Historical data reveal power-law dispersal patterns of invasive aquatic species.

Understanding how invasive species spread is of particular concern in the current era of globalisation and rapid environmental change. The occurrence of super-diffusive movements within the context of Lévy flights has been discussed with respect to particle physics, human movements, microzooplankton, disease spread in global epidemiology and animal foraging behaviour. Super-diffusive movements provide a theoretical explanation for the rapid spread of organisms and disease, but their applicability to empirical data on the historic spread of organisms has rarely been tested. This study focuses on the role of long-distance dispersal in the invasion dynamics of aquatic invasive species across three contrasting areas and spatial scales: open ocean (north-east Atlantic), enclosed sea (Mediterranean) and an island environment (Ireland). Study species included five freshwater plant species, Azolla filiculoides, Elodea canadensis, Lagarosiphon major, Elodea nuttallii and Lemna minuta; and ten species of marine algae, Asparagopsis armata, Antithamnionella elegans, Antithamnionella ternifolia, Codium fragile, Colpomenia peregrina, Caulerpa taxifolia, Dasysiphonia sp., Sargassum muticum, Undaria pinnatifida and Womersleyella setacea. A simulation model is constructed to show the validity of using historical data to reconstruct dispersal kernels. Lévy movement patterns similar to those previously observed in humans and wild animals are evident in the re-constructed dispersal pattern of invasive aquatic species. Such patterns may be widespread among invasive species and could be exacerbated by further development of trade networks, human travel and environmental change. These findings have implications for our ability to predict and manage future invasions, and improve our understanding of the potential for spread of organisms including infectious diseases, plant pests and genetically modified organisms.

Marine non-natives, issues, engagement and action in France and the UK

The first presentation focused on best practice in marine environments and was delivered by the MBA, in association with PEGASEAS. Information was presented about the significance of joint working across the Channel and a number of different projects including The Shore Thing Project were explained.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Projecting marine fish production and catch potential in Bangladesh in the 21st century under long-term environmental change and management scenarios

The fisheries sector is crucial to the Bangladeshi economy and wellbeing, accounting for 4.4% of national Gross Domestic Product (GDP) and 22.8% of agriculture sector production, and supplying ca.60% of the national animal protein intake. Fish is vital to the 16 million Bangladeshis living near the coast, a number that has doubled since the 1980s. Here we develop and apply tools to project the long term productive capacity of Bangladesh marine fisheries under climate and fisheries management scenarios, based on downscaling a global climate model, using associated river flow and nutrient loading estimates, projecting high resolution changes in physical and biochemical ocean properties, and eventually projecting fish production and catch potential under different fishing mortality targets. We place particular interest on Hilsa shad (Tenualosa ilisha), which accounts for ca.11% of total catches, and Bombay duck (Harpadon nehereus), a low price fish that is the second highest catch in Bangladesh and is highly consumed by low income communities. It is concluded that the impacts of climate change, under greenhouse emissions scenario A1B, are likely to reduce the potential fish production in the Bangladesh Exclusive Economic Zone (EEZ) by less than 10%. However, these impacts are larger for the two target species. Under sustainable management practices we expect Hilsa shad catches to show a minor decline in potential catch by 2030 but a significant (25%) decline by 2060. However, if overexploitation is allowed catches are projected to fall much further, by almost 95% by 2060, compared to the Business as Usual scenario for the start of the 21st century. For Bombay duck, potential catches by 2060 under sustainable scenarios will produce a decline of less than 20% compared to current catches. The results demonstrate that management can mitigate or exacerbate the effects of climate change on ecosystem productivity.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Contrasting transcriptome response to thermal stress in two key zooplankton species, Calanus finmarchicus and C. glacialis

Climate change has already led to the range expansion of warm-water plankton assemblages in the northeast Atlantic and the corresponding range contraction of colder-water species. The temperate copepod Calanus finmarchicus is predicted to shift farther northward into polar waters traditionally dominated by the arctic copepod C. glacialis. To identify temperaturemediated changes in gene expression that may be critical for the thermal acclimation and resilience of the 2 Calanus spp., we conducted a whole transcriptome profiling using RNA-seq on an Ion Torrent platform. Transcriptome responses of C. finmarchicus and C. glacialis from Disko Bay, west Greenland, were investigated under realistic thermal stresses (at + 5, +10 and +15°C) for 4 h and 6 d. C. finmarchicus showed a strong response to temperature and duration of stress, involving up-regulation of genes related to protein folding, transcription, translation and metabolism. In sharp contrast, C. glacialis displayed only low-magnitude changes in gene expression in response to temperature and duration of stress. Differences in the thermal responses of the 2 species, particularly the lack of thermal stress response in C. glacialis, are in line with laboratory and field observations and suggest a vulnerability of C. glacialis to climate change.

