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The Path of Least Resistance

In this guest post, Joesph Zooneveld takes us through least cost path mapping to find a mountains to sea biodiversity corridor of native bush.

In a recent GIS course at Lincoln University, I was tasked to find a spatial problem and then solve it using a GIS analysis. Being interested in conservation and biodiversity, I investigated the most efficient route for a biodiversity corridor across the Canterbury Plains. 

The Canterbury Plains have one of the lowest rates of native biodiversity in the whole of Aotearoa, with less than 0.5% of land cover in the region consisting of indigenous vegetation (Meurk, 2008). Much of that which remains is highly fragmented and of limited functional use to native fauna. A biodiversity corridor is a linear collection of wildlife habitat, generally native vegetation, which joins two or more larger areas of similar wildlife habitat (NSW Department of Environment and Conservation, 2004). Banks Peninsula and the Southern alps both contain substantial areas of both remnant and regenerating native vegetation. Connecting these two areas by a biodiversity corridor would improve the genetic exchange, increase bird seed dispersal in the area surrounding the corridor and facilitate further native regeneration on the Canterbury Plains. The two points to be connected in this study were the Omahu Bush Scenic Reserve and the Korowai-Torlesse Tussocklands Park. What is the most efficient route for this corridor to follow between these two areas? 

The ArcGIS Pro ‘Cost Path’ tool “calculates the least-cost path from a source to a destination” (ESRI, 2020a). It is a raster analysis tool that analyses the route between two points, calculating the route that accumulates the least total cost along the way, the path of least resistance. 

A flow diagram displaying how the cost-path analysis was approached is shown below.

In order for the tool to work correctly, the base raster layer was reclassified in order to make cells with no native vegetation ‘expensive’ to pass through and cells with native vegetation or restoration plantings ‘cheap’ to pass through. In order to make it cost-effective enough to avoid a near direct route between the start and finish points (worthwhile detouring through native vegetation), cells with no native vegetation were given a value of 10, restoration plantings a value of 3, native vegetation a value of 2 and areas of both a value of 1.

Following reclassification, the Cost Distance tool was used to create the input needed for the final cost path analysis, a backlink and cost distance layer. The cost distance tool “calculates the least accumulative cost distance for each cell from or to the least-cost source over a cost surface” (ESRI, 2020b).

The starting point for this tool was the Omahu Bush Scenic Reserve (named Conservation Estate). The output from the cost distance tool is shown below.



These two layers were then used as the input for the final cost path tool, with the feature destination (Native Vegetation) being the Korowai-Torlesse Tussocklands Park in the Southern Alps. 

The final output of this analysis, the least cost path across the Canterbury plains, is displayed below. Although a straight line between the start and finish point would mean the least number of cells were crossed, the analysis indicated that it is worthwhile taking a slight detour to take advantage of existing vegetation and restoration plantings along the Waikirikiri/Selwyn River. This is in line with Te Ara Kakariki’s current funding and support criteria that restoration sites should have high “proximity to the Waikirikiri/Selwyn River and to other sites (approximately 5kms)” (Te Ara Kakariki, 2020). Given that fruit eating birds are known to disperse seed up to 2.5 km (Meurk & Hall 2006),  a buffer of 2.5km radius was created surrounding the identified least-cost path. This was thought to spatially indicate where future restoration projects should be concentrated in order to maximise their efficacy and efficiency. The cost path tool was integral in producing this output. 



References

ESRI (2020a). Cost Path (Spatial Analyst). Retrieved 19/10/2020 from: https://pro.arcgis.com/en/pro-app/tool-reference/spatial-analyst/cost-path.htm

ESRI (2020b). Cost Distance (Spatial Analyst). Retrieved 19/10/2020 from: https://pro.arcgis.com/en/pro-app/tool-reference/spatial-analyst/cost-distance.htm

NSW Department of Environment and Conservation (2004). Wildlife Corridors. New South Wales Government. Retrieved 19/10/2020 from: https://www.environment.nsw.gov.au/resources/nature/landholderNotes15WildlifeCorridors.pdf

Meurk, C. (2008). Vegetation of the Canterbury Plains and downlands. In: The Natural History of Canterbury. Canterbury University Press

Meurk, C. & Hall, G. (2006). Options for enhancing forest biodiversity across New Zealand’s managed landscapes based on ecosystem modelling and spatial design. New Zealand Journal of Ecology. 30

Te Ara Kakariki (2020). Retrieved 22/10/2020 from: https://www.kakariki.org.nz/greendots/

 

• 29/10/2020


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