Dataset.

Supporting Information: Permeability of artificial barriers (fences) for wild boar (Sus scrofa) in Mediterranean mixed landscapes

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
  • Laguna, Eduardo
  • Barasona, José A.
  • Carpio, Antonio J.
  • Vicente, Joaquín
  • Acevedo, Pelayo
Table S1. Data for the 21 wild boar monitored by GPS-collars in this study. Table S2. Questionnaire for the characterization of fences, boundaries and perimeters of the estates in the study area. Fig. S1. Main type of fences presents in our study area. Type I (simple [A] or reinforced livestock-type fence [B]), type II (poorly-maintained big game-proof fence), type III (moderately-maintained big game-proof fence) and type IV (well-maintained big game- proof fence). Fig. S2. Fences crosses by wild boar family groups (data from photo-trapping) and some images of holes in fences obtained during the walking tour to quantify the permeability index (number of holes per km of fence). Table S3. Type of fence by main land use in the study area. Each fence (n=189) featured one or two land use. We included: length in m and percentage of type of fence for each of the possible combinations between land use. Table S4. Model selection results from the analysis of the factors influencing wild boar crossing success across fences. The corrected Akaike Information Criterion (AICc) and delta AICc (ΔAICc), i.e. the difference in AICc score relative to the model with the lowest value (most parsimonious model), are showed. As predictors were used: Type of fence (I-IV), Sex (males, females), Period (FSP, Hunting, FAP; see text for details) and their interactions (Sex*Period, Sex*Type and Type*Period). Individual (ID) was considered as a random effect factor. Fig. S3. Average daily activity of the wild boar monitored in this study. The grey band represent the inactivity period which will be excluded for the estimation of the crossing success. Fig. S4. Temporal and seasonal patterns of the interactions between animals and fences. (A) Number of crosses and bounces per month (from 1=January to 12=December). (B) Number of crosses and bounces per period (FSP= food shortage period, Hunting= hunting season, FAP= food abundance period). Appendix 1- Fence Behaviour Analysis., Peer reviewed
 
DOI: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340

HANDLE: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
 
Ver en: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
Dataset. 2022

SUPPORTING INFORMATION: PERMEABILITY OF ARTIFICIAL BARRIERS (FENCES) FOR WILD BOAR (SUS SCROFA) IN MEDITERRANEAN MIXED LANDSCAPES

Digital.CSIC. Repositorio Institucional del CSIC
  • Laguna, Eduardo
  • Barasona, José A.
  • Carpio, Antonio J.
  • Vicente, Joaquín
  • Acevedo, Pelayo
Table S1. Data for the 21 wild boar monitored by GPS-collars in this study. Table S2. Questionnaire for the characterization of fences, boundaries and perimeters of the estates in the study area. Fig. S1. Main type of fences presents in our study area. Type I (simple [A] or reinforced livestock-type fence [B]), type II (poorly-maintained big game-proof fence), type III (moderately-maintained big game-proof fence) and type IV (well-maintained big game- proof fence). Fig. S2. Fences crosses by wild boar family groups (data from photo-trapping) and some images of holes in fences obtained during the walking tour to quantify the permeability index (number of holes per km of fence). Table S3. Type of fence by main land use in the study area. Each fence (n=189) featured one or two land use. We included: length in m and percentage of type of fence for each of the possible combinations between land use. Table S4. Model selection results from the analysis of the factors influencing wild boar crossing success across fences. The corrected Akaike Information Criterion (AICc) and delta AICc (ΔAICc), i.e. the difference in AICc score relative to the model with the lowest value (most parsimonious model), are showed. As predictors were used: Type of fence (I-IV), Sex (males, females), Period (FSP, Hunting, FAP; see text for details) and their interactions (Sex*Period, Sex*Type and Type*Period). Individual (ID) was considered as a random effect factor. Fig. S3. Average daily activity of the wild boar monitored in this study. The grey band represent the inactivity period which will be excluded for the estimation of the crossing success. Fig. S4. Temporal and seasonal patterns of the interactions between animals and fences. (A) Number of crosses and bounces per month (from 1=January to 12=December). (B) Number of crosses and bounces per period (FSP= food shortage period, Hunting= hunting season, FAP= food abundance period). Appendix 1- Fence Behaviour Analysis., Peer reviewed




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