Development of habitat models for Nephtys species (Polychaeta: Nephtyidae) in the German Bight (North Sea)

The aim of the study was the development of habitat models for Nephtys species (Polychaeta: Nephtyidae). The investigation area was the German Bight, the southeastern part of the North Sea. Models were developed based on field data collected between 2000 and 2006. In addition, data on environmental variables were retrieved from long-term monitoring data sets and from the sediment map by Figge [Figge, K., 1981. Nordsee. Sedimentverteilung in der Deutschen Bucht. Map No. 2900. Publisher: Deutsches Hydrographisches Institut, Hamburg]. The statistical modelling technique used was multivariate adaptive regression splines (MARS). Models were fitted individually for each species. Evaluation of predictive discrimination and predictive accuracy of the developed models was by calculation of the area under the receiver operating curve (AUC) or sensitivity and specificity, respectively. Habitat models with best predictive fit were selected for the presentation of habitat suitability maps.Six Nepthys species were found: Nephtys assimilis, N. caeca, N. cirrosa, N. hombergii, N. incisa and N. longosetosa. N. hombergii was most common whereas N. incisa and N. longosetosa were rare. Habitat preferences varied considerably among the species. For all investigated Nephtys species except N. longosetosa a habitat model could be developed based on four predictor variables. The habitat models with best predictive fit were those for N. cirrosa and N. hombergii. The N. caeca habitat model was of limited predictive accuracy and only accept predictive discrimination. The number of predictors as well as the relative importance of the respective predictors in the model varied among the different species. Direct comparison of most suitable habitats for the different species based on modelling revealed that in the mostly sandy regions parallel to the German coast in water depths up to 20 m an overlap between N. caeca, N. hombergii and N. cirrosa exists. In the deeper central German Bight with mostly fine sands with increased mud contents N. hombergii, N. assimilis and, at least partially and rare in numbers, N. incisa co-occur. It can be concluded that important sediment characteristics like grain size median and mud content as well as water depth and mean salinity are useful parameters to describe the habitat requirements of most Nepthys species in the German Bight. However, additional variables need to be incorporated into such analyses.     

Spatial distribution patterns of the peppery furrow shell Scrobicularia plana (da Costa, 1778) along the European coast: A review

The bivalve Scrobicularia plana is an important species of shallow water benthic communities with a wide geographic distribution but also with a general patchy pattern, i.e. irregular in occurrence and in density. This review aims to determine the processes responsible for the species' spatial distribution pattern based on the available information on S. plana. Although several pre- and post-settlement processes are believed to influence spatial patterns of marine invertebrates, the general patchy distribution of S. plana seems to be determined by the existence of specific environmental conditions during settlement. Factors such as temperature, salinity, sediment type, hydrographic conditions and predation affect settlement and spat survival and not one but a combination of factors seems to explain the species distribution pattern. Future work should focus on determining the scale of patchiness, using hierarchical sampling, as well as the connectivity between populations by analysing the population genetic structure.     

Predicting the distribution of deep-sea vulnerable marine ecosystems using high-resolution data: Considerations and novel approaches

