The Economic Archaeology of Roman Economic Performance

Recent years have witnessed a paradigm shift in the study of the Roman economy. Methodologically modern economic analysis is now far more acceptable than it once was, and archaeology has become the major source of empirical data for many questions. On the substantive side there is now a far clearer appreciation of the major changes that the Roman economy underwent, with substantial growth of population and aggregate production and even some improvements in standard of living, but followed by equally dramatic decline. This economic success was not limited to the imperial core, but also extended to the provinces

Assessing flood risk at the global scale: model setup, results, and sensitivity

Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures

Understanding Terrorist Organizations with a Dynamic Model

Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization's membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.Comment: To appear as Springer Lecture Notes in Computer Science v2: vectorized 4 figures, fixed two typos, more detailed bibliograph

Acoustic and perceptual evaluation of Mandarin tone productions before and after perceptual training

This is the publisher's version, also available electronically from http://scitation.aip.org/content/asa/journal/jasa/113/2/10.1121/1.1531176.Training American listeners to perceive Mandarin tones has been shown to be effective, with trainees’ identification improving by 21%. Improvement also generalized to new stimuli and new talkers, and was retained when tested six months after training [Y. Wang et al., J. Acoust. Soc. Am. 106, 3649–3658 (1999)]. The present study investigates whether the tonecontrasts gained perceptually transferred to production. Before their perception pretest and after their post-test, the trainees were recorded producing a list of Mandarin words. Their productions were first judged by native Mandarin listeners in an identification task. Identification of trainees’ post-test tone productions improved by 18% relative to their pretest productions, indicating significant tone production improvement after perceptual training. Acoustic analyses of the pre- and post-training productions further reveal the nature of the improvement, showing that post-training tone contours approximate native norms to a greater degree than pretraining tone contours. Furthermore, pitch height and pitch contour are not mastered in parallel, with the former being more resistant to improvement than the latter. These results are discussed in terms of the relationship between non-native tone perception and production as well as learning at the suprasegmental level

The detection and location estimation of disasters using Twitter and the identification of Non-Governmental Organisations using crowdsourcing

status: publishe

Training American listeners to perceive Mandarin tones

This is the publisher's version, also available electronically from http://scitation.aip.org/content/asa/journal/jasa/106/6/10.1121/1.428217.Auditory training has been shown to be effective in the identification of non-native segmental distinctions. In this study, it was investigated whether such training is applicable to the acquisition of non-native suprasegmentalcontrasts, i.e., Mandarin tones. Using the high-variability paradigm, eight American learners of Mandarin were trained in eight sessions during the course of two weeks to identify the four tones in natural words produced by native Mandarin talkers. The trainees’ identification accuracy revealed an average 21% increase from the pretest to the post-test, and the improvement gained in training was generalized to new stimuli (18% increase) and to new talkers and stimuli (25% increase). Moreover, the six-month retention test showed that the improvement was retained long after training by an average 21% increase from the pretest. The results are discussed in terms of non-native suprasegmental perceptual modification, and the analogies between L2 acquisition processes at the segmental and suprasegmental levels

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application

An increase in food production in Europe could dramatically affect farmland biodiversity

Conversion of semi-natural habitats, such as field margins, fallows, hedgerows, grassland, woodlots and forests, to agricultural land could increase agricultural production and help meet rising global food demand. Yet, the extent to which such habitat loss would impact biodiversity and wild species is unknown. Here we survey species richness for four taxa (vascular plants, earthworms, spiders, wild bees) and agricultural yield across a range of arable, grassland, mixed, horticulture, permanent crop, for organic and non-organic agricultural land on 169 farms across 10 European regions. We find that semi-natural habitats currently constitute 23% of land area with 49% of species unique to these habitats. We estimate that conversion of semi-natural land that achieves a 10% increase in agricultural production will have the greatest impact on biodiversity in arable systems and the least impact in grassland systems, with organic practices having better species retention than non-organic practices. Our findings will help inform sustainable agricultural development

Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions

Although satellite-based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS-EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS-EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long-term coordinated actions