Detection parameters for managing invasive rats in urban environments
Abstract Effective mitigation of the impacts of invasive ship rats (Rattus rattus) requires a good understanding of their ecology, but this knowledge is very sparse for urban and peri-urban areas. We radiomarked ship rats in Wellington, New Zealand, to estimate detection parameters (σ, ε 0 , θ, and...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-20677-8 |
| _version_ | 1797996112466935808 |
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| author | Henry R. Mackenzie M. Cecilia Latham Dean P. Anderson Stephen Hartley Grant L. Norbury A. David M. Latham |
| author_facet | Henry R. Mackenzie M. Cecilia Latham Dean P. Anderson Stephen Hartley Grant L. Norbury A. David M. Latham |
| author_sort | Henry R. Mackenzie |
| collection | DOAJ |
| description | Abstract Effective mitigation of the impacts of invasive ship rats (Rattus rattus) requires a good understanding of their ecology, but this knowledge is very sparse for urban and peri-urban areas. We radiomarked ship rats in Wellington, New Zealand, to estimate detection parameters (σ, ε 0 , θ, and g 0 ) that describe the process of an animal encountering a device (bait stations, chew cards and WaxTags) from a distance, and then approaching it and deciding whether to interact with it. We used this information in simulation models to estimate optimal device spacing for eradicating ship rats from Wellington, and for confirming eradication. Mean σ was 25.37 m (SD = 11.63), which equates to a circular home range of 1.21 ha. The mean nightly probability of an individual encountering a device at its home range center (ε 0 ) was 0.38 (SD = 0.11), whereas the probability of interacting with the encountered device (θ) was 0.34 (SD = 0.12). The derived mean nightly probability of an individual interacting with a device at its home range center (g 0 ) was 0.13 (SD = 0.08). Importantly, σ and g 0 are intrinsically linked through a negative relationship, thus g 0 should be derived from σ using a predictive model including individual variability. Simulations using this approach showed that bait stations deployed for about 500 days using a 25 m × 25 m grid consistently achieved eradication, and that a surveillance network of 3.25 chew cards ha−1 or 3.75 WaxTags ha−1 active for 14 nights would be required to confidently declare eradication. This density could be halved if the surveillance network was deployed for 28 nights or if the prior confidence in eradication was high (0.85). These recommendations take no account of differences in detection parameters between habitats. Therefore, if surveillance suggests that individuals are not encountering devices in certain habitats, device density should be adaptively revised. This approach applies to initiatives globally that aim to optimise eradication with limited funding. |
| first_indexed | 2024-04-11T10:12:20Z |
| format | Article |
| id | doaj.art-f25b5674689e4414a4be615b8045a854 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T10:12:20Z |
| publishDate | 2022-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f25b5674689e4414a4be615b8045a8542022-12-22T04:30:04ZengNature PortfolioScientific Reports2045-23222022-10-0112111410.1038/s41598-022-20677-8Detection parameters for managing invasive rats in urban environmentsHenry R. Mackenzie0M. Cecilia Latham1Dean P. Anderson2Stephen Hartley3Grant L. Norbury4A. David M. Latham5Center for Biodiversity and Restoration Ecology, School of Biological Sciences, Te Herenga Waka-Victoria University of WellingtonManaaki Whenua-Landcare ResearchManaaki Whenua-Landcare ResearchCenter for Biodiversity and Restoration Ecology, School of Biological Sciences, Te Herenga Waka-Victoria University of WellingtonManaaki Whenua-Landcare ResearchManaaki Whenua-Landcare ResearchAbstract Effective mitigation of the impacts of invasive ship rats (Rattus rattus) requires a good understanding of their ecology, but this knowledge is very sparse for urban and peri-urban areas. We radiomarked ship rats in Wellington, New Zealand, to estimate detection parameters (σ, ε 0 , θ, and g 0 ) that describe the process of an animal encountering a device (bait stations, chew cards and WaxTags) from a distance, and then approaching it and deciding whether to interact with it. We used this information in simulation models to estimate optimal device spacing for eradicating ship rats from Wellington, and for confirming eradication. Mean σ was 25.37 m (SD = 11.63), which equates to a circular home range of 1.21 ha. The mean nightly probability of an individual encountering a device at its home range center (ε 0 ) was 0.38 (SD = 0.11), whereas the probability of interacting with the encountered device (θ) was 0.34 (SD = 0.12). The derived mean nightly probability of an individual interacting with a device at its home range center (g 0 ) was 0.13 (SD = 0.08). Importantly, σ and g 0 are intrinsically linked through a negative relationship, thus g 0 should be derived from σ using a predictive model including individual variability. Simulations using this approach showed that bait stations deployed for about 500 days using a 25 m × 25 m grid consistently achieved eradication, and that a surveillance network of 3.25 chew cards ha−1 or 3.75 WaxTags ha−1 active for 14 nights would be required to confidently declare eradication. This density could be halved if the surveillance network was deployed for 28 nights or if the prior confidence in eradication was high (0.85). These recommendations take no account of differences in detection parameters between habitats. Therefore, if surveillance suggests that individuals are not encountering devices in certain habitats, device density should be adaptively revised. This approach applies to initiatives globally that aim to optimise eradication with limited funding.https://doi.org/10.1038/s41598-022-20677-8 |
| spellingShingle | Henry R. Mackenzie M. Cecilia Latham Dean P. Anderson Stephen Hartley Grant L. Norbury A. David M. Latham Detection parameters for managing invasive rats in urban environments Scientific Reports |
| title | Detection parameters for managing invasive rats in urban environments |
| title_full | Detection parameters for managing invasive rats in urban environments |
| title_fullStr | Detection parameters for managing invasive rats in urban environments |
| title_full_unstemmed | Detection parameters for managing invasive rats in urban environments |
| title_short | Detection parameters for managing invasive rats in urban environments |
| title_sort | detection parameters for managing invasive rats in urban environments |
| url | https://doi.org/10.1038/s41598-022-20677-8 |
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