PML Applications (United Kingdom)

Abstract Photosynthesis–irradiance (PI) relationships are important for phytoplankton ecology and quantifying carbon fixation rates in the environment. However, the parameters of PI relationships are typically unknown across space and time. Here we use machine learning, satellite remote‐sensing, and a database of in situ PI relationships to build models that predict the seasonal cycle of PI parameters as a function of satellite‐observed variables. Using only surface light, temperature, and chlorophyll, we achieve an R 2 of 58% for predicting photosynthesis rates at saturating light () and an R 2 of 78% for predicting the light saturation parameter (). Predictability is maximized when averaging environmental covariates over 30‐d () and 25‐d () timescales, indicating that environmental history and community turnover timescales are important for predicting in situ PI relationships. These results will help improve the parameterization of satellite‐based primary production models and quantify emergent environmental integration timescales in photosynthetic communities.

In this paper, we report the use of conjugated polymer nanoparticles as a new analytical tool for the detection of microplastics, with the ability to stain polystyrene effectively for at least 2.5 year after initial detection.

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

Abstract. Biofouling is a major vector in the transfer of non-native species around the world. Species can be transported on virtually all submerged areas of ships (e.g. hulls, sea chests, propellers) and so antifouling systems are used to reduce fouling. However, with increased regulation of biocides used in antifoulants (e.g. the International Maritime Organization tributyltin ban in 2008), there is a need to find efficient and sustainable alternatives. Here, we tested the hypothesis that short doses of low salinity water could be used to kill fouling species in sea chests. Settlement panels were suspended at 1.5 m depth in a Plymouth marina for 24 months by which time they had developed mature biofouling assemblages. We exposed these panels to three different salinities (7, 20 and 33) for 2 hours using a model sea chest placed in the marina and flushed with freshwater. Fouling organism diversity and abundance were assessed before panels were treated, immediately after treatment, and then 1 week and 1 month later. Some native ascidian Dendrodoa grossularia survived, but all other macrobenthos were killed by the salinity 7 treatment after 1 week. The salinity 20 treatment was not effective at killing the majority of fouling organisms. On the basis of these results, we propose that sea chests be flushed with freshwater for at least 2 hours before ships leave port. This would not cause unnecessary delays or costs and could be a major step forward in improving biosecurity.

The question really should be: are we really serious about controlling the global spread of aquatic invasives? Given that it has so far taken over 11 years to even get close to ratifying the International Maritime Organisation (IMO) Ballast Water Convention, the answer has to be ‘not really’! Coupled with this, we are also aware that another significant vector of transport for aquatic invasives is hull fouling on ships, which is currently unregulated on a global scale.