Summarising spatial and temporal information in CPR data

The Continuous Plankton Recorder survey provides pan-oceanic data on geographic distribution, species composition, seasonal cycles of abundance, and long-term change during the last 70 years. In this paper we compare and contrast some of the historic data-analytic protocols of the survey, focusing primarily on the various means by which spatio-temporal information in CPR data has been exposed. Relative strengths and limitations are assessed, followed by suggestions for future approaches to the visualisation and summarising of CPR data.

Identifying four phytoplankton functional types from space: An ecological approach

Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

Coccolithophore bloom detection in the north east Atlantic using SeaWiFS: Algorithm description, application and sensitivity analysis

Coccolithophores are the largest source of calcium carbonate in the oceans and are considered to play an important role in oceanic carbon cycles. Current methods to detect the presence of coccolithophore blooms from Earth observation data often produce high numbers of false positives in shelf seas and coastal zones due to the spectral similarity between coccolithophores and other suspended particulates. Current methods are therefore unable to characterise the bloom events in shelf seas and coastal zones, despite the importance of these phytoplankton in the global carbon cycle. A novel approach to detect the presence of coccolithophore blooms from Earth observation data is presented. The method builds upon previous optical work and uses a statistical framework to combine spectral, spatial and temporal information to produce maps of coccolithophore bloom extent. Validation and verification results for an area of the north east Atlantic are presented using an in situ database (N = 432) and all available SeaWiFS data for 2003 and 2004. Verification results show that the approach produces a temporal seasonal signal consistent with biological studies of these phytoplankton. Validation using the in situ coccolithophore cell count database shows a high correct recognition rate of 80% and a low false-positive rate of 0.14 (in comparison to 63% and 0.34 respectively for the established, purely spectral approach). To guide its broader use, a full sensitivity analysis for the algorithm parameters is presented.

Temporal Variations In Annual Production And Biomass In Estuarine Populations Of 2 Polychaetes Nephtys-Hombergi And Ampharete-Acutifrons

Production rates and production/biomass ratios have been estimated for a large number of macrobenthic species (Hargrave, 1977; Robertson, 1979). The usefulness of such estimates is limited by a lack of information on their temporal and spatial stability; we are aware of only one study (Sarvala, 1980) in which production has been estimated for more than one year. The present study investigates the stability of the production (P), biomass (B) and P/B values of two polychaete species, Nephtys hombergi Savigny and Ampharete acutifrons (Grube), over a 5-year period.

Temporal changes in total and size-fractioned chlorophyll-a in surface waters of three provinces in the Atlantic Ocean (September to November) between 2003 and 2010

Phytoplankton total chlorophyll concentration (TCHLa) and phytoplankton size structure are two important ecological indicators in biological oceanography. Using high performance liquid chromatography (HPLC) pigment data, collected from surface waters along the Atlantic Meridional Transect (AMT), we examine temporal changes in TCHLa and phytoplankton size class (PSC: micro-, nano- and pico-phytoplankton) between 2003 and 2010 (September to November cruises only), in three ecological provinces of the Atlantic Ocean. The HPLC data indicate no significant change in TCHLa in northern and equatorial provinces, and an increase in the southern province. These changes were not significantly different to changes in TCHLa derived using satellite ocean-colour data over the same study period. Despite no change in AMT TCHLa in northern and equatorial provinces, significant differences in PSC were observed, related to changes in key diagnostic pigments (fucoxanthin, peridinin, 19′-hexanoyloxyfucoxanthin and zeaxanthin), with an increase in small cells (nano- and pico-phytoplankton) and a decrease in larger cells (micro-phytoplankton). When fitting a three-component model of phytoplankton size structure — designed to quantify the relationship between PSC and TCHLa to each AMT cruise, model parameters varied over the study period. Changes in the relationship between PSC and TCHLa have wide implications in ecology and marine biogeochemistry, and provide key information for the development and use of empirical ocean-colour algorithms. Results illustrate the importance of maintaining a time-series of in-situ observations in remote regions of the ocean, such as that acquired in the AMT programme.

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.

Predictable hydrodynamic conditions explain temporal variations in the density of benthic foraging seabirds in a tidal stream environment

Tidal stream turbines could have several direct impacts upon pursuit-diving seabirds foraging within tidal stream environments (mean horizontal current speeds > 2 ms−1), including collisions and displacement. Understanding how foraging seabirds respond to temporally variable but predictable hydrodynamic conditions immediately around devices could identify when interactions between seabirds and devices are most likely to occur; information which would quantify the magnitude of potential impacts, and also facilitate the development of suitable mitigation measures. This study uses shore-based observational surveys and Finite Volume Community Ocean Model outputs to test whether temporally predictable hydrodynamic conditions (horizontal current speeds, water elevation, turbulence) influenced the density of foraging black guillemots Cepphus grylle and European shags Phalacrocorax aristotelis in a tidal stream environment in Orkney, United Kingdom, during the breeding season. These species are particularly vulnerable to interactions with devices due to their tendency to exploit benthic and epi-benthic prey on or near the seabed. The density of both species decreased as a function of horizontal current speeds, whereas the density of black guillemots also decreased as a function of water elevation. These relationships could be linked to higher energetic costs of dives in particularly fast horizontal current speeds (>3 ms−1) and deeper water. Therefore, interactions between these species and moving components seem unlikely at particularly high horizontal current speeds. Combining this information, with that on the rotation rates of moving components at lower horizontal current speeds, could be used to assess collision risk in this site during breeding seasons. It is also likely that moderating any device operation during both lowest water elevation and lowest horizontal current speeds could reduce the risk of collisions for these species in this site during this season. The approaches used in this study could have useful applications within Environmental Impact Assessments, and should be considered when assessing and mitigating negative impacts from specific devices within development sites.