mediterranean and East-Atlantic groundfish shelf communities at both population and functional group levels. The joint likelihood of time trends in metrics is used to evaluate the evidence for different causes of changes. 3. A wide diversity of impacts is found to have equal evidence at the population level within each community. Consistency between the impacts identified and changes in pressures known from independent information is found at the functional group and community level. The results suggest that there is some compensation between species within functional groups. 4. Synthesis and applications. The method can be used to conduct an integrated assessment of community dynamics subject to multiple pressures. Joint trends in metrics provide evidence of which known pressures are having an impact on the community, and thus, which management actions should be taken to mitigate these changes

Spearman rank correlation coefficients calculated between all the diversity indices.

<p>All correlations are significantly different from zero (with <i>p</i><0.01), except for underlined values. The Spearman coefficient distribution under null hypothesis was approximated by a normal distribution with mean equal to 0 and standard deviation equal to 1/√ (n–1). Codes of diversity indices are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066753#pone-0066753-t001" target="_blank">Table 1</a>.</p

Geographical pattern in species diversity.

<p>Box-plot for (A) 1/<i>d</i>, (B) Δ^*, (C) Δ⁺, (D) Λ⁺ at the scale of the basin (left column), and the biogeographical zones (right column). Basin and biogeographical zone codes as in Fig. 5 Codes of diversity indices are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066753#pone-0066753-t001" target="_blank">Table 1</a>.</p

General results for GAM models of diversity indices.

<p>Deviance for Null model. ΔDeviance for the General model (including all the three variables/factors) and for each of the separated factors/variables. df: degree of freedom. ns: non significant effect when <i>p</i> (> ΔDeviance) >0.01. Percentage of the deviance of diversity indices explained by the factors/variables studied are given in brackets.</p