Habitat and ecological niche characteristics of the elusive Hairy‐eared Dwarf Lemur (Allocebus trichotis) with updated occurrence and geographic range data

Abstract

Ecological niche modeling (ENM) is particularly useful in the study of cryptic and elusive species that are only rarely seen, difficult to study in the wild, and simultaneously threatened by a multitude of anthropogenic factors. We collected presence records one such example, the understudied Hairy-eared Dwarf Lemur (Allocebus trichotis), from the literature and supplemented these with observations from surveys in previously unstudied areas to model its fundamental and realized niche throughout Madagascar.We further evaluated habitat characteristics at each sighting location to judge its conservation status and its adaptability toward habitat degradation. We found 31 presence localities in the literature and directly observed A. trichotis a further 23 times.According to the ENMs, precipitation of the driest quarter and maximum temperature of the warmest month mostly influenced its distribution, restricting it to the higher altitudes of the northeastern humid forests of Madagascar. Its fundamental niche, extent of occurrence, and area of occupancy were estimated as 65,819, 53,054, and 16,967 km² respectively. The latter, however, declined by 29.2% since 1990. On a habitat level, it was most often observed in primary forest habitats of different degradation stages (85.7%, n = 21). The fundamental niche of A. trichotis is most likely restricted by climatic factors. Although it can be found in moderately degraded forests, it is known to depend on the availability of tree holes and therefore old-growth forest structures. Ongoing deforestation and habitat fragmentation are likely to be the major threats to the survival of this species. Our ENMs provide evidence on where to intensify survey efforts on the elusive Hairy-eared Dwarf Lemurs of Madagascar.

Human activity and climate change accelerate the extinction risk to non‐human primates in China

“…Raster resolution varied between the bioclimatic and human activity data layers (0.25–1.00 km 2 ), so we resampled all layers to the resolution of the least fine raster (1.00 km 2 ) using the nearest‐neighbor method in the “raster” package. These variables considered to have a major effect on primate ecology and range distribution, including bio 1, bio 3, bio 6, bio 12, bio 14, bio 15 (Li, Chen, et al., 2022), bio 1, bio 2, bio 4, bio 5, bio7, bio16, bio17, bio 18 (Li et al., 2023), bio 2, bio 4, bio 6, bio7, bio 16, bio 17 (Condro et al., 2021), bio 2, bio3, bio 5, bio 12, bio 17 (Schüßler et al., 2023), bio 4, HPD (Zhao et al., 2022), GDP (Estrada et al., 2020), and NDVI (Willems et al., 2009) also were examined (Table S2).…”