An overview of the impacts of fishing on seabirds, including identifying future research directions

Knowledge of fisheries impacts, past and present, is essential for understanding the ecology and conservation of seabirds, but in a rapidly changing world, knowledge and research directions require updating. In this Introduction and in the articles in this Themed Set “Impacts of fishing on seabirds”, we update our understanding of how fishing impacts seabird communities and identify areas for future research. Despite awareness of the problems and mitigation efforts for >20 years, fisheries still negatively impact seabirds via the effects of bycatch, competition, and discards. Bycatch continues to kill hundreds of thousands of seabirds annually, with negative population-level consequences. Fisheries for forage fish (e.g. anchovy, sandeel, and krill) negatively impact seabirds by competing for the same stocks. Historically, discards supplemented seabird diets, benefitting some species but also increasing bycatch rates and altering seabird community composition. However, declining discard production has led to potentially deleterious diet switches, but reduced bycatch rates. To improve research into these problems, we make the following recommendations: (1) improve data collection on seabird–vessel interaction and bycatch rates, on fishing effort and vessel movements (especially small-scale fleets), and on mitigation compliance, (2) counter the current bias towards temperate and high-latitude ecosystems, larger-bodied species and particular life stages or times of year (e.g. adults during breeding), and (3) advance our currently poor understanding of combined effects of fisheries and other threats (e.g. climate change, offshore renewables). In addition, research is required on under-studied aspects of fishing impacts: consequences for depleted sub-surface predators, impacts of illegal, unreported and unregulated fishing, artisanal and emerging fisheries, such as those targeting mesopelagic fish, have received insufficient research attention. Some of these shortfalls can be overcome with new tools (e.g. electronic monitoring, remote sensing, artificial intelligence, and big data) but quantifying and addressing fishing impacts on seabirds requires greater research investment at appropriate spatio-temporal scales, and more inclusive dialogue from grassroots to national and international levels to improve governance as fishing industries continue to evolve

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Localization of Large ADP-Ribosylation Factor-Guanine Nucleotide Exchange Factors to Different Golgi Compartments: Evidence for Distinct Functions in Protein Traffic

Activation of several ADP-ribosylation factors (ARFs) by guanine nucleotide exchange factors (GEFs) regulates recruitment of coat proteins (COPs) on the Golgi complex and is generally assumed to be the target of brefeldin A (BFA). The large ARF-GEFs Golgi-specific BFA resistance factor 1 (GBF1) and BFA-inhibited GEFs (BIGs) localize to this organelle but catalyze exchange preferentially on class II and class I ARFs, respectively. We now demonstrate using quantitative confocal microscopy that these GEFs show a very limited overlap with each other (15 and 23%). In contrast, GBF1 colocalizes with the cis-marker p115 (86%), whereas BIGs overlap extensively with TGN38 (83%). Consistent with these distributions, GBF1, but not BIG1, partially relocalized to peripheral sites after incubation at 15°C. The new GBF1 structures represent peripheral vesicular tubular clusters (VTCs) because 88% of structures analyzed stained for both GBF1 and p115. Furthermore, as expected of VTCs, they rapidly reclustered to the Golgi complex in a microtubule-dependent manner upon warm-up. These observations suggest that GBF1 and BIGs activate distinct subclasses of ARFs in specific locations to regulate different types of reactions. In agreement with this possibility, COPI overlapped to a greater extent with GBF1 (64%) than BIG1 (31%), whereas clathrin showed limited overlap with BIG1, and virtually none with GBF1