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Coastal wetlands (mangrove, tidal marsh and seagrass) sustain the highest rates of carbon sequestration per unit area of all natural systems1,2, primarily because of their comparatively high productivity and preservation of organic carbon within sedimentary substrates3. Climate change and associated relative sea-level rise (RSLR) have been proposed to increase the rate of organic-carbon burial in coastal wetlands in the first half of the twenty-first century4, but these carbon–climate feedback effects have been modelled to diminish over time as wetlands are increasingly submerged and carbon stores become compromised by erosion4,5. Here we show that tidal marshes on coastlines that experienced rapid RSLR over the past few millennia (in the late Holocene, from about 4,200 years ago to the present) have on average 1.7 to 3.7 times higher soil carbon concentrations within 20 centimetres of the surface than those subject to a long period of sea-level stability. This disparity increases with depth, with soil carbon concentrations reduced by a factor of 4.9 to 9.1 at depths of 50 to 100 centimetres. We analyse the response of a wetland exposed to recent rapid RSLR following subsidence associated with pillar collapse in an underlying mine and demonstrate that the gain in carbon accumulation and elevation is proportional to the accommodation space (that is, the space available for mineral and organic material accumulation) created by RSLR. Our results suggest that coastal wetlands characteristic of tectonically stable coastlines have lower carbon storage owing to a lack of accommodation space and that carbon sequestration increases according to the vertical and lateral accommodation space6 created by RSLR. Such wetlands will provide long-term mitigating feedback effects that are relevant to global climate–carbon modelling. Wetlands exposed to rapid sea-level rise over the late Holocene contain more soil carbon than those that experienced a long period of sea-level stability.

Global warming potentially alters the terrestrial carbon (C) cycle, likely feeding back to further climate warming. However, how the ecosystem C cycle responds and feeds back to warming remains unclear. Here we used a meta-analysis approach to quantify the response ratios of 18 variables of the ecosystem C cycle to experimental warming and evaluated ecosystem C-cycle feedback to climate warming. Our results showed that warming stimulated gross ecosystem photosynthesis (GEP) by 15.7%, net primary production (NPP) by 4.4%, and plant C pools from above- and belowground parts by 6.8% and 7.0%, respectively. Experimental warming accelerated litter mass loss by 6.8%, soil respiration by 9.0%, and dissolved organic C leaching by 12.1%. In addition, the responses of some of those variables to experimental warming differed among the ecosystem types. Our results demonstrated that the stimulation of plant-derived C influx basically offset the increase in warming-induced efflux and resulted in insignificant changes in litter and soil C content, indicating that climate warming may not trigger strong positive C-climate feedback from terrestrial ecosystems. Moreover, the increase in plant C storage together with the slight but not statistically significant decrease of net ecosystem exchange (NEE) across ecosystems suggests that terrestrial ecosystems might be a weak C sink rather than a C source under global climate warming. Our results are also potentially useful for parameterizing and benchmarking land surface models in terms of C cycle responses to climate warming.

Soil microbes play critical roles in regulating terrestrial carbon (C) cycle and its feedback to climate change. However, it is still unclear how the soil microbial community and abundance respond to future climate change scenarios. In this meta-analysis, we synthesized the responses of microbial community and abundance to experimental warming from 64 published field studies. Our results showed that warming significantly increased soil microbial abundance by 7.6% on average. When grouped by vegetation or soil types, tundras and histosols had the strongest microbial responses to warming with increased microbial, fungal and bacterial abundances by 15.0%, 9.5% and 37.0% in tundra and 16.5%, 13.2% and 13.3% in histosols, respectively. We found significant negative relationships of the response ratios of microbial, fungal and bacterial abundances with the mean annual temperature, indicating that warming had stronger effects in colder than warmer regions. Moreover, the response ratios of microbial abundance to warming were positively correlated with those of soil respiration. Our findings therefore indicate that the large quantities of C stored in colder regions are likely to be more vulnerable to climate warming than the soil C stored in other warmer regions.

International audience; The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux‐tower‐based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free‐Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr−1) than JU11 (118 ± 6 Pg C yr−1). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr−1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr−1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is −3.0 ± 1.5 Pg C yr−1 °C−1, within the uncertainty of what derived from RLS (−3.9 ± 1.1 Pg C yr−1 °C−1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models