European Journal of Forest Research

, Volume 131, Issue 3, pp 727–738 | Cite as

Site and stand characteristics related to surface erosion occurrence in forests of Catalonia (Spain)

  • Mari Selkimäki
  • José Ramón González-Olabarria
  • Timo Pukkala
Original Paper


This study aims at identifying forest areas affected by surface erosion in Catalonia. It analyses the characteristics of forests that are related to erosion occurrence. The data on erosion observations and stand variables were obtained from the Third Spanish National Forest Inventory (2000–2001). We used the classification tree method to study the presence–absence of surface erosion in four different forest types, pure coniferous, pure broadleaf and mixed stands as well in forested semiarid areas. The method provided a description of the site and stand variables, which are associated with the occurrence of surface erosion. The results revealed that forest type and stand structure are strongly related to the probability of surface erosion occurrence. In pure broadleaf forests, surface erosion occurrence was greater in dense stands, whereas in pure coniferous pine forest, the erosion occurrence was greater in sparse stands. Surface erosion occurrence was the highest in stands dominated by Fagus sylvatica and Abies alba. In order to estimate the erosion probabilities of stands, we converted the results of the classification tree analysis into erosion probabilities and mapped forest areas as low, moderate or high surface erosion risk. The accuracy of the erosion probabilities was assessed using the ROC curve, which gave a fair level (0.75) of accuracy for the total classification tree, the best (0.78) for pure broadleaf and the lowest (0.66) for mixed forest. The results of this study can be applied in future forest management planning aiming to reduce erosion risk in forests.


Classification tree analysis Erosion probability Forest types Stand structure 



We thank the Centre Tecnològic Forestal de Catalunya for providing the part of the necessary data and the Graduate School in Forest Sciences for the financial support of this study. Our special thanks to Dr Blas Mola Yudego for his valuable contribution to the manuscript.


