Fear of the unknown: local knowledge and perceptions of the Eurasian lynx

The remnant population of Balkan lynx Lynx lynx martinoi is small, isolated and highly threatened. Since 2006 a conservation project has surveyed its status and promoted its recovery in Albania and Macedonia. Eurasian lynx are often associated with conflicts of an economic or social nature, and their conservation requires a focus on the people sharing the landscape with the species. In this study we adopt methods and conceptual frameworks from anthropology to explore the local knowledge and perceptions of lynx among rural hunters and livestock breeders in the western mountains of the Republic of Macedonia in south-east Europe. The main finding was that local people rarely saw or interacted with lynx. As the level of interactions with this species is very low, the lynx doesn?t appear to be a species associated with conflicts in Macedonia. There was also a general lack of both scientific and local knowledge, which has led to somewhat negative attitudes, mainly based on myths and rumours. Poaching of lynx and their prey seem to be the main barriers to lynx conservation.

Tools for better SLM knowledge management and informed decision-making in addressing land degradation at different scales: the WOCAT–LADA–DESIRE methodology

Desertification research conventionally focuses on the problem – that is, degradation – while neglecting the appraisal of successful conservation practices. Based on the premise that Sustainable Land Management (SLM) experiences are not sufficiently or comprehensively documented, evaluated, and shared, the World Overview of Conservation Approaches and Technologies (WOCAT) initiative (www.wocat.net), in collaboration with FAO’s Land Degradation Assessment in Drylands (LADA) project (www.fao.org/nr/lada/) and the EU’s DESIRE project (http://www.desire-project.eu/), has developed standardised tools and methods for compiling and evaluating the biophysical and socio-economic knowledge available about SLM. The tools allow SLM specialists to share their knowledge and assess the impact of SLM at the local, national, and global levels. As a whole, the WOCAT–LADA–DESIRE methodology comprises tools for documenting, self-evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing and decision support in the field, at the planning level, and in scaling up identified good practices. SLM depends on flexibility and responsiveness to changing complex ecological and socioeconomic causes of land degradation. The WOCAT tools are designed to reflect and capture this capacity of SLM. In order to take account of new challenges and meet emerging needs of WOCAT users, the tools are constantly further developed and adapted. Recent enhancements include tools for improved data analysis (impact and cost/benefit), cross-scale mapping, climate change adaptation and disaster risk management, and easier reporting on SLM best practices to UNCCD and other national and international partners. Moreover, WOCAT has begun to give land users a voice by backing conventional documentation with video clips straight from the field. To promote the scaling up of SLM, WOCAT works with key institutions and partners at the local and national level, for example advisory services and implementation projects. Keywords: Sustainable Land Management (SLM), knowledge management, decision-making, WOCAT–LADA–DESIRE methodology.

Knowledge and valuation of Andean agroforestry species: the role of sex, age, and migration among members of a rural community in Bolivia

Background Agroforestry is a sustainable land use method with a long tradition in the Bolivian Andes. A better understanding of people’s knowledge and valuation of woody species can help to adjust actor-oriented agroforestry systems. In this case study, carried out in a peasant community of the Bolivian Andes, we aimed at calculating the cultural importance of selected agroforestry species, and at analysing the intracultural variation in the cultural importance and knowledge of plants according to peasants’ sex, age, and migration. Methods Data collection was based on semi-structured interviews and freelisting exercises. Two ethnobotanical indices (Composite Salience, Cultural Importance) were used for calculating the cultural importance of plants. Intracultural variation in the cultural importance and knowledge of plants was detected by using linear and generalised linear (mixed) models. Results and discussion The culturally most important woody species were mainly trees and exotic species (e.g. Schinus molle, Prosopis laevigata, Eucalyptus globulus). We found that knowledge and valuation of plants increased with age but that they were lower for migrants; sex, by contrast, played a minor role. The age effects possibly result from decreasing ecological apparency of valuable native species, and their substitution by exotic marketable trees, loss of traditional plant uses or the use of other materials (e.g. plastic) instead of wood. Decreasing dedication to traditional farming may have led to successive abandonment of traditional tool uses, and the overall transformation of woody plant use is possibly related to diminishing medicinal knowledge. Conclusions Age and migration affect how people value woody species and what they know about their uses. For this reason, we recommend paying particular attention to the potential of native species, which could open promising perspectives especially for the young migrating peasant generation and draw their interest in agroforestry. These native species should be ecologically sound and selected on their potential to provide subsistence and promising commercial uses. In addition to offering socio-economic and environmental services, agroforestry initiatives using native trees and shrubs can play a crucial role in recovering elements of the lost ancient landscape that still forms part of local people’s collective identity.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.