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ENV510 Landscape Ecology and GIS
Kellerberrin
| New
England
| Kidman
Springs
| Crocodile
Nests
Problem
| Project | Methods
| Results 1 | Results
2 | Comparison
| Implications
A series of analyses conducted at a range of cell and window sizes examined with the field data, revealed that for KS1 a cell size of 0.2m (the lowest resolution possible) and a window size of 60mx60m was appropriate for modelling landscape pattern. Modelling of pattern in KS5 also required a cell size of 0.2m but this time a window size of 48mx48m was deemed to be appropriate.
The results show that at the scales listed above the autocorrelation approach produces surfaces that seem to be able to identify the main patches detected by fieldwork as areas which are positively autocorrelated.
In KS1 the percentage of the area that is positively autocorrelated is 18.7% while 77.7% of the area is negatively autocorrelated. This compares with 22.7 and 73.3% respectively for KS5. These figures reflect that even though the classification of KS1 made the area out to be quite homogeneous (particularly the area described as bare ground by the CSIRO classification), the area is in fact highly variable.
In comparison to KS1, KS5 had more dense patches and tended to have larger patches of mostly perennials with only small patches of annuals present. So the results from applying the autocorrelation approach seem to be consistent with fieldwork conducted in this area.
Differences in structure observed both by fieldwork and from the autocorrelation surfaces are probably related to higher disturbance factors in KS1, in particular those caused by intensive cattle grazing and trampling close to the watering hole. KS5 has been relatively undisturbed by either fire or grazing. The fact that KS1 is seen to be more heterogeneous at fine resolution as a result of disturbance could indicate that this part of the landscape is actually more unstable than KS5, making the approach a possible indicator of landscape condition.
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