Did curiosity kill the cat? The impacts of aerial baiting and Felixer deployment on feral cat populations on Three Hummock Island, Tasmania
Bibliographic record
Abstract
Context The eradication and control of feral cats (Felis catus) on offshore islands is a conservation priority in Australia to protect threatened species. However, this task is challenging and resource-intensive, particularly in remote and inaccessible locations. Aims This study aimed to evaluate the effectiveness of lethal aerial baiting and Felixer grooming traps in reducing feral cat activity on Three Hummock Island, Tasmania, to support the establishment of a hooded plover (Thinornis rubricollis) stronghold. Methods Two rounds of aerial baiting using Curiosity poisoned baits were undertaken in May 2021 and September 2023. Additionally, five Felixer units were deployed with a 6-month non-lethal period before being switched to lethal mode in November 2021. Felixers use image recognition to identify cats and apply a sodium fluoroacetate (1080) poison gel, which is ingested during grooming. A network of 20–60 camera traps, operating over 37,175 trap days during 2019–2024, was used to monitor changes in feral cat activity and site usage. Key results Feral cat relative activity (proportion of days with cat events) steadily declined following control efforts, with site usage halving after Felixer deployment in 2021 (dynamic-occupancy model slope for extinction without Felixers = −2.22, s.e. = 0.929, P = 0.0121). By contrast, aerial baiting did not significantly affect site usage (first round: estimate = 0.921, s.e. = 1.04, P = 0.378; second round: estimate = −1.021, s.e. = 0.687, P = 0.137) or activity. Despite targeting only nine cats, the Felixers contributed to a substantial decline in cat presence, suggesting a small, possibly inbred population prior to control. Camera trap images revealed that most cats were ginger, and many had kinked tails, further supporting the likelihood of inbreeding depression. Conclusions Felixers were effective in reducing feral cat activity with minimal intervention, whereas aerial baiting alone had limited impact. These findings highlight the potential of automated, low-effort control methods for managing feral cat populations on remote islands. Implications This study demonstrates that Felixers may be an effective alternative to traditional high-effort control methods, such as shooting, trapping, and baiting. However, ongoing monitoring and additional control efforts are required to ensure progress toward complete eradication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".