Diversity and structure of copepod assemblages were investigated using 259 WP2 zooplankton samples collected from the top 200 m of the Atlantic Ocean between 60°N and 63°S. Whilst richness at a number of taxonomic levels (genera-superfamily) demonstrated a smooth latitudinal cline from the tropics towards the poles, other diversity indices such as evenness and taxonomic distinctness showed abrupt changes around 40°N and 40°S, coincident with sea surface temperatures of 17 to 20°C. In the tropics and subtropics, copepod communities were characterised by high stable taxonomic diversity and a relatively even distribution of genera within samples. In contrast, at high latitudes and low temperatures communities showed large variation in overall diversity, evenness and distinctness. Multidimensional scaling and cluster analysis of transformed generic abundances, pooled into 5°latitudinal means, produced ordinations consistent with the recent subdivision of the oceans into 4 primary biomes based on temporal and spatial patterns of primary production. The copepod community corresponding to the Trades biome, where primary production is broadly continuous, exhibited high generic richness and evenness. In contrast, community structure in the Polar biome, where primary production is highly seasonal, was highly variable and dominated by a few genera. These genera tended to be herbivorous or omnivorous and stored lipid. The Westerlies biome and the Benguela province had intermediate copepod community characteristics. We therefore suggest that copepod diversity and community structure are closely tied not to temperature or energy input, but to the temporal patterns of primary and secondary production.
Acoustic surveys for biomass estimation require accurate identification of echoes from the target species. In one objective technique for identifying Antarctic krill, the difference between mean volume-backscattering strength at two frequencies is used, but can misclassify small krill and other plankton. Here, we investigate ways to improve target identification by including characteristics of backscattering energy and morphology of aggregations. To do this, multi-frequency acoustic data were collected concurrently with target fishing of Antarctic krill and other euphausiid and salp aggregations. Parameter sets for these known aggregations were collated and used to develop empirical classifications. Both linear discriminant-function analysis (DFA) and the artificial neural network technique were employed. In both cases, acoustic-backscattering energy parameters were most important for discriminating between Antarctic krill and other zooplankton. However, swarm morphology and other parameters improved the discrimination, particularly between krill and salps. Our study suggests that for krill-biomass estimates, a simple DFA based on acoustic-energy parameters is a substantial improvement over current dB-difference acoustic methods; but studies requiring the discrimination of zooplankton other than krill must still be supported by target fishing.
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