Global Dataset (global + dataset)

Distribution by Scientific Domains

Selected Abstracts

Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened

ECONOMIC NOTES, Issue 2 2005
Greg M. Gupton
We describe LossCalcÔ version 2.0: the Moody's KMV model to predict loss given default (LGD), the equivalent of (1 , recovery rate). LossCalc is a statistical model that applies multiple predictive factors at different information levels: collateral, instrument, firm, industry, country and the macroeconomy to predict LGD. We find that distance-to-default measures (from the Moody's KMV structural model of default likelihood) compiled at both the industry and firm levels are predictive of LGD. We find that recovery rates worldwide are predictable within a common statistical framework, which suggests that the estimation of economic firm value (which is then available to allocate to claimants according to each country's bankruptcy laws) is a dominant step in LGD determination. LossCalc is built on a global dataset of 3,026 recovery observations for loans, bonds and preferred stock from 1981 to 2004. This dataset includes 1,424 defaults of both public and private firms , both rated and unrated instruments , in all industries. We demonstrate out-of-sample and out-of-time LGD model validation. The model significantly improves on the use of historical recovery averages to predict LGD. [source]

Global trends in senesced-leaf nitrogen and phosphorus

GLOBAL ECOLOGY, Issue 5 2009
Zhiyou Yuan
ABSTRACT Aim, Senesced-leaf litter plays an important role in the functioning of terrestrial ecosystems. While green-leaf nutrients have been reported to be affected by climatic factors at the global scale, the global patterns of senesced-leaf nutrients are not well understood. Location, Global. Methods, Here, bringing together a global dataset of senesced-leaf N and P spanning 1253 observations and 638 plant species at 365 sites and of associated mean climatic indices, we describe the world-wide trends in senesced-leaf N and P and their stoichiometric ratios. Results, Concentration of senesced-leaf N was highest in tropical forests, intermediate in boreal, temperate, and mediterranean forests and grasslands, and lowest in tundra, whereas P concentration was highest in grasslands, lowest in tropical forests and intermediate in other ecosystems. Tropical forests had the highest N : P and C : P ratios in senesced leaves. When all data were pooled, N concentration significantly increased, but senesced-leaf P concentration decreased with increasing mean annual temperature (MAT) and mean annual precipitation (MAP). The N : P and C : P ratios also increased with MAT and MAP, but C : N ratios decreased. Plant functional type (PFT), i.e. life-form (grass, herb, shrub or tree), phylogeny (angiosperm versus gymnosperm) and leaf habit (deciduous versus evergreen), affected senesced-leaf N, P, N : P, C : N and C : P with a ranking of senesced-leaf N from high to low: forbs , shrubs , trees > grasses, while the ranking of P was forbs , shrubs , trees < grasses. The climatic trends of senesced-leaf N and P and their stoichiometric ratios were similar between PFTs. Main conclusions, Globally, senesced-leaf N and P concentrations differed among ecosystem types, from tropical forest to tundra. Differences were significantly related to global climate variables such as MAT and MAP and also related to plant functional types. These results at the global scale suggest that nutrient feedback to soil through leaf senescence depends on both the climatic conditions and the plant composition of an ecosystem. [source]

Richness patterns, species distributions and the principle of extreme deconstruction

GLOBAL ECOLOGY, Issue 2 2009
Levi Carina Terribile
ABSTRACT Aim, To analyse the global patterns in species richness of Viperidae snakes through the deconstruction of richness into sets of species according to their distribution models, range size, body size and phylogenetic structure, and to test if environmental drivers explaining the geographical ranges of species are similar to those explaining richness patterns, something we called the extreme deconstruction principle. Location, Global. Methods, We generated a global dataset of 228 terrestrial viperid snakes, which included geographical ranges (mapped at 1° resolution, for a grid with 7331 cells world-wide), body sizes and phylogenetic relationships among species. We used logistic regression (generalized linear model; GLM) to model species geographical ranges with five environmental predictors. Sets of species richness were also generated for large and small-bodied species, for basal and derived species and for four classes of geographical range sizes. Richness patterns were also modelled against the five environmental variables through standard ordinary least squares (OLS) multiple regressions. These subsets are replications to test if environmental factors driving species geographical ranges can be directly associated with those explaining richness patterns. Results, Around 48% of the total variance in viperid richness was explained by the environmental model, but richness sets revealed different patterns across the world. The similarity between OLS coefficients and the primacy of variables across species geographical range GLMs was equal to 0.645 when analysing all viperid snakes. Thus, in general, when an environmental predictor it is important to model species geographical ranges, this predictor is also important when modelling richness, so that the extreme deconstruction principle holds. However, replicating this correlation using subsets of species within different categories in body size, range size and phylogenetic structure gave more variable results, with correlations between GLM and OLS coefficients varying from ,0.46 up to 0.83. Despite this, there is a relatively high correspondence (r = 0.73) between the similarity of GLM-OLS coefficients and R2 values of richness models, indicating that when richness is well explained by the environment, the relative importance of environmental drivers is similar in the richness OLS and its corresponding set of GLMs. Main conclusions, The deconstruction of species richness based on macroecological traits revealed that, at least for range size and phylogenetic level, the causes underlying patterns in viperid richness differ for the various sets of species. On the other hand, our analyses of extreme deconstruction using GLM for species geographical range support the idea that, if environmental drivers determine the geographical distribution of species by establishing niche boundaries, it is expected, at least in theory, that the overlap among ranges (i.e. richness) will reveal similar effects of these environmental drivers. Richness patterns may be indeed viewed as macroecological consequences of population-level processes acting on species geographical ranges. [source]

