Habitat fragmentation is increasingly threatening wildlife by reducing areas of suitable home range and creating barriers to movement. Many conservation and mitigation efforts, led by groups ranging from governmental agencies to NGOs, aim to protect wildlife movement patterns between remnant habitat patches. These efforts require identifying areas of suitable habitat, both for movement and home ranges, in an increasingly fragmented landscape. Specifically, identifying where major movement corridors intersect with anthropogenic movement barriers (e.g., roads) is critical to determining locations for mitigation efforts, including wildlife underpasses. However, application of existing modeling approaches to on-the-ground conservation planning is often difficult due to undescribed differences between modeling methods. This study asks: how do various approaches to modeling wildlife movement differ in their identification of movement barriers and possible mitigation locations? I used a matrix of points across the landscape and ran full-factorial models using each point as a “start” and “end” point for wildlife movement across a ~2000 km2 landscape in the central Sierra Nevada Mountains in California. Both least-cost and circuit-theory based models were used to identify variation in on-the-ground movement paths. Variation was quantified by identifying locations where each movement model approach predicted wildlife movement intersecting existing barriers on the landscape.
The results of this work identify data requirements and a workflow for conservation planners to implement landscape connectivity modeling. Specifically, I propose a framework for considering intermediate-scale (hundreds to thousands of sq. km.) landscape modeling to identify where predicted high-use movement paths intersect with barriers (i.e. roads), which can then be targeted for mitigation. Using a case study in the Sierra Nevada Mountains, I present two key findings: 1. the importance for conservation planning to model movement across the landscape using a matrix of points across the landscape and factorial modeling approaches. Rather than including only several termini as wildlife movement “start” and “end” points, this identifies movement across the landscape with the acknowledgement that wildlife often live and move though sub-optimal habitats. Additionally, this has important implications for on-the-ground locations of mitigation sites. 2. The use of multiple modeling methods in conjunction provide additive, rather than substitutive value for conservation modeling. The strengths of least-cost modeling and circuit-theory modeling work provide important, but different, information to identify on-the-ground mitigation locations for applied ecology and conservation. Agencies, such as departments of transportation, can use these modeling techniques to identify locations most in need of mitigation.