Agriculture is often accountable for soil erosion, water pollution and land degradation. One-third of the earth’s soils are suffering from degradation, and much of this is due to a decline in the physical soil structure. Goal 15 of the UN’s Sustainable Development Goals is specifically addressing these problems. In the UK, topsoil loss is estimated to reach 2.2 million tonnes per year, affecting nearly 50% of all arable lands1. Quantifiable soil degradation costs range between £0.9 bn and £1.4 bn per year, with a central estimate of £1.2 bn, mainly linked to loss of organic content of soils (47% of total cost), compaction (39%) and erosion (12%)2.
Devising strategies to prevent land degradation are urgently needed to preserve the essential ecosystem services provided by soils. This can be done by ensuring the soil surface is covered, to increase soil strength (to resist erosion) and improve soil structure (for hydrological services and optimal crop growth). Soils have been manipulated for many years to reduce soil compaction and optimise crop growth, to improve drainage, to provide slope stability and to manage nutrients, pests and contaminants. In modern agriculture, this is mainly carried out using machinery or engineered amendments such as fertilisers. These options often have a limited effect and are costly and not sustainable, so alternatives need to be sought.
“one-third of the earth’s soils are suffering from degradation”
Plant roots are important improvers of soil structure, enhancing aggregate formation and stability3,4 and improving soil cohesion5. Root-induced macropores are of particular importance for runoff mitigation due to their large diameters and high connectivity, enhancing rapid rainfall infiltration and percolation to deeper soil layers6,7, and improving soil aeration. The mechanisms by which this engineering occurs include the physical penetration of the soil matrix by roots through vertical and lateral expansion (physical creation of macropores, also called bio-drilling) and the subsequent triggering of microbial activity arising from rhizodeposition of root exudates, cells and debris, which serve as energy sources for the rhizosphere microbiota. These biota improve the properties of the soil through adhesion, kinetic restructuring and filamentous binding8. In turn, the resulting soil structure subsequently promotes future root growth, creating a sustainable positive feedback loop.
In arable systems, increasing the capacity of soils to resist erosion and receive, retain and release water through structural rejuvenation is most feasible via the use of appropriate cover crops in the rotation as a best management practice. Cover crops are fast-growing annuals or perennials which, planted sequentially between two cash crops, have the ability to boost soil health and reduce the negative impact of agro-management on the environment. They are usually planted immediately after harvest9. Left to grow all winter, they cover and protect the soil surface against erosion and die off or are removed (mechanically or chemically) in early spring to make way for the cash crop.
There are a number of studies on the effect of specific cover crop species, as recently reviewed by Blanco-Canqui and Ruis (2020)10; examples include their impact on tackling soil compaction11,12, improving infiltration13,14, enhancing aggregate stability15,16 and reducing erosion17,18. However, there is not much focus on the effect of the traits of their root systems on soil physical properties. Research shows that soils planted with fit-for-purpose roots are better adapted to disturbances such as nutrient or water shortage19 or soil erosion14. Cover crops are able to create important macropores in the soil by shifting the soil during the growth of their taproots (e.g. mustard), or by granulation of soil particles into aggregates in terms of sod-forming plants (e.g. ryegrass)20. Despite its importance for plant productivity, the study of cover crop species’ root systems at multiple depths is a largely unexplored frontier in bio-engineering of agricultural soils. Root responses to the combination of soil physical stresses (e.g. mechanical impedance and water stress) depend on the communication and coordination of the different regions of the same root system21. No research has yet focused on matching root traits that are beneficial for soil functions, such as soil physical stability and water infiltration capacity, even though simultaneous consideration of more than one trait is required to understand adaptation and functioning (e.g. root response to soil compaction21. Bacq-Labreuil, Crawford, Mooney, Neal, and Ritz (2019)22 showed that the diversity of root morphology and interactions between roots and soil biota impact soil structural formation and dynamics. As root morphology can have different effects upon soil structure, the choice of cover crop with specific root traits can have both practical and ecological implications. It remains, however, unclear how combinations of root traits affect multiple soil properties such as infiltration, aggregate stability, porosity and compaction. Therefore, to increase the uptake of cover cropping for soil bio-engineering in agriculture, a classification of cover crop root systems based on functional traits is needed to study their potential for soil structural improvements, hydrological services and soil resource protection. Such knowledge of root–soil interactions would allow for screening of the right cover crop species for a specific problem.
