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Using multivariate analysis of soil fertility as a tool for forest fertilization planning

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Nutrient Cycling in Agroecosystems Aims and scope Submit manuscript

Abstract

The design of fertilization plans to cover large areas is complex, due to the considerable number of soil samples and soil fertility variables that must be taken into account. Classifying forest stands in groups according to their soil fertility (i.e. in nutrient management areas) can be very helpful to this respect and it is considered to be a first step in what has been called precision forestry. For this paper, we explore the capability of multivariate analyses of topsoil data to be used as tools for evaluating and classifying soil fertility. A case study from a teak (Tectona grandis L.f.) plantation in Costa Rica was used to evaluate and illustrate how to use multivariate analysis with these aims. A topsoil (0–20 cm) database with soil test results assembled by Panamerican Woods Ltd. was used. Different multivariate techniques [Principal Component Analysis, Non-metric Multidimensional Scaling (NMDS), Cluster analysis] were performed and compared. Cluster analysis resulted as an appropriate tool for grouping soil samples into soil fertility classes. Therefore, it is considered as a promising tool which would help to design a fertilization program to meet the specific needs of each group of stands with relatively homogeneous soil fertility properties. NMDS is also a suitable complementary tool to graphically explore the similarities within groups and the differences between them. The application of procedures similar to those being reported may help to optimize the design of nutritional and fertilization plans across large forest plantations, by using multivariate analysis to establish fertilization regimes that are appropriate to groups of stands of more homogeneous soil fertility.

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Notes

  1. The teak plantations used as a study case in this work are both owned by the Panamerican Woods Ltd. company (hereafter ‘PAW’).

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Acknowledgments

The authors would like to acknowledge the collaboration of Panamerican Woods Ltd. in regard to providing access to the soil database. The authors also thank Paul Robertson, Adam Collins and the personnel of the Natural Resources Laboratory at CIA (UCR) for their help and comments about English language, manuscript format and for their assistance about the contents of this paper. One of the authors, M. Morales, is an employee of a forest plantation company (Panamerican Woods) but none of the authors show any kind of conflict of interests. The present paper was conducted under the MACOSACEN project, financed by PCI-AECID. The authors also thank to two anonymous reviewers for their comments to the present manuscript.

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Authors and Affiliations

  1. Dpto. Silvopascicultura, E.T.S.I. Montes, Universidad Politécnica de Madrid (UPM), Ciudad Universitaria s/n, 28040, Madrid, Spain

    Jesús Fernández-Moya & Alfonso San Miguel-Ayanz

  2. Centro de Investigaciones Agronómicas (CIA), Universidad de Costa Rica (UCR), San José, Costa Rica

    Jesús Fernández-Moya & Alfredo Alvarado

  3. Panamerican Woods S.A., P.O. Box 7842-1000, San José, Costa Rica

    Manuel Morales

  4. Dpto. Ingeniería y Morfología del Terreno, E.T.S.I. Caminos, Canales y Puertos, Universidad Politécnica de Madrid (UPM), Ciudad Universitaria s/n, 28040, Madrid, Spain

    Miguel Marchamalo-Sacristán

Authors
  1. Jesús Fernández-Moya
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  2. Alfredo Alvarado
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  3. Manuel Morales
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  4. Alfonso San Miguel-Ayanz
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  5. Miguel Marchamalo-Sacristán
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Correspondence to Jesús Fernández-Moya.

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Fernández-Moya, J., Alvarado, A., Morales, M. et al. Using multivariate analysis of soil fertility as a tool for forest fertilization planning. Nutr Cycl Agroecosyst 98, 155–167 (2014). https://doi.org/10.1007/s10705-014-9603-3

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  • DOI: https://doi.org/10.1007/s10705-014-9603-3

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