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iForest - Biogeosciences and Forestry

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Modeling the fine root biomass dispersion using a special influence function

O Wälder (1), K Wälder (2)   

iForest - Biogeosciences and Forestry, Volume 1, Issue 5, Pages 141-144 (2008)
doi: https://doi.org/10.3832/ifor0469-0010141
Published: Nov 25, 2008 - Copyright © 2008 SISEF

Research Articles


This paper presents a successful application of techniques from the adjustment theory for modeling interaction in fine root biomass dispersion. Using special distance and species dependent weightings the influence function for fine root biomass dispersion of two species is estimated. Using the estimated influence functions the fine root biomass is predicted at the locations where the real data was sampled. Goodness of fit of our model is evaluated by comparing sample values and predicted values. However, the results show successful coincidence between sampled and predicted values. Finally, we present an example for the root dispersion in a mixed stand of beeches and spruces in Saxony/Germany.

  Keywords


Forest effects, Fine root biomass, Interaction, Influence function

Authors’ address

(1)
O Wälder
Institute for Cartography, Technical University of Dresden, Mommsenstrasse 13, D-01062 Dresden (Germany)
(2)
K Wälder
Institute for Stochastics, Freiberg University of Mining and Technology, Akademiestrasse 6, D-09596 Freiberg (Germany)

Corresponding author

Citation

Wälder O, Wälder K (2008). Modeling the fine root biomass dispersion using a special influence function. iForest 1: 141-144. - doi: 10.3832/ifor0469-0010141

Paper history

Received: Apr 01, 2008
Accepted: Oct 30, 2008

First online: Nov 25, 2008
Publication Date: Nov 25, 2008
Publication Time: 0.87 months

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Articles citing this article

List of the papers citing this article based on CrossRef Cited-by.

 
(1)
Ammer C, Wagner S (2005)
An approach for modeling the mean fine-root biomass of Norway spruce stands. Trees 19: 145-153.
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Accounting for large-scale factors in the study of understory vegetation using a conditional logistic model. Environmental and Ecological Statistics 14: 149-159.
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Die Reaktion der Feinwurzeln von Fichten (Picea abies [L.]). Karst. auf zunehmende Bodenversauerung. Göttinger Bodenkundliche Berichte 77: 1-126.
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Näther W, Wälder K (2003)
Experimental design and statistical inference for cluster point processes - with applications to the fruit dispersion of anemochorous forest trees. Biometrical Journal 45: 1006-1022.
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Näther W, Wälder K (2006)
Applying fuzzy measures for considering interaction effects in root dispersal models. Fuzzy Sets ans Systems 158: 572-578.
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Okland RH, Rydgren K, Okland T (1999)
Single-tree influence on understorey vegetation in a Norwegian boreal spruce forest. Oikos 87: 488-498.
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Spatial patterns of ground vegetation, soil microbial biomass and activity in a mixed spruce-birch stand. Ecography 22: 183-192.
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Wälder K, Wälder O (2008)
Analysing interaction effects using the mark correlation function. iForest 1: 34-38.
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(11)
Wälder O (2008)
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Strength of tree phytogenic fields in Lichen-Green Moss Pine forests. Russian Journal of Ecology 27: 1-7.
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