Senecio aquaticus is a problematic pest species due to its toxic nature. It can cause economic and habitat loss. Senecio aquaticus occurs on the rare and very species rich MG8 plant community. This community relies on management practices including grazing and hay cutting to persist. Where S.aquaticus is prevalent agricultural abandonment could lead to habitat loss. At present there are no adequate control methods for S.aquaticus as current ones are costly or may damage habitat. This thesis aimed to take an ecological approach to this problem to find a new control method that was both cost effective and would not damage the habitat. Four potential control methods were trialled. Farmyard manure application, Lime, Drainage gutters and Early hay cut, aiming to take advantage of S.aquaticus s poor competitive ability, by promoting the surrounding vegetation and out-competing the Senecio. Early hay cut aimed to prevent seed set. Hay cut and manure decreased the Senecio population after two years, hay cut having the biggest effect. Lime and drainage did not reduce abundance although S.aquaticus abundance was demonstrated to correlate with high water table. Pot experiments revealed that cutting time should be around the is" June to prevent plants reflowering and before seedset. Seed bank analysis indicated a short lived seed bank. Competition experiments revealed root competition to be most influential and adult plants most sensitive. Productivity decreased with competition intensity. Early hay cut had no negative impact on the plant community, however manure decreased diversity and likeness to MG8 with an increase in grass and loss of forbes. Due to this negative impact on plant community it should not be used. This study recommends the use of early hay cut around the is" of June for two consecutive years as a S.aquaticus control method. Page 11
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582630 |
| Date | January 2011 |
| Creators | Sargent, Eleanor |
| Publisher | Open University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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