South-east Asian apple snails, Pila spp., have been declining since the introduction of globally invasive, confamilial South American Pomacea spp., yet Pila ecology remains poorly studied, with most occurrence records unconfirmed. Pila scutata, a previously widespread species, presumed native to the Malay peninsula and assessed as Least Concern in the IUCN Red List, was formerly harvested for food, and may have experienced anthropogenic translocations. We surveyed the Malay peninsula (specifically Peninsular Malaysia and Singapore) to investigate the current distribution and genetic diversity of P. scutata. Six populations were found in Singapore, but only one in Peninsular Malaysia. Mitochondrial COI and 16S sequencing revealed that the Malaysian population shared a single haplotype of both genes with the Singapore populations (500 km distant). This low genetic diversity could stem from a recent anthropogenic introduction, which brings into question the true native range of P. scutata and, coupled with poorly resolved taxonomy of the genus, necessitates a reassessment of its IUCN Red List status. Introduced populations pose a dilemma, and the lack of genetic diversity is of concern in light of Pila decline throughout South-east Asia. Our results highlight that conservation management of P. scutata and its congeners must therefore be better informed by greater taxonomic resolution and more comprehensive investigations of their ecology, both in native and introduced ranges.

The shell of the Manus green tree snail Papustyla pulcherrima is renowned for its beauty and is subject to international protection under CITES, having been harvested intensively in the past. To determine its threat status, and whether further conservation action is justified, an inexpensive Wisdom of Crowds approach was used to estimate the change in relative density of the snail between 1998 and 2013. Local men and women were approached around the main market on Manus Island, Papua New Guinea, and asked to map the relative abundance of the snail on an ordinal scale, based on their personal observations in 2013 and 1998 (a year of cultural significance). The spatial abundance data from 400 surveys were analysed using an information-theoretic approach. A suite of cumulative link models incorporating geographical factors was used to determine the magnitude of the change and to investigate possible biological influences underpinning the reported pattern. High abundance of the snail was associated with intact forested areas, high elevation and low population density. A slow decline was evident, with the median percentage of map cells where the snail was categorized as plentiful decreasing by c. 20% between the 2 years. On this basis a categorization of Near Threatened was advocated for the species. Although it is arguable that Wisdom of Crowds methods cannot be substituted for in situ quantification, the approach appears to have utility as a preliminary assessment for further conservation expenditure, and as a tool for determining threat status.

The International Union for Conservation of Nature (IUCN) Red List provides a globally-recognized evaluation of the conservation status of species, with the aim of catalysing appropriate conservation action. However, in some parts of the world, species data may be lacking or insufficient to predict risk status. If species with shared ecological or life history characteristics also tend to share their risk of extinction, then ecological or life history characteristics may be used to predict which species may be at risk, although perhaps not yet classified as such by the IUCN. Statistical models may be a means to determine whether there are non-threatened or unclassified species that share the characteristics of threatened species, however there are no data on which model might be most appropriate or whether multiple models should be used. In this paper, three types of statistical models, namely regression trees, logistic regression and discriminant function analysis are compared using data on the ecological characteristics of Finnish lepidopterans (butterflies and moths). Overall, logistic regression performed slightly better than discriminant function analysis in predicting species status, and both outperformed regression trees. Uncertainty in species classification suggests that multiple analyses should be performed and particular attention devoted to those species for which the methods disagree. Such standard statistical methods may be a valuable additional tool in assessing the likely threat status of a species where there is a paucity of abundance data.