Effects of Altitude and Seasonal Variation on Stem Moisture Content and Radial Distribution in Scots Pine and Oriental Beech

The stem moisture content (MC) of living trees governs log weight, drying behavior, preservative uptake, and the susceptibility of timber to checking and decay, while also reflecting the response of the tree to climate. This study aimed to evaluate monthly variations in the stem MC of scots pine (Pinus sylvestris L.) and oriental beech (Fagus orientalis Lipsky) at two altitudes and examine the relationships between stem MC and environmental factors such as air humidity, temperature, and soil moisture. Stems were sampled monthly over a full annual cycle at two contrasting altitudes in the Andes. The cross-sections were partitioned into radial zones, and the air temperature, relative humidity, and soil moisture were recorded in parallel. Altitude and sampling month significantly affected stem MC for both species. The annual mean reached 57% at high altitudes versus 50% at low altitudes in Scots pine (Pinus sylvestris L.) and 70% versus 58% in oriental beech (Fagus orientalis Lipsky). Stem MC peaked in October-December and February-March, and fell to its annual minimum during summer. Radially, MC in Scots pine (Pinus sylvestris L.) increased from the bark towards the inner sapwood (mean ≈ 85%) and then dropped sharply to ≈ 35% in the heartwood, with the sapwood-heartwood contrast widening at higher altitudes. Oriental beech (Fagus orientalis Lipsky) showed a more gradual gradient (sapwood ≈ 79%, heartwood ≈ 55%), and at lower altitudes, the two zones became virtually indistinguishable in some summer months. Stem MC was positively correlated with soil moisture in both species. Oriental beech (Fagus orientalis Lipsky) additionally showed a positive correlation with relative humidity and a strong negative correlation with air temperature, whereas scots pine (Pinus sylvestris L.) MC was not associated with atmospheric variables. Therefore, altitudinal origin and felling month carry a predictable signal of log moisture, with direct consequences for transport, drying, impregnation, and defect management. January felling emerged as the most favorable window, and the dataset supports fire risk modelling, biomass energy calculations, and drought stress assessments for two ecologically and economically important species.