IBMs is that we are no longer constrained by the difficulties of obtaining
analytical or numerical solutions using differential calculus, or are dependent on
the mathematical tractability of complicated systems of differential (or integral)
equations (Railsback and Grimm 2011). With IBMs, one can model a wide
variety of behaviors, thus increasing the realism of the models—although often
at the expense of time consuming simulations.
The most effective tools for reducing barrier effects, such as overpasses or
viaducts, increase construction costs considerably (Smith et al. 2015).
Therefore, either before or after railway construction, simulations at the landscape level can be used to identify the location and type of the mitigation
measures to be implemented. For instance, Gundersen and Andreassen (1998)
included both train- and environment-related variables to model the occurrence
of WTCs during seasonal moose migration to valley bottoms, when WTC risk
is highest (Gundersen et al. 1998). and they tested the model predictability with
a subset of data not used for model development, a method that can be used to
infer future WTCs (Gundersen and Andreassen 1998).
Effectiveness of Mitigation Measures
Avoiding Crossing
Several studies have tested measures, like fencing, to avoid animal crossings of
railways. These can reduce WTCs but, on the other hand, they can increase barrier
effects (e.g., Ito et al. 2005, 2008, 2013; see also Chap. 14). Thus, they should only
be implemented in areas of high concentration of WTCs, and combined with
wildlife passes to maintain railway permeability (van der Grift 1999). Building
exclusion fences seems the most effective (van der Grift 1999; Ito et al. 2013), and
is even the most cost-effective measure, in the long run (Dorsey et al. 2015). The
application of odor repellents reduced animal mortality in a study in the Czech
Republic, but with contrasting results among taxa (Kušta et al. 2015). This technique was less effective at low temperatures, when repellents froze (Kušta et al.
2015; see also Castiov 1999). Indeed, Andreassen et al. (2005) found odour
repellents to have highly variable efficiency in reducing moose WTCs in Norway.
Instead, these authors found a more consistent decrease in WTCs after the placement of feeding stations to keep animals away from railways, and forest clearing in
the vicinity of the railway (Andreassen et al. 2005).
Interesting alternatives are those devices that aim to reduce WTCs without
having barrier effects (see Chap. 17). For example, trains equipped with ultrasonic
warning devices killed fewer moose in Canada than those without (Muzzi and
Bisset 1990). More recently, Babińska-Werka et al. (2015) reported the development of a device in Poland that uses alarm calls from several wild animals in
advance (30 s to 3 min) of an oncoming train that allows animals near the railway
54
R. Barrientos and L. Borda-de-Água
analytical or numerical solutions using differential calculus, or are dependent on
the mathematical tractability of complicated systems of differential (or integral)
equations (Railsback and Grimm 2011). With IBMs, one can model a wide
variety of behaviors, thus increasing the realism of the models—although often
at the expense of time consuming simulations.
The most effective tools for reducing barrier effects, such as overpasses or
viaducts, increase construction costs considerably (Smith et al. 2015).
Therefore, either before or after railway construction, simulations at the landscape level can be used to identify the location and type of the mitigation
measures to be implemented. For instance, Gundersen and Andreassen (1998)
included both train- and environment-related variables to model the occurrence
of WTCs during seasonal moose migration to valley bottoms, when WTC risk
is highest (Gundersen et al. 1998). and they tested the model predictability with
a subset of data not used for model development, a method that can be used to
infer future WTCs (Gundersen and Andreassen 1998).
Effectiveness of Mitigation Measures
Avoiding Crossing
Several studies have tested measures, like fencing, to avoid animal crossings of
railways. These can reduce WTCs but, on the other hand, they can increase barrier
effects (e.g., Ito et al. 2005, 2008, 2013; see also Chap. 14). Thus, they should only
be implemented in areas of high concentration of WTCs, and combined with
wildlife passes to maintain railway permeability (van der Grift 1999). Building
exclusion fences seems the most effective (van der Grift 1999; Ito et al. 2013), and
is even the most cost-effective measure, in the long run (Dorsey et al. 2015). The
application of odor repellents reduced animal mortality in a study in the Czech
Republic, but with contrasting results among taxa (Kušta et al. 2015). This technique was less effective at low temperatures, when repellents froze (Kušta et al.
2015; see also Castiov 1999). Indeed, Andreassen et al. (2005) found odour
repellents to have highly variable efficiency in reducing moose WTCs in Norway.
Instead, these authors found a more consistent decrease in WTCs after the placement of feeding stations to keep animals away from railways, and forest clearing in
the vicinity of the railway (Andreassen et al. 2005).
Interesting alternatives are those devices that aim to reduce WTCs without
having barrier effects (see Chap. 17). For example, trains equipped with ultrasonic
warning devices killed fewer moose in Canada than those without (Muzzi and
Bisset 1990). More recently, Babińska-Werka et al. (2015) reported the development of a device in Poland that uses alarm calls from several wild animals in
advance (30 s to 3 min) of an oncoming train that allows animals near the railway
54
R. Barrientos and L. Borda-de-Água