Plant and Soil

, Volume 322, Issue 1–2, pp 139–150 | Cite as

Spatial variability of soil properties under Pinus canariensis canopy in two contrasting soil textures

  • A. Rodríguez
  • J. Durán
  • J. M. Fernández-Palacios
  • A. Gallardo
Regular Article


Knowledge of the spatial pattern and scale of plant resources is important to aid in understanding the causes of this spatial pattern and their consequences on process at the population, community, and ecosystem levels. We tested whether the effect of individual plants on the soil properties beneath their canopies might be mediated by soil texture, since this soil property has great influence on the soil organic matter protection, the soil cation exchange capacity, and the nutrients diffusion rate. We hypothesize that variables directly related to organic matter (microbial biomass-N [MB-N] or dissolved organic-N [DON]), as well as soil nutrients interacting with soil secondary minerals (PO4-P and NH4-N), should more closely follow the plant canopy projection in sandy soils than loamy ones. We also expected a higher spatial range and dependence of NO3-N in sandy soils, although the spatial distribution should not necessarily be affected by the plant position. To test these hypotheses, we used square plots (8 m × 8 m or 6 m × 6 m) placed around isolated mature individuals of Pinus canariensis in both loamy and sandy soils in P. canariensis forests, with replicates in summer and winter. Spatial pattern and scale of MB-N, DON, and inorganic-N and -P were analyzed with geostatistical methods. In the summer sampling, all soil variables had lower spatial ranges in the loamy soil than the sandy soil. However, no clear trend was observed in the winter. The spatial dependence of NO3-N from the two sampling dates was higher for the sandy soil than the loamy soil. Kriged maps in the sandy soil revealed that the spatial distributions of the summer soil moisture, MB-N, DON, and PO4-P were all dependent on pine location. Our results suggested that the presence of P. canariensis individuals may be an important source of spatial heterogeneity in these forests. Soil texture may determine the magnitude of the pine canopy’s effect on the spatial distribution of chemical and biological soil properties when water content is scant, but it may have negligible effects under conditions of higher water availability.


Geostatistics Pinus canariensis Soil nitrogen Soil phosphorus Soil texture Spatial heterogeneity 



We thank Rocío Paramá, Rosana Estévez, Javier Méndez, and Gustavo Morales, who helped in soil sampling and chemical analyses. Special thanks are due to Felisa Covelo and Jesus Rodríguez for their unconditional help. Local government authorities (Cabildo Insular de La Palma) provided us with lodging, four-wheel drive vehicles, and other facilities to carry out research on the island; we especially thank Félix Medina for this help. This study was financed by the Ministerio Español de Ciencia y Tecnología of the Spanish government, and grants REN2003-08620-C02-01 and CGL2006-13665-C02-01. Alexandra Rodríguez was funded by a graduate student fellowship from the Galician (NW Spain) government.