  1. Barbier S, Balandier P, Gosselin F (2009) Influence of several tree traits on rainfall partitioning in temperate and boreal forest: a review. Ann For Sci 66:602CrossRefGoogle Scholar
  2. BDN (2001) Mapa Forestal de España. MFE50 Escala 1:50 000 Cataluña: Lerida, Gerona, Barcelona, Tarragona. Organismo Autónomo Parques Nacionales, MadridGoogle Scholar
  3. Berg B, McClaugherty C (2008) Plant litter–decomposition, humus formation, carbon sequestration, 2nd edn. Springer, HeidelbergGoogle Scholar
  4. Blanco H, Lal R (2008) Principles of soil conservation and management. Springer, NetherlandsGoogle Scholar
  5. Brandt J (1987) The effect of different types of forest management on the transformation of rainfall energy by the canopy in relation to soil erosion. In: Proceedings of the forest hydrology watershed management conference Vancouver, BC (1987), IAHS Publication No. 167, pp 213–222Google Scholar
  6. Breiman L (1996) Bagging predictors. Mach Learn 24:123–140Google Scholar
  7. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Wadsworth International Group, BelmontGoogle Scholar
  8. Brooks SM, Spencer T (1995) Vegetation modification of rainfall characteristics Implication for rainfall erositivity following logging in Sabah, Malaysia. J Trop For Sci 7(3):435–446Google Scholar
  9. Calder IR (2001) Canopy processes: implications for transpiration, interception and splash induced erosion, ultimately for forest management and water resources. Plant Ecol 153:203–214CrossRefGoogle Scholar
  10. Casas MC, Herrero M, Ninyerola M, Pons X, Rodríguez R, Rius A, Redaño A (2007) Analysis and objective mapping of extreme daily rainfall in Catalonia. Int J Climatol 27:399–409CrossRefGoogle Scholar
  11. Clavero P, Martín Vide J, Raso JM (1997) Atles climàtic de Catalunya (ACC). Institut Cartogràfic de Catalunya i Departament de Medi Ambient, Generalitat de Catalunya, BarcelonaGoogle Scholar
  12. Coll L, González-Olabarria JR, Mola-Yudego B, Pukkala T, Messier C (2011) Predicting understory maximum shrubs cover using altitude and overstory basal area in different Mediterranean forest. Eur J For Res 130:55–65CrossRefGoogle Scholar
  13. Cook EF, Goldman L (1984) Empiric comparison of multivariate analytic techniques: advantages and disadvantages of recursive portioning. J Chronic Dis 37:721–731PubMedCrossRefGoogle Scholar
  14. Costa M, Morla C, Sainz H (2005) Los Bosques Ibéricos–Una interpretación geobotánica, 4th edn. Editorial planeta, BarcelonaGoogle Scholar
  15. Covert SA, Robinchaud PR, Elliot WJ, Link TE (2005) Evaluation of runoff prediction from WEPP-based erosion models for harvesting and burned forest watershed. Trans ASAE 48(3):1091–1100Google Scholar
  16. DeBano LF (2000) The role of fire and soil heating on water repellency in wildland environments: a review. J Hydrol 231–232:195–206CrossRefGoogle Scholar
  17. DGCN (2001) Tercer Inventario Forestal Nacional (1997–2006) Cataluña. Ministerio de Medio Ambiente, MadridGoogle Scholar
  18. DGCN (2002) Plan Forestal Español 2002–2032. Ministerio de Medio Ambiente. Dirección General de Conservación de la Naturaleza, MadridGoogle Scholar
  19. DGCN (2004) Inventario nacional erosión suelos. Barcelona, Ministerio de Medio Ambiente, MadridGoogle Scholar
  20. Dissmeyer G, Foster GR (1980) A guide for predicting sheet and rill erosion on forest land. Technical publication. USDA Forest Service, AtlantaGoogle Scholar
  21. Dun S, Wu JQ, Elliot WJ, Robichaud PR, Flanagan DC, Frankenberger JR, Brown RE, Xu AC (2009) Adapting the water erosion prediction project (WEPP) model for forest application. J Hydrol 366:46–54CrossRefGoogle Scholar
  22. Edeso JM, Merino A, González MJ, Mapauri P (1999) Soil erosion under different harvesting managements in steep forestlands from Northern Spain. Land Degrad Dev 10:79–88CrossRefGoogle Scholar
  23. Elliot WJ, Robichaud PR (2001) Comparing erosion risks from forest operations to wildfire. Proceedings of the 2001 International Mountain Logging and 11th Pacific Northwest Skyline Symposium, Seattle, Washington. University of Washington, SeattleGoogle Scholar
