Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 1 Report: Rationale and proposed ecological groupings for Level 5 biotopes against which sensitivity assessments would be best undertaken.

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Recovery or decline of the Northwestern Black Sea: A societal choice revealed by socio-ecological modelling

During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.

Conceptual Ecological Modelling of Sublittoral Rock Habitats to Inform Indicator Selection

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Plymouth — A World Harbour through the ages

Plymouth Sound and adjacent estuaries, UK has been used as a working harbour throughout the ages and has a place in maritime history as the port from where the Pilgrim Fathers left for North America in 1620 on the Mayflower and Charles Darwin departed from on the HMS Beagle on his trip to Galapagos in 1831. Today, it remains a working harbour, home to the largest naval base in Western Europe, the host of numerous cruise ships and recreational boats, yet its complex of estuaries (Tamar, Plym, Lynher) and creeks is nationally and internationally recognised as of conservation importance due to its physical characteristics and flora and fauna. Here, we briefly recount the history and importance of Plymouth through the ages in terms of its historic use as a harbour, its marine science heritage and importance on the international stage. We also briefly describe its ecology.

Unanticipated biological changes and global warming

Evidence of global warming is now unequivocal, and studies suggest that it has started to influence natural systems of the planet, including the oceans. However, in the marine environment, it is well-known that species and ecosystems can also be influenced by natural sources of large-scale hydro-climatological variability. The North Atlantic Oscillation (NAO) was negatively correlated with the mean abundance of one of the subarctic key species Calanus finmarchicus in the North Sea. This correlation was thought to have broken down in 1996, however, the timing has never been tested statistically. The present study revisits this unanticipated change and reveals that the correlation did not break down in 1996 as originally proposed but earlier, at the time of an abrupt ecosystem shift in the North Sea in the 1980s. Furthermore, the analyses demonstrate that the correlation between the NAO and C. finmarchicus abundance is modulated by the thermal regime of the North Sea, which in turn covaries positively with global temperature anomalies. This study thereby provides evidence that global climate change is likely to alter some empirical relationships found in the past between species abundance or the ecosystem state and large-scale natural sources of hydro-climatological variability. A theory is proposed to explain how this might happen. These unanticipated changes, also called ‘surprises’ in climatic research, are a direct consequence of the complexity of both climatic and biological systems. In this period of rapid climate change, it is therefore hazardous to integrate meteo-oceanic indices such as the NAO in models used in the management of living resources, as it has been sometimes attempted in the past.

Climate, plankton and cod

While a few North Atlantic cod stocks are stable, none have increased and many have declined in recent years. Although overfishing is the main cause of most observed declines, this study shows that in some regions, climate by its influence on plankton may exert a strong control on cod stocks, complicating the management of this species that often assumes a constant carrying capacity. First, we investigate the likely drivers of changes in the cod stock in the North Sea by evaluating the potential relationships between climate, plankton and cod. We do this by deriving a Plankton Index that reflects the quality and quantity of plankton food available for larval cod. We show that this Plankton Index explains 46.24% of the total variance in cod recruitment and 68.89% of the variance in total cod biomass. Because the effects of climate act predominantly through plankton during the larval stage of cod development, our results indicate a pronounced sensitivity of cod stocks to climate at the warmer, southern edge of their distribution, for example in the North Sea. Our analyses also reveal for the first time, that at a large basin scale, the abundance of Calanus finmarchicus is associated with a high probability of cod occurrence, whereas the genus Pseudocalanus appears less important. Ecosystem-based fisheries management (EBFM) generally considers the effect of fishing on the ecosystem and not the effect of climate-induced changes in the ecosystem state for the living resources. These results suggest that EBFM must consider the position of a stock within its ecological niche, the direct effects of climate and the influence of climate on the trophodynamics of the ecosystem.

The future of the northeast Atlantic benthic flora in a high CO2 world

Seaweed and seagrass communities in the northeast Atlantic have been profoundly impacted by humans, and the rate of change is accelerating rapidly due to runaway CO2 emissions and mounting pressures on coastlines associated with human population growth and increased consumption of finite resources. Here, we predict how rapid warming and acidification are likely to affect benthic flora and coastal ecosystems of the northeast Atlantic in this century, based on global evidence from the literature as interpreted by the collective knowledge of the authorship. We predict that warming will kill off kelp forests in the south and that ocean acidification will remove maerl habitat in the north. Seagrasses will proliferate, and associated epiphytes switch from calcified algae to diatoms and filamentous species. Invasive species will thrive in niches liberated by loss of native species and spread via exponential development of artificial marine structures. Combined impacts of seawater warming, ocean acidification, and increased storminess may replace structurally diverse seaweed canopies, with associated calcified and noncalcified flora, with simple habitats dominated by noncalcified, turf-forming seaweeds.

Chapter 11: Human activities and ecosystem service use: impacts and trade-offs

Ecosystem services provided by the marine environment are fundamental to human health and well-being. Despite this, many marine systems are being degraded to an extent that may reduce their capacity to provide these ecosystem services. The ecosystem approach is a strategy for the integrated management of land, water and living resources that promotes conservation and sustainable use in an equitable way (UN Convention on Biological Diversity, 2000). Its application to marine management and spatial planning has been proposed as a means of maintaining the economic and social value of the oceans, not only in the present but for generations to come. Characterising the susceptibility of services (and combinations of services) to particular human activities based on knowledge of impacts on biodiversity and ecosystem functioning (as described in preceding chapters) is a challenge for future management of the oceans. In this chapter, we highlight the existing, but limited knowledge of how ecosystem services may be impacted by different human activities. We discuss how impacts on one service can impact multiple services and explore how the impacts on services can vary both spatially and temporally and according to context. We focus particularly on the effects on ecosystem services of activities whose impacts on biodiversity and ecosystem functioning have already been considered in previous chapters. Some of these activities are associated with poor management of ecosystem benefits, for example, from provisioning services (aquaculture and fisheries), or with excessive input of wastes, fertilisers and contaminants into the system overburdening the waste treatment and assimilation services. Other impacts are associated with the construction of structures or use of space designed to generate benefits from environmental services such as the presence of water as a carrier for shipping, or sources of wind, wave and tidal power. We discuss the trade-offs that are made, consciously or otherwise, between different ecosystem services, which arise from human activities to optimise or manage specific ecosystem services.

Impact of climate change on Antarctic krill

Antarctic krill Euphausia superba (hereafter ‘krill’) occur in regions undergoing rapid environmental change, particularly loss of winter sea ice. During recent years, harvesting of krill has increased, possibly enhancing stress on krill and Antarctic ecosystems. Here we review the overall impact of climate change on krill and Antarctic ecosystems, discuss implications for an ecosystem-based fisheries management approach and identify critical knowledge gaps. Sea ice decline, ocean warming and other environmental stressors act in concert to modify the abundance, distribution and life cycle of krill. Although some of these changes can have positive effects on krill, their cumulative impact is most likely negative. Recruitment, driven largely by the winter survival of larval krill, is probably the population parameter most susceptible to climate change. Predicting changes to krill populations is urgent, because they will seriously impact Antarctic ecosystems. Such predictions, however, are complicated by an intense inter-annual variability in recruitment success and krill abundance. To improve the responsiveness of the ecosystem-based management approach adopted by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), critical knowledge gaps need to be filled. In addition to a better understanding of the factors influencing recruitment, management will require a better understanding of the resilience and the genetic plasticity of krill life stages, and a quantitative understanding of under-ice and benthic habitat use. Current precautionary management measures of CCAMLR should be maintained until a better understanding of these processes has been achieved.