The effect of crop residues, cover crops, manures and nitrogen fertilization on soil organic carbon changes in agroecosystems: a synthesis of reviews

International initiatives are emphasizing the capture of atmospheric CO2 in soil organic C (SOC) to reduce the climatic footprint from agroecosystems. One approach to quantify the contribution of management practices towards that goal is through analysis of long-term experiments (LTEs). Our objectives were to analyze knowledge gained in literature reviews on SOC changes in LTEs, to evaluate the results regarding interactions with pedo-climatological factors, and to discuss disparities among reviews in data selection criteria. We summarized mean response ratios (RRs) and stock change rate (SCR) effect size indices from twenty reviews using paired comparisons (N). The highest RRs were found with manure applications (30%, N = 418), followed by aboveground crop residue retention and the use of cover crops (9–10%, N = 995 and 129), while the effect of nitrogen fertilization was lowest (6%, N = 846). SCR for nitrogen fertilization exceeded that for aboveground crop residue retention (233 versus 117 kg C ha−1 year−1, N = 183 and 279) and was highest for manure applications and cover crops (409 and 331 kg C ha−1 year−1, N = 217 and 176). When data allows, we recommend calculating both RR and SCR because it improves the interpretation. Our synthesis shows that results are not always consistent among reviews and that interaction with texture and climate remain inconclusive. Selection criteria for study durations are highly variable, resulting in irregular conclusions for the effect of time on changes in SOC. We also discuss the relationships of SOC changes with yield and cropping systems, as well as conceptual problems when scaling-up results obtained from field studies to regional levels

Multi-modelling predictions show high uncertainty of required carbon input changes to reach a 4‰ target

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4%(0) at 16 long-term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site-by-site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 +/- 1.2 Mg C ha(-)(1) year(-1) to increase SOC stocks by 4%(0) per year over 30 years, compared to the C input in the control treatments (multi-model median +/- median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water-related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi-model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water-related variables on SOC decomposition

C-TOOL: a simple model for simulating whole-profile carbon storage in temperate agricultural soils

Soil organic carbon (SOC) is a significant component of the global carbon (C) cycle. Changes in SOC storage affect atmospheric CO2 concentrations on decadal to centennial timescales. The C-TOOL model was developed to simulate farm- and regional-scale effects of management on medium- to long-term SOC storage in the profile of well-drained agricultural mineral soils. C-TOOL uses three SOC pools for both the topsoil (0–25 cm) and the subsoil (25–100 cm), and applies temperature-dependent first order kinetics to regulate C turnover. C-TOOL also enables the simulation of 14C turnover. The simple model structure facilitates calibration and requires few inputs (mean monthly air temperature, soil clay content, soil C/N ratio and C in organic inputs). The model was parameterised using data from 19 treatments drawn from seven long-term field experiments in the United Kingdom, Sweden and Denmark. It was found that the initial SOC content had to be optimised for each experiment, but also that one set of values for other model parameters could be applied at all sites. With this set of parameters, C-TOOL can be applied more widely to evaluate effects of management options on SOC storage in temperate agricultural soils. C-TOOL simulates observed losses of SOC in soils under intensive agricultural use and the gain in SOC derived from large inputs of animal manure and inclusion of perennial grassland. The model simulates changes in SOC for the entire profile, but lack of data on subsoil SOC storage hampers a proper model evaluation. Experimental verification of management effects on subsoil C storage, subsoil C inputs from roots, and vertical transport of C in the soil profile remains prioritised research areas

The potential impact of climate change on Australia's soil organic carbon resources

BACKGROUND: Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO(2 )on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM). RESULTS: We estimate organic carbon storage in the topsoil (0–10 cm) of the Australian continent in 1990 to be 8.1 Gt. This equates to 19 and 34 Gt in the top 30 and 100 cm of soil, respectively. By the year 2100, under a low emissions scenario, topsoil organic carbon stores of the continent will have increased by 0.6% (49 Mt C). Under a high emissions scenario, the Australian continent becomes a source of CO(2 )with a net reduction of 6.4% (518 Mt) in topsoil carbon, when compared to no climate change. This is partially offset by the predicted increase in NPP of 20.3% CONCLUSION: Climate change impacts must be studied holistically, requiring integration of climate, plant, ecosystem and soil sciences. The SOCRATES terrestrial carbon cycling model provides realistic estimates of changes in SOC storage in response to climate change over the next century, and confirms the need for greater consideration of soils in assessing the full impact of climate change and the development of quantifiable mitigation strategies

