John A. Baddeley

Models of biological nitrogen fixation of legumes. A review

Leguminous crops have the ability to fix nitrogen (N) biologically from the atmosphere. This can benefit not only the legumes themselves but also any intercropped or subsequent crops, thus reducing or removing the need to apply N fertilizers. Improved quantification of legume biological nitrogen fixation (BNF) will provide better guidance for farmers on managing N to optimise productivity and reduce harmful losses to the environment. There are many techniques available for the direct quantitative measurement of legume BNF in the field and in controlled environments. However, these are time-consuming and therefore expensive, and generate data relevant only to the time and place of measurement. Alternatively, legume BNF can be estimated by either empirical models or dynamic mechanistic simulation models. Comparatively, simulation by a dynamic model is preferable for quantifying legume BNF, because of its capability to simulate the response of N fixation to a wide range of environmental variables and legume growth status. Currently there is no published review of the approaches used to simulate, rather than measure, legume BNF. This review of peer-reviewed literature shows that most simulation models estimate the N fixation rate from a pre-defined potential N fixation rate, adjusted by the response functions of soil temperature, soil/plant water status, soil/plant N concentration, plant carbon (C) supply and crop growth stage. Here, we highlight and compare the methods used to estimate the potential N fixation rate, and the response functions to simulate legume BNF, in nine widely-cited models over the last 30 years.We then assess their relative strengths in simulating legume BNF with varying biotic and abiotic factors, and identify the discrepancies between experimental findings and simulations. After this comparison, we identify the areas where there is the potential to improve legume BNF simulation in the future. These include; (1) consideration of photosynthetic C supply, (2) refining the various effects of soil mineral N concentration, (3) characterization and incorporation of excess soil water stress and other factors into models, and (4) incorporation of the effects of grazing, coexistence and competition with intercrops and weeds into models to improve their practical relevance to sustainable agricultural systems. This review clarifies, for the first time, the current progress in legume BNF quantification in simulation models, and provides guidance for their further development, combining fundamental experimental and modelling work.

Developing Existing Plant Root System Architecture Models to Meet Future Agricultural Challenges

Improving our understanding of the relationships between soil conditions and plant growth, both above and below ground, will contribute to the development of cropping systems that are less reliant on mineral fertilizers for crop nutrition. Although many models predicting the flows of nutrients between plants and soil have been developed, few of these deal in detail with root architecture and dynamics. In this chapter, we review seven widely cited models of root architecture and development in terms of their ability to improve predictions of plant and soil nutrient flows. We have examined processes related to root system architecture and development, compared mathematical expressions and parameters used in the selected models, and summarized common processes and parameters for simulating root systems. This outcome should benefit researchers and model developers, preventing the need to spend limited resources on repeating the same process. Detailed conclusions include the fact that both inter-branching distance and insertion angle are essential parameters for representing root architecture. Additionally, in a three-dimensional model an extra parameter, radial angle, should be used for determining the location of a branch relative to the root from which it originated. Root growth is simulated by elongation rate and elongation direction, with root component diameter also represented in some models. Almost all the three-dimensional models reviewed calculate the current direction of newly formed root segments using the previous direction of tip extension together with an angle related to geotropism. This review was carried out as the first stage in a research program on integrating root growth models with soil nutrient cycling models. For this purpose, the review suggests that, in order to optimize practical applications of these models in cropping systems, there is a need to integrate a number of additional processes, including root longevity and mortality, environmental responses, and effects of management such as tillage or the pesticide application regime. The form of root mortality relevant to nutrient cycling in soil is that due to natural senescence of root components. This differs from catastrophic death of roots due to attack by pathogenic fungi, which has been considered in one existing root model. To achieve the required objectives, there is also a need to strengthen the integration of above-ground plant component dynamics with root system development, particularly in relation to breeding new crop varieties for sustainable agricultural systems.

Engineering a plant community to deliver multiple ecosystem services

The sustainable delivery of multiple ecosystem services requires the management of functionally diverse biological communities. In an agricultural context, an emphasis on food production has often led to a loss of biodiversity to the detriment of other ecosystem services such as the maintenance of soil health and pest regulation. In scenarios where multiple species can be grown together, it may be possible to better balance environmental and agronomic services through the targeted selection of companion species. We used the case study of legume-based cover crops to engineer a plant community that delivered the optimal balance of six ecosystem services: early productivity, regrowth following mowing, weed suppression, support of invertebrates, soil fertility building (measured as yield of following crop), and conservation of nutrients in the soil. An experimental species pool of 12 cultivated legume species was screened for a range of functional traits and ecosystem services at five sites across a geographical gradient in the United Kingdom. All possible species combinations were then analyzed, using a process-based model of plant competition, to identify the community that delivered the best balance of services at each site. In our system, low to intermediate levels of species richness (one to four species) that exploited functional contrasts in growth habit and phenology were identified as being optimal. The optimal solution was determined largely by the number of species and functional diversity represented by the starting species pool, emphasizing the importance of the initial selection of species for the screening experiments. The approach of using relationships between functional traits and ecosystem services to design multifunctional biological communities has the potential to inform the design of agricultural systems that better balance agronomic and environmental services and meet the current objective of European agricultural policy to maintain viable food production in the context of the sustainable management of natural resources.

