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.

Replacing rubber plantations by rain forest in Southwest China - Who would gain and how much?

The cultivation of rubber trees in Xishuangbanna Prefecture in China’s Yunnan Province has triggered an unprecedented economic development but it is also associated with severe environmental problems. Rubber plantations are encroaching the indigenous rainforests at a large scale and a high speed in Xishuangbanna. Many rare plant and animal species are endangered by this development, the natural water management is disturbed and even the microclimate in this region has changed over the past years. The present study aims at an assessment of the environmental benefits accruing from a reforestation project partly reversing the deforestation that has taken place over the past years. To this end a Contingent Valuation survey has been conducted in Xishuangbanna to elicit local residents’ willingness to pay for this reforestation program that converts existing rubber plantations back into forest. It is shown that local people's awareness of the environmental problems caused by increasing rubber plantation is quite high and that in spite of the economic advantages of rubber plantation there is a positive willingness among the local population to contribute financially to a reduction of existing rubber plantations for the sake of a partial restoration of the local rainforest. These results could be used for the practical implementation of a PES (Payments for Eco-System Services) system for reforestation in Xishuangbanna.