Differences in demersal community structure and biomass size spectra within and outside the Maltese Fishery Management Zone (FMZ)

We examined the protection effect of a long-established fisheries protection zone by studying the demersal communities and the biomass size spectra of specific taxonomic groups. The results and the relevant management implications of the community analysis are discussed within the context of the MEDITS trawl survey program, from which the data was derived. The demersal fishery resources on the muddy bottoms of Maltese trawling grounds were found to be stratified in four main depth ranges: 83 to 166 m (outer continental shelf), 140 to 230 m (shelf break), 270 to 440 m (shallow slope), and 466 to 701 m (deep slope). Significant differences were detected between the inside and outside zones of the outer continental shelf. Stations from this stratum inside the protected zone had twice as much biomass as those outside as well as larger individuals of some species (e.g. elasmobranchs). The depth strata identified do not coincide with those sampled in existing trawl survey programmes in the Sicilian Channel, which were set up without reference to demersal assemblage structure and its relation to depth. It is therefore clear that characterisation of the biotic assemblages is important in order to obtain a better sampling representation of each depth-stratum/assemblage type, and this should be considered in the survey design.peer-reviewe

Estimating effective detection area of passive, static acoustic data loggers from playback experiments with cetacean vocalisations

The study was funded by the Federal Ministry for the Environment, Nature conservation and Nuclear Safety of Germany (FKZ: 0325238), Bangor University and supported by SeaMôr Wildlife Tours.1. Passive acoustic monitoring (PAM) is used for many vocal species. However, few studies have quantified the fraction of vocalisations captured, and how animal distance and sound source level affect detection probability. Quantifying the detection probability or effective detection area (EDA) of a recorder is a prerequisite for designing and implementing monitoring studies, and essential for estimating absolute density and abundance from PAM data. 2. We tested the detector performance of cetacean click loggers (C-PODs) using artificial and recorded harbour porpoise clicks played at a range of distances and source levels. Detection rate of individual clicks and click sequences (or click trains) was calculated. A Generalised Additive Model (GAM) was used to create a detection function and estimate the effective detection radius (EDR) and EDA for both types of signals. 3. Source level and distance from logger influenced the detection probability. Whilst differences between loggers were evident, detectability was influenced more by the deployment site than within-logger variability. Maximum distance for detecting real recorded porpoise clicks was 566 m. Mean EDR for artificial signals with source level 176 dB re 1 μPa @ 1m was 187 m., and for a recorded vocalisation with source level up to 182 dB re 1 μPa was 188 m. For detections classified as harbour porpoise click sequences the mean EDR was 72 m. 4. The analytical methods presented are a valid technique for estimating the EDA of any logger used in abundance estimates. We present a practical way to obtain data with a cetacean click logger, with the caveat that artificial playbacks cannot mimic real animal behaviour and are at best able to account for some of the variability in detections between sites, removing logger and propagation effects so that what remains is density and behavioural differences. If calibrated against real-world EDAs (e.g., from tagged animals) it is possible to estimate site-specific detection area and absolute density. We highlight the importance of accounting for both biological and environmental factors affecting vocalisations so that accurate estimates of detection area can be determined, and effective monitoring regimes implemented.PostprintPeer reviewe

Differences in biological traits composition of benthic assemblages between unimpacted habitats

There is an implicit requirement under contemporary policy drivers to understand the characteristics of benthic communities under anthropogenically-unimpacted scenarios. We used a trait-based approach on a large dataset from across the European shelf to determine how functional characteristics of unimpacted benthic assemblages vary between different sedimentary habitats. Assemblages in deep, muddy environments unaffected by anthropogenic disturbance show increased proportions of downward conveyors and surface deposit-feeders, while burrowing, diffusive mixing, scavenging and predation traits assume greater numerical proportions in shallower habitats. Deep, coarser sediments are numerically more dominated by sessile, upward conveyors and suspension feeders. In contrast, unimpacted assemblages of coarse sediments in shallower regions are proportionally dominated by the diffusive mixers, burrowers, scavengers and predators. Finally, assemblages of gravelly sediments exhibit a relatively greater numerical dominance of non-bioturbators and asexual reproducers. These findings may be used to form the basis of ranking habitats along a functional sensitivity gradient

Estimating the sustainability of towed fishing-gear impacts on seabed habitats: a simple quantitative risk assessment method applicable to data-limited fisheries