A test of the generality of leaf trait relationships on the Tibetan Plateau

Jin-Sheng He
Summary ,,Leaf mass per area (LMA), nitrogen concentration (on mass and area bases, Nmass and Narea, respectively), photosynthetic capacity (Amass and Aarea) and photosynthetic nitrogen use efficiency (PNUE) are key foliar traits, but few data are available from cold, high-altitude environments. ,,Here, we systematically measured these leaf traits in 74 species at 49 research sites on the Tibetan Plateau to examine how these traits, measured near the extremes of plant tolerance, compare with global patterns. ,,Overall, Tibetan species had higher leaf nitrogen concentrations and photosynthetic capacities compared with a global dataset, but they had a slightly lower Amass at a given Nmass. These leaf trait relationships were consistent with those reported from the global dataset, with slopes of the standardized major axes Amass,LMA, Nmass,LMA and Amass,Nmass identical to those from the global dataset. Climate only weakly modulated leaf traits. ,,Our data indicate that covarying sets of leaf traits are consistent across environments and biogeographic regions. Our results demonstrate functional convergence of leaf trait relationships in an extreme environment. [source]

Global perspective on hydrology, water balance, and water resources management in arid basins

Yanjun Shen
Abstract Arid and semiarid regions comprise a large part of the world's terrestrial area and are home to hundreds of millions of people. Water resources in arid regions are rare and critical to society and to ecosystems. The hydrologic cycle in arid and semiarid regions has been greatly altered due to long-term human exploitation. Under conditions of global warming, water resources in these regions are expected to be more unstable and ecosystems likely will suffer from severe water stress. In the current special issue contributed to understanding ecohydrologic processes and water-related problems in arid regions of western China, this paper provides a global perspective on the hydrology and water balance of six major arid basins of the world. A number of global datasets, including the state-of-the-art ensemble simulation of land surface models by GSWP2 (Global Soil Wetness Project II, a project by GEWEX), were used to address the water balance terms in the world's major hydroclimatic regions. The common characteristics of hydrologic cycles and water balance in arid basins are as follows: strong evapotranspiration characterizes the hydrological cycle in arid basins; and in water use sectors irrigation consumes a large amount of water, resulting in degradation of native vegetation. From the ecohydrology viewpoint, a comprehensive study of hydrological and ecological processes of water utilization in arid basins is urgently needed. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Recent developments in gravity-wave effects in climate models and the global distribution of gravity-wave momentum flux from observations and models

M. J. Alexander
Abstract Recent observational and theoretical studies of the global properties of small-scale atmospheric gravity waves have highlighted the global effects of these waves on the circulation from the surface to the middle atmosphere. The effects of gravity waves on the large-scale circulation have long been treated via parametrizations in both climate and weather-forecasting applications. In these parametrizations, key parameters describe the global distributions of gravity-wave momentum flux, wavelengths and frequencies. Until recently, global observations could not define the required parameters because the waves are small in scale and intermittent in occurrence. Recent satellite and other global datasets with improved resolution, along with innovative analysis methods, are now providing constraints for the parametrizations that can improve the treatment of these waves in climate-prediction models. Research using very-high-resolution global models has also recently demonstrated the capability to resolve gravity waves and their circulation effects, and when tested against observations these models show some very realistic properties. Here we review recent studies on gravity-wave effects in stratosphere-resolving climate models, recent observations and analysis methods that reveal global patterns in gravity-wave momentum fluxes and results of very-high-resolution model studies, and we outline some future research requirements to improve the treatment of these waves in climate simulations. Copyright © 2010 Royal Meteorological Society and Crown in the right of Canada [source]