LAUSR

Abstract Deadwood decomposition plays a crucial role in global carbon and nutrient cycles. Factors controlling deadwood decomposition at local scales could also have strong effects at broader scales. We tested how trait variation within stems (i.e. tissue types) and forest habitat heterogeneity (i.e. location within forest) together influence the deadwood decay trajectory and decay rate. We conducted an in situ decomposition experiment of Abies faxoniana logs in an alpine forest on the eastern Qinghai-Tibetan Plateau, decomposing logs from a series of decay classes I-III (on a 5-class scale) for five years on the forest floor in canopy gap, gap edge and under closed canopy (each sized 25 ± 3 × 25 ± 3 m). We found strong differences in density and chemical composition between tissue types at least across decay classes I-III, which revealed the distinct contribution of each tissue type to carbon and nutrient cycling. There were remarkable interactions of tissue types and locations within forest. We found bark always decomposed faster than wood, while heartwood can decompose faster than sapwood in canopy edge and canopy gap. Locations within forest influenced the best fit decay model and decay rate of bark and sapwood in the same way, while it had no corresponding effects for heartwood decay dynamics. The largest difference in T0.25 and T0.4 (time to 25% and 40% mass loss) between locations were 1.52 and 3.21 (bark), 19.41 and 37.61 (wood overall), 31.82 and 60.15 (sapwood), and 12.86 and 22.84 (heartwood), respectively. We also found that pH was significantly negatively related with sapwood and heartwood mass loss, demonstrating that pH can potentially be applied to evaluate sapwood and heartwood mass loss when density correction is difficult to achieve at least at early to mid-decay stages. However, whether pH is a powerful predictor of decomposition trajectory across more species and biomes remains to be tested. We strongly recommend that further model predictions of coarse log decay include radial positions within stem and locations within forest as factors to increase the reliability of carbon budget estimates.