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.

Colloidal stability of nanoparticles derived from simulated cloud-processed mineral dusts

Laboratory simulation of cloud processing of three model dust types with distinct Fe-content (Moroccan dust, Libyan dust and Etna ash) and reference goethite and ferrihydrite were conducted in order to gain a better understanding of natural nanomaterial inputs and their environmental fate and bioavailability. The resulting nanoparticles (NPs) were characterised for Fe dissolution kinetics, aggregation/size distribution, micromorphology and colloidal stability of particle suspensions using a multi-method approach. We demonstrated that the: (i) acid-leachable Fe concentration was highest in volcanic ash (1 m Mg(-1) dust) and was followed by Libyan and Moroccan dust with an order of magnitude lower levels; (ii) acid leached Fe concentration in the<20 nm fraction was similar in samples processed in the dark with those under artificial sunlight, but average hydrodynamic diameter of NPs after cloud-processing (pH~6) was larger in the former; iii) NPs formed at pH~6 were smaller and less poly-disperse than those at low pH, whilst unaltered zeta potentials indicated colloidal instability; iv) relative Fe percentage in the finer particles derived from cloud processing does not reflect Fe content of unprocessed dusts (e.g. volcanic ash>Libyan dust). The common occurrence of Fe-rich "natural nanoparticles" in atmospheric dust derived materials may indicate their more ubiquitous presence in the marine environment than previously thought.