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High Explanatory Power (high + explanatory_power)
Selected AbstractsThe latitudinal gradient of beta diversity in relation to climate and topography for mammals in North AmericaGLOBAL ECOLOGY, Issue 1 2009Hong Qian ABSTRACT Aim Spatial turnover of species, or beta diversity, varies in relation to geographical distance and environmental conditions, as well as spatial scale. We evaluated the explanatory power of distance, climate and topography on beta diversity of mammalian faunas of North America in relation to latitude. Location North America north of Mexico. Methods The study area was divided into 313 equal-area quadrats (241 × 241 km). Faunal data for all continental mammals were compiled for these quadrats, which were divided among five latitudinal zones. These zones were comparable in terms of latitudinal and longitudinal span, climatic gradients and elevational gradients. We used the natural logarithm of the Jaccard index (lnJ) to measure species turnover between pairs of quadrats within each latitudinal zone. The slope of lnJ in relation to distance was compared among latitudinal zones. We used partial regression to partition the variance in lnJ into the components uniquely explained by distance and by environmental differences, as well as jointly by distance and environmental differences. Results Mammalian faunas of North America differ more from each other at lower latitudes than at higher latitudes. Regression models of lnJ in relation to distance, climatic difference and topographic difference for each zone demonstrated that these variables have high explanatory power that diminishes with latitude. Beta diversity is higher for zones with higher mean annual temperature, lower seasonality of temperature and greater topographic complexity. For each latitudinal zone, distance and environmental differences explain a greater proportion of the variance in lnJ than distance, climate or topography does separately. Main conclusions The latitudinal gradient in beta diversity of North American mammals corresponds to a macroclimatic gradient of decreasing mean annual temperature and increasing seasonality of temperature from south to north. Most of the variance in spatial turnover is explained by distance and environmental differences jointly rather than distance, climate or topography separately. The high predictive power of geographical distance, climatic conditions and topography on spatial turnover could result from the direct effects of physical limiting factors or from ecological and evolutionary processes that are also influenced by the geographical template. [source] Origins and characteristics of Nearctic landbirds in Britain and Ireland in autumn: a statistical analysisIBIS, Issue 4 2006IAN A. MCLAREN We used data from eastern North America in regressions to explain autumn frequencies of Nearctic landbird species in Britain and Ireland (UK-IR). The data were: day-counts of 16 August,15 November from Nova Scotia (NS) on Sable Island 1963,2000 and Seal Island (1963,2002), combined in half-monthly intervals to account for seasonality; published seasonal totals (10- to 11-day intervals, 20 August,10 November 1955,80) of birds killed at a Florida (FL) TV tower; and published counts following a ,Fallout', 11 October 1998, of unseasonal species and southern vagrants in NS, believed to have originated as migrants in the southeast USA that followed a cold front offshore into strong southwest flow beyond. We also used the following species variables: body mass and wing length for size; sd of mass as a proxy for lipid capacity; a five-level index of migratory span (1 for within North America to 5 for almost totally to South America); latitude of easternmost breeding, and distance to nearest normal range to indicate status in NS; a two-level index for day vs. night migrants; an index, where pertinent, of significant population change (0 and 2 for a decrease and increase, respectively, 1 for no change). We also used classification and regression trees to cluster the potential transatlantic vagrants into homogeneous groups based on the explanatory variables. Standard generalized linear model regressions using counts from NS islands and FL produced highly positively skewed residuals (many species too common in UK-IR), but robust regressions eliminated statistical problems, and strengthened effects of non-count variables. Results using Fallout records, representing a subset of longer-distance night migrants, were statistically acceptable. The Fallout list, when supplied with counts from the same species from the NS islands and FL, produced highly significant (R2 = 0.79,0.93) and statistically acceptable regressions that were not improved by robust versions. Overall, the results indicate that October counts, especially of generally larger, longer-distance migrants, best represented those reaching UK-IR. The effect of geographical remoteness was negative , vagrants in NS were less likely to appear in UK-IR. Population changes were important in predicting the 1956,2003 UK-IR counts from 1955,80 FL counts. The seasonal characteristics, high explanatory power of the Fallout list and over-representation of probable over-ocean migrants in the standard regressions all support suggestions by others that many Nearctic vagrants in UK-IR originate in flights off southeast USA and are displaced downwind across the North Atlantic. [source] Measurements of area and the (island) species,area relationship: new directions for an old patternOIKOS, Issue 10 2008Kostas A. Triantis The species,area relationship is one of the strongest empirical generalizations in geographical ecology, yet controversy persists about some important questions concerning its causality and application. Here, using more accurate measures of island surface size for five different island systems, we show that increasing the accuracy of the estimation of area has negligible impact on the fit and form of the species,area relationship, even though our analyses included some of the most topographically diverse island groups in the world. In addition, we show that the inclusion of general measurements of environmental heterogeneity (in the form of the so-called choros model), can substantially improve the descriptive power of models of island species number. We suggest that quantification of other variables, apart from area, that are also critical for the establishment of biodiversity and at the same time have high explanatory power (such as island age, distance, productivity, energy, and environmental heterogeneity), is necessary if we are to build up a more predictive science of species richness variation across island systems. [source] Implied correlation index: A new measure of diversificationTHE JOURNAL OF FUTURES MARKETS, Issue 2 2005Vasiliki D. Skintzi Most approaches in forecasting future correlation depend on the use of historical information as their basic information set. Recently, there have been some attempts to use the notion of "implied" correlation as a more accurate measure of future correlation. This study proposes an innovative methodology for backing-out implied correlation measures from index options. This new measure called implied correlation index reflects the market view of the future level of the diversification in the market portfolio represented by the index. The methodology is applied to the Dow Jones Industrial Average index, and the statistical properties and the dynamics of the proposed implied correlation measure are examined. The evidence of this study indicates that the implied correlation index fluctuates substantially over time and displays strong dynamic dependence. Moreover, there is a systematic tendency for the implied correlation index to increase when the market index returns decrease and/or the market volatility increases, indicating limited diversification when it is needed most. Finally, the forecast performance of the implied correlation index is assessed. Although the implied correlation index is a biased forecast of realized correlation, it has a high explanatory power, and it is orthogonal to the information set compared to a historical forecast. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:171,197, 2005 [source] | ||||||||||