Cover Crop Productivity in Contrasting Growing Conditions and Influence on the Subsequent Crop

In arable systems, cover crops provide multiple ecosystem services involved in soil protection and fertility. They can efficiently compete against weeds, control erosion or recycle nutrients. The supply of these services is however largely dependent on cover crop growth as most of the services are related to biomass production. The choice of a cover crop adapted to the growing conditions is thus essential. Growing mixtures instead of sole crops is expected to be a way to overcome variable growing conditions and to insure high biomass production.Different field trials have been conducted from 2013 to 2016 in Nyon, Switzerland to assess cover crop biomass production and stability, and their influence on the following crop. Indian mustard, field pea, black oat and phacelia were sown as sole crops and in mixtures with different diversity levels (2, 3 and 4 species). A mixture of 11 species (50% of legumes and 50% of other species) was also tested. Biomass production was assessed about three months after seeding, just before the seeding of the next main crop, in two 0.5 m × 0.5 m quadrats. For each cover crop, a risk of failure, e.g. the probability of producing less than 3 t/ha (minimal biomass allowing to provide the services expected from cover crops), was estimated. Weed pressure was appraised by weed biomass in quadrats. The yield of the following main crop, here winter wheat, was determined after harvesting with a combine harvester, at wheat maturity, in summer. Sole crops showed very contrasting performance according to the growing conditions. Pea was the most productive in low yielding conditions with 2 t/ha while other sole crops produced only 0.5 t/ha. Pea was barely more productive in high yielding conditions, reaching only 3 t/ha when cover crop average was 6 t/ha. By contrast, mustard and oat showed high production potential in these conditions, exceeding 7 t/ha. Pea should thus be favoured when the growing conditions are clearly identified as limiting (low N availability), while oat or mustard should be chosen in favourable conditions. However, in general, conditions are hardly predictable. Our results showed that mixtures should be preferred as they were adapted to a wider range of environments than sole crops, performing well regardless of the conditions and resulting in a lower risk of failure than sole crops. The 11-specie mixture revealed that generally 4 to 5 species are sufficient to insure a good performance regardless of the conditions. Regarding cover crop effect on the following crop, we evidenced the importance of high biomass production for efficient weed control and positive influence on crop yield in no till treatments.Our results showed that cover crop mixtures rather than sole crops should be chosen as they insure high biomass production and thus a good supply of ecosystem services. In addition, cover crop cultivation, even for a short period, proved to be paramount to the maintenance of grain yield and soil fertility on the long term, especially in reduced tillage systems

Cover Crops to Secure Low Herbicide Weed Control Strategies in Maize Grown with Reduced Tillage

As a key-element of conservation agriculture, the occasional or systematic suppression of full-inversion ploughing implies an adaptation of the cropping system. To assess the ability of cover crops to control weeds in a subsequent maize crop grown with reduced tillage, three annual experiments were implemented at the research station of Agroscope Changins, Nyon, Switzerland. Ten non-wintering cover crop (CC) species were sown in mid-summer and compared to a bare soil treatment in strip-plot experiments including different weeding strategies according to integrated weed management rules. In case of a predictable impasse for weed control, an alternative management option was chosen 1) at the end of winter: total herbicide application instead of no herbicide application, 2) at the beginning of May before maize sowing: minimum soil tillage instead of no tillage. The ability of cover crop species to control weed was evaluated at the stage 2-4 leaves of maize. The shoot dry matter yield of maize was measured at harvest at the end of August. At the beginning of November, mean CC dry shoot biomass varied between 1.2 and 11.1 t DM ha-1 depending on experimental year and CC species. On average over the three years, Asteraceae (Helianthusannuus and Guizotiaabyssinica) showed the highest shoot dry matter among the tested species (> 6.0 t DM ha-1). Legume species (Pisumsativum arvense, Trifolium alexandrinum and Vicia sativa) and Brassicaceae species (Brassicacampestrisoleifera and Raphanussativuslongipinnatus) presented the lowest 3-year mean shoot biomass (≤4.0 t DM ha-1) At the end of winter, the three legume species and Avenastrigosa showed the highest plant residue soil cover and Brassicaceae species the lowest one. CC residue soil cover at the end of winter was only slightly positively correlated with CC autumn shoot biomass. In three out of eight cases, the chosen weeding strategy was very efficient in terms of weed control at the stage 2-4 leaves of maize. In the remaining five cases, the weeding strategy did not succeed in preventing weed infestation at the beginning of maize development. A mean weed cover higher than 15% was observed when no total herbicide and/or no tillage was applied before maize sowing. In three out of these five cases, a significant CC effect on weed cover could be observed. CC species able to produce high amounts of biomass in autumn appeared to be useful in terms of weed control. The most efficient CC species varied from year to year: G. abyssinica in 2011, H. annuus in 2012 and A. strigosa in 2014. CC effect on maize yield was significant in a single case, but the effect of CC species tended to be positive compared to the control treatment without CC. Despite only partial efficacy, the use of cover crops is recommended for limiting weed incidence in cropping systems aimed at reducing soil tillage and herbicide use

