Circular food system approaches can support current European protein intake levels while reducing land use and greenhouse gas emissions.

Protein transition and circular food system transition are two proposed strategies for supporting food system sustainability. Here we model animal-sourced protein to plant-sourced protein ratios within a European circular food system, finding that maintaining the current animal-plant protein share while redesigning the system with circular principles resulted in the largest relative reduction of 44% in land use and 70% in greenhouse gas (GHG) emissions compared with the current food system. Shifting from a 60:40 to a 40:60 ratio of animal-sourced proteins to plant-sourced proteins yielded a 60% reduction in land use and an 81% GHG emission reduction, while supporting nutritionally adequate diets. Differences between current and recommended total protein intake did not substantially impact minimal land use and GHG emissions. Micronutrient inadequacies occurred with less than 18 g animal protein per capita per day. Redesigning the food system varied depending on whether land use or GHG emissions were reduced-highlighting the need for a food system approach when designing policies to enhance human and planetary health.

Interventions to increase circularity and reduce environmental impacts in food systems.

Applying specific circularity interventions to the food system may have environmental benefits. Using an iterative linear food system optimisation model (FOODSOM), we assess how changes in human diets, imports and exports, and the utilisation of waste streams impact land use and greenhouse gas emissions (GHG). After including these circularity principles, land use and GHG emissions were on average 40% and 68% lower than in the current food system, primarily driven by a reduction in production volumes and a shift towards feeding the domestic population. Shifting from the current diet to a circular diet decreased land use with 43% and GHG emissions with 52%. Allowing up to half of each nutrient in the human diet to be imported, while balancing imports with equal exports in terms of nitrogen, phosphorus and potassium, also decreased land use (up to 34%) and GHG emissions (up to 26%) compared to no imported food. Our findings show that circularity interventions should not be implemented mutually exclusively; by combining a circular diet with imported food and fully utilising waste streams, the lowest land use and GHG emissions can be realised.

Recoupling livestock and feed production in the Netherlands to reduce environmental impacts.

In many places on earth, livestock and feed production are decoupled, as feed is grown in one region and fed to livestock in another. This disrupts nutrient cycles by depleting resources in feed producing regions and accumulating resources in livestock areas, which leads to environmental degradation. One solution is to recouple livestock and feed production at a more local level, which enhances nutrient circularity. Recoupling livestock and feed production creates a natural ceiling for livestock numbers based on the feed producing capacity of a region. In this study we assess the consequences of recoupling livestock and feed production (i.e., by avoiding the import and export of animal feed) on ammonia and greenhouse gas (GHG) emissions, with and without feed-food competition. To this end, we used FOODSOM, an agro-ecological food system optimisation model representing the Dutch food system in this study. The Netherlands is one example of a region with high livestock densities and resource accumulation. We found that recoupling decreased livestock numbers (beef cattle: -100 %; dairy cattle: -29 %; broiler chickens: -57 %; laying hens: -67 %; pigs: -62 %; sheep -100 %) and animal-sourced food exports (-59 %) while still meeting the current human diet in the Netherlands. Consequently, ammonia emissions and GHG emissions decreased, and the nitrogen use efficiency increased from 31 % to 38 % at the food systems level. Recoupling alone was almost sufficient to meet national emission targets. Fully meeting these targets required further small changes in livestock numbers. Avoiding feed-food competition decreased livestock productivity and GHG emissions but did not improve nitrogen use efficiency. Total meat production could not meet domestic consumption levels while avoiding feed-food competition, and resulted in additional beef cattle. We show that recoupling livestock and feed production is a promising next step to enhance circularity while decreasing agricultures environmental impact.

Carbon for soils, not soils for carbon.

The role of soil organic carbon (SOC) sequestration as a 'win-win' solution to both climate change and food insecurity receives an increasing promotion. The opportunity may be too good to be missed! Yet the tremendous complexity of the two issues at stake calls for a detailed and nuanced examination of any potential solution, no matter how appealing. Here, we critically re-examine the benefits of global SOC sequestration strategies on both climate change mitigation and food production. While estimated contributions of SOC sequestration to climate change vary, almost none take SOC saturation into account. Here, we show that including saturation in estimations decreases any potential contribution of SOC sequestration to climate change mitigation by 53%-81% towards 2100. In addition, reviewing more than 21 meta-analyses, we found that observed yield effects of increasing SOC are inconsistent, ranging from negative to neutral to positive. We find that the promise of a win-win outcome is confirmed only when specific land management practices are applied under specific conditions. Therefore, we argue that the existing knowledge base does not justify the current trend to set global agendas focusing first and foremost on SOC sequestration. Away from climate-smart soils, we need a shift towards soil-smart agriculture, adaptative and adapted to each local context, and where multiple soil functions are quantified concurrently. Only such comprehensive assessments will allow synergies for land sustainability to be maximised and agronomic requirements for food security to be fulfilled. This implies moving away from global targets for SOC in agricultural soils. SOC sequestration may occur along this pathway and contribute to climate change mitigation and should be regarded as a co-benefit.

