Effects of experimental drought and plant diversity on multifunctionality of a model system for crop rotation.

In low-diversity productive grasslands, modest changes to plant diversity (richness, composition and relative abundance) may affect multiple ecosystem functions (multifunctionality), including yield. Despite the economic importance of productive grasslands, effects of plant diversity and environmental disturbance on multifunctionality are very rarely quantified. We systematically varied species richness, composition, and relative abundance of grassland ley communities and manipulated water supply (rainfed and drought) to quantify effects of diversity and environmental disturbance on multifunctionality. We then replaced the grassland leys with a monoculture crop to investigate 'follow-on' effects. We measured six agronomy-related ecosystem functions across one or both phases: yield, yield consistency, digestibility and weed suppression (grassland ley phase), legacy effect (effect on follow-on crop yield), and nitrogen fertiliser efficiency (full rotation). Drought reduced most ecosystem functions, although effects were species- and function-specific. Increased plant diversity affected mean performance, and reduced variation, across the six functions (contributing to multifunctional stability). Multifunctionality index values across a wide range of mixture diversity were higher than the best monoculture under both rainfed and drought conditions (transgressive over-performance). Higher-diversity, lower-nitrogen (150N) mixtures had higher multifunctionality than a low-diversity, higher-nitrogen (300N) grass monoculture. Plant diversity in productive grasslands is a practical farm-scale management action to mitigate drought impacts and enhance multifunctionality of grassland-crop rotation systems.

Preliminary Classification of Selected Farmland Habitats in Ireland Using Deep Neural Networks.

Ireland has a wide variety of farmlands that includes arable fields, grassland, hedgerows, streams, lakes, rivers, and native woodlands. Traditional methods of habitat identification rely on field surveys, which are resource intensive, therefore there is a strong need for digital methods to improve the speed and efficiency of identification and differentiation of farmland habitats. This is challenging because of the large number of subcategories having nearly indistinguishable features within the habitat classes. Heterogeneity among sites within the same habitat class is another problem. Therefore, this research work presents a preliminary technique for accurate farmland classification using stacked ensemble deep convolutional neural networks (DNNs). The proposed approach has been validated on a high-resolution dataset collected using drones. The image samples were manually labelled by the experts in the area before providing them to the DNNs for training purposes. Three pre-trained DNNs customized using the transfer learning approach are used as the base learners. The predicted features derived from the base learners were then used to train a DNN based meta-learner to achieve high classification rates. We analyse the obtained results in terms of convergence rate, confusion matrices, and ROC curves. This is a preliminary work and further research is needed to establish a standard technique.

Beneficial effects of multi-species mixtures on N2O emissions from intensively managed grassland swards.

In a field experiment, annual nitrous oxide (N2O) emissions and grassland yield were measured across different plant communities, comprising systematically varying combinations of monocultures and mixtures of three functional groups (FG): grasses (Lolium perenne, Phleum pratense), legumes (Trifolium pratense, Trifolium repens) and herbs (Cichorium intybus, Plantago lanceolata). Plots received 150 kg ha-1 year-1 nitrogen (N) (150 N), except L. perenne monocultures which received two N levels: 150 N and 300 N. The effect of plant diversity on N2O emissions was derived from linear combinations of species performances' in monoculture (species identity) and not from strong interactions between species in mixtures. Increasing from 150 N to 300 N in L. perenne resulted in a highly significant increase in cumulative N2O emissions from 1.39 to 3.18 kg N2O-N ha-1 year-1. Higher N2O emissions were also associated with the legume FG. Emissions intensities (yield-scaled N2O emissions) from multi-species mixture communities around the equi-proportional mixture were lowered due to interactions among species. For N2O emissions scaled by nitrogen yield in forage, the 6-species mixture was significantly lower than L. perenne at both 300 N and 150 N. In comparison to 300 N L. perenne, the same N yield or DM yield could have been produced with the equi-proportional 6-species mixture (150 N) while reducing N2O losses by 63% and 58% respectively. Compared to 150 N L. perenne, the same N yield or DM yield could have been produced with the 6-species mixture while reducing N2O losses by 41% and 24% respectively. Overall, this study found that multi-species grasslands can potentially reduce both N2O emissions and emissions intensities, contributing to the sustainability of grassland production.

