Genetic Diversity in Marine Molluscs: A Test of the Niche-Width Variation Hypothesis

Abstract. A test of the niche width variation hypothesis was conducted in the three Mediterranean littoral species of the family Trochidae: Monodonta turbinata, M. turbiformis and Gibbula richardi. Allozymic variation encoded by 26 gene loci was analyzed, and the levels of polymorphism (P), heterozygosity (H) and allele diversity per locus (A) were estimated and appear to support the niche-width variation hypothesis. The broad-niche species, M. turbiformis and G. richardi are more polymorphic and heterozygous than the relatively narrow-niche M. turbinata (P = 0.571; 0.731 and 0.417; H = 0.108; 0.116 and 0.078; A = 2.025; 2.489 and 1.965, respectively).     

Decadal Variability of Subsurface Temperature in the Central North Pacific

Decadal variability of subsurface temperature in the North Pacific has been investigated. Two dominant regions were found; the central subarctic region (CSa) and the north-eastern subtropical region (NESt). In CSa, cooling (warming) of wintertime subsurface temperature corresponds to the large (small) temperature gradient and southward (northward) shift of subsurface temperature front, associated with the increase (decrease) of positive wind stress curl and the southward (northward) shift of curl τ zero line with 2 years delay. It is suggested that the relocation of subtropical-subarctic boundary plays an important role. In NESt, importance of heat flux through the sea surface and heat divergence in the Ekman layer is also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

南海上层海洋热含量的年际和年代际变化

分析了1959—1988年南海表面至100m垂直平均温度（TAV）资料，结果表明：南海上层海洋热含量存在明显的准两年、4—5年和年代际振动。在E1Nino年，南海上层热含量显著增加。50年代末至70年代初，南海TAV为负距平，此后转为正距平。南海TAV的变化与ENSO事件、东亚冬季风和热带大气环流的变异密切相关。     

Wind-driven interannual variability over the northeast Pacific Ocean

Interannual variability of the sea surface height (SSH) over the northeast Pacific Ocean is hindcast with a reduced-gravity, quasi-geostrophic model that includes linear damping. The model is forced with monthly Ekman pumping fields derived from the NCEP reanalysis wind stresses. The numerical solution is compared with SSH observations derived from satellite altimeter data and gridded at a lateral resolution of 1 degree. Provided that the reduced gravity parameter is chosen appropriately, the results demonstrate that the model has significant hindcast skill over interior regions of the basin, away from continental boundaries. A damping time scale of 2 to 3 years is close to optimal, although the hindcast skill is not strongly dependent on this parameter.A simplification of the quasi-geostrophic model is considered in which Rossby waves are eliminated, yielding a Markov model driven by local Ekman pumping. The results approximately reproduce the hindcast skill of the more complete quasi-geostrophic model and indicate that the interannual SSH variability is dominated by the local response to wind forcing. There is a close correspondence the two leading empirical orthogonal modes of the local model and those of the observed SSH anomalies. The latter account for over half of the variance of the interannual signal over the region.     

Monitoring the Kuroshio Extension with Dynamically Constrained Synthesis of the Acoustic Tomography, Satellite Altimeter and in situ Data

A finite-difference quasigeostrophic (QG) model of an open ocean region has been employed to produce a dynamically constrained synthesis of acoustic tomography and satellite altimetry data with in situ observations. The assimilation algorithm is based upon the 4D variational data interpolation scheme controlled by the model's initial and boundary conditions. The data sets analyzed include direct and differential travel times measured at the array of five acoustic transceivers deployed by JAMSTEC in the region of the Kuroshio Extension in 1997, Topex/Poseidon altimetry, CTD soundings, and ADCP velocity profiles. The region monitored is located within the area 27.5°–36.5°N, 143°–155°. The results of assimilation show that mesoscale variability can be effectively reconstructed by five transceivers measuring direct and reciprocal travel times supported by relatively sparse in situ measurements. The misfits between model and data lie within the observational error bars for all the data types used in assimilation. We have compared the results of assimilation with the statistical inversion of travel time data and analyzed energy balances of the optimized model solution. Energy exchange between the depth-averaged and shear components of the observed currents reveals a weak decay of the barotropic mode at the rate of 0.2 ± 0.7⋅10⁻⁵ cm²/s³ due to topographic interaction. Mean currents in the region are unstable with an estimate of the available potential energy flux from the mean current to the eddies of 4.7 ± 2.3⋅10⁻⁵ cm²/s³. Kinetic energy transition has the same sign and is estimated as 2.8 ± 2.5⋅10⁻⁵ cm²/s³. Potential enstrophy is transferred to the mesoscale at a rate of 5.5 ± 2.7⋅10⁻¹⁸ s⁻³. These figures provide observational evidence of the properties of free geostrophic turbulence which were predicted by theory and observed in numerical experiments. This revised version was published online in July 2006 with corrections to the Cover Date.     

