Conservation value of an exotic species: the case of coconuts on the Kayapo indigenous lands, south-eastern Amazonia

In a meeting between FUNAI (the Brazilian Indian National Foundation) and the Kayapo in the Kayapo village of Aukre, in October 2005, the Kayapo Indians requested support to increase the culture of coconuts (Cocos nucifera) in their lands. The introduction of exotic species is a cause of biological diversity loss throughout the world. However, this is by no means applicable to all kinds of exotic species. We argue that the culture of coconuts may actually be a useful tool for the conservation of this country’s indigenous lands, despite criticism to the contrary. It may also be useful as source for raw material for the indigenous people who are presently experiencing a population boom. For the Kayapo of south-eastern Amazonia, such a demographic explosion, coupled with their increasing dependence on money to purchase industrialized goods, tend to substantially increase the pressure on their lands, which still contain a substantial amount of well-preserved seasonally-dry Amazonian forests. We investigated the actual economic relevance of coconuts for the Kayapo by measuring human and coconut populations and found that this exotic palm is not important for the subsistence of these Indians, due to coconut scarcity, and that such importance is not forthcoming. In the Amazon, coconuts may be particularly useful for the Indians’ nutrition due to the high energetic value of the solid endosperm of the mature fruit. Therefore, given the importance of indigenous lands for the conservation of the Amazonian forests, the encouragement of subsistence coconut cultures in indigenous lands is defensible as a measure for the conservation of biodiversity.     

A spatial scan statistic for zero-inflated Poisson process

The scan statistic is widely used in spatial cluster detection applications of inhomogeneous Poisson processes. However, real data may present substantial departure from the underlying Poisson process. One of the possible departures has to do with zero excess. Some studies point out that when applied to data with excess zeros, the spatial scan statistic may produce biased inferences. In this work, we develop a closed-form scan statistic for cluster detection of spatial zero-inflated count data. We apply our methodology to simulated and real data. Our simulations revealed that the Scan-Poisson statistic steadily deteriorates as the number of zeros increases, producing biased inferences. On the other hand, our proposed Scan-ZIP and Scan-ZIP+EM statistics are, most of the time, either superior or comparable to the Scan-Poisson statistic.