Evaluation of the impact of heat on wheat dormancy, late maturity α-amylase and grain size under controlled conditions in diverse germplasm.

In the Australian wheat belts, short episodes of high temperatures or hot spells during grain filling are becoming increasingly common and have an enormous impact on yield and quality, bringing multi-billion losses annually. This problem will become recurrent under the climate change scenario that forecast increasing extreme temperatures, but so far, no systematic analysis of the resistance to hot spells has yet been performed in a diverse genetic background. We developed a protocol to study the effects of heat on three important traits: grain size, grain dormancy and the presence of Late Maturity α-Amylase (LMA), and we validated it by analysing the phenotypes of 28 genetically diverse wheat landraces and exploring the potential variability existing in the responses to hot spells. Using controlled growth environments, the different genotypes were grown in our standard conditions until 20 days after anthesis, and then moved for 10 days into a heat chamber. Our study showed that our elevated temperature treatment during mid-late filling triggered multiple detrimental effects on yield and quality. We observed a reduction in grain size, a reduction in grain dormancy and increased LMA expression in most of the tested genotypes, but potential resistant lines were identified for each analyzed trait opening new perspectives for future genetic studies and breeding for heat-insensitive commercial lines.

Patterns of crop cover under future climates.

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

Noah's Ark conservation will not preserve threatened ecological communities under climate change.

BACKGROUND: Effective conservation of threatened ecological communities requires knowledge of where climatically suitable habitat is likely to persist into the future. We use the critically endangered Lowland Grassland community of Tasmania, Australia as a case study to identify options for management in cases where future climatic conditions become unsuitable for the current threatened community. METHODS: We model current and future climatic suitability for the Lowland Themeda and the Lowland Poa Grassland communities, which make up the listed ecological community. We also model climatic suitability for the structurally dominant grass species of these communities, and for closely related grassland and woodland communities. We use a dynamically downscaled regional climate model derived from six CMIP3 global climate models, under the A2 SRES emissions scenario. RESULTS: All model projections showed a large reduction in climatically suitable area by mid-century. Outcomes are slightly better if closely related grassy communities are considered, but the extent of suitable area is still substantially reduced. Only small areas within the current distribution are projected to remain climatically suitable by the end of the century, and very little of that area is currently in good condition. CONCLUSIONS: As the climate becomes less suitable, a gradual change in the species composition, structure and habitat quality of the grassland communities is likely. Conservation management will need to focus on maintaining diversity, structure and function, rather than attempting to preserve current species composition. Options for achieving this include managing related grassland types to maintain grassland species at the landscape-scale, and maximising the resilience of grasslands by reducing further fragmentation, weed invasion and stress from other land uses, while accepting that change is inevitable. Attempting to maintain the status quo by conserving the current structure and composition of Lowland Grassland communities is unlikely to be a viable management option in the long term.

Improving the use of species distribution models in conservation planning and management under climate change.

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models.

A tool for simulating and communicating uncertainty when modelling species distributions under future climates.

Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions.We provide a tool for simulating uncertainty, focusing on uncertainty due to data quality. We illustrate the use of the tool using a Tasmanian endemic species as a case study. Our simulations provide probabilistic, spatially explicit illustrations of the impact of uncertainty on model projections. We also illustrate differences in model projections using six different global climate models and two contrasting emissions scenarios.Our case study results illustrate how different sources of uncertainty have different impacts on model output and how the geographic distribution of uncertainty can vary.Synthesis and applications: We provide a conceptual framework for understanding sources of uncertainty based on a review of potential sources of uncertainty in species distribution modelling; a tool for simulating uncertainty in species distribution models; and protocols for dealing with uncertainty due to climate models and emissions scenarios. Our tool provides a step forward in understanding and communicating the impacts of uncertainty on species distribution models under future climates which will be particularly helpful for informing discussions between researchers, policy makers, and conservation practitioners.