The potential impact of climate change on Australia's soil organic carbon resources

BACKGROUND: Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO(2 )on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM). RESULTS: We estimate organic carbon storage in the topsoil (0–10 cm) of the Australian continent in 1990 to be 8.1 Gt. This equates to 19 and 34 Gt in the top 30 and 100 cm of soil, respectively. By the year 2100, under a low emissions scenario, topsoil organic carbon stores of the continent will have increased by 0.6% (49 Mt C). Under a high emissions scenario, the Australian continent becomes a source of CO(2 )with a net reduction of 6.4% (518 Mt) in topsoil carbon, when compared to no climate change. This is partially offset by the predicted increase in NPP of 20.3% CONCLUSION: Climate change impacts must be studied holistically, requiring integration of climate, plant, ecosystem and soil sciences. The SOCRATES terrestrial carbon cycling model provides realistic estimates of changes in SOC storage in response to climate change over the next century, and confirms the need for greater consideration of soils in assessing the full impact of climate change and the development of quantifiable mitigation strategies

The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models

The Arabidopsis thaliana F-box gene HAWAIIAN SKIRT is a new player in the microRNA pathway

In Arabidopsis, the F-box HAWAIIAN SKIRT (HWS) protein is important for organ growth. Loss of function of HWS exhibits pleiotropic phenotypes including sepal fusion. To dissect the HWS role, we EMS-mutagenized hws-1 seeds and screened for mutations that suppress hws-1 associated phenotypes. We identified shs-2 and shs-3 (suppressor of hws-2 and 3) mutants in which the sepal fusion phenotype of hws-1 was suppressed. shs-2 and shs-3 (renamed hst-23/hws-1 and hst-24/hws-1) carry transition mutations that result in premature terminations in the plant homolog of Exportin-5 HASTY (HST), known to be important in miRNA biogenesis, function and transport. Genetic crosses between hws-1 and mutant lines for genes in the miRNA pathway, also suppress the phenotypes associated with HWS loss of function, corroborating epistatic relations between the miRNA pathway genes and HWS. In agreement with these data, accumulation of miRNA is modified in HWS loss or gain of function mutants. Our data propose HWS as a new player in the miRNA pathway, important for plant growth

Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity

Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use1. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments1, 2 and global crop models3 to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[0;47]%–27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4–17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities

Genome-Wide Identification of Alternative Splice Forms Down-Regulated by Nonsense-Mediated mRNA Decay in Drosophila

Alternative mRNA splicing adds a layer of regulation to the expression of thousands of genes in Drosophila melanogaster. Not all alternative splicing results in functional protein; it can also yield mRNA isoforms with premature stop codons that are degraded by the nonsense-mediated mRNA decay (NMD) pathway. This coupling of alternative splicing and NMD provides a mechanism for gene regulation that is highly conserved in mammals. NMD is also active in Drosophila, but its effect on the repertoire of alternative splice forms has been unknown, as has the mechanism by which it recognizes targets. Here, we have employed a custom splicing-sensitive microarray to globally measure the effect of alternative mRNA processing and NMD on Drosophila gene expression. We have developed a new algorithm to infer the expression change of each mRNA isoform of a gene based on the microarray measurements. This method is of general utility for interpreting splicing-sensitive microarrays and high-throughput sequence data. Using this approach, we have identified a high-confidence set of 45 genes where NMD has a differential effect on distinct alternative isoforms, including numerous RNA–binding and ribosomal proteins. Coupled alternative splicing and NMD decrease expression of these genes, which may in turn have a downstream effect on expression of other genes. The NMD–affected genes are enriched for roles in translation and mitosis, perhaps underlying the previously observed role of NMD factors in cell cycle progression. Our results have general implications for understanding the NMD mechanism in fly. Most notably, we found that the NMD–target mRNAs had significantly longer 3′ untranslated regions (UTRs) than the nontarget isoforms of the same genes, supporting a role for 3′ UTR length in the recognition of NMD targets in fly

Multimodel ensembles of wheat growth: many models are better than one.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models

Climate change impact and adaptation for wheat protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production