  1. Antonovics J, Clay K, Schmitt J (1987) The measurement of small-scale environmental heterogeneity using clonal transplants of Anthoxanthum odoratum and Danthonia spicata. Oecologia 71:601–607 doi: 10.1007/BF00379305 CrossRefGoogle Scholar
  2. Box GEP, Cox DR (1964) An analysis of transformations. J R Stat Soc [Ser A] 26:211–243Google Scholar
  3. Brookes PC, Landman A, Pruden G, Jenkinson DS (1985) Chloroform fumigation and the release of soil nitrogen; a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol Biochem 17:837–842 doi: 10.1016/0038-0717(85)90144-0 CrossRefGoogle Scholar
  4. Cabrera ML, Beare MH (1993) Alkaline persulphate oxidation for determining total nitrogen in microbial biomass extracts. Soil Sci Soc Am J 57:1007–1012Google Scholar
  5. Cain ML, Subler S, Evans JP, Fortin MJ (1999) Sampling spatial and temporal variation in soil nitrogen availability. Oecologia 118:397–404 doi: 10.1007/s004420050741 CrossRefGoogle Scholar
  6. Climent J, Tapias R, Pardos JA, Gil L (2004) Fire adaptations in the Canary Islands pine (Pinus canariensis). Plant Ecol 171:185–196 doi: 10.1023/B:VEGE.0000029374.64778.68 CrossRefGoogle Scholar
  7. Covelo F, Rodríguez A, Gallardo A (2008) Spatial pattern and scale of leaf N and P resorption efficiency and proficiency in a Quercus robur population. Plant Soil 311:109–119 doi: 10.1007/s11104-008-9662-9 CrossRefGoogle Scholar
  8. D’Elia CF, Steudler PA, Corwin N (1977) Determination of total nitrogen in aqueous samples using persulfate digestion. Limnol Oceanogr 22:760–764Google Scholar
  9. Doyle A, Weintraub MN, Schimel JP (2004) Persulfate digestion and simultaneous colorimetric analysis of carbon and nitrogen in soil extracts. Soil Sci Soc Am J 68:669–676CrossRefGoogle Scholar
  10. Dupuis EM, Whalen JK (2007) Soil properties related to the spatial pattern of microbial biomass and respiration in agroecosystems. Can J Soil Sci 87:479–484Google Scholar
  11. Durán J, Rodríguez A, Fernández-Palacios JM, Gallardo A (2008) Changes in soil N and P availability in a Pinus canariensis fire chronosequence. For Ecol Manage 256:384–387CrossRefGoogle Scholar
  12. Ettema CH, Wardle DA (2002) Spatial soil ecology. Trends Ecol Evol 17:177–183 doi: 10.1016/S0169-5347(02)02496-5 CrossRefGoogle Scholar
  13. FAO (1996) Digital soil map of the world and derived soil properties. Derived from the FAO/UNESCO soil map of the world. FAO, RomeGoogle Scholar
  14. Filella I, Peñuelas J (2003) Indications of hydraulic lift by Pinus halepensis and its effects on the water relations of neighbour shrubs. Biol Plant 47:209–214 doi: 10.1023/B:BIOP.0000022253.08474.fd CrossRefGoogle Scholar
  15. Fisher RF, Binkley D (2000) Ecology and management of forest soils, 3rd edn. Wiley, New YorkGoogle Scholar
  16. Gallardo A (2003) Effect of tree canopy on the spatial distribution of soil nutrients in a Mediterranean Dehesa. Pedobiologia (Jena) 47:117–125 doi: 10.1078/0031-4056-00175 CrossRefGoogle Scholar
  17. Gallardo A, Paramá R (2007) Spatial variability of soil elements in two plant communities of NW Spain. Geoderma 139:199–208 doi: 10.1016/j.geoderma.2007.01.022 CrossRefGoogle Scholar
  18. Gallardo A, Rodríguez-Saucedo JJ, Covelo F, Fernández Alés R (2000) Soil nitrogen heterogeneity in a Dehesa ecosystem. Plant Soil 222:71–82 doi: 10.1023/A:1004725927358 CrossRefGoogle Scholar
  19. Gallardo A, Paramá R, Covelo F (2006) Differences between soil ammonium and nitrate spatial pattern in six plant communities. Simulated effect on plant populations. Plant Soil 279:333–346 doi: 10.1007/s11104-005-8552-7 CrossRefGoogle Scholar
  20. Génova MM, Santana C, Martín E (1999) Longevidad y anillos de crecimiento en el Pino de la Virgen (El Paso, la Palma). Vegueta 4:27–32Google Scholar
  21. Gross KL, Pregitzer KS, Burton AJ (1995) Spatial variation in nitrogen availability in three successional plant communities. J Ecol 83:357–367 doi: 10.2307/2261590 CrossRefGoogle Scholar
