The question of why some types of organic matter are more persistent while others decompose quickly in soils has motivated a large amount of research in recent years. Persistence is commonly characterized as turnover or mean residence time of soil organic matter (SOM). However, turnover and residence times are ambiguous measures of persistence, because they could represent the concept of either age or transit time. To disambiguate these concepts and propose a metric to assess SOM persistence, we calculated age and transit time distributions for a wide range of soil organic carbon models. Furthermore, we show how age and transit time distributions can be obtained from a stochastic approach that takes a deterministic model of mass transfers among different pools and creates an equivalent stochastic model at the level of atoms. Using this approach we show the following: (1) Age distributions have relatively old mean values and long tails in relation to transit time distributions, suggesting that carbon stored in soils is on average much older than carbon in the release flux. (2) The difference between mean ages and mean transit times is large, with estimates of soil organic carbon persistence on the order of centuries or millennia when assessed using ages and on the order of decades when using transit or turnover times. (3) The age distribution is an appropriate metric to characterize persistence of SOM. An important implication of our analysis is that random chance is a factor that helps to explain why some organic matter persists for millennia in soil.

Radiocarbon (14C) is a powerful tracer of the global carbon cycle that is commonly used to assess carbon cycling rates in various Earth system reservoirs and as a benchmark to assess model performance. Therefore, it has been recommended that Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 report predicted radiocarbon values for relevant carbon pools. However, a detailed representation of radiocarbon dynamics may be an impractical burden on model developers. Here, we present an alternative approach to compute radiocarbon values from the numerical output of an ESM that does not explicitly represent these dynamics. The approach requires computed 12C stocks and fluxes among all carbon pools for a particular simulation of the model. From this output, a time-dependent linear compartmental system is computed with its respective state-transition matrix. Using transient atmospheric 14C values as inputs, the state-transition matrix is then applied to compute radiocarbon values for each pool, the average value for the entire system, and component fluxes. We demonstrate the approach with ELMv1-ECA, the land component of an ESM model that explicitly represents 12C, and 14C in 7 soil pools and 10 vertical layers. Results from our proposed method are highly accurate (relative error <0.01%) compared with the ELMv1-ECA 12C and 14C predictions, demonstrating the potential to use this approach in CMIP6 and other model simulations that do not explicitly represent 14C.

Wetland methane (CH₄) emissions over the Boreal-Arctic region are vulnerable to climate change and linked to climate feedbacks, yet understanding of their long-term dynamics remains uncertain. Here, we upscaled and analysed two decades (2002-2021) of Boreal-Arctic wetland CH₄ emissions, representing an unprecedented compilation of eddy covariance and chamber observations. We found a robust increasing trend of CH₄ emissions (+8.9%) with strong inter-annual variability. The majority of emission increases occurred in early summer (June and July) and were mainly driven by warming (52.3%) and ecosystem productivity (40.7%). Moreover, a 2 °C temperature anomaly in 2016 led to the highest recorded annual CH₄ emissions (22.3 Tg CH₄ yr^-1) over this region, driven primarily by high emissions over Western Siberian lowlands. However, current-generation models from the Global Carbon Project failed to capture the emission magnitude and trend, and may bias the estimates in future wetland CH₄ emission driven by amplified Boreal-Arctic warming and greening.

Managed grasslands have the potential to store carbon (C) and partially mitigate climate change. However, it remains difficult to predict potential C storage under a given soil or management practice. To study C storage dynamics due to long-term (1952-2009) phosphorus (P) fertilizer and irrigation treatments in New Zealand grasslands, we measured radiocarbon (¹⁴C) in archived soil along with observed changes in C stocks to constrain a compartmental soil model. Productivity increases from P application and irrigation in these trials resulted in very similar C accumulation rates between 1959 and 2009. The ∆¹⁴C changes over the same time period were similar in plots that were both irrigated and fertilized, and only differed in a non-irrigated fertilized plot. Model results indicated that decomposition rates of fast cycling C (0.1 to 0.2 year^-1) increased to nearly offset increases in inputs. With increasing P fertilization, decomposition rates also increased in the slow pool (0.005 to 0.008 year^-1). Our findings show sustained, significant (i.e. greater than 4 per mille) increases in C stocks regardless of treatment or inputs. As the majority of fresh inputs remain in the soil for less than 10 years, these long term increases reflect dynamics of the slow pool. Additionally, frequent irrigation was associated with reduced stocks and increased decomposition of fresh plant material. Rates of C gain and decay highlight trade-offs between productivity, nutrient availability, and soil C sequestration as a climate change mitigation strategy.

Supplementary information

The online version contains supplementary material available at 10.1007/s10533-021-00838-z.

Organic carbon (OC) association with soil minerals stabilizes OC on timescales reflecting the strength of mineral-C interactions. We applied ramped thermal oxidation to subsoil B horizons with different mineral-C associations to separate OC according to increasing temperature of oxidation, i.e. thermal activation energy. Generally, OC released at lower temperatures was richer in bioavailable forms like polysaccharides, while OC released at higher temperatures was more aromatic. Organic carbon associated with pedogenic oxides was released at lower temperatures and had a narrow range of 14C content. By contrast, N-rich compounds were released at higher temperatures from samples with 2 : 1 clays and short-range ordered (SRO) amorphous minerals. Temperatures of release overlapped for SRO minerals and crystalline oxides, although the mean age of OC released was older for the SRO. In soils with more mixed mineralogy, the added presence of older OC released at temperatures greater than 450°C from clays resulted in a broader distribution of OC ages within the sample, especially for soils rich in 2 : 1 layer expandable clays such as smectite. While pedogenic setting affects mineral stability and absolute OC age, mineralogy controls the structure of OC age distribution within a sample, which may provide insight into model structures and OC dynamics under changing conditions. This article is part of the Theo Murphy meeting issue Radiocarbon in the Anthropocene.

