A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA

Many organisms persist in fragmented habitat where movement between patches is essential for long-term demographic and genetic stability. In the absence of direct observation of movement, connectivity or isolation metrics are useful to characterize potential patch-level connectivity. However, multiple metrics exist at varying levels of complexity, and empirical data on species distribution are rarely used to compare performance of metrics. We compared 12 connectivity metrics of varying degrees of complexity to determine which metric best predicts the distribution of prairie dog colonies along an urban gradient of 385 isolated habitat patches in Denver, Colorado, USA. We found that a modified version of the incidence function model including area-weighting of patches and a cost-weighted distance surface best predicted occupancy, where we assumed roads were fairly impermeable to movement, and low-lying drainages provided dispersal corridors. We also found this result to be robust to a range of cost weight parameters. Our results suggest that metrics should incorporate both patch area and the composition of the surrounding matrix. These results provide guidance for improved landscape habitat modeling in fragmented landscapes and can help identify target habitat for conservation and management of prairie dogs in urban systems.     

Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation

The loss of connectivity of natural areas is a major threat for wildlife dispersal and survival and for the conservation of biodiversity in general. Thus, there is an increasing interest in considering connectivity in landscape planning and habitat conservation. In this context, graph structures have been shown to be a powerful and effective way of both representing the landscape pattern as a network and performing complex analysis regarding landscape connectivity. Many indices have been used for connectivity analyses so far but comparatively very little efforts have been made to understand their behaviour and sensitivity to spatial changes, which seriously undermines their adequate interpretation and usefulness. We systematically compare a set of ten graph-based connectivity indices, evaluating their reaction to different types of change that can occur in the landscape (habitat patches loss, corridors loss, etc.) and their effectiveness for identifying which landscape elements are more critical for habitat conservation. Many of the available indices were found to present serious limitations that make them inadequate as a basis for conservation planning. We present a new index (IIC) that achieves all the properties of an ideal index according to our analysis. We suggest that the connectivity problem should be considered within the wider concept of habitat availability, which considers a habitat patch itself as a space where connectivity exists, integrating habitat amount and connectivity between habitat patches in a single measure.