Throughout the past century, vegetation scientists have been studying plant communities to develop classification standards for global mapping purposes. In Turkey, although there are several vegetation classification schemes in use by botanists, foresters or geographers, none is widely accepted by all for vegetation mapping. In this study, a hierarchical, ecologically meaningful, physiognomic-floristic classification system was adapted and developed for terrestrial vegetation in Turkey. The system has eight hierarchical levels, with the alliance and the association as its lowest two floristic levels, and the classes are designed to be easily detected in the field or indirectly through remote sensing. To test of its utility, a supervised vegetation classification of the whole Mediterranean Region of Turkey was carried out using Landsat ETM images. The accuracy of the classification ranged between 55% and 69% depending on the level of hierarchy. A further test for its ecological utility was carried out by comparing identified vegetation classes with breeding bird communities derived from data gathered through field observations at 193 ecological communities at 83 sites. The proposed classification scheme has proven to be reasonably accurate when widely available satellite imagery is used and ecologically meaningful as shown by a high concordance with observed bird community patterns. It is suggested that this new system can be safely applied to other regions of Turkey for purposes of vegetation mapping, species habitat modeling, and nature conservation if proper image set and ancillary data is used.

ABSTRACT Classifying and Mapping Diversity in a Species-Poor System: the mangrove meta-community of Laguna Chacahua National Park, Oaxaca, Mexico by Elizabeth Kay Weisgerber Both field transects and imagery grid plots were analyzed with the goal of creating a community classification map for the mangrove forest of Parque Nacional Lagunas de Chacahua. In total, data was collected in 49 sites throughout the park, recording measures such as DBH, basal area, estimated dominance, frequency, cover and relative dominance. Field locations were marked and georeferenced with a GPS and grid plots overlaid on satellite imagery of the park were generated via a random number table. Species' attributes delineating the identifiable features for each dominant species within Chacahua were noted and used to recognize patterns in species assemblages. Fourteen distinct ‘sub-communities’ within the mangrove meta-community were recognized using this data and verified with 165 field photos. Relative dominance values were compared between field and grid data. These data revealed a similar pattern with Rhizophora mangle being most dominant under each method. Avicennia germinans was second in relative dominance, Laguncularia racemosa a close third while Conocarpus erectus was rarely found, most likely due to over-harvesting. Rapid degradation of mangrove forests is occurring on a global scale. Understanding the complex dynamics that occur within the mangrove meta-community is essential to its conservation. Vegetation maps are essential tool in monitoring changes throughout the mangrove but are rarely of sufficient detail for everyday use. Generating highly detailed vegetation maps in a cost-effective and timely manner is an important step for their conservation, particularly in developing countries. This study demonstrates methods and techniques for producing a vegetation map that portrays the level of complexity that exists within the species-poor mangrove environment. This map will be donated to the management team of Parque Nacional Lagunas de Chacahua to better aid in management.