Approaches to quantifying forest structures

By Arne Pommerening. 2002

519 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/394022604c9f6d116f5bccfea261e8a46b5a4f0e

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In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

A permutation test of spatial randomness: application to nearest neighbour indices in forest stands (2010, background): “For example, from descriptions of spatial stand structure one can identify the suitability of habitats or the population development of wildlife and plant species (Pommerening 2002).”
Remote sensing of structural complexity indices for habitat and species distribution modeling. (2010, background): “Microhabitat datamay bemore compatible with RS when expressed as a structural complexity index (SCI), a composite variable widely used in forest ecology to summarize several vegetation structural measures (e.g.McElhinnyet al., 2005;Neumann&Starlinger, 2001; Pommerening, 2002).”
Evaluating structural indices by reversing forest structural analysis (2006, methodology): “This is not the case with the diameter differentiation (formulae 3 and 4) where a different approach to constructing classes has been chosen (see e.g. Pommerening, 2002).”
Characterization of the structure, dynamics, and productivity of mixed-species stands: review and perspectives (2015, background): “Pretzsch (2002) hypothesized that through the better use of niches by different species in the same stand, there will be no such optimum, and maximum growth can be maintained over a wider range of densities (Fig.”
Continuous Cover Forestry (2012, background): “This allows them to be related to various ecological scales and also, to a certain degree, to account for long-range point interactions (Pommerening 2002).”
Scale-dependent competition at the stand level assessed from crown areas (2008, methodology): “…in forests, and involving methods such as the mark-correlation function, weighted Ripley’s K-function, or spatial autocorrelation (e.g. Penttinen et al., 1992; Capobianco and Renshaw, 1998; Mateu et al., 1998; Wells and Getis, 1999; Pommerening, 2002; Shi and Zhang, 2003; Doležal et al., 2006).”
Relationships between stand growth and structural diversity in spruce-dominated forests in New Brunswick, Canada. (2009, background): “Structural diversity is often defined as one or a combination of spatial distribution, species diversity, and variation in tree dimensions, such as the size and height (Staudhammer and LeMay 2001; Pommerening 2002; McElhinny et al. 2005).”
Biocomplexity and restoration of biodiversity in temperate coniferous forest: inducing spatial heterogeneity with variable‐density thinning (2003, background): “Forestry in Europe has to demonstrate sustainability by providing wildlife habitat (Larson, 2001; Pommerening, 2002; Nordlind and Ostlund, 2003).”
The contribution of structural indices to the modelling of Sitka spruce (Picea sitchensis) and birch (Betula spp.) crowns (2008, background): “Instead, the random selection of crown measurement sample trees excluded buffer strips (Pommerening and Stoyan, 2006) in each plot.”