Sardine cycles, krill declines, and locust plagues: revisiting ‘wasp-waist’ food webs

‘Wasp-waist’ systems are dominated by a mid trophic-level species that is thought to exert top-down control on its food and bottom-up control on its predators. Sardines, anchovy, and Antarctic krill are suggested examples, and here we use locusts to explore whether the wasp-waist concept also applies on land. These examples also display the traits of mobile aggregations and dietary diversity, which help to reduce the foraging footprint from their large, localised biomasses. This suggests that top-down control on their food operates at local aggregation scales and not at wider scales suggested by the original definition of wasp-waist. With this modification, the wasp-waist framework can cross-fertilise marine and terrestrial approaches, revealing how seemingly disparate but economically important systems operate.

Feeding of larval sardine Sardina pilchardus (Walbaum) off the north coast of Spain

In April and May 1991 and between March and June 1992 data regarding the diet of larval S. pilchardus in relation to food availability was gathered. Interpretation of results is compromised by the tendency of sardine larvae to defecate their gut contents during sampling. The most common food organisms in the guts (78-89%) were the developmental stages of copepods (eggs, nauplii and copepodites). Percentage composition of copepod nauplii in the diet decreased with increasing larval size, while copepodites increased. There was no consistent relationship between food availability and feeding success, probably because feeding conditions were generally adequate.

Biophysical models of larval dispersal in the Benguela Current ecosystem

We synthesise and update results from the suite of biophysical, larval-dispersal models developed in the Benguela Current ecosystem. Biophysical models of larval dispersal use outputs of physical hydrodynamic models as inputs to individual-based models in which biological processes acting during the larval life are included. In the Benguela, such models were first applied to simulate the dispersal of anchovy Engraulis encrasicolus and sardine Sardinops sagax ichthyoplankton, and more recently of the early life stages of chokka-squid Loligo reynaudii and Cape hakes Merluccius spp. We identify how the models have helped advance understanding of key processes for these species. We then discuss which aspects of the early life of marine species in the Benguela Current ecosystem are still not well understood and could benefit from new modelling studies.

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

The Southern Ocean and South Pacific Region

The Region comprises three sub-regions (FAO Statistical Areas) with very different characteristics. The South Pacific includes the vast and virtually unpopulated Southern Ocean surrounding the Antarctic. It has the world’s largest fisheries off Peru and Chile and some of the world’s best managed fisheries in Australia and New Zealand. The Region has over 27% of the world’s ocean area and over 98% of the Region’s total area of 91 million km2 is ‘open ocean’. The Region contains less than 5% of the global continental shelf area and only a fraction of this area is covered by three large marine ecosystems (the New Zealand Shelf, the Humboldt Current and the Antarctic large marine ecosystems (LMEs). The Humboldt Current System (HCS) is the world’s largest upwelling which provides nutrients for the world’s largest fisheries. The Region also has a high number of seamounts. The marine capture fisheries of the Region produce over 13 million tons annually and an expanding aquaculture industry produces over 1.5 million tons. Peru’s anchoveta fishery provides about half the world’s supply of fish meal and oil, key ingredients of animal and fish feeds. El Niño Southern Oscillations (ENSOs), known more generally as El Niños, can substantially change the species composition of the key small pelagic catches (anchovy, sardine, horse mackerel and jack mackerel) causing production to fluctuate from about 4-8 million tons. Partly due to the lack of upwelling and shelf areas, fisheries production in the Southern Ocean and Area 81 is relatively small but supports economically important commercial and recreational fisheries and aquaculture in New Zealand and in New South Wales (Australia). Krill remains a major underexploited resource, but is also a keystone species in the Antarctic food web. The Region is home to numerous endangered species of whales, seals and seabirds and has a high number of seamounts, vulnerable ecosystems fished for high-value species such as orange roughy.

The Southern Ocean and South Pacific Region

The Region comprises three sub-regions (FAO Statistical Areas) with very different characteristics. The South Pacific includes the vast and virtually unpopulated Southern Ocean surrounding the Antarctic. It has the world’s largest fisheries off Peru and Chile and some of the world’s best managed fisheries in Australia and New Zealand. The Region has over 27% of the world’s ocean area and over 98% of the Region’s total area of 91 million km2 is ‘open ocean’. The Region contains less than 5% of the global continental shelf area and only a fraction of this area is covered by three large marine ecosystems (the New Zealand Shelf, the Humboldt Current and the Antarctic large marine ecosystems (LMEs). The Humboldt Current System (HCS) is the world’s largest upwelling which provides nutrients for the world’s largest fisheries. The Region also has a high number of seamounts. The marine capture fisheries of the Region produce over 13 million tons annually and an expanding aquaculture industry produces over 1.5 million tons. Peru’s anchoveta fishery provides about half the world’s supply of fish meal and oil, key ingredients of animal and fish feeds. El Niño Southern Oscillations (ENSOs), known more generally as El Niños, can substantially change the species composition of the key small pelagic catches (anchovy, sardine, horse mackerel and jack mackerel) causing production to fluctuate from about 4-8 million tons. Partly due to the lack of upwelling and shelf areas, fisheries production in the Southern Ocean and Area 81 is relatively small but supports economically important commercial and recreational fisheries and aquaculture in New Zealand and in New South Wales (Australia). Krill remains a major underexploited resource, but is also a keystone species in the Antarctic food web. The Region is home to numerous endangered species of whales, seals and seabirds and has a high number of seamounts, vulnerable ecosystems fished for high-value species such as orange roughy.

Is the Russell Cycle a true cycle? Multidecadal zooplankton and climate trends in the western English Channel

The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.

Is the Russell Cycle a true cycle? Multidecadal zooplankton and climate trends in the western English Channel

The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.