Little is known about species distribution patterns in deep-sea environments, primarily because sampling surveys in the high seas are expensive and time consuming. The increasing need to manage and protect vulnerable marine ecosystems, such as cold-water corals, has motivated the use of predictive modelling tools, which produce continuous maps of potential species or habitat distribution from limited point observations and full coverage environmental data. Rapid advances in acoustic remote sensing, oceanographic modelling and sampling technology now provide high quality datasets, facilitating model development with high spatial detail. This paper provides a short overview of existing methodologies for predicting deep-sea benthic species distribution, and illustrates emerging issues related to spatial and thematic data resolution, and the use of transect-derived species distribution data. In order to enhance the ecological relevance and reliability of deep-sea species distribution models, novel techniques are presented based on a case study predicting the distribution of the cold-water coral Lophelia pertusa in three carbonate mound provinces in Irish waters. Specifically, the study evaluates (1) the capacity of newly developed high-resolution (250 m grid cell size) hydrodynamic variables to explain local scale cold-water coral distribution patterns, (2) the potential value of species occurrence proportion data to maintain semi-quantitative information of coral prevalence (i.e. coverage) and sampling effort per grid cell within the response variable, and (3) mixed effect modelling to deal with spatially grouped transect data. The study shows that predictive models using vertical and horizontal flow parameters perform significantly better than models based on terrain parameters only. Semi-quantitative proportion data may decrease model uncertainty and increase model reliability, and provide a fruitful avenue of research for analysing large quantities of video data in a detailed yet time-efficient manner. The study concludes with an outlook of how species distribution models could improve our understanding of vulnerable marine ecosystem functioning and processes in the deep sea.     

Review of three-dimensional ecological modelling related to the North Sea shelf system: Part 1: models and their results

The state-of-the-art in modelling the marine ecosystem of the greater North Sea is reviewed, providing an overview especially about three-dimensional models that describe and predict how the marine ecosystem of the greater North Sea area functions and how concentrations and fluxes of biologically important elements vary in space and time, throughout the shelf and over years, in response to physical forcing. Articles with a strong concentration on modelling were selected from the available literature, and all articles around the existing “ecological modelling groups” dealing with the area of the North Sea were sorted in chronological order of their appearance in the literature. We found eleven of such groups and described their different modelling efforts. Selecting the seven three-dimensional models (NORWECOM, GHER, ECOHAM, ERSEM, ELISE, COHERENS and POL3dERSEM), we characterized the complexity of the models, by comparing the resolution in time and space, and the resolution of the trophic structure by discussing the number and kind of state variables and of the processes relating these state variables to each other.The review of biogeochemical/ecological modelling for the greater North Sea shows that important findings by model simulations have either confirmed existing knowledge derived from field work or have given new insight into the mechanisms of the functioning of the North Sea system: the temporal and spatial development and magnitude of primary production, its spreading from the coasts to the north-west over the open North Sea, its mechanisms of limitation, the functioning of the pelagic small food web and of the benthic web, the mechanisms of nutrient regeneration, the effects of riverine and atmospheric nutrient inputs causing eutrophication of coastal waters, the extent of eutrophication in the North Sea, and the budgets for nitrogen, phosphorus, and silicon. The three-dimensional ecological models of the greater North Sea have provided consistent distributions and dynamics of the lower trophic levels on their regional, annual and decadal scales which cannot be derived to this degree of coverage by observations.The state-of-the-art in validation for these models is presented in part 2     

Spatial macrozoobenthic distribution patterns in relation to major environmental factors- A case study from the Pomeranian Bay (southern Baltic Sea)

The aim of this study was to identify potential environmental “key factors” causing spatial distributions of macrozoobenthic communities to improve our understanding concerning benthic biotic/abiotic interactions and ecosystem functioning. To this end benthic and environmental data, collected over a period of 4 years (2003–2006) at 191 sampling stations in the Pomeranian Bay (southwest Baltic Sea), were analysed. This represents the most comprehensive study performed in this respect in the Baltic Sea up to date and also the necessary first step towards a model able to predict macrofaunal distributions regarding autecological species-environment interactions. Based on species abundances, distinctive macrobenthic community patterns were identified and evaluated via univariate correlation methods, multivariate numerical classification and ordination techniques (e.g. PCA, CCA). These patterns were caused by clear responses of several benthic species to certain prevailing environmental conditions. The observed distribution of selected species followed a strong gradient of depth and was explained best by the sediment parameters total organic carbon (TOC), median grain size and sorting. By using different statistical methods these abiotic/biotic interactions were modelled allowing to extend our knowledge concerning ecosystem functioning, and provide a tool to assess natural and anthropogenic forced changes in species distribution.     

