Evaluating Variables’ Influence on Forwarder Performance and Fuel Efficiency in Mountain Salvage Logging Using an Automatic Work-Element Detection Method

Extreme climate events are increasingly damaging forests, particularly in Europe’s Alps. These disturbances lead to more damaged timber, necessitating rapid salvage operations to preserve timber value and protect ecosystems. However, salvage logging, though essential, raises concerns about its environmental impact, especially on soil conservation and forest regeneration. To mitigate these effects, best practices such as leaving logging residues and avoiding wet soils are recommended. Nevertheless, fuel efficiency remains a critical concern. This study focuses on addressing gaps in understanding forwarder productivity in salvage logging, considering factors such as assortment number, extraction distance, and payload. Utilizing Automatic Work-Element Detection (AWED) for data collection, this study enhances fuel efficiency analysis. Findings show that the average cycle time was 27.4 min, with 4.9 L of fuel consumed per cycle. Each cycle covered 241.3 m, extracting 11.7 m3 of timber, yielding a productivity rate of 31.6 m3 per machine hour and a fuel efficiency of 0.4 L per m3 and per 100 m. Traveling was the most time- and fuel-intensive task. Assortment type significantly impacted loading time and fuel consumption, with short sawlogs requiring fewer crane cycles. Key factors influencing productivity and fuel efficiency were average log volume, distance, payload, and slope.