A comparative error analysis of manual versus automated methods of data acquisition for algebraic strain estimation

This paper presents a statistical analysis of the algebraic strain estimation algorithm of Shimamoto and Ikeda [Shimamoto, T., Ikeda, Y., 1976. A simple algebraic method for strain estimation from deformed eillipsoidal objects: 1. Basic theory. Tectonophysics 36, 315–337]. It is argued that the error in their strain estimation procedure can be quantified using an expected discrepancy measure. An analysis of this measure demonstrates that the error is inversely proportional to the number of clasts used. The paper also examines the role of measurement error, in particular that incurred under (i) a moment based and (ii) manual data acquisition methods. Detailed analysis of these two acquisition methods shows that in both cases, the effect of measurement error on the expected discrepancy is small relative to the effect of the sample size (number of objects). Given their relative speed advantage, this result favours the use of automated measurement methods even if they incur more measurement error on individual objects. Validation of these results is carried out by means of a simulation study, as well as by reference to studies appearing in previous literature. The results are also applied to obtain an upper bound on the error of strain estimation for various studies published in the literature on strain analysis.     

Driving forces of tropical deforestation: The role of remote sensing and spatial models

Remote sensing technologies are increasingly used to monitor landscape change in many parts of the world. While the availability of extensive and timely imagery from various satellite sensors can aid in identifying the rates and patterns of deforestation, modelling techniques can evaluate the socioeconomic and biophysical forces driving deforestation processes. This paper briefly reviews some emerging spatial methodologies aimed at identifying driving forces of land use change and applies one such methodology to understand deforestation in Mexico. Satellite image classification, change analysis and econometric modelling are used to identify the rates, hotspots and drivers of deforestation in a case study of the southern Yucatán peninsular region, an enumerated global hotspot of biodiversity and tropical deforestation. In particular, the relative roles of biophysical and socioeconomic factors in driving regional deforestation rates are evaluated. Such methodological approaches can be applied to other regions of the forested tropics and contribute insights to conservation planning and policy.     

Flood Damage Reduction Program (FDRP) in Québec: Case Study of the Chaudiére River

This study presents the evolution of agreements between the governments of Canadaand Québec on flood damage reduction. In Québec, the implementation of a regulation about building in floodplains came about in 1983–1984. Today, this regulation takes the form of a policy called ``Policy of shores, littoral and floodplain protection'. Municipalities must adopt rules that concur with the principles of this policy.The Chaudiére River basin was selected for analysis of urban developmentduring the period following the application of building rules in flood-risk areas.Despite the ban on building in the strong current zone (0–20 year return periodflood zone), many buildings, essentially residential, have been erected in thiszone. These new constructions generally account for a low percentage of thetotal property value in the 0–100 year flooding area, but are legal since theyare connected to a water and sewage network that existed prior to the officialfloodplain regulation.Flood damage along the Chaudiére River will tend to increase for two reasons.Firstly, while respecting the policy mentioned above, sites are still available infloodplains for future development. Secondly, no structural flood protection workshave been erected in view of the fact they are only marginally profitable from anbenefit-cost point of view.     

Re-Os Isotopic Measurements at the Femtomole Level in Natural Samples

Here we describe a new chemical separation method for Os and an improved mass spectrometric procedure for Re and Os. This technique is based on the selective extraction of OsO₄ from aqueous solution in liquid bromine. Among other advantages, this procedure avoids the cumbersome distillation procedure for Os and uses only commercial "off the shelf" PFA teflon labware. Blank levels for 0.5 g sample sizes are: 0.06 pg and 0.5 pg for Os and Re respectively. Samples containing as little as 1 pg g⁻¹ Os can be analysed reliably with this method. Adaptation to other dissolution methods is also discussed.     

Effects of Greenhouse Gas Emissions on World Agriculture, Food Consumption, and Economic Welfare

