The interaction of crop rotations and soil quality: an economic analysis

Non-Peer ReviewedA model is briefly described that integrates an environmental component that simulates crop yields and changes in soil quality and an economic component that calculates rotation scale costs and revenues based on yield and input data provided by the environmental component. The model is used to simulate crop yield, soil quality and economic performance of a number of alternative annual crop rotations over a 50 year period. This information is used to quantify the impact of alternative crop rotations on soil organic carbon and the economic value of on-site SOC to the rotations, with values ranging from $0.20 to$2.50/ton SOC/hectare/yr

Understanding microbially mediated processes involved in N, P and C cycling in wheat-based cropping systems

Non-Peer Reviewe

Effect of crop rotations on soil organic matter in two Black Chernozems

Non-Peer Reviewe

Generating Behaviorally Diverse Policies with Latent Diffusion Models

Recent progress in Quality Diversity Reinforcement Learning (QD-RL) has enabled learning a collection of behaviorally diverse, high performing policies. However, these methods typically involve storing thousands of policies, which results in high space-complexity and poor scaling to additional behaviors. Condensing the archive into a single model while retaining the performance and coverage of the original collection of policies has proved challenging. In this work, we propose using diffusion models to distill the archive into a single generative model over policy parameters. We show that our method achieves a compression ratio of 13x while recovering 98% of the original rewards and 89% of the original coverage. Further, the conditioning mechanism of diffusion models allows for flexibly selecting and sequencing behaviors, including using language. Project website: https://sites.google.com/view/policydiffusion/hom

Conditionally Combining Robot Skills using Large Language Models

This paper combines two contributions. First, we introduce an extension of the Meta-World benchmark, which we call "Language-World," which allows a large language model to operate in a simulated robotic environment using semi-structured natural language queries and scripted skills described using natural language. By using the same set of tasks as Meta-World, Language-World results can be easily compared to Meta-World results, allowing for a point of comparison between recent methods using Large Language Models (LLMs) and those using Deep Reinforcement Learning. Second, we introduce a method we call Plan Conditioned Behavioral Cloning (PCBC), that allows finetuning the behavior of high-level plans using end-to-end demonstrations. Using Language-World, we show that PCBC is able to achieve strong performance in a variety of few-shot regimes, often achieving task generalization with as little as a single demonstration. We have made Language-World available as open-source software at https://github.com/krzentner/language-world/

Economics of crop diversification opportunities for the Brown and Dark Brown Soil Zones of Saskatchewan

Non-Peer ReviewedProducers, particularly in the Brown and drier parts of the Dark Brown soil zones, have begun to extend and diversify their crop rotations, becoming less reliant on summerfallow and monoculture cereal cropping. The areas planted to crops such as canola, mustard, flax, field pea, chickpea and lentil expanded dramatically in recent years, often into new or non-traditional production areas. These changes in land use practices are expected to continue, and perhaps grow in future years. This study determines and compares the economic merits and relative riskiness (both production and market) of producing chickpea, field pea, lentil, mustard, canola, and flax with spring wheat, durum wheat or barley when grown on chemical fallow and zero-till stubble for various plausible product price scenarios. Field data collected at Swift Current, Scott and Congress were extended with use of a STELLA® model, to elucidate the short-term and the longer-term economic and environmental impacts of these newer cropping systems. Our findings indicate that under current market conditions, risk averse producers in the Brown soil zone would typically choose either a 4-year Fallow-Chickpea-Wheat-Wheat rotation or a 5-year Durum-Chickpea-Mustard-Wheat-Lentil rotation. In the Dark Brown soil zone, risk averse producers would choose a 4-year Canola-Wheat-Lentil- Wheat rotation

Microbial community structure under various wheat-based cropping systems

Non-Peer ReviewedThe effects of cropping systems on soil biological quality are slow to develop. We sampled the soil of a 36-year old long-term experiment established on an Orthic Brown Chernozem, at Swift Current SK, in the fall of 2003, to define the long-term impact of 10 cropping systems on soil biological quality. Numerous variables related to soil function - soil pH, organic C (SOC), moisture, enzymatic activities, available N, P, and S - and soil community structure - phospholipid fatty acids (PLFA) indicators of fungal saprobes, arbuscular mycorrhizal fungi and bacterial groups - were used to describe soil quality. Soils under different cropping systems had become distinct, as revealed by discriminant analyses. Variations in SOC, and pH were most influential in discriminating the soils. SOC varied from 2.38% under continuous wheat to 1.81% under a fallow-wheat rotation. pH went from 6.55 under fallow-wheat-wheat receiving no P-fertilizer, to 4.89, under chemical fallow – fall rye – wheat. Absence of fallow under normal fertilization increased SOC and decreased soil pH. Variations in SOC and pH were concurrent with variations in microbial community structure. Enhanced AM fungi abundance under low soil P, could compensate for the large soil P depletion created by 36 years without P fertilizer, in a fallow-wheat-wheat rotation, and P-fertilized and non-P-fertilized plots produced similar yields. The season of 2003 was dryer than normal and it remains to be seen if AM fungi can compensate for low soil available P when soil moisture is abundant

Seasonal variation in the soil microbial community in wheat-growing soil and influence of C, N, and P inputs

Non-Peer ReviewedIt has long been know that N and P fertilization increases plant growth and yield, but the impact of fertilization on soil microorganisms has rarely been considered. Long-term plots (36-year old) under fallow-wheat-wheat (F-W-W) rotations with no P or no N fertilization, or normally fertilized, and plots receiving low C inputs due to frequent fallow (F-W rotation) were used to define the impact of C, N and P on the seasonal variation of the soil microbial communities in the fallow-after-wheat or the wheat-after-fallow phases of the rotations. The soil was sampled on June 8, July 4, August 5 and September 16, in 2003. There was no significant (P≤ 0.05) time by treatment interactions. Populations of bacteria, arbuscular mycorrhizal (AM) fungi and saprophytic fungi, as estimated by phospholipids fatty acid (PLFA) indicators, were strongly reduced on July 4th, a date corresponding to rapid plant growth. Sporulation of fungal saprobes was enhanced at that date, as indicated by the neutral lipid fatty acid (NLFA) to PLFA fraction ratio of the fatty acid C18:2. It appears that a competition for resources exists between soil microorganisms and wheat, at least in July at the time of active crop growth. While P availability had little effect on soil microorganisms, absence of N fertilization increased sporulation in AM and saprophytic fungi. In spite of the biotrophic1 nature of AM fungi, C input in the form of infrequent fallow or presence of living wheat plant favoured the partitioning of fatty acids into reserve lipid i.e., NLFA