Resistance to temperature extremes between and within life cycle stages in Drosophila serrata, D-birchii and their hybrids: intraspecific and interspecific comparisons

Intraspecific Drosophila studies suggest that resistance to heal and cold stresses are largely independent and that correlations across life cycle stages are low whereas comparisons of Drosophila species indicate correlations between heat and cold resistance as well as between resistance levels in different life cycle stages. These inconsistent results may reflect differences in associations among traits at the interspecific and intraspecific levels or interspecific correlations arising because of correlated selection pressures. These alternatives were tested using Drosophila serrata, D. birchii and hybrids derived from these species. Variation among hybrid lines and families was used to test associations at the interspecific level while intraspecific variation was examined using isofemale lines of D. serrata. There was a significant association between adult heat knockdown time at 38 degreesC and adult cold resistance in one set of hybrid lines. An association between female knockdown resistance to heat and larval heat resistance was also evident in one set of hybrids. Resistance to heat anti cold at the larval stage were not correlated at either the intraspecific or interspecific levels. At the intraspecific level, lan al heat resistance and two measures of adult heat resistance were uncorrelated. Moreover, adult and larval cold resistance measures were not correlated at either the intraspecific or interspecific levels. These results suggest that there are no associations between resistance to heat and cold extremes and that extreme temperature resistance is largely independent across life cycle stages at both the intraspecific and interspecific levels. Species associations may therefore arise from correlated selection pressures rather than trait correlations. (C) 2000 The Linnean Society of London.

Assessment of the ensembles regional climate models in the representation of precipitation variability and extremes over Portugal

A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.

A nonlinear threshold model for the dependence of extremes of stationary sequences

One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models

Climatic extremes improve predictions of spatial patterns of tree species.

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D(2), +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

2008 Statewide Monthly Temperature Monthly Extremes, 2008

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau.

Genome-wide association study of blood pressure extremes identifies variant near UMOD associated with hypertension.

Hypertension is a heritable and major contributor to the global burden of disease. The sum of rare and common genetic variants robustly identified so far explain only 1%-2% of the population variation in BP and hypertension. This suggests the existence of more undiscovered common variants. We conducted a genome-wide association study in 1,621 hypertensive cases and 1,699 controls and follow-up validation analyses in 19,845 cases and 16,541 controls using an extreme case-control design. We identified a locus on chromosome 16 in the 5' region of Uromodulin (UMOD; rs13333226, combined P value of 3.6×10(-11)). The minor G allele is associated with a lower risk of hypertension (OR [95%CI]: 0.87 [0.84-0.91]), reduced urinary uromodulin excretion, better renal function; and each copy of the G allele is associated with a 7.7% reduction in risk of CVD events after adjusting for age, sex, BMI, and smoking status (H.R. = 0.923, 95% CI 0.860-0.991; p = 0.027). In a subset of 13,446 individuals with estimated glomerular filtration rate (eGFR) measurements, we show that rs13333226 is independently associated with hypertension (unadjusted for eGFR: 0.89 [0.83-0.96], p = 0.004; after eGFR adjustment: 0.89 [0.83-0.96], p = 0.003). In clinical functional studies, we also consistently show the minor G allele is associated with lower urinary uromodulin excretion. The exclusive expression of uromodulin in the thick portion of the ascending limb of Henle suggests a putative role of this variant in hypertension through an effect on sodium homeostasis. The newly discovered UMOD locus for hypertension has the potential to give new insights into the role of uromodulin in BP regulation and to identify novel drugable targets for reducing cardiovascular risk.

Trends in indices of daily precipitation extremes in Catalonia (NE Spain), 1951-2003

The aim of this paper is to quantitatively characterize the climatology of daily precipitation indices in Catalonia (northeastern Iberian Peninsula) from 1951 to 2003. This work has been performed analyzing a subset of the ETCCDI (Expert Team on Climate Change Detection and Indices) precipitation indices calculated from a new interpolated dataset of daily precipitation, namely SPAIN02, regular at 0.2° horizontal resolution (around 20 km) and from two high-quality stations: the Ebro and Fabra observatories. Using a jack-knife technique, we have found that the sampling error of the SPAIN02 regional averaged is relatively low. The trend analysis has been implemented using a Circular Block Bootstrap procedure applicable to non-normal distributions and autocorrelated series. A running trend analysis has been applied to analyze the trend persistence. No general trends at a regional scale are observed, considering the annual or the seasonal regional averaged series of all the indices for all the time windows considered. Only the consecutive dry days index (CDD) at annual scale shows a locally coherent spatial trend pattern; around 30% of the Catalonia area has experienced an increase of around 2¿3 days decade¿1. The Ebro and Fabra observatories show a similar CDD trend, mainly due to the summer contribution. Besides this, a significant decrease in total precipitation (around ¿10 mm decade¿1) and in the index "highest precipitation amount in five-day period" (RX5DAY, around ¿5 mm decade¿1), have been found in summer for the Ebro observatory.

Phylogenetic relatedness and proboscis length contribute to structuring bumblebee communities in the extremes of abiotic and biotic gradients

Aim To improve our understanding of how biological communities assemble, we investigated changes in bumblebee communities in space along an elevation gradient. We assessed how much deterministic abiotic and biotic factors shape community assembly. We focused on proboscis length (influencing the species' dietary regime) and phylogenetic relatedness to investigate if competition and environmental filtering occur in more and less productive climates, respectively. Location Western Swiss Alps. Methods We recorded bumblebee species in 149 plots along a 1800-m wide elevation gradient. We contrasted two major clades of bumblebees, a short-tongued and a long-tongued clade. We calculated the phylogenetic and proboscis-length diversity of the bumblebee communities and compared these observed data with a random distribution to detect clustering likely to be caused by environmental filtering or overdispersion likely to be caused by competition. We compared the prevalence of clustered and overdispersed communities along the gradients of plant species richness (biotic) and temperature (abiotic). Results Under colder conditions, where plant species richness is lower and floral resources are scarcer, the clade with shorter proboscides prevails over the clade with longer proboscides, and communities are functionally and phylogenetic clustered. Under warmer conditions, we found phylogenetic but not functional overdispersion in communities. Main conclusions We show for the first time a strong correlation between phylogenetic relatedness, proboscis length and species distribution along temperature and plant richness gradients shaping bumblebee communities. The low temperatures and low levels of plant species richness limit the dispersal of the species from the long-tongued clade, which have more specialized diets, into high-elevation areas. Competition under warmer conditions may produce communities composed of less closely related species that share distinct ecological preferences. Our empirical results corroborate theoretical expectation as well as experiments on the prevalence of deterministic processes in the most severe and most productive parts of environmental gradients.