Katja Brinkmann

Effects of socio-economic household characteristics on traditional knowledge and usage of wild yams and medicinal plants in the Mahafaly region of south-western Madagascar

BackgroundRural households in the Mahafaly region of semi-arid SW-Madagascar strongly depend on the exploitation of natural resources for their basic needs and income regeneration. An overuse of such resources threatens the natural environment and people’s livelihood. Our study focuses on the diversity and use of wild yams and medicinal plants.MethodsWe hypothesized that knowledge on the use of these resources highly depends on farmers’ socio-economic household characteristics. To test this hypothesis, an ethnobotanical survey was conducted based on semi-structured interviews recording socio-economic base data and information on local knowledge of medicinal and wild yam species. This was followed by field inventories compiling plant material for botanical identification.ResultsSix species of wild yam and a total of 214 medicinal plants from 68 families and 163 genera were identified. Cluster and discriminant analysis yielded two groups of households with different wealth status characterized by differences in livestock numbers, off-farm activities, agricultural land and harvests. A generalized linear model highlighted that economic factors significantly affect the collection of wild yams, whereas the use of medicinal plants depends to a higher degree on socio-cultural factors.ConclusionsWild yams play an important role in local food security in the Mahafaly region, especially for poor farmers, and medicinal plants are a primary source of health care for the majority of local people. Our results indicate the influence of socio-economic household characteristics on the use of forest products and its intensity, which should be considered in future management plans for local and regional forest conservation.

Temporal and spatial changes of land use in rare metal mining areas of Rwanda

Abstract To analyse the effects of mining activities on land use and land cover changes in the Gatumba mining district of Rwanda, aerial photos from 1958, 1974 and 2009 were classified using segmentation approaches. Drastic land cover changes were observed in the study region with the highest mining activities in 1974. From 1958 to 1974, woodland decreased by 54% and cropland increased rapidly. From 1974 to 2009 the process reversed, with woodland increasing while cropland decreased by 51%. This was mainly due to enforced legal regulations of the Government of Rwanda to control land degradation and a decline of mining activities.

ACQUISITION AND AUTOMATED RECTIFICATION OF HIGH-RESOLUTION RGB AND NEAR-IR AERIAL PHOTOGRAPHS TO ESTIMATE PLANT BIOMASS AND SURFACE TOPOGRAPHY IN ARID AGRO-ECOSYSTEMS

Increasing image resolution and shrinking camera size facilitates easy mounting of digital cameras on Unmanned Aerial Vehicles (UAVs) to collect large amounts of high-resolution aerial photos for soil surface and vegetation monitoring. Major challenges remain geo-referencing of these images, reliable stitching (mosaicking), elimination of geometric image distortions and compensation of limited image quality and high cost of the equipment. In this study, we report upon the design and field-testing of a custom-made, cost-effective mini-UAV allowing the acquisition of RGB and near-IR images covering areas of 1–2 km 2 in each flight and the development of a software tool to automatically combine the geo-referenced images into a seamless image mosaic. Object-orientated image classification was used to estimate plant biomass. The images allowed to determine the distribution and biomass of selected plant species and other landscape features such as field borders and settlement patterns as well as to construct a simple 3D model of the topography of the surveyed area. The setup facilitates the cost-effective acquisition, mosaicking and classification of hundreds of RGB and near-IR images with a spatial resolution of 5–10 cm.

Transformation processes in farming systems and surrounding areas of Inle Lake, Myanmar, during the last 40 years

Inle Lake in Eastern Myanmar is strongly affected by environmental effects of rapid population growth and an increase in the agricultural and tourist sector. To identify land use and land cover changes (LUCC), a post-classification comparison method was employed using historical Corona images (1968) and Landsat data (1989, 2000 and 2009). A supervised classification was performed for the Landsat datasets, whereas a visual interpretation was used for the Corona images. During the last 40 years, the dominant landscape transformation processes were urbanization (+203%), crop expansion (+34%) with a particular increase of floating gardens (+390%), land abandonment (+167%), deforestation (−49%) and wetland losses in marshlands (−83%) and waterbodies (−16%). The main driving forces of LUCC appeared to be population increase, industrial activities, government policies, widespread rural poverty and changes in market prices and access.