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.

Automatic classification of field-collected dinoflagellates by artificial neural network

Automatic taxonomic categorisation of 23 species of dinoflagellates was demonstrated using field-collected specimens. These dinoflagellates have been responsible for the majority of toxic and noxious phytoplankton blooms which have occurred in the coastal waters of the European Union in recent years and make severe impact on the aquaculture industry. The performance by human 'expert' ecologists/taxonomists in identifying these species was compared to that achieved by 2 artificial neural network classifiers (multilayer perceptron and radial basis function networks) and 2 other statistical techniques, k-Nearest Neighbour and Quadratic Discriminant Analysis. The neural network classifiers outperform the classical statistical techniques. Over extended trials, the human experts averaged 85% while the radial basis network achieved a best performance of 83%, the multilayer perceptron 66%, k-Nearest Neighbour 60%, and the Quadratic Discriminant Analysis 56%.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.

What are the local impacts of energy systems on marine ecosystem services: a systematic map protocol

Background: Increasing concentrations of atmospheric greenhouse gases (GHG) and its impact on the climate has resulted in many international governments committing to reduce their GHG emissions. The UK, for example, has committed to reducing its carbon emissions by 80% by 2050. Suggested ways of reaching such a target are to increase dependency on offshore wind, offshore gas and nuclear. It is not clear, however, how the construction, operation and decommissioning of these energy systems will impact marine ecosystem services, i.e. the services obtained by people from the natural environment such as food provisioning, climate regulation and cultural inspiration. Research on ecosystem service impacts associated with offshore energy technologies is still in its infancy. The objective of this review is to bolster the evidence base by firstly, recording and describing the impacts of energy technologies at the marine ecosystems and human level in a consistent and transparent way; secondly, to translate these ecosystem and human impacts into ecosystem service impacts by using a framework to ensure consistency and comparability. The output of this process will be an objective synthesis of ecosystem service impacts comprehensive enough to cover different types of energy under the same analysis and to assist in informing how the provision of ecosystem services will change under different energy provisioning scenarios. Methods: Relevant studies will be sourced using publication databases and selected using a set of selection criteria including the identification of: (i) relevant subject populations such as marine and coastal species, marine habitat types and the general public; (ii) relevant exposure types including offshore wind farms, offshore oil and gas platforms and offshore structures connected with nuclear; (iii) relevant outcomes including changes in species structure and diversity; changes in benthic, demersal and pelagic habitats; and changes in cultural services. The impacts will be synthesised and described using a systematic map. To translate these findings into ecosystem service impacts, the Common International Classification of Ecosystem Services (CICES) and Millennium Ecosystem Assessment (MEA) frameworks are used and a detailed description of the steps taken provided to ensure transparency and replicability.

Can benthic community structure be used to predict the process of bioturbation in real ecosystems

Disentangling the roles of environmental change and natural environmental variability on biologically mediated ecosystem processes is paramount to predict future marine ecosystem functioning. Bioturbation, the biogenic mixing of sediments, has a regulating role in marine biogeochemical processes. However, our understanding of bioturbation as a community level process and of its environmental drivers is still limited by loose use of terminology, and a lack of consensus about what bioturbation is. To help resolve these challenges, this empirical study investigated the links between four different attributes of bioturbation (bioturbation depth, activity and distance, and biodiffusive transport); the ability of an index of bioturbation (BPc) to predict each of them; and their relation to seasonality, in a shallow coastal system – the Western Channel Observatory, UK. Bioturbation distance depended on changes in benthic community structure, while the other three attributes were more directly influenced by seasonality in food availability. In parallel, BPc successfully predicted bioturbation distance but not the other attributes of bioturbation. This study therefore highlights that community bioturbation results from this combination of processes responding to environmental variability at different time-scales. However, community level measurements of bioturbation across environmental variability are still scarce, and BPc is calculated using commonly available data on benthic community structure and the functional classification of invertebrates. Therefore, BPc could be used to support the growth of landscape scale bioturbation research, but future uses of the index need to consider which bioturbation attributes the index actually predicts. As BPc predicts bioturbation distance, estimated here using a random-walk model applicable to community settings, studies using either of the metrics should be directly comparable and contribute to a more integrated future for bioturbation research.

Tillin, H. & Tyler-Walters, H., 2014. Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 2 Report – Literature review and sensitivity assessments for ecological groups for circalittoral and offshore Level 5 biotopes. JNCC Report No. 512B, 260 pp.

