Motivated by the rapid increase in atmospheric CO2 due to human activities since the Industrial Revolution, several international scientific research programs have analyzed the role of individual components of the Earth system in the global carbon cycle. Our knowledge of the carbon cycle within the oceans, terrestrial ecosystems, and the atmosphere is sufficiently extensive to permit us to conclude that although natural processes can potentially slow the rate of increase in atmospheric CO2, there is no natural "savior" waiting to assimilate all the anthropogenically produced CO2 in the coming century. Our knowledge is insufficient to describe the interactions between the components of the Earth system and the relationship between the carbon cycle and other biogeochemical and climatological processes. Overcoming this limitation requires a systems approach.

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In recent years, increased awareness of the potential interactions between rising atmospheric CO2 concentrations ([ CO2 ]) and temperature has illustrated the importance of multifactorial ecosystem manipulation experiments for validating Earth System models. To address the urgent need for increased understanding of responses in multifactorial experiments, this article synthesizes how ecosystem productivity and soil processes respond to combined warming and [ CO2 ] manipulation, and compares it with those obtained in single factor [ CO2 ] and temperature manipulation experiments. Across all combined elevated [ CO2 ] and warming experiments, biomass production and soil respiration were typically enhanced. Responses to the combined treatment were more similar to those in the [ CO2 ]-only treatment than to those in the warming-only treatment. In contrast to warming-only experiments, both the combined and the [ CO2 ]-only treatments elicited larger stimulation of fine root biomass than of aboveground biomass, consistently stimulated soil respiration, and decreased foliar nitrogen (N) concentration. Nonetheless, mineral N availability declined less in the combined treatment than in the [ CO2 ]-only treatment, possibly due to the warming-induced acceleration of decomposition, implying that progressive nitrogen limitation (PNL) may not occur as commonly as anticipated from single factor [ CO2 ] treatment studies. Responses of total plant biomass, especially of aboveground biomass, revealed antagonistic interactions between elevated [ CO2 ] and warming, i.e. the response to the combined treatment was usually less-than-additive. This implies that productivity projections might be overestimated when models are parameterized based on single factor responses. Our results highlight the need for more (and especially more long-term) multifactor manipulation experiments. Because single factor CO2 responses often dominated over warming responses in the combined treatments, our results also suggest that projected responses to future global warming in Earth System models should not be parameterized using single factor warming experiments.

Summary• The flux of carbon from tree photosynthesis through roots to ectomycorrhizal (ECM) fungi and other soil organisms is assumed to vary with season and with edaphic factors such as nitrogen availability, but these effects have not been quantified directly in the field.• To address this deficiency, we conducted high temporal-resolution tracing of 13 C from canopy photosynthesis to different groups of soil organisms in a young boreal Pinus sylvestris forest.• There was a 500% higher below-ground allocation of plant C in the late (August) season compared with the early season (June). Labelled C was primarily found in fungal fatty acid biomarkers (and rarely in bacterial biomarkers), and in Collembola, but not in Acari and Enchytraeidae. The production of sporocarps of ECM fungi was totally dependent on allocation of recent photosynthate in the late season. There was no short-term (2 wk) effect of additions of N to the soil, but after 1 yr, there was a 60% reduction of below-ground C allocation to soil biota.• Thus, organisms in forest soils, and their roles in ecosystem functions, appear highly sensitive to plant physiological responses to two major aspects of global change: changes in seasonal weather patterns and N eutrophication.

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive effects of climate warming (T), altered precipitation amounts [doubled (DP) and halved (HP)] and seasonality (SP, moving precipitation in July and August to January and February to create summer drought), and elevated [CO 2 ] (C) on net primary production (NPP), heterotrophic respiration (R h ), net ecosystem production (NEP), transpiration, and runoff. We examined those responses in seven ecosystems, including forests, grasslands, and heathlands in different climate zones. The modeling analysis showed that none of the threeway interactions among T, C, and altered precipitation was substantial for either carbon or water processes, nor consistent among the seven ecosystems. However, two-way interactive effects on NPP, R h , and NEP were generally positive (i.e. amplification of one factor's effect by the other factor) between T and C or between T and DP. A negative interaction (i.e. depression of one factor's effect by the other factor) occurred for simulated NPP between T and HP. The interactive effects on runoff were positive between T and HP. Four pairs of two-way interactive effects on plant transpiration were positive and two pairs negative. In addition, wet sites generally had smaller relative changes in NPP, R h , runoff, and transpiration but larger absolute changes in NEP than dry sites in response to the treatments. The modeling results suggest new hypotheses to be tested in multifactor global change experiments. Likewise, more experimental evidence is needed for the further improvement of ecosystem models in order to adequately simulate complex interactive processes.