Annals of Forest Science

, Volume 70, Issue 3, pp 309–318 | Cite as

Modeling recent bark stripping by red deer (Cervus elaphus) in South Belgium coniferous stands

  • Gauthier Ligot
  • Thibaut Gheysen
  • François Lehaire
  • Jacques Hébert
  • Alain Licoppe
  • Philippe Lejeune
  • Yves Brostaux
Original Paper



Over the past few decades, the impact of large herbivorous ungulates on forest vegetation has been clearly highlighted. Among those impacts, bark stripping of coniferous trees is one of the most damaging. Bark stripping leads to rot development, inducing serious loss of timber value.


The present study aimed firstly at evidencing the factors explaining the variations observed in fresh bark peeling rate for spruce and Douglas-fir in southern Belgium and secondly at identifying the key factors to consider when setting up a deer management plan.


Fresh bark peeling rate was recorded with a systematic sampling survey from 2004 to 2007. The covered territory was then divided into 63 distinct hunting zones of area ranging from 1,000 to 25,000 ha. About 5,000 plots were monitored annually. Each zone was characterized with a large number of explanatory variables. The explanatory variables were integrated firstly into fixed linear models using a stepwise procedure, and then into a mixed model.


The significant variables included in the model (R 2 = 44 %) are (by decreasing order of importance) red deer densities, proportion of coniferous stands and agricultural areas, snow cover, distance to urban habitats, and species diversity in the understory.


The models revealed the impacts of several factors on bark peeling: deer density, deer-carrying capacity of the territory, landscape structure, and severity of winter conditions. The adjusted model allowed subtracting the impact of winter conditions in order to produce a relevant indicator for hunting management. In addition, the model was used to assess the sensitivity of a forested area to bark peeling based on its environmental characteristics.


Red deer Bark stripping Winter conditions Coniferous Wallonia 



We wish to thank the nonprofit association Forêt Wallonne, and in particular engineers Delphine Arnal and Cédric Daine, for their follow-up work on the field inventory, as well as all the employees working for the DNF forest services for carrying out the field survey. They also express their gratitude to both Hugues Lecomte (Walloon Permanent Forest Resources Inventory) and Pascal Mormal (Royal Meteorological Institute of Belgium) for making valuable data available.


This study was financially supported by the Walloon Region’s Public Service—Direction générale opérationnelle Agriculture, Ressources Naturelles et Environnement de la Région wallonne—under the Framework Agreement for Forest Research and Extension and by the FRS-FNRS through a grant awarded to G. Ligot.


