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Biodiversity and Conservation

, Volume 27, Issue 5, pp 1239–1256 | Cite as

The importance of fine-scale breeding site selection patterns under a landscape-sharing approach for wolf conservation

  • Luis Llaneza
  • Víctor Sazatornil
  • José Vicente López-BaoEmail author
Original Paper

Abstract

For large carnivores persisting in human-dominated landscapes, conservation planning is often hindered by the large spatial requirements of these species, availability of protected areas, and human land uses. Protected areas are usually too small to support viable populations, and scattered across a human land-use matrix. Therefore, large carnivore conservation should be planned at large spatial scales under a land-sharing approach (allowing the coexistence between large carnivores and people in the same landscape), which means increasing the focus on the human-dominated matrix. Most of the critical factors determining large carnivore persistence (i.e., those related to food availability and vulnerability to humans) interact synergistically in space and time during the breeding season. Here, using as a case study a wolf population in NW Iberia, we studied fine-scale breeding site selection patterns (1 and 9 km2) in relation to human pressure, and the availability of food and refuge. The selection of wolf breeding sites in this human-dominated landscape was not determined by potential availability of prey biomass in the immediate vicinity (1 km2). However, wolves selected breeding sites with high availability of refuge (concealing vegetation), and low human accessibility and activity levels. Paved roads showed the highest proportion of independent contribution to explaining breeding site selection patterns (negative influence), being followed by refuge availability (positive influence) and the remoteness of breeding sites in relation to the surrounding spatial context (positive influence). Refuge availability, even at very small spatial scales taking into account the spatial requirements of wolves, may compensate for moderate levels of human activities in the vicinity of breeding sites. The strength of breeding selection patterns varied along a hierarchical process at different spatial scales. Under a landscape-sharing approach, integrating key processes observed in the human-dominated matrix, such as breeding site selection patterns, into landscape planning is of paramount importance for carnivore conservation. By temporally restricting human use on breeding sites and small portions of surrounding lands (~ 1 km2), and by maintaining several small refuge areas interspersed within the human-dominated matrix, we could favor wolf persistence without reducing land availability for other uses, improving the conditions for coexistence between wolves and humans.

Keywords

Large carnivores Human-dominated landscapes Canis lupus Coexistence Land-sharing Refuge quality Homesite Urban compactness Carnivore persistence 

Notes

Acknowledgements

We are in debt to the staff of the Regional Government of Galicia (Belén Bris, Rogelio Fernández, Carmen Juliani, Mercedes Robles, Emilio Rosa, Jesús Santamarina, Javier Turrillo). Spatial information from wolves in the study area comes from research projects funded by DESA S.L. and GAMESA S.L. We thank Enrique Anchústegui (DESA) and Aitziber Céspedes (GAMESA) for their collaboration and support. J.V.L.B. was supported by a Ramon & Cajal research contract (RYC-2015-18932) from the Spanish Ministry of Economy, Industry and Competitiveness. This is scientific paper no. 19 from the Iberian Wolf Research Team (IWRT).

Supplementary material

10531_2017_1491_MOESM1_ESM.docx (41 kb)
Supplementary material 1 (DOCX 40 kb)

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Authors and Affiliations

  1. 1.A.RE.NA. Asesores en Recursos Naturales, S.LLugoSpain
  2. 2.Departamento de Bioloxía Celular e EcoloxíaUniversidad de Santiago de CompostelaSantiago de CompostelaSpain
  3. 3.Department of Evolutionary Biology, Ecology and Environmental SciencesUniversity of BarcelonaBarcelonaSpain
  4. 4.Research Unit of Biodiversity (UO/CSIC/PA)Oviedo UniversityMieresSpain

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