Anna Edlinger

There are high expectations that agricultural practices can mitigate climate change and improve soil health by increasing soil organic carbon (SOC) stocks. However, existing large scale SOC monitoring treats agricultural management as a black box, meaning that observed patterns and trends cannot inform on the option space of agricultural practices to improve or deteriorate SOC stocks. Here, we combine for the first time management data from large scale systematic farm surveys ( n = 248,362 farms) and representative soil monitoring data ( n = 8834 locations) to quantify the impact of agricultural practices on three SOC metrics across all pedoclimatic zones of Europe (EU + UK): stocks, stocks relative to pedoclimatic benchmarks, and yearly change in SOC concentration. Our findings show that in arable and tree crops, but not in grasslands, management intensity is a significant contributor to SOC loss, with impact varying by soil and climate region. However, we also observed that several practices (e.g., high share of manure, organic management, and a high proportion of leys in crop rotation) demonstrated potential for increasing SOC stocks. Under a scenario where all agricultural land in Europe would be managed as that of the 10% most optimally managed farms in terms of SOC benefit, SOC stocks would increase by 1.58 Pg C across Europe (95% CI: 1.27–1.89 Pg C). Whereas under a scenario where farms are managed as the 10% least optimally managed farms, SOC would decrease by −0.92 Pg C (−1.15 to −0.68 Pg C). However, it is important to note that these estimates reflect steady‐state SOC stocks only (i.e., they do not represent the transient build‐up or loss over time, or interactions with a changing climate). This paper thus quantifies how agricultural practices influence patterns in SOC stocks at the continental scale, identifying leverage points for site‐specific policies to improve SOC stocks.

The world’s growing population raises concerns about future food security. At the same time, environmental challenges such as climate change, biodiversity loss, and the depletion of natural resources must be addressed, calling for a transformation of agriculture. This need is exacerbated by the limited availability of land suitable for arable farming. In this study, we examined the potential of agricultural land for arable farming and grassland use in Switzerland, under the premise that agricultural land use should align with the biophysical and environmental capacity of each location. In an iterative co-design process with scientists and public authorities, we elaborated three scenarios for agricultural transformation, which progressively incorporated (i) biophysical constraints (soil, climate, and topography) and (ii) environmental constraints (soil loss and eutrophication due to risk of erosion), as well as (iii) greenhouse gas emissions from drained organic soils. Our results show that the allocation of 40% arable land and 60% grassland in the most restrictive scenario closely resembles the current distribution (46% and 54%), respectively. However, the scenarios also revealed significant spatial shifts between arable land and grassland at the local level: only two-thirds of today’s arable land areas match their natural site conditions. Evidence from this study underscores the critical importance of site-adapted transitions of agricultural land use and the need for site-adapted management alternatives for farmland presently assigned to inadequate land use. Overall, this research provides a novel contribution by allowing the identification of hotspot areas for agricultural transformation at the local scale. We show that these site-specific land use analyses are essential for guiding effective land use planning and policy advice that strengthen the integrity of environmental performance and agricultural productivity, and support the development of targeted and sustainable land use strategies.

Agricultural management is critical in shaping soil carbon (C) stocks, pools and fluxes. The soil priming effect (PE) is known as a key component of the global C cycle that reflects alterations in soil organic carbon (SOC) mineralization induced by fresh C inputs. Here, we show that priming can help to predict soil C content across European Long-Term Experiments (LTEs), a result which was maintained at continental and global scales. Results reveal that lower-intensity management significantly enhances PE in soils from European croplands. Conversely, high-intensity management led to lower or even negative PE. Management intensity influences PE directly through alterations in SOC and indirectly by modifying aggregates stability and microbial biomass. Both fertilization and tillage affect PE, with soils under organic fertilization and no-tillage showing higher values of PE. These findings advance our understanding of the long-term impacts of agricultural management on the C cycle at the continental scale.

