The nutrient cycling model NuCM is one of the most detailed models for simulating processes that influence nutrient cycling in forest ecosystems. A field study was conducted at Tieshanping, a Masson pine (Pinus masson...The nutrient cycling model NuCM is one of the most detailed models for simulating processes that influence nutrient cycling in forest ecosystems. A field study was conducted at Tieshanping, a Masson pine (Pinus massoniana Lamb.) forest site, in Chongqing, China, to monitor the impacts of acidic precipitation on nutrient cycling. NuCM simulations were compared with observed data from the study site. The model produced an approximate fit with the observed data. It simulated the mean annual soil solution concentrations in the two simulation years, whereas it sometimes failed to reproduce seasonal variation. Even though some of the parameters required by model running were measured in the field, some others were still highly uncertain and the uncertainties were analyzed. Some of the uncertain parameters necessary for model running should be measured and calibrated to produce a better fit between modeled results and field data.展开更多
基金the Chinese-Norwegian Cooperation Project Integrated Monitoring Program on Acidification of Chinese Terrestrial Systems (IMPACTS)the Chinese Academy of Forestry (No.CAFYBB200700X)
文摘The nutrient cycling model NuCM is one of the most detailed models for simulating processes that influence nutrient cycling in forest ecosystems. A field study was conducted at Tieshanping, a Masson pine (Pinus massoniana Lamb.) forest site, in Chongqing, China, to monitor the impacts of acidic precipitation on nutrient cycling. NuCM simulations were compared with observed data from the study site. The model produced an approximate fit with the observed data. It simulated the mean annual soil solution concentrations in the two simulation years, whereas it sometimes failed to reproduce seasonal variation. Even though some of the parameters required by model running were measured in the field, some others were still highly uncertain and the uncertainties were analyzed. Some of the uncertain parameters necessary for model running should be measured and calibrated to produce a better fit between modeled results and field data.
