Community Ecology

, Volume 10, Issue 1, pp 81–90 | Cite as

A comparison of three indirect methods for estimating understory light at different spatial scales in temperate mixed forests

  • F. Tinya
  • B. Mihók
  • S. Márialigeti
  • Zs. Mag
  • P. ÓdorEmail author


Three indirect light measurement methods were compared in mixed deciduous and coniferous forests with heterogeneous stand structure: tRAYci - a spatially explicit light model calculating percentage of above canopy light (PACL); LAI-2000 Plant Canopy Analyzer measuring diffuse non-interceptance (DIFN); and spherical densiometer estimating canopy openness (CO). Correlations between the different light variables were analyzed at several spatial scales (at 5 × 5, 10 × 10, 15 × 15, 20 × 20 and 30 × 30 m2). Relationships between light variables and the cover of alight flexible plant, blackberry (Rubus fruticosus agg.), as a potentially sensitive response variable for light conditions were also investigated. LAI-2000 (D1FN) and tRAYci (PACL) seemed the most appropriate for the description of the light environment in the investigated stands. DIFN and PACL had stronger correlations with each other and with blackberry cover than CO. Spatial heterogeneity of light (expressed with coefficient of variation) showed much stronger correlations than mean values both between the methods and between light intensity and Rubus cover. The correlation values between the methods increased towards coarser scales (from 5 × 5 to 30 × 30 m2), while the correlation between light intensity and blackberry cover had a maximal response at the scale of 20 ×20 m2 if a lower resolution of light estimation was used, and had also a maximum at smaller scales if the light was calculated for more points per plot by tRAYci. LAI-2000 can be recommended for the comparison of different stands, however, for fine scale description of light conditions of a stand tRAYci seems to be more appropriate.


Light model Light-understory interaction Plant canopy analyzer Spatial steps Spherical densiometer 



