Comparative analysis of climate change adaptation options across the southern Australian livestock industry

Climate change is predicted to have a substantial negative effect on the productivity of grasslands across southern Australia (Moore and Ghahramani 2013). We used the GRAZPLAN biophysical simulation models to assess several possible grassland management and animal genetic improvement adaptations under SRES A2 climate change scenario. Simulations spanned the five dimensions of geography, time, global circulation models, enterprise, and adaptations. Impact of climate change was predicted to reduce profitability of livestock industry by 46%, 58%, and 72% at 2030, 2050 and 2070, respectively. Increasing soil fertility could return the average profitability of five livestock enterprises to its historical level at 54%, 50%, and 25% of locations in 2030, 2050, and 2070. Increasing the proportion of Lucerne in pasture was effective for 35%, 22%, and 15% of locations in 2030, 2050, and 2070. Increasing fleece growth rates was the most effective genetic adaptation that could return profitability of sheep enterprises to its historical level for 24%, 52%, and 28% of locations in 2030, 2050, and 2070. Removing annual legumes in an attempt to preserve ground cover by replacing annual grass and larger sire body size were less effective options. The incremental adaptations we examined could significantly increase profitability of the enterprises at 2030. However, at many locations in drier regions it appears unlikely that a single adaptation can return profit to the historical level. In most of the high rainfall zone, systemic adaptation using a combination of grassland management and animal genetic improvement could return livestock systems to historical profitability in 2030 and 2050

Comparative Analysis of Climate Change Adaptation Options across the Southern Australian Livestock Industry

Climate change is predicted to have a substantial negative effect on the productivity of grasslands across southern Australia (Moore and Ghahramani 2013). We used the GRAZPLAN biophysical simulation models to assess several possible grassland management and animal genetic improvement adaptations under SRES A2 climate change scenario. Simulations spanned the five dimensions of geography, time, global circulation models, enterprise, and adaptations. Impact of climate change was predicted to reduce profitability of livestock industry by 46%, 58%, and 72% at 2030, 2050 and 2070, respectively. Increasing soil fertility could return the average profitability of five livestock enterprises to its historical level at 54%, 50%, and 25% of locations in 2030, 2050, and 2070. Increasing the proportion of Lucerne in pasture was effective for 35%, 22%, and 15% of locations in 2030, 2050, and 2070. Increasing fleece growth rates was the most effective genetic adaptation that could return profitability of sheep enterprises to its historical level for 24%, 52%, and 28% of locations in 2030, 2050, and 2070. Removing annual legumes in an attempt to preserve ground cover by replacing annual grass and larger sire body size were less effective options. The incremental adaptations we examined could significantly increase profitability of the enterprises at 2030. However, at many locations in drier regions it appears unlikely that a single adaptation can return profit to the historical level. In most of the high rainfall zone, systemic adaptation using a combination of grassland management and animal genetic improvement could return livestock systems to historical profitability in 2030 and 2050

Estimated Effects of Climate Change on Grassland Production and Legume Content across Southern Australia

Climate changes caused by anthropogenic increases in greenhouse gases such as CO2 will affect southern Australia along with the rest of the globe. Dryland pastures supporting extensive beef, sheepmeat and wool production occupy a third of southern Australia’s farming zone. These livestock production systems are highly sensitive to climatic variation, because they depend almost entirely on pasture as their source of feed. Given the diversity of current climates, soils and pastures that are found across southern Australia, and the spatial variation in projected climate changes (CSIRO 2007), it can also be expected that the impacts of changing climates on pasture production will differ across space. Annual and perennial forage legumes are an important part of the feedbase across most of southern Australia; experimental research suggests that legumes are likely to be favoured by increasing atmospheric CO2 concentrations (e.g. Clark et al. 1997) and it is therefore possible that higher legume content in grasslands might be one positive effect of global climate change. In this study, therefore, we have modelled grassland and livestock production to examine the changes in amount, seasonal distribution and legume content of grass-based pastures at locations across southern Australia under climates projected for 2030, 2050 and 2070

Climate Change Impact and Adaptation in Temperate Grassland and Livestock Industries

Climate is projected to have negative impact on temperate grassland and livestock productions across the globe. Moderately elevated atmospheric CO2 in the near future is expected to increase plant photosynthetic rates but this is likely to be limited by soil nitrogen deficits. However, in Australia at least it is unlikely that positive effect of elevated CO2 on plant production be able to offset the negative impacts of climate change. Currently there is a considerable gap between actual and achievable production and profit in Australian grazing systems and many management and genetic improvements for climate adaptation would operate by filling this gap. Because of likely substantial declines in efficiency frontier of grazing systems under changing climate compared to the historical climate, filling the production gap will be a more challenging task in coming decades. Research into climate change impact and adaptation in managed grasslands has been mostly limited to Europe, North America and Australasia. Large areas of managed grasslands exist in South America, China, Africa and south-west Asia for which there is little understanding of the likely impact of climate change impact and effectiveness of potential adaptation options. These grasslands are typically managed at lower intensity than European or North American systems and often form part of crop-livestock farming systems. There is a clear need for research into the direct and indirect impacts of climate change on these grasslands and on the livestock and people they support

Climate change impact, adaptation, and mitigation in temperate grazing systems: a review

