Modelling change in the Peruvian-Chilean Eastern Pacific Fisheries

Time-series analyses of the Peruvian-Chilean Eastern Pacific Fisheries output are presented. The paper discusses how human action and adverse environmental conditions have affected regional productivity levels and fish stock. It is shown that overfishing during critical environmental periods is the likely cause for fluctuations in regional output and the decline of Peru's fishing (anchovy) industry, in opposition to the theory that holds that stock depletion is caused solely by ENSO (El Niño/Southern Oscillation) events. Policy implications are drawn from empirical findings, tressing the need for strict resource management and future restrictions on fish captures when ENSO events are highly probable.     

The effect of thermal treatment on the 57Fe Mössbauer spectrum of beryl

Mössbauer spectra (MS) of blue, green and yellow beryl (ideally Be₃Al₂Si₆O₁₈) containing approximately 1% of iron were obtained at 295 and 500 K. Room temperature (RT) spectra of both blue and green samples showed the presence of an asymmetric Fe²⁺ doublet (ΔE _Q~2.7 mm/s, δ~1.1 mm/s), with a very broad low-velocity peak. There is no clear evidence for the presence of a ferric component. The MS of the yellow sample at RT consists of an intense central absorption with parameters typical for Fe³⁺ (ΔE _Q~0.4 mm/s, δ~0.29 mm/s), plus an apparently symmetrical Fe²⁺ doublet. This sample acquires a light-blue shade upon heating in air at about 620 K. Thermal treatments at high temperatures caused no significant changes in the MS, but the green and yellow beryl acquire a blue colour. All these results are interpreted in relation to the existence of channel water and the distribution of iron among the available crystallographic sites.     

Clustering and visualization of earthquake data in a grid environment

We present a web client-server service WEB-IS, which we have developed for remote analysis and visualization of seismic data consisting of both small magnitude events and large earthquakes. We show that the problem-solving environment (PSE) intended for prediction of large magnitude earthquakes can be based on this WEB-IS idea. The clustering schemes, feature generation, feature extraction techniques and rendering algorithms form a computational framework of this environment. On the other hand, easy and fast access both to the seismic data distributed among distant computing resources and to computational and visualization resources can be realized in a GRID framework. We discuss the usefulness of NaradaBrokering (iNtegrated Asynchronous Real-time Adaptive Distributed Architecture) as a middleware, allowing for flexibility and high throughput for remote visualization of geophysical data. The WEB-IS functionality was tested both on synthetic and the actual earthquake catalogs. We consider the application of similar methodology for tsunami alerts.     

Observation-based blended projections from ensembles of regional climate models

We consider the problem of projecting future climate from ensembles of regional climate model (RCM) simulations using results from the North American Regional Climate Change Assessment Program (NARCCAP). To this end, we develop a hierarchical Bayesian space-time model that quantifies the discrepancies between different members of an ensemble of RCMs corresponding to present day conditions, and observational records. Discrepancies are then propagated into the future to obtain high resolution blended projections of 21st century climate. In addition to blended projections, the proposed method provides location-dependent comparisons between the different simulations by estimating the different modes of spatial variability, and using the climate model-specific coefficients of the spatial factors for comparisons. The approach has the flexibility to provide projections at customizable scales of potential interest to stakeholders while accounting for the uncertainties associated with projections at these scales based on a comprehensive statistical framework. We demonstrate the methodology with simulations from the Weather Research & Forecasting regional model (WRF) using three different boundary conditions. We use simulations for two time periods: current climate conditions, covering 1971 to 2000, and future climate conditions under the Special Report on Emissions Scenarios (SRES) A2 emissions scenario, covering 2041 to 2070. We investigate and project yearly mean summer and winter temperatures for a domain in the South West of the United States.     