Development of habitat models for Nephtys species (Polychaeta: Nephtyidae) in the German Bight (North Sea)

The aim of the study was the development of habitat models for Nephtys species (Polychaeta: Nephtyidae). The investigation area was the German Bight, the southeastern part of the North Sea. Models were developed based on field data collected between 2000 and 2006. In addition, data on environmental variables were retrieved from long-term monitoring data sets and from the sediment map by Figge [Figge, K., 1981. Nordsee. Sedimentverteilung in der Deutschen Bucht. Map No. 2900. Publisher: Deutsches Hydrographisches Institut, Hamburg]. The statistical modelling technique used was multivariate adaptive regression splines (MARS). Models were fitted individually for each species. Evaluation of predictive discrimination and predictive accuracy of the developed models was by calculation of the area under the receiver operating curve (AUC) or sensitivity and specificity, respectively. Habitat models with best predictive fit were selected for the presentation of habitat suitability maps.Six Nepthys species were found: Nephtys assimilis, N. caeca, N. cirrosa, N. hombergii, N. incisa and N. longosetosa. N. hombergii was most common whereas N. incisa and N. longosetosa were rare. Habitat preferences varied considerably among the species. For all investigated Nephtys species except N. longosetosa a habitat model could be developed based on four predictor variables. The habitat models with best predictive fit were those for N. cirrosa and N. hombergii. The N. caeca habitat model was of limited predictive accuracy and only accept predictive discrimination. The number of predictors as well as the relative importance of the respective predictors in the model varied among the different species. Direct comparison of most suitable habitats for the different species based on modelling revealed that in the mostly sandy regions parallel to the German coast in water depths up to 20 m an overlap between N. caeca, N. hombergii and N. cirrosa exists. In the deeper central German Bight with mostly fine sands with increased mud contents N. hombergii, N. assimilis and, at least partially and rare in numbers, N. incisa co-occur. It can be concluded that important sediment characteristics like grain size median and mud content as well as water depth and mean salinity are useful parameters to describe the habitat requirements of most Nepthys species in the German Bight. However, additional variables need to be incorporated into such analyses.     

Modeling sensitive elasmobranch habitats

Basic information on the distribution and habitat preferences of ecologically important species is essential for their management and protection. In the Mediterranean Sea there is increasing concern over elasmobranch species because their biological (ecological) characteristics make them highly vulnerable to fishing pressure. Their removal could affect the structure and function of marine ecosystems, inducing changes in trophic interactions at the community level due to the selective elimination of predators or prey species, competitors and species replacement. In this study Bayesian hierarchical spatial models are used to map the sensitive habitats of the three most caught elasmobranch species (Galeus melastomus, Scyliorhinus canicula, Etmopterus spinax) in the western Mediterranean Sea, based on fishery-dependent bottom trawl data. Results show that habitats associated with hard substrata and sandy beds, mainly in deep waters and with a high seabed gradient, have a greater probability registering the presence of the studied species than those associated with muddy shallow waters. Temperature and chlorophyll-α concentration show a negative relationship with S. canicula occurrence. Our results identify some of the sensitive habitats for elasmobranchs in the western Mediterranean Sea (GSA06 South), providing essential and easy-to-use interpretation tools, such as predictive distribution maps, with the final aim of improving management and conservation of these vulnerable species.     

Dispersal patterns of the eggs and larvae of spring-spawning fish in the Irish Sea, UK

