Connectivity increase threshold

Landscape connectivity (IIC) increased by means of gap-crossing capability threshold; however the rate of this increase began to decelerate after a specific distance. A total of 41 canopies were subjected to the connectivity model – 14 study areas with three canopies each, minus the Lower Kersal sample plots absent canopy ≥17.1m in 2005. A total of 40 canopy

connectivity models exhibited a rate of connectivity increase distance threshold. Out of the 40 canopy connectivity models which exhibited such a threshold (95% of all canopy connectivity models), 60% were set at 90m and 17.5% set at 120m and therefore, 77.5% of all canopy connectivity results revealed a connectivity increase threshold of 90-120m. When including those canopies which exhibited an actual threshold of between 90-120m (a total of 4 canopies) this value increases to 85% (10% set at 60m, 5% set at 150m), consequently, a rate in

connectivity increase threshold emerges. Hence, it can be stated that the influence of a

passerine’s ability to cross gaps on potential landscape connectivity begins to decrease after 90 -120m.

Such a threshold has not been identified before. Zollner and Lima (2005) did state that ‘as perceptual ranges approach a large fraction of the width of the landscape an increase in perceptual range does little to increase dispersal success’ (p 226). However, the authors did not specifically identify a connectivity increase threshold; nonetheless, this comment therefore raises a point of concern in regards to the credence of the 90-120m connectivity threshold. In particular, the tree canopy sample plots are 500m in diameter and therefore the landscape would become close to maximum connectivity levels nearer the 200m gap-crossing capability threshold, thus the rate in connectivity would naturally reduce as distance increased. However, the same 90-120m threshold was identified within the larger river valley survey area, which has a maximum width of around 4,000m. The 90-120m threshold, identified over time, in differing canopies, and in different study areas, therefore seems to be an inherent property of the

connectivity of Salford’s UTI when described using passerine gap-crossing capability thresholds. This finding has a number of implications for future practice. Due to IIC measuring both

connectivity is more important than inter-patch connectivity. That is to say, area of habitat patch is more influential to connectivity after 90-120m gap-crossing capability threshold because although a passerine may cross such a gap there is still insufficient access to

functionally sized habitat. Therefore, if overall canopy area cannot be increased within a given area, UTI management practice should target gaps in the canopy below 90-120m for overall connectivity to increase. Furthermore, the implication of this threshold also affects future studies in the way of selecting focal species. For example, to undertake the research within this thesis no focal species or genus were selected as this was considered a too narrow approach and results could potentially be biased towards that focal species/genus and therefore of little use if methods/results were to be transferable. However, due to the more general approach the 90-120m threshold suggests that future connectivity studies – which aim to improve the connectivity of an area for a certain species – should focus less on passerine habitat generalist, which potentially will move across bigger canopy gaps, and instead consider passerine habitat specialists who may resist crossing large canopy gaps (see section 2.5 and 4.2.1). To clarify, after a gap-crossing capability threshold of 90-120m is reached, UTI connectivity does not increase as much as below 90-120m. It is therefore logical to assume that studies which achieve improving landscape connectivity for passerine species, which only have a perception of, or capability to cross gaps less than 90-120m, will increase overall connectivity greater than focusing on more generalist species which are capable of crossing 200m gaps. Therefore, improving connectivity for specialist species may improve overall connectivity.

If this theoretical approach was to be adopted by future studies than it would be remiss not to mention that connectivity increased the greatest when the gap-crossing capability threshold increased from 30 to 60m. This increase was as big as 240% (Figure 4-17 and Appendix B). Therefore, focusing on closing 60m gaps would increase overall connectivity and studies that improved connectivity for even more forest specialist species (which will only cross small 30m gaps) would have a greater impact on overall landscape connectivity then trying to close 200m gaps. Of course, it must be made explicit that the greatest way to increase connectivity is to increase habitat area; however urban landscapes can make this difficult. The research in Chapter 4 therefore highlights an alternative approach, providing the hypothesis that the most

beneficial increase in connectivity is ascertained by targeting and closing canopy gaps below 90- 120m and specifically those gaps between 30 and 60m. This hypothesis could then guide future research.

4.4.3 Connectivity of the vertically stratified UTI canopies

The vertical connectivity analysis reveals that there is a need to reduce the connectivity inequality between the vertically stratified UTI canopies. In the main, the canopy ≥3m and

canopy ≥7.2m have relatively similar associative connectivity values. The canopy ≥3m is only around 1.1-16 times more connected than the canopy ≥7.2m canopy, with 16 being the exception to the rule and a 2 time increase being the norm. As such the influential effect of including trees between 3m and 7.2m in the potential landscape connectivity model is minor. In contrast, trees 17.1m and above were severely disconnected and unrepresented across a large amount of the river valley study area and as such the difference in connectivity between the canopy ≥3m and ≥7.2m and the canopy ≥17.1m is great. For the entire river valley study area the canopy >3m is between 27 and 173 times more connected than the canopy ≥17.1m while the canopy ≥7.2m is between 19 and 88 times more connected. The tree canopy sample plots reveal even greater variation, depending on the original abundance of canopy cover. In

particular, the canopy ≥17.1m is between 3 and 511 times less connected than the canopy ≥3m and between 3 and 219 times less connected than the canopy ≥7.2m. The lower difference values are found in the higher canopy cover sample plots Peel Park and Kersal, where the vertical distribution of the canopies are more equal than both the river valley study area and the lower canopy cover areas (i.e. Higher Broughton and Lower Kersal). Furthermore, in the Peel Park and Kersal sample plots the canopy ≥17.1m is better represented, reducing these connectivity differences are therefore a potential UTI management criteria.

Although the canopy ≥17.1m was the least connected of all the canopies it was often most influenced by an increase in gap-crossing capability threshold (minus the low density tree canopy sample plots). The greatest increase in connectivity from 30m to 200m was calculated

for the canopy ≥17.1m of the river valley study area in 2009 at 741%. Therefore, the canopy