Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km² spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Tropical broadleaf trees contribute almost half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which have a widespread distribution. The annual global isoprene emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene (440 to 660 Tg carbon) depending on the driving variables which include temperature, solar radiation, Leaf Area Index, and plant functional type. The global annual isoprene emission estimated using the standard driving variables is ~600 Tg isoprene. Differences in driving variables result in emission estimates that differ by more than a factor of three for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models, due to the substantial uncertainties in other model components, but at least some global models produce reasonable results when using isoprene emission distributions similar to MEGAN estimates. In addition, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and land-use) demonstrates the potential for large future changes in emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions

A Logging Operation on the Jicarilla Apache Reservation

It may be the fault of the teachers who taught us geography, or it may be our own fault, but most of us have entertained the idea that New Mexico is a barren treeless waste but quite the contrary is true, especially in the northern and western parts of the state. The original stand of timber was estimated at over eighteen billion feet, most of which was Western Yellow Pine

Short Subjects: Athens and Sparta: The Archivist and Resource Allocators

One result of the social, economic, and technological changes and developments of the past two decades has been an increased monetary pressure on educational institutions. Rare is the academic or other nonprofit institution that has not found it necessary to mount a fund-raising campaign. Economic pressures on educational institutions are not new nor are efforts to solve them. What is new is the intensity and pervasiveness. of monetary accountability, the professionalism . employed in fund raising, and the web of involvement that affects everyone in an administrative position, no matter how minor. Fiscal responsibilities that once were confined to the province of presidents, treasurers, and governing boards now fall within the accountability of all levels of administration. Archives ·administrators are faced not with a problem but \u27with a challenge: How do archives get their share of the pie from resource allocators and through the efforts of professional institutional fund raisers

Numerical computation of an Evans function for travelling waves

We demonstrate a geometrically inspired technique for computing Evans functions for the linearised operators about travelling waves. Using the examples of the F-KPP equation and a Keller-Segel model of bacterial chemotaxis, we produce an Evans function which is computable through several orders of magnitude in the spectral parameter and show how such a function can naturally be extended into the continuous spectrum. In both examples, we use this function to numerically verify the absence of eigenvalues in a large region of the right half of the spectral plane. We also include a new proof of spectral stability in the appropriate weighted space of travelling waves of speed $c \geq 2 \sqrt{\delta}$ in the F-KPP equation.Comment: 37 pages, 11 figure

MissForest - nonparametric missing value imputation for mixed-type data

Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set. Missing value imputation offers a solution to this problem. However, the majority of available imputation methods are restricted to one type of variable only: continuous or categorical. For mixed-type data the different types are usually handled separately. Therefore, these methods ignore possible relations between variable types. We propose a nonparametric method which can cope with different types of variables simultaneously. We compare several state of the art methods for the imputation of missing values. We propose and evaluate an iterative imputation method (missForest) based on a random forest. By averaging over many unpruned classification or regression trees random forest intrinsically constitutes a multiple imputation scheme. Using the built-in out-of-bag error estimates of random forest we are able to estimate the imputation error without the need of a test set. Evaluation is performed on multiple data sets coming from a diverse selection of biological fields with artificially introduced missing values ranging from 10% to 30%. We show that missForest can successfully handle missing values, particularly in data sets including different types of variables. In our comparative study missForest outperforms other methods of imputation especially in data settings where complex interactions and nonlinear relations are suspected. The out-of-bag imputation error estimates of missForest prove to be adequate in all settings. Additionally, missForest exhibits attractive computational efficiency and can cope with high-dimensional data.Comment: Submitted to Oxford Journal's Bioinformatics on 3rd of May 201

Room temperature spin relaxation in GaAs/AlGaAs multiple quantum wells

We have explored the dependence of electron spin relaxation in undoped GaAs/AlGaAs quantum wells on well width (confinement energy) at 300 K. For wide wells, the relaxation rate tends to the intrinsic bulk value due to the D'yakonov-Perel (DP) mechanism with momentum scattering by phonons. In narrower wells, there is a strong dependence of relaxation rate on well width, as expected for the DP mechanism, but also considerable variation between samples from different sources, which we attribute to differences in sample interface morphology. (C) 1998 American Institute of Physics. [S0003-6951(98)02541-8].</p

Should Marketing be Cross-Functional? : Conceptual Development and International Empirical Evidence

While it has frequently been stated that decisions on marketing activities should be made cross-functionally, there is no empirical evidence that shows benefits of performing marketing activities in this way. This paper examines the link between the cross-functional dispersion of influence on marketing activities and performance at the SBU level and considers dynamism of the market which may moderate the strength of this relationship. Using data from a cross-national study in three industry sectors, the authors find that cross-functional dispersion of influence on marketing activities increases the performance of the SBU. They also find that the relationship between the cross-functional dispersion of influence on marketing activities is negatively influenced by dynamism of the market. This research thus provides empirical evidence for the positive performance implications of cross-functional interaction in the context of marketing activities