Multiple-scale habitat modeling approach for rare plant conservation

Multiple-scale habitat assessment for rare plants is an important component of conservation and development planning. It is challenging, however, due to lack of information synthesis on the ecology of rare plants, lack of eff ective approaches for habitat assessment at multiple spatial scales, and la ck of spatial data for relevant environmental attributes and scales. A mult iple-scale habitat modeling approach was developed to meet this need. Regio nal-, landscape-, and site-scale habitat models were developed for eight ra re plant species found in southern Texas, USA. The models were partially va lidated and used for planning of rare plant conservation and highway constr uction. Regional-scale habitat models were used to predict, based on coarse -scale geographic information system (GIS) data, spatial distribution of ar eas containing potential habitat of rare plant species and the probability of encountering potential rare plant habitats. Site-scale models, based on synthesis of the literature and field investigations, were developed for fi eld survey and mapping of rare plant habitats to enable accurate assessment of potential and present habitat suitability of specific locations using f ine-resolution field data on soil, landform and vegetation structure. The g reatest need for assessing the presence and potential habitat of rare plant s is at the landscape scales. Thus, landscape-scale models were developed f or spatially explicit assessment of potential and present habitat suitabili ty, based on site-scale models but using GIS and remote sensing-based data. These models can be used as effective tools for conservation planning, mon itoring and management of rare plant habitat, as well as for reduction of l and use conflicts and development cost, The processes of model development and application synthesizes the diffuse literature, identifies knowledge an d data gaps to guide future research, and provides a framework for assimila ting new information acquired in the future to improve habitat assessment. (C) 2000 Elsevier Science B.V. All rights reserved.