The legacy effect of synthetic N fertiliser.

Cumulative crop recovery of synthetic fertiliser nitrogen (N) over several cropping seasons (legacy effect) generally receives limited attention. The increment in crop N uptake after the first-season uptake from fertiliser can be expressed as a fraction (∆RE) of the annual N application rate. This study aims to quantify ∆RE using data from nine long-term experiments (LTEs). As such, ∆RE is the difference between first season (RE1st) and long-term (RELT) recovery of synthetic fertiliser N. In this study, RE1st was assessed either by the 15N isotope method or by a zero-N subplot freshly superimposed on a long-term fertilised LTE treatment plot. RELT was calculated by comparing N uptake in the total aboveground crop biomass between a long-term fertilised and long-term control (zero-N) treatment. Using a mixed linear effect model, the effects of climate, crop type, experiment duration, average N rate, and soil clay content on ∆RE were evaluated. Because the experimental setup required for the calculation of ∆RE is relatively rare, only nine suitable LTEs were found. Across these nine LTEs in Europe and North America, the mean ∆RE was 24.4% (±12.0%, 95% CI) of annual N application, with higher values for winter wheat than for maize. This result shows that fertiliser-N retained in the soil and stubble may contribute substantially to crop N uptake in subsequent years. Our results suggest that an initial recovery of 43.8% (±11%, 95% CI) of N application may increase to around 66.0% (±15%, 95% CI) on average over time. Furthermore, we found that ∆RE was not clearly related to long-term changes in topsoil total N stock. Our findings show that the-often used-first-year recovery of synthetic fertiliser N application does not express the full effect of fertiliser application on crop nutrition. The fertiliser contribution to soil N supply should be accounted for when exploring future scenarios on N cycling, including crop N requirements and N balance schemes. Highlights: Nine long-term cereal experiments in Europe and USA were analysed for long-term crop N recovery of synthetic N fertiliser.On average, and with application rates between 34 and 269 kg N/ha, crop N recovery increased from 43.8% in the first season to 66.0% in the long term.Delta recovery was larger for winter wheat than maize.Observed increases in crop N uptake were not explained by proportionate increases in topsoil total N stock.

Establishing long-term nitrogen response of global cereals to assess sustainable fertilizer rates.

Insight into the response of cereal yields to nitrogen fertilizer is fundamental to improving nutrient management and policies to sustain economic crop benefits and food sufficiency with minimum nitrogen pollution. Here we propose a new method to assess long-term (LT) regional sustainable nitrogen inputs. The core is a novel scaled response function between normalized yield and total net nitrogen input. The function was derived from 25 LT field trials for wheat, maize and barley in Europe, Asia and North America and is fitted by a second-order polynomial (R2 = 0.82). Using response functions derived from common short-term field trials, with soil nitrogen not in steady state, gives the risks of soil nitrogen depletion or nitrogen pollution. The scaled LT curve implies that the total nitrogen input required to attain the maximum yield is independent of this maximum yield as postulated by Mitscherlich in 1924. This unique curve was incorporated into a simple economic model with valuation of externalities of nitrogen surplus as a function of regional per-capita gross domestic product. The resulting LT sustainable nitrogen inputs range from 150 to 200 kgN ha-1 and this interval narrows with increasing yield potential and decreasing gross domestic product. The adoption of LT response curves and external costs in cereals may have important implications for policies and application ceilings for nitrogen use in regional and global agriculture and ultimately the global distribution of cereal production.

Circularity in animal production requires a change in the EAT-Lancet diet in Europe.

It is not known whether dietary guidelines proposing a limited intake of animal protein are compatible with the adoption of circular food systems. Using a resource-allocation model, we compared the effects of circularity on the supply of animal-source nutrients in Europe with the nutritional requirements of the EAT-Lancet reference diet. We found the two to be compatible in terms of total animal-source proteins but not specific animal-source foods; in particular, the EAT-Lancet guidelines recommend larger quantities of poultry meat over beef and pork, while a circular food system produces mainly milk, dairy-beef and pork. Compared with the EAT-Lancet reference diet, greenhouse gas emissions were reduced by up to 31% and arable land use reduced by up to 42%. Careful consideration of the feasible substitutability between animal-source foods is needed to define potential roles of animal products in circular human diets.

Regenerative Agriculture: An agronomic perspective.

