Olalla Díaz-Yáñez, Blas Mola-Yudego, José Ramón González-Olabarria. (2017). What variables make a forest stand vulnerable to browsing damage occurrence? Silva Fennica vol. 51 no. 2 article id 1693. https://doi.org/10.14214/sf.1693

Keywords: moose; forest damage; cervid; machine learning; risk modelling; ungulates

Highlights: Stands more vulnerable to browsing damage are young with lower densities and dominated by birch, pine or mixed species; Stand size could play a role on forest susceptibility to browsing occurrence.

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Ungulate browsing results in important damages on the forests, affecting their structure, composition and development. In the present paper, we examine the occurrence of browsing damage in Norwegian forests, using data provided by the National Forest Inventory along several consecutive measurements (entailing the period 1995–2014). A portfolio of variables describing the stand, site and silvicultural treatments are analyzed using classification trees to retrieve combinations related to browsing damage. Our results indicate that the most vulnerable forest stands are young with densities below 1400 trees ha^–1 and dominated by birch, pine or mixed species. In addition, stand diversity and previous treatments (e.g. thinnings) increase the damage occurrence and other variables, like stand size, could play a role on forest susceptibility to browsing occurrence although the latter is based on weaker evidence. The methods and results of our study can be applied to implement management measures aiming at reducing the browsing damages of forests.

Díaz-Yáñez, School of Forest Sciences, University of Eastern Finland, PO Box 111, 80101 Joensuu, Finland http://orcid.org/0000-0003-3829-5759 E-mail: olalla.diaz@gmail.com
Mola-Yudego, Norwegian Institute of Bioenergy Research, P.O. Box, 115, 1431 Ås, Norway; School of Forest Sciences, University of Eastern Finland, PO Box 111, 80101 Joensuu, Finland http://orcid.org/0000-0003-0286-0170 E-mail: blas.mola@uef.fi
González-Olabarria, Forest Sciences Centre of Catalonia (CTFC-CEMFOR), Ctra. de St. Llorenç de Morunys, km 2, 25280 Solsona, Spain http://orcid.org/0000-0002-5040-712X E-mail: jr.gonzalez@ctfc.es

article id 138, category Research article

Santiago Martín-Alcón, José Ramón González-Olabarría, Lluís Coll. (2010). Wind and snow damage in the Pyrenees pine forests: effect of stand attributes and location. Silva Fennica vol. 44 no. 3 article id 138. https://doi.org/10.14214/sf.138

Keywords: models; stand structure; conifers; Pyrenees; snow damages; stability; wind damages

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Wind and snow-induced damage have been analyzed at stand level for three pine forests in the Central-Eastern Pyrenees (Pinus nigra Arn. salzmanii, Pinus sylvestris L. and Pinus uncinata Ram.). Stand-level models have been then developed for the most affected two species, Pinus sylvestris L. and Pinus uncinata Ram., to describe damage severity. The models were based on data from national forest inventory plots. They included variables related to the spatial location and structure of the stands, being validated using a sub-set of the database (25% of the plots randomly selected). Mountain pine forests (Pinus uncinata Ram.) were the most heavily affected by wind and snow disturbances. For both mountain and Scots pine species, topographic exposure and the severity of the local storm regime had an important effect on the degree of damage. Stand’s resistance to wind and snow was found to be dependent on the combined effect of basal area and mean slenderness of the dominant trees. For a given slenderness ratio, damage increased strongly in lower-density stands, particularly in stands with basal areas below 15 m²/ha. Stand structure was particularly important to define the resistance of Scots pine stands, which presented a higher vulnerability to wind and snow under higher degree of even-agedness. The models presented in this study provide empirically-based information that can be used to implement silvicultural practices to minimize the risk of those forests to suffer wind and snow-related damages.

Martín-Alcón, Forest Technology Center of Catalonia, Solsona, Lleida, Spain E-mail: santiago.martin@ctfc.es
González-Olabarría, Forest Technology Center of Catalonia, Solsona, Lleida, Spain E-mail: jrgo@nn.es
Coll, Forest Technology Center of Catalonia, Solsona, Lleida, Spain E-mail: lc@nn.es

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