Specific interactions leading to transgressive overyielding in cover crop mixtures

Growing mixtures of species instead of sole crops is expected to increase the ecosystem services provided by cover crops. This study aimed at understanding the interactions between species and investigating how they affect the performance of the mixture. Four species were combined in six bispecific mixtures in a field experiment. The performance of each species when grown in a mixture was compared to its performance as a sole crop at different sowing densities, to characterise the influence of intra- and interspecific competition for each species. Intra- and interspecific competition coefficients were quantified using a response surface design and the hyperbolic yield-density equation. Interactions between the four species ranged from facilitation to competition. Most of the mixtures exhibited transgressive overyielding. Without nitrogen (N) fertilisation, high complementarity between species allowed to achieve the highest biomass. With N fertilisation, high dominance of one mixture component should be avoided to achieve good performance. A revised approach in the use of the land equivalent ratio for the evaluation of cover crop mixtures is also proposed in this study. It allows to better identify transgressive overyielding in mixtures and to better characterise the effect of one species on the other within the mixture

Deep imaging of the shell elliptical galaxy NGC3923 with MegaCam

Context. The elliptical galaxy NGC 3923 is known to be surrounded by a number of stellar shells, probable remnants of an accreted galaxy. Despite its uniqueness, the deepest images of its outskirts come from the 1980s. On the basis of the modified Newtonian dynamics (MOND), it has recently been predicted that a new shell lies in this region. Aims. We obtain the deepest image ever of the galaxy, map the tidal features in it, and search for the predicted shell. Methods. The image of the galaxy was taken by the MegaCam camera at the Canada-France-Hawaii Telescope in the g' band. It reached the surface-brightness limit of 29 mag/arcsec2. In addition, we reanalyzed an archival HST image of the galaxy. Results. We detected up to 42 shells in NGC 3923. This is by far the highest number among all shell galaxies. We present the description of the shells and other tidal features in the galaxy. A probable progenitor of some of these features was discovered. The shell system likely originates from two or more progenitors. The predicted shell was not detected, but the new image revealed that the prediction was based on incorrect assumptions and poor data.Comment: 14 pages, 2 tables, 19 figures, accepted for publication in A&

Comparison of visual assessment and digital image analysis for canopy cover estimation

Nowadays, in the context of agriculture, cover crops are crops cultivated with the sole aim of providing important ecosystem services such as erosion prevention. Many services offered by these crops are directly linked to the development of their vegetation, and especially of canopy cover. A proper estimation of this cover is thus necessary to evaluate cover crop performance. Many methods to estimate canopy cover exist, but differ in terms of effort and time needed to implement them. In this study, we compared visual assessment of canopy cover in the field with two methods of digital image analysis (Assess and Canopeo), for different cover crop species and vegetation types. Visual estimation was positively correlated with both type of image analysis estimations. However, it showed systematically lower values of canopy cover, especially at intermediate canopy cover values. The type of vegetation influenced the visual and digital image estimations, narrow leaf species being the most difficult to evaluate visually. This study showed that depending on its utilisation, visual canopy cover assessment could be useful, especially when only relative estimation of canopy cover is needed. When absolute canopy cover estimation is needed, the use of digital image analysis should be preferred

Integrating simulation data from a crop model in the development of an agri-environmental indicator for soil cover in Switzerland

