Notes on the ecology of gorals in two areas of Southern Asia

Les auteurs comparent certains aspects de l'écologie des gorals dans le nord-est de l'Inde (Nemorhaedus goral bedfordi) et le nord-ouest de la Thaïlande (Nemorhaedus caudatus evansi). Dans les deux cas, ces Rupicaprini habitent des pentes raides (> 30 %) à très raides (> 60 %). En Inde, les milieux ouverts sont évités quand la température dépasse 20 °C. Les mâles adultes sont surtout solitaires, alors que les femelles tendent a former de petits groupes pouvant atteindre 11 individus. La taille moyenne des groupes est indépendante de la densité de la population local

Conservation introduction of the threatened Apennine chamois Rupicapra pyrenaica ornata : post-release dispersal differs between wild-caught and captive founders

AbstractSixteen Apennine chamois Rupicapra pyrenaica ornata (10 females, 6 males) were released into a protected area, the Sibillini Mountains National Park, Central Apennines, Italy, and monitored using global positioning system radio tags during 2008–2010. Founders caught in the wild (n = 8) and those reared in large enclosures (n = 8) differed in movement frequency (inter-fix distance per hour) and maximum distance covered (from the release site) in the first 5 months after release: both were significantly greater in wild individuals, males moved significantly more than females, wild individuals shifted their home ranges significantly more often than captive ones, and no differences were observed between the sexes or age classes. A mixed strategy of selection of wild and captive founders has proven successful in preventing large movements in the initial stages of release yet still providing sufficient opportunity to avoid inbreeding depression

Food habits and trophic niche variation of the Red fox Vulpes vulpes (L., 1758) in a Mediterranean coastal area

La région alimentaire du renard roux a été étudié par analyse des fèces dans la zone côtière italienne de la Marenn

THE MISUSE OF STATISTICS AMONG BIOLOGISTS

This paper deals with some common misunderstandings about the statistical evaluation of data by biologists. Neglecting assumptions, twisting models, misusing GLM and GLMs, non-representativeness of samples and the use of exoteric-looking statistical manipulation of data to demonstrate obvious results are relevant examples. Often, the “best” methods are the simplest ones, as long as they are appropriate. One should never forget that, to a biologist, the statistical manipulation of data should just be a way to evaluate the significance of his conclusions: it ought to never become his main goal, e.g. because statisticians can do it better