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Fine roots play a key role in carbon, nutrient, and water biogeochemical cycles in forest ecosystems. However, inter-annual dynamics of fine root production, mortality, and turnover on the basis of long-term measurement have been less studied. Here, field scanning rhizotrons were employed for tracking fine root by branch order over a 6years period in a larch plantation. For total fine roots, from the first- to the fifth-order roots, annual root length production, length mortality, standing crops, and turnover rate varied up to 3.4, 2.3, 1.5, and 2.3-folds during the study period, respectively. The inter-annual variability of those roots indices in the first-order and the second-order roots were greater than that of the higher order (third- to fifth-order) roots. The turnover rate was markedly larger for the first-order roots than for the higher order roots, showing the greatest variability up to 20times. Seasonal dynamics of root length production followed a general concentrated pattern with peak typically occurring in June or July, whereas root length mortality followed a general bimodal mortality pattern with the dominant peak in May and the secondary peak in August or October. Furthermore, the seasonal patterns of root length production and mortality were similar across years, especially for the first-order and the second-order roots. These results from long-term observation were beneficial for reducing uncertainty of characterizing fine root demography in consideration of large variation among years. Our findings highlight it is important for better understanding of fine root dynamics and determining root demography through distinguishing observation years and root branch orders.

Forest gap models are important tools for assessing the impact of global climate change on forest dynamics of tree species composition and size structure. In this study, the FAREAST gap model was used to examine the response of forest dynamics on Gongga Mountain, which is located on the southeastern fringe of the Tibetan Plateau, under three climate change scenarios. The simulated results showed that the climax community of the deglaciation slash would be mixed species of Picea brachytyla, Tsuga chinensis, and Pinus densata under climate change scenarios, as opposed to the pure Abies fabri forest under the current climate. Climate change also drove replacement of Populus purdomiis by Betula utilis, which became the most abundant pioneer tree species on the deglaciation slash. Under scenarios of climate change, three responses of the four typical forests distributed between 2200 and 3580 m above sea level are observed, such as dieback of today’s forest at 2200 and 3150 m, gradual change of the species composition at 2780 m, and afforestation at 3580 m. It is worth noting that the scenarios of climatic change are of inherent uncertainty, in the same way as the formulation of the ecological factors used in the models. It is suggested that simulations not be interpreted as predictions of the future development of the forest, but as a means of assessing their sensitivity to climate change. It is concluded that mountainous forests are quite sensitive to climate change.