The value of local community knowledge in species distribution modelling for a threatened Neotropical parrot

摘要: Species distribution models are widely used in conservation planning, but obtaining the necessary occurrence data can be challenging, particularly for rare species. In these cases, citizen science may provide insight into species distributions. To understand of newly described and Critically Endangered Amazona lilacina, we collated observations reliable eBird records from 2010–2020. We combined with environmental predictors either randomly generated background points or absence checklists, to build using MaxEnt. also conducted interviews people local species’ range gather community-sourced data. grouped according perceived expertise observer, based on ability identify A. lilacina its distinguishing features, knowledge ecology, overall awareness parrot biodiversity, observation type. evaluated all AUC Tjur R2. Field built performed better than those (AUC = 0.80 ± 0.02, R2 = 0.46 ± 0.01 compared AUC = 0.78 ± 0.03, R2 = 0.43 ± 0.21). The best performing community model presence who were able recognise a photograph correctly describe physical behavioural characteristics (AUC = 0.84 ± 0.05, R2 = 0.51± 0.01). There was up 92% overlap between field models, which when combined, predicted 17,772 km2 suitable habitat. Use offers cost-efficient method obtain modelling; offer recommendations how assess performance present final map potential lilacina.