Because of many uncertainties, quantitative estimates of agriculturally related economic impacts of greenhouse gas emissions are often given low confidence. A major source of uncertainty is our inability to accurately project future changes in economic activity, emissions, and climate. This paper focuses on two issues. First, to what extent do variable projections of climate generate uncertainty in agriculturally related economic impacts? Second, to what extent do agriculturally related economic impacts of greenhouse gas emissions depend on economic conditions at the time of impacts? Results indicate that uncertainty due to variable projections of climate is fairly large for most of the economic effects evaluated in this analysis. Results also indicate that economic conditions at the time of impact influence the direction and size of as well as the confidence in the economic effects of identical projections of greenhouse gas impacts. The economic variable that behaves most consistently in this analysis is world crop production. Increases in mean global temperature, for example, cause world crop production to decrease on average under both 1990 and improved economic conditions and in both instances the confidence with respect to variable projections of climate is medium (e.g.,67%) or greater. In addition and as expected, CO₂ fertilization causesworld crop production to increase on average under 1990 and improved economic conditions. These results suggest that crop production may be a fairly robust indicator of the potential impacts of greenhouse gas emissions.A somewhat unexpected finding is that improved economic conditions are not necessarily a panacea to potential greenhouse-gas-induced damages, particularly at the region level. In fact, in some regions, impacts of climate change or CO₂ fertilization that are beneficial undercurrent economic conditions may be detrimental under improved economic conditions (relative to the new economic base). Australia plus New Zealand suffer from this effect in this analysis because under improved economic conditions they are assumed to obtain a relatively large share of income from agricultural exports. When the climate-change and CO₂-fertilization scenariosin this analysis are also included, agricultural exports from Australia plus New Zealand decline on average. The resultant declines in agricultural income in Australia plus New Zealand are too large to be completely offset by rising incomes in other sectors. This indicates that regions that rely on agricultural exports for relatively large shares of their income may be vulnerable not only to direct climate-induced agricultural damages, but also to positive impacts induced by greenhouse gas emissions elsewhere.     

Fractal Analysis of the Complexity of United States Coastlines

Coastlines have long been used as a principal example of a natural feature that exhibits fractal structure. With the advent of large digitized databases, it has become possible to examine in detail large regions of coast and to examine differences in complexity, as measured by the fractal dimension, among regions. In this study, we have determined the fractal dimension of the Atlantic and Pacific coastlines of the conterminous United States. The traditional divider method was used in obtaining the fractal dimension of each coastline arc from the NOAA Medium-Resolution Shoreline Data Set. On average, the Atlantic coast has much higher fractal dimension than the Pacific coast. The results also indicate that the complexity of the Atlantic coast increases toward low latitudes. These results have implications for the interpretation of species distributions and diversity patterns along the coast and for the understanding of the dynamics of biotic recovery from mass extinctions.     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

Wind energy estimates by use of a diagnostic model

A diagnostic model is a relatively simple and practical tool for modeling the wind flow of the boundary layer in complex terrain. The model begins with a wind analysis based on available surface wind reports and geostrophic winds (computed from pressure data). The height of the boundary layer top (upper surface of the computational domain) is prescribed to fit local conditions. Using the continuity equation in terrain-following coordinates, the winds at mesh points are adjusted to produce nondivergence while maintaining the original vertical component of vorticity. The method of computing the nondivergent winds uses direct alterations. This method may be useful for other modeling purposes and will be described. Data for a long period (usually a year) are analyzed to obtain eigenvectors and the associated time series of their coefficients at each observation time. The model is run only for the five or six eigenvectors that explain most of the variance. The wind field at any particular time is reconstructed from the eigenvector solutions and their appropriate coefficients. Comparisons of model results with measured winds at sites representing different types of terrain will be shown. The accuracy and economy of the model make it a useful tool for estimating wind energy and also for giving wind fields for low-level diffusion models.     

Evolution of a Holocene banner bank controlled by morphodynamics and structural setting of a macrotidal coast: Saint-Brieuc Bay(NW-Europe)

The morphology and internal structure of the Horaine Bank(Bay of Saint-Brieuc, NW France) are described based on multibeam echosounder and high-resolution seismic datasets coupled with vibro-core data. The Horaine Bank shows large-scale bedforms in the lee of a submerged rocky shoal, which allowed defining it as a Banner Bank.The internal structure of the sandbank reveals four seismic units(U1–U4) on a Cambrian basement(U0). The basal unit U1 is interpreted as reworked lowstand fluvial sediments those infilled micro incised valleys during a rise in sea level. This unit is overlain by paleo-coastal barrier sand-spit(U2) whose development was controlled by swell in the context of a rapid rise in sea level. The successive prograding unit(U3) is interpreted as flooding deposits in continuity with unit U2. The unit U4 is characterized by oblique reflectors oriented in two opposite directions. This last unit, dated post 3500 yr BP, corresponds to migrating dunes superimposed on the bank and observable in the high-resolution bathymetric data. The strong correlation between tidal currents and the apparent clockwise migration of dune crests suggests the presence of a tidal gyre controlling the present-day dynamics of most of the Horaine bank dunes. This study proposes a new model for the construction of banner banks characterized by the gradual transition of a sand spit to a banner bank during marine transgression and ensuing hydrodynamic variability.