Monitoring dioxins and furans in the vicinity of an old municipal waste incinerator after pronounced reductions of the atmospheric emissions

In order to get an overall picture of the environmental impact of an old municipal solid waste incinerator (MSWI) from S. Adrià del Besòs (Barcelona, Catalonia, Spain), a monitoring program addressed at determining the levels of a number of pollutants in the vicinity of the facility was initiated in 1998. In March 1999, an adaptation was carried out due to EU legislation on pollutant emissions from the stack. As a result, emissions of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) were notably reduced, and a significant (30%) decrease was found in the levels of PCDD/F in herbage samples collected in the vicinity of the MSWI. In March 2001, herbage samples were collected at the same sampling points and the PCDD/F levels measured again. The current PCDD/F concentrations range from 0.23 to 1.43 ng I-TEQ kg(-1) (dry matter), with median and mean values of 0.58 and 0.66 ng I-TEQ kg(-1) (dry matter), respectively, while in the 2000 survey the PCDD/F concentrations ranged from 0.22 to 1.20 ng I-TEQ kg(-1) (dry matter), with median and mean values of 0.57 and 0.61 ng I-TEQ kg(-1) (dry matter), respectively. Although the current PCDD/F concentrations in herbage samples are comparable to those found in recent surveys carried out in various places of Catalonia, an exhaustive evaluation of the data, including principal component analysis, indicates that other emission sources of PCDD/Fs also have a notable environmental impact on the area under direct influence of the MSWI.     

Thresholds of species loss in Amazonian deforestation frontier landscapes

In the Brazilian Amazon, private land accounts for the majority of remaining native vegetation. Understanding how land‐use change affects the composition and distribution of biodiversity in farmlands is critical for improving conservation strategies in the face of rapid agricultural expansion. Working across an area exceeding 3 million ha in the southwestern state of Rondônia, we assessed how the extent and configuration of remnant forest in replicate 10,000‐ha landscapes has affected the occurrence of a suite of Amazonian mammals and birds. In each of 31 landscapes, we used field sampling and semistructured interviews with landowners to determine the presence of 28 large and medium sized mammals and birds, as well as a further 7 understory birds. We then combined results of field surveys and interviews with a probabilistic model of deforestation. We found strong evidence for a threshold response of sampled biodiversity to landscape level forest cover; landscapes with <30–40% forest cover hosted markedly fewer species. Results from field surveys and interviews yielded similar thresholds. These results imply that in partially deforested landscapes many species are susceptible to extirpation following relatively small additional reductions in forest area. In the model of deforestation by 2030 the number of 10,000‐ha landscapes under a conservative threshold of 43% forest cover almost doubled, such that only 22% of landscapes would likely to be able to sustain at least 75% of the 35 focal species we sampled. Brazilian law requires rural property owners in the Amazon to retain 80% forest cover, although this is rarely achieved. Prioritizing efforts to ensure that entire landscapes, rather than individual farms, retain at least 50% forest cover may help safeguard native biodiversity in private forest reserves in the Amazon. Umbrales de Pérdida de Especies en los Paisajes Fronterizos de Deforestación en el Amazonas Ochoa‐Quintero     

On sensitivity analysis: Let’s use it more!

The key factors that influence the population growth rate can be identified with sensitivity analysis. Caswell presented an algorithm based on vector calculus that speeds up, and improves the practicality of the application of the sensitivity analysis, by calculating the derivatives of the explicit elements from the population Leslie matrix. Despite the usefulness of the sensitivity analysis, it is still barely applied to empirical data, partially due to requirements of high quality demographic data and failure of compatibility between time intervals of field data collection and organism’s life stage timing. This can result in the absence of a certain vital rate as a separated element in the population projection matrix, and thus intricacy in obtaining its sensitivity. In this note we call the attention for the applied value of sensitivity analysis, and also we point to a simple formula that is easily implemented in Caswell Matlab algorithm, to calculate the sensitivity of a vital rate that is not explicit as a matrix element.