Directional Connectivity of Wolf (Canis lupus) Populations in Northwest Spain and Anthropogenic Effects on Dispersal Patterns

Abstract

In view of the extensive information available on wolf ecology and habitat suitability, and on the fragmentation of wolf populations by motorways and similar infrastructures, a key factor in their conservation, the aim of the present study was to model the directional connectivity of wolf populations in the region of Galicia in northwest Spain, and to quantify anthropogenic effects on wolf dispersal patterns. To this end, we map the probability of wolf movement by means of known relationships between wolf movement and anthropogenic, vegetation and topographic factors. The relative importance of each factor was quantified by sensitivity analyses. Three types of cost surface were constructed: (a) isotropic surfaces, (b) anisotropic cost surfaces taking into account terrain slope effects in the movement, and (c) surfaces obtained by combining the isotropic and anisotropic surfaces. The results obtained by approaches (a) and (c) indicate that one of the region's motorways (the AP-9) probably acts as a significant barrier to wolf movement, possibly isolating two subpopulations, while the remaining motorways probably do not have major effects on dispersal. Estimation of lowest-cost routes for wolf displacement allowed identification of areas critical for connectivity, in which it would be of interest to perform detailed studies with more precise input data on motorway course and the location of drainage channels and underpasses, etc. (these being the factors identified by sensitivity analysis to be those with the most marked effects on the cost surfaces). The visualization of connectivity enabled by this approach will allow wolf management and conservation efforts to be focused on critical areas: such efforts might include measures aimed to encourage wolf dispersal through areas in which conflict with human activity is minimized, thus contributing positively to the management of a socially conflictive species. Finally, evaluation of the different cost surfaces suggests that it would be of interest to introduce two modifications to the anisotropic algorithm, to allow the user to weigh the importance of the different input factors, and to allow the inclusion of more than one anisotropic factor in the model.

The highs and lows of dispersal: how connectivity and initial population size jointly shape establishment dynamics in discrete landscapes

“…By either allowing or preventing the dispersal of individuals from the introduction site, we considered an extreme case where landscape features would correspond to insurmountable barriers in natura. These barriers can be anthropogenic (Rodriguez‐Freire and Crecente‐Maseda ), but they can also be natural landscape features (Rueness et al ) or variations in environmental conditions (Winemiller et al ). In the context of introduced populations, such as the use of biological control agents in agriculture, landscape elements like windbreaks, hedgerows or ditches, can act as barriers to dispersal (Lovei et al , Wratten et al ).…”

Presence of Iberian wolf (Canis lupus signatus) in relation to land cover, livestock and human influence in Portugal

“…For this purpose, knowledge about minimal requirements for the survival of wolves, comprising land cover, food availability and human influences, are essential. Wolf habitat models can help to gain this information and improve the carnivore's conservation by determining priority areas, developing conservation corridors between important wolf habitats and highlighting potential conflict zones between wolves and humans (Kramer-Schadt et al, 2005;Rhodes et al, 2006;Rodriguez-Freire and Crecente-Maseda, 2008). The aim of our study was, therefore, to develop a habitat model based on data about wolf presence in central northern Portugal and gain insight into potentially important environmental factors (biotic and abiotic) for wolf distribution, with a particular emphasis on the impact of anthropogenic variables on the predator's presence.…”

Combining ensemble models and connectivity analyses to predict wolf expected dispersal routes through a lowland corridor

“…Because of the uncertainty about the maximum dispersal distance of the wolf, we tested two Euclidean distance thresholds: 100 km (low dispersal ability) and 850 km (high dispersal ability) [31]. We chose these two threshold distances because the mean wolf dispersal distance has been reported to range from about 13 to about 80 km [54,55], but occasionally individuals may travel much longer distances reaching 840-866 km [55,56]. In addition, genetic analyses performed on European wolf populations have revealed that the range of spatial influence is 650-850 km, meaning that the genetic diversity of a wolf population is influenced by populations up to 850 km apart [12].…”