Kari T. Korhonen, Matti Maltamo. (1991). The evaluation of forest inventory designs using correlation functions. Silva Fennica vol. 25 no. 2 article id 5444. https://doi.org/10.14214/sf.a15598

Keywords: forest inventories; correlation analysis; correlograms; sampling error; spatial correlation,

Abstract | View details | Full text in PDF | Author Info

Correlation functions of the mean volume, land use class and soil class were estimated using the data of the Finnish National Forest Inventory. Estimated functions were used for approximating the standard error of e.g. the mean volume of a cluster of plots. Standard error estimates can be used for comparing different inventory designs.

The PDF includes an abstract in Finnish.

Korhonen, E-mail: kk@mm.unknown
Maltamo, E-mail: mm@mm.unknown

Category : Research article

article id 262, category Research article

Julian C. Fox, Huiquan Bi, Peter K. Ades. (2008). Modelling spatial dependence in an irregular natural forest. Silva Fennica vol. 42 no. 1 article id 262. https://doi.org/10.14214/sf.262

Keywords: correlogram; Eucalypt; growth modelling; moving average autoregression; Moran’s I; spatial autocorrelation

Abstract | View details | Full text in PDF | Author Info

The spatial dependence present in a natural stand of Eucalyptus pilularis (Smith) dominated mixed species forest was characterised and modelled. Two wildfires imposed a significant spatial dependence on the post disturbance stand. It was hypothesised that spatial variation in the intensity of the wildfires generated the observed structures. The influence of patch formation, micro-site variability and competitive influences were also noted in the residuals of a distance-dependent individual-tree growth model. A methodology capable of modelling these complicated patterns of observed dependence was sought, and candidates included the spatial interaction, direct specification and Papadakis methods. The spatial interaction method with a moving average autoregression was identified as the most appropriate method for explicitly modelling spatial dependence. Both the direct specification and Papadakis methods failed to capture the influence of competition. This study highlights the possibility that stand disturbances such as natural and artificial fires, insect and fungal attacks, and wind and snow damage are capable of imposing powerful spatial dependencies on the post disturbance stand. These dependencies need to be considered if individual tree growth models are to provide valid predictions in disturbed stands.

Fox, School of Forest and Ecosystem Science, University of Melbourne, Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121 Australia E-mail: jcfox@unimelb.edu.au
Bi, Forest Resources Research, New South Wales Department of Primary Industries, PO Box 100, Beecroft, NSW 2119 Australia E-mail: hb@nn.au
Ades, School of Forest and Ecosystem Science, University of Melbourne, Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121 Australia E-mail: pka@nn.au

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