  22. Guo D, Mou P, Jones RH, Mitchel RJ (2002) Temporal changes in spatial patterns of soil moisture following disturbance: an experimental approach. J Ecol 90:338–347 doi: 10.1046/j.1365-2745.2001.00667.x CrossRefGoogle Scholar
  23. Hossain AKMA, Khanna PK, Field JB (1993) Acid-peroxide digestion procedure for determining total nitrogen in chloroform-fumigated and non-fumigated soil extracts. Soil Biol Biochem 25:967–969 doi: 10.1016/0038-0717(93)90100-P CrossRefGoogle Scholar
  24. Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New YorkGoogle Scholar
  25. Jackson RB, Caldwell MM (1993) Geostatistical patterns of soil heterogeneity around individual perennial plants. J Ecol 81:683–692 doi: 10.2307/2261666 CrossRefGoogle Scholar
  26. James SE, Pärtel M, Wilson SD, Peltzer DA (2003) Temporal heterogeneity of soil moisture in grassland and forest. J Ecol 91:234–239CrossRefGoogle Scholar
  27. Joergensen RG, Mueller T (1996) The fumigation-extraction method to estimate soil microbial biomass: calibration of the KEN value. Soil Biol Biochem 28:33–37 doi: 10.1016/0038-0717(95)00101-8 CrossRefGoogle Scholar
  28. Jones DL, Willett VB (2006) Experimental evaluation of methods to quantify dissolved organic nitrogen (DON) and dissolved organic carbon (DOC) in soil. Soil Biol Biochem 38:991–999 doi: 10.1016/j.soilbio.2005.08.012 CrossRefGoogle Scholar
  29. Jones DL, Healey JR, Willett VB, Farrar JF, Hodge A (2005) Dissolved organic nitrogen uptake by plants—an important N uptake pathway? Soil Biol Biochem 37:413–423 doi: 10.1016/j.soilbio.2004.08.008 CrossRefGoogle Scholar
  30. Kwon GJ, Lee BA, Nam JM, Kim JG (2007) The relationship of vegetation to environmental factors in Wangsuk stream and Gwarim reservoir in Korea: II. Soil environments. Ecol Res 22:75–86 doi: 10.1007/s11284-006-0188-4 Google Scholar
  31. Lechowicz MJ, Bell G (1991) The ecology and genetics of fitness in forest plants. II. Microspatial heterogeneity of the edaphic environment. J Ecol 79:687–696 doi: 10.2307/2260661 CrossRefGoogle Scholar
  32. Legendre P, Fortin MJ (1989) Spatial pattern and ecological analysis. Vegetatio 80:107–138 doi: 10.1007/BF00048036 CrossRefGoogle Scholar
  33. Nelson DW, Sommers LE (1996). Total carbon, organic carbon and organic matter. In: Soil science society of america and america society of agronomy (eds) Methods of soils analysis. Part 3. Chemical methods. SSAA Books Series n° 5. Madison, USA, pp 961–1009Google Scholar
  34. Pebesma EJ, Wesseling CG (1998) Gstat: a program for geostatistical modelling, prediction and simulation. Comput Geosci 24:17–31 doi: 10.1016/S0098-3004(97)00082-4 CrossRefGoogle Scholar
  35. Quilchano C, Marañón T, Pérez-Ramos IM, Noejovich L, Valladares F, Zavala MA (2008) Patterns and ecological consequences of abiotic heterogeneity in managed cork oak forests of Southern Spain. Ecol Res 23:127–139 doi: 10.1007/s11284-007-0343-6 CrossRefGoogle Scholar
  36. R Development Core Team (2008) R: A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  37. Ribeiro PJ Jr, Diggle PJ (2001) geoR: a package for geostatistical analysis. R-NEWS 1:15–18Google Scholar
  38. Robertson GP (1987) Geostatistics in ecology: interpolating with known variance. Ecology 68:744–748 doi: 10.2307/1938482 CrossRefGoogle Scholar
  39. Robertson GP (1988) Spatial variability in a succesional plant community: patterns of nitrogen availability. Ecology 69:1517–1524 doi: 10.2307/1941649 CrossRefGoogle Scholar
  40. Robertson GP, Gross CL (1994) Assessing the heterogeneity of belowground resources: quantifying pattern and scale. In: Caldwell MM, Pearcy RW (eds) Plant exploitation of environmental heterogeneity. Academic, New York, pp 237–253Google Scholar
  41. Robertson GP, Crum JR, Ellis BG (1993) The spatial variability of soil resources following long-term disturbance. Oecologia 96:451–456 doi: 10.1007/BF00320501 CrossRefGoogle Scholar
  42. Robertson GP, Klingensmith KM, Klug MJ, Paul EA, Crum JR, Ellis BG (1997) Soil resources, microbial activity and primary production across an agricultural ecosystem. Ecol Appl 7:158–170 doi: 10.1890/1051-0761(1997)007[0158:SRMAAP]2.0.CO;2 CrossRefGoogle Scholar