Diffuse Non-interceptance


Canopy Openness


Diameter at Breast Height


Leaf Area Density


Percentage of the Above Canopy Light


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  1. Anderson, M.C. 1964. Studies of the woodland light climate I. The photographic computation of light conditions. J. Ecol. 52: 27–41.CrossRefGoogle Scholar
  2. Anderson, M.C. 1966. Stand structure and light penetration II. A theoretical analysis. J. App. Ecol. 3: 41–54.CrossRefGoogle Scholar
  3. Bellow, J.G. and P.K.R. Nair. 2003. Comparing common methods for assessing understory light availability in shaded-perennial agroforestry systems. Agric. Forest Meteor. 114: 197–211.CrossRefGoogle Scholar
  4. Brown, N., S. Jennings, P. Wheeler and J. Nabe-Nielsen. 2000. An improved method for the rapid assessment of forest understorey light environments. J. App. Ecol. 37: 1044–1053.CrossRefGoogle Scholar
  5. Brunner, A. 1998. A light model for spatially explicit forest stand models. Forest Ecol. Manage. 107: 19–46.CrossRefGoogle Scholar
  6. Brunner, A. 2004. tRAYci - A light calculation program for spatially explicit forest stand models. User’s Manual, Danish Centre for Forest, Landscape and Planning, KLV, Hørsholm, Denmark.Google Scholar
  7. Brunner, A., D.B. Manning, J. Huss, D. Rozenbergar, J. Diaci, F. Schousboe and L.W. Hansen 2004. Scenarios of regeneration and stand production of beech under different silvicultural regimes with Regenerator. NAT-MAN Working Report 47.Google Scholar
  8. Canham, C.D. and P.L. Marks. 1985. The response of woody plants to disturbance: patterns of establishment and growth. In: Pickett, S.T.A. and P.S. White (eds.): The Ecology of Natural Disturbance and Patch Dynamics. Academic Press Inc., Orlando. pp. 197–216.Google Scholar
  9. Cescatti, A. 1997a. Modelling the radiative transfer in discontinuous canopies of asymmetric crowns. I. Model structure and algorithms. Ecol. Model. 101: 263–274.CrossRefGoogle Scholar
  10. Cescatti, A. 1997b. Modelling the radiative transfer in discontinuous canopies of asymmetric crowns. II. Model testing and application in a Norway spruce stand. Ecol. Model. 101: 275–284.CrossRefGoogle Scholar
  11. Chazdon, R.L. and C.B. Field. 1987. Photographic estimation of photosynthetically active Radiation - Evaluation of a computerized technique. Oecologia 73: 525–532.CrossRefGoogle Scholar
  12. Coates, K.D., C.D. Canham, M. Beaudet, D.L. Sachs and C. Messier. 2003. Use of a spatially explicit individual-tree model (SOR-TIE/BC) to explore the implications of patchiness in structurally complex forests. Forest Ecol. Manage. 186: 297–310.CrossRefGoogle Scholar
  13. Collins, B.S., K.P. Dunne and S.T.A. Pickett. 1985. Responses of forest herbs to canopy gaps. In: Pickett, S.T.A. (ed.): The Ecology of Natural Disturbance and Patch Dynamics. Academic Press Inc., Orlando. pp. 218–234.Google Scholar
  14. Comeau, P.G. 2000. Measuring Light in the Forest. Extension Note 42, British Columbia Ministry of Forests, Victoria.Google Scholar
  15. Comeau, P., R. Macdonald, R. Bryce and B. Groves. 1998a. Lite: a model for estimating light interception and transmission through forest canopies, users manual and program documentation. Research Branch, Ministry of Forests, Victoria, B.C. Working Paper 35/1998.Google Scholar
  16. Comeau, P.G., F. Gendron and T. Letchford. 1998b. A comparison of several methods for estimating light under a paper birch mixedwood stands. Can. J. Forest Res. 28: 1843–1850.CrossRefGoogle Scholar
  17. Comeau, P.G. and J.L. Heineman. 2003. Predicting understory light microclimate from stand parameters in young paper birch (Betula papyrifera Marsh.) stands. Forest Ecol. Manage. 180: 303–315.CrossRefGoogle Scholar
  18. Constabel, A.J. and V.J. Lieffers. 1996. Seasonal patterns of light transmission through boreal mixedwood canopies. Can. J. Forest Res. 26: 1008–1014.CrossRefGoogle Scholar
  19. Emborg, J. 1998. Undestorey light conditions and regeneration with respect to the structural dynamics of a near-natural temperate deciduous forest in Denmark. Forest Ecol. Manage. 106: 83–95.CrossRefGoogle Scholar
  20. Engelbrecht, B.M.J. and H.M. Herz. 2001. Evaluation of different methods to estimate understorey light conditions in tropical forests. J. Trop. Ecol. 17: 207–224.CrossRefGoogle Scholar
  21. Englund, S.R., J.J. O’Brien and D.B. Clark. 2000. Evaluation of digital and film hemispherical photography and spherical densiometry for measuring forest light environments. Can. J. Forest Res. 30: 1999–2005.CrossRefGoogle Scholar
  22. Ferment, A., N. Picard, S. Gourlet-Fleury and Ch. Baraloto. 2001. A comparison of five indirect methods for characterizing the light environment in a tropical forest. Ann. Forest Sci. 58: 877–891.CrossRefGoogle Scholar