Solar parks are a rapidly expanding form of land use, primarily aimed at producing renewable energy. However, the aim is to make them multifunctional, and limit negative impacts on soils and biodiversity which requires light availability for plant growth. Previous research has shown a significant decline in plant biomass and soil biota beneath solar panels across different solar parks in the Netherlands that have a dense packing of relatively large, relatively flat solar panel arrays. The ground irradiance under these solar panel arrays is well below 10% of the open field irradiance, and the ecological decline was related to very low light availability beneath the panels. However, plant growth, soil biota and soil organic carbon may still be well-supported at intermediate levels of light availability and by favourable microclimatic conditions. In this research an experimental solar park was constructed with varying solar panel density to test the effect of a light gradient on the vegetation, CO2-fluxes, and on soil biota. The experiment consisted of 6 different light treatments (8%, 20%, 30%, 40%, 65% and 100% of annual open field irradiance) and 3 vegetation treatments (non-sowing, sowing of shade tolerant plant species and sowing of a “standard” species diverse grassland mixture). Plant biomass and species composition, nematode and earthworm abundance and net ecosystem exchange (NEE) were measured. Plant biomass, and the abundance of earthworms and nematodes all significantly increased with increasing levels of light, with the strongest increases between 8% and 20% light. At low light levels, shade tolerant plant species’ biomass was higher compared to the other vegetation treatments. These results show with a relatively small increase in light availability can lead to large benefits to soil health and biodiversity.

It is becoming increasingly evident that one-size-fits-all solutions are rare when it comes to enhancing soil organic carbon (SOC) stocks in agricultural soils. Instead, context-specific management recommendations are needed, guided by a detailed understanding of how different management practices interact with environmental factors, such as climate or soil type, to affect SOC stocks. Since it is impossible to test all such combinations in controlled experiments, using large datasets of on-farm data is a promising alternative. Here, we predicted crop-specific management for all sample locations of the European wide soil monitoring of SOC in agricultural soils (LUCAS Soil, n = 8,834 repeat samples from the years 2009, 2015 and 2018) using individual farm management data representatively surveyed yearly for all EU + UK regions (n = 82,000 farms per year). We will present results of how relevant agricultural practices, including crop rotation diversity, cropping intensity, fertilizer use, fertilizer type, organic farming and tillage intensity, impact SOC stocks at the European scale. In addition, the large sample size and coverage of extensive environmental gradients allows disentangling the effect of management and environmental drivers on SOC stocks. We expect that these results provide a more nuanced view of how management impacts SOC under various soil and climatic conditions, contributing to the development of context-specific management recommendations to increase SOC stocks in agricultural soils.

Denitrification, a major source of gaseous nitrogen emissions from agricultural soils, is influenced by management. Practices promoting belowground diversity are suggested to support sustainable agriculture, but how they modulate nitrogen losses via denitrification remains inconclusive. Here we sampled 106 cereal fields spanning a 3000 km North-South gradient across Europe and compiled 56 associated climatic, soil, microbial and management variables. We show that increased denitrification potential was associated with higher proportion of time with crop cover over the last ten years and was best predicted by microbial biomass and microbial functional guilds involved in nitrogen cycling, in particular denitrification. We also demonstrate that several diversification practices affect the variation in denitrification potential predictors, suggesting a trade-off between agricultural diversification and nitrogen losses via denitrification. However, increased crop diversity in rotations improved yield-scaled denitrification, highlighting the potential of this practice to minimize nitrogen losses while contributing to sustainable food production.

Societal Impact Statement: Agricultural production systems in the global North combine monocultures of specialised varieties and breeds with external interventions and inputs. Increasing the diversity of varieties, breeds and species may increase the system's resilience to external pressures through beneficial interactions. However, more diverse agricultural systems actually show large variation in their response to stresses. We propose to use functional‐structural modelling, alternating with field experiments, to optimise the design of biodiverse systems and validate predicted interactions under stresses. This information can then be used to design biodiverse production systems that are more resilient and guide crop variety and livestock breeding for them. Summary: Many arable, horticultural, livestock and forestry production systems are optimised for productivity in monocultures, with environmental factors managed primarily through external interventions and inputs (fertilizers, herbicides, pesticides, antibiotics, irrigation). Enhancing system resilience may be achieved by (re)introducing diversity within and between species and breeds of crops, livestock and trees. While the ecological concepts underlying the effect of biodiversity on resilience are known, in practice the response of more biodiverse agricultural production systems to external pressures shows large variation. Hence, resilient production systems do not emerge automatically from greater diversity but must be designed. Studying the specific combining advantages of different species/varieties/breeds at the production system level may provide the required information, but the number of possible combinations and interactions is too large to screen with controlled field experiments only. We argue that modelling provides a solution to this combinatorial problem by allowing for an in silico exhaustive search of possible interactions. We describe various crop models and discuss the use of functional‐structural models for (re‐)designing production systems, specifying the functional traits to be selected for in crop variety and livestock breeding. While process‐based functional‐structural models can predict how genotypes will respond to environmental stressors, experimental trials measure these responses in the field. An iterative process– where models inform experiments and experiments, in turn, refine models– may lead to a nuanced understanding of resilience mechanisms and a robust set of tools for designing diversified production systems. We discuss opportunities and pitfalls of this combined approach.