A framework for designing multi-functional cover crops By J STORKEY1, T F DÖRING2,3, J A BADDELEY4, R COLLINS5, S RODERICK6, R STOBART7, H E JONES8,6 and C WATSON4 1 Rothamsted Research, Harpenden, Herts AL5 2JQ The Organic Research Centre, Elm Farm, Hamstead Marshall, Berks RG20 0HR 3 Humboldt University Berlin, Albrecht-Thaer-Weg 5, 14195 Berlin, Germany 4 SRUC, Craibstone Estate, Aberdeen AB21 9YA 5 IBERS, Aberystwyth University, Gogerddan, Aberystwyth, Ceredigion SY23 3EB 6 Duchy College, Rosewarne, Cambourne, Cornwall TR14 0AB 7 NIAB TAG, Morley Office, Wymondham, Norfolk NT18 9DF 8 Reading University, Whiteknights, Reading, Berkshire, RG6 6AH 2 Summary Cover crops are sown to provide a number of ecosystem services including nutrient management, mitigation of diffuse pollution, improving soil structure and organic matter content, weed suppression, nitrogen fixation and provision of resources for biodiversity. Although the decision to sow a cover crop may be driven by a desire to achieve just one of these objectives, the diversity of cover crops species and mixtures available means that there is potential to combine a number of ecosystem services within the same crop and growing season. Designing multi-functional cover crops would potentially help to reconcile the often conflicting agronomic and environmental agendas and contribute to the optimal use of land. We present a framework for integrating multiple ecosystem services delivered by cover crops that aims to design a mixture of species with complementary growth habit and functionality. The optimal number and identity of species will depend on the services included in the analysis, the functional space represented by the available species pool and the community dynamics of the crop in terms of dominance and coexistence. Experience from a project that applied the framework to fertility building leys in organic systems demonstrated its potential and emphasised the importance of the initial choice of species to include in the analysis. Key words: ecosystem service, functional traits, competition, species mixtures Introduction One consequence of the advent of inorganic fertilisers and pesticides has been the simplification of crop rotations with crop choice being driven more by short term market forces as opposed to agronomic considerations to do with regulating pest, weed and disease pressure and maintaining soil health. However, it is increasingly being recognised that this current, chemical based, model of intensive agriculture may not be sustainable because of the erosion of ecosystem services provided by resilient soils and diverse beneficial insect populations (Baulcombe et al., 2009; Brown et al., 2011). One way to mitigate the negative consequences of intensification is to diversify cropping systems, reducing the risks of selecting for epidemics of economically damaging pests, weeds and diseases adapted to single crops, reducing the pressure on soils and providing more diverse habitats for non-crop biodiversity (Smith et al., 2010; Davis et al., 2012). In this context, cover crops present an opportunity to deliver multiple ecosystem service in the same crop and growing season as several species can be grown together (Schipanski et al., 2014; Storkey et al., 2015). A large number of species are currently grown as cover crops with many more potential mixtures of species available. These species and mixtures will vary in their capacity to deliver different ecosystem services and methodologies and decision support tools are required to identify the optimal species choice or mixture for a given purpose and context. This will depend on what the cover crop is required to deliver and the ‘habitat template’ in terms of soil type, establishment conditions and growing window. We present a framework developed as part of the LegLINK project (‘Using legume based mixtures to enhance nitrogen use efficiency and economic viability of cropping systems’) that ran between 2009 and 2012 (HGCA Project Report No. 513). The focus of the project was on fertility building leys in organic systems with the aim of better managing the release of nitrogen from green manures by integrating species with a higher lignin and polyphenol content. However, the general principles used in the project to design the optimal system could be applied to any cover crop to integrate multiple ecosystem services, including those included in conventional systems. Materials and methods The initial step in designing a multi-functional cover crop is to review all candidate species. In LegLINK, an expert group derived this ‘long list’ of species and compiled available data on agronomic and biological traits (Table 1). However, we propose that a similar list including all possible cover crop species that brings together all the available data on their traits is required to provide the foundation for a comprehensive support tool for selecting species. The long list compiled was then used to select candidate species for field trials. In terms of optimising multi-functionality, it was desirable to capture as much functional diversity within the available species pool within the constraints of only being able to include a sub set within the field experiments. A Principal Components Analysis (PCA) was, therefore run to identify a set of species that were spread across the multi-dimensional