  23. Fotelli, M.N., P. Rudolph, H. Rennenberg and A. Gessler. 2005. Irradiance and temperature affect the competitive interference of blackberry on the physiology of European beech seedlings. New Phytol. 165: 453–462.CrossRefGoogle Scholar
  24. Frazer, G.W., R.A. Fournier, J.A. Trofymow and R.J. Hall. 2001. A comparison of digital and film fisheye photography for analysis of forest canopy structure and gap light transmission. Agric. Forest Meteor. 109: 249–263.CrossRefGoogle Scholar
  25. Gálhidy, L., B. Mihók, A. Hagyó, K. Rajkai and T. Standovár. 2006. Effects of gap size and associated changes in light and soil moisture on the understorey vegetation of a Hungarian beech forest. Plant Ecol. 183: 133–145.CrossRefGoogle Scholar
  26. Gendron, F., C. Messier and P.G. Comeau. 1998. Comparison of various methods for estimating the mean growing season percent photosynthetic photon flux density in forests. Agric. Forest Meteor. 92: 55–70.CrossRefGoogle Scholar
  27. Gersonde, R., J.J. Battles and K.L. O’Hara. 2004. Characterizing the light environment in Sierra Nevada mixed-conifer forests using a spatially explicit light model. Can. J. Forest Res. 34: 1332–1342.CrossRefGoogle Scholar
  28. Hale, S.E. 2003. The effect of thinning intensity on the below-canopy light environment in a Sitka spruce plantation. Forest Ecol. Manage. 179: 341–349.CrossRefGoogle Scholar
  29. Hale, S.E. and C. Edwards. 2002. Comparison of film and digital hemispherical photography across a wide range of canopy densities. Agric. Forest Meteor. 112: 51–56.CrossRefGoogle Scholar
  30. Jelaska, S.D., O. Antonic, M. Bozic, J. Krizan and V. Kusan. 2006. Responses of forest herbs to available understory light measured with hemispherical photographs in silver fir-beech forest in Croatia. Ecol. Model. 194: 209–218.CrossRefGoogle Scholar
  31. Ke, G. and M.J.A. Werger. 1999. Different responses to shade of evergreen and deciduous oak seedlings and the effect of acorn size. Acta Oecol. 20: 579–586.CrossRefGoogle Scholar
  32. Klimes, L., J. Klimesova, R. Hendriks and J. van Groenendael. 1997. Clonal plant architecture: a comparative analysis of form and function. In: de Kroon, H. and J. van Groenendael (eds.), The ecology and evolution of clonal plants. Backhuys, Leiden. pp. 1–29.Google Scholar
  33. Lalic, B. and D.T. Mihailovic. 2004. An empirical relation describing leaf-area density inside the forest for environmental modeling. J. App. Meteor. 43: 641–645.CrossRefGoogle Scholar
  34. Lemmon, P.E. 1956. A spherical densiometer for estimating forest overstory density. Forest Sci. 2: 314–319.Google Scholar
  35. Lemmon, P.E. 1957. A new instrument for measuring forest over-story density. J. Forestry 55: 667–668.Google Scholar
  36. LI-COR Inc. 1990. LAI-2000 Plant Canopy Analyzer. Instruction Manual. LI-COR Inc., Lincoln.Google Scholar
  37. LI-COR Inc. 1991. 1000–90 Communication and utility software for LI-COR Instruments. LI-COR Inc., Lincoln.Google Scholar
  38. LI-COR Inc. 1992. 2000–90 Support software for the LAI-2000 Plant Canopy Analyzer. LI-COR Inc., Lincoln.Google Scholar
  39. MacFarlane, D.W., E.J. Green, A. Brunner and R.L. Amateis. 2003. Modeling loblolly pine canopy dynamics for a light capture model. Forest Ecol. Manage. 173: 145–168.CrossRefGoogle Scholar
  40. Machado, J.L. and P.B. Reich. 1999. Evaluation of several measures of canopy openness as predictors of photosynthetic photon flux density in deeply shaded conifer-dominated forest understory. Can. J. Forest Res. 29: 1438–1444.CrossRefGoogle Scholar
  41. Marosi, S. and S. Somogyi (eds.) 1990. Magyarország kistájainak katasztere. (Cadastre of Hungarian regions.) MTA Földrajztudományi Kutató Intézet, Budapest.Google Scholar
  42. Martens, S.N., D.D. Breshears and C.W. Meyer. 2000. Spatial distributions of understory light along the grassland/forest continuum: effects of cover, height, and spatial pattern of tree canopies. Ecol. Model. 126: 79–93.CrossRefGoogle Scholar
  43. Matthews, J.D. 1991. Silvicultural Systems. Calderon Press, Oxford.Google Scholar
  44. Messier, C. and P. Puttonen. 1995. Spatial and temporal variation in the light environment of developing Scots pine stands - the basis for a quick and efficient method of characterizing light. Can. J. Forest Res. 25:343–354.CrossRefGoogle Scholar
  45. Messier, C. and S. Parent. 1997. Reply - The effects of direct-beam light on overcast day estimates of light availability: On the accuracy of the instantaneous one-point overcast-sky conditions method to estimate mean daily%PPFD under heterogeneous overstory canopy conditions. Can. J. Forest Res. 27: 274–275.CrossRefGoogle Scholar