  43. Rodríguez A, Durán J, Gallardo A (2007) Influence of legumes on N cycling in a heathland in northwest Spain. Web Ecol 7:87–93Google Scholar
  44. Rodríguez A, Durán J, Fernández-Palacios JM, Gallardo A (2008) Short-term wildfire effects on the spatial pattern and scale of labile organic-N and inorganic-N and P pools. For Ecol Manage. doi: 10.1016/j.foreco.2008.10.006
  45. Rossi RE, Mulla DJ, Journel AG, Franz EH (1992) Geostatistical tools for modelling and interpreting ecological spatial dependence. Ecol Monogr 62:277–314 doi: 10.2307/2937096 CrossRefGoogle Scholar
  46. Ryel RJ, Caldwell MM (1998) Nutrient acquisition from soils with patchy nutrient distributions as assessed with simulation models. Ecology 79:2735–2744CrossRefGoogle Scholar
  47. Ryel RJ, Caldwell MM, Manwaring JH (1996) Temporal dynamics of soil spatial heterogeneity in sagebrush-wheatgrass steppe during a growing season. Plant Soil 184:299–309 doi: 10.1007/BF00010459 CrossRefGoogle Scholar
  48. Saetre P (1999) Spatial patterns of ground vegetation, soil microbial biomass and activity in a mixed spruce-birch stand. Ecography 22:183–192 doi: 10.1111/j.1600-0587.1999.tb00467.x CrossRefGoogle Scholar
  49. Schlesinger WH (1997) Biogeochemistry: an analysis of global change, 2nd edn. Academic, San Diego, CaliforniaGoogle Scholar
  50. Schlesinger WH, Reynolds JF, Cunningham GL, Huenneke LF, Jarrell WM, Virginia RA, Whitford WG (1990) Biological feedbacks in global desertification. Science 247:1043–1048 doi: 10.1126/science.247.4946.1043 PubMedCrossRefGoogle Scholar
  51. Schlesinger WH, Raikes JA, Hartley AE, Cross AF (1996) On the spatial pattern of soil nutrients in desert ecosystems. Ecology 77:364–374 doi: 10.2307/2265615 CrossRefGoogle Scholar
  52. Schutter ME, Sandeno JM, Dick RP (2001) Seasonal, soil type and alternative management influences on microbial communities of vegetable cropping systems. Biol Fertil Soils 34:397–410 doi: 10.1007/s00374-001-0423-7 CrossRefGoogle Scholar
  53. Sims GK, Ellsworth TR, Mulvaney RL (1995) Microscale determination of inorganic nitrogen in water and soil extracts. Commun Soil Sci Plann 26:303–316 doi: 10.1080/00103629509369298 CrossRefGoogle Scholar
  54. Smeck NE (1985) Phosphorus dynamics in soils and landscape. Geoderma 36:185–199 doi: 10.1016/0016-7061(85)90001-1 CrossRefGoogle Scholar
  55. Tausz M, Trummer W, Wonisch A, Goessler W, Grill D, Jimenez MS, Morales D (2004) A survey of foliar mineral nutrient concentrations of Pinus canariensis at field plots in Tenerife. For Ecol Manage 189:49–55CrossRefGoogle Scholar
  56. Tilman D (1988) Plant strategies and the dynamics and structure of plant communities. Princeton University Press, PrincetonGoogle Scholar
  57. Wang L, Mou PP, Huang J, Wang J (2007) Spatial heterogeneity of soil nitrogen in a subtropical forest in China. Plant Soil 295:137–150 doi: 10.1007/s11104-007-9271-z CrossRefGoogle Scholar
  58. Wattel-Koekkoek EJW, van Genuchten PPL, Buurman P, van Lagen B (2001) Amount and composition of clay-associated soil organic matter in a range of kaolinitic and smectitic soil. Geoderma 99:27–49 doi: 10.1016/S0016-7061(00)00062-8 CrossRefGoogle Scholar
  59. Zinke PJ (1962) The patterns of influence of individual forest trees on soil properties. Ecology 43:130–133 doi: 10.2307/1932049 CrossRefGoogle Scholar
  60. Zhou Z, Sun OJ, Luo Z, Jin H, Chen Q, Han X (2008) Variation in small-scale spatial heterogeneity of soil properties and vegetation with different land use in semiarid grassland ecosystem. Plant Soil 310:103–112 doi: 10.1007/s11104-008-9633-1 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • A. Rodríguez
    • 1
  • J. Durán
    • 1
  • J. M. Fernández-Palacios
    • 2
  • A. Gallardo
    • 1
  1. 1.Department of Physics, Chemical and Natural SystemsPablo de Olavide UniversitySevilleSpain
  2. 2.Department of Parasitology, Ecology and GeneticsLa Laguna UniversityLa LagunaSpain

Personalised recommendations