Environmental Engineering Reference
In-Depth Information
falcon that breeds successfully with the remaining bird, then the productivity rate
over time will depend of the replacement rate, which is dependent on the number
and distribution of falcons in the non-breeding fl oating population. Currently the
size of the non-breeding fl oating population is unknown, but will be largely related
to falcon productivity within the region. Given the type of habitats within the wider
region, it is expected that other pairs of breeding falcons are present regionally.
If the results of the modelling hold true, then the future status of nesting falcons
at the site may vary between the following scenarios:
1. Presence of an active breeding pair via replacement of individuals killed in
collisions from the fl oating population;
2. Presence of unpaired individuals;
3. Absence of falcons as a breeding species at the site; and
4. Fluctuations between these scenarios.
The results of the CRM analysis refl ect, in part, the location of the falcons' nest
within the wind farm and that the area containing the nest is the centre of their home
range in both the breeding and non-breeding season. This results in high levels of
year round activity primarily within the southern half of the wind farm. Because the
falcons' movements were centred on the nest site during both winter and summer,
any changes in the location of nest sites in the future would likely change the collision
risk for adults as well as fl edged juveniles.
Benefi ts of Enhanced Collision Risk Modelling
for Assessing Risk
In the absence of empirical data on falcons within operational wind farms in New
Zealand, this modelling approach provides an objectively derived guide from which
to scale potential mitigation. Notably, because the results are based on quantitative
data collected in the fi eld at the proposed project location, combined with a model-
ling process that takes into account the specifi c characteristics of the proposal,
they provide a greater level of transparency and scrutiny in decision making and
impact management than approaches based on qualitative assessments in the
absence of data (Fuller
2013
; Smales
2013)
.
Collision modelling provides an objective transparent approach to understanding
collision risk because it involves an objective approach to using available data to
estimate a general level of potential effect and (notwithstanding disagreements
between experts) is thus favoured by decision-makers as evidence-based. It is
important to consider that the method produces relatively coarse estimates that
should be considered at a high level, rather than as precise estimates. It is critical to
conduct post-construction monitoring to verify the model's projections in terms of
realised effect and in the context of mitigation or biodiversity offsets. In addition,
approaches to risk assessment that include spatial probability mapping, such as this
