First record of greater white-toothed shrew Crocidura russula in Ireland

1. Skeletal remains of greater white-toothed shrew Crocidura russula were recovered from barn owl Tyto alba and kestrel Falco tinnunculus pellets collected at 15 locations in Counties Tipperary and Limerick in Ireland in September 2007 and March 2008. Seven greater white-toothed shrews were trapped at four locations in Tipperary in March 2008. This is the first Irish record of C. russula and compelling evidence that the species is established in Ireland.

Arsenic residues in predatory birds from an area of Britain with naturally and anthropogenically elevated arsenic levels

Birds of prey forage over large areas and so might be expected to accumulate contaminants which are elevated but heterogeneously distributed in the general environment. The aim of this study was to test the hypothesis that arsenic levels in raptors from a region with elevated environmental arsenic concentrations were higher than those in birds from an uncontaminated part of Britain. Arsenic concentrations in the liver, kidney and muscle of kestrels, Falco tinnunculus, sparrowhawks, Accipiter nisus, and barn owls, Tyto alba, from south-west (SW) England, an area with naturally and anthropogenically (through mining) elevated environmental arsenic concentrations, were compared with those in birds from SW Scotland, where no such geochemical anomaly exists. Arsenic residues in kestrels from SW England were approximately three times greater than those in birds from SW Scotland for the three tissue types analysed. This was not the case for the other species in which arsenic residues were similar in birds from both regions. It is suggested that differences between species in both diet and arsenic metabolism could explain why kestrels have elevated arsenic tissue burdens in response to general environmental contamination but sparrowhawks and barn owls do not.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.