Using a vegetation classification framework for rapid assessment measures of biodiversity: a case study from wetlands in the Southwest

Background/Question/Methods

The challenge in developing effective ecological assessment tools is in balancing ease of application versus the intensity required to generate meaningful data and outcomes.  This is perhaps most acute when considering plant biodiversity metrics such as species richness or exotic invasions, which can reflect on ecological integrity and function of an ecosystem.  Traditionally, the approach has been to develop simplified, non-taxon-specific measures for rapid assessments that have limited biodiversity information content, and then relegating the measures of actual biodiversity structure to intensive botanical surveys that are commonly beyond the reach or scope of a rapid assessment protocol, and thus typically not executed.  We propose that a vegetation classification framework can help bridge this gap between intensive surveys and efficient implementation by using community types or plant associations as representatives of the biodiversity quotient of a site.  We present a case study where a suite of mid-montane wetlands in the Southwest were field mapped and categorized by community type, and those community types in turn rated as part of an exotic species composition rapid assessment metric.  We compared this rapid metric to outcomes based on intensive plot-based botanical surveys at the same sites.

Results/Conclusions

Based on 32 sample sites along an anthropogenic-disturbance gradient, implementing a vegetation community type-based metric generated a range of assessment scores for exotic species composition that approximated a normal distribution.  The scores compared favorably to those derived from intensive botanical surveys but required significantly less botanical knowledge for implementation.  In the process, we developed a metric calculator that simplifies the process of data acquisition and processing, a key element of rapid assessments.  The approach can be used without a fully realized vegetation classification, but would be more efficient and have additional applications where assemblages are well understood and quantified.