An innovative statistical approach to constructing a readily comprehensible food web for a demersal fish community

Many food webs are so complex that it is difficult to distinguish the relationships between predators and their prey. We have therefore developed an approach that produces a food web which clearly demonstrates the strengths of the relationships between the predator guilds of demersal fish and their prey guilds in a coastal ecosystem. Subjecting volumetric dietary data for 35 abundant predators along the lower western Australia coast to cluster analysis and the SIMPROF routine separated the various species x length class combinations into 14 discrete predator guilds. Following nMDS ordination, the sequence of points for these predator guilds represented a 'trophic' hierarchy. This demonstrated that, with increasing body size, several species progressed upwards through this hierarchy, reflecting a marked change in diet, whereas others remained within the same guild. A novel use of cluster analysis and SIMPROF then identified each group of prey that was ingested in a common pattern across the full suite of predator guilds. This produced 12 discrete groups of taxa (prey guilds) that each typically comprised similar ecological/functional prey, which were then also aligned in a hierarchy. The hierarchical arrangements of the predator and prey guilds were plotted against each other to show the percentage contribution of each prey guild to the diet of each predator guild. The resultant shade plot demonstrates quantitatively how food resources are spread among the fish species and revealed that two prey guilds, one containing cephalopods and teleosts and the other small benthic/epibenthic crustaceans and polychaetes, were consumed by all predator guilds.

Live discrimination of Calanus glacialis and C. finmarchicus females: can we trust phenological differences?

Two key players in the Arctic and subarctic marine ecosystem are the calanoid copepods, Calanus finmarchicus and C. glacialis. Although morphologically very similar, these sibling species have different life cycles and roles in the Arctic pelagic marine ecosystem. Considering that the distribution of C. glacialis corresponds to Arctic water masses and C. finmarchicus to Atlantic water masses, the species are frequently used as climate indicators. Consequently, correct identification of the two species is essential if we want to understand climate-impacted changes on Calanus-dominated marine ecosystems such as the Arctic. Here, we present a novel morphological character (redness) to distinguish live females of C. glacialis and C. finmarchicus and compare it to morphological (prosome length) and genetic identification. The characters are tested on 300 live females of C. glacialis and C. finmarchicus from Disko Bay, western Greenland. Our analysis confirms that length cannot be used as a stand-alone criterion for separation. The results based on the new morphological character were verified genetically using a single mitochondrial marker (16S) and nuclear loci (six microsatellites and 12 InDels). The pigmentation criterion was also used on individuals (n = 89) from Young Sound fjord, northeast Greenland to determine whether the technique was viable in different geographical locations. Genetic markers based on mitochondrial and nuclear loci were corroborative in their identification of individuals and revealed no hybrids. Molecular identification confirmed that live females of the two species from Greenlandic waters, both East and West, can easily be separated by the red pigmentation of the antenna and somites of C. glacialis in contrast to the pale opaque antenna and somites of C. finmarchicus, confirming that the pigmentation criterion is valid for separation of the two species

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.