“cover crops have the ability to boost soil health and reduce the negative impact of agro-management”
A greenhouse experiment was carried out, growing seven different cover crop species as monocultures in large 1 m × 1.2 m × 0.8 m containers. The 24 plant containers were placed in a randomised block design, including three replicates per species and three control bare soils, without plants. The soil was purchased from a specialised topsoil supplier and sieved through a 4-mm sieve. Soil was characterised as having a loam soil texture (52% sand, 20% clay, 28% silt) following the USDA soil classification system, containing 0.17% of total nitrogen, 48 mg kg−1 of total phosphorus and 237 mg kg−1 of potassium. The bottom 50 cm of the containers were filled with the soil compacted at a bulk density of 1.5 g cm−3 and the top 30 cm of soil was loosely packed at a bulk density of 1.2 g cm−3. Each of the 24 containers was placed on a weighing system with a capacity of 4,000 kg and accuracy of 100 g. The balances are connected to a control computer, and weights were recorded sequentially at 10-s intervals. A control system was programmed to top up the water content four times a day through a series of soaker hoses up to a reference gravimetric soil water content of 0.18 g g−1. Air temperature was continuously monitored. Moisture sensors were installed into each container at 60 and 70 cm depth and recorded moisture content hourly. In addition, soil moisture profile probes with an HH2 reader were used to measure at 10, 20, 30 and 40 cm from the surface, weekly. The cover crops were sown in rows in June 2018 and grown for 90 days. Table 1 lists the cover crop species used, their seeding densities (ranging from 10 to 45 kg ha−1) and their plant densities (ranging from 12 to 144 plant m−2). The selected seeding rates correspond with the recommended lowest seeding densities used in agriculture.
Plant phenotyping, sampling and analysis
After 90 days of growth, samples were collected to measure and calculate the following above- and belowground plant traits: aboveground biomass (AB; g m−2), root biomass (RB; g m−3), root length density (RLD; cm cm−3) root diameter (D; mm), specific root length (SRL; m g−1), root surface area (RSA; m2), deep root length fraction (DRLF; −), calculated as the ratio of total length of roots in the deep soil (30–60 cm) over total root length in the entire profile, and root-to-shoot ratio (R:S) calculated as ratio of total root mass and total shoot biomass. The root traits were determined from cored samples with a volume of 754 cm3 collected at the following depths: 0–15 cm, 15–30 cm, 30–45 cm and 45–60 cm. Four replicated root cores were taken from each container using a root auger. Roots were separated from the soil using the wet sieving method23 and a 500-μm sieve. Washed roots were scanned with a flatbed scanner and the images were analysed. The scanned roots and the harvested aboveground plant material were oven-dried at 70°C for 48 h and weighed with an analytical scale.
“such knowledge of root–soil interactions would allow for screening of the right cover crop species for a specific problem”
All soil samples were taken prior to sampling for root traits. Post-harvest soil samples were taken at 10 cm (topsoil) and 30 cm (subsoil) depth, air dried, mixed and sieved to 2 and 0.5 mm.
The following soil physical properties were determined post-harvest (Table 2): bulk density samples were taken at 15, 30 and 50-cm depth using rings of 5 cm in diameter. Penetration resistance (MPa) was measured with a penetrologger recording resistance up to 80-cm depth in 1-cm increments with three replicated profiles per box.