Agriculture is in crisis. Soil health is collapsing. Biodiversity faces the sixth mass extinction. Crop yields are plateauing. Against this crisis narrative swells a clarion call for Regenerative Agriculture. But what is Regenerative Agriculture, and why is it gaining such prominence? Which problems does it solve, and how? Here we address these questions from an agronomic perspective. The term Regenerative Agriculture has actually been in use for some time, but there has been a resurgence of interest over the past 5 years. It is supported from what are often considered opposite poles of the debate on agriculture and food. Regenerative Agriculture has been promoted strongly by civil society and NGOs as well as by many of the major multi-national food companies. Many practices promoted as regenerative, including crop residue retention, cover cropping and reduced tillage are central to the canon of 'good agricultural practices', while others are contested and at best niche (e.g. permaculture, holistic grazing). Worryingly, these practices are generally promoted with little regard to context. Practices most often encouraged (such as no tillage, no pesticides or no external nutrient inputs) are unlikely to lead to the benefits claimed in all places. We argue that the resurgence of interest in Regenerative Agriculture represents a re-framing of what have been considered to be two contrasting approaches to agricultural futures, namely agroecology and sustainable intensification, under the same banner. This is more likely to confuse than to clarify the public debate. More importantly, it draws attention away from more fundamental challenges. We conclude by providing guidance for research agronomists who want to engage with Regenerative Agriculture.

Impacts of intensifying or expanding cereal cropping in sub-Saharan Africa on greenhouse gas emissions and food security.

Cropping is responsible for substantial emissions of greenhouse gasses (GHGs) worldwide through the use of fertilizers and through expansion of agricultural land and associated carbon losses. Especially in sub-Saharan Africa (SSA), GHG emissions from these processes might increase steeply in coming decades, due to tripling demand for food until 2050 to match the steep population growth. This study assesses the impact of achieving cereal self-sufficiency by the year 2050 for 10 SSA countries on GHG emissions related to different scenarios of increasing cereal production, ranging from intensifying production to agricultural area expansion. We also assessed different nutrient management variants in the intensification. Our analysis revealed that irrespective of intensification or extensification, GHG emissions of the 10 countries jointly are at least 50% higher in 2050 than in 2015. Intensification will come, depending on the nutrient use efficiency achieved, with large increases in nutrient inputs and associated GHG emissions. However, matching food demand through conversion of forest and grasslands to cereal area likely results in much higher GHG emissions. Moreover, many countries lack enough suitable land for cereal expansion to match food demand. In addition, we analysed the uncertainty in our GHG estimates and found that it is caused primarily by uncertainty in the IPCC Tier 1 coefficient for direct N2 O emissions, and by the agronomic nitrogen use efficiency (N-AE). In conclusion, intensification scenarios are clearly superior to expansion scenarios in terms of climate change mitigation, but only if current N-AE is increased to levels commonly achieved in, for example, the United States, and which have been demonstrated to be feasible in some locations in SSA. As such, intensifying cereal production with good agronomy and nutrient management is essential to moderate inevitable increases in GHG emissions. Sustainably increasing crop production in SSA is therefore a daunting challenge in the coming decades.

An Evaluation of the Plant Density Estimator the Point-Centred Quarter Method (PCQM) Using Monte Carlo Simulation.

BACKGROUND: In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns) plant populations and empirical ones. PRINCIPAL FINDINGS: PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N - 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N - 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published. SIGNIFICANCE: If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process. Since in practice, the spatial pattern of a plant association remains unknown before starting a vegetation survey, for field applications the use of PCQM3 along with the corrected estimator is recommended. However, for sparse plant populations, where the use of PCQM3 may pose practical limitations, the PCQM2 or PCQM1 would be applied. During application of PCQM in the field, care should be taken to summarize the distance data based on 'the inverse summation of squared distances' but not 'the summation of inverse squared distances' as erroneously published.

An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest.

In vegetation science and forest management, tree density is often used as a variable. To determine the value of this variable, reliable field methods are necessary. When vegetation is sparse or not easily accessible, the use of sample plots is not feasible in the field. Therefore, plotless methods, like the Point Centred Quarter Method, are often used as an alternative. In this study we investigate the accuracy of different plotless sampling methods. To this end, tree densities of a mangrove forest were determined and compared with estimates provided by several plotless methods. None of these methods proved accurate across all field sites with mean underestimations up to 97% and mean overestimations up to 53% in the field. Applying the methods to different vegetation patterns shows that when random spatial distributions were used the true density was included within the 95% confidence limits of all the plotless methods tested. It was also found that, besides aggregation and regularity, density trends often found in mangroves contribute to the unreliability. This outcome raises questions about the use of plotless sampling in forest monitoring and management, as well as for estimates of density-based carbon sequestration. We give recommendations to minimize errors in vegetation surveys and recommendations for further in-depth research.