Eivind Meen 
,
Anders Nielsen,
Mikael Ohlson
Forest stand modelling as a tool to predict performance of the understory herb Cornus suecica
Meen E., Nielsen A., Ohlson M. (2012). Forest stand modelling as a tool to predict performance of the understory herb Cornus suecica. Silva Fennica vol. 46 no. 4 article id 906. https://doi.org/10.14214/sf.906
Abstract
Forest simulation models have been widely used to predict future stand structure. Generally these models do not include the understory vegetation and its response on stand structure change or other environmental factors. Previous simulation studies have shown that stand structure related variables, e.g. basal area, can explain diversity of the forest floor vegetation in boreal forests. We hypothesise that such variables also can be used to explain the performance of understory species and we conceptualise how plant ecology and forest modelling can be combined to predict the performance of understory plants in Norwegian boreal forests. We predict the performance of an understory plant species (Cornus suecica) over time using simulated values of forest variables as input to models expressing the relationship between forest environment variables and plant performance variables (viz. plant height, plant dry weight, number of flowers, number of branches and number of leaves). We also present relationships between plant performance and explanatory variables commonly used in basic ecological research, variables that currently not are readily compatible with forest simulators (e.g. soil chemical variables).We found basal area of canopy trees being the most important explanatory variable explaining C. suecica performance. The performance variable dry weight was predicted by one single model whereas the other performance variables were best predicted by model averaging. Forest simulations for 150 years showed values of plant performance of C. suecica to be reduced during forest succession.
Keywords
canopy layer;
field layer;
stand structure dynamics;
forest simulator;
composite models;
Akaike’s information criterion
-
Meen,
Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway
E-mail
eivind.meen@umb.no
- Nielsen, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail an@nn.no
- Ohlson, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail mo@nn.no
Received 27 February 2012 Accepted 10 July 2012 Published 31 December 2012
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