Evaluating the Community Land Model in a pine stand with shading manipulations and 13 CO 2 labeling
Abstract. Carbon allocation and flow through ecosystems regulates land surface atmosphere CO2 exchange and thus is a key, albeit uncertain, component of mechanistic models. The Partitioning in Trees and Soil (PiTS) experiment model project tracked carbon allocation through a young Pinus taeda stand following pulse labeling with 13CO2 and two levels of shading. The field component of this project provided process oriented data that were used to evaluate terrestrial biosphere model simulations of rapid shifts in carbon allocation and hydrological dynamics under varying environmental conditions. Here we tested the performance of the Community Land Model version 4 (CLM4) in capturing short term carbon and water dynamics in relation to manipulative shading treatments and the timing and magnitude of carbon fluxes through various compartments of the ecosystem. When calibrated with pretreatment observations, CLM4 was capable of closely simulating stand level biomass, transpiration, leaf level photosynthesis, and pre labeling 13C values. Over the 3 week treatment period, CLM4 generally reproduced the impacts of shading on soil moisture changes, relative change in stem carbon, and soil CO2 efflux rate. Transpiration under moderate shading was also simulated well by the model, but even with optimization we were not able to simulate the high levels of transpiration observed in the heavy shading treatment, suggesting that the Ball Berry conductance model is inadequate for these conditions. The calibrated version of CLM4 gave reasonable estimates of label concentration in phloem and in soil surface CO2 after 3 weeks of shade treatment, but it lacks the mechanisms needed to track the labeling pulse through plant tissues on shorter timescales. We developed a conceptual model for photosynthate transport based on the experimental observations, and we discussed conditions under which the hypothesized mechanisms could have an important influence on model behavior in larger scale applications. Implications for future experimental studies are described, some of which are already being implemented in follow on studies.