Particulate and dissolved aluminum and titanium in the upper water column of the Atlantic Ocean

This study investigates the oceanic behavior of the lithogenic trace elements Al and Ti in the upper 200 m of the Atlantic Ocean. The distribution of both metals in the dissolved and particulate phases was assessed along an E-W transect in the eastern tropical North Atlantic (December 2009) and along a meridional Atlantic transect (April-May 2010). The surface water concentrations of particulate and dissolved Al and Ti reflected the previously observed pattern of atmospheric inputs into the Atlantic Ocean. Subsurface minima at stations with pronounced fluorescence maxima were observed, suggesting a link between biological productivity and the removal of both dissolved and particulate Al and Ti. This may include uptake mechanisms, adsorption and aggregation processes on biogenic particle surfaces and the formation of large, fast sinking biogenic particles, e.g., fecal pellets. Residence times in the upper water column (100 m) of the tropical and subtropical North Atlantic were estimated to range in the order of days to weeks in the particulate phases (Al: 3-22 days, Ti: 4-37 days) and were 0.9-3.8 years for Al and 10-31 years for Ti in the dissolved phases. Longer residence times in both phases in the South Atlantic are consistent with lower biological productivity and decreased removal rates. In the upper water column, Al was predominantly present in the dissolved form, whereas Ti mostly occurred in the particulate form. Largest deviations in the partition coefficients between the particulate and dissolved phases were found in the surface waters, together with excess dissolved Al over Ti compared to the crustal source. This likely reflects elevated dissolution of Al compared to Ti from atmospheric mineral particles.

Scale-dependent response diversity of seabirds to prey in the North Sea

Functional response diversity is defined as the diversity of responses to environmental change among species that contribute to the same ecosystem function. Because different ecological processes dominate on different spatial and temporal scales, response diversity is likely to be scale dependent. Using three extensive data sets on seabirds, pelagic fish, and zooplankton, we investigate the strength and diversity in the response of seabirds to prey in the North Sea over three scales of ecological organization. Two-stage analyses were used to partition the variance in the abundance of predators and prey among the different scales of investigation: variation from year to year, variation among habitats, and variation on the local patch scale. On the year-to-year scale, we found a strong and synchronous response of seabirds to the abundance of prey, resulting in low response diversity. Conversely, as different seabird species were found in habitats dominated by different prey species, we found a high diversity in the response of seabirds to prey on the habitat scale. Finally, on the local patch scale, seabirds were organized in multispecies patches. These patches were weakly associated with patches of prey, resulting in a weak response strength and a low response diversity. We suggest that ecological similarities among seabird species resulted in low response diversity on the year-to-year scale. On the habitat scale, we suggest that high response diversity was due to interspecific competition and niche segregation among seabird species. On the local patch scale, we suggest that facilitation with respect to the detection and accessibility of prey patches resulted in overlapping distribution of seabirds but weak associations with prey. The observed scale dependencies in response strength and diversity have implications for how the seabird community will respond to different environmental disturbances.

A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.