Impending extinction of the world’s primates due to human activities; immediate global attention is needed to reverse the trend.

Wildlife trade is the very heart of biodiversity conservation and sustainable development providing an income for some of the least economically affluent people and it generates considerable revenue nationally. In Asia the unsustainable trade in wildlife has been identified as one of the main conservation challenges. Internationally, wildlife trade is regulated through the Convention on International Trade in Endangered Species of wild fauna and flora (CITES) to which all Southeast Asian nations are signatory. I obtained data on international trade in CITES-listed animals in the period 1998-2007. In all [35 million animals (0.3 million butterflies; 16.0 million seahorses; 0.1 million other fish; 17.4 million reptiles; 0.4 million mammals; 1.0 million birds) were exported in this period, 30 million (*300 species) of them being wild-caught. In addition 18 million pieces and 2 million kg of live corals were exported. Malaysia, Vietnam, Indonesia and China are the major exporters of wild-caught animals and the European Union and Japan are the most significant importers. Over this period exports in birds significantly decreased, trade in the other taxa either increased or remained stable. For all taxa but butterflies the vast majority of individuals represent wild-caught individuals. Records of illegal or undeclared international trade are scant but can be significantly larger than levels of official exports. It is concluded that there is an urgent need for better assessments of what levels of exploitation are sustainable (including exploring appropriate proxies for Non Detriment Findings), for initiatives to make regulatory mechanisms more effective (including the introduction of minimum mandatory standards and monitoring selected wildlife trade hubs), and for better licensing and registration. Funding for at least some of these initiatives can be obtained by imposing small levies on exports of CITES-listed wildlife.

Of the 10,272 currently recognized reptile species, the trade of fewer than 8% are regulated by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) and the European Wildlife Trade Regulations (EWTR). However, the International Union for Conservation of Nature (IUCN) Red List has assessed 45% of the world's reptile species and determined that at least 1390 species are threatened by “biological resource use”. Of these, 355 species are intentionally targeted by collectors, including 194 non-CITES-listed species. Herein we review the global reptile pet trade, its impacts, and its contribution to the over-harvesting of species and populations, in light of current international law. Findings are based on an examination of relevant professional observations, online sources, and literature (e.g., applicable policies, taxonomy [reptile database], trade statistics [EUROSTAT], and conservation status [IUCN Red List]). Case studies are presented from the following countries and regions: Australia, Central America, China, Galapagos Islands (Ecuador), Germany, Europe, India, Indonesia (Kalimantan), Islamic Republic of Iran, Japan, Madagascar, Mexico, New Zealand, the Philippines, South Africa, Sri Lanka, Vietnam, Western Africa, and Western Asia. The European Union (EU) plays a major role in reptile trade. Between 2004 and 2014 (the period under study), the EU member states officially reported the import of 20,788,747 live reptiles. This review suggests that illegal trade activities involve species regulated under CITES, as well as species that are not CITES-regulated but nationally protected in their country of origin and often openly offered for sale in the EU. Further, these case studies demonstrate that regulations and enforcement in several countries are inadequate to prevent the overexploitation of species and to halt illegal trade activities. (Résumé d'auteur

Aim  Data on geographical ranges are essential when defining the conservation status of a species, and in evaluating levels of human disturbance. Where locality data are deficient, presence‐only ecological niche modelling (ENM) can provide insights into a species’ potential distribution, and can aid in conservation planning. Presence‐only ENM is especially important for rare, cryptic and nocturnal species, where absence is difficult to define. Here we applied ENM to carry out an anthropogenic risk assessment and set conservation priorities for three threatened species of Asian slow loris (Primates: Nycticebus).Location  Borneo, Java and Sumatra, Southeast Asia.Methods  Distribution models were built using maximum entropy (MaxEnt) ENM. We input 20 environmental variables comprising temperature, precipitation and altitude, along with species locality data. We clipped predicted distributions to forest cover and altitudinal data to generate remnant distributions. These were then applied to protected area (PA) and human land‐use data, using specific criteria to define low‐, medium‐ or high‐risk areas. These data were analysed to pinpoint priority study sites, suitable reintroduction zones and protected area extensions.Results  A jackknife validation method indicated highly significant models for all three species with small sample sizes (n = 10 to 23 occurrences). The distribution models represented high habitat suitability within each species’ geographical range. High‐risk areas were most prevalent for the Javan slow loris (Nycticebus javanicus) on Java, with the highest proportion of low‐risk areas for the Bornean slow loris (N. menagensis) on Borneo. Eighteen PA extensions and 23 priority survey sites were identified across the study region.Main conclusions  Discriminating areas of high habitat suitability lays the foundations for planning field studies and conservation initiatives. This study highlights potential reintroduction zones that will minimize anthropogenic threats to animals that are released. These data reiterate the conclusion of previous research, showing MaxEnt is a viable technique for modelling species distributions with small sample sizes.