  46. Messier, C., S. Parent and Y. Bergeron. 1998. Effects of overstory and understory vegetation on the understory light environment in mixed boreal forests. J. Veg. Sci. 9: 511–520.CrossRefGoogle Scholar
  47. Mihók, B. and T. Standovár. 2005. Fénybecslési módszerek összehasonlító vizsgálata az Ipoly Erdő Rt. Királyréti Erdészete által bükkös állományokban létesített mesterséges lékekben. (Comparison of light estimating methods in artificial gaps of beech forest made by the Ipoly Erdő Rt., Forestry of Királyrét.) Working report, Királyrét, Hungary.Google Scholar
  48. Mihók, B., A. Hagyó, T. Standovár, L. Gálhidy and J. Ruff. 2007. Figyeljük a fény játékát - Milyen módszert használjunk erdei állományokban kialakuló lékek fényviszonyainak jellemzésére? (What is the appropriate method to describe the light conditions of forest gaps?) Erdészeti Lapok 142: 156–159.Google Scholar
  49. Mizunaga, H. 2000. Prediction of PPFD variance at forest floor in a thinned Japanese cypress plantation. Forest Ecol. Manage. 126: 309–319.CrossRefGoogle Scholar
  50. Mountford, E.P., P.S. Savill and D.P. Bebber. 2006. Patterns of regeneration and ground vegetation associated with canopy gaps in a managed beechwood in southern England. Forestry 79:389–408.CrossRefGoogle Scholar
  51. Parent, S. and C. Messier. 1996. A simple and efficient method to estimate microsite light availability under a forest canopy. Can. J. Forest Res. 26: 151–154.CrossRefGoogle Scholar
  52. Pinno, B.D., V.J. Lieffers and K.J. Stadt. 2001. Measuring and modelling the crown and light transmission characteristics of juvenile aspen. Can. J. Forest Res. 31: 1930–1939.CrossRefGoogle Scholar
  53. Rhoads, A.G., S.P. Hamburg, T.J. Fahey, T.G. Siccama and R. Kobe. 2004. Comparing direct and indirect methods of assessing canopy structure in a northern hardwood forest. Can. J. Forest Res. 34: 584–591.CrossRefGoogle Scholar
  54. Roxburgh, J.R. and D. Kelly. 1995. Uses and limitations of hemispherical photography for estimating forest light environments. New Zealand J. Ecol. 19: 213–217.Google Scholar
  55. Silbernagel, J. and M. Moeur. 2001. Modeling canopy openness and understory gap patterns based on image analysis and mapped tree data. Forest Ecol. Manage. 149: 217–233.CrossRefGoogle Scholar
  56. SPSS Inc. 2005. SPSS 14.0 for Windows. Release 14.0.0. SPSS Inc.Google Scholar
  57. Stadt, K.J., S.M. Landhausser and J.D. Stewart. 1997. Comment -The effects of direct-beam light on overcast day estimates of light availability. Can. J. Forest Res. 27: 272–274.CrossRefGoogle Scholar
  58. Stadt, K.J. and V.J. Lieffers. 2000. MIXLIGHT: a flexible light transmission model for mixed-species forest stands. Agric. Forest Meteor. 102: 235–252.CrossRefGoogle Scholar
  59. Tímár, G., P. Ódor and L. Bodonczi. 2002. Az Őrségi Tájvédelmi Körzet erdeinek jellemzése. (The characteristics of forest vegetation of the Őrség Landscape Protected Area.) Kanitzia 10: 109–136.Google Scholar
  60. Tinya, F., S. Márialigeti, I. Király, B. Németh, P. Ódor. 2009. The effect of light conditions on herbs, bryophytes and seedlings of temperate mixed forests in Őrség, Western Hungary. Plant Ecol. DOI 10.1007/s11258-008-9566-zGoogle Scholar
  61. Tutin, T.G., V.H. Heywood, N.A. Burges, D.M. Moore, D.H. Valentine, S.M. Walters and D.A. Webb. 1964–1993. Flora Europea. Cambridge University Press, Cambridge.Google Scholar
  62. Valladares, F. and B. Guzman. 2006. Canopy structure and spatial heterogeneity of understory light in an abandoned Holm oak woodland. Ann. Forest Sci. 63: 749–761.CrossRefGoogle Scholar
  63. Welles, J.M. 1990. Some indirect methods of estimating canopy structure. Remote Sensing Reviews 5: 31–43.CrossRefGoogle Scholar
  64. Welles, J.M. and J.M. Norman. 1991. Instrument for indirect measurement of canopy architecture. Agronomy J. 83: 818–825.CrossRefGoogle Scholar
  65. West, D.C., H.H. Shugart andD.B. Botkin. 1981. Forest Succession. Concepts and application. Springer Verlag, New York.CrossRefGoogle Scholar
  66. Whigham, D.F. 2004. Ecology of woodland herbs in temperate deciduous forests. Ann. Rev. Ecol. Evol. Syst. 35: 583–621.CrossRefGoogle Scholar
  67. Zar, J.H. 1999. Biostatistical Analysis. Prentice Hall, New Jersey.Google Scholar

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© Akadémiai Kiadó, Budapest 2008

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • F. Tinya
    • 1
    • 2
  • B. Mihók
    • 1
  • S. Márialigeti
    • 1
  • Zs. Mag
    • 1
  • P. Ódor
    • 1
    Email author
  1. 1.Department of Plant Taxonomy and EcologyLoránd Eötvös UniversityBudapestHungary
  2. 2.Department of Plant PathologyCorvinus University of BudapestBudapestHungary

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