Precision forestry allows decision-making on tree level or pixel level, as compared to stand-level data. However, little is known about the importance of precision in thinning decisions and its long-term effects on within-stand variation, stand economy and growth. In this study, silviculture was optimized for Net Present Value (NPV) in 20 conifer-dominated forest stands in hemi-boreal southern Sweden. The precision-thinning approach, Precision Thinning (PT), is compared with a stand-level approach, Stand Level Thinning (SLT) that is optimized for the same criteria but based on stand-level data. The results suggest no substantial long-term benefit or drawback in implementing thinning decisions based on pixel-level data as compared to stand-level data when optimizing stand economy. The result variables NPV and Mean annual increment of living stem volume (MAI(net)) were not higher for PT than for SLT. The within-stand variation in basal area (m(2)/ha(-1)) was lower at the end of the rotation compared to the start of the simulation for both SLT and PT. At the end of the rotation, SLT had higher variation in basal area compared to PT. However, pixel-level information enables adapting the silviculture to the within-stand variation which may favour other forest management goals than strictly financial goals.
