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Abstract Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty. 

Abstract We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO₂), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO₂, warming, and decreased precipitation combined because higher water‐use efficiency with elevated CO₂and higher fertility with warming compensate for responses to drought. Response to elevated CO₂, warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO₂and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C‐nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO₂and climate change. 

Summary As Arctic soils warm, thawed permafrost releases nitrogen (N) that could stimulate plant productivity and thus offset soil carbon losses from tundra ecosystems. Although mycorrhizal fungi could facilitate plant access to permafrost‐derived N, their exploration capacity beyond host plant root systems into deep, cold active layer soils adjacent to the permafrost table is unknown.We characterized root‐associated fungi (RAF) that colonized ericoid (ERM) and ectomycorrhizal (ECM) shrub roots and occurred below the maximum rooting depth in permafrost thaw‐front soil in tussock and shrub tundra communities. We explored the relationships between root and thaw front fungal composition and plant uptake of a¹⁵N tracer applied at the permafrost boundary.We show that ERM and ECM shrubs associate with RAF at the thaw front providing evidence for potential mycelial connectivity between roots and the permafrost boundary. Among shrubs and tundra communities, RAF connectivity to the thaw boundary was ubiquitous. The occurrence of particular RAF in both roots and thaw front soil was positively correlated with¹⁵N recovered in shrub biomassTaxon‐specific RAF associations could be a mechanism for the vertical redistribution of deep, permafrost‐derived nutrients, which may alleviate N limitation and stimulate productivity in warming tundra.