Biology subjects

McInnes, J. C.

Publications and source records attributed to McInnes, J. C..

4 recordsLinked to original sources

bioRxiv2026

First detected incursions of avian influenza H5N1 clade 2.3.4.4b into mainland Australia from the Southern Ocean

High pathogenicity avian influenza H5N1 clade 2.3.4.4b has caused a panzootic of devastating impact to poultry and wildlife globally. The Australian continent and broader Oceania until recently remained the last major region without confirmed detections. Here we report the first H5N1 clade 2.3.4.4b detections from two live seabirds - a brown skua and a southern giant petrel - found on the south coast of Western Australia in June 2026. Virus genome sequencing showed that both viruses were most closely related to H5N1 viruses detected recently on sub-Antarctic islands in the Southern Indian Ocean. In time-calibrated phylogeographic analyses, both viruses sampled in Western Australia clustered with viruses from Heard Island, a sub-Antarctic external territory of Australia. Ancestral location reconstruction also identified Heard Island as the most probable source location, although unsampled intermediate locations cannot be excluded. The two Western Australian detections were estimated to be independent incursions from Heard Island, rather than local transmission on mainland Australia. There was no evidence of reassortment with endemic avian influenza viruses in Australia, and both virus sequences retained key avian-like genetic markers and lacked known substitutions for reduced antiviral susceptibility. These detections revealed a Southern Ocean pathway of recurrent H5N1 incursions into Australia, highlighting the risk of potential establishment on the mainland and the need for heightened surveillance and rapid, nationally-coordinated, virus genomic characterisation.

microbiology↗

bioRxiv2026

Mass mortality of southern elephant seals during multi-species outbreak of HPAI H5N1 on sub-Antarctic Heard Island

High pathogenicity avian influenza (HPAI) has spread across the sub-Antarctic, causing significant wildlife impacts. We report its first detection in an Australian external territory, Heard Island and McDonald Islands, which supports over one million breeding seabirds and seals. Drone and ground surveys (October 2025, January 2026), combined with viral genome analysis, confirmed infection with Influenza A H5N1 clade 2.3.4.4b at Heard Island. Drone surveys revealed mass mortality in southern elephant seals, with 8,573 pups (62%) recorded dead across Heard Island by the final surveys. Mortality increased at an average rate of 5.6% per day in a subset of harems, and the highest observed mortality in a harem was 97%. Based on the average (76%) mortality in the final surveys, total estimated pup mortality at Heard Island was 13,359 (from a total population of 17,364 pups), though this may be an underestimate as mortality was ongoing at this time. HPAI was detected in six of nine species tested and, we suspect, led to elevated mortality in king and gentoo penguins. Phylogenetic analysis indicates the virus was introduced from Crozet Islands, with an estimated arrival around August 2025. These data show the continued easterly spread of HPAI around the sub-Antarctic, with severe but heterogeneous impacts across taxa. Our results demonstrate the value of drones for large-scale monitoring, underscoring the need for continued and enhanced HPAI surveillance across the Southern Ocean.

ecology↗

bioRxiv2021

Detecting seabird responses to invasive species eradication

Maximising survey efficiency can help reduce the trade-off between spending limited conservation resources on evaluating performance of past interventions and directing those resources towards future interventions. Seabird responses to island eradications are often poorly evaluated owing to financial, logistical and methodological challenges associated with remote field work and species ecology. We surveyed an assemblage of threatened seabirds following the worlds largest island eradication of multiple invasive species, testing multiple survey designs and outputs. We compared the outcomes of two important choices made during survey design: 1) whether to use unbiased or targeted surveys; and 2) implementing design-based or model-based analyses. An unbiased whole-island stratified randomised survey design performed well in terms of confidence in the final population estimates for widespread species, but poorly for localised recolonising species. For widespread species, model-based analyses resulted in slightly lower population estimates with narrower confidence intervals than traditional design-based approaches but failed to capture the realised niches of recolonising species, resulting in population estimates three orders of magnitude higher than current best estimates. We conclude that a multi-method approach to survey design best captures the size and distribution of recovering populations when the study system is ecologically diverse--importantly our results suggest there is no single strategy for efficient surveys of diverse seabird communities following large island invasive species eradications.

ecology↗

bioRxiv2018

Counting with DNA in metabarcoding studies: how should we convert sequence reads to dietary data?

Advances in DNA sequencing technology have revolutionised the field of molecular analysis of trophic interactions and it is now possible to recover counts of food DNA barcode sequences from a wide range of dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumers diet should we work strictly with datasets summarising the frequency of occurrence of different food taxa, or is it possible to use the relative number of sequences? Both approaches are applied in the dietary metabarcoding literature, but occurrence data is often promoted as a more conservative and reliable option due to taxa-specific biases in recovery of sequences. Here, we point out that diet summaries based on occurrence data overestimate the importance of food consumed in small quantities (potentially including low-level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that even with recovery biases incorporated, using relative read abundance (RRA) information can provide a more accurate view of population-level diet in many scenarios. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue to addressing methodological challenges, and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.

ecology↗