Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 1649-1654 |
| Number of pages | 6 |
| Journal | Ecological Modelling |
| Volume | 221 |
| Issue number | 13-14 |
| Early online date | 3 May 2010 |
| DOIs | |
| Publication status | Published - 10 Jul 2010 |
Fingerprint
Keywords
- angular dispersion
- competition index
- neighbourhood models
- spatial arrangement
Cite this
Improving the effectiveness of angular dispersion in plant neighbourhood models. / Richards, M. L. A.; Aitkenhead, M.; McDonald, A. J. S.
In: Ecological Modelling, Vol. 221, No. 13-14, 10.07.2010, p. 1649-1654.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Improving the effectiveness of angular dispersion in plant neighbourhood models
AU - Richards, M. L. A.
AU - Aitkenhead, M.
AU - McDonald, A. J. S.
PY - 2010/7/10
Y1 - 2010/7/10
N2 - Spatial arrangement can be an important factor affecting competition among plants. We evaluated three ways to improve the effectiveness of angulardispersion (AD) for describing spatial arrangement in plantneighbourhoodmodels. First, we modified Zar's (1974) AD formula by weighting each neighbour by its competitive influence. We calculated this using two different competition indices to derive an AD of competitive influence, rather than of equally weighted plant locations, around a subject plant. Secondly, we constrained the effect of AD on the neighbourhoodmodel using an optimised parameter that defines the minimum value that AD can adopt. Thirdly, we included the direction in which competition is concentrated (the mean azimuth of the weighted AD) in the growth models. These developments were evaluated within a radial growth model of Scots pine and birch growing in semi-natural, spatially heterogeneous forest. Weighted AD resulted in significant improvements in predicted radial growth of target trees over the traditional measure of AD. The optimised parameter that defines the minimum value of AD consistently evolved values significantly higher than zero. This suggests that clumped and dispersed neighbourhoods do not differ in their negative effects on a subject tree as much as expected. The inclusion of directional components of the weighted AD did not improve the accuracy of the growth models. Weighting of the angulardispersion of neighbours improved the performance of local competition models.
AB - Spatial arrangement can be an important factor affecting competition among plants. We evaluated three ways to improve the effectiveness of angulardispersion (AD) for describing spatial arrangement in plantneighbourhoodmodels. First, we modified Zar's (1974) AD formula by weighting each neighbour by its competitive influence. We calculated this using two different competition indices to derive an AD of competitive influence, rather than of equally weighted plant locations, around a subject plant. Secondly, we constrained the effect of AD on the neighbourhoodmodel using an optimised parameter that defines the minimum value that AD can adopt. Thirdly, we included the direction in which competition is concentrated (the mean azimuth of the weighted AD) in the growth models. These developments were evaluated within a radial growth model of Scots pine and birch growing in semi-natural, spatially heterogeneous forest. Weighted AD resulted in significant improvements in predicted radial growth of target trees over the traditional measure of AD. The optimised parameter that defines the minimum value of AD consistently evolved values significantly higher than zero. This suggests that clumped and dispersed neighbourhoods do not differ in their negative effects on a subject tree as much as expected. The inclusion of directional components of the weighted AD did not improve the accuracy of the growth models. Weighting of the angulardispersion of neighbours improved the performance of local competition models.
KW - angular dispersion
KW - competition index
KW - neighbourhood models
KW - spatial arrangement
U2 - 10.1016/j.ecolmodel.2010.03.006
DO - 10.1016/j.ecolmodel.2010.03.006
M3 - Article
VL - 221
SP - 1649
EP - 1654
JO - Ecological Modelling
JF - Ecological Modelling
SN - 0304-3800
IS - 13-14
ER -