Predicting occurrences of geographically restricted rare floral elements with qualitative habitat data

Abstract

Habitat-directed survey methods are often used for locating narrowly distributed rare species and communities across landscapes, though their predictive accuracy varies, depending on the element targeted and the type of data employed. We discuss habitat-directed surveys for rare floral elements in the context of landscape-level management planning, focusing in particular upon a case study from southern New Brunswick. Databases of rare species and community occurrences are important requisites for such planning, but existing information is usually deficient and expensive to develop. A habitat-based approach directs surveys to sites with a higher-than-random probability of hosting rare elements and avoids areas deemed unlikely to be of interest due to environment or disturbance factors. We describe a four-part survey procedure that uses readily available qualitative habitat descriptions and geographic information systems (GIS) based land resource data to identify sites potentially hosting rare biota. The procedure includes remote-sensed and on-site screening to confirm significance and collect ancillary data needed for conservation planning. The use of existing data is cost and time efficient, a necessity given often narrow planning windows and restricted budgets. The method described here is well suited to geographically restricted plant biota associated with distinct habitats, especially in unsurveyed or highly fragmented landscapes. However, the approach does not apply to species of wide-ranging and environmentally heterogeneous habitats. As well, by targeting only highly specific locations assumed to be "optimal" habitat, the occurrence of rare biota in other areas cannot be definitively determined and some sites will almost certainly be missed. The limitations of the procedure highlight the need for multifaceted biodiversity assessment over large areas.Key words: ecosystem management, rare species, gap analysis, habitat-directed biodiversity survey, reserve network, New Brunswick.