Plastic and marine turtles: a review and call for research

Plastic debris is now ubiquitous in the marine environment affecting a wide range of taxa, from microscopic zooplankton to large vertebrates. Its persistence and dispersal throughout marine ecosystems has meant that sensitivity toward the scale of threat is growing, particularly for species of conservation concern, such as marine turtles. Their use of a variety of habitats, migratory behaviour, and complex life histories leave them subject to a host of anthropogenic stressors, including exposure to marine plastic pollution. Here, we review the evidence for the effects of plastic debris on turtles and their habitats, highlight knowledge gaps, and make recommendations for future research. We found that, of the seven species, all are known to ingest or become entangled in marine debris. Ingestion can cause intestinal blockage and internal injury, dietary dilution, malnutrition, and increased buoyancy which in turn can result in poor health, reduced growth rates and reproductive output, or death. Entanglement in plastic debris (including ghost fishing gear) is known to cause lacerations, increased drag—which reduces the ability to forage effectively or escape threats—and may lead to drowning or death by starvation. In addition, plastic pollution may impact key turtle habitats. In particular, its presence on nesting beaches may alter nest properties by affecting temperature and sediment permeability. This could influence hatchling sex ratios and reproductive success, resulting in population level implications. Additionally, beach litter may entangle nesting females or emerging hatchlings. Lastly, as an omnipresent and widespread pollutant, plastic debris may cause wider ecosystem effects which result in loss of productivity and implications for trophic interactions. By compiling and presenting this evidence, we demonstrate that urgent action is required to better understand this issue and its effects on marine turtles, so that appropriate and effective mitigation policies can be developed.

A review of climate change and the implementation of marine biodiversity legislation in the United Kingdom

1. Marine legislation, the key means by which the conservation of marine biodiversity is achieved, has been developing since the 1960s. In recent decades, an increasing focus on ‘holistic’ policy development is evident, compared with earlier ‘piecemeal’ sectoral approaches. Important marine legislative tools being used in the United Kingdom, and internationally, include the designation of marine protected areas and the Marine Strategy Framework Directive (MSFD) with its aim of meeting ‘Good Environmental Status’ (GES) for European seas by 2020. 2. There is growing evidence of climate change impacts on marine biodiversity, which may compromise the effectiveness of any legislation intended to promote sustainable marine resource management. 3. A review of key marine biodiversity legislation relevant to the UK shows climate change was not considered in the drafting of much early legislation. Despite the huge increase in knowledge of climate change impacts in recent decades, legislation is still limited in how it takes these impacts into account. There is scope, however, to account for climate change in implementing much of the legislation through (a) existing references to environmental variability; (b) review cycles; and (c) secondary legislation and complementary policy development. 4. For legislation relating to marine protected areas (e.g. the EC Habitats and Birds Directives), climate change has generally not been considered in the site-designation process, or for ongoing management, with the exception of the Marine (Scotland) Act. Given that changing environmental conditions (e.g. rising temperatures and ocean acidification) directly affect the habitats and species that sites are designated for, how this legislation is used to protect marine biodiversity in a changing climate requires further consideration. 5. Accounting for climate change impacts on marine biodiversity in the development and implementation of legislation is vital to enable timely, adaptive management responses. Marine modelling can play an important role in informing management decisions.

Ecological equivalence of species within phytoplankton functional groups

1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

Costs and benefits to European shipping of ballast-water and hull-fouling treatment: Impacts of native and non-indigenous species

Maritime transport and shipping are impacted negatively by biofouling, which can result in increased fuel consumption. Thus, costs for fouling reduction can be considered an investment to reduce fuel consumption. Anti-fouling measures also reduce the rate of introduction of non-indigenous species (NIS). Further mitigation measures to reduce the transport of NIS within ballast water and sediments impose additional costs. The estimated operational cost of NIS mitigation measures may represent between 1.6% and 4% of the annual operational cost for a ship operating on European seas, with the higher proportional costs in small ships. However, fouling by NIS may affect fuel consumption more than fouling by native species due to differences in species’ life-history traits and their resistance to antifouling coatings and pollution. Therefore, it is possible that the cost of NIS mitigation measures could be smaller than the cost from higher fuel consumption arising from fouling by NIS.

Marine regime shifts in ocean biogeochemical models: a case study in the Gulf of Alaska

Regime shifts have been reported in many marine ecosystems, and are often expressed as an abrupt change occurring in multiple physical and biological components of the system. In the Gulf of Alaska, a regime shift in the late 1970s was observed, indicated by an abrupt increase in sea surface temperature and major shifts in the catch of many fish species. This late 1970s regime shift in the Gulf of Alaska was followed by another shift in the late 1980s, not as pervasive as the 1977 shift, but which nevertheless did not return to the prior state. A thorough understanding of the extent and mechanisms leading to such regime shifts is challenged by data paucity in time and space. We investigate the ability of a suite of ocean biogeochemistry models of varying complexity to simulate regime shifts in the Gulf of Alaska by examining the presence of abrupt changes in time series of physical variables (sea surface temperature and mixed layer depth), nutrients and biological variables (chlorophyll, primary productivity and plankton biomass) using change-point analysis. Our study demonstrates that ocean biogeochemical models are capable of simulating the late 1970s shift, indicating an abrupt increase in sea surface temperature forcing followed by an abrupt decrease in nutrients and biological productivity. This predicted shift is consistent among all the models, although some of them exhibit an abrupt transition (i.e. a significant shift from one year to the next), whereas others simulate a smoother transition. Some models further suggest that the late 1980s shift was constrained by changes in mixed layer depth. Our study demonstrates that ocean biogeochemical can successfully simulate regime shifts in the Gulf of Alaska region, thereby providing better understanding of how changes in physical conditions are propagated from lower to upper trophic levels through bottom-up controls.