Nitrous oxide mitigation in UK agriculture

Nitrous oxide (N2O) makes the single largest contribution to greenhouse gas (GHG) emissions from UK and European Union agriculture. Ambitious government targets for GHG mitigation are leading to the implementation of changes in agricultural management in order to reduce these emissions (mitigation measures). We review the evidence for the contribution of those measures with the greatest mitigation potential which provide an estimated 4.3 t CO2e ha−1 y−1 GHG reduction in the UK. The mitigation options considered were: using biological fixation to provide nitrogen (N) inputs (clover, Trifolium), reducing N fertilizer, improving land drainage, avoiding N excess, fully accounting for manure/slurry N, species introduction (including legumes), improved timing of mineral fertilizer N application, nitrification inhibitors, improved timing of slurry and manure application, and adopting systems less reliant on inputs. These measures depend mostly on increasing the efficiency of N fertilizer use and improving soil conditions; however, they provide the added benefit of increasing the economic efficiency of farming systems, and can often be viewed as “win-win” solutions.

Models of Biological Nitrogen Fixation of Legumes

Leguminous crops have the ability to fix nitrogen (N) biologically from the atmosphere. This can benefit not only the legumes themselves but also any intercropped or subsequent crops, thus reducing or removing the need to apply N fertilizers. Improved quantification of legume biological nitrogen fixation (BNF) will provide better guidance for farmers on managing N to optimise productivity and reduce harmful losses to the environment. There are many techniques available for the direct quantitative measurement of legume BNF in the field and in controlled environments. However, these are time-consuming and therefore expensive, and generate data relevant only to the time and place of measurement. Alternatively, legume BNF can be estimated by either empirical models or dynamic mechanistic simulation models. Comparatively, simulation by a dynamic model is preferable for quantifying legume BNF, because of its capability to simulate the response of N fixation to a wide range of environmental variables and legume growth status. Currently there is no published review of the approaches used to simulate, rather than measure, legume BNF. This review of peer-reviewed literature shows that most simulation models estimate the N fixation rate from a pre-defined potential N fixation rate, adjusted by the response functions of soil temperature, soil/plant water status, soil/plant N concentration, plant carbon (C) supply and crop growth stage. Here, we highlight and compare the methods used to estimate the potential N fixation rate, and the response functions to simulate legume BNF, in nine widely-cited models over the last 30 years. We then assess their relative strengths in simulating legume BNF with varying biotic and abiotic factors, and identify the discrepancies between experimental findings and simulations. After this comparison, we identify the areas where there is the potential to improve legume BNF simulation in the future. These include; (1) consideration of photosynthetic C supply, (2) refining the various effects of soil mineral N concentration, (3) characterization and incorporation of excess soil water stress and other factors into models, and (4) incorporation of the effects of grazing, coexistence and competition with intercrops and weeds into models to improve their practical relevance to sustainable agricultural systems. This review clarifies, for the first time, the current progress in legume BNF quantification in simulation models, and provides guidance for their further development, combining fundamental experimental and modelling work.

Legumes intercropped with spring barley contribute to increased biomass production and carry-over effects

Intercropping systems that include legumes can provide symbiotically fixed nitrogen (N) and potentially increase yield through improved resource use efficiency. The aims of the present study were: (a) to evaluate the effects of different legumes (species and varieties) and barley on grain yield, dry matter production and N uptake of the intercrop treatments compared with the associated cereal sole crop; (b) to assess the effects on the yields of the next grain crop and (c) to determine the accumulation of N in shoots of the crops in a low-input rotation. An experiment was established near Edinburgh, UK, consisting of 12 hydrologically isolated plots. Treatments were a spring barley ( Hordeum vulgare cvar Westminster) sole crop and intercrops of barley/white clover ( Trifolium repens cvar Alice) and barley/pea ( Pisum sativum cvar Zero4 or cvar Nitouche) in 2006. All the plots were sown with spring oats ( Avena sativa cvar Firth) in 2007 and perennial ryegrass in 2008. No fertilizers, herbicides or pesticides were used at any stage of the experiment. Above-ground biomass (barley, clover, pea, oat and ryegrass) and grain yields (barley, pea and oat) were measured at key stages during the growing seasons of 2006, 2007 and 2008; land equivalent ratio (LER) was measured only in 2006. At harvest, the total above-ground biomass of barley intercropped with clover (4·56 t biomass/ha) and barley intercropped with pea cvar Zero4 (4·49 t biomass/ha) were significantly different from the barley sole crop (3·05 t biomass/ha; P P P