Articles
Mapping of lingonberry (Vaccinium vitis-idaea L.) cover and yields in Norway
Article number
1440_52
Pages
377 – 382
Language
English
Abstract
The year-to-year variation in the availability of lingonberries (Vaccinium vitis-idaea L.) is a challenge for commercial exploitation.
There is also a need to identify the best locations for lingonberry harvesting.
Here, we present research that utilized field observations from the Norwegian National Forest Inventory to model and map the association between lingonberry cover and stand characteristics.
Additionally, a set of permanent sampling plots were established for annual recording of berry yields in different Norwegian regions, representing variations in slope and forest characteristics.
Ultimately, the recorded information on yield from the temporary sample plots were combined with predictions from the cover model, as well as data from remote sensing and climatic data from nearby weather stations (for locations see Figure 1a) to derive: 1) a model for lingonberry yield, and 2) and a yield map covering all forest land in Norway.
Variables included in the final berry yield model are main tree species, soil parent material, mean temperature June-August, stand basal area, latitude, slope and distance to coastline (Miina et al., 2024).
There is also a need to identify the best locations for lingonberry harvesting.
Here, we present research that utilized field observations from the Norwegian National Forest Inventory to model and map the association between lingonberry cover and stand characteristics.
Additionally, a set of permanent sampling plots were established for annual recording of berry yields in different Norwegian regions, representing variations in slope and forest characteristics.
Ultimately, the recorded information on yield from the temporary sample plots were combined with predictions from the cover model, as well as data from remote sensing and climatic data from nearby weather stations (for locations see Figure 1a) to derive: 1) a model for lingonberry yield, and 2) and a yield map covering all forest land in Norway.
Variables included in the final berry yield model are main tree species, soil parent material, mean temperature June-August, stand basal area, latitude, slope and distance to coastline (Miina et al., 2024).
Publication
Authors
I. Martinussen, M. Hauglin, A. Granhus, A.L. Hykkerud, J. Miina
Keywords
cover maps, generalized linear mixed model, ground vegetation, national forest inventory data, yield predictions
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