This study presents a list of land snails and slugs found on limestone hills in the District of Bau, the state of Sarawak in Malaysian Borneo. Systematic and random sampling for land snails was conducted at eight limestone outcrops, namely, Gunung Stulang, Padang Pan, Gunung Kapor, Gunung Lobang Angin, Gunung Doya, Gunung Batu, Bukit Sekunyit and Gunung Sebayat. A total of 122 land snail species was documented with photographs of each species. Of the 122 species collected, 13 are new to science, namely,Acmella bauensissp. nov.,Japonia bauensissp. nov.,Plectostoma margaretchanaesp. nov.,Microcystina arabiisp. nov.,Microcystina atonisp. nov.,Microcystina pariparisp. nov.,Microcystina liratasp. nov.,Microcystina oswaldbrakenisp. nov.,Microcystina kilatsp. nov.,Philalanka jambusanensissp. nov.,Everettia microrhytidasp. nov.,Everettia minutasp. nov., andParalaoma sarawakensissp. nov.

A study to describe the diversity of wild felids was carried out in Jerangau Forest Reserve, Ulu Terengganu, Malaysia, using camera traps, over a period of 21 months. A total of 24 camera traps were used, with a total of 5,972 trap days. Six species of wild cats in five genera were recorded: tiger Panthera tigris, leopard Panthera pardus, clouded leopard Neofelis nebulosa, leopard cat Prionailurus bengalensis, golden cat Catopuma temminckii and marbled cat Pardofelis marmorata. This represents all but two of the felid species known to occur in Peninsular Malaysia. The use of camera traps provided detailed information on the occurrence and activity patterns of these relatively secretive mammals. The most frequently photographed species was tiger (38.5% of records) followed by leopard (26.3%) and leopard cat (21.9%). The presence of charismatic flagship species such as tiger in this unprotected lowland dipterocarp secondary forest will be of help to local conservation organizations and the Wildlife Department in any proposals for the protection of these areas.

Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60 % tree cover) whereas the Dirus Complex was predicted to occur in areas with 10–100 % tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.