Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes

In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.     

Effects of Stock Use and Backpackers on Water Quality in Wilderness in Sequoia and Kings Canyon National Parks, USA

During 2010–2011, a study was conducted in Sequoia and Kings Canyon National Parks (SEKI) to evaluate the influence of pack animals (stock) and backpackers on water quality in wilderness lakes and streams. The study had three main components: (1) a synoptic survey of water quality in wilderness areas of the parks, (2) paired water quality sampling above and below several areas with differing types and amounts of visitor use, and (3) intensive monitoring at six sites to document temporal variations in water quality. Data from the synoptic water quality survey indicated that wilderness lakes and streams are dilute and have low nutrient and Escherichia coli concentrations. The synoptic survey sites were categorized as minimal use, backpacker-use, or mixed use (stock and backpackers), depending on the most prevalent type of use upstream from the sampling locations. Sites with mixed use tended to have higher concentrations of most constituents (including E. coli) than those categorized as minimal-use (P ≤ 0.05); concentrations at backpacker-use sites were intermediate. Data from paired-site sampling indicated that E. coli, total coliform, and particulate phosphorus concentrations were greater in streams downstream from mixed-use areas than upstream from those areas (P ≤ 0.05). Paired-site data also indicated few statistically significant differences in nutrient, E. coli, or total coliform concentrations in streams upstream and downstream from backpacker-use areas. The intensive-monitoring data indicated that nutrient and E. coli concentrations normally were low, except during storms, when notable increases in concentrations of E. coli, nutrients, dissolved organic carbon, and turbidity occurred. In summary, results from this study indicate that water quality in SEKI wilderness generally is good, except during storms; and visitor use appears to have a small, but statistically significant influence on stream water quality.     

Optimal Pollution Trading Without Pollution Reductions: A Note1

García, Jorge H., Matthew T. Heberling, and Hale W. Thurston, 2011. Optimal Pollution Trading Without Pollution Reductions: A Note. Journal of the American Water Resources Association (JAWRA) 47(1):52‐58. DOI: 10.1111/j.1752‐1688.2010.00476.x Abstract: Various kinds of water pollution occur in pulses (e.g., agricultural and urban runoff). Ecosystems, such as wetlands, can serve to regulate these pulses and smooth pollution distributions over time. This smoothing reduces total environmental damages when “instantaneous” damages are marginally increasing. This paper introduces a water quality trading model between a farm (a pulse‐pollution source) and a firm (a more steady pollution source) where the object of exchange is the “temporary” retention of runoff as opposed to total runoff reductions. The optimal trading ratio requires firm emissions to be offset by more than a proportional retention of the initial agricultural runoff pulse. The reason is twofold: (1) emissions are steady or constant over time and, in this sense, have relatively larger environmental impact; and (2) certain kinds of runoff management cause delayed environmental damages.     

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.     

Predator–prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator–prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.     

Polyhydroxyalkanoates: Biosynthesis from Alternative Carbon Sources and Analytic Methods: A Short Review

Journal of Polymers and the Environment - In recent decades, the global accumulation of plastics and the resulting pollution, as well as the increase in the price of oil, have driven studies aimed...     

Hydrothermal carbonization of biomass and waste: A review

Environmental Chemistry Letters - The replacement of traditional and non-renewable resources by shifting towards renewable-based strategies is a strategy implemented by the European Union...     

Phycobiliproteins extract from Spirulina protects against single-dose cadmium-induced reproductive toxicity in male mice

Environmental Science and Pollution Research - Cadmium (Cd) is known for its many toxic effects on male population such as hypogonadism and fertility difficulties, which are oftenly associated with...     

Correction to: Socioeconomic Risks of Extreme El Niño Event-Related Road Damages in Peru

Environmental Modeling & Assessment -     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.