Mapping landscape connectivity for large spatial extents

Context

Mapping landscape connectivity across large spatial extents is an important component of ecological reserve network designs and species recovery plans. It can, however, be limited by computational power. One way to overcome this problem is to split the study area into smaller tiles, map landscape connectivity within each of those tiles, and then merge tiles back together to form composite connectivity maps.

Objectives

We tested the effects of landscape structure on the accuracy of composite landscape connectivity maps created from tiles and tested two methods to increase this accuracy.

Methods

We correlated replicate, composite current density maps with untiled maps. We tested whether our findings depended on the composition of the landscape by testing maps with corridors, barriers, different mixtures of high- and low-cost habitat, and road networks.

Results

We found that composite current density maps underestimated large-scale connectivity and overestimated the contribution of small habitat patches to overall connectivity. These biases became more pronounced as the tiles became relatively smaller. Landscapes with corridors or barriers were particularly sensitive. We increased the accuracy of tiled maps by increasing pixel size or by averaging several maps created using a “moving window” approach.

Conclusions

There is a trade-off between tile size and pixel size when modelling connectivity across large spatial extents. We suggest using the largest tile size possible when tiling is necessary, in conjunction with increased pixel size and a moving window method to increase accuracy of the composite current density maps.