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Microbially-explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (RH ), a stringent test for soil biogeochemical models, has never been evaluated. We used statistical global RH products, as well as 7,821 daily site-scale RH measurements, to evaluate the spatio-temporal performance of one first-order decay model (CASA-CNP) and two microbially-explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different input datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the input data used to drive them. Spatial variability in RH fluxes was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of RH well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise, but also needs to be improved for realistic spatio-temporal variability of RH . Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models.

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO2 assimilation (Asat), aboveground wood NPP (ANPPw), and soil respiration (Rs) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, Asat and ANPPw, were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPPw resistance and, conversely, negatively related to Rs resistance. Subcanopy Asat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with Rs declines suggest the net C sink was sustained in the initial months following disturbance. We conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance.

The concept of stability is central to the study and sustainability of vital ecosystem goods and services as disturbances increase globally. While ecosystem ecologists, including carbon (C) cycling scientists, have long‐considered multiple dimensions of disturbance response, our discipline lacks an agreed‐upon analytical framework for characterizing multidimensional stability. Here, we advocate for the broader adoption of a standardized and normalized multidimensional stability framework for analyzing disturbance response. This framework includes four dimensions of stability: the degree of initial change in C fluxes (i.e., resistance); rate (i.e., resilience) and variability (i.e., temporal stability) of return to pre‐disturbance C fluxes; and the extent of return to pre‐disturbance C fluxes (i.e., recovery). Using this framework, we highlight findings not readily seen from analysis of absolute fluxes, including trade‐offs between initial and long‐term C flux responses to disturbance; different overall stability profiles among fluxes; and, using a pilot dataset, similar relative stability of net primary production following fire and insect disturbances. We conclude that ecosystem ecologists’ embrace of a unifying multidimensional stability framework as a complement to approaches focused on absolute C fluxes could advance global change research by aiding in the novel interpretation, comprehensive synthesis, and improved forecasting of ecosystems’ response to an increasing array of disturbances.

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean $${149}_{-23}^{+29}$$ 149 − 23 + 29 Pg C yr−1) are significantly higher than most GPP estimates reported in the literature ($${113}_{-18}^{+18}$$ 113 − 18 + 18 Pg C yr−1). Similarly, historical GPP estimates imply a soil respiration flux (RsGPP, bootstrap mean of $${68}_{-8}^{+10}$$ 68 − 8 + 10 Pg C yr−1) statistically inconsistent with most published RS values ($${87}_{-8}^{+9}$$ 87 − 8 + 9 Pg C yr−1), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global RS:GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.

Surface and space-based observations, field experiments, and models all contribute to our evolving understanding of the ways that Earth’s many systems absorb and release carbon.