Talk Measuring simultaneously habitat loss and fragmentation due to infrastructures: a novel Habitat Functionality metric

The ecological impact of transportation infrastructures is often considerably higher than their mere footprint in terms of direct habitat loss. Roads and railways can represent barriers to movements preventing access to potentially suitable habitat. When assessing the total effect of a given transportation infrastructure, it is crucial to quantify both direct habitat loss, and indirect habitat loss due to fragmentation. We developed a novel Habitat Functionality Metric, HFM, to quantify simultaneously the total effect of habitat loss and fragmentation. The metric is calculated using animal movement data (GPS), based on a graph theoretical approach.

First, using a large set of GPS-tracking data for wild reindeer in Norway, we estimated reindeer Habitat Quality (using Habitat Selection Probability Functions, Lele 2009), and Movement connectivity (using the Step Selection Function, Fortin et al. 2005; and Randomized Shortest Path framework, Kivimäki et al. 2014). After, the HFM was computed by calculating the connectivity of all pixels in the landscape weighted by their habitat quality. This weighted sum allowed us to integrate effects from anthropogenic infrastructures on habitat quality (e.g. habitat loss) and connectivity (e.g. habitat fragmentation) within one metric. Hence, landscapes with highest HFM scores indicate large amounts of connected, high-quality habitat, while landscapes with lowest HFM score indicate highly fragmented and/or poor-quality habitat. HFM can be used in a scenario-approach to quantify the total impact of existing or planned infrastructures and, therefore, it allows identifying land-planning or mitigation options causing the lowest cumulative impact on animal space use. The HFM will be used to guide Environmental Impact Assessment and support the identification of the most sustainable mitigation measures for wild reindeer in Norway.

Our approach does not include demographic data, and therefore relies on the assumption that habitat quality is adequately captured by the preference exhibited by the individual animals. Despite this limitation, that needs to be addressed in future studies, we believe that our approach represents a major step forward towards a more comprehensive assessment of the ecological impacts of transport infrastructures, as it combines and synthesizes both effects in terms of habitat loss and fragmentation.

connectivity, habitat, assessment