1. Impacts of bottom fishing, particularly trawling and dredging, on seabed (benthic) habitats are commonly perceived to pose serious environmental risks. Quantitative ecological risk assessment can be used to evaluate actual risks and to help guide the choice of management measures needed to meet sustainability objectives. 2. We develop and apply a quantitative method for assessing the risks to benthic habitats by towed bottom-fishing gears. The method is based on a simple equation for relative benthic status (RBS), derived by solving the logistic population growth equation for the equilibrium state. Estimating RBS requires only maps of fishing intensity and habitat type — and parameters for impact and recovery rates, which may be taken from meta-analyses of multiple experimental studies of towed-gear impacts. The aggregate status of habitats in an assessed region is indicated by the distribution of RBS values for the region. The application of RBS is illustrated for a tropical shrimp-trawl fishery. 3. The status of trawled habitats and their RBS value depend on impact rate (depletion per trawl), recovery rate and exposure to trawling. In the shrimp-trawl fishery region, gravel habitat was most sensitive, and though less exposed than sand or muddy-sand, was most affected overall (regional RBS=91% relative to un-trawled RBS=100%). Muddy-sand was less sensitive, and though relatively most exposed, was less affected overall (RBS=95%). Sand was most heavily trawled but least sensitive and least affected overall (RBS=98%). Region-wide, >94% of habitat area had >80% RBS because most trawling and impacts were confined to small areas. RBS was also applied to the region's benthic invertebrate communities with similar results. 4. Conclusions. Unlike qualitative or categorical trait-based risk assessments, the RBS method provides a quantitative estimate of status relative to an unimpacted baseline, with minimal requirements for input data. It could be applied to bottom-contact fisheries worldwide, including situations where detailed data on characteristics of seabed habitats, or the abundance of seabed fauna are not available. The approach supports assessment against sustainability criteria and evaluation of alternative management strategies (e.g. closed areas, effort management, gear modifications)

Stable isotope signatures reveal small-scale spatial separation in populations of European sea bass

Scientific information about European sea bass Dicentrarchus labrax stocks in the NE Atlantic is limited and a more accurate definition of the stock boundaries in the area is required to improve assessment and management advice. We investigated the connectivity and movement patterns of D. labrax in Wales (UK) using the stable isotope (δ13C and δ15N) composition of their scales. Analysis of δ13C and δ15N values in the last growing season was performed on 189 adult sea bass caught at 9 coastal feeding grounds. Fish >50 cm total length (TL) caught in estuaries had very low δ13C, which is characteristic of freshwater (organic/soil) input, indicating the primary use of estuaries as feeding areas. A random forest classification model was used to test for any differences in δ15N and δ13C values between north, mid and south Wales and whether it was possible to correctly assign a fish to the area where it was caught. This analysis was restricted to fish of a similar size (40-50 cm TL) caught in open coastal areas (n = 156). The classification model showed that about 75% of the fish could be correctly assigned to their collection region based on their isotope composition. The majority of the misclassifications of fish were of fish from north Wales classifying to mid Wales and vice versa, while the majority of fish from south Wales were correctly assigned (80%). Our findings suggest that 2 sub-populations of sea bass in Welsh waters use separate feeding grounds (south vs. mid/north Wales), and may need separate management

Predicting the Impact of Climate Change on Threatened Species in UK Waters

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina)

Trawl fishing impacts on the status of seabed fauna in diverse regions of the globe

Bottom trawl fishing is a controversial activity. It yields about a quarter of the world's wild seafood, but also has impacts on the marine environment. Recent advances have quantified and improved understanding of large-scale impacts of trawling on the seabed. However, such information needs to be coupled with distributions of benthic invertebrates (benthos) to assess whether these populations are being sustained under current trawling regimes. This study collated data from 13 diverse regions of the globe spanning four continents. Within each region, we combined trawl intensity distributions and predicted abundance distributions of benthos groups with impact and recovery parameters for taxonomic classes in a risk assessment model to estimate benthos status. The exposure of 220 predicted benthos-group distributions to trawling intensity (as swept area ratio) ranged between 0% and 210% (mean = 37%) of abundance. However, benthos status, an indicator of the depleted abundance under chronic trawling pressure as a proportion of untrawled state, ranged between 0.86 and 1 (mean = 0.99), with 78% of benthos groups > 0.95. Mean benthos status was lowest in regions of Europe and Africa, and for taxonomic classes Bivalvia and Gastropoda. Our results demonstrate that while spatial overlap studies can help infer general patterns of potential risk, actual risks cannot be evaluated without using an assessment model that incorporates trawl impact and recovery metrics. These quantitative outputs are essential for sustainability assessments, and together with reference points and thresholds, can help managers ensure use of the marine environment is sustainable under the ecosystem approach to management

Prioritization of knowledge-needs to achieve best practices for bottom trawling in relation to seabed habitats

