Selected nucleon form factors and a composite scalar diquark

A covariant, composite scalar diquark, Fadde'ev amplitude model for the nucleon is used to calculate pseudoscalar, isoscalar- and isovector-vector, axial-vector and scalar nucleon form factors. The last yields the nucleon sigma-term and on-shell sigma-nucleon coupling. The calculated form factors are soft, and the couplings are generally in good agreement with experiment and other determinations. Elements in the dressed-quark-axial-vector vertex that are not constrained by the Ward-Takahashi identity contribute ~20% to the magnitude of g_A. The calculation of the nucleon sigma-term elucidates the only unambiguous means of extrapolating meson-nucleon couplings off the meson mass-shell.Comment: 12 pages, REVTEX, 5 figures, epsfi

Analytic properties of the Landau gauge gluon and quark propagators

We explore the analytic structure of the gluon and quark propagators of Landau gauge QCD from numerical solutions of the coupled system of renormalized Dyson--Schwinger equations and from fits to lattice data. We find sizable negative norm contributions in the transverse gluon propagator indicating the absence of the transverse gluon from the physical spectrum. A simple analytic structure for the gluon propagator is proposed. For the quark propagator we find evidence for a mass-like singularity on the real timelike momentum axis, with a mass of 350 to 500 MeV. Within the employed Green's functions approach we identify a crucial term in the quark-gluon vertex that leads to a positive definite Schwinger function for the quark propagator.Comment: 42 pages, 16 figures, revtex; version to be published in Phys Rev

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Phases in Group Development: The Negative Evidence

Evidence contrary to the widely held view that groups move through discernible developmental phases is analyzed in detail. Definitional issues relating to phases in group development and group types are considered. Reviews and thirteen studies (to 1981) cited by others as not supporting the existence of developmental trends are mterpreted in this context. Methodological and conceptual problems are noted. The negative evidence as such does not seem persuasive. It ts concluded that researchers\u27 attention should no longer be devoted to trying to provide a yes or no answer to the question Do groups change? but rather to identifying significant differences and similarities in group development among various groups and types of groups, and to relating variations in developmental processes to important group outcomes