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Under future CMIP5 climate change scenarios for 2050, an increase in wheat yield of about 10% is predicted in Great Britain (GB) as a result of the combined effect of CO 2 fertilization and a shift in phenology. Compared to the present day, crops escape increases in the climate impacts of drought and heat stresses on grain yield by developing before these stresses can occur. In the future, yield losses from water stress over a growing season will remain about the same across Great Britain with losses reaching around 20% of potential yield, while losses from drought around flowering will decrease and account for about 9% of water limited yield. Yield losses from heat stress around flowering will remain negligible in the future. These conclusions are drawn from a modelling study based on the response of the Sirius wheat simulation model to local-scale 2050-climate scenarios derived from 19 Global Climate Models from the CMIP5 ensemble at 25 locations representing current or potential wheat-growing areas in GB. However, depending on susceptibility to water stress, substantial interannual yield variation between locations is predicted, in some cases suggesting low wheat yield stability. For this reason, local-scale studies should be performed to evaluate uncertainties in yield prediction related to future weather patterns.
Thibaut Putelat; Andrew P. Whitmore; Nimai Senapati; Mikhail A. Semenov. Local impacts of climate change on winter wheat in Great Britain. Royal Society Open Science 2021, 8, 1 .
AMA StyleThibaut Putelat, Andrew P. Whitmore, Nimai Senapati, Mikhail A. Semenov. Local impacts of climate change on winter wheat in Great Britain. Royal Society Open Science. 2021; 8 (6):1.
Chicago/Turabian StyleThibaut Putelat; Andrew P. Whitmore; Nimai Senapati; Mikhail A. Semenov. 2021. "Local impacts of climate change on winter wheat in Great Britain." Royal Society Open Science 8, no. 6: 1.
Soil Quality or Soil Health are terms adopted by the scientific community as a metaphor for the effects of differing land management practices on the properties and functions of soil. Many other terms and metaphors are in use that defy neat quantification: human health, for example. Our challenge is to understand the importance of using such metaphors, but without compromising the underlying scientific understanding upon which they are based. We present here an approach based on expert elicitation in the field of soil quality and management, which offers a universal way of putting numbers to the metaphor. Like humans, soils differ and so do the ways in which they become unhealthy. We structure experts’ views of the extent to which soil delivers the functions expected of it within Bayesian Belief Networks anchored by measurable properties of soil. With these networks, we deduce the value of additional data to the precision of estimates of soil quality and health and infer the likely state of soil at locations in England & Wales. We conclude that the value of soil is best scored as its fitness for purpose or its utility. Our methodology has general applicability and could be deployed elsewhere or in other disciplines.
Andrew Whitmore; Kirsty Hassall; Alice Milne; Arthur Dailey; Margaret Glendining; Steve P. McGrath; Joanna Zawadzka; Jim Harris; Ron Corstanje; Aidan Keith; Lindsay Todman; Joanna Clark; Paul Alexander; Philippa Arnold; Amanda Bennett; Anne Bhogal; Felicity Crotty; Claire Horrocks; Nicola Noble; Robert Rees; Matthew Shepherd; Elizabeth Stockdale; E Tipping. Putting numbers to a metaphor: Soil Quality, Health or Fitness? 2021, 1 .
AMA StyleAndrew Whitmore, Kirsty Hassall, Alice Milne, Arthur Dailey, Margaret Glendining, Steve P. McGrath, Joanna Zawadzka, Jim Harris, Ron Corstanje, Aidan Keith, Lindsay Todman, Joanna Clark, Paul Alexander, Philippa Arnold, Amanda Bennett, Anne Bhogal, Felicity Crotty, Claire Horrocks, Nicola Noble, Robert Rees, Matthew Shepherd, Elizabeth Stockdale, E Tipping. Putting numbers to a metaphor: Soil Quality, Health or Fitness? . 2021; ():1.
Chicago/Turabian StyleAndrew Whitmore; Kirsty Hassall; Alice Milne; Arthur Dailey; Margaret Glendining; Steve P. McGrath; Joanna Zawadzka; Jim Harris; Ron Corstanje; Aidan Keith; Lindsay Todman; Joanna Clark; Paul Alexander; Philippa Arnold; Amanda Bennett; Anne Bhogal; Felicity Crotty; Claire Horrocks; Nicola Noble; Robert Rees; Matthew Shepherd; Elizabeth Stockdale; E Tipping. 2021. "Putting numbers to a metaphor: Soil Quality, Health or Fitness?" , no. : 1.