Many marine species produce pelagic propagules which, because of their life-history characteristics and the local hydrodynamics, can disperse considerable distances from the point of release. Distances travelled are affected by factors such as: release time and location, egg and larval stage duration, local environmental conditions and active swimming and settlement behaviours. Understanding such dispersal patterns is important for the design of effective ecosystem-conservation strategies. We used a regional scale, coupled physical-biological model for the Irish Sea to simulate the possible dispersal of eggs and larvae of five species of fish with contrasting early life histories (cod Gadus morhua, plaice Pleuronectes platessa, witch Glyptocephalus cynoglossus, sprat Sprattus sprattus and pogge Agonus cataphractus). The hydrodynamic model was forced with meteorological data for 1995, a year when extensive plankton surveys were conducted in the Irish Sea. A particle tracking method featuring particle release (spawning) and species-dependent particle development and behaviour was then run based on flow and temperature fields from the hydrodynamical model. Modelled larval distributions and settlement areas corresponded favourably with observations from field sampling. The settlement destinations (or onset of shoaling for sprat) were affected both by their initial spawning location and by the species-specific development rates and behaviours coded into the model. Eggs and larvae typically remained within 160 km of their spawning origin, although a minority travelled up to 300 km. Even in a relatively enclosed sea such as the Irish Sea, fish eggs and larvae can be dispersed over 100s of km. This provides a major challenge for the design of effective spatial management strategies if it is necessary to protect a species across its life-history stages. Further progress in the design of effective conservation measures for species or communities will need an integrated approach taking account of key aspects of early life history and behaviour.     

Identifying soft sediments at sea using GIS-modelled predictor variables and Sediment Profile Image (SPI) measured response variables

Macrofauna composition and diversity in soft sediments are commonly used as “health indicators” in various pollution monitoring programmes worldwide. Hence, finding a modelling method for predicting the presence of soft sediments and enable production of digital maps of where soft sediments are likely to be found would be valuable for developing a cost-effective sampling design. This study presents a first-generation model that can predict where to find soft sediments in coastal areas with a complex topography and a mosaic of seabed habitat types. We used geophysical data that were quantitative, objectively defined (through GIS modelling) and integrated over time. We analysed, using a Generalised Additive Model (GAM) and the model-selection approach Akaike Information Criterion (AIC), the influence of in-situ measured depth and GIS-modelled terrain structures, wave exposure and current speed on the distribution of soft sediment measured using a Sediment Profile Image (SPI) camera. Our analyses showed that the probability of finding soft sediment was best determined by depth, terrain curvature and median current speed at the seafloor. These predictors were used to develop a spatial predictive GIS-model/-map (for parts of Skagerrak, Norway, with a spatial resolution of 25 m × 25 m) of the probability of soft seabed occurrence.     

Species–environment relationships and potential for distribution modelling in coastal waters

Due to increasing pressure on the marine environment there is a growing need to understand species–environment relationships. To provide background for prioritising among variables (predictors) for use in distribution models, the relevance of predictors for benthic species was reviewed using the coastal Baltic Sea as a case-study area. Significant relationships for three response groups (fish, macroinvertebrates, macrovegetation) and six predictor categories (bottom topography, biotic features, hydrography, wave exposure, substrate and spatiotemporal variability) were extracted from 145 queried peer-reviewed field-studies covering three decades and six subregions. In addition, the occurrence of interaction among predictors was analysed. Hydrography was most often found in significant relationships, had low level of interaction with other predictors, but also had the most non-significant relationships. Depth and wave exposure were important in all subregions and are readily available, increasing their applicability for cross-regional modelling efforts. Otherwise, effort to model species distributions may prove challenging at larger scale as the relevance of predictors differed among both response groups and regions. Fish and hard bottom macrovegetation have the largest modelling potential, as they are structured by a set of predictors that at the same time are accurately mapped. A general importance of biotic features implies that these need to be accounted for in distribution modelling, but the mapping of most biotic features is challenging, which currently lowers the applicability. The presence of interactions suggests that predictive methods allowing for interactive effects are preferable. Detailing these complexities is important for future distribution modelling.     

