Environmental Engineering Reference
In-Depth Information
will spawn further foci of invasion (Panetta and Lawes 2005). For example, in the
successful eradication of blackberries (
Rubus megalococcus
and
R
.
adenotrichos
) from
the Galapagos Islands, over half of the costs were expended delimiting the infest-
ations (Buddenhagen 2006). Clearly, increasing e ciencies in delimiting weed
distribution will be worth the eff ort. Development of predictive models based on
landscape characteristics (Shafi i
et al
. 2003) or these in conjunction with weed
dispersal parameters (Pullar
et al
. 2006) are an attempt to do this. Delimitation
can also be a problem for some vertebrate eradication campaigns. For example, the
attempt to eradicate red foxes from Tasmania is made very di cult by the managers'
inability to know where foxes occur over this 6 million hectare island—despite
over 1000 reported sightings of unknown reliability (Saunders
et al
. 2006).
h e issue of delimitation and detecting survivors or immigrants is a subset of the
wider problem of fi nding rare objects or events, which is part of the fi eld of search
theory that evolved out of applications of military science to search-and-rescue
(Haley and Stone 1979). Search theory has major potential for the management of
pests (Ramsey
et al
. 2009) and weeds (Cacho
et
al
. 2006). To be 100% certain that
no pest or weed exists in an area one would need to search everywhere in the area
with an infallible detector, but as neither condition is usually met managers often
have to interpret a string of 'zero found' data (Regan
et al
. 2006). h e key param-
eters required to do this e ciently are a detection probability (the chance that if
there is an object in the area searched or within range of the detection device that
it will be detected), and some analysis of the meaning of a string of 'zero detected'
events.
Seed banks present a particular problem in eradicating weeds. Maximum seed lon-
gevity for some species can be decades and so an eradication project must continue
until no viable seeds remain. Many plants also produce prolifi c numbers of seeds
with effective dispersal mechanisms. This means that eradication is often compro-
mised when plants recruited from the seed bank during the eradication operation
reproduce and recharge the seed bank (Panetta 2007). The need for visits to infest-
ation sites at frequencies set by plant maturation periods, and the costs to search
for new plants, appear to be the major determinants setting the upper boundaries
for weed eradication feasibility.
Seed banks of some weeds may be depleted rapidly, especially where manage-
ment involves soil disturbance and prevention of further seed input. However,
in some cases there remains a dormant but highly persistent component. Here,
frequency distributions of seed longevity are highly skewed and mirror the highly
leptokurtic distributions of seeds in space. h is can make it rather di cult to set
stopping rules in weed eradication projects. Regan
et al
. (2006) have suggested
optimal stopping times for weed eradication based on the economic trade-off
between the costs of continued monitoring with its intrinsic uncertainties, and the
cost of being wrong and declaring success too soon.
