65 research outputs found

    Atmospheric particulate matter (PM) effect on the growth of Solanum lycopersicum cv. Roma plants

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    This study shows the direct effect of atmospheric particulate matter on plant growth. Tomato (Solanum lycopersicum L.) plants were grown for 18. d directly on PM10 collected on quartz fiber filters. Organic and elemental carbon and polycyclic aromatic hydrocarbons (PAHs) contents were analyzed on all the tested filters. The toxicity indicators (i.e., seed germination, root elongation, shoot and/or fresh root weight, chlorophyll and carotenoids content) were quantified to study the negative and/or positive effects in the plants via root uptake. Substantial differences were found in the growth of the root apparatus with respect to that of the control plants. A 17-58% decrease of primary root elongation, a large amount of secondary roots and a decrease in shoot (32%) and root (53-70%) weights were found. Quantitative analysis of the reactive oxygen species (ROS) indicated that an oxidative burst in response to abiotic stress occurred in roots directly grown on PM10, and this detrimental effect was also confirmed by the findings on the chlorophyll content and chlorophyll-to-carotenoid ratio

    Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: A Mediterranean assessment

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    Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result

    Habitat mapping and change detection in Natura2000 coastal sites in Southern Apulia

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    Monitoring biodiversity at habitat and landscape level is becoming widespread in Europe and elsewhere as countries establish national and international habitat conservation policies and monitoring systems. Long-term habitat mapping and change detection are essential for the management of coastal wetlands as well as for evaluating the impact of conservation policies. Earth observation (EO) data and techniques are a valuable resource for long-term habitat mapping, through direct mapping of habitats or by integrating Land Cover/Use (LC/LU) maps with contextual spatial information and in situ data. The Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) has been identified as the most effective for translating EO-derived LC/LU classes to habitat types, since it allows a better description of natural habitats in comparison to other classification systems; moreover, LCCS has proven to be a effective tool in change detection, both at the level of conversion and modification (Tomaselli et al., 2013; Adamo et al 2014). As regards the present contribution, vegetation, LC and habitat mapping has been performed on three coastal sites belonging to the Natura 2000 and located in Southern Apulia (Italy), in years 2007 and 2015. Vegetation maps represented the baseline position for natural and semi-natural types, defined as phytosociological units in accordance with the Zurich-Montpellier method. Vegetation units were then reclassified in habitat types (according to the Annex I to the 92/43 EEC Directive and EUNIS) and in LC classes (according to Corine Land Cover and LCCS). The adopted landscape classification procedure refers to a hierarchical model with three different information levels: the vegetation unit, the habitat type, and the LC type. The mapping products were then compared, in the different acquisitions, in order to point out the ability of different taxonomies in detecting changes in vegetation and habitat types. LCCS turned out to be the most effective, highlighting changes such as height, structure and density, which were not evidenced with other classification systems

    Vegetation survey and plant landscape mapping of the SCI IT9140002 "Litorale Brindisino" (Puglia, Southern Italy)

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    A vegetation survey of the SCI IT9140002 - "Litorale Brindisino" (Apulia Region, Italy), with a focus on the coastal environments, along with vegetation and habitat maps, are here presented. The SCI is a coastal site characterized by dunes and salt marshes and, landwards, by garrigues, maquis and grasslands. The coastal belt is characterized by a highly fragmented landscape, because of anthropogenic pressures and coastal erosion. The vegetation was studied according to the phytosociological method and the survey led to the identification of 22 plant communities belonging to 11 syntaxonomic classes. Vegetation and habitat maps were digitized in ArcGis 10.2 from recent orthophotos in combination with topographical maps, at a scale of 1:5,000. The presence of several complex vegetation mosaics was highlighted
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