Stochastic Dominance, Entropy and Biodiversity Management

In this paper we develop a model of population dynamics using the Shannon entropy index, a measure of diversity that allows for global and specific population shocks. We model the effects of increasing the number of parcels on biodiversity, varying the number of spatially diverse parcels to capture risk diversification. We discuss the concepts of stochastic dominance as a means of project selection, in order to model biodiversity returns and risks. Using a Monte Carlo simulation we find that stochastic dominance may be a useful theoretical construct for project selections but it is unable to rank every case.

Economic Growth and Threatened and Endangered Species Listings: A VAR Analysis

We conduct several analyses to examine the link between threatened and endangered species listings and macroeconomic activity. Preliminary tests using ordinary least squares are run on both time series data on the national level and cross sectional data at the state level. The analysis is then extended using vector autoregressive (VAR) techniques. VAR results, impulse response functions and variance decompositions are reported to shed more light on the causal relationships between threatened and endangered species, GDP and population. Our results indicate that there is little or no empirical evidence that GDP growth rates lead to changes in the number of threatened and endangered species listings.

Stochastic Dominance, Entropy and Biodiversity Management

In this paper we develop a model of population dynamics using the Shannon entropy index, a measure of diversity that allows for global and specific population shocks. We model the effects of increasing the number of parcels on biodiversity, varying the number of spatially diverse parcels to capture risk diversification. We discuss the concepts of stochastic dominance as a means of project selection, in order to model biodiversity returns and risks. Using a Monte Carlo simulation we find that stochastic dominance may be a useful theoretical construct for project selections but it is unable to rank every case. Key Words: Stochastic Dominance, Entropy, Biodiversity Management

Economic Growth and Threatened and Endangered Species Listings: A VAR Analysis

We conduct several analyses to examine the link between threatened and endangered species listings and macroeconomic activity. Preliminary tests using ordinary least squares are run on both time series data on the national level and cross sectional data at the state level. The analysis is then extended using vector autoregressive (VAR) techniques. VAR results, impulse response functions and variance decompositions are reported to shed more light on the causal relationships between threatened and endangered species, GDP and population. Our results indicate that there is little or no empirical evidence that GDP growth rates lead to changes in the number of threatened and endangered species listings. Key Words: Economic growth, endangered and threatened species, vector autoregression

The state-contingent approach to production under uncertainty

The central claim of this paper is that the state-contingent approach provides the best way to think about all problems in the economics of uncertainty, including problems of consumer choice, the theory of the firm, and principal–agent relationships. This claim is illustrated by recent developments in, and applications of, the state-contingent approach.risk, state-contingent production, uncertainty, Risk and Uncertainty,

A decreased probability of habitable planet formation around low-mass stars

Smaller terrestrial planets (< 0.3 Earth masses) are less likely to retain the substantial atmospheres and ongoing tectonic activity probably required to support life. A key element in determining if sufficiently massive "sustainably habitable" planets can form is the availability of solid planet-forming material. We use dynamical simulations of terrestrial planet formation from planetary embryos and simple scaling arguments to explore the implications of correlations between terrestrial planet mass, disk mass, and the mass of the parent star. We assume that the protoplanetary disk mass scales with stellar mass as Mdisk ~ f Mstar^h, where f measures the relative disk mass, and 1/2 < h < 2, so that disk mass decreases with decreasing stellar mass. We consider systems without Jovian planets, based on current models and observations for M stars. We assume the mass of a planet formed in some annulus of a disk with given parameters is proportional to the disk mass in that annulus, and show with a suite of simulations of late-stage accretion that the adopted prescription is surprisingly accurate. Our results suggest that the fraction of systems with sufficient disk mass to form > 0.3 Earth mass habitable planets decreases for low-mass stars for every realistic combination of parameters. This "habitable fraction" is small for stellar masses below a mass in the interval 0.5 to 0.8 Solar masses, depending on disk parameters, an interval that excludes most M stars. Radial mixing and therefore water delivery are inefficient in lower-mass disks commonly found around low-mass stars, such that terrestrial planets in the habitable zones of most low-mass stars are likely to be small and dry.Comment: Accepted to ApJ. 11 pages, 6 figure

Contributions of organic and inorganic matter to sediment volume and accretion in tidal wetlands at steady state

A mixing model derived from first principles describes the bulk density ( BD) of intertidal wetland sediments as a function of loss on ignition (LOI). The model assumes that the bulk volume of sediment equates to the sum of self-packing volumes of organic and mineral components or BD = 1 / [LOI/k(1) + (1-LOI) / k(2)], where k(1) and k(2) are the self-packing densities of the pure organic and inorganic components, respectively. The model explained 78 % of the variability in total BD when fitted to 5075 measurements drawn from 33 wetlands distributed around the conterminous United States. The values of k(1) and k(2) were estimated to be 0.085 + / - 0.0007 g cm(-3) and 1.99 + / - 0.028 g cm(-3), respectively. Based on the fitted organic density (k(1)) and constrained by primary production, the model suggests that the maximum steady state accretion arising from the sequestration of refractory organic matter is \u3c = 0.3 cm yr (-1). Thus, tidal peatlands are unlikely to indefinitely survive a higher rate of sea-level rise in the absence of a significant source of mineral sediment. Application of k(2) to a mineral sediment load typical of East and eastern Gulf Coast estuaries gives a vertical accretion rate from inorganic sediment of 0.2 cm yr(-1). Total steady state accretion is the sum of the parts and therefore should not be greater than 0.5 cm yr(-1) under the assumptions of the model. Accretion rates could deviate from this value depending on variation in plant productivity, root: shoot ratio, suspended sediment concentration, sediment-capture efficiency, and episodic events

New block-based blind equalization algorithms

New block-based blind equalization algorithms are introduced based upon the cost function underlying the recently proposed soft constraint satisfaction blind equalization algorithm. The derivation of these .algorithms is based on mapping the original constrained optimization problem in CN into a much simpler optimization problem in W2. Versions of the new algorithms are also developed for fractionally-spaced equalizers. Simulations on a baud-spaced and a fractionally-spaced channel support the potential of the resulting block-based techniques

Drought Policy: A State-Contingent View

The standard approach to modelling production under uncertainty has relied on the concept of a stochastic production. In this paper, it is argued that a state-contingent production model is more flexible and realistic. The model is applied to the problem of drought policy