Identifying Important Hornbill Landscapes in Sarawak, Malaysia

With land use change rapidly increasing in Asia, conservation prioritisation has emerged as an important tool in identifying critical landscapes for biodiversity to safeguard them from human pressures. In Peninsular Malaysia, the Malaysian Nature Society (MNS/BirdLife in Malaysia) developed a set of Criteria to identify Important Hornbill Landscapes (IHLs) – hornbill hotspots which are conservation priority sites in Malaysia and serve to inform land use planning and conservation action. Application of the Criteria has so far been restricted to Peninsular Malaysia, thus in this study, we adapt it to Sarawak, a Malaysian state in Borneo that supports 80 of the hornbill species diversity in the country. We expand on this conservation prioritisation methodology using Maximum Entropy Species Distribution Modelling (MaxEnt), to validate the Criteria's applicability and to identify potential IHLs in Sarawak. Our data sources included literature reviews, citizen science databases and interviews. Expectedly, survey effort was spatially biased. We identified eight IHLs, mostly concentrated in eastern Sarawak, across national parks, wildlife sanctuaries and forest management units. Existing published literature on the distribution of hornbill habitats in Sarawak corroborated with our MaxEnt outputs which aligned with the results of the IHL Criteria-based assessment, validating the latter and supporting its use in Sarawak. We additionally identified six potential IHLs based on MaxEnt outputs which confirmed the value of pairing MaxEnt with the Criteria-based assessment, for such a prioritisation exercise. To our knowledge, this study not only demonstrates the significance of combining MaxEnt and the Criteria for IHL identification, but it also represents the first application of the IHL Criteria outside of Peninsular Malaysia. Our findings can, therefore, serve as a case study for future applications of IHL Criteria in Borneo and potentially for other parts of Asia.

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