Decadal changes in climate and ecosystems in the North Atlantic Ocean and adjacent seas

Climate change is unambiguous and its effects are clearly detected in all functional units of the Earth system. This study presents new analyses of sea-surface temperature changes and show that climate change is affecting ecosystems of the North Atlantic. Changes are seen from phytoplankton to zooplankton to fish and are modifying the dominance of species and the structure, the diversity and the functioning of marine ecosystems. Changes also range from phenological to biogeographical shifts and have involved in some regions of the Atlantic abrupt ecosystem shifts. These alterations reflect a response of pelagic ecosystems to a warmer temperature regime. Mechanisms are complex because they are nonlinear exhibiting tipping points and varying in space and time. Sensitivity of organisms to temperature changes is high, implicating that a small temperature modification can have sustained ecosystem effects. Implications of these changes for biogeochemical cycles are discussed. Two observed changes detected in the North Sea that could have opposite effects on carbon cycle are discussed. Increase in phytoplankton, as inferred from the phytoplankton colour index derived from the Continuous Plankton Recorder (CPR) survey, has been detected in the North Sea. This pattern has been accompanied by a reduction in the abundance of the herbivorous species Calanus finmarchicus. This might have reduced the grazing pressure and increase diatomaceous ‘fluff’, therefore carbon export in the North Sea. Therefore, it could be argued that the biological carbon pump might increase in this region with sea warming. In the meantime, however, the mean size of organisms (calanoid copepods) has dropped. Such changes have implications for the turnover time of biogenic carbon in plankton organisms and the mean residence time of particulate carbon they produce. The system characterising the warmer period is more based on recycling and less on export. The increase in the minimum turnover time indicates an increase in the ecosystem metabolism, which can be considered as a response of the pelagic ecosystems to climate warming. This phenomenon could reduce carbon export. These two opposite patterns of change are examples of the diversity of mechanisms and pathways the ecosystems may exhibit with climate change. Oversimplification of current biogeochemical models, often due to lack of data and biological understanding, could lead to wrong projection on the direction ecosystems and therefore some biogeochemical cycles might take in a warmer world.

Synergistic effects of climate and fishing in a marine ecosystem

Current climate change and overfishing are affecting the productivity and structure of marine ecosystems. This situation is unprecedented for the marine biosphere and it is essential to understand the mechanisms and pathways by which ecosystems respond. We report that climate change and overfishing are likely to be responsible for a rapid restructuring of a highly productive marine ecosystem with effects throughout the pelagos and the benthos. In the mid-1980s, climate change, consequent modifications in the North Sea plankton, and fishing, all reduced North Sea cod recruitment. In this region, production of many benthic species respond positively and immediately to temperature. Analysis of a long-term, spatially extensive biological (plankton and cod) and physical (sea surface temperature) dataset suggests that synchronous changes in cod numbers and sea temperature have established an extensive trophic cascade favoring lower trophic level groups over economic fisheries. A proliferation of jellyfish that we detect may signal the climax of these changes. This modified North Sea ecology may provide a clear indication of the synergistic consequences of coincident climate change and overfishing. The extent of the ecosystem restructuring that has occurred in the North Sea suggests we are unlikely to reverse current climate and human-induced effects through ecosystem resource management in the short term. Rather, we should understand and adapt to new ecological regimes. This implies that fisheries management policies will have to be fully integrated with the ecological consequences of climate change to prevent a similar collapse in an exploited marine ecosystem elsewhere.

Marine biodiversity and ecosystem function relationships:the potential for practical monitoring applications

