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.

Calcium exerts a strong influence upon phosphohydrolase gene abundance and phylogenetic diversity in soil.

The mechanisms by which microbial communities maintain functions within the context of changing environments are key to a wide variety of environmental processes. In soil, these mechanisms support fertility. Genes associated with hydrolysis of organic phosphoesters represent an interesting set of genes with which to study maintenance of function in microbiomes. Here, we shown that the richness of ecotypes for each gene varies considerably in response to application of manure and various inorganic fertilizer combinations. We show, at unprecedented phylogenetic resolution, that phylogenetic diversity of phosphohydrolase genes are more responsive to soil management and edaphic factors than the taxonomic biomarker 16S rRNA gene. Available phosphorus - assessed by measuring Olsen-P - exerted some influence on alkaline phosphatase distribution: however, consistent and significant differences were observed in gene abundance between treatments that were inconsistent with bioavailable orthophosphate being the dominant factor determining gene abundance. Instead, we observed gene niche separation which was most strongly associated with soil exchangeable calcium. Our study suggests that the bioavailability of enzyme cofactors (exchangeable calcium in the case of phoD, phoX and ßPPhy studied here) influence the abundance of genes in soil microbial communities; in the absence of cofactors, genes coding for alternative enzyme families that do not require the limiting cofactor (for example, non-specific acid phosphatases which require vanadate) become more abundant.

The electronic Rothamsted Archive (e-RA), an online resource for data from the Rothamsted long-term experiments.

The electronic Rothamsted Archive, e-RA (www.era.rothamsted.ac.uk) provides a permanent managed database to both securely store and disseminate data from Rothamsted Research's long-term field experiments (since 1843) and meteorological stations (since 1853). Both historical and contemporary data are made available via this online database which provides the scientific community with access to a unique continuous record of agricultural experiments and weather measured since the mid-19th century. Qualitative information, such as treatment and management practices, plans and soil information, accompanies the data and are made available on the e-RA website. e-RA was released externally to the wider scientific community in 2013 and this paper describes its development, content, curation and the access process for data users. Case studies illustrate the diverse applications of the data, including its original intended purposes and recent unforeseen applications. Usage monitoring demonstrates the data are of increasing interest. Future developments, including adopting FAIR data principles, are proposed as the resource is increasingly recognised as a unique archive of data relevant to sustainable agriculture, agroecology and the environment.

Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK.

This paper describes an agricultural model (Roth-CNP) that estimates carbon (C), nitrogen (N) and phosphorus (P) pools, pool changes, their balance and the nutrient fluxes exported from arable and grassland systems in the UK during 1800-2010. The Roth-CNP model was developed as part of an Integrated Model (IM) to simulate C, N and P cycling for the whole of UK, by loosely coupling terrestrial, hydrological and hydro-chemical models. The model was calibrated and tested using long term experiment (LTE) data from Broadbalk (1843) and Park Grass (1856) at Rothamsted. We estimated C, N and P balance and their fluxes exported from arable and grassland systems on a 5km×5km grid across the whole of UK by using the area of arable of crops and livestock numbers in each grid and their management. The model estimated crop and grass yields, soil organic carbon (SOC) stocks and nutrient fluxes in the form of NH4-N, NO3-N and PO4-P. The simulated crop yields were compared to that reported by national agricultural statistics for the historical to the current period. Overall, arable land in the UK have lost SOC by -0.18, -0.25 and -0.08MgCha-1y-1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24MgCha-1y-1 during 1800-1950, 1950-1970 and 1970-2010 simulated in this study. Simulated N loss (by leaching, runoff, soil erosion and denitrification) increased both under arable (-15, -18 and -53kgNha-1y-1) and grass (-18, -22 and -36kgNha-1y-1) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1kgPha-1y-1 under arable and 2.8, 11.3 and 3.6kgPha-1y-1 under grass lands 1800-1950, 1950-1970 and 1970-2010.

The landscape model: A model for exploring trade-offs between agricultural production and the environment.

We describe a model framework that simulates spatial and temporal interactions in agricultural landscapes and that can be used to explore trade-offs between production and environment so helping to determine solutions to the problems of sustainable food production. Here we focus on models of agricultural production, water movement and nutrient flow in a landscape. We validate these models against data from two long-term experiments, (the first a continuous wheat experiment and the other a permanent grass-land experiment) and an experiment where water and nutrient flow are measured from isolated catchments. The model simulated wheat yield (RMSE 20.3-28.6%), grain N (RMSE 21.3-42.5%) and P (RMSE 20.2-29% excluding the nil N plots), and total soil organic carbon particularly well (RMSE3.1-13.8%), the simulations of water flow were also reasonable (RMSE 180.36 and 226.02%). We illustrate the use of our model framework to explore trade-offs between production and nutrient losses.

Communicating the uncertainty in estimated greenhouse gas emissions from agriculture.

In an effort to mitigate anthropogenic effects on the global climate system, industrialised countries are required to quantify and report, for various economic sectors, the annual emissions of greenhouse gases from their several sources and the absorption of the same in different sinks. These estimates are uncertain, and this uncertainty must be communicated effectively, if government bodies, research scientists or members of the public are to draw sound conclusions. Our interest is in communicating the uncertainty in estimates of greenhouse gas emissions from agriculture to those who might directly use the results from the inventory. We tested six methods of communication. These were: a verbal scale using the IPCC calibrated phrases such as 'likely' and 'very unlikely'; probabilities that emissions are within a defined range of values; confidence intervals for the expected value; histograms; box plots; and shaded arrays that depict the probability density of the uncertain quantity. In a formal trial we used these methods to communicate uncertainty about four specific inferences about greenhouse gas emissions in the UK. Sixty four individuals who use results from the greenhouse gas inventory professionally participated in the trial, and we tested how effectively the uncertainty about these inferences was communicated by means of a questionnaire. Our results showed differences in the efficacy of the methods of communication, and interactions with the nature of the target audience. We found that, although the verbal scale was thought to be a good method of communication it did not convey enough information and was open to misinterpretation. Shaded arrays were similarly criticised for being open to misinterpretation, but proved to give the best impression of uncertainty when participants were asked to interpret results from the greenhouse gas inventory. Box plots were most favoured by our participants largely because they were particularly favoured by those who worked in research or had a stronger mathematical background. We propose a combination of methods should be used to convey uncertainty in emissions and that this combination should be tailored to the professional group.