Management and technical approaches that achieve a sustainable level of fish production while at the same time minimizing or limiting the wider ecological effects caused through fishing gear contact with the seabed might be considered to be ‘best practice’. To identify future knowledge-needs that would help to support a transition towards the adoption of best practices for trawling, a prioritization exercise was undertaken with a group of 39 practitioners from the seafood industry and management, and 13 research scientists who have an active research interest in bottom-trawl and dredge fisheries. A list of 108 knowledge-needs related to trawl and dredge fisheries was developed in conjunction with an ‘expert task force’. The long list was further refined through a three stage process of voting and scoring, including discussions of each knowledge-need. The top 25 knowledge-needs are presented, as scored separately by practitioners and scientists. There was considerable consistency in the priorities identified by these two groups. The top priority knowledge-need to improve current understanding on the distribution and extent of different habitat types also reinforced the concomitant need for the provision and access to data on the spatial and temporal distribution of all forms of towed bottom-fishing activities. Many of the other top 25 knowledge-needs concerned the evaluation of different management approaches or implementation of different fishing practices, particularly those that explore trade-offs between effects of bottom trawling on biodiversity and ecosystem services and the benefits of fish production as food.Fil: Kaiser, Michel J.. Bangor University; Reino UnidoFil: Hilborn, Ray. University of Washington; Estados UnidosFil: Jennings, Simon. Fisheries and Aquaculture Science; Reino UnidoFil: Amaroso, Ricky. University of Washington; Estados UnidosFil: Andersen, Michael. Danish Fishermen; DinamarcaFil: Balliet, Kris. Sustainable Fisheries Partnership; Estados UnidosFil: Barratt, Eric. Sanford Limited; Nueva ZelandaFil: Bergstad, Odd A. Institute of Marine Research; NoruegaFil: Bishop, Stephen. Independent Fisheries Ltd; Nueva ZelandaFil: Bostrom, Jodi L. Marine Stewardship Council; Reino UnidoFil: Boyd, Catherine. Clearwater Seafoods; CanadáFil: Bruce, Eduardo A. Friosur S.A.; ChileFil: Burden, Merrick. Marine Conservation Alliance; Estados UnidosFil: Carey, Chris. Independent Fisheries Ltd.; Estados UnidosFil: Clermont, Jason. New England Aquarium; Estados UnidosFil: Collie, Jeremy S. University of Rhode Island,; Estados UnidosFil: Delahunty, Antony. National Federation of Fishermen; Reino UnidoFil: Dixon, Jacqui. Pacific Andes International Holdings Limited; ChinaFil: Eayrs, Steve. Gulf of Maine Research Institute; Estados UnidosFil: Edwards, Nigel. Seachill Ltd.; Reino UnidoFil: Fujita, Rod. Environmental Defense Fund; Reino UnidoFil: Gauvin, John. Alaska Seafood Cooperative; Estados UnidosFil: Gleason, Mary. The Nature Conservancy; Estados UnidosFil: Harris, Brad. Alaska Pacific University; Estados UnidosFil: He, Pingguo. University of Massachusetts Dartmouth; Estados UnidosFil: Hiddink, Jan G. Bangor University; Reino UnidoFil: Hughes, Kathryn M. Bangor University; Reino UnidoFil: Inostroza, Mario. EMDEPES; ChileFil: Kenny, Andrew. Fisheries and Aquaculture Science; Reino UnidoFil: Kritzer, Jake. Environmental Defense Fund; Estados UnidosFil: Kuntzsch, Volker. Sanford Limited; Estados UnidosFil: Lasta, Mario. Diag. Montegrande N° 7078. Mar del Plata; ArgentinaFil: Lopez, Ivan. Confederacion Española de Pesca; EspañaFil: Loveridge, Craig. South Pacific Regional Fisheries Management Organisation; Nueva ZelandaFil: Lynch, Don. Gorton; Estados UnidosFil: Masters, Jim. Marine Conservation Society; Reino UnidoFil: Mazor, Tessa. CSIRO Marine and Atmospheric Research; AustraliaFil: McConnaughey, Robert A. US National Marine Fisheries Service; Estados UnidosFil: Moenne, Marcel. Pacificblu; ChileFil: Francis. Marine Scotland Science; Reino UnidoFil: Nimick, Aileen M. Alaska Pacific University; Estados UnidosFil: Olsen, Alex. A. Espersen; DinamarcaFil: Parker, David. Young; Reino UnidoFil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Penney, Christine. Clearwater Seafoods; CanadáFil: Pierce, David. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Pitcher, Roland. CSIRO Marine and Atmospheric Research; AustraliaFil: Pol, Michael. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Richardson, Ed. Pollock Conservation Cooperative; Estados UnidosFil: Rijnsdorp, Adriaan D. Wageningen IMARES; Países BajosFil: Rilatt, Simon. A. Espersen; DinamarcaFil: Rodmell, Dale P. National Federation of Fishermen's Organisations; Reino UnidoFil: Rose, Craig. FishNext Research; Estados UnidosFil: Sethi, Suresh A. Alaska Pacific University; Estados UnidosFil: Short, Katherine. F.L.O.W. Collaborative; Nueva ZelandaFil: Suuronen, Petri. Fisheries and Aquaculture Department; ItaliaFil: Taylor, Erin. New England Aquarium; Estados UnidosFil: Wallace, Scott. The David Suzuki Foundation; CanadáFil: Webb, Lisa. Gorton's Inc.; Estados UnidosFil: Wickham, Eric. Unit four –1957 McNicoll Avenue; CanadáFil: Wilding, Sam R. Monterey Bay Aquarium; Estados UnidosFil: Wilson, Ashley. Department for Environment; Reino UnidoFil: Winger, Paul. Memorial University Of Newfoundland; CanadáFil: Sutherland, William J. University of Cambridge; Reino Unid

Models of marine fish biodiversity : assessing predictors from three habitat classification schemes

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modeling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modeling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability