Abstract Stakeholders need scientific advice on the environmental impacts of offshore wind (OW) before the facilities are installed. The utility of conventional environmental monitoring methods as a basis for forecasting OW impacts is limited because they do not explain the causes of the observed effects. We propose a multistep approach, based on process-oriented hypothesis testing, targeted monitoring and numerical modeling, to answer key stakeholder questions about planning an OW facility: Q1—Where do we place future OW farms so that impacts on the ecosystem are minimized? Q2—Which species and ecosystem processes will be impacted and to what degree? Q3—Can we mitigate impacts and, if so, how? and Q4—What are the risks of placing an OW facility in one location vs. another? Hypothesis testing can be used to assess impacts of OW facilities on target species-ecological process. This knowledge is transferable and is broadly applicable, a priori, to assess suitable locations for OW (Q1). Hypothesis testing can be combined with monitoring methods to guide targeted monitoring. The knowledge generated can identify the species/habitats at risk (Q2), help selecting/developing mitigation measures (Q3), and be used as input parameters for models to forecast OW impacts at a large spatial scale (Q1; Q4).

Abstract After three decades of working as a research scientist, I am stepping back to consider the events, questions, and principles that have guided my scientific journey. Important questions and research objectives have been how to implement the ecosystem approach to fisheries management in practice, the development of new data uses, the application of new observation methods and models, and estimating and accounting for uncertainty. Stakeholder engagement—why and how—is a topic that has increased in importance over time. While our observation methods did not change much over many decades, they are now changing rapidly due to new technological developments, but also societal and environmental changes.

Abstract Identifying isolated populations is a key step towards enacting effective conservation management. European lobsters (Homarus gammarus) from Oosterschelde in the Netherlands are subject to fishery pressure and have previously been reported as genetically differentiated. They are also putatively of transplanted origin and have subsequently endured recent bottlenecking and environmental change. We assessed Oosterschelde lobsters to evaluate their demographic independence and appraise potential founder effects and evolutionary responses to isolation. Using restriction-site associated DNA sequencing, we genotyped 6185 single nucleotide polymorphisms across 188 individuals from 27 sites across the Atlantic range of H. gammarus to investigate population genetic diversity, structure, and potential adaptation. Our results show that Oosterschelde lobsters are genetically divergent from other stocks. We evidence extensive differentiation via both neutral and outlier loci, indicative of strong biophysical and demographic isolation, and detect signatures of reduced genetic diversity that may reflect weak founder effects or subsequent population contractions. Among outlier loci, we identify candidates for range-wide local adaptation via variants in genes of important biological functionality and link a private allele of Oosterschelde to a locus potentially conveying adaptive tolerance to environmental hypoxia. Given our findings, we advise proactive monitoring of Oosterschelde lobsters to explore whether existing management measures effectively conserve this discrete, self-recruiting population.

Abstract Distance sampling surveys are extensively used to estimate the abundance of wide-ranging species but are prone to detection biases. This may be particularly acute for strip-transect protocols, which assume perfect detection. We examined this assumption by quantifying the detection probability of a declining seabird (Scopoli’s shearwater, Calonectris diomedea), with particular attention to time of day and observation conditions at sea. We found detection probability was negatively affected by sun glare but positively by cloud cover and considerably dropped during mid-day hours due to circadian changes in behaviour (reduced detectability while resting). This result urges for systematically assessing and correcting detection bias when using strip-transect data to derive abundance information. Here, we did so by building a detection-corrected presence-absence ensemble model and combining it with a compilation of colony sizes and locations. A Monte-Carlo simulation ensured uncertainty propagation within and across data sources. The corrected abundance map showed shearwaters were largely prevalent in the central Mediterranean, Tunisia hosting most of the population both at sea and at colonies (45% of the global population; 79% of breeding pairs). This first accurate map is an essential conservation tool, emphasizing the importance of transnational actions for such species, that know no political boundaries.

Abstract Offshore wind farms have recently emerged as a renewable energy solution. However, the long-term impacts of wind turbine noise on fish chorusing phenology are largely unknown. We deployed a hydrophone 10 m from a foremost turbine in Taiwan situated at the Miaoli offshore wind farm (Taiwan Strait) for two years to investigate sound levels and assess the potential influence of turbine noise on seasonal fish chorusing patterns during 2017 and 2018. Wind turbine noise (measured in the 20–250 Hz frequency band) was significantly higher in autumn and winter (mean SPL: 138–143 dB re 1 μPa) and was highly correlated with wind speed (r = 0.76, P < 0.001). During both years, fish chorusing exhibited a consistent trend, that is, beginning in spring, peaking in summer, decreasing in autumn, and absent in winter. Our results show the noise from a single turbine during the two-year monitoring period did not influence the seasonal fish chorusing (r = −0.17, P ≈ 1). Since the offshore wind farm installations are growing in magnitude and capacity across the Taiwan Strait, this study for the first time provides baseline operational sound levels and an understanding of the fish seasonal vocalization behavior at the foremost turbine of the first wind farm in Taiwan. The results presented here provide useful insights for policymakers and constitute a reference starting point for advancing knowledge on the possible effects of wind turbines on fish chorusing in the studied area.

