Selecting genes for function: Exploiting genetic diversity in grasses to manage the biophysical interactions in grassland soils

Grassland is an important land use in the UK, accounting for 35% of all land cover and more than 70% of farmed land. Grassland utility is becoming more multifunctional with an increasing need to consider the pivotal role of grassland management in river basin corridors and their role in rainfall-runoff processes, which have a significant influence on flooding. The ability of vegetation to increase macro-porosity and to influence soil hydraulic properties has been recently observed. However, little is known about how grassland management influences soil profile hydraulic properties and larger scale rainfall-runoff processes. Not only should grasslands be freely draining in wet periods, but sustainable grasses need to be able to extract water stored in deep layers during dry summer periods. A unique collection of grasses that have a diverse set of gene x environment interactions will be used to link the genetics of deep rooting and water use efficiency with their function. The gene mapping approach used here will simultaneously identify genes for rooting traits and water-use-efficiency both in UK grass species and in other monocot crop species including the model monocot crop rice, thereby facilitating information exchange for the benefit of all concerned with monocot crop-sustainability. To realize the benefits from breeding grasses and selecting grass with genes for predetermined function it is necessary to understand the implications at the field and catchment scales. This is to say that we need to up-scale from microcosm and runoff plot experiments to the catchment scale. The variation in plant root growth within species and between grass species will be assessed to enable more accurate model predictions of the influence of grass rooting behaviour on soil hydraulic properties. This will provide a basis for active grassland management that has the potential to manipulate both productivity (i.e. through water availability), and environmental services through increased infiltration into the soil profile and decreased surface water run-off. The final objective of this project is to develop a model that integrates the new knowledge such that the outputs of the project may be generalized and used to reduce flood risk at the landscape scale.

The purpose of this project is to test if the observed differences in the rooting behaviour and water use efficiency of existing and novel grass cultivars can explain 1) differences in water extraction patterns by grasses and changes in soil hydraulic properties at the plant and microcosm scales and 2) variation in the eco-hydrology of managed grasslands at the plot and small catchment scales. The project is based around three testable objectives that will provide a basic understanding of how soil-plant interactions in grasslands affect soil structure and eco-hydrology. The Lolium-Festuca complex provides a unique resource for the genetic analysis and 'dissection' of the complex traits that underpin crop sustainability. This project exploits introgression lines produced during the EU FPV project SAGES (which IGER co-ordinated) with Festuca-derived genes in Lolium cultivars with proven capabilities for enhanced water-use-efficiency, or soil-water extraction compared with standard Lolium cultivars. It further exploits the use of a unique set of IGER monosomic chromosome substitution lines where each of the 7 Festuca chromosomes in turn has replaced its Lolium chromosome homoeologue. The inclusion of the monosomic chromosome addition lines gives us complete genome coverage and opportunities to identify alternative genes for water-use-efficiency, or soil-water extraction other than those located during the SAGES project. The experimental work will occur at a range of scales. Initial root penetration studies will be conducted on grass cultivars from Lolium and Festuca species each with contrasting rooting traits and water-use-efficiency, and on introgression lines of Lolium containing different combinations of Festuca-derived genes using the wax layer method developed by the Rothamsted team. Data from these studies will be used to identify grasses to be grown in soil microcosms. Here both good root penetration and water extraction will be measured alongside changes to the soil moisture regime and structure assessed through the novel use of non-invasive geophysical techniques. Plot scale assessment of the influence of grasses characterised under the EU FPV SAGES project will be carried out on the Rowden experimental platform at IGER. Grasses to be grown in the runoff plot scale experiments will be identified with the aid of the initial wax layer screening method and prior knowledge of Dr. Humphreys (co-ordinator of EU SAGES project). In these plots we will be able to measure surface and subsurface runoff as well as root penetration and water extraction. We will investigate the use of oxygen discrimination to estimate the depth of water extraction in a UK grassland context. The experiments described will allow us to combine grass plant genetics and physiology with soil science in order to design novel grass genotypes for deep rooting, water use efficiency, increased infiltration and soil profile storage capacity to meet the challenges of climate change. Improved water extraction will be attributed to deep root penetration and improved soil water infiltration and storage in the soil will be attributed to changes in soil structure. Intraspecific differences of ecophysiological responses are large in grass species. We will assess how intra- and interspecies variation influences plant-soil hydrological functioning through model development and testing. To understand the implications for the project at the catchment and farm scale we will develop a stochastic SVAT-runoff model. Results from the plot scale studies will allow the development and testing of the SVAT-runoff model at the landscape scale using hydrological and land use data from the IGER Denbrook research catchment (48ha), enabling large scale predictions of the consequences of utilising novel grass genetic combinations to improve the hydrological functioning of grassland landscapes.