Successful management of an invasive
species requires in depth knowledge of the invader, the
invaded ecosystem, and their interactions. The complexity
of the species-system interactions can be
reduced and represented in ecological models for
better comprehension. In this study, a spatially explicit
population model was created using the RAMAS
software package to simulate the past and future
invasion dynamics of the eastern grey squirrel (Sciurus
carolinensis) in the fragmented habitat in case study
areas in Ireland. This invasive squirrel species causes
economic damage by bark stripping forest crops and is
associated with the decline of its native congener (S.
vulgaris). Three combinations of demographic and
dispersal parameters, which best matched the distribution
of the species shortly after introduction, were
used to simulate invasion dynamics. Future population
expansion was modeled under scenarios of no control
and two different management strategies: fatal culls
and immunocontraceptive vaccination programmes.
In the absence of control, the grey squirrel range is
predicted to expand to the south and southwest of
Ireland endangering internationally important habitats,
vulnerable forest crops, and the native red
squirrel. The model revealed that region-wide intensive
and coordinated culls would have the greatest
impact on grey squirrel populations. Control strategies
consisting solely of immunocontraceptive vaccines,
often preferred by public interest groups, are predicted
to be less effective. Complete eradication of the grey
squirrel from Ireland is not economically feasible and
strategic evidence-based management is required to
limit further range expansion. Ecological models can
be used to choose between informed management
strategies based on predicted outcomes.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/612964 |
| Date | 18 February 2016 |
| Creators | Goldstein, Emily A., Butler, Fidelma, Lawton, Colin |
| Contributors | School of Natural Resources and the Environment, ENR2, University of Arizona |
| Publisher | Springer |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | Copyright © Springer International Publishing Switzerland 2016 |
| Relation | http://link.springer.com/10.1007/s10530-016-1092-7 |
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