Grassland futures in Great Britain – Productivity assessment and scenarios for land use change opportunities

This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).To optimise trade-offs provided by future changes in grassland use intensity, spatially and temporally explicit estimates of respective grassland productivities are required at the systems level. Here, we benchmark the potential national availability of grassland biomass, identify optimal strategies for its management, and investigate the relative importance of intensification over reversion (prioritising productivity versus environmental ecosystem services). Process-conservative meta-models for different grasslands were used to calculate the baseline dry matter yields (DMY; 1961–1990) at 1 km2 resolution for the whole UK. The effects of climate change, rising atmospheric [CO2] and technological progress on baseline DMYs were used to estimate future grassland productivities (up to 2050) for low and medium CO2 emission scenarios of UKCP09. UK benchmark productivities of 12.5, 8.7 and 2.8 t/ha on temporary, permanent and rough-grazing grassland, respectively, accounted for productivity gains by 2010. By 2050, productivities under medium emission scenario are predicted to increase to 15.5 and 9.8 t/ha on temporary and permanent grassland, respectively, but not on rough grassland. Based on surveyed grassland distributions for Great Britain in 2010 the annual availability of grassland biomass is likely to rise from 64 to 72 million tonnes by 2050. Assuming optimal N application could close existing productivity gaps of ca. 40% a range of management options could deliver additional 21 ∗ 106 tonnes of biomass available for bioenergy. Scenarios of changes in grassland use intensity demonstrated considerable scope for maintaining or further increasing grassland production and sparing some grassland for the provision of environmental ecosystem services.Peer reviewedFinal Published versio

Climate factors contribute to grassland net primary productivity

Our call set out to enlarge the evidence base and methods for improving and evaluating grasslands in a changing environment as a sustainable ecosystem for all life [...

Environmental costs and benefits of growing Miscanthus for bioenergy in the UK

Funded by BBSRC. Grant Number: LK0863 Natural Environment Research Council (NERC) Carbo-BioCrop project. Grant Number: NE/H01067X/1 MAGLUE projectPeer reviewedPublisher PD

Optimizing the bioenergy water footprint by selecting SRC willow canopy phenotypes: regional scenario simulations

© The Author(s) 2019. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Background and Aims: Bioenergy is central for the future energy mix to mitigate climate change impacts; however, its intricate link with the water cycle calls for an evaluation of the carbon–water nexus in biomass production. The great challenge is to optimize trade-offs between carbon harvest and water use by choosing cultivars that combine low water use with high productivity. Methods: Regional scenarios were simulated over a range of willow genotype × environment interactions for the major UK soil × climate variations with the process-based model LUCASS. Soil available water capacity (SAWC) ranged from 51 to 251 mm and weather represented the north-west (wet, cool), north-east (dry, cool), south-west (wet, warm) and south-east (dry, warm) of the UK. Scenario simulations were evaluated for small/open narrow-leaf (NL) versus large/closed broad-leaf (BL) willow canopy phenotypes using baseline (1965–89) and warmer recent (1990–2014) weather data. Key Results: The low productivity under baseline climate in the north could be compensated by choosing BL cultivars (e.g. ‘Endurance’). Recent warmer climate increased average productivity by 0.5–2.5 t ha−1, especially in the north. The modern NL cultivar ‘Resolution’ had the smallest and most efficient water use. On marginal soils (SAWC <100 mm), yields remained below an economic threshold of 9 t ha−1 more frequently under baseline than recent climate. In the drought-prone south-east, ‘Endurance’ yielded less than ‘Resolution’, which consumed on average 17 mm year−1 less water. Assuming a planting area of 10 000 ha, in droughty years between 1.3 and 4.5 × 106 m3 of water could be saved, with a small yield penalty, for ‘Resolution’. Conclusions: With an increase in air temperature and occasional water scarcities expected with climate change, high-yielding NL cultivars should be the preferred choice for sustainable use of marginal lands and reduced competition with agricultural food crops.Peer reviewedFinal Published versio

Modelling the Interactions of Soils, Climate, and Management for Grass Production in England and Wales

This study examines the effectiveness of a model called LINGRA-N-Plus to simulate the interaction of climate, soil and management on the green leaf and total dry matter yields of ryegrass in England and Wales. The LINGRA-N-Plus model includes modifications of the LINGRA-N model such as temperature- and moisture-dependent soil nitrogen mineralization and differential partitioning to leaves and stems with thermal time from the last harvest. The resulting model was calibrated against the green leaf and total grass yields from a harvest interval x nitrogen application experiment described by Wilman et al. (1976). When the LINGRA-N-Plus model was validated against total grass yields from nitrogen experiments at ten sites described by Morrison et al. (1980), its modelling efficiency improved greatly compared to the original LINGRA-N. High predicted yields, at zero nitrogen application, were related to soils with a high initial nitrogen content. The lowest predicted yields occurred at sites with low rainfall and shallow rooting depth; mitigating the effect of drought at such sites increased yields by up to 4 t ha−1. The results highlight the usefulness of grass models, such as LINGRA-N-Plus, to explore the combined effects of climate, soil, and management, like nitrogen application, and harvest intervals on grass productivity

