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Australia has a role to play in future global food security as it contributes 0·12 of global wheat exports. How much more can it contribute with current technology and varieties? The present paper seeks to quantify the gap between water-limited yield potential (Yw) and farmer yields (Ya) for wheat in Australia by implementing a new protocol developed by the Global Yield Gap and Water Productivity Atlas (GYGA) project. Results of past Australian yield gap studies are difficult to compare with studies in other countries because they were conducted using a variety of methods and at a range of scales. The GYGA project protocols were designed to facilitate comparisons among countries through the application of a consistent yet flexible methodology. This is the first implementation of GYGA protocols in a country with the high spatial and temporal climatic variability that exists in Australia.The present paper describes the application of the GYGA protocol to the whole Australian grain zone to derive estimates of rainfed wheat yield gap. The Australian grain zone was partitioned into six key agro-climatic zones (CZs) defined by the GYGA Extrapolation Domain (GYGA-ED) zonation scheme. A total of 22 Reference Weather Stations (RWS) were selected, distributed among the CZs to represent the entire Australian grain zone. The Agricultural Production Systems sIMulator (APSIM) Wheat crop model was used to simulate Yw of wheat crops for major soil types at each RWS from 1996 to 2010. Wheat varieties, agronomy and distribution of wheat cropping were held constant over the 15-year period. Locally representative dominant soils were selected for each RWS and generic sowing rules were specified based on local expertise. Actual yield (Ya) data were sourced from national agricultural data sets. To upscale Ya and Yw values from RWS to CZs and then to national scale, values were weighted according to the area of winter cereal cropping within RWS buffer zones. The national yield gap (Yg = Yw–Ya) and relative yield (Y% = 100 × Ya/Yw) were then calculated from the weighted values.The present study found that the national Yg was 2·0 tonnes (t)/ha and Y% was 47%. The analysis was extended to consider factors contributing to the yield gap. It was revealed that the RWS 15-year average Ya and Yw were strongly correlated (R2 = 0·76) and that RWS with higher Yw had higher Yg. Despite variable seasonal conditions, Y% was relatively stable over the 15 years. For the 22 RWS, average Yg correlated positively and strongly with average annual rainfall amount, but surprisingly it correlated poorly with RWS rainfall variability. Similarly, Y% correlated negatively but less strongly (R2 = 0·33) with RWS average annual rainfall, and correlated poorly with RWS rainfall variability, which raises questions about how Australian farmers manage climate risk. Interestingly a negative relationship was found between Yg and variability of Yw for the 22 RWS (R2 = 0·66), and a positive relationship between Y% and Yw variability (R2 = 0·23), which suggests that farmers in lower yielding, more variable sites are achieving yields closer to Yw. The Yg estimates appear to be quite robust in the context of estimates from other Australian studies, adding confidence to the validity of the GYGA protocol. Closing the national yield gap so that Ya is 0·80 of Yw, which is the level of Yg closure achieved consistently by the most progressive Australian farmers, would increase the average annual wheat production (20·9 million t in 1996/07 to 2010/11) by an estimated 15·3 million t, which is a 72% increase. This indicates substantial potential for Australia to increase wheat production on existing farmland areas using currently available crop varieties and farming practices and thus make a substantial contribution to achieving future global food security. [ABSTRACT FROM PUBLISHER]

We have previously demonstrated that type II ryanodine receptors (RyR2) tetramers can be rapidly rearranged in response to a phosphorylation cocktail. The cocktail modified downstream targets indiscriminately, making it impossible to determine whether phosphorylation of RyR2 was an essential element of the response. Here, we used the ß-agonist isoproterenol and mice homozygous for one of the following clinically relevant mutations: S2030A, S2808A, S2814A, or S2814D. We measured the length of the dyad using transmission electron microscopy (TEM) and directly visualized RyR2 distribution using dual-tilt electron tomography. We found that the S2814D mutation, by itself, significantly expanded the dyad and reorganized the tetramers, suggesting a direct link between the phosphorylation state of the tetramer and its microarchitecture. S2808A and S2814A mutant mice, as well as wild types, had significant expansions of their dyads in response to isoproterenol, while S2030A mutants did not. In agreement with functional data from these mutants, S2030 and S2808 were necessary for a complete ß-adrenergic response, unlike S2814 mutants. Additionally, all mutants had unique effects on the organization of their tetramer arrays. Lastly, the correlation of structural with functional changes suggests that tetramer-tetramer contacts play an important functional role. We thus conclude that both the size of the dyad and the arrangement of the tetramers are linked to the state of the channel tetramer and can be dynamically altered by a ß-adrenergic receptor agonist. [ABSTRACT FROM AUTHOR]

The development of detailed national pathways towards sustainable food and land systems aims to provide stakeholders with clarity on how long-term goals could be achieved and to reduce roadblocks in the way to making commitments. However, the inability to perfectly capture the relationships between all variables in a system and the unknown probability of future values (deep uncertainty) makes it very difficult to design scenarios that account for the full breadth of system uncertainty. Here we use scenario discovery to systematically explore the effect of different parameter ranges on model outputs, and design resilient pathways to sustainability in which multiple target achievement requires a broad portfolio of solutions. We use a model of the Australian food and land system, the FABLE (Food, Agriculture, Biodiversity, Land-use, Energy) Calculator, to investigate conditions for achieving a sustainable Australian food and land system under scenarios based on the Shared Socioeconomic Pathways (SSP) 1, 2, and 3 narratives. Here we link the FABLE Calculator with a Monte Carlo simulation tool to explore hundreds of thousands of scenarios. This allows us to identify the ranges of systemic drivers that achieve multiple sustainability targets around diets, net forest growth, agricultural water consumption, greenhouse gas emissions, biodiversity conservation, and exports by 2050. Our results show that livestock productivity and density, afforestation, and dietary change are powerful influencers for sustainability target achievement. Around 10% of the SSP1 scenarios could achieve all modelled sustainability targets. However, practically none of the scenarios based on SSP2 and SSP3 narratives could achieve such targets. The results suggest that there are options to achieve a more sustainable and resilient Australian food and land-use system with better socio-economic and environmental outcomes than under current trends. However, its achievement requires significant structural changes and coordinated interventions in several components of the domestic food and land system to increase its resilience and environmental and socio-economic performance. Understanding the bounds within which this system needs to change and operate to achieve sustainability targets will enable greater clarity and flexibility during discussions between decision-makers and stakeholders., Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-022-01202-2., (© Crown 2022.)