Potential development of Irish agricultural sustainability indicators for current and future policy evaluation needs.

There is a significant and detailed range of sustainability indicators for Irish agri-food production, but there remain areas where further indicator development or new indicators could prove valuable. This review provides an outline of potential developments in Irish assessment of agricultural sustainability following the latest research and in order to meet policy demands. Recent research findings have suggested means of improved quantitative modelling of greenhouse gas emissions, but additional dietary and soil data may be important for this, especially for the potential inclusion of any soil sequestration. This information could also benefit more detailed modelling of nutrient losses to water. Specific concerns over pesticide and antibiotic use may require additional survey work on the particular locations or types of farms of interest. Biodiversity monitoring could be improved by expanding the range of results-oriented agri-environment schemes or employing remote-sensing habitat monitoring, likely supplemented with targeted field surveys for specific objectives. Farm-level economic sustainability is largely well-covered, but additional data collection may be of benefit to address specific issues such as labour costs. Recent additional surveys on farm-level social sustainability have addressed important social indicators of isolation and access to local services, and could be rolled out on a larger number of farms in the future. Wider societal concerns such as animal welfare, genetically modified materials in foodstuffs and antibiotic resistance have limited indicators currently available, and could also benefit from additional surveys. The breadth and detail required in agri-food sustainability indicators present a significant challenge to survey design and implementation, but many developments can be achieved without additional surveys through the use of remote sensing and geospatial technologies and integration of existing datasets. Despite the important benefits of further developments in Irish sustainability indicators, consideration must also be given to farmer confidentiality and survey fatigue.

Higher species richness enhances yield stability in intensively managed grasslands with experimental disturbance.

Climate models predict increased frequency and severity of drought events. At an Irish and Swiss site, experimental summer droughts were applied over two successive years to grassland plots sown with one, two or four grassland species with contrasting functional traits. Mean yield and plot-to-plot variance of yield were measured across harvests during drought and after a subsequent post-drought recovery period. At both sites, there was a positive relationship between species richness and yield. Under rainfed control conditions, mean yields of four-species communities were 32% (Wexford, Ireland) and 51% (Zürich, Switzerland) higher than in monocultures. This positive relationship was also evident under drought, despite significant average yield reductions (-27% at Wexford; -21% at Zürich). Four-species communities had lower plot-to-plot variance of yield compared to monoculture or two-species communities under both rainfed and drought conditions, which demonstrates higher yield stability in four-species communities. At the Swiss but not the Irish site, a high degree of species asynchrony could be identified as a mechanism underlying increased temporal stability in four-species communities. These results indicate the high potential of multi-species grasslands as an adaptation strategy against drought events and help achieve sustainable intensification under both unperturbed and perturbed environmental conditions.

Enhancing the diversity of breeding invertebrates within field margins of intensively managed grassland: Effects of alternative management practices.

