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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.

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Question: Can we predict the spatial distribution of plant communities in semi‐arid rangelands based on a limited set of environmental variables? Where are priority areas for conservation located? Location: Al Jabal al Akhdar, Sultanate of Oman. Methods: A Classification Tree Analysis (CTA) was used to model the presence/absence of seven rangeland communities and agricultural areas based on seven selected environmental predictor variables. The latter were either obtained from existing digital datasets or derived from a digital elevation model and satellite images, whereas the grazing intensity was spatially modelled with the kernel density estimation technique. The resulting decision rules of a CTA were applied for predictive mapping within the study area (400 km2, resolution of 5 m) by means of ENVI's decision tree classifier. Plant communities of natural rangelands were subsequently evaluated to determine priority areas for nature conservation. Results: Altitude, grazing intensity and landform revealed the highest predictive power. Most of the rangelands were predicted as Sideroxylon–Oleetum. The overall classification accuracy was 89%, whereby agricultural areas and the Ziziphus spina‐christi‐Nerium oleander community at wadi sites had no misclassification. Inaccuracies occurred mainly because of low sample numbers and errors in available maps of predictor variables. The highest rank for nature conservation was observed for the Teucrio‐Juniperetum occupying 20% of the study area. Conclusions: Vegetation mapping using CTA is a valuable tool for rangeland monitoring and identification of key representative areas for nature conservation. An extrapolation of the model used might be feasible to regions adjacent to the central Hajar Mountains.