Life cycle assessment of European anchovy (Engraulis encrasicolus) landed by purse seine vessels in northern Spain

Purpose: The main purpose of this article is to assess the environmental impacts associated with the fishing operations related to European anchovy fishing in Cantabria (northern Spain) under a life cycle approach. Methods: The life cycle assessment (LCA) methodology was applied for this case study including construction, maintenance, use, and end of life of the vessels. The functional unit used was 1 kg of landed round anchovy at port. Inventory data were collected for the main inputs and outputs of 32 vessels, representing a majority of vessels in the fleet. Results and discussion: Results indicated, in a similar line to what is reported in the literature, that the production, transportation, and use of diesel were the main environmental hot spots in conventional impact categories. Moreover, in this case, the production and transportation of seine nets was also relevant. Impacts linked to greenhouse gas (GHG) emissions suggest that emissions were in the upper range for fishing species captured with seine nets and the value of global warming potential (GWP) was 1.44 kg CO2 eq per functional unit. The ecotoxicity impacts were mainly due to the emissions of antifouling substances to the ocean. Regarding fishery-specific categories, many were discarded given the lack of detailed stock assessments for this fishery. Hence, only the biotic resource use category was computed, demonstrating that the ecosystems' effort to sustain the fishery is relatively low. Conclusions: The use of the LCA methodology allowed identifying the main environmental hot spots of the purse seining fleet targeting European anchovy in Cantabria. Individualized results per port or per vessel suggested that there are significant differences in GHG emissions between groups. In addition, fuel use is high when compared to similar fisheries. Therefore, research needs to be undertaken to identify why fuel use is so high, particularly if it is related to biomass and fisheries management or if skipper decisions could play a role.The authors thank the Ministry of Economy and Competitiveness of the Spanish Government for their financial support via the project GeSAC-Conserva: Sustainable Management of the Cantabrian Anchovies (CTM2013-43539-R) and to Pedro Villanueva-Rey for valuable scientific exchange. Jara Laso thanks the Ministry of Economy and Competitiveness of Spanish Government for their financial support via the research fellowship BES-2014-069368 and to the Ministry of Rural Environment, Fisheries and Food of Cantabria for the data support. Dr. Ian Vázquez-Rowe thanks the Peruvian LCA Network for operational support. Reviewers are also thanked for the valuable and detailed suggestions. The work of Dr. Rosa M. Crujeiras has been funded by MTM2016-76969P (AEI/FEDER, UE)

Biodegradable DFADs: Current Status and Prospects

Until recently, dFAD structure, materials and designs have remained quite rudimentary and virtually the same since their discovery, characterized by the increase of the dimensions and prevailing heavy use of plastic components. Biodegradable materials are called to be an important part of the solution, as they can faster degrade in the environment, free of toxins and heavy metals, reducing their lifespan, and preventing them from accumulating in sensitive areas once they are abandoned, lost or discarded. During last decades, regulatory measures at tRFMOs have advanced in the gradual implementation of biodegradable materials in dFAD constructions together with other measures limiting the number of active dFADs and the use of netting materials. However, more clarity is needed starting with a standardised definition of biodegradable dFADs among tRFMOs, to provide operational guidance. Research with those natural and synthetic materials is required, along with updated data collection for monitoring standards, as well as alternative and complementary actions need to be explored to contribute to minimising dFAD adverse effects on environment. Acknowledging the current difficulties for the implementation of fully biodegradable dFADs a stepwise process towards the implementation of fully biodegradable dFADs should be considered

Kernel-based support vector machines for automated health status assessment in monitoring sensor data

Publisher Copyright: © 2017, Springer-Verlag London Ltd.This paper presents a novel algorithm to assess the health status in monitoring sensor data using a kernel-based support vector machine (SVM) approach. Today, accurate fault prediction is a key issue raised by maintenance. In particular, automatically modelling the normal behaviour from condition monitoring data is probably one of the most challenging problems, specially when there is limited information of real faults. To overcome this difficulty, a data-driven learning framework based on nonparametric density estimation for outlier detection and ν-SVM for normality modelling, with optimal bandwidth selection, is proposed. A health score based on the log-normalisation of the distance to the separating hyperplane is also provided. Experimental results obtained when analysing the propagation of a critical fault over time in a marine diesel engine demonstrate the validity of the algorithm. The predictions of normality models learned were compared to those of the k-nearest neighbours (kNN) method. Low false positive rates on healthy data and improved prediction capacities are achieved.Peer reviewe

A computational approach to managing coupled human–environmental systems: the POSEIDON model of ocean fisheries

Sustainable management of complex human–environment systems, and the essential services they provide, remains a major challenge, felt from local to global scales. These systems are typically highly dynamic and hard to predict, particularly in the context of rapid environmental change, where novel sets of conditions drive coupled socio-economic-environmental responses. Faced with these challenges, our tools for policy development, while informed by the past experience, must not be unduly constrained; they must allow equally for both the fine-tuning of successful existing approaches and the generation of novel ones in unbiased ways. We study ocean fisheries as an example class of complex human–environmental systems, and present a new model (POSEIDON) and computational approach to policy design. The model includes an adaptive agent-based representation of a fishing fleet, coupled to a simplified ocean ecology model. The agents (fishing boats) do not have programmed responses based on empirical data, but respond adaptively, as a group, to their environment (including policy constraints). This conceptual model captures qualitatively a wide range of empirically observed fleet behaviour, in response to a broad set of policies. Within this framework, we define policy objectives (of arbitrary complexity) and use Bayesian optimization over multiple model runs to find policy parameters that best meet the goals. The trade-offs inherent in this approach are explored explicitly. Taking this further, optimization is used to generate novel hybrid policies. We illustrate this approach using simulated examples, in which policy prescriptions generated by our computational methods are counterintuitive and thus unlikely to be identified by conventional frameworks