Investigating short-time-scale variations in cometary ions around comet 67P

The highly varying plasma environment around comet 67P/Churyumov–Gerasimenko inspired an upgrade of the ion mass spectrometer (Rosetta Plasma Consortium Ion Composition Analyzer) with new operation modes, to enable high time resolution measurements of cometary ions. Two modes were implemented, one having a 4 s time resolution in the energy range 0.3–82 eV/q and the other featuring a 1 s time resolution in the energy range 13–50 eV/q. Comparing measurements made with the two modes, it was concluded that 4 s time resolution is enough to capture most of the fast changes of the cometary ion environment. The 1462 h of observations done with the 4 s mode were divided into hour-long sequences. It is possible to sort 84 per cent of these sequences into one of five categories, depending on their appearance in an energy–time spectrogram. The ion environment is generally highly dynamic, and variations in ion fluxes and energies are seen on time-scales of 10 s to several minutes

Deriving wheat crop productivity indicators using Sentinel-1 time series

High-frequency Earth observation (EO) data have been shown to be effective in identifying crops and monitoring their development. The purpose of this paper is to derive quantitative indicators of crop productivity using synthetic aperture radar (SAR). This study shows that the field-specific SAR time series can be used to characterise growth and maturation periods and to estimate the performance of cereals. Winter wheat fields on the Rothamsted Research farm in Harpenden (UK) were selected for the analysis during three cropping seasons (2017 to 2019). Average SAR backscatter from Sentinel-1 satellites was extracted for each field and temporal analysis was applied to the backscatter cross-polarisation ratio (VH/VV). The calculation of the different curve parameters during the growing period involves (i) fitting of two logistic curves to the dynamics of the SAR time series, which describe timing and intensity of growth and maturation, respectively; (ii) plotting the associated first and second derivative in order to assist the determination of key stages in the crop development; and (iii) exploring the correlation matrix for the derived indicators and their predictive power for yield. The results show that the day of the year of the maximum VH/VV value was negatively correlated with yield (r = −0.56), and the duration of “full” vegetation was positively correlated with yield (r = 0.61). Significant seasonal variation in the timing of peak vegetation (p = 0.042), the midpoint of growth (p = 0.037), the duration of the growing season (p = 0.039) and yield (p = 0.016) were observed and were consistent with observations of crop phenology. Further research is required to obtain a more detailed picture of the uncertainty of the presented novel methodology, as well as its validity across a wider range of agroecosystem

Septic rupture of the ascending aorta after aortocoronary bypass surgery

We describe an exceptional case of non-fatal septic rupture of the ascending aorta in a patient with sternal dehiscence, deep sternal wound infection (DSWI) and pleural empyema after aortocoronary bypass surgery. Routine follow-up computed tomography (CT) detected a mediastinal pseudoaneurysm originating from the ascending aorta. Thereby, massive and irregular sternal bone defects and contrast-enhancing mediastinal soft tissue suggest osteomyelitis and highly-active and aggressive DSWI as initial triggers. Urgent thoracotomy 1 day later included ascending aorta reconstruction, total sternum resection and broad wound debridement. Follow-up CT 1 year later showed a regular postoperative result in a fully recovered patient

Translating and applying a simulation model to enhance understanding of grassland management

Each new generation of grassland managers could benefit from an improved understanding of how modification of nitrogen application and harvest dates in response to different weather and soil conditions will affect grass yields and quality. The purpose of this study was to develop a freely available grass yield simulation model, validated for England and Wales, and to examine its strengths and weaknesses as a teaching tool for improving grass management. The model, called LINGRA-N-Plus, was implemented in a Microsoft Excel spreadsheet and iteratively evaluated by students and practitioners (farmers, consultants, and researchers) in a series of workshops across the UK over 2 years. The iterative feedback led to the addition of new algorithms, an improved user interface, and the development of a teaching guide. The students and practitioners identified the ease of use and the capacity to understand, visualize and evaluate how decisions, such as variation of cutting intervals, affect grass yields as strengths of the model. We propose that an effective teaching tool must achieve an appropriate balance between being sufficiently detailed to demonstrate the major relationships (e.g., the effect of nitrogen on grass yields) whilst not becoming so complex that the relationships become incomprehensible. We observed that improving the user-interface allowed us to extend the scope of the model without reducing the level of comprehension. The students appeared to be interested in the explanatory nature of the model whilst the practitioners were more interested in the application of a validated model to enhance their decision making