  1. Bates D, Maechler M (2009) lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-32.Google Scholar
  2. Bugmann H, Weisberg P (2003) Forest–ungulate interactions: monitoring, modeling and management. J Nat Conser 10:193–201. doi: 10.1078/1617-1381-00028 CrossRefGoogle Scholar
  3. Colson V, Garcia S, Rondeux J, Lejeune P (2010) Map and determinants of woodlands visiting in Wallonia. Urban For Urban Green 9:83–91. doi: 10.1016/j.ufug.2009.04.002 CrossRefGoogle Scholar
  4. Dagnelie P (2006) Statistique théorique et appliquée: 2. Inférence statistique à 1 et 2 dimensions, vol 2. De Boeck Université,Google Scholar
  5. Debeljak M, Dzeroski S, Jerina K, Kobler A, Adamic M (2001) Habitat suitability modelling for red deer (Cervus elaphus L.) in south-central Slovenia with classification trees. Ecol Modell 138:321–330. doi: 10.1016/S0304-3800(00)00411-7 CrossRefGoogle Scholar
  6. Dolman PM, Wäber K (2008) Ecosystem and competition impacts of introduced deer. Wildl Res 35:202–214. doi: 10.1071/WR07114 CrossRefGoogle Scholar
  7. Fichant R (2003) Le cerf: biologie, comportement, gestion. Gerfaut, ParisGoogle Scholar
  8. Gheysen T, Brostaux Y, Hébert J, Ligot G, Rondeux J, Lejeune P (2011) A regional inventory and monitoring setup to evaluate bark peeling damage by red deer (Cervus elaphus) in coniferous plantations in Southern Belgium. Environmental Monitoring and Assessment 181:335–345. doi: 10.1007/s10661-010-1832-6
  9. Gill R (1992) A review of damage by mammals in north temperate forests: 1. Deer. Forestry 65:145–169. doi: 10.1093/forestry/65.2.145 CrossRefGoogle Scholar
  10. Girompaire J, Ballon P (1992) Results of barking by red dees in the Alsatian Vosges. Rev For Fr 6:501–511CrossRefGoogle Scholar
  11. Hall GP, Gill KP (2005) Management of wild deer in Australia. J Wildl Manag 69:837–844. doi:10.2193/0022-541X(2005)069[0837:MOWDIA]2.0.CO;2CrossRefGoogle Scholar
  12. Heikkilä R, Härkönen S (1996) Moose browsing in young Scots pine stands in relation to forest management. For Ecol Manag 88:179–186. doi: 10.1016/S0378-1127(96)03823-6 CrossRefGoogle Scholar
  13. Honda T, Ueda H, Takiguchi K (2008) Risk factors affecting the probability of damage by sika deer in plantation forests in Yamanashi Prefecture, Japan. Landsc Ecol Eng 4:97–102. doi: 10.1007/s11355-008-0047-2 CrossRefGoogle Scholar
  14. Jerina K, Dajcman M, Adamic M (2008) Red deer (Cervus elaphus) bark stripping on spruce with regard to spatial distribution of supplemental feeding places. Zbornik gozdarstva in lesarstva 86:33–43Google Scholar
  15. Kiffner C, Rössiger E, Trisl O, Schulz R, Rühe F (2008) Probability of recent bark stripping damage by red deer (Cervus elaphus) on Norway spruce (Picea abies) in a low mountain range in Germany—a preliminary analysis. Silva Fenn 42:125–134Google Scholar
  16. Klopcic M, Jerina K, Boncina A (2010) Long-term changes of structure and tree species composition in Dinaric uneven-aged forests: are red deer an important factor? Eur J For Res 129:277–288. doi: 10.1007/s10342-009-0325-z CrossRefGoogle Scholar
  17. Kowalski S, Montgomery D (2011) Minitab manual. Companion, design and analysis of experiments. Wiley, ChichesterGoogle Scholar
  18. Langsrud Ø (2003) ANOVA for unbalanced data: use type II instead of type III sums of squares. Stat Comput 13:163–167CrossRefGoogle Scholar
  19. Lecomte H, Florkin P, Morimont J, Thirion M (2003) La forêt Wallonne, état de la ressource à la fin du 20ème siècle. JambesGoogle Scholar
  20. Licoppe AM (2006) The diurnal habitat used by red deer (Cervus elaphus L.) in the Haute Ardenne. Eur J Wildl Res 52:164–170. doi: 10.1007/s10344-006-0027-5 CrossRefGoogle Scholar
  21. Palm R, Brostaux Y, Claustriaux JJ (2011) Macros Minitab pour le choix d’une transformation pour la normalisation de variables. Notes de Statistique et d’informatique16Google Scholar
  22. Petrak M (1998) Integration of the demands of red deer (Cervus elaphus) and man in relation to forestry, hunting and tourism. Gibier faune sauvage 15:921–926Google Scholar
  23. Putman RJ, Moore NP (1998) Impact of deer in lowland Britain on agriculture, forestry and conservation habitats. Mamm Rev 28:141–164. doi: 10.1046/j.1365-2907.1998.00031.x CrossRefGoogle Scholar
  24. R Development Core Team (2008) R: a language and environment for statistical computing, vol 3. R Foundation for Statistical Computing, ViennaGoogle Scholar
  25. Reimoser F, Armstrong H, Suchant R (1999) Measuring forest damage of ungulates: what should be considered. For Ecol Manag 120:47–58. doi: 10.1016/S0378-1127(98)00542-8 CrossRefGoogle Scholar
  26. Reimoser F, Lexer W, Forstner M, Hackl J, Heckl F (2003) Criteria and indicators of sustainable hunting. Z Jagdwiss 49:275–287Google Scholar
  27. Rondeux J, Lecomte H (2002) L’inventaire permanent des ressources forestières: observatoire et base d’un tableau de bord de la forêt wallonne. Les cahiers forestiers de Gembloux. Département des Eaux et Forêts, Faculté des Sciences Agronomiques de Gembloux, GemblouxGoogle Scholar
  28. Simon J, Kolá C (2001) Economic evaluation of bark stripping by red deer on the basis of analysis on a time growth series of spruce stands in the Hrubý Jeseník Mts. Managing Editorial Board-Redak ní rada Chairman-P edseda vol 47, pp 402–409Google Scholar
  29. Takatsuki S (2009) Effects of sika deer on vegetation in Japan: a review. Biol Conserv 142:1922–1929. doi: 10.1016/j.biocon.2009.02.011 CrossRefGoogle Scholar
  30. Vasaitis R, Lygis V, Vasiliauskaite I, Vasiliauskas A (2012) Wound occlusion and decay in Picea abies stems. Eur J For Res 131:1211–1216. doi: 10.1007/s10342-011-0592-3 CrossRefGoogle Scholar
  31. Vasiliauskas R (2001) Damage to trees due to forestry operations and its pathological significance in temperate forests: a literature review. Forestry 74:319–336CrossRefGoogle Scholar
  32. Verheyden H, Ballon P, Bernard V, Saint-Andrieux C (2006) Variations in bark-stripping by red deer Cervus elaphus across Europe. Mamm Rev 36:217–234. doi: 10.1111/j.1365-2907.2006.00085.x CrossRefGoogle Scholar
  33. Vospernik S (2006) Probability of bark stripping damage by red deer (Cervus elaphus) in Austria. Silva Fenn 40:589–601Google Scholar
  34. Wheatley M (2010) Domains of scale in forest-landscape metrics: implications for species-habitat modeling. Acta Oecol 36:259–267. doi: 10.1016/j.actao.2009.12.003 CrossRefGoogle Scholar
  35. Zuur AF, leno EN, Walker N, Saveliev A, Smith GM (2009) Zero-truncated and zero-inflated models for count data. In: Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (eds) Mixed effects models and extensions in ecology with R. Springer, New York, pp 1–33Google Scholar

Copyright information

© INRA and Springer-Verlag France 2012

Authors and Affiliations

  • Gauthier Ligot
    • 1
  • Thibaut Gheysen
    • 1
  • François Lehaire
    • 1
  • Jacques Hébert
    • 1
  • Alain Licoppe
    • 2
  • Philippe Lejeune
    • 1
  • Yves Brostaux
    • 3
  1. 1.Department of Forest and Nature ManagementUniversity of Liège, Gembloux Agro-Bio TechGemblouxBelgium
  2. 2.Department of Study of Nature and Farming (DEMNA)Natural and Agricultural Environmental Studies DepartmentGemblouxBelgium
  3. 3.Department of Statistics, Computer Science, and MathematicsUniversity of Liège, Gembloux Agro-Bio TechGemblouxBelgium

Personalised recommendations