Enteric methane (CH 4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

The projected human population of nine billion by 2050 has led to ever growing discussion of the need for increasing agricultural output to meet estimated food demands, while mitigating environmental costs. Many stakeholders in agricultural circles are calling for the intensification of agriculture to meet these demands. However, it is neither clear nor readily agreed upon what is meant by intensification. Here, we compare the three major uses, 'ecological intensification', 'sustainable intensification' and 'agroecological intensification', by analysing their various definitions, principles and practices, and also their historical appearance and evolution. We used data from the scientific literature, the grey literature, the websites of international organizations and the Scopus and FAOLEX databases. Our major findings are: (1) sustainable intensification is the most frequently used term so far. (2) The three concepts ecological intensification, sustainable intensification and agroecological intensification overlap in terms of definitions, principles and practices, thus creating some confusion in their meanings, interpretations and implications. Nevertheless, some differences exist. (3) Sustainable intensification is more widely used and represents in many cases a rather generalised category, into which most current farming practices can be put so long as sustainability is in some way addressed. However, despite its wider use, it remains imprecisely defined. (4) Ecological and agroecological intensification do introduce some major nuances and, in general, more explicitly stated definitions. For instance, ecological intensification emphasizes the understanding and intensification of biological and ecological processes and functions in agroecosystem. (5) The notion of agroecological intensification accentuates the system approach and integrates more cultural and social perspectives in its concept. (6) Even if some boundaries can be seen, confusion is still predominant in the use of these terms. These blurred boundaries currently contribute to the use of these terms for justifying many different kinds of practices and interventions. We suggest that greater precision in defining the terms and the respective practices proposed would indicate more clearly what authors or institutions are aiming at with the proposed intensification. In this sense, we provide new definitions for all three intensification concepts based on the earlier ones.

Increasing the quantity and quality of plant biomass production in space and time can improve the capacity of agroecosystems to capture and store atmospheric carbon (C) in the soil. Cover cropping is a key practice to increase system net primary productivity (NPP) and increase the quantity of high-quality plant residues available for integration into soil organic matter (SOM). Cover crop management and local environmental conditions, however, influence the magnitude of soil C stock change. Here, we used a comprehensive meta-analysis approach to quantify the effect of cover crops on soil C stocks from the 0-30 cm soil depth in temperate climates and to identify key management and ecological factors that impact variation in this response. A total of 40 publications with 181 observations were included in the meta-analysis representing six countries across three different continents. Overall, cover crops had a strong positive effect on soil C stocks (P < 0.0001) leading to a 12% increase, averaging 1.11 Mg C/ha more soil C relative to a no cover crop control. The strongest predictors of SOC response to cover cropping were planting and termination date (i.e., growing window), annual cover crop biomass production, and soil clay content. Cover crops planted as continuous cover or autumn planted and terminated led to 20-30% greater total soil C stocks relative to other cover crop growing windows. Likewise, high annual cover crop biomass production (>7 MgÁha −1 Áyr −1) resulted in 30% higher total soil C stocks than lower levels of biomass production. Managing for greater NPP by improving synchronization in cover crop growing windows and climate will enhance the capacity of this practice to drawdown carbon dioxide (CO 2) from the atmosphere across agroecosystems. The integration of growing window (potentially as a proxy for biomass growth), climate, and soil factors in decision-support tools are relevant for improving the quantification of soil C stock change under cover crops, particularly with the expansion of terrestrial soil C markets.