A global meta-analysis of soil organic carbon in the Anthropocene

Anthropogenic activities profoundly impact soil organic carbon (SOC), affecting its contribution to ecosystem services such as climate regulation. Here, we conducted a thorough review of the impacts of land-use change, land management, and climate change on SOC. Using second-order meta-analysis, we synthesized findings from 230 first-order meta-analyses comprising over 25,000 primary studies. We show that (i) land conversion for crop production leads to high SOC loss, that can be partially restored through land management practices, particularly by introducing trees and incorporating exogenous carbon in the form of biochar or organic amendments, (ii) land management practices that are implemented in forests generally result in depletion of SOC, and (iii) indirect effects of climate change, such as through wildfires, have a greater impact on SOC than direct climate change effects (e.g., from rising temperatures). The findings of our study provide strong evidence to assist decision-makers in safeguarding SOC stocks and promoting land management practices for SOC restoration. Furthermore, they serve as a crucial research roadmap, identifying areas that require attention to fill the knowledge gaps concerning the factors driving changes in SOC.

A global overview of studies about land management, land-use change, and climate change effects on soil organic carbon

Major drivers of gains or losses in soil organic carbon (SOC) include land management, land-use change, and climate change. Thousands of original studies have focused on these drivers of SOC change and are now compiled in a growing number of meta-analyses. To critically assess the research efforts in this domain, we retrieved and characterized 192 meta-analyses of SOC stocks or concentrations. These meta-analyses comprise more than 13,200 original studies conducted from 1910 to 2020 in 150 countries. First, we show that, despite a growing number of studies over time, the geographical coverage of studies is limited. For example, the effect of land management, land-use change, and climate change on SOC has been only occasionally studied in North and Central Africa, and in the Middle East and Central Asia. Second, the meta-analyses investigated a limited number of land management practices, mostly mineral fertilization, organic amendments, and tillage. Third, the meta-analyses demonstrated relatively low quality and transparency. Lastly, we discuss the mismatch between the increasing number of studies and the need for more local, reusable, and diversified knowledge on how to preserve high SOC stocks or restore depleted SOC stocks.

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa

Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO₂ ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO₂ ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO₂ ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

Beyond conservation agriculture

Global support for Conservation Agriculture (CA) as a pathway to Sustainable Intensification is strong. CA revolves around three principles: no-till (or minimal soil disturbance), soil cover, and crop rotation. The benefits arising from the ease of crop management, energy/cost/time savings, and soil and water conservation led to widespread adoption of CA, particularly on large farms in the Americas and Australia, where farmers harness the tools of modern science: highly-sophisticated machines, potent agrochemicals, and biotechnology. Over the past 10 years CA has been promoted among smallholder farmers in the (sub-) tropics, often with disappointing results. Growing evidence challenges the claims that CA increases crop yields and builds-up soil carbon although increased stability of crop yields in dry climates is evident. Our analyses suggest pragmatic adoption on larger mechanized farms, and limited uptake of CA by smallholder farmers in developing countries. We propose a rigorous, context-sensitive approach based on Systems Agronomy to analyze and explore sustainable intensification options, including the potential of CA. There is an urgent need to move beyond dogma and prescriptive approaches to provide soil and crop management options for farmers to enable the Sustainable Intensification of agriculture.

How do various maize crop models vary in their responses to climate change factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Adoption potential of conservation agriculture practices in sub-Saharan Africa: results from five case studies

Despite the reported benefits of conservation agriculture (CA), its wider up-scaling in Sub-Saharan Africa (SSA) has remained fairly limited. This paper shows how a newly developed qualitative expert assessment approach for CA adoption (QAToCA) was applied to determine its adoption potential in SSA. CA adoption potential is not a predictor of observed adoption rates. Instead, our aim was to systematically check relevant factors that may be influencing its adoption. QAToCA delivers an assessment of how suitable conditions "and thus the likelihood for CA adoption" are. Results show that the high CA adoption potentials exhibited by the Malawi and Zambia case relate mostly to positive institutional factors. On the other hand, the low adoption potential of the Zimbabwe case, in spite of observed higher estimates, is attributed mainly to unstable and less secured market conditions for CA. In the case of Southern Burkina Faso, the potential for CA adoption is determined to be high, and this assessment deviates from lower observed figures. This is attributed mainly to strong competition of CA and livestock for residues in this region. Lastly, the high adoption potential found in Northern Burkina Faso is explained mainly by the fact that farmers here have no alternative other than to adopt the locally adapted CA system-Zaï farming. Results of this assessment should help promoters of CA in the given regions to reflect on their activities and to eventually adjust or redesign them based on a more explicit understanding of where problems and opportunities are found.