Integrated Monitoring of Mola mola Behaviour in Space and Time

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.

Integrated Monitoring of Mola mola Behaviour in Space and Time

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.

Measurement Of The Responses Of Individuals To Environmental-Stress And Pollution - Studies With Bivalve Mollusks

Certain physiological differences between individuals in different populations of the mussel, Mytilus edulis, are described. In particular, the scope for growth differs in space and time and may be used to assess the animals' physiological condition. When the required measurements are made in the field, the rates of growth predicted from the physiological data agree well with observed rates of growth. An alternative approach utilizes mussels transplanted to various waters, with indices of condition then measured in the laboratory under standard conditions; an example of this approach is illustrated. Laboratory experiments are used to equate various levels of physiological condition with fecundity, in an attempt to equate physiological effects on the individual with likely population damage. A cytochemical index of stress is described, based on the latency of lysosomal enzymes; spatial variability in this index, and its relation with the scope for growth, are discussed. Finally, the results of some experiments on the effects of petroleum hydrocarbons on mussels are described and the presence of inducible activity of NADPH-dependent tetrazolium reductase in the blood cells is demonstrated. Certain considerations that apply in adopting similar measurements of biological effects of pollution in environmental monitoring programmes are discussed.

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.

Multi-decadal oceanic ecological datasets and their application in marine policy and management

Long-term biological time-series in the oceans are relatively rare. Using the two longest of these we show how the information value of such ecological time-series increases through space and time in terms of their potential policy value. We also explore the co-evolution of these oceanic biological time-series with changing marine management drivers. Lessons learnt from reviewing these sequences of observations provide valuable context for the continuation of existing time-series and perspective for the initiation of new time-series in response to rapid global change. Concluding sections call for a more integrated approach to marine observation systems and highlight the future role of ocean observations in adaptive marine management.

Spatial and temporal variability in Scotian Shelf zooplankton communities

Zooplankton are indicators of the response of marine ecosystems to environmental variability. The relationships between zooplankton communities on the Scotian Shelf and hydrographic and geographic regions of the Scotian Shelf in the 1990s and 2000s were described using complementary data sets, each resolving different space and time scales. The Atlantic Zone Monitoring Program (AZMP) sampled Scotian Shelf zooplankton from the whole water column twice per year at stations along three cross-shelf transects and semi-monthly at a fixed station on the inshore central shelf, while Continuous Plankton Recorder (CPR) samples were collected from near-surface waters approximately monthly on an along-shelf transect. Variability patterns were compared among these three data sets to identify robust spatial and interannual trends. Stations were clustered based on taxonomic composition, and spatial clusters were compared to hydrographic boundaries and bathymetry to determine whether temporal changes in community composition were driven by changes in water mass distributions on the shelf. This project identifies zooplankton community and abundance shifts that may affect fish recruitment in the northwest Atlantic and contributes to development of ecosystem-based fisheries management on the Scotian Shelf.

Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.