  24. Elliot WJ, Hall DE, Graves SR (1999) Predicting sedimentation from forest roads. J For 97(8):23–29Google Scholar
  25. FAO (2006) World reference base for soil resources 2006—a framework for international classification, correlation and communication. World Soil Resources Reports 103, RomeGoogle Scholar
  26. Fernández S, Marquínez J, Menéndez Duarte R (2005) A susceptibility model for post wildfire soil erosion in a temperate oceanic mountain area of Spain. Catena 61:256–272CrossRefGoogle Scholar
  27. Ferri C, Flach P, Hernández-Orallo J (2003) Decision trees for ranking: effect of new smoothing methods, new splitting criteria and simple pruning methods. Technical report, DSIC, UPVGoogle Scholar
  28. Flanagan DC, Livingston SJ (1995) Water erosion prediction project (WEPP) version 95.7 user summary. West Lafayette, IN. NSERL Report No. 11. USDA-ARS National Soil Erosion Research Laboratory, West Lafayette, IndGoogle Scholar
  29. Gómez-Gutiérrez A, Schnabel S, Lavado-Contador JF (2009) Using and comparing two nonparametric methods (CART and MARS) to model the potential distribution of gullies. Ecol Model 220:3630–3637CrossRefGoogle Scholar
  30. González JR, Pukkala T (2007) Characterization of forest fires in Catalonia (north-east Spain). Eur J of For Res 126:421–429CrossRefGoogle Scholar
  31. González-Hidalgo JC, Peña-Monne JL, de Luis M (2007) A review of daily soil erosion in Western Mediterranean areas. Catena 71:193–199CrossRefGoogle Scholar
  32. González-Olabarria JR, Pukkala T (2011) Integrating fire risk considerations in landscape level forest planning. For Ecol Manag 261:278–287CrossRefGoogle Scholar
  33. Gracia C, Burriel JA, Ibáñez JJ, Mata T, Vayreda J (2004) Inventari Ecologic i Forestal de Catalunya. CREAF, CatalunyaGoogle Scholar
  34. Grimm M, Jones R, Montanarella L (2002) Soil erosion risk in europe. EUR 19939 EN, European soil bureau. Institute for environment & sustainability. JRC Ispra, ItalyGoogle Scholar
  35. Han J, Kamber M (2001) Data mining: concepts and techniques. Morgan Kaufmann, San FranciscoGoogle Scholar
  36. Hosmer DW, Lemeshow S (2000) Applied logistic regression, 2nd edn. Wiley, New YorkCrossRefGoogle Scholar
  37. ICONA (1991) Plan Nacional de lucha contra la erosión. Ministerio de Agricultura, pesca y alimentación. Instituto Nacional para la conservación de la naturaleza, MadridGoogle Scholar
  38. Jones C (2001) RUSLE applications on Arizona rangelands. Arizona Ranchers’ Management guide. Rangeland Manag 73–78Google Scholar
  39. Kang W, Deng X, Zhao Z (2008) Effects of canopy interception on energy conversion processes in a Chinese fir plantation ecosystem. Front For China 3:264–270CrossRefGoogle Scholar
  40. Karr JR, Dudley DR (1981) Ecological perspective on water quality goals. Environ Manag 5:55–68CrossRefGoogle Scholar
  41. Laflen JM, Elliot WJ, Flanagan DC, Meyer CR, Nearing MA (1997) WEPP-predicting water erosion using a process based model. J Soil Water Conserv 52:96–102Google Scholar
  42. Lal R (2003) Soil erosion and the global carbon budget. Environ Int 29:437–450PubMedCrossRefGoogle Scholar
  43. Lana X, Burgueño A (1998) Spatial and temporal characterization of annual extreme droughts in Catalonia (Northeast Spain). Int J Climatol 18:93–110CrossRefGoogle Scholar
  44. Merlo M, Croitoru L (2005) Valuing Mediterranean forest: towards total economic value. CABI Publishing, WallingfordCrossRefGoogle Scholar
  45. Morgan RPC (2005) Soil erosion and conservation, 3rd edn. Blackwell, OxfordGoogle Scholar
  46. Morgan RPC, Quinton JN, Smith RE, Govers G, Poesen JWA, Auerswald K, Chisci G, Torri D, Styczen ME (1998) The European soil erosion model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf Process Landf 23:527–544CrossRefGoogle Scholar
  47. Morris GL, Fan J (1998) Reservoir sedimentation handbook–design and management of dams, reservoirs and watersheds for sustainable use. McGraw-Hill, New YorkGoogle Scholar
  48. Ninyerola M, Pons X, Roure JM (2000) A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques. Int J Climatol 20:1823–1841CrossRefGoogle Scholar
