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

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

Examining the reactive proactive questionnaire in adults in forensic and non-forensic settings: A variable- and person-based approach.

The Reactive Proactive Questionnaire (RPQ) was originally developed to assess reactive and proactive aggressive behavior in children. Nevertheless, some studies have used the RPQ in adults. This study examines the reliability of the RPQ within an adult sample by investigating whether reactive and proactive aggression can be distinguished at a variable- and person-based level. Male adults from forensic samples (N = 237) and from the general population (N = 278) completed the RPQ questionnaire. Variable-based approaches, including factor analyses, were conducted to verify the two-factor model of the RPQ and to examine alternative factor solutions of the 23 items. Subsequently, a person-based approach, i.e., Latent Class Analysis (LCA), was executed to identify homogeneous classes of subjects with similar profiles of aggression in the observed data. The RPQ proved to have sufficient internal consistency. Multiple-factor models were examined, but the original two-factor model was statistically and theoretically considered as most solid and in line with previous research. The multi-level LCA identified three different classes of aggression severity (class 1 showed low aggressive behavior; class 2 subjects displayed modest aggression levels; and class 3 exhibited the highest level of aggressive behavior). In addition, class 1 and 2 showed more reactive than proactive aggression, whereas class 3 displayed comparable levels of reactive/proactive aggression. The RPQ appears to have clinical relevance for adult populations in the way that it can distinguish severity levels of aggression. Before the RPQ is implemented in adult populations, norm scores need to be developed. Aggr. Behav. 43:155-162, 2017. (c) 2016 Wiley Periodicals, Inc

Generation of Up to Date Land Cover Maps for Central Asia

Human activity and climate variability has always changed the Earth’s surface and both will mainly contribute to future alteration in land cover and land use changes. In this chapte we demonstrate a land cover and land use classification approach for Central Asia addressing regional characteristics of the study area. With the aim of regional classification map for Central Asia a specific classification scheme based on the Land Cover Classification System (LCCS) of the Food and Agriculture Organisation of the United Nations Environment Programme (FAO-UNEP) was developed. The classification was performed by using a supervised classification method applied on metrics, which were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data with 250 m spatial resolution. The metrics wer derived from annual time-series of red and nearinfrared reflectance as well as from Normalized Difference Vegetation Index (NDVI) and thus reflect the temporal behavior of different land cover types. Reference data required for a supervised classification approach were collected from several high resolution satellite imagery distributed all over the study area. The overall accuracy results for performed classification of the year 2001 and 2009 are 91.2 and 91.3 %. The comparison of both classification maps shows significant alterations for different classes. Water bodies such as Shardara Water Reservoir and Aral Sea have changed in their extent. Whereby, the size of the Shardara Water Reservoir is very dynamic from year to year due to water management and the eastern lobe of southern Aral Sea has decreased because of the lack of inflow from Amu Darja. Furthermore, some large scale changes were detected in sparsely vegetated areas in Turkmenistan, where spring precipitation mainly affects the vegetation density. In the north of Kazakhstan significant forest losses caused by forest fires and logging were detected. The presented classification approach is a suitable tool for monitoring land cover and land use in Central Asia. Such independent information is important for accurate assessment of water and land recourses

Liver involvement in congenital disorders of glycosylation (CDG). A systematic review of the literature

Congenital disorders of glycosylation (CDG) are a rapidly growing family of genetic diseases caused by defects in glycosylation. Nearly 100 CDG types are known so far. Patients present a great phenotypic diversity ranging from poly- to mono-organ/system involvement and from very mild to extremely severe presentation. In this literature review, we summarize the liver involvement reported in CDG patients. Although liver involvement is present in only a minority of the reported CDG types (22 %), it can be debilitating or even life-threatening. Sixteen of the patients we collated here developed cirrhosis, 10 had liver failure. We distinguish two main groups: on the one hand, the CDG types with predominant or isolated liver involvement including MPI-CDG, TMEM199-CDG, CCDC115-CDG, and ATP6AP1-CDG, and on the other hand, the CDG types associated with liver disease but not as a striking, unique or predominant feature, including PMM2-CDG, ALG1-CDG, ALG3-CDG, ALG6-CDG, ALG8-CDG, ALG9-CDG, PGM1-CDG, and COG-CDG. This review aims to facilitate CDG patient identification and to understand CDG liver involvement, hopefully leading to earlier diagnosis, and better management and treatment