The following soil tests to quantify soil functioning regarding runoff mitigation, erosion control and soil structural improvements were performed post-harvest: topsoil macropore infiltration rate, topsoil aggregate stability and soil porosity. Water infiltration rate (cm h−1) was measured using single ring infiltrometers. Core samples were collected with the bipartite root auger from the topsoil layer (0–15 cm) to test and calculate the effects of the roots of the cover crops on soil aggregate stability by using a modified wet sieving method24 with a sieve size of 20 mm. In this method a value of 1 means that roots hold all soil in place and a value of 0 means that the root system does not help in holding the soil together, meaning that all soil is eroded away. Soil rings (PVC, 3 cm in diameter, 3 cm height) were extracted for determination of soil porosity at 15, 30 and 50-cm soil depth. These soil samples were scanned with high-resolution X-ray computer tomography, with a resolution of 28 μm, exposure time of 200 ms, number of projections of 2,998, voltage of 170 kV and a current of 150 μA. Each scan was reconstructed and then manually combined. Samples were thresholded to separate solid and pores using in-house developed software25 and geometric properties of the pore space were calculated following Houston et al. (2017)26.
“the present work provided a new “toolbox” for both farmers and soil conservationists”
Cover cropping is a successful soil conservation technique, but it has limitations. It can only be effective if it is recognised as part of a well-planned, integrated farming system. There are a number of factors (e.g. environmental conditions, soil degradation status, cash crop type, method of tillage) that should be taken into consideration before building cover crops into the farming system to sustain both the ecological and economic benefits of cover cropping. The present work provided a new “toolbox” for both farmers and soil conservationists by presenting correlations between root traits and soil physical properties showing how root traits can help alleviate soil compaction or increase aggregate stability. The monoculture results provide a valuable starting point for the selection and combination of different cover crop mixtures. They can inform further studies on how different mixtures of cover crops and their root systems can affect and enhance multiple soil functions. This would, however, also require the development of tools to distinguish between the different cover crops’ root biomass in a multispecies mixture.
- Pimentel, D., & Burgess, M. (2013). Soil erosion threatens food production. Agriculture, 3, 443– 463.
- Graves, A. R., Morris, J., Deeks, L. K., Rickson, R. J., Kibblewhite, M. G., Harris, J. A., Truckle, I. (2015). The total costs of soil degradation in England and Wales. Ecological Economics, 119, 399– 413. https://doi.org/10.1016/j.ecolecon.2015.07.026
- Haynes, R. J., & Beare, M. H. (1997). Influence of six crop species on aggregate stability and some labile organic matter fractions. Soil Biology and Biochemistry, 29, 1647– 1653.
- Kavdir, Y., & Smucker, A. J. (2005). Soil aggregate sequestration of cover crop root and shoot-derived nitrogen. Plant and Soil, 272, 263– 276.
- de Baets, S., Torri, D., Poesen, J., Salvador, M. P., & Meersmans, J. (2008). Modeling increased soil cohesion due to roots with EUROSEM. Earth Surface Processes and Landforms, 33, 1948– 1963.
- Cresswell, H. P., & Kirkegaard, J. A. (1995). Subsoil amelioration by plant roots—The process and the evidence. Australian Journal of Soil Research, 33, 221– 239.
- Ghestem, M., Sidle, R. C., & Stokes, A. (2011). The influence of plant root systems on subsurface flow: Implications for slope stability. Bioscience, 61, 869– 879.
