A new species of gekkonid lizard is described from Phnom Khpoh, an isolated karstic hill within an extensive karstic archipelago in Battambang Province, western Cambodia. Phylogenetic analysis using a 1041 base pair fragment of the mitochondrial gene ND2 recovered Hemiphyllodactylus khpoh sp. nov. as the sister species of H. pardalis, found 335 km to the west in southern Thailand. Analyses of meristic, morphometric, and categorical characters of morphology and color pattern differentiated H. khpoh sp. nov. from both the morphologically distinct H. pardalis and the very similar Hemiphyllodactylus sp. from Phnom Kulen, approximately 130 km to the northeast in Siem Reap Province. The statistical morphological analyses and comparisons also showed that H. khpoh sp. nov. is well-differentiated from the recently described H. bokor and H. samkos from the nearby Cardamom Mountains as well from species in clade 6-a recently designated lineage from China, Laos, and Vietnam to which H. khpoh sp. nov. + H. pardalis compose the sister lineage. The discovery of H. khpoh sp. nov. highlights the rich but understudied biodiversity of karstic landscapes, emphasizing the need for continued research in the extensive unexplored karstic archipelago of western Cambodia. This region is poised to reveal unparalleled gekkonid diversity, comparable to that observed in the similarly sized karstic archipelago of the Salween Basin in southern Myanmar. Although karstic landscapes are proving to be some of the most biodiverse habitats on the planet, less than 1% of them are afforded any formal protection.
Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (Macaca fascicularis). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.
Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as "defaunation." This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.