Local versus landscape spatial influence on biodiversity: a case study across five European industrialized areas

Land use change—mostly habitat loss and fragmentation—has been recognized as one of the major drivers of biodiversity loss worldwide. According to the habitat amount hypothesis, these phenomena are mostly driven by the habitat area effect. As a result, species richness is a function of both the extent of suitable habitats and their availability in the surrounding landscape, irrespective of the dimension and isolation of patches of suitable habitat. In this context, we tested how the extent of natural areas, selected as proxies of suitable habitats for biodiversity, influences species richness in highly anthropogenic landscapes. We defined five circular sampling areas of 5 km radius, including both natural reserves and anthropogenic land uses, centred in five major industrial sites in France, Italy and Germany. We monitored different biodiversity indicators for both terrestrial and aquatic ecosystems, including breeding birds, diurnal butterflies, grassland vegetation, odonata, amphibians, aquatic plants and benthic diatoms. We studied the response of the different indicators to the extent of natural land uses in the sampling area (local effect) and in the surrounding landscape (landscape effect), identified as a peripheral ring encircling the sampling area. Results showed a positive response of five out of seven biodiversity indicators, with aquatic plants and odonata responding positively to the local effect, while birds, vegetation and diatoms showed a positive response to the landscape effect. Diatoms also showed a significant combined response to both effects. We conclude that surrounding landscapes act as important biodiversity sources, increasing the local biodiversity in highly anthropogenic contexts.     

Outbreak of fatal nitrate toxicosis associated with consumption of fennels (Foeniculum vulgare) in cattle farmed in Campania region (southern Italy)

Nitrate and nitrite are toxicants that have become increasingly significant environmental chemicals. Increase in environmental distribution of nitrogenous compounds, especially in surface and ground water, has been attributed to the intensive use of nitrate as agricultural fertilizers and to increasing amounts of nitrogenous wastes produced by municipalities, industries, and feedlots. The purpose of this study is to illustrate a fatal nitrate toxicosis in cattle associated with the consumption of fennels (Foeniculum vulgare). Fifteen cows from the same farm suddenly developed weakness, muscular tremors, respiratory distress, and finally convulsions. The affected animals died within 24 to 48 h from the onset of the clinical signs. Five cows underwent a complete post-mortem examination. In all examined animals, gross lesions included presence of dark unclotted blood around the nostrils and the anal region, moderate inflammation of the gastrointestinal mucosa, and brown discoloration of the skeletal muscles and kidneys. The histological examination showed tubular degeneration and congestion of glomerular vessels in the kidney. Toxicological analysis detected nitrates at 4 672.2 ppm in the fennels used to feed the animals. The source of exposure to nitrates was identified in the fennels. The fennels were grown in a polluted area of the Campania region in southern Italy and distributed in a public market for human consumption. The waste from the sale of the fennels was fed to the cows. The accumulation of nitrates in some vegetables poses a risk not only for animal health but also for human and environmental safety.     

Leaching of S-metolachlor,terbuthylazine, desethyl-terbuthylazine,mesotrione, flufenacet,isoxaflutole, and diketonitrile in field lysimeters as affected by the time elapsed between spraying and first leaching event

The effect of elapsed time between spraying and first leaching event on the leaching behavior of five herbicides (terbuthylazine, S-metolachlor, mesotrione, flufenacet, and isoxaflutole) and two metabolites (desethyl-terbuthylazine and diketonitrile) was evaluated in a 2011–2012 study in northwest Italy. A battery of 12 lysimeters (8.4 m² long with a depth of 1.8 m) were used in the study, each filled with silty-loam soil and treated during pre-emergence with the selected herbicides by applying a mixture of commercial products Lumax (4 L ha^?1) and Merlin Gold (1 L ha^?1). During treatment periods, no gravity water was present in lysimeters. Irrigation events capable of producing leaching (40 mm) were conducted on independent groups of three lysimeters on 1 day after treatment (1 DAT), 7 DAT, 14 DAT, and 28 DAT. The series was then repeated 14 days later. Leachate samples were collected a few days after irrigation; compounds were extracted by solid phase extraction and analyzed by high-performance liquid chromatography and gas chromatography–mass spectrometry. Under study conditions, terbuthylazine and S-metolachlor showed the highest leaching potentials. Specifically, S-metolachlor concentrations were always found above 0.25 µg L^?1. Desethyl-terbuthylazine was often detected in leached waters, in most cases at concentrations above 0.1 µg L^?1. Flufenacet leached only when irrigation occurred close to the time of herbicide spraying. Isoxaflutole and mesotrione were not measured (<0.1 µg L^?1), while diketonitrile was detected in concentrations above 0.1 µg L^?1 on 1 DAT in 2011 only.     

Mapping Cumulative Environmental Risks: Examples from the EU NoMiracle Project

We present examples of cumulative chemical risk mapping methods developed within the NoMiracle project. The different examples illustrate the application of the concentration addition (CA) approach to pesticides at different scale, the integration in space of cumulative risks to individual organisms under the CA assumption, and two techniques to (1) integrate risks using data-driven, parametric statistical methods, and (2) cluster together areas with similar occurrence of different risk factors, respectively. The examples are used to discuss some general issues, particularly on the conventional nature of cumulative risk maps, and may provide some suggestions for the practice of cumulative risk mapping.