Abstract In marine species with large populations and high dispersal potential, large-scale genetic differences and clinal trends in allele frequency can provide insight into the evolutionary processes that shape diversity. Lumpfish, Cyclopterus lumpus, is found throughout the North Atlantic and has traditionally been harvested for roe and more recently used as a cleaner fish in salmon aquaculture. We used a 70 K SNP array to evaluate trans-Atlantic differentiation, genetic structuring, and clinal variation across the North Atlantic. Basin-scale structuring between the Northeast and Northwest Atlantic was significant, with enrichment for loci associated with developmental/mitochondrial function. We identified a putative structural variant on chromosome 2, likely contributing to differentiation between Northeast and Northwest Atlantic Lumpfish, and consistent with post-glacial trans-Atlantic secondary contact. Redundancy analysis identified climate associations both in the Northeast (N = 1269 loci) and Northwest (N = 1637 loci), with 103 shared loci between them. Clinal patterns in allele frequencies were observed in some loci (15%—Northwest and 5%—Northeast) of which 708 loci were shared and involved with growth, developmental processes, and locomotion. The combined evidence of trans-Atlantic differentiation, environmental associations, and clinal loci, suggests that both regional and large-scale potentially-adaptive population structuring is present across the North Atlantic.

Abstract The greater argentine is a benthopelagic fish with a northern amphi-Atlantic and southern Arctic distribution. Landings of this species have been steadily increasing since the early 2000s, mainly for ultra-processed fish food. The rising economic importance of this species begs for an accurate delineation of the management units needed to ensure the sustainability of the fishery. The alignment between management and biological units was investigated on three of the ICES stocks in the NE Atlantic (123a4, 5a14, and 5b6a) by genotyping 88 ad hoc-developed SNPs on 1299 individuals sampled along the Norwegian coast, north of Shetland, around the Faroe Islands, and in the Denmark Strait within Icelandic waters. Candidate loci to positive selection were particularly crucial for units’ delineation and supported the current ICES 5b6a and 5a14 stocks around the Faroe Islands and Iceland, respectively. However, within the third stock investigated, 123a4, which corresponded mainly to the Norwegian coast, the sample from area 3a (Skagerrak) was significantly different from all the remaining in the same stock. This differentiation advocates for reconsideration of the present policy and suggests considering ICES Area 3a (Skagerrak) as an independent management unit. The environmental conditions in the Skagerrak area have left a genetic print on other marine taxa, which could putatively be the case in the greater argentine.

Abstract Estimating changes in the biomass of a fish stock is crucial for successful management. However, fishery assessment may be affected by the quality of the inputs used in stock assessment models. Survey biomass indices derived from fishery-independent and catch per unit effort (CPUE) biomass indices derived from fishery-dependent data are key inputs for model calibration. These indices have biases that could compromise the accuracy of the stock assessment models results. Therefore, there are plenty proposed methods to standardize survey or CPUE biomass data. From simpler models like generalized linear models (GLMs) to more complex models that take into account spatio-temporal correlation, like geostatistical models, and sampling dependence, like marked point processes. But many of them do not consider the underlying spatio-temporal or sampling dependence of these data. Hence, the goal of the study is to present a spatio-temporal simulation and Bayesian modeling framework to assess the impact of applying models that do not consider spatio-temporal and sampling dependence. Results indicate that geostatistical models and marked point processes achieve the lowest measures of error. Hence, to capture the underlying spatio-temporal process of the survey and CPUE biomass indices and data sampling preferentiality, it is essential to apply models that consider the spatio-temporal and sampling dependence.

Abstract We build on previous research describing correlative links between changes in the abundance of the copepod Calanus finmarchicus, a foundational zooplankton species of the pelagic food web, and diminishing recruitment of young-of-year American lobster (Homarus americanus) to benthic nurseries in the Gulf of Maine. Using parallel 31-year time series of lobster larvae and zooplankton collected on the New Hampshire coast between 1988 and 2018, we investigated how changes in phenology of stage I larval lobster and their putative copepod prey, C. finmarchicus, affect their temporal overlap and potential to interact during the larval season. We found that over the time series both the lobster egg hatch and first appearance of larvae began earlier in the season, a trend significantly correlated with ocean warming. The last appearance of larvae in late summer has been delayed, however, thereby extending the larval season. Even with the longer larval lobster season, the C. finmarchicus season has increasingly been ending before the peak abundance of stage I lobster larvae. The net effect is a widening mismatch in phenology of the two species, an outcome consistent with the hypothesis that changes in abundance and phenology of C. finmarchicus have contributed to recent declines in lobster recruitment.