To manage agricultural landscapes more sustainably, we must understand and quantify the synergies and trade-offs between environmental impact, production, and other ecosystem services. Models play an important role in this type of analysis as generally it is infeasible to test multiple scenarios by experiment. These models can be linked with algorithms that optimise for multiple objectives by searching a space of allowable management interventions (the control variables). Optimisation of landscapes for multiple objectives can be computationally challenging, however, particularly if the scale of management is typically smaller (e.g. field scale) than the scale at which the objective is quantified (landscape scale) resulting in a large number of control variables whose impacts do not necessarily scale linearly. In this paper, we explore some practical solutions to this problem through a case study. In our case study, we link a relatively detailed, agricultural landscape model with a multiple-objective optimisation algorithm to determine solutions that both maximise profitability and minimise greenhouse gas emissions in response to management. The optimisation algorithm combines a non-dominated sorting routine with differential evolution, whereby a ‘population’ of 100 solutions evolves over time to a Pareto optimal front. We show the advantages of using a hierarchical approach to the optimisation, whereby it is applied to finer-scale units first (i.e. fields), and then the solutions from each optimisation are combined in a second step to produce landscape-scale outcomes. We show that if there is no interaction between units, then the solution derived using such an approach will be the same as the one obtained if the landscape is optimised in one step. However, if there is spatial interaction, or if there are constraints on the allowable sets of solutions, then outcomes can be quite different. In these cases, other approaches to increase the efficiency of the optimisation may be more appropriate—such as initialising the control variables for half of the population of solutions with values expected to be near optimal. Our analysis shows the importance of aligning a policy or management recommendation with the appropriate scale.
Alice E. Milne; Kevin Coleman; Lindsay C. Todman; Andrew P. Whitmore. Model-based optimisation of agricultural profitability and nutrient management: a practical approach for dealing with issues of scale. Environmental Monitoring and Assessment 2020, 192, 1 -13.
AMA StyleAlice E. Milne, Kevin Coleman, Lindsay C. Todman, Andrew P. Whitmore. Model-based optimisation of agricultural profitability and nutrient management: a practical approach for dealing with issues of scale. Environmental Monitoring and Assessment. 2020; 192 (11):1-13.
Chicago/Turabian StyleAlice E. Milne; Kevin Coleman; Lindsay C. Todman; Andrew P. Whitmore. 2020. "Model-based optimisation of agricultural profitability and nutrient management: a practical approach for dealing with issues of scale." Environmental Monitoring and Assessment 192, no. 11: 1-13.
Crop residues are valuable soil amendments in terms of the carbon and other nutrients they contain, but the incorporation of residues does not always translate into increases in nutrient availability, soil organic matter (SOM), soil structure, and overall soil fertility. Studies have demonstrated accelerated decomposition rates of chemically heterogeneous litter mixtures, compared to the decomposition of individual litters, in forest and grassland systems. Mixing high C:N ratio with low C:N ratio amendments may result in greater carbon use efficiency (CUE) and nonadditive benefits in soil properties. We hypothesised that nonadditive benefits would accrue from mixtures of low-quality (straw or woodchips) and high-quality (vegetable waste compost) residues applied before lettuce planting in a full factorial field experiment. Properties indicative of soil structure and nutrient cycling were used to assess the benefits from residue mixtures, including soil respiration, aggregate stability, bulk density, SOM, available N, potentially mineralisable N, available P, K, and Mg, and crop yield. Soil organic matter and mineral N levels were significantly and nonadditively greater in the straw–compost mixture compared to individual residues, which mitigated the N immobilisation occurring with straw-only applications. The addition of compost significantly increased available N, K, and Mg levels. Together, these observations suggest that greater nutrient availability improved the ability of decomposer organisms to degrade straw in the straw–compost mixture. We demonstrate that mixtures of crop residues can influence soil properties nonadditively. Thus, greater benefits may be achieved by removing, mixing, and reapplying crop residues than by simply returning them to the soils in situ.
Marijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures. SOIL 2020, 6, 467 -481.
AMA StyleMarijke Struijk, Andrew P. Whitmore, Simon R. Mortimer, Tom Sizmur. Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures. SOIL. 2020; 6 (2):467-481.
Chicago/Turabian StyleMarijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. 2020. "Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures." SOIL 6, no. 2: 467-481.
Irrigated dryland agroecosystems could become more sustainable if crop and soil management enhanced soil organic carbon (SOC). We hypothesized that combining high inputs from cover crops with no-tillage will increase long-term SOC stocks. Caatinga shrublands had been cleared in 1972 for arable crops and palm plantations before implementing field experiments on Mango and Melon systems (established in 2009 and 2012, respectively). Each of the two experiments were managed with no-till (NT) or conventional till (CT), and three types of cover cropping, either a plant mixture of 75% (PM1) or 25% (PM2) legumes, or spontaneous vegetation (SV). The RothC model was used with a daily timestep to simulate the soil moisture dynamics and C turnover for this dry climate. Carbon inputs were between 2.62 and 5.82 Mg C ha−1 year−1 and increased the depleted SOC stocks by 0.08 to 0.56 Mg C ha−1 year−1. Scenarios of continuous biomass inputs of ca. 5 Mg C ha−1 year−1 for 60 years are likely to increase SOC stocks in the mango NT beyond the original Caatinga SOC by between 19.2 and 20.5 Mg C ha−1. Under CT similar inputs would increase SOC stocks only marginally above depletion (2.75 to 2.47 Mg C ha−1). Under melon, annual carbon inputs are slightly greater (up to 5.5 Mg C ha−1 year−1) and SOC stocks would increase on average by another 8% to 22.3 to 20.6 Mg C ha−1 under NT and by 8 Mg C ha−1 under CT. These long-term simulations show that combining NT with high quality cover crops (PM1, PM2) would exceed SOC stocks of the initial Caatinga within 20 and 25 years under irrigated melon and mango cultivation, respectively. These results present a solution to reverse prior loss of SOC by replacing CT dryland agriculture with irrigated NT plus high input cover crops agroecosystems.