trait space. This was combined with information of frost tolerance, and tolerance to grazing to exclude species that were not suitable for the specific system being designed within the LegLINK project. Again, we propose that a large scale multivariate analysis on a more comprehensive dataset would be a useful exercise to identify functionally similar species or groups that could form the basis of a species mix within the constraints of a specific cropping system. Scientific name Common name Anthyllis vulneraria Onobrychis viciifolia Trifolium pratense Medicago sativa Kidney vetch Sainfoin red clover Lucerne Large birdsfoot trefoil Black medic Perennial ryegrass Lotus pedunculatus Medicago lupulina Lolium perenne Maximum height (cm) 60 60 100 90 Seed weight (mg) 3.05 19.2 1.8 2.4 Rooting depth Grazing tolerance med/deep med/deep deep deep no yes moderate yes 60 60 1 1.6 medium medium yes yes 90 2 shallow yes White sweet Melilotus alba clover Trifolium repens white clover Trifolium hybridum Alsike clover Lotus corniculatus Birdsfoot trefoil Vicia sativa Winter vetch Lupinus alba White lupin Lupinus luteus Yellow lupin Lupinus augustifolius Blue lupin Lolium multiflorum Italian ryegrass Trifolium incarnatum crimson clover Subterranean Trifolium subteranneu clover Trifolium alexandrinum Egyptian clover Vicia hirsuta Hairy vetch Trigonella foenum graecum Fenugreek Trifolium resupinatum Persian clover Vicia lathyroides Summer vetch Lathyrus Pratensis Meadow Pea 150 50 40 35 120 120 60 120 130 50 2.3 0.5 0.7 1.2 41 297.5 129.6 168 2.9 3.1 v deep medium med/deep medium med/deep deep deep deep shallow medium no yes moderate yes no no no no yes no 20 6.7 deep yes 45 30 2.8 4.9 med/deep med/deep moderate no 20 11.9 medium moderate 50 20 120 0.8 1.95 12.39 med/deep med/deep v deep moderate no no Table 1. Example of initial list of species with selection of agronomic and biological traits that acts as a starting point for selecting optimal mix of species. We propose developing a comprehensive resource that includes all potential species and traits. Within the LegLINK project, there was the opportunity to screen the selected cover crop species for a range of ecosystem services. Within the generic framework we are presenting here, this will not ordinarily be possible. However, from experience gained from the LegLINK project and using evidence from the wider literature it is possible to predict relative performance in terms of the delivery of different services from functional traits. For example, we would expect capture of nutrients to be associated with species with deep, well developed rooting systems, good early establishment with large seed size and support of pollinators with flowering traits. A number of these ecosystem service / functional trait relationships were quantified in the LegLINK project (Storkey et al., 2015), Figure 1, and could be used to predict multi-functionality of species and mixtures not tested within the project. Where a mixture is being assessed, one would use the aggregated trait value that represents the ‘average’ value taking into account relative biomass: n trait agg pi x trait i i 1 where n = number of species in community, p relative proportion of species i and traiti = trait value for species i. 600 Numbers of invertebrates (m-2) 550 R² = 0.8644 500 450 400 350 300 250 200 0.01 0.015 0.02 0.025 0.03 0.035 Specific leaf area (m2 / g) Figure 1. Relationship between support of invertebrates (a resource for farmland birds (Storkey et al., 2013)) and a functional trait, specific leaf area, for a range of legume cover crop species. This and similar relationships could be used to predict the function of species not included in the LegLINK analysis. Data on the growth habit and phenology of the range of candidate species would also be useful for estimating the potential complementarity between species in terms of coexistence in space and time. In LegLINK, a simulation model of plant competition was parameterised for each species but it should be possible to derive general rules based on plant ecological strategy and traits such as maximum height, rooting depth and flowering time to mix species that would be expected to occupy different niches in the canopy. Results The species originally included in the candidate list for the LegLINK project fell into three broad ecological strategies. These differences in functional characteristics were reflected in the variation of delivery of the range of ecosystem services. Firstly, there was a group of large seeded tall species, including Lathyrus pratensis (meadow pea), Vicia sativa (winter vetch) and Onobrychis viciifolia (sanfoin). These species tended to establish well, grow quickly early in the season but some did not respond well to mowing. Secondly, there was a group of shorter, fast growing species with a high specific leaf area and small seed including Trifolium repens, T.pratense and T.hybridum. These species grew back quickly after mowing and supported high numbers of invertebrates but were relatively slow to establish. Finally, Lotus pedunculatus and Medicago lupulina were short, slow growing and tended to have a higher lignin and polyphenol content which meant residues broke down more slowly after incorporation of the cover crop. Two species, Trifolium pratense (red clover) and Medicago sativa (Lucerne) occupied the centre of