Empirical prediction models for Vaccinium myrtillus and V. vitis-idaea berry yields in North Karelia, Finland

By M. Ihalainen, K. Salo, T. Pukkala. 2003

46 citations recorded by the source corpus.

Forest berries and the outdoor experiences related to berry collection are important goods and services provided by Finnish forests. Consequently, there is a need for models which facilitate the prediction of the impacts of alternative forest management options on berry yields. Very few such models are available. In particular, empirical models are lacking. Models used in forest management should express the effect of variables altered in forest management such as stand density and mean tree size. This study developed empirical models for bilberry and cowberry yields in North Karelia. The data consisted of 362 measurements of 40 m2 sample plots. The plots were located in clusters. The same plot was measured over 1 to 4 years. Besides berry yield some site and growing stock characteristics of each plot were measured. A random parameter model was used to express the berry yield as a function of site fertility, growing stock characteristics, and random parameters. The random part of the models accounted for the effect of plot, measurement year, and cluster. The fixed predictors of the model for bilberry were stand age and forest site type. Stand basal area, mean tree diameter and forest site type were used to predict cowberry yields. The most significant random parameter was the plot factor. The fixed model part explained only a few per cent of the variation in berry yields. The signs of regression coefficients were logical and the model predictions correlated rather well with the predictions of earlier models.

Subfields: Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/aeb13f4766fc7359936abe94f686b9fd9d17ce20

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. T. Pukkala
2. Rafal Podlaski

In Global and Planetary Change

1. T. Pukkala
2. A. Trasobares
3. M. Palahí
4. Rafal Podlaski
5. E. Lähde
6. O. Laiho

In Nature and Landscape Conservation

1. Elena Peribáñez Blasco
2. T. Pukkala
3. A. Trasobares
4. M. Palahí
5. Rafal Podlaski
6. E. Lähde
7. O. Laiho

Citations in the corpus

• Comparison of beta, Johnson’s SB, Weibull and truncated Weibull functions for modeling the diameter distribution of forest stands in Catalonia (north-east of Spain) (2007, background): “2000), the production of non-wood forest products (see Kangas 1998; Ihalainen et al. 2003) or the maintenance of ecological and recreational functions of the forest are related to forest stand composition and structure (see Pukkala 2002; Palahı́ et al.”