TY - JOUR

T1 - Spatial relationships between tree species and gap characteristics in broad-leaved deciduous woodland.

AU - Koukoulas, S.

AU - Blackburn, G.A.

PY - 2005/10

Y1 - 2005/10

N2 - Questions: 1. What are the spatial patterns of all trees, individual tree species, trees within particular height classes, all gaps and gaps with specific properties across the study site in broad-leaved deciduous forest at a range of scales? 2. Are patterns of the above features spatially associated? 3. Are these patterns indicative of gap creation mechanisms and phases of regeneration? Location: Frame Wood, New Forest, UK. Methods: Ripley�s K-function analysis was applied to spatial information derived from airborne remotely sensed imagery to characterize the patterns of trees and gaps and to test for spatial interactions between these patterns. The patterns of trees and gaps with specific physical and spatial properties were analysed. Results: The pattern of all tree species combined was random for most scales; Quercus robur followed the same random pattern, while Fagus sylvatica and Betula pendula were clustered over most spatial scales. Large gaps (> 250 m2) and larger trees (> 17.5 m) were randomly distributed, while smaller gaps and smaller trees were clustered. Significant spatial relationships were demonstrated between the patterns of different tree species and between trees within different size classes, as well as between the patterns of trees and gaps with specific properties. Conclusions: Small gap patterns and field evidence indicated that progressive gap enlargement is the most likely creation mechanism for large gaps (> 250 m2). Clustered patterns of younger individuals were indicative of patches of past regeneration. As a complement to field-based data, data derived from remotely sensed imagery provides spatially comprehensive information with which to further investigate woodland stand/community processes and gap dynamics.

AB - Questions: 1. What are the spatial patterns of all trees, individual tree species, trees within particular height classes, all gaps and gaps with specific properties across the study site in broad-leaved deciduous forest at a range of scales? 2. Are patterns of the above features spatially associated? 3. Are these patterns indicative of gap creation mechanisms and phases of regeneration? Location: Frame Wood, New Forest, UK. Methods: Ripley�s K-function analysis was applied to spatial information derived from airborne remotely sensed imagery to characterize the patterns of trees and gaps and to test for spatial interactions between these patterns. The patterns of trees and gaps with specific physical and spatial properties were analysed. Results: The pattern of all tree species combined was random for most scales; Quercus robur followed the same random pattern, while Fagus sylvatica and Betula pendula were clustered over most spatial scales. Large gaps (> 250 m2) and larger trees (> 17.5 m) were randomly distributed, while smaller gaps and smaller trees were clustered. Significant spatial relationships were demonstrated between the patterns of different tree species and between trees within different size classes, as well as between the patterns of trees and gaps with specific properties. Conclusions: Small gap patterns and field evidence indicated that progressive gap enlargement is the most likely creation mechanism for large gaps (> 250 m2). Clustered patterns of younger individuals were indicative of patches of past regeneration. As a complement to field-based data, data derived from remotely sensed imagery provides spatially comprehensive information with which to further investigate woodland stand/community processes and gap dynamics.

KW - Frame Wood

KW - Gap-tree spatial relationship

KW - Forest spatial structure

KW - New Forest

KW - Remote sensing

KW - Ripley�s Kfunction

KW - Spatial point pattern.

M3 - Journal article

VL - 16

SP - 587

EP - 596

JO - Journal of Vegetation Science

JF - Journal of Vegetation Science

SN - 1100-9233

IS - 5

ER -