A framework for designing multi-functional cover crops

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 co-existence. 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

Phosphorus fertilisation and large legume species affect jarrah forest restoration after bauxite mining

Re-establishing nutrient-cycling is often a key goal of mine-site restoration. This goal can be achieved by applying fertilisers (particularly P) in combination with seeding N-fixing legumes. However, the effect of this strategy on other key restoration goals such as the establishment and growth of non-leguminous species has received little attention. We investigated the effects of P-application rates either singly, or in combination with seeding seven large understorey legume species, on jarrah forest restoration after bauxite mining. Five years after P application and seeding, legume species richness, density and cover were higher in the legume-seeded treatment. However, the increased establishment of legumes did not lead to increased soil N. Increasing P-application rates from 0 to 80 kg P ha−1 did not affect legume species richness, but significantly reduced legume density and increased legume cover: cover was maximal (∼50%) where 80 kg P ha−1 had been applied with large legume seeds. Increasing P-application had no effect on species richness of non-legume species, but increased the density of weeds and native ephemerals. Cover of non-legume species decreased with increasing P-application rates and was lower in plots where large legumes had been seeded compared with non-seeded plots. There was a significant legume × P interaction on weed and ephemeral density: at 80 kg P ha−1 the decline in density of these groups was greatest where legumes were seeded. In addition, the decline in cover for non-legume species with increasing P was greatest when legumes were seeded. Applying 20 kg P ha−1 significantly increased tree growth compared with tree growth in unfertilised plots, but growth was not increased further at 80 kg ha−1 and tree growth was not affected by seeding large legumes. Taken together, these data indicate that 80 kg ha−1 P-fertiliser in combination with (seeding) large legumes maximised vegetation cover at five years but could be suboptimal for re-establishing a jarrah forest community that, like unmined forest, contains a diverse community of slow-growing re-sprouter species. The species richness and cover of non-legume understorey species, especially the resprouters, was highest in plots that received either 0 or 20 kg ha−1 P and where large legumes had not been seeded. Therefore, our findings suggest that moderation of P-fertiliser and legumes could be the best strategy to fulfil the multiple restoration goals of establishing vegetation cover, while at the same time maximising tree growth and species richness of restored forest.

The effects of maize planting density and weeding regimes on light and water use

Light and water are among essential resources required for production of photosynthates in plants. A study on the effects of weeding regimes and maize planting density on light and water use was conducted during the 2001/2 short and 2002 long rain seasons at Muguga in - the central highlands of Kenya. Weeding regimes were: weed free (W1), weedy (W2), herbicide (W3) and hand weeding twice (W4). Maize planting densities were 9 (D1) and 18 plants m-2 (D2) intercropped with Phaseolus vulgaris (beans). The experiment was laid as randomized complete block design replicated four times and repeated twice. All plots were thinned to 4 plants m-2 at tasseling stage (96 DAE) and thinnings quantified as forage. Soil moisture content (SMC), photosynthetically active radiation (PAR) interception, evapo-transpiration (ET crop), water use efficiency (WUE), and harvest index (HI), were determined. Percent PAR was higher in D2 than in D1 before thinning but higher in D1 than in D2 after thinning in both seasons. PAR interception was highest in W2 but similar in W1, W3 and W4 in both seasons. SMC was significantly lower in W2 but similar in W1, W3 and W4. D2 had lower SMC than D1 in season two. Weeding regime significantly influenced ET crop, while planting density and weeding regime significantly influenced WUE and HI. D2 maximizes water and light use for forage production but results to increased intra-specific plant competition for water and light severely before thinning (96 DAE) that reduce grain yield in dual purpose maize, relative to D1.

Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales

Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

Towards more precise sugar beet management based on geostatistical analysis of spatial variability within fields

Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.