Long-term trends in yield variance of temperate managed grassland.

The management of climate-resilient grassland systems is important for stable livestock fodder production. In the face of climate change, maintaining productivity while minimizing yield variance of grassland systems is increasingly challenging. To achieve climate-resilient and stable productivity of grasslands, a better understanding of the climatic drivers of long-term trends in yield variance and its dependence on agronomic inputs is required. Based on the Park Grass Experiment at Rothamsted (UK), we report for the first time the long-term trends in yield variance of grassland (1965-2018) in plots given different fertilizer and lime applications, with contrasting productivity and plant species diversity. We implemented a statistical model that allowed yield variance to be determined independently of yield level. Environmental abiotic covariates were included in a novel criss-cross regression approach to determine climatic drivers of yield variance and its dependence on agronomic management. Our findings highlight that sufficient liming and moderate fertilization can reduce yield variance while maintaining productivity and limiting loss of plant species diversity. Plots receiving the highest rate of nitrogen fertilizer or farmyard manure had the highest yield but were also more responsive to environmental variability and had less plant species diversity. We identified the days of water stress from March to October and temperature from July to August as the two main climatic drivers, explaining approximately one-third of the observed yield variance. These drivers helped explain consistent unimodal trends in yield variance-with a peak in approximately 1995, after which variance declined. Here, for the first time, we provide a novel statistical framework and a unique long-term dataset for understanding the trends in yield variance of managed grassland. The application of the criss-cross regression approach in other long-term agro-ecological trials could help identify climatic drivers of production risk and to derive agronomic strategies for improving the climate resilience of cropping systems. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-023-00885-w.

Adequacy of nitrogen-based indicators for assessment of cropping system performance: A modelling study of Danish scenarios.

The EU nitrogen expert panel (EUNEP) has proposed nitrogen-based indicators for farm productivity (N output), efficiency (NUE) and environmental emissions (N surplus). This model-based study (using the Daisy model) was carried out, i) to study the effects of soil type, soil organic matter (SOM), cropping pre-histories varying in C input, 3-to-4 manure-to-mineral N proportions and ten crop rotations on the N-based indicators, and ii) to evaluate the adequacy of these indicators by establishing quantitative relationships between N surplus, N loss and soil organic N (SON) stock change. The results, averaged over 24-year simulation period, indicated that grass-clover dominant rotations had highest N output and showed a tendency to increase SON stocks when compared with spring-cereal monocultures. For most rotations, the NUE ranged between 70 and 75 %. The SON stocks were mainly influenced by initial SOM and cropping prehistory, and stocks increased only under low initial SOM and low C input cropping pre-history (spring barley). Overall, SON stocks tended to increase under low C input pre-history, coarse sand, low initial SOM and high manure N, however, this combination did not result in highest productivity, NUE, and lowest N losses. The relations between N surplus, N loss and SON stock change were strongly affected by crop rotations, emphasizing that using N surplus as an indicator for N leaching/losses while ignoring changes in SON stocks may result in biased conclusions, e.g. estimated average error for N losses ranged from -45 % (underestimation) for maize monoculture to +50 % (overestimation) for continuous grass-clover ley. The results also imply that the environmental assessment of cropping systems must be improved by combining above indicators with estimation of N loss and SON stock changes. This study provides a detailed account of N balance components/N indicators for diverse crop rotations and their use according to the recommendations of the EUNEP.

Scenario analysis using the Daisy model to assess and mitigate nitrate leaching from complex agro-environmental settings in Denmark.

Nitrate (N) leaching from intensively managed cropping systems is of environmental concern and it varies at local scale. To evaluate the performance of agricultural practices at this scale, there is a need to develop comprehensive assessments of N leaching and the N leaching reduction potential of mitigation measures. A model-based analysis was performed to (i) estimate N leaching from Danish cropping systems, representing 20 crop rotations, 3 soil types, 2 climates and 3-4 levels of manure (slurry)-to-fertilizer ratios, but with same available N (according to regulatory N fertilization norms), and (ii) appraise mitigation potential of on-farm measures (i.e. catch crops, early sowing of winter cereals) to reduce N leaching. The analysis was performed using a process-based agro-environmental model (Daisy). Simulated average N leaching over 24 years ranged from 16 to 85 kg N/ha/y for different crop rotations. Rotations with a higher proportion of spring crops were more prone to leaching than rotations having a higher proportion of winter cereals and semi-perennial grass-clover leys. N leaching decreased with increasing soil clay content under all conditions. The effect of two climates (different regions, mainly differing in precipitation) on N leaching was generally similar, with slight variation across rotations. Supplying a part of the available N as manure-N resulted in similar N leaching as mineral fertilizer N alone during the simulation period. Among the mitigation measures, both undersown and autumn sown catch crops were effective. Effectiveness of measures also depended on their place and frequency of occurrence in a rotation. Adopting catch crops during the most leaching-prone years and with higher frequency were effective choices. This analysis provided essential data-driven knowledge on N leaching risk, and potential of leaching reduction options. These results can serve as a supplementary guiding-tool for farmers to plan management practices, and for legislators to design farm-specific regulatory measures.