A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa,Peru

The town of Santa Teresa (Cusco Region, Peru) has been affected by several large debris-flow events in the recent past, which destroyed parts of the town and resulted in a resettlement of the municipality. Here, we present a risk analysis and a risk management strategy for debris-flows and glacier lake outbursts in the Sacsara catchment. Data scarcity and limited understanding of both physical and social processes impede a full quantitative risk assessment. Therefore, a bottom-up approach is chosen in order to establish an integrated risk management strategy that is robust against uncertainties in the risk analysis. With the Rapid Mass Movement Simulation (RAMMS) model, a reconstruction of a major event from 1998 in the Sacsara catchment is calculated, including a sensitivity analysis for various model parameters. Based on the simulation results, potential future debris-flows scenarios of different magnitudes, including outbursts of two glacier lakes, are modeled for assessing the hazard. For the local communities in the catchment, the hazard assessment is complemented by the analysis of high-resolution satellite imagery and fieldwork. Physical, social, economic, and institutional vulnerability are considered for the vulnerability assessment, and risk is eventually evaluated by crossing the local hazard maps with the vulnerability. Based on this risk analysis, a risk management strategy is developed, consisting of three complementing elements: (i) standardized risk sheets for the communities; (ii) activities with the local population and authorities to increase social and institutional preparedness; and (iii) a simple Early Warning System. By combining scientific, technical, and social aspects, this work is an example of a framework for an integrated risk management strategy in a data scarce, remote mountain catchment in a developing country.     

Classify-normalize-classify

Changing atmospheric conditions often result in a data distribution shift in remote sensing images for different dates and locations making it difficult to discriminate between various classes of interest. To alleviate this data shift issue, we introduce a novel supervised classification framework, called Classify-Normalize-Classify (CNC). The proposed scheme uses a two classifier approach where the first classifier performs a rough segmentation of the class of interest (COI) in the input image. Then, the median signal of the estimated COI regions is subtracted from all image pixels values to normalize them. Finally, the second classifier is applied to the normalized image to produce the refined COI segmentation. The proposed methodology was tested to detect deforestation using bitemporal Landsat 8 OLI images over the Amazon rainforest. The CNC framework compared favorably to benchmark masks of the PRODES program and state-of-the-art classifiers run on surface reflectance images provided by USGS.     

Ecotoxicological evaluation of dredged sediments from Rodrigo de Freitas Lagoon (Rio de Janeiro State,Brazil) using bioassays with earthworms and collembolans

The toxicity and metal bioavailability were studied in dredged sediments from Rodrigo de Freitas Lagoon (Rio de Janeiro, RJ, Brazil) using acute and avoidance tests with Eisenia andrei, and reproduction tests with Folsomia candida. The sediment was mixed with an artificial soil, and two natural soils (ferralsol and chernosol—representative Brazilian tropical soils) to obtain the following doses: 1, 3, 6, 12, 18, 24 and 30%. Total metal concentrations were determined in the sediment to support the interpretation of ecotoxicological data. Metal concentrations in the mixtures were in agreement with the threshold limits established by Brazilian law. However, significant avoidance responses were found on doses ≥?3% and were the most sensitive endpoint. Earthworm mortality found in artificial soil mixtures (LC50?=?3.9) suggests higher toxicity levels than those obtained in ferralsol (LC50?=?7.6%) and chernosol (11.0%) treatments. Earthworm mortality, avoidance responses and collembolan reproduction levels found in ferralsol mixtures (LC50?=?9.2; avoidance EC50?=?2.3%; reproduction EC50?=?2.8%) were higher compared to chernosol treatments (LC50?=?11.0%; avoidance EC50?=?4.3%; reproduction EC50?=?4.9%). The reduction of toxicity levels in chernosol mixtures is probably due to the abundance of expansive clay minerals in chernosols with capacity of adsorbing metals and other xenobiotic substances from soil pore water, decreasing metal bioavailability. Finally, threshold limits defined by Brazilian legislation for soil quality and land disposal of dredged sediments are not sufficient to prevent noxious effects on soil fauna and should be complemented with a preliminary ecotoxicological evaluation.