A novel shear vane used to determine the evolution of hydraulic dredge tracks in sub-tidal marine sediments

A novel shear vane is described which can be used to record the shear strength of discrete depth horizons of a variety of marine sediment types in situ. This vane, or modifications of it, has great potential in allowing measurement of in situ shear strength without requiring any samples to be removed from the sea bed, a process which can often destroy the fine structure of the sediment. The vane was used to monitor the change in sediment shear strength caused by a hydraulic dredge, which was used to fish razor clams (Ensis arcuatus) in a sheltered bay within the Clyde Sea area, Scotland. Data collected using this apparatus provided valuable and immediate information on the stratification of the sea bed post-dredging and allowed the evolution of the dredge track to be regularly monitored by divers over a period of 100 d.     

Exploring the spatial distribution patterns of South African Cape hakes using generalised additive models

We developed delta generalised additive models (GAMs) to predict the spatial distribution of different size classes of South African hakes, Merluccius capensis and M. paradoxus, using demersal trawl survey data and geographical (latitude and longitude) and environmental features (depth, temperature, bottom dissolved oxygen and sediment type). Our approach consists of fitting, for each hake size class, two independent models, a binomial GAM and a quasi-Poisson GAM, whose predictions are then combined using the delta method. Delta GAMs were validated using an iterative cross-validation procedure, and their predictions were then employed to produce distribution maps for the southern Benguela. Delta GAM predictions confirmed existing knowledge about the spatial distribution patterns of South African hakes, and brought new insights into the factors influencing the presence/absence and abundance of these species. Our GAM approach can be used to produce distribution maps for spatially explicit ecosystem models of the southern Benguela in a rigorous and objective way. Ecosystem models are critical features of the ecosystem approach to fisheries, and distribution maps constructed using our GAM approach will enable a reliable allocation of species biomasses in spatially explicit ecosystem models, which will increase trust in the spatial overlaps and, therefore, the trophic interactions predicted by these models.     

Grazing effects by Nereis diversicolor on development and growth of green algal mats

Nereis diversicolor is generally considered to be a predator and deposit feeder, but have also been found to graze on benthic algae in shallow coastal areas. In this study we investigated the grazing effects on the development and growth of green algae, Ulva spp. Algal growth was studied in an experiment including two levels of sediment thickness; 100 mm sediment including macrofauna and 5 mm sediment without macrofauna, and three treatments of varying algal biomass; sediment with propagules, sediment with low algal biomass (120 g dry weight (dwt) m^− 2) and sediment with high algal biomass (240 g dwt m^− 2). In the 100 mm sediment, with a natural population of macrofauna, N. diversicolor was the dominating (60% of total biomass) species. After three weeks of experimentation the result showed that N. diversicolor was able to prevent initial algal growth, affect growth capacity and also partly reduce full-grown algal mats. The weight of N. diversicolor was significantly higher for polychaetes in treatments with algae added compared to non-algal treatments. There were also indications that a rich nutrient supply per algae biomass counteracted the grazing capacity of N. diversicolor.     

Predicting suitable habitat for the cold-water coral Lophelia pertusa (Scleractinia)

Ecological-niche factor analysis (ENFA) was applied to the reef framework-forming cold-water coral Lophelia pertusa. The environmental tolerances of this species were assessed using readily available oceanographic data, including physical, chemical, and biological variables. L. pertusa was found at mean depths of 468 and 480 m on the regional and global scales and occupied a niche that included higher than average current speed and productivity, supporting the theory that their limited food supply is locally enhanced by currents. Most records occurred in areas with a salinity of 35, mean temperatures of 6.2–6.7  °C and dissolved oxygen levels of 6.0–6.2 ml l⁻¹. The majority of records were found in areas that were saturated with aragonite but had low concentration of nutrients (silicate, phosphate, and nitrate). Suitable habitat for L. pertusa was predicted using ENFA on a global and a regional scale that incorporated the north-east Atlantic Ocean. Regional prediction was reliable due to numerous presence points throughout the area, whereas global prediction was less reliable due to the paucity of presence data outside of the north-east Atlantic. However, the species niche was supported at each spatial scale. Predicted maps at the global scale reinforced the general consensus that the North Atlantic Ocean is a key region in the worldwide distribution of L. pertusa. Predictive modelling is an approach that can be applied to cold-water coral species to locate areas of suitable habitat for further study. It may also prove a useful tool to assist spatial planning of offshore marine protected areas. However, issues with eco-geographical datasets, including their coarse resolution and limited geographical coverage, currently restrict the scope of this approach.     