Defining scenarios of future vectors of change in marine life and associated economic sectors

Addressing the multitude of challenges in marine policy requires an integrated approach that considers the multitude of drivers, pressures, and interests, from several disciplinary angles. Scenarios are needed to harmonise the analyses of different components of the marine system, and to deal with the uncertainty and complexity of the societal and biogeophysical dynamics in the system. This study considers a set of socio-economic scenarios to (1) explore possible futures in relation to marine invasive species, outbreak forming species, and gradual changes in species distribution and productivity; and (2) harmonise the projection modelling performed within associated studies. The exercise demonstrates that developing interdisciplinary scenarios as developed in this study is particularly complicated due to (1) the wide variety in endogeneity or exogeneity of variables in the different analyses involved; (2) the dual role of policy decisions as variables in a scenario or decisions to be evaluated and compared to other decisions; and (3) the substantial difference in time scale between societal and physical drivers.

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

Modelling the Stoichiometric Regulation of C-Rich Toxins in Marine Dinoflagellates

Toxin production in marine microalgae was previously shown to be tightly coupled with cellular stoichiometry. The highest values of cellular toxin are in fact mainly associated with a high carbon to nutrient cellular ratio. In particular, the cellular accumulation of C-rich toxins (i.e., with C:N > 6.6) can be stimulated by both N and P deficiency. Dinoflagellates are the main producers of C-rich toxins and may represent a serious threat for human health and the marine ecosystem. As such, the development of a numerical model able to predict how toxin production is stimulated by nutrient supply/deficiency is of primary utility for both scientific and management purposes. In this work we have developed a mechanistic model describing the stoichiometric regulation of C-rich toxins in marine dinoflagellates. To this purpose, a new formulation describing toxin production and fate was embedded in the European Regional Seas Ecosystem Model (ERSEM), here simplified to describe a monospecific batch culture. Toxin production was assumed to be composed by two distinct additive terms; the first is a constant fraction of algal production and is assumed to take place at any physiological conditions. The second term is assumed to be dependent on algal biomass and to be stimulated by internal nutrient deficiency. By using these assumptions, the model reproduced the concentrations and temporal evolution of toxins observed in cultures of Ostreopsis cf. ovata, a benthic/epiphytic dinoflagellate producing C-rich toxins named ovatoxins. The analysis of simulations and their comparison with experimental data provided a conceptual model linking toxin production and nutritional status in this species. The model was also qualitatively validated by using independent literature data, and the results indicate that our formulation can be also used to simulate toxin dynamics in other dinoflagellates. Our model represents an important step towards the simulation and prediction of marine algal toxicity.

Analyses of sublittoral macrobenthic community change in a marine nature reserve using similarity profiles (SIMPROF).

Sublittoral macrobenthic communities in the Skomer Marine Nature Reserve (SMNR), Pembrokeshire, Wales, were sampled at 10 stations in 1993, 1996, 1998, 2003, 2007 and 2009 using a Day grab and a 0.5 mm mesh. The time series is analysed using Similarities Profiles (SIMPROF) tests and associated methods. Q-mode analysis using clustering with Type 1 SIMPROF addresses multivariate structure among samples, showing that there is clear structure associated with differences among years. Inverse (r-mode) analysis using Type 2 SIMPROF decisively rejects a hypothesis that species are not associated with each other. Clustering of the variables (species) with Type 3 SIMPROF identifies groups of species which covary coherently through the time-series. The time-series is characterised by a dramatic decline in abundances and diversity between the 1993 and 1996 surveys. By 1998 there had been a shift in community composition from the 1993 situation, with different species dominating. Communities had recovered in terms of abundance and species richness, but different species dominated the community. No single factor could be identified which unequivocally explained the dramatic changes observed in the SMNR. Possible causes were the effects of dispersed oil and dispersants from the Sea Empress oil spill in February 1996 and the cessation of dredge-spoil disposal off St Anne’s Head in 1995, but the most likely cause was severe weather. With many species, and a demonstrable recovery from an impact, communities within the SMNR appear to be diverse and resilient. If attributable to natural storms, the changes observed here indicate that natural variability may be much more important than is generally taken into account in the design of monitoring programmes.