Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Tool for Long-Term Forest Stand Projections of Swedish Forests
The analysis of forest management strategies at landscape and regional levels forms a vital part of finding viable directions that will satisfy the many services expected of forests. This article describes the structure and content of a stand simulator, GAYA, which has been adapted to Swedish conditions. The main advantage of the GAYA implementation compared to other resources is that it generates a large number of management programmes within a limited time frame. This is valuable in cases where the management programmes appear as activities in linear programming (LP) problems. Two methods that are engaged in the projections, a climate change response function and a soil carbon model, are designed to complement other methods, offering transparency and computational effectiveness. GAYA is benchmarked against projections from the Heureka system for a large set of National Forest Inventory (NFI) plots. The long-term increment for the entire NFI set is smaller for GAYA compared with Heureka, which can be attributed to different approaches for modelling the establishment of new forests. The carbon pool belonging to living trees shows the same trend when correlated to standing volume. The soil carbon pool of GAYA increases with increased standing volume, while Heureka maintains the same amount over the 100-year projection period.
A Tool for Long-Term Forest Stand Projections of Swedish Forests
The analysis of forest management strategies at landscape and regional levels forms a vital part of finding viable directions that will satisfy the many services expected of forests. This article describes the structure and content of a stand simulator, GAYA, which has been adapted to Swedish conditions. The main advantage of the GAYA implementation compared to other resources is that it generates a large number of management programmes within a limited time frame. This is valuable in cases where the management programmes appear as activities in linear programming (LP) problems. Two methods that are engaged in the projections, a climate change response function and a soil carbon model, are designed to complement other methods, offering transparency and computational effectiveness. GAYA is benchmarked against projections from the Heureka system for a large set of National Forest Inventory (NFI) plots. The long-term increment for the entire NFI set is smaller for GAYA compared with Heureka, which can be attributed to different approaches for modelling the establishment of new forests. The carbon pool belonging to living trees shows the same trend when correlated to standing volume. The soil carbon pool of GAYA increases with increased standing volume, while Heureka maintains the same amount over the 100-year projection period.
A Tool for Long-Term Forest Stand Projections of Swedish Forests
Ljusk Ola Eriksson (Autor:in) / Johan Bergh (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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