Type: Journal Article
Reference: Stojanovic, D., Hogg, C. J., Alves, F., Baker, G. B., Biggs, J. R., Bussolini, L., Carey, M. J., Crates, R., Magrath, M. J. L., Pritchard, R., Troy, S., Young, C. M., & Heinsohn, R. (2023). Conservation management in the context of unidentified and unmitigated threatening processes. Biodiversity and Conservation, 1-17. doi: 10.1007/s10531-023-02568-0
Abstract
The decision to intervene in endangered species management is often complicated. Migratory species exemplify this difficulty because they experience diverse threats at different times and places that can act cumulatively and synergistically on their populations. We use population viability analysis (PVA) to compare potential conservation interventions on the critically endangered, migratory Orange-bellied Parrot Neophema chrysogaster. This species suffers high juvenile mortality, but it is not clear why this is so. Given uncertainty about the best recovery strategy, we compare PVA scenarios that simulate various ways of utilizing captive-bred parrots to support the wild population in the context of unresolved threatening processes. Increasing the number of juveniles entering the population each year had the greatest benefit for population growth rate and size. Directly lowering juvenile mortality rates is difficult given uncertainty about the drivers of mortality in the wild. In lieu of this, releasing 100 juveniles from captivity to the wild population each autumn (either as a stand-alone action, or in combination with other interventions) was the most feasible and straightforward intervention of the options we tested. However, our PVAs also show that unless substantial and sustainable reductions can be made to juvenile mortality rates, Orange-bellied Parrots will remain dependent on intensive conservation management. This study highlights the utility of PVAs for answering practical questions about how to implement species conservation. PVAs provide a way to incorporate the best available information in a replicable modelling framework, and to identify impacts of parameter uncertainty on demographic trends.