- Miransari, M. (2014). Plant growth promoting Rhizobacteria. Journal of Plant Nutrition, 37, 2227– 2235. https://doi.org/10.1080/01904167.2014.920384
- Abdalla, M., Hastings, A., Cheng, K., Yue, Q., Chadwick, D., Espenberg, M., Smith, P. A. (2019). A critical review of the impacts of cover crops on nitrogen leaching, net greenhouse gas balance and crop productivity. Global Change Biology, 25, 2530– 2543. https://doi.org/10.1111/gcb.14644
- Blanco-Canqui, H., & Ruis, S. J. (2020). Cover crop impacts on soil physical properties: A review. Soil Science Society of America Journal, 84, 1527– 1576. https://doi.org/10.1002/saj2.20129
- Chen, G., & Weil, R. R. (2010). Penetration of cover crop roots through compacted soils. Plant and Soil, 331, 31– 43. https://doi.org/10.1007/s11104-009-0223-7
- Williams, S. M., & Weil, R. R. (2004). Crop cover root channels may alleviate soil compaction effects on soybean crop. Soil Science Society of America Journal, 68, 1403– 1409. https://doi.org/10.2136/sssaj2004.1403
- Kahimba, F. C., Sri Ranjan, R., Froese, J., Entz, M., & Nason, R. (2008). Cover crop effects on infiltration, soil temperature, and soil moisture distribution in the Canadian prairies. Applied Engineering in Agriculture, 24, 321– 333. https://doi.org/10.13031/2013.24502
- Yu, Y., Loiskandl, W., Kaul, H. P., Himmelbauer, M., Wei, W., Chen, L., & Bodner, G. (2016). Estimation of runoff mitigation by morphologically different cover crop root systems. Journal of Hydrology, 538, 667– 676.
- Liu, A., Ma, B. L., & Bomke, A. A. (2005). Effects of cover crops on soil aggregate stability, total organic carbon, and polysaccharides. Soil Science Society of America Journal, 69, 2041– 2048. https://doi.org/10.2136/sssaj2005.0032
- Walsh, B. D., MacKenzie, A. F., Salmins, S., & Buszard, D. J. (1996). Impact of soil management systems on organic dwarf apple orchards and soil aggregate stability, bulk density, temperature and water content. Canadian Journal of Soil Science, 76, 203– 209. https://doi.org/10.4141/cjss96-028
- de Baets, S., Poesen, J., Meersmans, J., & Serlet, L. (2011). Cover crops and their erosion-reducing effects during concentrated flow erosion. Catena, 85, 237– 244.
- Kasper, T. C., Radke, J. K., & Laflen, J. M. (2001). Small grain cover crops and wheel traffic effects on infiltration, runoff, and erosion. Journal of Soil and Water Conservation, 56, 160– 164.
- Barkaoui, K., Roumet, C., & Volaire, F. (2016). Mean root trait more than root trait diversity determines drought resilience in native and cultivated Mediterranean grass mixtures. Agriculture Ecosystems & Environment, 231, 122– 132. https://doi.org/10.1016/j.agee.2016.06.035
- McGourty, G., & Reganold, J. P. (2005). Managing vineyard soil organic matter with cover crops. Soil Environment and Vine Mineral Nutrition, 56(2), 145– 150.
- Bengough, A. G., Bransby, M. F., Hans, J., McKenna, S. J., Roberts, T. J., & Valentine, T. A. (2006). Root responses to soil physical conditions; growth dynamics from field to cell. Journal of Experimental Botany, 57, 437– 447. https://doi.org/10.1093/jxb/erj003
- Bacq-Labreuil, A., Crawford, J., Mooney, S. J., Neal, A. L., & Ritz, K. (2019). Cover crop species have contrasting influence upon soil structural genesis and microbial community phenotype. Scientific Reports, 9, 7473. https://doi.org/10.1038/s41598-019-43937-6
- Smit, A. L., Bengough, A. G., Engels, C., van Noordwijk, M., Pellerin, S., & van de Geijn, S. C. (2000). Root methods, a handbook. Heidelberg: Springer-Verlag.
- Frei, M. (2009). Validation of a new approach to determine vegetation effects on superficial soil movements. Zurich: Swiss Federal Institute of Technology.
- Hapca, S. M. A., Houston, N., Otten, W., & Baveye, P. C. (2013). New local thresholding method for soil images by minimising grayscale intra-class variance. Vadose Zone Journal, 12, 3. https://doi.org/10.2136/vzj2012.0172
- Houston, A. N., Otten, W., Falconer, R., Monga, O., Baveye, P. C., & Hapca, S. M. (2017). Quantification of the pore size distribution of soils: Assessment of existing software using tomographic and synthetic 3D images. Geoderma, 299, 73– 82.