Agriculture generates important impacts on the environment, which can be evaluated with agri-environmental indicators. A key element of environment protection in agriculture is the maintenance of a dense soil cover for the longest possible period. Notably, soil cover is known to diminish erosion risks and nitrate leaching. In this study, an agri-environmental indicator for soil cover is presented, which integrates data from the crop model STICS to quantify vegetation growth dynamics. Simulations were conducted with STICS for the major crops cultivated in Switzerland across several contrasting pedoclimatic situations. They were then integrated with data for crop residue cover to evaluate soil cover at the field and farm levels in the framework of a farm network survey. At the field level, for the period from the harvest of the previous crop through the harvest of the main crop, the highest soil cover was achieved by silage maize and winter barley. A high variability between fields was observed, due to the diversity of cultural practices during the period preceding the seeding of the main crops. Some crops, winter wheat in particular, showed a high number of days with insufficient soil cover (under 30%), leading to potential environmental risks. This shows the crucial need of promoting conservation agriculture principles (permanent soil cover, minimum soil disturbance, diversification of crop rotation) in arable systems to better protect the soils and the environment. The soil cover indicator presented here provided a continuous quantification of soil cover, whereas most of the currently used indicators provide qualitative or roughly quantitative results

Unifying Data Perspectivism and Personalization: An Application to Social Norms

Instead of using a single ground truth for language processing tasks, several recent studies have examined how to represent and predict the labels of the set of annotators. However, often little or no information about annotators is known, or the set of annotators is small. In this work, we examine a corpus of social media posts about conflict from a set of 13k annotators and 210k judgements of social norms. We provide a novel experimental setup that applies personalization methods to the modeling of annotators and compare their effectiveness for predicting the perception of social norms. We further provide an analysis of performance across subsets of social situations that vary by the closeness of the relationship between parties in conflict, and assess where personalization helps the most

Challenges of GPT-3-based Conversational Agents for Healthcare

The potential to provide patients with faster information access while allowing medical specialists to concentrate on critical tasks makes medical domain dialog agents appealing. However, the integration of large-language models (LLMs) into these agents presents certain limitations that may result in serious consequences. This paper investigates the challenges and risks of using GPT-3-based models for medical question-answering (MedQA). We perform several evaluations contextualized in terms of standard medical principles. We provide a procedure for manually designing patient queries to stress-test high-risk limitations of LLMs in MedQA systems. Our analysis reveals that LLMs fail to respond adequately to these queries, generating erroneous medical information, unsafe recommendations, and content that may be considered offensive.Comment: 12 pages, 9 Tables, accepted to RANLP 202

Understanding Interpersonal Conflict Types and their Impact on Perception Classification

Studies on interpersonal conflict have a long history and contain many suggestions for conflict typology. We use this as the basis of a novel annotation scheme and release a new dataset of situations and conflict aspect annotations. We then build a classifier to predict whether someone will perceive the actions of one individual as right or wrong in a given situation. Our analyses include conflict aspects, but also generated clusters, which are human validated, and show differences in conflict content based on the relationship of participants to the author. Our findings have important implications for understanding conflict and social norms

Bayesian confidence in optimal decisions

The optimal way to make decisions in many circumstances is to track the difference in evidence collected in favour of the options. The drift diffusion model (DDM) implements this approach, and provides an excellent account of decisions and response times. However, existing DDM-based models of confidence exhibit certain deficits, and many theories of confidence have used alternative, non-optimal models of decisions. Motivated by the historical success of the DDM, we ask whether simple extensions to this framework might allow it to better account for confidence. Motivated by the idea that the brain will not duplicate representations of evidence, in all model variants decisions and confidence are based on the same evidence accumulation process. We compare the models to benchmark results, and successfully apply 4 qualitative tests concerning the relationships between confidence, evidence, and time, in a new preregistered study. Using computationally cheap expressions to model confidence on a trial-by-trial basis, we find that a subset of model variants also provide a very good to excellent account of precise quantitative effects observed in confidence data. Specifically, our results favour the hypothesis that confidence reflects the strength of accumulated evidence penalised by the time taken to reach the decision (Bayesian readout), with the penalty applied not perfectly calibrated to the specific task context. These results suggest there is no need to abandon the DDM or single accumulator models to successfully account for confidence reports