  49. Palahi M, Mavsar R, Gracia C, Birot Y (2008) Mediterranean forest under focus. Int For Rev 10:676–688Google Scholar
  50. Pierson FB, Robichaud PR, Moffet CA, Spaeth KE, Williams CJ, Hardegree SP, Clark PE (2008) Soil water repellency and infiltration in coarse-textured soils of burned and unburned sagebrush ecosystems. Catena 74:98–108CrossRefGoogle Scholar
  51. Planchais I, Sinoquet H (1998) Foliage determinants of light interception in sunny and shaded branches of Fagus sylvatica (L.). Agric For Met 89:241–253CrossRefGoogle Scholar
  52. Provost F, Domingos P (2003) Tree induction for probability based ranking. Mach Learn 52(3):199–215CrossRefGoogle Scholar
  53. Razafindrabe BHN, He B, Inoue S, Ezaki T, Shaw R (2010) The role of stand density in controlling soil erosion: implication to sediment – related disasters in Japan. Environ Monit Assess 160:337–354Google Scholar
  54. Renard KG, Foster GR, Weessies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). US Department of Agriculture, Agriculture Handbook 703Google Scholar
  55. Rouget M, Richardson DM, Lavorel S, Vayreda J, Gracia C, Milton SJ (2001) Determinants of distribution of six pinus species in Catalonia, Spain. J Veg Sci 12:491–502CrossRefGoogle Scholar
  56. Sayer E (2006) Using experimental manipulation to assess the roles of leaf litter in the functioning of forest ecosystems. Biol Rev 81:1–31PubMedCrossRefGoogle Scholar
  57. Scarascia-Mugnozza G, Oswald H, Piussi P, Radoglou K (2000) Forest of the Mediterranean region: gaps in knowledge and research needs. For Ecol Manag 132:97–109CrossRefGoogle Scholar
  58. Sesnie SE, Gessler PE, Finegan B, Thessler S (2008) Integrating Landsat TM and SRTM-DEM derived variables with decision trees for habitat classification and change detection in complex neotropical environments. Remote Sens Environ 112(5):2145–2159CrossRefGoogle Scholar
  59. Soil Atlas of Europe (2006) 1 km Raster version of the European soil database (v. 2.0). In: Marc Van Liedekerke, Arwyn Jones, Panos Panagos (eds) European Soil Bureau Network & European Commission, EUR 19945 ENGoogle Scholar
  60. Spaeth K, Pierson FB, Weltz MA, Blackburn WH (2003) Evaluation of USLE and RUSLE estimated soil loss on rangeland. J Range Manag 56:234–246CrossRefGoogle Scholar
  61. Therneau TM, Atkinson EJ (1997) An introduction to recursive partitioning using the RPART routines. Technical Report 61, Mayo Clinic, Section of StatisticsGoogle Scholar
  62. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94CrossRefGoogle Scholar
  63. Thuiller W, Vayreda J, Pino J, Sabate S, Lavorel S, Gracia C (2003) Large-scale environmental correlates of forest tree distribution in Catalonia (NE Spain). Global Ecol Biogeogr 12:313–325CrossRefGoogle Scholar
  64. Tóth N, Pataki B (2007) On classification confidence and ranking using decision trees. In: Proceedings of 11th international conference on intelligent engineering systems, pp 133–138Google Scholar
  65. Trabaud L (1994) Post-fire plant community dynamics in the Mediterranean Basin. In: Moreno JM, Oechel WC (eds) ‘The role of fire in the Mediterranean-Type ecosystems. Ecological studies, Springer, New York, pp 1–15CrossRefGoogle Scholar
  66. Vayssiéres MP, Plant RE, Allen-Diaz BH (2000) Classification trees: an alternative non-parametric approach for predicting species distribution. J Veg Sci 11:679–694CrossRefGoogle Scholar
  67. Wischmeier WH, Smith DP (1978) Predicting rainfall erosion losses–a guide for selection for conservation planning. Agricultural Handbook (US Dept of Agriculture) 537Google Scholar
  68. Zhang H, Wang Q, Dai L, Guofan S, Tang L, Wang S, Gu H (2006) Quantifying soil erosion with GIS-based RUSLE under different forest management options in Jianchang forest farm. Sci China E Technol Sci 49(Supp. 1):160–166CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Mari Selkimäki
    • 1
  • José Ramón González-Olabarria
    • 2
  • Timo Pukkala
    • 1
  1. 1.School of Forest SciencesUniversity of Eastern FinlandJoensuuFinland
  2. 2.Centre Tecnològic Forestal de CatalunyaSolsonaSpain

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