Vanderlise Giongo; Kevin Coleman; Monica Da Silva Santana; Alessandra Monteiro Salviano; Nelci Olszveski; Davi Jose Silva; Tony Jarbas Ferreira Cunha; Angelucia Parente; Andrew Whitmore; Goetz Richter. Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon – Experiments and modelling. Science of The Total Environment 2020, 725, 138072 .
AMA StyleVanderlise Giongo, Kevin Coleman, Monica Da Silva Santana, Alessandra Monteiro Salviano, Nelci Olszveski, Davi Jose Silva, Tony Jarbas Ferreira Cunha, Angelucia Parente, Andrew Whitmore, Goetz Richter. Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon – Experiments and modelling. Science of The Total Environment. 2020; 725 ():138072.
Chicago/Turabian StyleVanderlise Giongo; Kevin Coleman; Monica Da Silva Santana; Alessandra Monteiro Salviano; Nelci Olszveski; Davi Jose Silva; Tony Jarbas Ferreira Cunha; Angelucia Parente; Andrew Whitmore; Goetz Richter. 2020. "Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon – Experiments and modelling." Science of The Total Environment 725, no. : 138072.
Marijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. Supplementary material to "Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures". 2020, 1 .
AMA StyleMarijke Struijk, Andrew P. Whitmore, Simon R. Mortimer, Tom Sizmur. Supplementary material to "Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures". . 2020; ():1.
Chicago/Turabian StyleMarijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. 2020. "Supplementary material to "Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures"." , no. : 1.
Crop residues are valuable soil amendments in terms of the carbon and other nutrients they contain, but incorporation of residues does not always translate into increases in nutrient availability, soil organic matter (SOM), soil structure, and overall soil fertility. Studies have demonstrated accelerated decomposition rates of chemically heterogeneous litter mixtures, compared to the decomposition of individual litters, in forest and grassland systems. Mixing high C : N ratio with low C : N ratio amendments may result in greater carbon use efficiency and non-additive benefits in soil properties (i.e. mixture ≠ sum of the parts). We hypothesised that non-additive benefits would accrue from mixtures of low-quality (straw or woodchips) and high-quality (vegetable-waste compost) residues applied before lettuce planting in a full-factorial field experiment. Properties indicative of soil structure and nutrient cycling were used to assess benefits from residue mixtures, including soil respiration, aggregate stability, bulk density, SOM, available and potentially mineralisable N, available P, K and Mg, and crop yield. Soil organic matter and mineral nitrogen levels were significantly and non-additively greater in the straw-compost mixture compared to individual residues, which mitigated the N immobilisation occurring with straw-only applications. Addition of compost significantly increased soil available N, K and Mg levels. Together, these observations suggest that greater nutrient availability improved the ability of decomposer organisms to degrade straw in the straw-compost mixture. We demonstrate that mixtures of crop residues can influence soil properties non-additively. Thus, greater benefits may be achieved by removing, mixing, and re-applying crop residues, than by simply returning them to the soils in situ.
Marijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures. 2020, 1 -22.
AMA StyleMarijke Struijk, Andrew P. Whitmore, Simon R. Mortimer, Tom Sizmur. Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures. . 2020; ():1-22.
Chicago/Turabian StyleMarijke Struijk; Andrew P. Whitmore; Simon R. Mortimer; Tom Sizmur. 2020. "Obtaining more benefits from crop residues as soil amendments by application as chemically heterogeneous mixtures." , no. : 1-22.