Soils contain more carbon than the atmosphere and vegetation combined. An increased flow of carbon from the atmosphere into soil pools could help mitigate anthropogenic emissions of carbon dioxide and climate change. Yet we do not know how quickly soils might respond because the age distribution of soil carbon is uncertain. Here we used 789 radiocarbon (∆14C) profiles, along with other geospatial information, to create globally gridded datasets of mineral soil ∆14C and mean age. We found that soil depth is a primary driver of ∆14C, whereas climate (for example, mean annual temperature) is a major control on the spatial pattern of ∆14C in surface soil. Integrated to a depth of 1 m, global soil carbon has a mean age of 4,830 ± 1,730 yr, with older carbon in deeper layers and permafrost regions. In contrast, vertically resolved land models simulate ∆14C values that imply younger carbon ages and a more rapid carbon turnover. Our data-derived estimates of older mean soil carbon age suggest that soils will accumulate less carbon than predicted by current Earth system models over the twenty-first century. Reconciling these models with the global distribution of soil radiocarbon will require a better representation of the mechanisms that control carbon persistence in soils.

In the mostly pristine Congo Basin, agricultural land-use change has intensified in recent years. One potential and understudied consequence of this deforestation and conversion to agriculture is the mobilization and loss of organic matter from soils to rivers as dissolved organic matter. Here, we quantify and characterize dissolved organic matter sampled from 19 catchments of varying deforestation extent near Lake Kivu over a two-week period during the wet season. Dissolved organic carbon from deforested, agriculturally-dominated catchments was older (¹⁴C age: ~1.5kyr) and more biolabile than from pristine forest catchments. Ultrahigh-resolution mass spectrometry revealed that this aged organic matter from deforested catchments was energy-rich and chemodiverse, with higher proportions of nitrogen- and sulfur-containing formulae. Given the molecular composition and biolability, we suggest that organic matter from deforested landscapes is preferentially respired upon disturbance, resulting in elevated in-stream concentrations of carbon dioxide. We estimate that while deforestation reduces the overall flux of dissolved organic carbon by ~56%, it does not significantly change the yield of biolabile dissolved organic carbon. Ultimately, the exposure of deeper soil horizons through deforestation and agricultural expansion releases old, previously stable, and biolabile soil organic carbon into the modern carbon cycle via the aquatic pathway.

Given the importance of soil for the global carbon cycle, it is essential to understand not only how much carbon soil stores but also how long this carbon persists. Previous studies have shown that the amount and age of soil carbon are strongly affected by the interaction of climate, vegetation, and mineralogy. However, these findings are primarily based on studies from temperate regions and from fine-scale studies, leaving large knowledge gaps for soils from understudied regions such as sub-Saharan Africa. In addition, there is a lack of data to validate modeled soil C dynamics at broad scales. Here, we present insights into organic carbon cycling, based on a new broad-scale radiocarbon and mineral dataset for sub-Saharan Africa. We found that in moderately weathered soils in seasonal climate zones with poorly crystalline and reactive clay minerals, organic carbon persists longer on average (topsoil: 201 ± 130 years; subsoil: 645 ± 385 years) than in highly weathered soils in humid regions (topsoil: 140 ± 46 years; subsoil: 454 ± 247 years) with less reactive minerals. Soils in arid climate zones (topsoil: 396 ± 339 years; subsoil: 963 ± 669 years) store organic carbon for periods more similar to those in seasonal climate zones, likely reflecting climatic constraints on weathering, carbon inputs and microbial decomposition. These insights into the timescales of organic carbon persistence in soils of sub-Saharan Africa suggest that a process-oriented grouping of soils based on pedo-climatic conditions may be useful to improve predictions of soil responses to climate change at broader scales.

Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH4). The FLUXNET-CH4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH4 Community Product v1.0 have provided invaluable insights into the drivers of ecosystem-to-regional spatial patterns and daily-to-decadal temporal dynamics in temperate, boreal, and Arctic climate regions. However, as the wetland CH4 monitoring network grows, there is a critical knowledge gap about where new monitoring infrastructure ought to be located to improve understanding of the global wetland CH4 budget. Here we address this gap with a spatial representativeness analysis at existing and hypothetical observation sites, using 16 process-based wetland biogeochemistry models and machine learning. We find that, in addition to eddy covariance monitoring sites, existing chamber sites are important complements, especially over high latitudes and the tropics. Furthermore, expanding the current monitoring network for wetland CH4 emissions should prioritize, first, tropical and second, sub-tropical semi-arid wetland regions. Considering those new hypothetical wetland sites from tropical and semi-arid climate zones could significantly improve global estimates of wetland CH4 emissions and reduce bias by 79% (from 76 to 16 TgCH4 y−1), compared with using solely existing monitoring networks. Our study thus demonstrates an approach for long-term strategic expansion of flux observations.