POTENTIAL SUITABLE HABITAT DISTRIBUTION FOR TWO ENDEMIC AND HIGHLY THREATENED SPECIES OF Leptophryne (AMPHIBIA; BUFONIDAE) IN JAVA

Abstract

Bufonid toad genus Leptophryne comprises three species; L. borbonica, L. cruentata, and L. javanica. These three species occurred in Java Island. Two out of three species, L. cruentata and L. javanica, are endemic and classified as critically endangered (CR) and endangered (EN), respectively. Leptophryne javanica recently described in 2018, and it is separated from L. cruentata by having distinct morphology, molecular and call characteristics. Both L. cruentata and L. javanica share the same habitat type (i.e. mountain forest, waterfall, rocky stream). Until early 2000, these two endemic Leptophryne were considered restricted to Mt. Gede. From 2000 to 2018, these species were also recorded in Mt. Halimun, Mt. Ciremai, and Mt. Slamet. These new localities indicate that there is potential distribution outside previously known locations. This study aims to predict the potential suitable habitat of endemic Leptophryne (L. cruentata and L. javanica) and identify the most important environmental variables on its distribution. MaxEnt modelling was applied to generate a potential suitable habitat distribution map. Twelve presence data were used for the model consist of 10 coordinates in Mt. Gede Pangrango, one in Mt. Ciremai, and one in Mt. Slamet. To build the model, 21 environmental variables were utilized: land cover, altitudinal and 19 variables of precipitation and temperature along with the species presence data. The result shows there is suitable habitat outside the known locations, consist of 14 patches in western Java, five in central Java and four in eastern Java. The most potential is in the mountainous area at southern Bandung. The lowest temperature fluctuation, highest elevation, lowest mean temperature during the warmest season, and better land cover provides the best habitat suitability. Further study is required to verify these potential distributions based on the modelling result.