Multiple-scale habitat modeling approach for rare plant conservation

Abstract

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 effective approaches for habitat assessment at multiple spatial scales, and lack of spatial data for relevant environmental attributes and scales. A multiple-scale habitat modeling approach was developed to meet this need. Regional-, landscape-, and site-scale habitat models were developed for eight rare plant species found in southern Texas, USA. The models were partially validated and used for planning of rare plant conservation and highway construction. Regional-scale habitat models were used to predict, based on coarse-scale geographic information system (GIS) data, spatial distribution of areas 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 field survey and mapping of rare plant habitats to enable accurate assessment of potential and present habitat suitability of specific locations using fine-resolution field data on soil, landform and vegetation structure. The greatest need for assessing the presence and potential habitat of rare plants is at the landscape scales. Thus, landscape-scale models were developed for spatially explicit assessment of potential and present habitat suitability, based on site-scale models but using GIS and remote sensing-based data. These models can be used as effective tools for conservation planning, monitoring and management of rare plant habitat, as well as for reduction of land use conflicts and development cost. The processes of model development and application synthesizes the diffuse literature, identifies knowledge and data gaps to guide future research, and provides a framework for assimilating new information acquired in the future to improve habitat assessment.