the multi-dimensional trait space and were good ‘allrounders’. An analysis of the optimal multi-functional mix of the available species included one of these all-rounders complemented by species from the extremes of the trait-space (Storkey et al., 2015). In designing the optimal mix, the seasonality of growth and growth habitat was important to consider in the LegLINK data. Mixtures that performed well were those that combined a large seeded, fast growing species early in the season with one that grew back quickly after mowing late in the season. In this case, sequential flowering was also sometimes observed, extending the overall period of flowering resources for pollinators. As well as complementary growth, combining species also had benefits for yield of the following crop. Yield of a winter wheat crop, grown without fertiliser inputs, after the incorporation of the cover crops in the autumn was generally related to the accumulated biomass of the legumes. However, there were also differences in the response of the components of yield to different species. For the same amount of total crop yield, wheat following a fast growing, leafy species like white clover had more ears but smaller grain than a crop following a woodier species such as Lucerne (Figure 2). This was explained by the different breakdown characteristics of the residue. The residue of fast growing species broke down quickly, making nutrients available to the crop early in the growing season, whereas, residue of species with higher lignin content broke down more slowly meaning nutrients were still available during grain filling. This is a good illustration of the potential for mixing species to gain additional benefit – a mix of white clover and lucerne could maintain yield while reducing the risk of leaching of nutrients from the system. Figure 2. Thousand grain weight and head density of wheat crop following incorporation of different cover crops expressed as ranks. Cover crop species that produced high biomass tended to result in higher crop yields but there was variation in the effect on different yield components. AC- Alsike clover, BM – Black medick, BT – Birdsfoot trefoil, CC – Crimson clover, LT – Large birdsfoot trefoil, LU – Lucerne, MP – Meadow pea, SC – Sweet white clover, SF – Sanfoin, WV – Winter vetch. NM & IM are mixtures of all species either inoculated or non-innoculated. Discussion There is a growing interest in integrating cover crops into conventional rotations for a variety of reasons but a lack of empirical evidence to guide the choice and potential combination of species. The framework we have developed based on the collation of data on functional traits and agronomic characteristics of candidate cover crop species and the quantification of relationships between traits and ecosystem service delivery has the potential to provide this evidence and serve as a decision making tool. However, this will depend on a concerted effort to bring together all of the information in the scientific literature and from growers experience with many different species of cover crops into a single repository. This needs to be done in a structured, objective way that identifies standard metrics across the crops that will allow them to be compared like-for-like across a range of ecosystem services. Such an exercise will result in novel combinations of crops for trialling in the field as well as the identification of potential gaps in the functional space covered by species currently cultivated as cover crops that could potentially be filled by additional species that have not, up to now, been considered as candidate cover crops. Acknowledgments This work was sponsored by Defra and industry partners under the Defra Sustainable Arable LINK programme (LK09106). Rothamsted Research is a national institute of bioscience strategically funded by the Biotechnology and Biological Sciences Research Council. References Baulcombe D, Crute I, Davies B, Dunwell J, Gale M, Jones J, Pretty J, Sutherland W J, Toulmin C. 2009. Reaping the benefits: Science and the Sustainable Intensification of Global Agriculture. The Royal Society. Brown C, Walpole M, Simpson L, Tierney M. 2011. Introduction to the UK National Ecosystem Assessment., The UK National Ecosystem Assessment Technical Report. UNEP-WCMC, Cambridge. Davis A S, Hill J D, Chase C A, Johanns A M, Liebman M. 2012. Increasing Cropping System Diversity Balances Productivity, Profitability and Environmental Health. Plos One 7:8. Schipanski M E, Barbercheck M, Douglas M R, Finney D M, Haider K, Kaye J P, Kemanian A R, Mortensen D A, Ryan M R, Tooker J, White C. 2014. A framework for evaluating ecosystem services provided by cover crops in agroecosystems. Agricultural Systems 125:12-22. Smith R G, Mortensen D A, Ryan M R. 2010. A new hypothesis for the functional role of diversity in mediating resource pools and weed-crop competition in agroecosystems. Weed Research 50:37-48. Storkey J, Brooks D, Haughton A, Hawes C, Smith B M, Holland J M. 2013. Using functional traits to quantify the value of plant communities to invertebrate ecosystem service providers in arable landscapes. Journal of Ecology 101:38-46. Storkey J, Doring T, Baddeley J, Collins R, Roderick S, Jones H, Watson C A. 2015. Engineering a plant community to deliver multiple ecosystem services. Ecological Applications 25:10341043.