Although snow petrels are ubiquitous around the Antarctic, population estimates of
this “not so charismatic” top predator are generally limited. Such information is highly
valuable for the monitoring and management of Antarctic and Southern Ocean
ecosystems, especially in a climate change context. There is a need to complement
long–term temporal demographic information obtained at a limited number of
monitoring sites with spatial distribution data.
Systematic surveys of snow petrels and Wilson’s storm petrels were undertaken at
Casey (2002-2003) and Mawson (2004-2005) in order to provide better regional
population estimates and test the performance of predictive distribution models based
on topographic and substrate variables for refining such estimates. As habitat selection
modelling is rarely used in Antarctic regions, methodological developments focus on
dealing with the peculiarities of a semi-colonial hollow-nesting species, testing habitat
selection modelling approaches and comparing the output of four types of models
(Generalized Linear and Generalized Additive Models, Classification Trees and
Ecological Niche Factor Analysis) across a range of scales.
Snow petrel nest distribution was directly related to the nature of the rock substrate
and to major topographic/geomorphological parameters such as hill slope and the
direction of the prevailing winds. Model performance varied with the scale at which
models were implemented, suggesting that nest selection processes happen
predominantly at the habitat unit and individual nest scales. Further study at the nest
scale highlighted that the influence of biotic related parameters such as conspecific
attraction (modelled as autocorrelation due to coloniality) may be of lesser influence
than selection based on individual nest quality. An alternative modelling method,
ENFA, which creates environmental envelopes for the niche of the species with
presence data only was identified as valuable for Antarctic data sets, which often lack
comprehensive records of species absence.
The validation of the models created at Casey with nest data collected in the Mawson
region returned satisfactory prediction rates in two different habitat types, coastal
islands and inland mountains, suggesting that it may be possible to predict snow petrel
distribution across East Antarctica using remotely sensed information on topography
and geomorphology, for example high-resolution aerial photography to guide in the
design of and complement ground surveys.
Similar modelling procedures applied to Wilson’s storm petrels produced more
mitigated results and selection for this species appeared to be based principally on nest
microhabitat characteristics. However, modelling provided useful information on the
large-scale habitat preferences and ecological requirements of both species
| Identifer | oai:union.ndltd.org:ADTP/246237 |
| Date | January 2006 |
| Creators | Olivier, F |
| Source Sets | Australiasian Digital Theses Program |
| Detected Language | English |
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