At present, organic fertilizers are not widely used in intensive arable agriculture, and not much is known about their effects on crop nutrition. In a field experiment at Rothamsted, UK, anaerobic digestate (AD), compost, farmyard manure (FYM), straw, and mixes of amendment + straw, were applied at: 1, 1.75, 2.5 or 3.5 t carbon ha−1, with all plots receiving the same input of mineral fertilizer. After five seasons of application, plots receiving non-straw amendments had greater straw and grain yield of 28% and 18% respectively, and plots receiving the highest amendment rate had a 37% higher straw and 23% higher grain yield, compared to control plots. Whereas, the straw-only amendment did not increase yield compared to the control. The concentrations of secondary and micro nutrients in the crop, particularly P, Ca, and S in the straw, and P and Fe in the grain, were significantly greater in the crop receiving non-straw amendment compared to the control. Interestingly K, Fe, and Zn were greater in the crop straw treated with the straw-only amendment. Therefore ‘biomass dilution’ of secondary and micro nutrients did not occur in the higher-yielding amended plots after five seasons, and organic fertilizers would improve the quality of high-yielding, intensively produced crops. The study also demonstrates that portable x-ray fluorescence (pXRF) could be a reliable, cost-effective tool for screening potential organic fertilizers.
Cathy L. Thomas; Gifty E. Acquah; Andrew P. Whitmore; Steve P. McGrath; Stephan M. Haefele. The Effect of Different Organic Fertilizers on Yield and Soil and Crop Nutrient Concentrations. Agronomy 2019, 9, 776 .
AMA StyleCathy L. Thomas, Gifty E. Acquah, Andrew P. Whitmore, Steve P. McGrath, Stephan M. Haefele. The Effect of Different Organic Fertilizers on Yield and Soil and Crop Nutrient Concentrations. Agronomy. 2019; 9 (12):776.
Chicago/Turabian StyleCathy L. Thomas; Gifty E. Acquah; Andrew P. Whitmore; Steve P. McGrath; Stephan M. Haefele. 2019. "The Effect of Different Organic Fertilizers on Yield and Soil and Crop Nutrient Concentrations." Agronomy 9, no. 12: 776.
Expert opinion is increasingly being used to inform Bayesian Belief Networks, in particular to define the conditional dependencies modelled by the graphical structure. The elicitation of such expert opinion remains a major challenge due to both the quantity of information required and the ability of experts to quantify subjective beliefs effectively. In this work, we introduce a method designed to initialise conditional probability tables based on a small number of simple questions that capture the overall shape of a conditional probability distribution before enabling the expert to refine their results in an efficient way. These methods have been incorporated into a software Application for Conditional probability Elicitation (ACE), freely available at https://github.com/KirstyLHassall/ACE (Hassall, 2019).
Kirsty L. Hassall; Gordon Dailey; Joanna Zawadzka; Alice E. Milne; Jim Harris; Ron Corstanje; Andrew P. Whitmore. Facilitating the elicitation of beliefs for use in Bayesian Belief modelling. Environmental Modelling & Software 2019, 122, 104539 .
AMA StyleKirsty L. Hassall, Gordon Dailey, Joanna Zawadzka, Alice E. Milne, Jim Harris, Ron Corstanje, Andrew P. Whitmore. Facilitating the elicitation of beliefs for use in Bayesian Belief modelling. Environmental Modelling & Software. 2019; 122 ():104539.
Chicago/Turabian StyleKirsty L. Hassall; Gordon Dailey; Joanna Zawadzka; Alice E. Milne; Jim Harris; Ron Corstanje; Andrew P. Whitmore. 2019. "Facilitating the elicitation of beliefs for use in Bayesian Belief modelling." Environmental Modelling & Software 122, no. : 104539.
Agricultural landscapes provide many functions simultaneously including food production, regulation of water and regulation of greenhouse gases. Thus, it is challenging to make land management decisions, particularly transformative changes, that improve on one function without unintended consequences for other functions. To make informed decisions the trade-offs between different landscape functions must be considered. Here, we use a multi-objective optimization algorithm with a model of crop production that also simulates environmental effects such as nitrous oxide emissions to identify trade-off frontiers and associated possibilities for agricultural management. Trade-offs are identified in three soil types, using wheat production in the UK as an example, then the trade-off for combined management of the three soils is considered. The optimization algorithm identifies trade-offs between different objectives and allows them to be visualised. For example, we observed a highly non-linear trade-off between wheat yield and nitrous oxide emissions, illustrating where small changes might have a large impact. We used a cluster analysis to identify distinct management strategies with similar management actions and use these clusters to link the trade-off curves to possibilities for management. There were more possible strategies for achieving desirable environmental outcomes and remaining profitable when the management of different soil types was considered together. Interestingly, it was on the soil capable of the highest potential profit that lower profit strategies were identified as useful for combined management. Meanwhile, to maintain average profitability across the soils, it was necessary to maximise the profit from the soil with the lowest potential profit. These results are somewhat counterintuitive and so the range of strategies supplied by the model could be used to stimulate discussion amongst stakeholders. In particular, as some key objectives can be met in different ways, stakeholders could discuss the impact of these management strategies on other objectives not quantified by the model.
Lindsay C. Todman; Kevin Coleman; Alice Milne; Juliana D.B. Gil; Pytrik Reidsma; Marie-Hélène Schwoob; Sébastien Treyer; Andrew Whitmore. Multi-objective optimization as a tool to identify possibilities for future agricultural landscapes. Science of The Total Environment 2019, 687, 535 -545.
