The road towards wildlife friendlier infrastructure: Mitigation planning through landscape-level priority settings and species connectivity frameworks

Occupancy of the Ethiopian endemic Moorland Francolin in pristine and degraded Afroalpine biome using a camera trap approach

“…Distance to road was also the other strongest covariate influencing the occupancy probability of Moorland Francolins, similar to other reports in ground‐dwelling bird species (Whitworth et al, 2018 ). The occupancy probability of the species was higher along the edge of roadsides and trails than at sites located in remote in GCCA, in concordance with other reports on wildlife species (Kroeger et al, 2022 ; Paemelaere et al, 2023 ). This is unexpected because roads can attract hunters and predators, delivering also other human‐induced perturbations (Dean et al, 2019 ; Kroeger et al, 2022 ).…”

“…The detectability may be affected by spatial variations and sample sizes. Our hypothesis that species detection increases with number of days of cameras deployed showed consistency with other findings in bird (Paemelaere et al, 2023 ; Si et al, 2014 ) and mammal species (Holzner et al, 2021 ; Semper‐Pascual et al, 2020 ; Shannon et al, 2014 ; Si et al, 2014 ; Wevers et al, 2021 ). The magnitude of sampling occasion on detection probability estimate demonstrates species‐specific response (Iannarilli et al, 2021 ).…”

“…There was no significant difference for the covariate in this area, yet relatively high model-averaged beta coefficient estimate; model weight and confidence intervals reveal irregularity in association with the species, most presumably due to lack of habitat heterogeneity, a small sample size, limited number of cameras, and small sampling occasions, as compared to recommended occasions. Hence distance to settlement had a slightly significant positive influence on the species in SEA, agreeing with previous studies on pheasants (Chen et al, 2019;Jolli et al, 2012;Nuttall et al, 2017;O'Brien & Kinnaird, 2008), other bird (Pardo et al, 2017) and mammal species (Paemelaere et al, 2023;Semper-Pascual et al, 2020).…”

A spatiotemporal analysis of ungulate–vehicle collision hotspots in response to road construction and realignment

“…Our study highlights the importance of spatiotemporal scale in planning and evaluating wildlife mitigation measures on roads. We recognize that while road mortality data and UVC hotspot analyses are important, they do not necessarily indicate where wildlife crossing opportunities are most needed for priority species (Jacobson et al 2016, Paemelaere et al 2023. We recommend the use of planning frameworks that also incorporate the behavioral responses of priority species to roads and traffic volume (Jacobson et al 2016) and species-or guild-specific ecological considerations (Paemelaere et al 2023;Kintsch et al, unpublished manuscript: https://arc-solutions.org/wp-content/ uploads/2021/03/08.-ICOET-WildlifeCrossingGuilds-paper.pdf).…”

“…We recognize that while road mortality data and UVC hotspot analyses are important, they do not necessarily indicate where wildlife crossing opportunities are most needed for priority species (Jacobson et al 2016, Paemelaere et al 2023. We recommend the use of planning frameworks that also incorporate the behavioral responses of priority species to roads and traffic volume (Jacobson et al 2016) and species-or guild-specific ecological considerations (Paemelaere et al 2023;Kintsch et al, unpublished manuscript: https://arc-solutions.org/wp-content/ uploads/2021/03/08.-ICOET-WildlifeCrossingGuilds-paper.pdf). By monitoring UVC hotspot evolution over space and time, we were able to identify stable vs. ephemeral hotspots, detect a fenceend and barrier effect for ungulates, and explore hotspot stability before and after construction.…”