A gap analysis of reconnaissance surveys assessing the impact of the 2019–20 wildfires on vertebrates in Australia

Southwell, Darren; Wilkinson, David P.; Hao, Tianxiao; Valavi, Roozbeh; Smart, Adam; Wintle, Brendan A.

doi:10.1016/j.biocon.2022.109573

Cited by 2 publications

(3 citation statements)

References 62 publications

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“…It was fortunate, here, that Gooday's (2016) study provided relatively proximate ‘before’ data to allow inferences to be drawn as to the effects of the earthquake on Kaikōura's NZFSs. As substantial natural disasters are uncommon and unpredictable, missing baseline data often impedes such analyses (Southwell et al, 2022). McIntosh et al (2018) describe the improvements made to population monitoring of Australian fur seals ( Arctocephalus pusillus doriferus ) when a coordinated, range‐wide five‐yearly census approach was adopted in 2002, replacing previous sporadic and opportunistic surveys.…”

Section: Discussionmentioning

confidence: 99%

“…It was fortunate, here, that Gooday's ( 2016) study provided relatively proximate 'before' data to allow inferences to be drawn as to the effects of the earthquake on Kaik oura's NZFSs. As substantial natural disasters are uncommon and unpredictable, missing baseline data often impedes such analyses (Southwell et al, 2022).…”

Section: Abundance Estimatesmentioning

confidence: 99%

“…Without effectively monitoring such parameters, important population trends can be masked (McIntosh et al, 2018), and interventions can come too late to achieve the desired outcomes (Voyles et al, 2014). Frequently, the logistics and costs of long‐term monitoring programmes make them difficult to maintain (McIntosh et al, 2018), and gaps in the record can be exposed following catastrophic events (Schwing et al, 2020; Southwell et al, 2022) as attempts are made to understand their ecological impacts.…”

Section: Introductionmentioning

confidence: 99%

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Earthquake impacts on a protected pinniped in New Zealand

Hall,

Chilvers,

Weir

et al. 2024

Aquatic Conservation

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The impacts of natural disasters on marine mammals are poorly understood and difficult to study, which can hamper management responses following such events. This study provides the first distribution and abundance assessment of New Zealand fur seal (NZFS: Arctocephalus forsteri) colonies around Kaikōura, New Zealand, since a 7.8 magnitude earthquake in November 2016 caused substantial changes to both the local marine and terrestrial environments, and led to the reconstruction of a major highway that runs adjacent to NZFS colonies. Mark–recapture and direct counts in the 2022–2023 breeding season estimated pup production for NZFS breeding colonies along the Kaikōura coast. Using established multipliers, pup estimates were used to provide the first comprehensive population estimate for Kaikōura's NZFS population since the earthquake. Three new colonies and three new subcolonies were assessed and recorded, additional to reassessments of two established colonies. Overall, Kaikōura's NZFS population has grown and spread post‐earthquake, with an upper total population estimate of between 21,560 and 28,327 animals in the 2022–2023 breeding season. Some sites, such as Lynch's Reef, appear to have benefited from earthquake‐induced coastal uplift, with pup production increasing. Contrastingly, the estimated 2,401 (±99) pups produced at Ōhau Point in 2023 is similar to pre‐earthquake estimates. This indicates that the earthquake has disrupted previously documented growth at this site. The distribution of NZFS breeding at Ōhau Point has also changed substantially since the last pre‐earthquake assessment. From these findings, alterations to the Ōhau Point New Zealand Fur Seal Sanctuary and similar protections at other locations on the Kaikōura coast are suggested, as greater numbers of NZFSs are now accessible to human interaction and disturbance. The results demonstrate both how natural disasters and subsequent infrastructure modifications can impact coastal species and how conservation measures may need to be amended accordingly.

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Section: Discussionmentioning

confidence: 99%

Section: Abundance Estimatesmentioning

confidence: 99%