AMA StyleLindsay C. Todman, Kevin Coleman, Alice Milne, Juliana D.B. Gil, Pytrik Reidsma, Marie-Hélène Schwoob, Sébastien Treyer, Andrew Whitmore. Multi-objective optimization as a tool to identify possibilities for future agricultural landscapes. Science of The Total Environment. 2019; 687 ():535-545.
Chicago/Turabian StyleLindsay C. Todman; Kevin Coleman; Alice Milne; Juliana D.B. Gil; Pytrik Reidsma; Marie-Hélène Schwoob; Sébastien Treyer; Andrew Whitmore. 2019. "Multi-objective optimization as a tool to identify possibilities for future agricultural landscapes." Science of The Total Environment 687, no. : 535-545.
• There exist three distinct types of data sparsity that inhibit the formation of spatially coherent zones. • By defining a neighbourhood of points through the Voronoi partition, the effects of spatial sparsity can be avoided. • Observed data points are often not co-located, resulting in big data losses through current methods. • By implementing missing data approaches within the clustering algorithms, data loss can be mitigated.
Kirsty L. Hassall; Andrew P. Whitmore; Alice E. Milne. Accounting for data sparsity when forming spatially coherent zones. Applied Mathematical Modelling 2019, 72, 537 -552.
AMA StyleKirsty L. Hassall, Andrew P. Whitmore, Alice E. Milne. Accounting for data sparsity when forming spatially coherent zones. Applied Mathematical Modelling. 2019; 72 ():537-552.
Chicago/Turabian StyleKirsty L. Hassall; Andrew P. Whitmore; Alice E. Milne. 2019. "Accounting for data sparsity when forming spatially coherent zones." Applied Mathematical Modelling 72, no. : 537-552.
Andrew Balmford; Tatsuya Amano; Harriet Bartlett; Dave Chadwick; Adrian Collins; David Edwards; Rob Field; Philip Garnsworthy; Rhys Green; Pete Smith; Helen Waters; Andrew Whitmore; Donald M. Broom; Julian Chara; Tom Finch; Emma Garnett; Alfred Gathorne-Hardy; Juan Hernandez-Medrano; Mario Herrero; Fangyuan Hua; Agnieszka Latawiec; Tom Misselbrook; Ben Phalan; Benno I. Simmons; Taro Takahashi; James Vause; Erasmus Zu Ermgassen; Rowan Eisner. Author Correction: The environmental costs and benefits of high-yield farming. Nature Sustainability 2019, 2, 339 -341.
AMA StyleAndrew Balmford, Tatsuya Amano, Harriet Bartlett, Dave Chadwick, Adrian Collins, David Edwards, Rob Field, Philip Garnsworthy, Rhys Green, Pete Smith, Helen Waters, Andrew Whitmore, Donald M. Broom, Julian Chara, Tom Finch, Emma Garnett, Alfred Gathorne-Hardy, Juan Hernandez-Medrano, Mario Herrero, Fangyuan Hua, Agnieszka Latawiec, Tom Misselbrook, Ben Phalan, Benno I. Simmons, Taro Takahashi, James Vause, Erasmus Zu Ermgassen, Rowan Eisner. Author Correction: The environmental costs and benefits of high-yield farming. Nature Sustainability. 2019; 2 (4):339-341.
Chicago/Turabian StyleAndrew Balmford; Tatsuya Amano; Harriet Bartlett; Dave Chadwick; Adrian Collins; David Edwards; Rob Field; Philip Garnsworthy; Rhys Green; Pete Smith; Helen Waters; Andrew Whitmore; Donald M. Broom; Julian Chara; Tom Finch; Emma Garnett; Alfred Gathorne-Hardy; Juan Hernandez-Medrano; Mario Herrero; Fangyuan Hua; Agnieszka Latawiec; Tom Misselbrook; Ben Phalan; Benno I. Simmons; Taro Takahashi; James Vause; Erasmus Zu Ermgassen; Rowan Eisner. 2019. "Author Correction: The environmental costs and benefits of high-yield farming." Nature Sustainability 2, no. 4: 339-341.
Developing sustainable food systems is essential, especially for emerging economies, where food systems are changing rapidly and affect the environment and natural resources. We explored possible future pathways for a sustainable food system in China, using multiple environmental indicators linked to eight of the Sustainable Development Goals (SDGs). Forecasts for 2030 in a business as usual scenario (BAU) indicate increases in animal food consumption as well as increased shortages of the land available and the water needed to produce the required food in China. Associated greenhouse gas emissions and nitrogen and phosphorus losses could become 10-42% of global emissions in 2010. We developed three main pathways besides BAU [produce more and better food (PMB), consume and waste less food (CWL), and import more food (IMF)] and analyzed their impacts and contributions to achieving one or more of the eight SDGs. Under these scenarios, the demand for land and water and the emissions of GHG and nutrients may decrease by 7-55% compared to BAU, depending on the pathway followed. A combination of PMB and CWL was most effective, while IMF externalizes impacts to countries exporting to China. Modestly increasing feed or food imports in a selective manner could ease the pressure on natural resources. Our modeling framework allows us to analyze the effects of changes in food production-consumption systems in an integrated manner, and the results can be linked to the eight SDGs. Despite formidable technological, social, educational, and structural barriers that need to be overcome, our study indicates that the ambitious targets of China's new agricultural and environmental strategy appear to be achievable.
