The diachronic analysis of the local connectivity values shows that the impact of
the HSR line ranges from a few meters to several kilometers. The impact is often
located near the infrastructure but, in some sections, it may occur up to 12 km from
the line. This variability is related to the landscape configuration and the initial state
of the connectivity of the habitat patches. Indeed, all impacted habitat patches are
into components fragmented by the HSR line. The extent of disturbance therefore
depends on the size of these components, with a large component increasing the
distance of the impact as in the north-east of the study area. This highlights the
value of a regional-scale analysis for taking into account the long-distance effect of
an infrastructure on connectivity. From this perspective, graph-based methods are
interesting because they include both structural and functional aspects of connectivity. Our results are consistent with several previous studies that highlighted the
importance of integrating the barrier effect in addition to the direct loss of habitat in
environmental impact assessment (Clauzel et al. 2013; Forman and Alexander
1998; Fu et al. 2010; Girardet et al. 2013; Liu et al. 2014).
This graph-based approach provides an approximation of the potential impact
but not a hard and fast measurement of the true impact. In order to validate our
approach, these findings could be confirmed by field observations to test whether
the real impact of the infrastructure is similar to that predicted by the model. In June
2011, a specific field survey was conducted in the Ognon valley to observe the tree
frog presence after the construction of the HSR line. A total of 227 sites was visited
with 42 presences and 185 absences. The results from this survey were compared
with the connectivity changes predicted by the model. All presence points were
located where there was no impact according to the model. The absence points were
located in more or less affected areas, with a potential connectivity change between
0 and −90%. These survey results should be considered carefully because the
Spring of 2011 was very unfavorable for the tree frog due to early drying up of
water bodies. These climatic conditions could therefore explain the many points of
absence of the species. Furthermore, the time delay between the construction of the
HSR line and the surveys was not sufficient to assess the real impact of the
infrastructure. Other field surveys should be conducted in the coming years to
assess precisely the conservation status of the tree frog populations and of their
habitats in the region. These surveys will also identify the causes of extinction of
breeding populations, as several environmental factors may lie behind the extinction process, and be compounded to the long-distance effects of the infrastructure.
The method used to identify the best locations for new amphibian crossings goes
beyond the prioritization of candidate sites developed by García-Feced et al. (2011).
It is cumulative and so includes changes made to graph topology by adding previous links before searching for the next one. Graph modelling is used to include
broad-scale connectivity as a criterion to be maximized, which is a key factor for
the ecological sustainability of landscapes and for the viability of metapopulations
(Opdam et al. 2006). In this study, the tested locations corresponded to the links, i.e.
corridors potentially used by the tree frog, cut by the HSR line. Relying on the
initial network of the species increases the likelihood of functional crossings
because these links already connected habitat patches before the implementation of
224
C. Clauzel
the HSR line ranges from a few meters to several kilometers. The impact is often
located near the infrastructure but, in some sections, it may occur up to 12 km from
the line. This variability is related to the landscape configuration and the initial state
of the connectivity of the habitat patches. Indeed, all impacted habitat patches are
into components fragmented by the HSR line. The extent of disturbance therefore
depends on the size of these components, with a large component increasing the
distance of the impact as in the north-east of the study area. This highlights the
value of a regional-scale analysis for taking into account the long-distance effect of
an infrastructure on connectivity. From this perspective, graph-based methods are
interesting because they include both structural and functional aspects of connectivity. Our results are consistent with several previous studies that highlighted the
importance of integrating the barrier effect in addition to the direct loss of habitat in
environmental impact assessment (Clauzel et al. 2013; Forman and Alexander
1998; Fu et al. 2010; Girardet et al. 2013; Liu et al. 2014).
This graph-based approach provides an approximation of the potential impact
but not a hard and fast measurement of the true impact. In order to validate our
approach, these findings could be confirmed by field observations to test whether
the real impact of the infrastructure is similar to that predicted by the model. In June
2011, a specific field survey was conducted in the Ognon valley to observe the tree
frog presence after the construction of the HSR line. A total of 227 sites was visited
with 42 presences and 185 absences. The results from this survey were compared
with the connectivity changes predicted by the model. All presence points were
located where there was no impact according to the model. The absence points were
located in more or less affected areas, with a potential connectivity change between
0 and −90%. These survey results should be considered carefully because the
Spring of 2011 was very unfavorable for the tree frog due to early drying up of
water bodies. These climatic conditions could therefore explain the many points of
absence of the species. Furthermore, the time delay between the construction of the
HSR line and the surveys was not sufficient to assess the real impact of the
infrastructure. Other field surveys should be conducted in the coming years to
assess precisely the conservation status of the tree frog populations and of their
habitats in the region. These surveys will also identify the causes of extinction of
breeding populations, as several environmental factors may lie behind the extinction process, and be compounded to the long-distance effects of the infrastructure.
The method used to identify the best locations for new amphibian crossings goes
beyond the prioritization of candidate sites developed by García-Feced et al. (2011).
It is cumulative and so includes changes made to graph topology by adding previous links before searching for the next one. Graph modelling is used to include
broad-scale connectivity as a criterion to be maximized, which is a key factor for
the ecological sustainability of landscapes and for the viability of metapopulations
(Opdam et al. 2006). In this study, the tested locations corresponded to the links, i.e.
corridors potentially used by the tree frog, cut by the HSR line. Relying on the
initial network of the species increases the likelihood of functional crossings
because these links already connected habitat patches before the implementation of
224
C. Clauzel