Context Accurate spatiotemporal modeling of roadkill hotspots is essential for the assessment of high risk roadkill locations. Increasing the spatiotemporal resolution of models may facilitate greater cost-effective solutions for roadkill mitigation strategies.
Objective This study develops a novel spatiotemporal roadkill distribution model to simulate roadkill probability. Moreover, we systematically identify top prioritized road segments by the most frequent roadkill occurrence for multiple focal species.
Methods Based on the theory of the Poisson process, the proposed spatiotemporal roadkill distribution model with seasonal effects is validated with four focal reptilian species. The model simulates spatiotemporal roadkill patterns and addresses uncertainty by referencing ensemble species distribution models. Finally, we systematically prioritize road segments by the most frequent roadkill occurrence for multiple focal species.
Results The efficacy of the proposed spatiotemporal roadkill distribution model which is validated in terms of the area under the receiver operating characteristic curve (AUC) and accurate proportions. The AUC values based independent roadkill data tests ranged from 0.73 to 0.84. Both the efficacy of the proposed model, and the increases in uncertainty are attributable to decreasing seasonal sampling size and variation. Based on the independent roadkill data, more than 70% of roadkill events occurred within the top 30% priority segments by our approaches.
Conclusions The proposed model is successfully applied in simulation of spatiotemporal roadkill probability. The seasonal effects benefit identification of high roadkill probability. Through the systematic identification and the proposed model, our approach provides useful information for the design of costeffective surveys and appropriate conservation planning and mitigation strategies.
Keywords Spatiotemporal roadkill modeling Hotspot, Species distribution, Uncertainty, Systematic conservation planning
Cite or download this article as:
Lin, YP., Anthony, J., Lin, WC. et al. Landscape Ecol (2019). https://doi.org/10.1007/s10980-019-00807-w