Lin Ma; Zhaohai Bai; Wenqi Ma; Mengchu Guo; Rongfeng Jiang; Junguo Liu; Oene Oenema; Gerard Velthof; Andrew Whitmore; John Crawford; Achim Dobermann; Marie Schwoob; Fusuo Zhang. Exploring Future Food Provision Scenarios for China. Environmental Science & Technology 2018, 53, 1385 -1393.
AMA StyleLin Ma, Zhaohai Bai, Wenqi Ma, Mengchu Guo, Rongfeng Jiang, Junguo Liu, Oene Oenema, Gerard Velthof, Andrew Whitmore, John Crawford, Achim Dobermann, Marie Schwoob, Fusuo Zhang. Exploring Future Food Provision Scenarios for China. Environmental Science & Technology. 2018; 53 (3):1385-1393.
Chicago/Turabian StyleLin Ma; Zhaohai Bai; Wenqi Ma; Mengchu Guo; Rongfeng Jiang; Junguo Liu; Oene Oenema; Gerard Velthof; Andrew Whitmore; John Crawford; Achim Dobermann; Marie Schwoob; Fusuo Zhang. 2018. "Exploring Future Food Provision Scenarios for China." Environmental Science & Technology 53, no. 3: 1385-1393.
The pursuit of global food security and agricultural sustainability, the dual aim of the second sustainable development goal (SDG-2), requires urgent and concerted action from developing and developed countries. This, in turn, depends on clear and universally applicable targets and indicators which are partially lacking. The novel and complex nature of the SDGs poses further challenges to their implementation on the ground, especially in the face of interlinkages across SDG objectives and scales. Here we review the existing SDG-2 indicators, propose improvements to facilitate their operationalization, and illustrate their practical implementation in Nigeria, Brazil and the Netherlands. This exercise provides insights into the concrete actions needed to achieve SDG-2 across contrasting development contexts and highlights the challenges of addressing the links between targets and indicators within and beyond SDG-2. Ultimately, it underscores the need for integrated policies and reveals opportunities to leverage the fulfillment of SDG-2 worldwide.
Juliana Dias Bernardes Gil; Pytrik Reidsma; Ken Giller; Lindsay Todman; Andrew Whitmore; Martin Van Ittersum. Sustainable development goal 2: Improved targets and indicators for agriculture and food security. Ambio 2018, 48, 685 -698.
AMA StyleJuliana Dias Bernardes Gil, Pytrik Reidsma, Ken Giller, Lindsay Todman, Andrew Whitmore, Martin Van Ittersum. Sustainable development goal 2: Improved targets and indicators for agriculture and food security. Ambio. 2018; 48 (7):685-698.
Chicago/Turabian StyleJuliana Dias Bernardes Gil; Pytrik Reidsma; Ken Giller; Lindsay Todman; Andrew Whitmore; Martin Van Ittersum. 2018. "Sustainable development goal 2: Improved targets and indicators for agriculture and food security." Ambio 48, no. 7: 685-698.
How we manage farming and food systems to meet rising demand is pivotal to the future of biodiversity. Extensive field data suggest that impacts on wild populations would be greatly reduced through boosting yields on existing farmland so as to spare remaining natural habitats. High-yield farming raises other concerns because expressed per unit area it can generate high levels of externalities such as greenhouse gas emissions and nutrient losses. However, such metrics underestimate the overall impacts of lower-yield systems. Here we develop a framework that instead compares externality and land costs per unit production. We apply this framework to diverse data sets that describe the externalities of four major farm sectors and reveal that, rather than involving trade-offs, the externality and land costs of alternative production systems can covary positively: per unit production, land-efficient systems often produce lower externalities. For greenhouse gas emissions, these associations become more strongly positive once forgone sequestration is included. Our conclusions are limited: remarkably few studies report externalities alongside yields; many important externalities and farming systems are inadequately measured; and realizing the environmental benefits of high-yield systems typically requires additional measures to limit farmland expansion. Nevertheless, our results suggest that trade-offs among key cost metrics are not as ubiquitous as sometimes perceived.
