Simulating animal movements to predict wildlife-vehicle collisions: illustrating an application of the novel R package SiMRiv

  • Lorenzo QuagliettaEmail author
  • Miguel Porto
  • Adam T. Ford
Original Article
Part of the following topical collections:
  1. Road Ecology


In conservation, there is a high demand for methods to predict how animals respond to human infrastructure, such as estimating the location of road mortalities and evaluating the effectiveness of mitigation measures. Computer-based simulation models have emerged as an important tool in understanding wildlife-infrastructure interactions. Such models, however, often assume animal omniscience of the landscape yielding unrealistic movements, focus more on genetic connectivity than actual movement paths, or are case-specific and mathematically/computationally challenging to apply. Here, we illustrate the potential of SiMRiv, a novel R package for simulating spatially explicit, individual multistate (Markovian) movements incorporating landscape heterogeneity, in the subject of road ecology. In particular, we used SiMRiv to reproduce wildlife movement patterns and predict high-risk areas for road-kill, using Eurasian otters (Lutra lutra) as a model species. We compared the number of road crossings in real otter movements and null models (simulated, multistate Markovian movements) incorporating the effect of the landscape structure (here, water dependence). The number of road crossings in real and simulated movements was remarkably similar, and available limited real road-kill data supported SiMRiv’s road-kill risk predictions. Further, other emergent movement properties were also very similar in real and simulated movements. Overall, results show that SiMRiv has potential for reconstructing real wildlife movement patterns, as well as for predicting road-kill risk areas. SiMRiv constitutes a flexible, powerful, and intuitive tool to help biologists and managers to test mechanistic hypotheses on wildlife movement ecology, including those related to wildlife-vehicle interactions.


Landscape connectivity Individual-based mechanistic movement simulation models Movement ecology Resistance Road ecology Road-kill hotspots 



We thank the collaborators who helped with field tracking data collection, António Mira and the “Move” project for their help with the otter carcass collection and the collaboration and support to LQ’s Ph.D., the veterinarians J. Potes and J. Reis (Évora University) who surgically implanted the radio-transmitters into the otters, A. Bokkasa for his help with the proof reading, and three anonymous referees for their useful suggestions.

Funding information

In this work, we used a subsample of field tracking data collected within the framework of the Ph.D. project of LQ, for which limited funding was provided by Fundação Luis de Molina (Évora University) and supplemented by LQ’s Ph.D. fellowship. We had no specific funding for this project. ATF is supported by the National Science and Engineering Research Council and the Canada Research Chairs Program.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.CIBIO/InBio – Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, VairãoVairãoPortugal
  2. 2.CEABN/InBIO, Centro de Ecologia Aplicada “Prof Baeta Neves”, Instituto Superior de AgronomiaUniversidade de LisboaLisbonPortugal
  3. 3.Department of BiologyUniversity of British ColumbiaKelownaCanada

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