Severe declines in biodiversity have been well documented for many taxonomic groups due to intensification of agricultural practices. Establishment and appropriate management of arable field margins can improve the diversity and abundance of invertebrate groups; however, there is much less research on field margins within grassland systems. Three grassland field margin treatments (fencing off the existing vegetation "fenced"; fencing with rotavation and natural regeneration "rotavated" and; fencing with rotavation and seeding "seeded") were compared to a grazed control in the adjacent intensively managed pasture. Invertebrates were sampled using emergence traps to investigate species breeding and overwintering within the margins. Using a manipulation experiment, we tested whether the removal of grazing pressure and nutrient inputs would increase the abundance and richness of breeding invertebrates within grassland field margins. We also tested whether field margin establishment treatments, with their different vegetation communities, would change the abundance and richness of breeding invertebrates in the field margins. Exclusion of grazing and nutrient inputs led to increased abundance and richness in nearly all invertebrate groups that we sampled. However, there were more complex effects of field margin establishment treatment on the abundance and richness of invertebrate taxa. Each of the three establishment treatments supported a distinct invertebrate community. The removal of grazing from grassland field margins provided a greater range of overwintering/breeding habitat for invertebrates. We demonstrate the capacity of field margin establishment to increase the abundance and richness in nearly all invertebrate groups in study plots that were located on previously more depauperate areas of intensively managed grassland. These results from grassland field margins provide evidence to support practical actions that can inform Greening (Pillar 1) and agri-environment measures (Pillar 2) of the Common Agricultural Policy (CAP). Before implementing specific management regimes, the conservation aims of agri-environment measures should be clarified by defining the target species or taxonomic groups.

Biodiversity and ecosystem function: making sense of numerous species interactions in multi-species communities.

Understanding the biodiversity and ecosystem function relationship can be challenging in species-rich ecosystems. Traditionally, species richness has been relied on heavily to explain changes in ecosystem function across diversity gradients. Diversity-Interactions models can test how ecosystem function is affected by species identity, species interactions, and evenness, in addition to richness. However, in a species-rich system, there may be too many species interactions to allow estimation of each coefficient, and if all interaction coefficients are estimable, they may be devoid of any sensible biological meaning. Parsimonious descriptions using constraints among interaction coefficients have been developed but important variability may still remain unexplained. Here, we extend Diversity-Interactions models to describe the effects of diversity on ecosystem function using a combination of fixed coefficients and random effects. Our approach provides improved standard errors for testing fixed coefficients and incorporates lack-of-fit tests for diversity effects. We illustrate our methods using data from a grassland and a microbial experiment. Our framework considerably reduces the complexities associated with understanding how species interactions contribute to ecosystem function in species-rich ecosystems.

Nitrogen yield advantage from grass-legume mixtures is robust over a wide range of legume proportions and environmental conditions.

Current challenges to global food security require sustainable intensification of agriculture through initiatives that include more efficient use of nitrogen (N), increased protein self-sufficiency through homegrown crops, and reduced N losses to the environment. Such challenges were addressed in a continental-scale field experiment conducted over 3 years, in which the amount of total nitrogen yield (Ntot ) and the gain of N yield in mixtures as compared to grass monocultures (Ngainmix ) was quantified from four-species grass-legume stands with greatly varying legume proportions. Stands consisted of monocultures and mixtures of two N2 -fixing legumes and two nonfixing grasses. The amount of Ntot of mixtures was significantly greater (P ≤ 0.05) than that of grass monocultures at the majority of evaluated sites in all 3 years. Ntot and thus Ngainmix increased with increasing legume proportion up to one-third of legumes. With higher legume percentages, Ntot and Ngainmix did not continue to increase. Thus, across sites and years, mixtures with one-third proportion of legumes attained ~95% of the maximum Ntot acquired by any stand and had 57% higher Ntot than grass monocultures. Realized legume proportion in stands and the relative N gain in mixture (Ngainmix /Ntot in mixture) were most severely impaired by minimum site temperature (R = 0.70, P = 0.003 for legume proportion; R = 0.64, P = 0.010 for Ngainmix /Ntot in mixture). Nevertheless, the relative N gain in mixture was not correlated to site productivity (P = 0.500), suggesting that, within climatic restrictions, balanced grass-legume mixtures can benefit from comparable relative gains in N yield across largely differing productivity levels. We conclude that the use of grass-legume mixtures can substantially contribute to resource-efficient agricultural grassland systems over a wide range of productivity levels, implying important savings in N fertilizers and thus greenhouse gas emissions and a considerable potential for climate change mitigation.

Current use of impact models for agri-environment schemes and potential for improvements of policy design and assessment.

Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES.