Identification methods and deterministic factors of owl roadkill hotspot locations in Mediterranean landscapes

Abstract

Road fatalities are among the major causes of mortality for Strigiformes species and may affect the population's survival. The use of mitigation strategies must be considered to overcome this problem. However, because mitigation along the total length of all roads is not financially feasible, the locations where Strigiformes roadkills are more frequent (i.e., road fatality hotspots) must be identified. In addition to hotspot identification, factors that influence the occurrence of such fatalities should be recognized to allow mitigation measures to be delineated. We used road fatality data collected from 311 km of southern Portugal roads over a 2-year period to compare the performance of five hotspot identification methods: binary logistic regression (BLR), ecological niche factor analysis (ENFA), Kernel density estimation, nearest neighbor hierarchical clustering (NNHC), and Malo's method. BLR and ENFA modelling were also used for recognizing roadkill deterministic factors. Our results suggest that Malo's method should be preferred for hotspot identification. The main factors driving owl roadkillings are those associated with good habitat conditions for species occurrence and specific conditions that promote hunting behavior near roads. Based on these factors, several mitigation measures are recommended.

Habitat or matrix: which is more relevant to predict road-kill of vertebrates?

“…Volant mammals and owls can cross highways fast, especially in open vegetation sites with an eventual vehicle collision as consequence. Even forest species of owls can move through matrix, particularly in conditions that promote hunting behavior (Gomes et al, 2009). Despite the low number of road-kill events of reptiles, probably because they are easily detectable with a monitoring on foot (Teixeira et al, 2013), herbaceous vegetation also was positively related to their road-kill.…”

Priority ranking of road sites for mitigating wildlife roadkill

“…Unlike studies that aim to establish predictive models of roadkill (Malo et al 2004, Gomes et al 2009, Roger & Ramp 2009), the RI intends to rank the kilometers and identify those in which the installation of mitigation devices is a priority. The proposal for the RI presented here was developed in one case study, based on sections of one kilometer.…”

“…Of these effects, the most studied in recent years is the roadkills of wild animals (Clevenger et al 2003, Taylor & Goldingay 2004, Pinowski 2005, Coelho et al 2008, Gomes et al 2009). Accidents occur because the highway cuts through the habitat of the species, interfering with their natural range of movement and resulting in collisions with vehicles (Coffin 2007).…”

“…Brazilian studies seek to establish mitigation strategies for a large number of species (Coelho et al 2008, GumierCosta & Sperber 2009, Turci & Bernarde 2009), normally involving different classes. Outside Brazil, the majority of publications focus on a specific species (Finder et al 1999, Gomes et al 2009, Roger & Ramp 2009), order (Aresco 2005), or class (Hels & Buchwald 2001). Possibly this difference is related to the existing species richness, or to economic issues as well.…”

“…The identification of hotspots has involved such varied areas as the criminal (Glässer & Vajihollahi 2008) or health (d'Aignaux et al 2001, used in the definition of public policies, identification of priority areas for conservation (Myers et al 2000), and in critical roadkill areas (Ramp et al 2005, Gomes et al 2009, Roger & Ramp 2009). Brazil lacks studies on wildlife roadkill that are aimed at the implementation and evaluation of mitigation measures, and most studies have focused on listing the species that are run over (Bager et al 2007).…”