Select issue
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
1950-1959
1940-1949
1926-1939
Acta Forestalia Fennica
1992-1999
1984-1991
1974-1983
1968-1973
1953-1968
1933-1952
1913-1932
Articles by Trond Eid
Category : Research article
article id 376,
category
Research article
(2005).
Recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway.
Silva Fennica
vol.
39
no.
3
article id 376.
https://doi.org/10.14214/sf.376
Keywords:
regeneration;
national forest inventories;
growth simulators;
probability models;
conditional models;
Norway
Abstract |
View details
|
Full text in PDF |
Author Info
The objective of the present study was to develop recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. The models were developed from permanent sample plots established by the National Forest Inventory, and they will be included in a growth simulator that is part of a large-scale forestry scenario model. The modelling was therefore restricted to independent variables directly or indirectly available from inventories for practical forest management planning. A two-stage modelling approach that suited the stochastic nature of recruitment in boreal forests was used. Models predicting the probability of recruitment were estimated in a first stage, and conditional models for the number of recruits were developed in a second. The probability models as well as the conditional models were biologically realistic and logical. The goodness of fit tests revealed that the probability models fitted the data well, while the coefficients of determination for the conditional models were relatively low. No independent test data were available, but comparisons of predicted and observed number of recruits in different sub-groups of the data revealed few large deviations. The high level of large random errors was probably due to the great variability observed in number of recruits rather than inappropriate specifications of the models. Provided the generally high level of uncertainty connected to analysis performed with large-scale forestry scenario models and the stochastic nature of recruitment, the presented models seem to give satisfactory levels of accuracy.
-
Lexerød,
Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway
E-mail:
nils.lexerod@umb.no
- Eid, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway. E-mail nils.lexerod@umb.no E-mail: te@nn.no
Click this link to register to Silva Fennica.
If you are a registered user, log in to save your selected articles for later access.
Your selected articles
Silva Fennica ·
Finnish Society of Forest Science
