Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6543357 | Forest Ecology and Management | 2014 | 10 Pages |
Abstract
The aim of this study was to predict the effect of forest management intensity on mushroom productivity at the landscape level by means of a model-based scenario analysis. The study area was Catalonia region, north-eastern Iberian Peninsula. Mushroom yield models were developed for the most common pine-dominated forest ecosystems. The models accounted for the effect of site and stand structure on mushroom occurrence and yield. The mushroom yield models and individual-tree growth models were used in continuous cover forestry simulation and optimization to assess the impact of alternative regional forest management intensity scenarios on landscape-level mushroom productivity. The baseline scenario was defined as the estimated current forest harvesting intensity in Catalonia (i.e., 25% of annual forest growth). The time frame was 30 yr. The current average productivity of valuable mushrooms is 14 kg haâ1 yrâ1 (4600 tonnes yrâ1). Under the current forest management intensity, a loss of 220 tonnes yrâ1 (5%) in mushroom production at the regional level can be expected. In the absence of forest management, the loss in productivity can attain almost 500 tonnes yrâ1 (11%). With forest harvesting intensity similar to the average in Europe, an increase of 100 tonnes yrâ1 (2%) in mushroom production could be expected. If forest harvesting was equal to 100% of annual forest growth, an increase of 262 tonnes yrâ1 (6%) could be expected. Mushroom productivity increases with increasing forest management intensity. Low forest management intensities may result in a progressive reduction in mushroom yield. Intermediate management intensities would maintain the current mushroom productivity. Sustained yield harvesting policy would contribute to increasing mushroom productivity in continuous cover forestry.
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Authors
Sergio de-Miguel, José Antonio Bonet, Timo Pukkala, Juan MartÃnez de Aragón,