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A general method for the classification of forest stands using species composition and vertical and horizontal structure

  • Miquel De CáceresEmail author
  • Santiago Martín-Alcón
  • Jose Ramón González-Olabarria
  • Lluís Coll
Research Paper

Abstract

Key message

We present a novel approach to define pure- and mixed-forest typologies from the comparison of pairs of forest plots in terms of species identity, diameter, and height of their trees.

Context

Forest typologies are useful for many purposes, including forest mapping, assessing habitat quality, studying forest dynamics, or defining sustainable management strategies. Quantitative typologies meant for forestry applications normally focus on horizontal and vertical structure of forest plots as main classification criteria, with species composition often playing a secondary role. The selection of relevant variables is often idiosyncratic and influenced by a priori expectations of the forest types to be distinguished.

Aims

We present a general framework to define forest typologies where the dissimilarity between forest stands is assessed using coefficients that integrate the information of species composition with the univariate distribution of tree diameters or heights or the bivariate distribution of tree diameters and heights.

Methods

We illustrate our proposal with the classification of forest inventory plots in Catalonia (NE Spain), comparing the results obtained using the bivariate distribution of diameters and heights to those obtained using either tree heights or tree diameters only.

Results

The number of subtypes obtained using the tree diameter distribution for the calculation of dissimilarity was often the same as those obtained from the tree height distribution or to those using the bivariate distribution. However, classifications obtained using the three approaches were often different in terms of forest plot membership.

Conclusion

The proposed classification framework is particularly suited to define forest typologies from forest inventory data and allows taking advantage of the bivariate distribution of diameters and heights if both variables are measured. It can provide support to the development of typologies in situations where fine-scale variability of topographic, climatic, and legacy management factors leads to fine-scale variation in forest structure and composition, including uneven-aged and mixed stands.

Keywords

Dissimilarity coefficients Forest plot Forest typology Mixed forests Stand structure 

Notes

Acknowledgements

The authors would like to thank Mario Beltrán (CTFC) for useful discussions around the method and its potential applications.

Funding

The study was supported by projects 979S/2013 (Autonomous Agency of National Parks, Spanish Ministry of Agriculture Food and Environment) and a Spanish “Ramon y Cajal” fellowship to M.D.C (RYC-2012-11109).

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interest.

Supplementary material

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Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Forest Science and Technology Center of Catalonia (CTFC)SolsonaSpain
  2. 2.Centre for Ecological Research and Forestry Applications (CREAF)Cerdanyola del VallesSpain
  3. 3.Agresta S. Coop.MadridSpain
  4. 4.Department of Agriculture and Forest Engineering (EAGROF)University of LleidaLleidaSpain

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