There is an increasing demand for environmental assessments of the marine environment to include ecosystem function. However, existing schemes are predominantly based on taxonomic (i.e. structural) measures of biodiversity. Biodiversity and Ecosystem Function (BEF) relationships are suggested to provide a mechanism for converting taxonomic information into surrogates of ecosystem function. This review assesses the evidence for marine BEF relationships and their potential to be used in practical monitoring applications (i.e. operationalized). Five key requirements were identified for the practical application of BEF relationships: (1) a complete understanding of strength, direction and prevalence of marine BEF relationships, (2) an understanding of which biological components are influential within specific BEF relationships, (3) the biodiversity of the selected biological components can be measured easily, (4) the ecological mechanisms that are the most important for generating marine BEF relationships, i.e. identity effects or complementarity, are known and (5) the proportion of the overall functional variance is explained by biodiversity, and hence BEF relationships, has been established. Numerous positive and some negative BEF relationships were found within the literature, although many reproduced poorly the natural species richness, trophic structures or multiple functions of real ecosystems (requirement 1). Null relationships were also reported. The consistency of the positive and negative relationships was often low that compromised the ability to generalize BEF relationships and confident application of BEF within marine monitoring. Equally, some biological components and functions have received little or no investigation. Expert judgement was used to attribute biological components using spatial extent, presence and functional rate criteria (requirement 2). This approach highlighted the main biological components contributing the most to specific ecosystem functions, and that many of the particularly influential components were found to have received the least amount of research attention. The need for biodiversity to be measureable (requirement 3) is possible for most biological components although difficult within the functionally important microbes. Identity effects underpinned most marine BEF relationships (requirement 4). As such, processes that translated structural biodiversity measures into functional diversity were found to generate better BEF relationships. The analysis of the contribution made by biodiversity, over abiotic influences, to the total expression of a particular ecosystem function was rarely measured or considered (requirement 5). Hence it is not possible to determine the overall importance of BEF relationships within the total ecosystem functioning observed. In the few studies where abiotic factors had been considered, it was clear that these modified BEF relationships and have their own direct influence on functional rate. Based on the five requirements, the information required for immediate ‘operationalization’ of BEF relationships within marine functional monitoring is lacking. However, the concept of BEF inclusion within practical monitoring applications, supported by ecological modelling, shows promise for providing surrogate indicators of functioning.

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.

The origin and evolution of synaptic proteins - choanoflagellates lead the way.

The origin of neurons was a key event in evolution, allowing metazoans to evolve rapid behavioral responses to environmental cues. Reconstructing the origin of synaptic proteins promises to reveal their ancestral functions and might shed light on the evolution of the first neuron-like cells in metazoans. By analyzing the genomes of diverse metazoans and their closest relatives, the evolutionary history of diverse presynaptic and postsynaptic proteins has been reconstructed. These analyses revealed that choanoflagellates, the closest relatives of metazoans, possess diverse synaptic protein homologs. Recent studies have now begun to investigate their ancestral functions. A primordial neurosecretory apparatus in choanoflagellates was identified and it was found that the mechanism, by which presynaptic proteins required for secretion of neurotransmitters interact, is conserved in choanoflagellates and metazoans. Moreover, studies on the postsynaptic protein homolog Homer revealed unexpected localization patterns in choanoflagellates and new binding partners, both which are conserved in metazoans. These findings demonstrate that the study of choanoflagellates can uncover ancient and previously undescribed functions of synaptic proteins.

An unusually large phytoplankton spring bloom drives rapid changes in benthic diversity and ecosystem function

In 2012, the Western English Channel experienced an unusually large and long-lived phytoplankton spring bloom. When compared with data from the past 20 years, average phytoplankton biomass at Station L4 (part of the Western Channel Observatory) was approximately 3× greater and lasted 50% longer than any previous year. Regular (mostly weekly) box core samples were collected from this site before, during and after the bloom to determine its impact on macrofaunal abundance, diversity, biomass, community structure and function. The spring bloom of 2012 was shown to support a large and rapid response in the majority of benthic taxa and functional groups. However, key differences in the precise nature of this response, as well as in its timing, was observed between different macrofauna feeding groups. Deposit feeders responded almost instantly at the start of the bloom, primarily thorough an increase in abundance. Suspension feeders and opportunistic/predatory/carnivorous taxa responded slightly more slowly and primarily with an increase in biomass. At the end of the bloom a rapid decline in macrobenthic abundance, diversity and biomass closely followed the decline in phytoplankton biomass. With suspension feeders showing evidence of this decline a few weeks before deposit feeders, it was concluded that this collapse in benthic communities was driven primarily by food availability and competition. However, it is possible that environmental hypoxia and the presence of toxic benthic cyanobacteria could also have contributed to this decline. This study shows evidence for strong benthic–pelagic coupling at L4; a shallow (50 m), coastal, fine-sand habitat. It also demonstrates that in such habitats, it is not just planktonic organisms that demonstrate clear community phenology. Different functional groups within the benthic assemblage will respond to the spring bloom in specific manner, with implications for key ecosystem functions and processes, such as secondary production and bioturbation. Only by taking integrated benthic and pelagic observations over such fine temporal scales (weekly) was the current study able to identify the intimate structure of the benthic response. Similar studies from other habitats and under different bloom conditions are urgently needed to fully appreciate the strength of benthic–pelagic coupling in shallow coastal environments.