Using non-systematically collected data to evaluate the conservation status of elusive species: a case study on Australia’s Oenpelli python

Abstract

Abstract ContextSpecies conservation assessments require information on distribution, habitat requirements and population demography and trends. Uncertain conservation assessments limit effective planning and may lead to poor management decisions. Top-order predators generally receive considerable attention from ecologists and conservation biologists, with the notable exception of large pythons and boas. They are typically elusive and have low population densities, posing challenges for ecological research and monitoring. Ecological and demographic data are lacking for most large snake species and are generally inadequate to properly assess conservation status or to evaluate their broader ecological roles. The Oenpelli python (Simalia oenpelliensis) is Australia’s second-longest snake species, but remains one of the least-known of the world’s pythons. AimsWe sought to use non-systematically collected data from multiple sources to evaluate Oenpelli python population trends and habitat associations, and to assess its conservation status. MethodsWe identified a priori biases in data and evaluated their influences on environmental models and temporal variability in reporting patterns. We then used these findings to assess the conservation status of this species, identify knowledge gaps, and refine future survey and monitoring methods. Key resultsOenpelli python records were strongly associated with monsoon rainforest, sandstone outcrops and perennial streams, irrespective of detection biases. Total area of occupancy was estimated to be 19252km2. Detection patterns were strongly seasonal and associated with periods of low rainfall and low moonlight, informing better-targeted survey and monitoring methods with improved sensitivity. ConclusionsOenpelli pythons have a highly fragmented distribution owing to their strong association with monsoon rainforest. This habitat is likely to provide more food resources and refuge from high temperatures than are the surrounding savanna woodlands. Detection probability should improve by surveying Oenpelli pythons in September on moonless nights and following periods of high rainfall. Taking a precautionary approach, the Oenpelli python qualifies as Vulnerable under IUCN criteria, supporting its current Red List and Northern Territory Government status. ImplicationsNon-systematically collected data on poorly known species can be used to improve conservation assessments where there may otherwise be high uncertainty. The present study also highlighted the paucity of ecological knowledge of large iconic snake species globally.