A GIS modelling framework to evaluate marine spatial planning scenarios: Co-location of offshore wind farms and aquaculture in the German EEZ

The concept of co-location of marine areas receives an increased significance in the light of sustainable development in the already heavily used offshore marine realm. Within this study, different spatial co-location scenarios for the coupling of offshore aquacultures and wind farms are evaluated in order to support efficient and sustainable marine spatial management strategies. A Geographic Information System (GIS) and multi-criteria evaluation (MCE) techniques were combined to index suitable co-sites in the German exclusive economic zone of the North Sea. The MCE was based on criteria such as temperature, salinity or oxygen. In total, 13 possible aquaculture candidates (seaweed, bivalves, fish and crustaceans) were selected for the scenario configuration. The GIS modelling framework proved to be powerful in defining potential co-location sites. The aquaculture candidate oarweed (Laminaria digitata) revealed the highest suitability scores at 10–20 m depth from April to June, followed by haddock (Melanogrammus aeglefinus) at 20–30 m depth and dulse (Palmaria palmata) and Sea belt (Saccharina latissima) at 0–10 m depth between April and June. In summary, results showed several wind farms were de facto suitable sites for aquaculture since they exhibited high suitability scores for Integrated Multi-Trophic Aquaculture (IMTA) systems combining fish species, bivalves and seaweeds. The present results illustrate how synergies may be realised between competing needs of both offshore wind energy and offshore IMTA in the German EEZ of the North Sea. This might offer guidance to stakeholders and assist decision-makers in determining the most suitable sites for pilot projects using IMTA techniques.     

黄海浒苔漂移输运模式的建立与应用

本文利用NCEPGFS预报风场和中国近海高分辨率三维MASNUM海浪-潮流-环流耦合海洋数值预报系统的预报数据,建立黄海浒苔漂移输运模式,用于黄海浒苔溯源和漂移输运数值模拟研究。使用2009年5月份黄海表层漂流浮标数据和2012年MODIS卫星遥感浒苔漂移分布资料对所建立的漂移输运模式进行验证,结果表明所建立的模式能够有效的模拟出浒苔暴发区漂流浮标运动状况,并能够有效地模拟出2012年浒苔漂移输运过程。最后运用所建立的模式开展2008年和2010年浒苔漂移输运过程,模拟结果与文献报道的卫星观测结果一致。模拟结果表明,受海洋表层流影响两年浒苔特征显著不同:2010年浒苔影响海域明显小于2008年,且2010年浒苔主体没有大规模在青岛近岸堆积。     

Onshore sandbar migration at Tairua Beach (New Zealand): Numerical simulations and field measurements

We observed the onshore migration (3.5 m/day) of a nearshore sandbar at Tairua Beach, New Zealand during 4 days of low-energy wave conditions. The morphological observations, together with concurrent measurements of waves and suspended sediment concentrations, were used to test a coupled, wave-averaged, cross-shore model. Because of the coarse bed material and the relatively low-energy conditions, the contribution of the suspended transport to the total transport was predicted and observed to be negligible. The model predicted the bar to move onshore because of the feedback between near-bed wave skewness, bedload, and the sandbar under weakly to non-breaking conditions at high tide. The predicted bathymetric evolution contrasts, however, with the observations that the bar migrated onshore predominantly at low tide. Also, the model flattened the bar, while in the observations the sandbar retained its steep landward-facing flank. A comparison between available observations and numerical simulations suggests that onshore propagating surf zone bores in very shallow water (< 0.25 m) may have been responsible for most of the observed bar behaviour. These processes are missing from the applied model and, given that the observed conditions can be considered typical of very shallow sandbars, highlight a priority for further field study and model development. The possibility that the excess water transported by the bores across the bar was channelled alongshore to near-by rip-channels further implies that traditional cross-shore measures to judge the applicability of a cross-shore morphodynamic model may be misleading.     

