• Energy Research

AbstractWe have read with interest an opinion paper recently published in the European Journal of Soil Science (Berthelin et al., 2022). This paper presents some interesting considerations, at least one of which is already well known to soil scientists working on soil organic carbon (SOC), that is, a large portion (80%–90%) of fresh carbon inputs to soil is subject to rapid mineralization. The short‐term mineralization kinetics of organic inputs is well‐known and accounted for in soil organic matter models. Thus, clearly, the long‐term predictions based on these models do not overlook short‐term mineralization. We point out that many agronomic practices can significantly contribute to SOC sequestration. If conducted responsibly whilst fully recognising the caveats, SOC sequestration can lead to a win‐win situation where agriculture can both contribute to the mitigation of climate change and adapt to it, whilst at the same time delivering other co‐benefits such as reduced soil erosion and enhanced biodiversity.Highlights Rapid mineralization of organic inputs is an important factor for soil carbon sequestration. Mineralization kinetics of organic inputs are well‐known and accounted for in soil organic matter models. Many agronomic practices can contribute significantly to SOC sequestration. SOC sequestration can lead to a win‐win situation where agriculture can both contribute to the mitigation of climate change and adapt to it.

SUMMARYAgricultural production in the Sudano–Sahelian zone of west Africa is highly vulnerable to the impacts of climate variability and climate change. The present study aimed to understand farmers’ perceptions of climate variability and change and to evaluate adaptation options together with farmers, including tactical management of planting date in combination with the use of mineral fertilizer. Farmers perceived an increase in annual rainfall variability, an increase in the occurrence of dry spells during the rainy season, and an increase in temperature. Overall, this is in line with the observed meteorological data. Drought tolerant, short maturing crop varieties and appropriate planting dates were the commonly preferred adaptation strategies to deal with climate variability. On-farm trials confirmed that planting delays significantly reduce crop yields. The use of mineral fertilizer is often promoted, but risky for smallholders: although larger fertilizer applications increased the yield of maize (Zea mays) and millet (Pennisetum glaucum) significantly, a gross margin analysis indicated that it did not lead to more profit for all farmers. We conclude that integrating management of nutrients and planting time with improved farmer access to timely weather information, especially on the onset of the rains, is critical to enhancing adaptive capacity to increased climate variability and change.

Recent experimental studies have revealed that soil carbon (C) and nitrogen (N) content and soil N availability often decrease following conversion of improved pasture to Pinus radiata plantations. These decreases are a concern partly because of possible negative consequences for future forest productivity. This issue is investigated by applying the G'DAY model of C and N cycling in pasture and forest ecosystems to simulate the replacement of improved, legume-rich pasture by P. radiata plantations that are grown over several harvest cycles at a site in New Zealand. We illustrate how process models can be used for analysing constraints on long-term productivity by performing a sensitivity analysis of G'DAY's response to various rates of N removal. We find that simulated productivity declines over successive forest rotations and that the rate of decline is sensitive to N losses through wood harvesting, slash removal, and N leakage (i.e. leaching and soil gaseous emission). However, even when these N losses are zero, forest productivity still declines because of a gradual depletion of labile soil N reserves. Simulations are used to evaluate the mean annual increment (MAI) in wood volume over forty 30-year forest rotations. With harvesting only, simulated MAI declines from 44 m(3) ha(-1)yr(-1) in the first rotation to 18 m; ha(-1)yr(-1) in the fortieth rotation. The simulated MAI in the fortieth rotation is 13 m(3) ha(-1)yr(-1) with harvesting and leakage, and 11 m(3) ha(-1)yr(-1) with harvesting, leakage and 50% slash removal. If the simulation with harvesting only is modified so N removed in harvests is replaced by an equivalent fertiliser addition, MAI is 28 m(3) ha(-1)yr(-1) in the fortieth rotation. Results presented are tentative and should be regarded with caution until the model is fully tested.

These are the raw data of the paper "Long-term tillage, residue management and crop rotation impacts on N2O and CH4 emissions on two contrasting soils in sub-humid Zimbabwe” authored by Armwell Shumba, Regis Chikowo, Marc Corbeels, Johan Six, Christian Thierfelder, Rémi Cardinael

AbstractPotential 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.

Worldwide, native grasslands are being converted to non-native pastures and cropland. This process threatens local grassland biomes as well as the livelihoods of farm families that utilize these grasslands. In the Río de la Plata grasslands region meat production and multispecies native grasslands have coexisted for more than 400 years. Low levels of meat productivity and farm income, however, trigger replacement of native grasslands by crops and leys and threaten the survival of local beef farming systems. We studied the economic and environmental performance of beef farming in the region based on interviews and field measurements on 280 case study farms with the following aims: (a) to identify the multi-functional economic and environmental performance of beef farms across the Rio de la Plata grasslands biome; (b) to identify farms with ‘outstanding’ multi-functional performance; (c) to compare performance levels with those found in other regions; and (d) to discuss the implications of the outstanding farms for the development of new systems of meat production. The representativeness of the case study farms was ascertained by comparing them with a farm typology constructed from survey data of 15,448 beef farms situated predominantly on native grasslands in Argentina, Brazil and Uruguay. We identified seven farm types on the basis of farm size, labour, farm specialization, land use and stocking rate. We identified positive deviant farms based on Pareto-ranking and compared these with a classification based on threshold values provided by experts. Out of the 280 farms, 41 were ranked as Pareto-optimal, i.e. outperformed other farms in one or more indicators without being outperformed in other indicators. Out of these, 5 were positive deviants, achieving on average 192 kg LW ha−1 yr−1 of livestock productivity and 201 US$ ha−1 year−1 farm income, having most favourable values for fossil energy consumption, phosphorus balance, carbon footprint and having over 95% of their land under native grassland as a proxy for biodiversity conservation value. Four of these farms belonged to farm types that together represented 55% of the population, suggesting scope for widescale improvement. Compared to the values reported for the OECD countries the beef farming systems of the Río de la Plata grasslands region consume less energy and positive deviant farms demonstrated approximately average livestock productivity and carbon footprint. Increasing livestock productivity in the Rio de la Plata grasslands region resulted in a stronger decline of the carbon footprint without compromising the current negligible levels of fossil fuel energy use. Further elucidation of management practices that lead to positive deviant performance will require modelling of the interaction of pasture and herd dynamics at farm level and is needed to support targeted policy support for sustainable natural grassland-based beef production in the region.

AbstractMajor 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.