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Stochastic population models hindcast population trajectory and breeding history of an endangered parrot

Gautschi, Daniel, Stojanovic, Dejan, Macgregor, Nicholas A., Ortiz-Catedral, Luis, Wilson, Melinda, Olsen, Penny, Crates, Ross, Heinsohn, Robert (2023) Stochastic population models hindcast population trajectory and breeding history of an endangered parrot. Emu - Austral Ornithology, 123 (4). pp. 335-344. ISSN 1448-5540. (doi:10.1080/01584197.2023.2267606) (KAR id:104185)


Understanding the population dynamics of endangered species is crucial to their conservation. Stochastic population models can be used to explore factors involved in population change, contributing to the understanding of a species’ population dynamics. Norfolk Island Green Parrots Cyanoramphus cookii have undergone significant population fluctuations in the last 50 years. Since 2013, most nestlings hatched in managed, predator-proofed nest sites have been individually marked. These nests have been considered the primary source of population growth. Yet, in 2021, most adult birds were unmarked, raising the question of whether unmarked parrots have been entering the population through undetected breeding in natural nests, and to what extent. We modelled Green Parrot population growth between 2013 and 2021 using stochastic population models in VORTEX to explore the potential dynamics involved in the observed population growth. Basic models involving breeding only in managed nests produced population estimates between 158 and 266, whereas more complex models that included breeding in unmanaged nests, and accounted for the large proportion of unmarked birds, produced population estimates between 360 and 1,041. We conclude that natural nests may have played a significant role in the population growth since 2013. If this is the case, broad-scale predator control may be largely responsible. Furthermore, our study shows how population models may be used to infer underlying demographic processes and inform conservation strategies, even in instances of data scarcity. Our method can be applied to other threatened species, and may prove particularly useful for small populations whose population dynamics remain unclear.

Item Type: Article
DOI/Identification number: 10.1080/01584197.2023.2267606
Uncontrolled keywords: Nature and Landscape Conservation, Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics
Subjects: Q Science > QH Natural history > QH75 Conservation (Biology)
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 12 Mar 2024 15:19 UTC
Last Modified: 13 Mar 2024 13:03 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Macgregor, Nicholas A..

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