Andrew Balmford; Tatsuya Amano; Harriet Bartlett; Dave Chadwick; Adrian Collins; David Edwards; Rob Field; Philip Garnsworthy; Rhys Green; Pete Smith; Helen Waters; Andrew Whitmore; Donald M. Broom; Julián Chará; Tom Finch; Emma Garnett; Alfred Gathorne-Hardy; Juan Hernandez-Medrano; Mario Herrero; Fangyuan Hua; Agnieszka Latawiec; Tom Misselbrook; Ben Phalan; Benno I. Simmons; Taro Takahashi; James Vause; Erasmus Zu Ermgassen; Rowan Eisner. The environmental costs and benefits of high-yield farming. Nature Sustainability 2018, 1, 477 -485.
AMA StyleAndrew Balmford, Tatsuya Amano, Harriet Bartlett, Dave Chadwick, Adrian Collins, David Edwards, Rob Field, Philip Garnsworthy, Rhys Green, Pete Smith, Helen Waters, Andrew Whitmore, Donald M. Broom, Julián Chará, Tom Finch, Emma Garnett, Alfred Gathorne-Hardy, Juan Hernandez-Medrano, Mario Herrero, Fangyuan Hua, Agnieszka Latawiec, Tom Misselbrook, Ben Phalan, Benno I. Simmons, Taro Takahashi, James Vause, Erasmus Zu Ermgassen, Rowan Eisner. The environmental costs and benefits of high-yield farming. Nature Sustainability. 2018; 1 (9):477-485.
Chicago/Turabian StyleAndrew Balmford; Tatsuya Amano; Harriet Bartlett; Dave Chadwick; Adrian Collins; David Edwards; Rob Field; Philip Garnsworthy; Rhys Green; Pete Smith; Helen Waters; Andrew Whitmore; Donald M. Broom; Julián Chará; Tom Finch; Emma Garnett; Alfred Gathorne-Hardy; Juan Hernandez-Medrano; Mario Herrero; Fangyuan Hua; Agnieszka Latawiec; Tom Misselbrook; Ben Phalan; Benno I. Simmons; Taro Takahashi; James Vause; Erasmus Zu Ermgassen; Rowan Eisner. 2018. "The environmental costs and benefits of high-yield farming." Nature Sustainability 1, no. 9: 477-485.
Soils are fundamental to terrestrial ecosystem functioning and food security, thus their resilience to disturbances is critical. Furthermore, they provide effective models of complex natural systems to explore resilience concepts over experimentally-tractable short timescales. We studied soils derived from experimental plots with different land-use histories of long-term grass, arable and fallow to determine whether regimes of extreme drying and re-wetting would tip the systems into alternative stable states, contingent on their historical management. Prior to disturbance, grass and arable soils produced similar respiration responses when processing an introduced complex carbon substrate. A distinct respiration response from fallow soil here indicated a different prior functional state. Initial dry:wet disturbances reduced the respiration in all soils, suggesting that the microbial community was perturbed such that its function was impaired. After 12 drying and rewetting cycles, despite the extreme disturbance regime, soil from the grass plots, and those that had recently been grass, adapted and returned to their prior functional state. Arable soils were less resilient and shifted towards a functional state more similar to that of the fallow soil. Hence repeated stresses can apparently induce persistent shifts in functional states in soils, which are influenced by management history.
L. C. Todman; Fiona Fraser; R. Corstanje; J. A. Harris; M. Pawlett; K. Ritz; A. P. Whitmore. Evidence for functional state transitions in intensively-managed soil ecosystems. Scientific Reports 2018, 8, 11522 .
AMA StyleL. C. Todman, Fiona Fraser, R. Corstanje, J. A. Harris, M. Pawlett, K. Ritz, A. P. Whitmore. Evidence for functional state transitions in intensively-managed soil ecosystems. Scientific Reports. 2018; 8 (1):11522.
Chicago/Turabian StyleL. C. Todman; Fiona Fraser; R. Corstanje; J. A. Harris; M. Pawlett; K. Ritz; A. P. Whitmore. 2018. "Evidence for functional state transitions in intensively-managed soil ecosystems." Scientific Reports 8, no. 1: 11522.
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 5 km × 5 km 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 −0.08 Mg C ha−1 y−1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24 Mg C ha−1 y−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 −53 kg N ha−1 y−1) and grass (−18, −22 and −36 kg N ha−1 y−1) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1 kg P ha−1 y−1 under arable and 2.8, 11.3 and 3.6 kg P ha−1 y−1 under grass lands 1800–1950, 1950–1970 and 1970–2010.
Shibu E. Muhammed; Kevin Coleman; Lianhai Wu; Victoria A. Bell; Jessica A.C. Davies; John N. Quinton; Edward J. Carnell; Samuel J. Tomlinson; Anthony J. Dore; Ulrike Dragosits; Pamela S. Naden; Margaret J. Glendining; Edward Tipping; Andrew P. Whitmore. Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK. Science of The Total Environment 2018, 634, 1486 -1504.
