Maximum-Entropy Weighting of Multi-Component Earth Climate Models

A maximum entropy-based framework is presented for the synthesis of projections from multiple Earth climate models. This identifies the most representative (most probable) model from a set of climate models -- as defined by specified constraints -- eliminating the need to calculate the entire set. Two approaches are developed, based on individual climate models or ensembles of models, subject to a single cost (energy) constraint or competing cost-benefit constraints. A finite-time limit on the minimum cost of modifying a model synthesis framework, at finite rates of change, is also reported.Comment: Inspired by discussions at the Mathematical and Statistical Approaches to Climate Modelling and Prediction workshop, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, 11 Aug. to 22 Dec. 2010. Accepted for publication in Climate Dynamics, 8 August 201

Groundwater vulnerability assessment: A review including new statistical and hybrid methods

The concept of groundwater vulnerability was first introduced in the 1970s in France to recognize sensitive areas in which surface pollution could affect groundwater, and to enable others to develop management methods for groundwater protection against surface pollutants. Since this time, numerous methods have been developed for groundwater vulnerability assessment (GVA). These can be categorized into four groups: (i) overlay and index-based methods, (ii) process-based simulation models, (iii) statistical methods, and (iv) hybrid methods. This work provides a comprehensive review of modern GVA methods, which in contrast to previous reviews, examines the last two categories in detail. First, the concept of groundwater vulnerability is defined, then the major GVA methods are introduced and classified. This includes detailed accounts of statistical methods, which can be subdivided into orthodox statistical, data-driven and Bayesian methods, and their advantages and disadvantages, as well as modern hybrid methods. It is concluded that Bayesian inference offers many advantages compared with other GVA methods. It combines theory and data to give the posterior probabilities of different models, which can be continually updated with new data. Furthermore, using the Bayesian approach, it is possible to calculate the probability of a proposition, which is exactly what is needed to make decisions. However, despite the advantages of Bayesian inference, its applications to date have been very limited

Comparison of DRASTIC and DRASTICL groundwater vulnerability assessments of the Burdekin Basin, Queensland, Australia

In the Burdekin Basin, Queensland, Australia, groundwater contamination due to agricultural activities has led to concerns over its impacts on globally significant ecosystems such as the Great Barrier Reef. An appropriate method for groundwater vulnerability assessment is essential for the sustainable use of this groundwater resource and its longer-term environmental management. The aim of this study is to apply and assess the suitability of the standard DRASTIC index-based method for groundwater vulnerability assessment of the Burdekin Basin. The intrinsic groundwater vulnerability is calculated in ArcGIS, using data for the period 2010 to 2021. The results are compared to available water quality data. The calculated DRASTIC scores are found to be only weakly correlated with water quality parameters, including the nitrate concentration (R = 0.07), which should behave as a proxy measure of groundwater vulnerability. To address this, a modified DRASTICL method containing a land use parameter is also implemented, to assess the specific groundwater vulnerability. The correlation between DRASTICL scores and nitrate levels (R = 0.2) is more significant but is still relatively weak. From this study, it is recommended that alternative methods be developed to assess groundwater vulnerability in the Burdekin Basin, and other comparable aquifer systems

Zipf's Law : Balancing signal usage cost and communication efficiency

Copyright: © 2015 Salge et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedWe propose a model that explains the reliable emergence of power laws (e.g., Zipf's law) during the development of different human languages. The model incorporates the principle of least effort in communications, minimizing a combination of the information-Theoretic communication inefficiency and direct signal cost. We prove a general relationship, for all optimal languages, between the signal cost distribution and the resulting distribution of signals. Zipf's law then emerges for logarithmic signal cost distributions, which is the cost distribution expected for words constructed from letters or phonemes. Copyright:Peer reviewedFinal Published versio

Differences in the Aerobic Capacity of Flight Muscles between Butterfly Populations and Species with Dissimilar Flight Abilities

Habitat loss and climate change are rapidly converting natural habitats and thereby increasing the significance of dispersal capacity for vulnerable species. Flight is necessary for dispersal in many insects, and differences in dispersal capacity may reflect dissimilarities in flight muscle aerobic capacity. In a large metapopulation of the Glanville fritillary butterfly in the Åland Islands in Finland, adults disperse frequently between small local populations. Individuals found in newly established populations have higher flight metabolic rates and field-measured dispersal distances than butterflies in old populations. To assess possible differences in flight muscle aerobic capacity among Glanville fritillary populations, enzyme activities and tissue concentrations of the mitochondrial protein Cytochrome-c Oxidase (CytOx) were measured and compared with four other species of Nymphalid butterflies. Flight muscle structure and mitochondrial density were also examined in the Glanville fritillary and a long-distance migrant, the red admiral. Glanville fritillaries from new populations had significantly higher aerobic capacities than individuals from old populations. Comparing the different species, strong-flying butterfly species had higher flight muscle CytOx content and enzymatic activity than short-distance fliers, and mitochondria were larger and more numerous in the flight muscle of the red admiral than the Glanville fritillary. These results suggest that superior dispersal capacity of butterflies in new populations of the Glanville fritillary is due in part to greater aerobic capacity, though this species has a low aerobic capacity in general when compared with known strong fliers. Low aerobic capacity may limit dispersal ability of the Glanville fritillary.Peer reviewe