Analysis and modeling of spatial stand structures. Methodological considerations based on mixed beech-larch stands in Lower Saxony

Analysis and modeling of spatial stand structures. Methodological considerations based on mixed... The first part of this paper highlights spatial stand structure as the central stand characteristic and introduces methods of pattern identification. This involves two nearest-neighbour methods for the identification of stand structures, i.e., the aggregation index R by Clark and Evans (Clark, Ph.J. and Evans, F.C., 1954. Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology 35 (4) 445–453.) for univariate patterns and the segregation index S by Pielou (Pielou, E.C., 1977. Mathematical Ecology. Wiley.) for bivariate patterns. Both were used to describe the structure of 53 experimental plots of mixed beech-larch stands in Lower Saxony which provided the data base for this investigation. The second part of the study deals with the development of the STRUGEN stand structure generator, designed for the modeling and reproduction of spatial stand structures. To generate stand structures, a two-dimensional homogeneous Poisson process is used as well as a set of two-dimensional distribution functions which determine mixture type and intermingling intensity of main and associated tree species. Moreover, a distance function secures minimum distances between competing neighbouring trees. Consequently, the produced pattern is the result of a combination of an inhomogeneous Poisson process (for generating mixture units) and a hard-core process (for securing minimum distances between neighbours). The STRUGEN generator was designed and successfully used for the investigation of 53 mixed beech-larch stands. It provides initial values and stand structures for distance-dependent single-tree models from estimated qualitative stand characteristics. STRUGEN is a useful tool and allows initial, pragmatic steps towards fully utilising available qualitative and quantitative information to diagnose the state of a forest and to predict its growth. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Forest Ecology and Management Elsevier

Analysis and modeling of spatial stand structures. Methodological considerations based on mixed beech-larch stands in Lower Saxony

Forest Ecology and Management, Volume 97 (3) – Oct 9, 1997

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Publisher
Elsevier
Copyright
Copyright © 1997 Elsevier Ltd
ISSN
0378-1127
eISSN
1872-7042
DOI
10.1016/S0378-1127(97)00069-8
Publisher site
See Article on Publisher Site

Abstract

The first part of this paper highlights spatial stand structure as the central stand characteristic and introduces methods of pattern identification. This involves two nearest-neighbour methods for the identification of stand structures, i.e., the aggregation index R by Clark and Evans (Clark, Ph.J. and Evans, F.C., 1954. Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology 35 (4) 445–453.) for univariate patterns and the segregation index S by Pielou (Pielou, E.C., 1977. Mathematical Ecology. Wiley.) for bivariate patterns. Both were used to describe the structure of 53 experimental plots of mixed beech-larch stands in Lower Saxony which provided the data base for this investigation. The second part of the study deals with the development of the STRUGEN stand structure generator, designed for the modeling and reproduction of spatial stand structures. To generate stand structures, a two-dimensional homogeneous Poisson process is used as well as a set of two-dimensional distribution functions which determine mixture type and intermingling intensity of main and associated tree species. Moreover, a distance function secures minimum distances between competing neighbouring trees. Consequently, the produced pattern is the result of a combination of an inhomogeneous Poisson process (for generating mixture units) and a hard-core process (for securing minimum distances between neighbours). The STRUGEN generator was designed and successfully used for the investigation of 53 mixed beech-larch stands. It provides initial values and stand structures for distance-dependent single-tree models from estimated qualitative stand characteristics. STRUGEN is a useful tool and allows initial, pragmatic steps towards fully utilising available qualitative and quantitative information to diagnose the state of a forest and to predict its growth.

Journal

Forest Ecology and ManagementElsevier

Published: Oct 9, 1997

References

  • Statistical analysis of spatial point processes: A soft-core model and cross-correlations of marks
    Stoyan, D.

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