Search

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high-quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID-19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land- vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal ( i.e., farm-site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 Elsevier Ltd. All rights reserved.)

This study aimed at providing confidence in the predictability of the impacts of drill cuttings (DC) discharge on the cold-water coral Lophelia pertusa. L. pertusa was exposed to DC from offshore exploration in the lab with the goal to assess precautionary thresholds of effects. Two exposure scenarios with DC were tested: a long-term (LT) pulsed exposure (12 weeks, peak concentrations: 2-50 mg/L, mean concentrations: 1-25 mg/L) and a short-term (ST) continuous exposure (2.5 weeks, mean concentrations: 4-42 mg/L). After exposure, a recovery period of 16 and 4 weeks was maintained in LT and ST, respectively. While there was an assumption that DC might result in an increase in respiration, decrease in growth, enhanced mucus production, reduced fatty acid content, only a significant rise was noted in skeleton growth at DC 4 mg/L and a significant increase of mucus particulate organic carbon at 25 mg/L at end of the exposure. DC did not markedly reduce prey capture rate consecutive to DC exposure. However, the effect of DC produced an increase of coral polyp activity during exposure and a return to pre-exposure conditions after cessation of DC, and coenosarc was smothered from DC even after a long recovery period (4 weeks). Overall, a DC concentration of 10 mg/L seems to represent a threshold above which changes in coral conditions were observed however with no apparent physiological consequences for the coral within the experimental time scale.

Rising oil and gas activities in northern high latitudes have led to an increased risk of petroleum pollution in these ecosystems. Further, seasonal high UV radiation at high latitudes may elevate photo-enhanced toxicity of petroleum pollution to marine organisms. Zooplanktons are a key ecological component of northern ecosystems; therefore, it is important to assess their sensitivity to potential pollutants of oil and gas activity. As ontogenetic development may be particularly sensitive, the aim of this study was to examine the impact of chronic exposure to oil water dispersion (OWD) on development and feeding of early life stages of the Northern krill, Meganyctiphanes norvegica. In a range of experiments, embryonic, nonfeeding, and feeding larval stages were exposed to concentrations of between 0.01 and 0.1 mg/L of oil or photo-modified oil for 19 and 21 d. No significant effects on egg respiration, hatching success, development, length and larval survival were observed from these treatments. Similarly, evolution of fatty acid composition patterns during ontogenetic development was unaffected. The results indicates a high degree of resilience of these early developmental stages to such types and concentrations of pollutants. However, feeding and motility in later calyptopis-stage larvae were significantly impaired at exposure of 0.1 mg/L oil. Data indicate that feeding larval stage of krill was more sensitive to OWD than early nonfeeding life stages. This might be attributed to the narcotic effects of oil pollutants, their direct ingestion, or accumulated adverse effects over early development.

Despite the importance of the cold-water coral Lophelia pertusa to deep-sea reef ecosystem functioning, current knowledge of key physiological responses to available food resources is scarce. Scenarios with varying food density may help to understand how corals deal with seasonal variations in the dark ocean and might be used to study consequences of anthropogenic activities potentially affecting food availability. Thus, the physiological responses of L. pertusa to varying food (Artemia salina nauplii) concentration, ranging from 20% to 300% of carbon equivalent turned over by basal coral respiration, were investigated. A starvation group was also included. Measurements of respiration, growth, mucus production, and energy reserves (storage fatty acids) were performed at several time intervals over 26 weeks. In general, data showed a stronger effect of experimental time on measured responses, but no significant influence of food density treatment. In starved corals, respiration rate declined to 52% of initial respiration, while skeleton growth rate was maintained at the same rate as Artemia-fed corals throughout the investigation. Mucus production measured as the sum of dissolved organic carbon (DOC) and particulate organic carbon (POC) was also similar across food treatments, but POC production exceeded that of DOC at the highest food density. No marked effect was observed on storage fatty acids. These results confirm that L. pertusa is highly resilient to environmental conditions with suboptimal food densities over a time scale of months. Regulation of several physiological processes, including respiration and mucus production, possibly in combination with an opportunistic feeding strategy, contributed to this tolerance to maintain viable corals. Thus, it appears that L. pertusa is well adapted to life in the deep sea.

Mass mortality events caused by pulse anthropogenic or environmental perturbations (e.g., extreme weather, toxic spills or epizootics) severely reduce the abundance of a population in a short time. The frequency and impact of these events are likely to increase across the globe. Studies on how such events may affect ecological communities of interacting species are scarce. By combining a multispecies Gompertz model with a Bayesian state-space framework, we quantify community-level effects of a mass mortality event in a single species. We present a case study on a community of fish and zooplankton in the Barents Sea to illustrate how a mass mortality event of different intensities affecting the lower trophic level (krill) may propagate to higher trophic levels (capelin and cod). This approach is especially valuable for assessing community-level effects of potential anthropogenic-driven mass mortality events, owing to the ability to account for uncertainty in the assessed impact due to uncertainty about the ecological dynamics. We hence quantify how the assessed impact of a mass mortality event depends on the degree of precaution considered. We suggest that this approach can be useful for assessing the possible detrimental outcomes of toxic spills, for example oil spills, in relatively simple communities such as often found in the Arctic, a region under increasing influence of human activities due to increased land and sea use., (© 2016 John Wiley & Sons Ltd.)

Ecological impact assessment modeling systems are valuable support tools for managing impacts from commercial activities on marine habitats and species. The inclusion of toxic effects modeling in these systems is predicated on the availability and quality of ecotoxicology data. Here we report on a data gathering exercise to obtain toxic effects data on oil compounds for a selection of cold-water marine species of fish and plankton associated with the Barents Sea ecosystem. Effects data were collated from historical and contemporary literature resources for the endpoints mortality, development, growth, bioaccumulation and reproduction. Evaluating the utility and applicability of these data for modeling, we find that data coverage is limited to a sub-set of the required endpoints. There is a need for new experimental studies for zooplankton focused on the endpoints development and bioaccumulation and for larvae and juvenile fish focused on growth and development., (Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This paper describes the methodology of building a predictive model for the purpose of marine pollution monitoring, based on low quality biomarker data. A step-by-step, systematic data analysis approach is presented, resulting in design of a purely data-driven model, able to accurately discriminate between various coastal water pollution levels. The environmental scientists often try to apply various machine learning techniques to their data without much success, mostly because of the lack of experience with different methods and required 'under the hood' knowledge. Thus this paper is a result of a collaboration between the machine learning and environmental science communities, presenting a predictive model development workflow, as well as discussing and addressing potential pitfalls and difficulties. The novelty of the modelling approach presented lays in successful application of machine learning techniques to high dimensional, incomplete biomarker data, which to our knowledge has not been done before and is the result of close collaboration between machine learning and environmental science communities.

Inhaled nitric oxide (NO) has been recently proposed as a new treatment in newborns and children with severe hypoxemic respiratory failure. Differently from other vasodilators, inhaled nitric oxide selectively lowers pulmonary vascular resistance and pulmonary arterial pressure, and improves the ventilation/perfusion matching by directing pulmonary blood flow toward better ventilated areas, ultimately improving systemic oxygenation. In our experience, we have observed that inhaled NO may acutely ameliorate gas exchange in patients with severe respiratory failure. This may allow a reduction of both ventilatory parameters and fraction of inspired oxygen, thus limiting further damage to the lungs. Nonetheless, the underlying disease and the clinical conditions before NO treatment seem to maintain a crucial role in the ultimate prognosis of these patients. Further studies are needed in order to better define indications, dosages, and safety of nitric oxide treatment, and to verify its authentic prognostic value in neonates and children with acute respiratory failure.