Spatio-temporal variability of small copepods (especially Oithona plumifera) in shallow nearshore waters off the south coast of South Africa

Although small copepods are one of the main dietary sources for many commercially important fish, their role in the pelagic trophic dynamics has traditionally been underestimated due to the methodology commonly used in plankton sampling. Temporal variation in abundance of adults and nauplii of small copepods (particularly Oithona plumifera) in nearshore waters on the south coast of South Africa was investigated fortnightly over 14 months at site (km) and location (100 m) scales. Sampling was within <500 m of the shore, where depth was ca. 10 m, using vertical hauls of an 80-μm mesh plankton net from 1 m above the seabed to the surface. Twenty-seven adult copepod taxa were recorded, but Oithona spp. was consistently the most abundant. Taxon richness was 7–19 on each sampling occasion. There was strong temporal variation (Oithona varied between 0 and 2300 m⁻³), but much of this was short-term variability (e.g. between consecutive sampling sessions), with no seasonality or other long-term discernable patterns. There were periods of consistently low numbers, but very high numbers often followed samples with low abundances. Nor was there spatial structure at the location scale, though numbers differed between sites. Despite considerable variability at the location scale within sites, Kenton consistently showed higher densities than High Rocks. Separate analyses, with Bonferroni adjustment, showed that this difference was significant on eight out of 21 occasions for Oithona, six for other pelagic copepods and three for nauplii. This suggests that hydrodynamics favour aggregation of plankton at Kenton. A high degree of short-term variability, with a tendency for aggregation of small zooplankton at certain sites has implications for both pelagic processes and food-web links between the benthic and pelagic environments.     

Abundance of the introduced seastar, Asterias amurensis, and spatial variability in soft sediment assemblages in SE Tasmania: Clear correlations but complex interpretation

The northern Pacific seastar, Asterias amurensis, was first collected in southeast Tasmania in 1986. Mistaken for the endemic asteroid Uniophora granifera, its true identity was not realised until 1992. It is now a conspicuous predator in soft sediment habitats in this region, and is considered a major threat to native assemblages and commercial species. We examined the structure of soft sediment assemblages at different spatial scales in southeast Tasmania, and correlated spatial variation in community composition with seastar abundances. We found that the structure of soft sediment assemblages is highly variable at a range of spatial scales from metres to tens of kilometres. Clear differences in the composition of assemblages and abundances of major taxa were detected between areas with and without seastars and between areas with low and high seastar densities. However, the nature of these patterns suggests that they are more likely due to differences in sediment characteristics than due to impacts of the seastar. Thus, spatial differences in soft sediment assemblages might have been erroneously attributed to seastars without detailed information on important physical factors such as sediment characteristics. A second survey, using larger sampling units (1 m²) but across a more limited spatial extent, targeted bivalves and heart urchins that were identified as important prey of the seastar in observations of feeding and in experimental studies. Large-scale patterns of abundance and size structure were consistent with seastar effects anticipated from small-scale experimental and feeding studies for some, but not all, species. While the field survey ultimately provided evidence about the presence or absence of seastar impacts at large-scales, the identification of key ecological variables in experimental and feeding studies proved crucial to both the design and interpretation of patterns observed in the large-scale surveys. Overall, this work highlighted the necessity to consider multiple lines of evidence rather than relying on a single ‘inferential’ test, in the absence of pre-impact data.     

Optimum Sample Size to Detect Perturbation Effects: The Importance of Statistical Power Analysis – A Critique

Abstract. The current article describes statistical power analysis as an efficient strategy for the estimation of the optimum sample size. The principle aim is constructively to criticise and enrich the results presented by Mouillot et al. (1999) , who estimate the optimum sample size for evaluating possible perturbations. The authors did not make any reference to statistical power analysis, even though their objective clearly went beyond a simple stock evaluation to assess management strategies in a particular marine ecosystem. Surprisingly, they proposed (a priori) an ANOVA design to test a hypothesis considering both space and temporal scales. However, the authors did not cover important topics related with power analysis and the precautionary principle, both used into environment impact assessment programmes for marine ecosystems. Based on their results and on statistical power analysis, it is demonstrated that the variability (dispersion statistics), a key factor they used to estimate the sample size, is less relevant than the magnitude of perturbation (effect size). Therefore, a greater effort must be devoted to estimate the effect size of a particular phenomenon rather than a desired variability.