AMA StyleShibu E. Muhammed, Kevin Coleman, Lianhai Wu, Victoria A. Bell, Jessica A.C. Davies, John N. Quinton, Edward J. Carnell, Samuel J. Tomlinson, Anthony J. Dore, Ulrike Dragosits, Pamela S. Naden, Margaret J. Glendining, Edward Tipping, Andrew P. Whitmore. Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK. Science of The Total Environment. 2018; 634 ():1486-1504.
Chicago/Turabian StyleShibu E. Muhammed; Kevin Coleman; Lianhai Wu; Victoria A. Bell; Jessica A.C. Davies; John N. Quinton; Edward J. Carnell; Samuel J. Tomlinson; Anthony J. Dore; Ulrike Dragosits; Pamela S. Naden; Margaret J. Glendining; Edward Tipping; Andrew P. Whitmore. 2018. "Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK." Science of The Total Environment 634, no. : 1486-1504.
S.M. Donaldson; I.C. Dodd; A.P. Whitmore. Soil bulk density impacts on root water potential and ABA export in drying soil. Acta Horticulturae 2018, 15 -22.
AMA StyleS.M. Donaldson, I.C. Dodd, A.P. Whitmore. Soil bulk density impacts on root water potential and ABA export in drying soil. Acta Horticulturae. 2018; (1197):15-22.
Chicago/Turabian StyleS.M. Donaldson; I.C. Dodd; A.P. Whitmore. 2018. "Soil bulk density impacts on root water potential and ABA export in drying soil." Acta Horticulturae , no. 1197: 15-22.
Nitrogen (N) supply from organic amendments [such as farmyard manure (FYM), slurries or crop residues] to crops is commonly expressed in the amendment’s Nitrogen Fertiliser Replacement Value (NFRV). Values for NFRV can be determined by comparison of crop yield or N uptake in amended plots against mineral fertiliser-only plots. NFRV is then defined as the amount of mineral fertiliser N saved when using organic amendment-N (kg/kg), while attaining the same crop yield. Factors known to affect NFRV are crop type cultivated, soil type, manuring history and method or time of application. We investigated whether long-term NFRV depends on N application rates. Using data from eight long term experiments in Europe, values of NFRV at low total N supply were compared with values of NFRV at high total N supply. Our findings show that FYM has a significant higher NFRV value at high total N supply than at low total N supply (1.12 vs. 0.53, p = 0.04). For the other amendment types investigated, NFRV was also higher at high total N supply than at low total N supply, but sample sizes were too small or variations too large to detect significant differences. Farmers in Europe usually operate at high rates of total N applied. If fertiliser supplements are based on NFRV of the manure estimated at low total N supply, N fertiliser requirements might be overestimated. This might lead to overuse of N, lower N use efficiency and larger losses of N to the environment.
R. Hijbeek; H. F. M. Ten Berge; Andrew Whitmore; D. Barkusky; J. J. Schröder; Martin van Ittersum. Nitrogen fertiliser replacement values for organic amendments appear to increase with N application rates. Nutrient Cycling in Agroecosystems 2017, 110, 105 -115.
AMA StyleR. Hijbeek, H. F. M. Ten Berge, Andrew Whitmore, D. Barkusky, J. J. Schröder, Martin van Ittersum. Nitrogen fertiliser replacement values for organic amendments appear to increase with N application rates. Nutrient Cycling in Agroecosystems. 2017; 110 (1):105-115.
Chicago/Turabian StyleR. Hijbeek; H. F. M. Ten Berge; Andrew Whitmore; D. Barkusky; J. J. Schröder; Martin van Ittersum. 2017. "Nitrogen fertiliser replacement values for organic amendments appear to increase with N application rates." Nutrient Cycling in Agroecosystems 110, no. 1: 105-115.
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 (RMSE 3.1 − 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.
Kevin Coleman; Shibu E. Muhammed; Alice E. Milne; Lindsay C. Todman; A. Gordon Dailey; Margaret J. Glendining; Andrew Whitmore; Kevin Coleman. The landscape model: A model for exploring trade-offs between agricultural production and the environment. Science of The Total Environment 2017, 609, 1483 -1499.
AMA StyleKevin Coleman, Shibu E. Muhammed, Alice E. Milne, Lindsay C. Todman, A. Gordon Dailey, Margaret J. Glendining, Andrew Whitmore, Kevin Coleman. The landscape model: A model for exploring trade-offs between agricultural production and the environment. Science of The Total Environment. 2017; 609 ():1483-1499.
Chicago/Turabian StyleKevin Coleman; Shibu E. Muhammed; Alice E. Milne; Lindsay C. Todman; A. Gordon Dailey; Margaret J. Glendining; Andrew Whitmore; Kevin Coleman. 2017. "The landscape model: A model for exploring trade-offs between agricultural production and the environment." Science of The Total Environment 609, no. : 1483-1499.