17 resultados para BROWN CAPUCHINS


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Habitually, capuchin monkeys access encased hard foods by using their canines and premolars and/or by pounding the food on hard surfaces. Instead, the wild bearded capuchins (Cebus libidinosus) of Boa Vista (Brazil) routinely crack palm fruits with tools. We measured size, weight, structure, and peak-force-at-failure of the four palm fruit species most frequently processed with tools by wild capuchin monkeys living in Boa Vista. Moreover, for each nut species we identify whether peak-force-at-failure was consistently associated with greater weight/volume, endocarp, thickness, and structural complexity. The goals of this study were (a) to investigate whether these palm fruits are difficult, or impossible, to access other than with tools and (b) to collect data on the physical properties of palm fruits that are comparable to those available for the nuts cracked open with tools by wild chimpanzees. Results showed that the four nut species differ in terms of peak-force-at-failure and that peak-force-at-failure is positively associated with greater weight (and consequently volume) and apparently with structural complexity (i.e. more kernels and thus more partitions); finally for three out of four nut species shell thickness is also positively associated with greater volume. The finding that the nuts exploited by capuchins with tools have very high resistance values support the idea that tool use is indeed mandatory to crack them open. Finally, the peak-force-at-failure of the piassava nuts is similar to that reported for the very tough panda nuts cracked open by wild chimpanzees; this highlights the ecological importance of tool use for exploiting high resistance foods in this capuchin species.

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The usual tests to compare variances and means (e. g. Bartlett`s test and F-test) assume that the sample comes from a normal distribution. In addition, the test for equality of means requires the assumption of homogeneity of variances. In some situation those assumptions are not satisfied, hence we may face problems like excessive size and low power. In this paper, we describe two tests, namely the Levene`s test for equality of variances, which is robust under nonnormality; and the Brown and Forsythe`s test for equality of means. We also present some modifications of the Levene`s test and Brown and Forsythe`s test, proposed by different authors. We analyzed and applied one modified form of Brown and Forsythe`s test to a real data set. This test is a robust alternative under nonnormality, heteroscedasticity and also when the data set has influential observations. The equality of variance can be well tested by Levene`s test with centering at the sample median.