Application of Least-Cost Movement Modeling in Planning Wildlife Mitigation Measures along Transport Corridors: Case Study of Forests and Moose in Lithuania

Abstract

The present work presents the development of a moose movement model to explore the value of wildlife mitigation structures and examine how hypothetical changes in land use patterns could alter wildlife habitats at landscape scales. Collisions between vehicles and animals pose a threat to humans and wildlife populations, the most dangerous collisions being with moose. Migrations of moose are generally predictable and habitat-dependent. Here, we use GIS-based simulations of moose movements to examine road-related habitat fragmentation around the main highways A1 and A2 in Lithuania. From forest data, we develop a moose habitat suitability map. Then, by running multiple simulation iterations, we generate potential moose pathways and statistically describe the most efficient potential long-range movement routes that are based on the principles of habitat utilization. Reflecting the probabilities of cross-highway moose movement, ranks are assigned to all 1 km highway segments, characterizing them in terms of their likelihood of moose movement, and thus identifying discrete migration corridors and highway crossing zones. Bottlenecks are identified through simulation, such as where sections of wildlife fencing end without highway crossing structures, thereby creating a ‘spillover’ effect, i.e., moose moving parallel to the highway, then crossing. The tested model has proven the prognostic capacity of the tool to foresee locations of moose-vehicle collisions with high accuracy, thus allowing it to be a valuable addition to the toolbox of highway planners.

Habitat Suitability Based Models for Ungulate Roadkill Prognosis

“…The movement component was based on the “least-cost” principle, which states that wildlife movement is most likely to follow a path of least resistance. Modeling was presented in detail in [ 27 ], thus, here we present only a short summary of this method.…”

“…We converted our habitat maps into a friction surfaces using the empirically derived formulas to convert habitat maps to the “resistance” or “friction” grids [ 27 ]. Formulas ensured that the generated pathways closely followed high quality habitat patches expressing high theoretical forage potential: when HSI = 0.00–0.40, friction value y = 5.12e −6.9315 × HSI when HSI = 0.41–0.50, y = −2.88 HSI + 1.472 when HSI = 0.51–1.00, y = 1.024e −6.9315 × HSI …”

“…With increasing availability of digital habitat suitability and biophysical and land-use data, GIS tools and applications are becoming more popular among resource managers and transportation planners for amassing information and modeling impacts and habitat linkages across roads [ 22 , 23 , 24 , 25 ]. Wildlife Movement Simulation (WMS) models, being cost effective, are a natural extension of these tools [ 18 , 26 , 27 ]. In highly fragmented ecosystems, WMS models not only help locate wildlife movement corridors, but also permit their ranking in terms of their ability to sustain wildlife movement.…”

Moose Management Strategies under Changing Legal and Institutional Frameworks

“…However, high numbers of moose pose a direct threat to humans, as their large size and long legs cause injuries or lethal consequences in wildlife-vehicle collisions [89]. This also is characteristic to Lithuania, where the growth of moose populations has resulted in an increase in moose-related wildlife-vehicle collisions [90,91]. While mitigation strategies should be species-tailored [92], they are all costly.…”

Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

“…WVCs present a serious problem and an increasing threat to traffic safety, socioeconomics, animal welfare, and wildlife management and conservation in many countries [4][5][6][7]. The number of WVCs is steadily increasing in many countries [1, [8][9][10][11][12] and in Lithuania [2,13].…”