The impacts of Invasive Non-Native Species (INNS) are well documented, and INNS management is widely considered one of top threats to global biodiversity and ecosystem function. The American signal crayfish, Pacifastacus leniusculus, is a destructive invader of freshwater ecosystems. In Scotland, this species currently has a restricted distribution. Despite the known impacts and high rates of dispersal, little is being done to manage populations that threaten to spread into Scotland's economically important catchments. One barrier to action on the management of signal crayfish is uncertainty over the implementation and efficacy of control methods. Capture-mark-recapture analysis was used to estimate the size- and season-specific capture probabilities of three traditional and two novel mechanical removal methods. By simulating the effect of harvest with these removal methods on a density-independent population model, a range of optimal seasonal combinations of removal methods were derived. Little empirical evidence exists in compensatory density-dependent dynamics in signal crayfish. I found that the probability of an individual cannibalising was affected by its size and also the density of conspecifics around it. I trialled a seasonally optimal combination of removal methods in two populations, manipulating sections of stream with different crayfish removal intensities, and tracked the movements of marked individuals. There was a high rate of dispersal (33%) that was influenced by the quality of the patch it was leaving, dispersing to, and the intensities of removal applied to the stream sections. Crayfish had a greater probability of moving to high density sections with the highest removal treatment. My conclusions suggest that conventional removal efforts (trapping), may fail due to compensatory effects on mortality and dispersal, and that novel approaches such as targeting smaller size classes are required, but only after quantitative predictions and field trials.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:742363 |
| Date | January 2017 |
| Creators | Houghton, Rupert J. |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=236448 |
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