Use of satellite data for modelling food availability and survival of marine fish larvae

A modelling scheme is described which uses satellite retrieved sea-surface temperature and chlorophyll-a to derive monthly zooplankton biomass estimates in the eastern North Atlantic; this forms part of a bio-physical model of inter-annual variations in the growth and survival of larvae and post-larvae of mackerel (Scomber scombrus). The temperature and chlorophyll data are incorporated first to model copepod (Calanus) egg production rates. Egg production is then converted to available food using distribution data from the Continuous Plankton Recorder (CPR) Survey, observed population biomass per unit daily egg production and the proportion of the larval mackerel diet comprising Calanus. Results are validated in comparison with field observations of zooplankton biomass. The principal benefit of the modelling scheme is the ability to use the combination of broad scale coverage and fine scale temporal and spatial variability of satellite data as driving forces in the model; weaknesses are the simplicity of the egg production model and the broad-scale generalizations assumed in the raising factors to convert egg production to biomass.

Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.

The importance of high frequency data in ecological modelling.

The purpose of this note is to discuss the role of high frequency data in ecological modelling and to identify some of the data requirements for the further development of ecological models for operational oceanography. There is a pressing requirement for the establishment of data acquisition systems for key ecological variables with a high spatial and temporal coverage. Such a system will facilitate the development of operational models. It is envisaged that both in-situ and remotely sensed measurements will need to combined to achieve this aim.

Data rescue and re-use: Recycling old information to address new policy concerns

Information on past trends is essential to inform future predictions and underpin attribution needed to drive policy responses. It has long been recognised that sustained observations are essential for disentangling climate-driven change from other regional and local-scale anthropogenic impacts and environmental fluctuations or cycles in natural systems. This paper highlights how data rescue and re-use have contributed to the debate on climate change responses of marine biodiversity and ecosystems. It also illustrates via two case studies the re-use of old data to address new policy concerns. The case studies focus on (1) plankton, fish and benthos from the Western English Channel and (2) broad-scale and long-term studies of intertidal species around the British Isles. Case study 1 using the Marine Biological Association of the UK's English Channel data has shown the influence of climatic fluctuations on phenology (migration and breeding patterns) and has also helped to disentangle responses to fishing pressure from those driven by climate, and provided insights into ecosystem-level change in the English Channel. Case study 2 has shown recent range extensions, increases of abundance and changes in phenology (breeding patterns) of southern, warm-water intertidal species in relation to recent rapid climate change and fluctuations in northern and southern barnacle species, enabling modelling and prediction of future states. The case is made for continuing targeted sustained observations and their importance for marine management and policy development.

Modelling a light-driven phytoplankton succession

We used a numerical model to investigate if and to what extent cellular photoprotective capacity accounts for succession and vertical distribution of marine phytoplankton species/groups. A model describing xanthophyll photoprotective activity in phytoplankton has been implemented in the European Regional Sea Ecosystem Model and applied at the station L4 in the Western English Channel. Primary producers were subdivided into three phytoplankton functional types defined in terms of their capacity to acclimate to different light-specific environments: low light (LL-type), high light (HL-type) and variable light (VL-type) adapted species. The LL-type is assumed to have low cellular level of xanthophyll-cycling pigments (PX) relative to the modelled photosynthetically active pigments (chlorophyll and fucoxanthin (FUCO) = PSP). The HL-type has high PX content relative to PSP while VL-type presents an intermediate PX to PSP ratio. Furthermore, the VL-type is capable of reversibly converting FUCO to PX and synthesizing new PX under high-light stress. In order to reproduce phytoplankton community succession with each of the three groups being dominant in different periods of the year, we had also to assume reduced grazing pressure on HL-adapted species. Model simulations realistically reproduce the observed seasonal patterns of pigments and nutrients highlighting the reasonability of the underpinning assumptions. Our model suggests that pigment-mediated photophysiology plays a primary role in determining the evolution of marine phytoplankton communities in the winter-spring period corresponding to the shoaling of the mixed layer and the increase of light intensity. Grazing selectivity however contributes to the phytoplankton community composition in summer.

A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling

1. A first step in the analysis of complex movement data often involves discretisation of the path into a series of step-lengths and turns, for example in the analysis of specialised random walks, such as Lévy flights. However, the identification of turning points, and therefore step-lengths, in a tortuous path is dependent on ad-hoc parameter choices. Consequently, studies testing for movement patterns in these data, such as Lévy flights, have generated debate. However, studies focusing on one-dimensional (1D) data, as in the vertical displacements of marine pelagic predators, where turning points can be identified unambiguously have provided strong support for Lévy flight movement patterns. 2. Here, we investigate how step-length distributions in 3D movement patterns would be interpreted by tags recording in 1D (i.e. depth) and demonstrate the dimensional symmetry previously shown mathematically for Lévy-flight movements. We test the veracity of this symmetry by simulating several measurement errors common in empirical datasets and find Lévy patterns and exponents to be robust to low-quality movement data. 3. We then consider exponential and composite Brownian random walks and show that these also project into 1D with sufficient symmetry to be clearly identifiable as such. 4. By extending the symmetry paradigm, we propose a new methodology for step-length identification in 2D or 3D movement data. The methodology is successfully demonstrated in a re-analysis of wandering albatross Global Positioning System (GPS) location data previously analysed using a complex methodology to determine bird-landing locations as turning points in a Lévy walk. For this high-resolution GPS data, we show that there is strong evidence for albatross foraging patterns approximated by truncated Lévy flights spanning over 3·5 orders of magnitude. 5. Our simple methodology and freely available software can be used with any 2D or 3D movement data at any scale or resolution and are robust to common empirical measurement errors. The method should find wide applicability in the field of movement ecology spanning the study of motile cells to humans.