Predictive habitat modelling of humpback (Megaptera novaeangliae) and Antarctic minke (Balaenoptera bonaerensis) whales in the Southern Ocean as a planning tool for seismic surveys

Seismic surveys are frequently a matter of concern regarding their potentially negative impacts on marine mammals. In the Southern Ocean, which provides a critical habitat for several endangered cetacean species, seismic research activities are undertaken at a circumpolar scale. In order to minimize impacts of these surveys, pre-cruise planning requires detailed, spatio-temporally resolved knowledge on the likelihood of encountering these species in the survey area. In this publication we present predictive habitat modelling as a potential tool to support decisions for survey planning. We associated opportunistic sightings (2005–2011) of humpback (Megaptera novaeangliae, N=93) and Antarctic minke whales (Balaenoptera bonaerensis, N=139) with a range of static and dynamic environmental variables. A maximum entropy algorithm (Maxent) was used to develop habitat models and to calculate daily basinwide/circumpolar prediction maps to evaluate how species-specific habitat conditions evolved throughout the spring and summer months. For both species, prediction maps revealed considerable changes in habitat suitability throughout the season. Suitable humpback whale habitat occurred predominantly in ice-free areas, expanding southwards with the retreating sea ice edge, whereas suitable Antarctic minke whale habitat was consistently predicted within sea ice covered areas. Daily, large-scale prediction maps provide a valuable tool to design layout and timing of seismic surveys as they allow the identification and consideration of potential spatio-temporal hotspots to minimize potential impacts of seismic surveys on Antarctic cetacean species.     

Atlas of Japan (East) Sea hydrographic properties in summer, 1999

Hydrographic properties from CTD and discrete bottle sample profiles covering the Japan (East) Sea in summer, 1999, are presented in vertical sections, maps at standard depths, maps on isopycnal surfaces, and as property–property distributions. This data set covers most of the Sea with the exception of the western boundary region and northern Tatar Strait, and includes nutrients, pH, alkalinity, and chlorofluorocarbons, as well as the usual temperature, salinity, and oxygen observations.     

Population abundance and seasonal migration patterns indicated by commercial catch-per-unit-effort of hakes (Merluccius capensis and M. paradoxus) in the northern Benguela Current Large Marine Ecosystem

We developed generalised additive models (GAMs) to estimate standardised time-series of population abundance indices for assessment purposes and to infer ecological and behavioural information on northern Benguela hakes, Merluccius capensis and M. paradoxus, using haul-by-haul commercial trawl catch-rate data as proxies for hake densities. The modelling indicated that individual ship identifiers should be used rather than general vessel characteristics, such as vessel size. The final models explained 79% and 68% of the variability in the commercial catch rates of M. capensis and M. paradoxus, respectively. The spatial density patterns were consistent and confirmed existing knowledge about these species in the northern Benguela system. Furthermore, seasonal migration patterns were described for the first time and were found to correspond to the known spawning areas and seasons for M. capensis and M. paradoxus. Spatial density patterns were validated using the geostatistical modelling results of fisheries-independent trawl survey data. Improved understanding of the relationships between fleet dynamics and fish movement can be achieved by taking into consideration the present catch-rate model and spatial and seasonal distribution maps. We conclude that the yearly standardised CPUE time-series are problematic as proxies for total stock abundance because of spatial coverage issues. Consequently, such CPUE data should not be used for stock-size assessments and fisheries advice concerning northern Benguela hakes until this is solved. We generally recommend the exclusion of standardised CPUE time-series from stock assessments when important and changing parts of the stock distribution cannot be targeted by the fishery, such as due to closed areas or seasons.