Human activities within the marine environment give rise to a number of pressures on seabed habitats. Improved understanding of the sensitivity of subtidal sedimentary habitats is required to underpin the management advice provided for Marine Protected Areas, as well as supporting other UK marine monitoring and assessment work. The sensitivity of marine sedimentary habitats to a range of pressures induced by human activities has previously been systematically assessed using approaches based on expert judgement for Defra Project MB0102 (Tillin et al. 2010). This previous work assessed sensitivity at the level of the broadscale habitat and therefore the scores were typically expressed as a range due to underlying variation in the sensitivity of the constituent biotopes. The objective of this project was to reduce the uncertainty around identifying the sensitivity of selected subtidal sedimentary habitats by assessing sensitivity, at a finer scale and incorporating information on the biological assemblage, for 33 Level 5 circalittoral and offshore biotopes taken from the Marine Habitat Classification of Britain and Ireland (Connor et al. 2004). Two Level 6 sub-biotopes were also included in this project as these contain distinctive characterising species that differentiate them from the Level 5 parent biotope. Littoral, infralittoral, reduced and variable salinity sedimentary habitats were excluded from this project as the scope was set for assessment of circalittoral and offshore sedimentary communities. This project consisted of three Phases. • Phase 1 - define ecological groups based on similarities in the sensitivity of characterising species from the Level 5 and two Level 6 biotopes described above. • Phase 2 - produce a literature review of information on the resilience and resistance of characterising species of the ecological groups to pressures associated with activities in the marine environment. • Phase 3 - to produce sensitivity assessment ‘proformas’ based on the findings of Phase 2 for each ecological group. This report outlines results of Phase 2. The Tillin et al., (2010) sensitivity assessment methodology was modified to use the best available scientific evidence that could be collated within the project timescale. An extensive literature review was compiled, for peer reviewed and grey literature, to examine current understanding about the effects of pressures from human activities on circalittoral and offshore sedimentary communities in UK continental shelf waters, together with information on factors that contribute to resilience (recovery) of marine species. This review formed the basis of an assessment of the sensitivity of the 16 ecological groups identified in Phase 1 of the project (Tillin & Tyler-Walters 2014). As a result: • the state of knowledge on the effects of each pressure on circalittoral and offshore benthos was reviewed; • the resistance, resilience and, hence, sensitivity of sixteen ecological groups, representing 96 characteristic species, were assessed for eight separate pressures; • each assessment was accompanied by a detailed review of the relevant evidence; Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • knowledge gaps and sources of uncertainty were identified for each group; • each assessment was accompanied by an assessment of the quality of the evidence, its applicability to the assessment and the degree of concordance (agreement) between the evidence, to highlight sources of uncertainty as an assessment of the overall confidence in the sensitivity assessment, and finally • limitations in the methodology and the application of sensitivity assessments were outlined. This process demonstrated that the ecological groups identified in Phase 1 (Tillin & Tyler-Walters 2014) were viable groups for sensitivity assessment, and could be used to represent the 33 circalittoral and offshore sediments biotopes identified at the beginning of the project. The results of the sensitivity assessments show: • the majority of species and hence ecological groups in sedimentary habitats are sensitive to physical change, especially loss of habitat and sediment extraction, and change in sediment type; • most sedimentary species are sensitive to physical damage, e.g. abrasion and penetration, although deep burrowing species (e.g. the Dublin Bay prawn - Nephrops norvegicus and the sea cucumber - Neopentadactyla mixta) are able to avoid damaging effects to varying degrees, depending on the depth of penetration and time of year; • changes in hydrography (wave climate, tidal streams and currents) can significantly affect sedimentary communities, depending on whether they are dominated by deposit, infaunal feeders or suspension feeders, and dependant on the nature of the sediment, which is itself modified by hydrography and depth; • sedentary species and ecological groups that dominate the top-layer of the sediment (either shallow burrowing or epifaunal) remain the most sensitive to physical damage; • mobile species (e.g. interstitial and burrowing amphipods, and perhaps cumaceans) are the least sensitive to physical change or damage, and hydrological change as they are already adapted to unstable, mobile substrata; • sensitivity to changes in organic enrichment and hence oxygen levels, is variable between species and ecological groups, depending on the exact habitat preferences of the species in question, although most species have at least a medium sensitivity to acute deoxygenation; • there is considerable evidence on the effects of bottom-contact fishing practices and aggregate dredging on sedimentary communities, although not all evidence is directly applicable to every ecological group; • there is lack of detailed information on the physiological tolerances (e.g. to oxygenation, salinity, and temperature), habitat preferences, life history and population dynamics of many species, so that inferences has been made from related species, families, or even the same phylum; • there was inadequate evidence to assess the effects of non-indigenous species on most ecological groups, and Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • there was inadequate evidence to assess the effects of electromagnetic fields and litter on any ecological group. The resultant report provides an up-to-date review of current knowledge about the effects of pressures resulting from human activities of circalittoral and offshore sedimentary communities. It provides an evidence base to facilitate and support the provision of management advice for Marine Protected Areas, development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. However, such a review will require at least annual updates to take advantage of new evidence and new research as it becomes available. Also further work is required to test how ecological group assessments are best combined in practice to advise on the sensitivity of a range of sedimentary biotopes, including the 33 that were originally examined.