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There are two major characteristics of the integral index of connectivity (IIC) which need to be acknowledged in order to understand the results in chapter 4.3. The first is that IIC

measures both intra- and inter-patch connectivity simultaneously. The second attribute of IIC, like all landscape pattern indices, is that its absolute values are not as empirically useful as its relative values. In regards to the first attribute of IIC low scores in the river valley sample plot can be attributed to the large amount of small canopy patches and as a result low intra-patch connectivity. Locally connected regions do exist within the study landscape, for example the Peel Park and Kersal sample plots, yet the large amount of small, scattered patches that are present throughout the landscape reduces the overall landscape connectivity score. As stated by Neel (2008), the ‘dependence on the ratio between area of the focal habitat and total landscape extent makes [IIC] potentially problematic for situations in which patches are very small relative to the total landscape’(p. 951) . However, although the inclusion of intra-patch connectivity within the calculation of IIC can cause low values in highly scattered landscapes, it does not necessarily mean it is ‘problematic’. Rather it must be kept in mind that IIC attempts to calculate functional connectivitynot just structural connectivity.

Neel (2008) held intra-patch connectivity as negatively responsible for the low IIC values of Cushenbury/silvery—white milkvetch (Astragalus albens)patches within southern California. From this position, the author added a caveat stating that, in fact, the majority of A. albens

patches had a high proportion of neighbouring patches within a critical distance, thus meaning higher levels of connectivity actually existed, if only locally. By adding this stipulation, the highly descriptive powers of IIC (in regards to landscape connectivity) were overlooked for the simpler descriptive powers of neighbourhood – in other words the implications of functional connectivity were overshadowed by structural connectivity. Although low IIC scores can be attributed to the presence of smaller sized patches, this does not mean there is an explanatory flaw within the metric but rather an explanatory strength – it highlights the lack of functional habitat. For instance, If a given species cannot effectively use the patches within a landscape, i.e. patches are no more than just stepping stones which can be used to move through or out of the landscape or only provide supplementary resources, then the landscape isn’t functionally

connected. Such a landscape, like the river valley study area, contains small habitat patches with structurally connected neighbours but it does not mean they are areas within which functional connectivity can occur. Therefore, the low IIC results of the river valley study area suggest that the most effective way to increase connectivity would be to increase the number of large area canopy patches. In urban areas such an approach is evidently difficult – practically impractical – as free land is highly contested and preference is afforded to other forms of infrastructure plus built surfaces. Another approach would be to identify where closing gaps in the canopy would provide the greatest benefit to overall landscape connectivity. Before such an approach is discussed, the second main attribute (absolute values are not as useful as relative values) of IIC should be addressed.

Measuring the relative importance of canopy patches for maintaining landscape

connectivity would be more insightful than a single IIC score. Furthermore, if large area canopy patches are identified as important for maintaining connectivity this would also support the claim that an increase in large patches, within the river valley study area, is necessary (analysing patch importance is undertaken in Chapter 6). In addition, the study into the temporal and vertical changes of landscape connectivity provides the opportunity to assess relative IIC values.

By incorporating the temporal scale, levels of connectivity exhibited by the river valley study area and tree canopy sample plot’s UTI’s can be compared. However, the results in section 4.3 reveal no pertinent pattern - in regards to connectivity change. As a result, UTI management processes cannot be influenced by research insights such as ‘connectivity is

decreasing/increasing at a given rate and therefore this project plan should be followed’; rather connectivity is in a state of flux. Certainly, and in general, the river valley study area’s UTI increases in connectivity from 2005 to 2009, yet the results from the tree canopy sample plots reveal more complex and sometimes opposing results.

If a panarchy approach is taken towards the results in section 4.3 then the IIC results of the smaller tree canopy sample plots are set and restrained by the processes acting in the larger river valley study area while at the same time the river valley study area is a construct of the smaller tree canopy sample plots thus its own IIC results are influenced by the processes acting in the smaller survey areas. Changes to, development in, and losses of cover can greatly affect the ecological function - when related to connectivity - of the UTI over time. However, the results reveal that the UTI is always in flux; it is not set to an equilibrium which can be identified and aimed for. For example, the canopy ≥17.1m canopy decreases across 2005 to 2013 in the Kersal sample plot yet increases from 2005 to 2009 and then decreases to a level lower than that of 2005 in the Peel Park sample plot. Therefore, temporal changes in connectivity cannot provide useful management information. Instead, connectivity results should be incorporated into understanding how resilient to change the UTI is (see Chapter 5).

Despite the lack of pertinent temporal patterns there were other evident patterns emerging from the analysis in Chapter 4 – general rules that can be applied to the effective management, maintenance, and creation of UTIs. The benefit of using a temporal connectivity analysis is that any patterns, or apparent ‘rules’, which occur across sample plots in different points in time are not a product of that time but rather an inherent property of UTI landscape patterns and passerine perception (i.e. through gap-crossing capabilities). These research outputs embody new theories and highlight potential avenues of future research.