Agriculture Systems

An agricultural ecosystem is an ecosystem managed with a purpose, usually to produce crops or animal products. Agricultural ecosystems are designed by humans, and are based on a long chain of experience and experiments. The emphasis in, for example, Western Europe has changed from maximum productivity only to also include environmental considerations, such as reduction of nutrient losses to groundwater and maintaining an open landscape with high biodiversity, etc. In less-productive regions such as sub-Saharan Africa, environmental considerations still have low priority. Agricultural ecosystems comprise almost 40% (5 Gha) of the total land area of the Earth. About 11% of the total land area is arable land (cultivated with crops), and approximately 27% of the total land area is under permanent pasture, grazed by cattle, goats, sheep, camels, etc. Plant biodiversity is extremely low – if weed control is successful there may be only one species present. In spite of this, belowground biodiversity can be high, although often lower than in natural ecosystems. Ecological research performed in agricultural systems has advantages compared with research in most natural ecosystems, since agricultural fields are ‘homogenized’, that is, trees, larger stones, etc. are removed and regular soil cultivation to some extent evens out differences in topsoil properties over time

Temperature dependence of carbon mineralisation: conclusions from a long-term incubation of subalpine soil samples

Carbon mineralisation from soil samples was analysed during a 104-day laboratory incubation at 5, 15 and 25 degrees C. The samples were taken from the upper horizon of each of two topographically different micro-sites (gully: A-horizon; ridge: Oe/Oa-layer) at the Stillberg Alp close to Davos in the Swiss Central Alps. On both the soils, carbon mineralisation rates decreased substantially with incubation time (e.g. from 0.3 to 0.18 mg CO2-C d(-1) g(-1) organic carbon in the Oe-Oa-layer and from 0.6 to 0.2 mg CO2-C d(-1) g(-1) organic carbon at 25 degrees C in the A-horizon). Carbon mineralisation was well described by a first-order kinetic two-compartment model and a functional temperature dependence of the rate constants. Both temperature models, the exponential pro-function and a quadratic function described the cumulative C-mineralisation correctly within one standard error of estimate (SE) of the measured values. However, the Q(10) model gave a slightly better fit to the data, and Q(10)-values of 2.5 and 2.8 were computed for the rate constants of the organic layer and the A-horizon, respectively. While the temperature dependence of the (time independent) rate constants of mineralisation appeared to be well-defined, this was not the case for Q(10) of the instantaneous respiration rates, which were a non-linear function of incubation time. The general pattern of fluctuation of the instantaneous Q(10)-values was in accordance with the results computed by the models, and can be explained by the parallel decomposition of two different soil organic matter pools. To avoid the effects of the time of the respiration measurement on the calculated Q(10), it is recommended to analyse the whole time series in order to infer the temperature dependence of respiration, or at least to standardise the time at which soil respiration is measured. In a second part of the study, our laboratory results temperature effects were extrapolated to the field, using measurements of soil temperature as driving variables to a recently developed carbon balance model. Carbon mineralisation was roughly estimated to be 52-84 g C m(-2) year(-1) for the gullies and 70-125 g C m(-2) year(-1) for the ridges. Unexpectedly, the choice of the temperature model had a great influence on the estimate of annual carbon mineralisation, even though models differed only little concerning the fit to the laboratory incubation data. However, it could be shown that winter-time mineralisation probably accounted for at least 22 and 40% of the whole-year mineralisation on the ridges and the gullies, respectively, and therefore, should not be neglected in carbon-balance studies. (C) 2000 Elsevier Science Ltd. All rights reserved