Managed temperate grasslands occupy 25% of the world, which is 70% of global agricultural land. These lands are an important source of food for the global population. This review paper examines the impacts of climate change on managed temperate grasslands and grassland-based livestock and effectiveness of adaptation and mitigation options and their interactions. The paper clarifies that moderately elevated atmospheric CO2 (eCO2) enhances photosynthesis, however it may be restiricted by variations in rainfall and temperature, shifts in plant’s growing seasons, and nutrient availability. Different responses of plant functional types and their photosynthetic pathways to the combined effects of climatic change may result in compositional changes in plant communities, while more research is required to clarify the specific responses. We have also considered how other interacting factors, such as a progressive nitrogen limitation (PNL) of soils under eCO2, may affect interactions of the animal and the environment and the associated production. In addition to observed and modelled declines in grasslands productivity, changes in forage quality are expected. The health and productivity of grassland-based livestock are expected to decline through direct and indirect effects from climate change. Livestock enterprises are also significant cause of increased global greenhouse gas (GHG) emissions (about 14.5%), so climate risk-management is partly to develop and apply effective mitigation measures. Overall, our finding indicates complex impact that will vary by region, with more negative than positive impacts. This means that both wins and losses for grassland managers can be expected in different circumstances, thus the analysis of climate change impact required with potential adaptations and mitigation strategies to be developed at local and regional levels

Climate change impact on Western Australian mixed farm systems

Primary enterprises are expected to contend with more frequent climate crises, environmental degradation and even climate-related regulatory change (IPCC, 2014). These stressors occur against an existing backdrop of conventional drivers including economic, biophysical, institutional, cultural and political pressures (Marshall et al., 2012). Australia’s primary industries have historically operated in a highly variable climate and this has posed significant challenges to production, requiring sound and responsive risk management practices. Climate change, brings with it a number of new challenges not yet accounted for by Australian primary producers, and so understanding the scale of these impacts is of importance in undertsanding the changing nature of agricultural risk in the near future. Western Australia with about 4 million ha of wheat production is a major contributor to the Australian agrifood sector and economy. Like cereal production, pastures in WA play a major role in agricultural enterprises and contribute over $3 billion annually through animal production, improvements to crop rotations and conserved fodder (The Department of Agriculture and Food, 2014). Farming profitably in the Western Australia in recent years has been a challenge due in part to declines in annual rainfall as well as exposure to both heat and cold teperature extremes (McConnell & O’Hare, 2013), although lower production might be still profitable. Climate drives the productivity, profitability and environmental health of these systems as they often have to respond to low and variable rainfall. Here we identify the likely effect of climate change in 2030 on mixed farm systems of the Western Australia across a climate transect in terms of production, profit, and environmental impacts for projected climate scenarios in 2030 relative to the baseline of 1980-1999. This work will give insight for designing strategies to respond to changes in climate such as optimized shift towards more intensive livestock systems, dual-purpose cropping, etc

Multi-partite entanglement and quantum phase transition in the one-, two-, and three-dimensional transverse field Ising model

In this paper we consider the quantum phase transition in the Ising model in the presence of a transverse field in one, two and three dimensions from a multi-partite entanglement point of view. Using \emph{exact} numerical solutions, we are able to study such systems up to 25 qubits. The Meyer-Wallach measure of global entanglement is used to study the critical behavior of this model. The transition we consider is between a symmetric GHZ-like state to a paramagnetic product-state. We find that global entanglement serves as a good indicator of quantum phase transition with interesting scaling behavior. We use finite-size scaling to extract the critical point as well as some critical exponents for the one and two dimensional models. Our results indicate that such multi-partite measure of global entanglement shows universal features regardless of dimension $d$. Our results also provides evidence that multi-partite entanglement is better suited for the study of quantum phase transitions than the much studied bi-partite measures.Comment: 7 pages, 8 Figures. To appear in Physical Review

Low prevalence, quasi-stationarity and power-law distribution in a model of spreading

Understanding how contagions (information, infections, etc) are spread on complex networks is important both from practical as well as theoretical point of view. Considerable work has been done in this regard in the past decade or so. However, most models are limited in their scope and as a result only capture general features of spreading phenomena. Here, we propose and study a model of spreading which takes into account the strength or quality of contagions as well as the local (probabilistic) dynamics occurring at various nodes. Transmission occurs only after the quality-based fitness of the contagion has been evaluated by the local agent. The model exhibits quality-dependent exponential time scales at early times leading to a slowly evolving quasi-stationary state. Low prevalence is seen for a wide range of contagion quality for arbitrary large networks. We also investigate the activity of nodes and find a power-law distribution with a robust exponent independent of network topology. Our results are consistent with recent empirical observations.Comment: 7 pages, 8 figures. (Submitted

Association of serum uric acid with high-sensitivity C-reactive protein in postmenopausal women.

OBJECTIVES: To explore the independent correlation between serum uric acid and low-grade inflammation (measured by high-sensitivity C-reactive protein, hs-CRP) in postmenopausal women. METHODS: A total of 378 healthy Iranian postmenopausal women were randomly selected in a population-based study. Circulating hs-CRP levels were measured by highly specific enzyme-linked immunosorbent assay method and an enzymatic calorimetric method was used to measure serum levels of uric acid. Pearson correlation coefficient, multiple linear regression and logistic regression models were used to analyze the association between uric acid and hs-CRP levels. RESULTS: A statistically significant correlation was seen between serum levels of uric acid and log-transformed circulating hs-CRP (r = 0.25, p < 0.001). After adjustment for age and cardiovascular risk factors (according to NCEP ATP III criteria), circulating hs-CRP levels were significantly associated with serum uric acid levels (β = 0.20, p < 0.001). After adjustment for age and cardiovascular risk factors, hs-CRP levels ≥3 mg/l were significantly associated with higher uric acid levels (odds ratio =1.52, 95% confidence interval 1.18-1.96). CONCLUSION: Higher serum uric acid levels were positively and independently associated with circulating hs-CRP in healthy postmenopausal women. KEYWORDS: C-reactive protein; Uric acid; inflammation; postmenopaus