Assessing Prairies With FQAs
Ecological measurement/monitoring of habitats is a huge topic covering many techniques, but a simple approach that all land owners/managers can perform is Floristic Quality Assessment — using tools right here on this web site!
When a prairie is plowed up, its loss is obvious. When a prairie is degraded by invasive exotics and loss of endemic species because of fragmentation or mismanagement, it is much harder to tell — so measurement techniques are required.
Professional botanists and ecologists make their livings performing detailed quantitative analyses of habitats using exhaustive survey techniques followed by sophisticated statistical analysis. Ideally, we would all perform such studies to assess our prairies, but very few of us have the requisite knowledge, skills, and time.
Fortunately, there is a very useful quick-and-dirty approach that produces meaningful information about a prairie simply by doing an inventory of what plants are there. This technique is called Floristic Quality Assessment (FQA) and we provide some cool tools on this web site to make it easy to do this.
Here we’re focusing on FQA concepts and issues in particular. You can read more practical tips about how to use the FQA tools here at our web site in this detailed FAQ. You can also read our general discussion about monitoring and measuring plant populations.
Floristic Quality Assessment was developed in the late 1970s by Swink and Wilhelm to assess natural areas around Chicago. The goal was to create a technique that would allow rapid, more-or-less quantitative characterization of lands without the expensive, time-consuming standard botanical measurement techniques.
The basic idea is quite intuitive: the “assemblage of species acts as a phytometer of habitat quality”. In simpler terms, you can tell how “good” a piece of land is by doing an inventory of what species of plants are present. The identity of the species present and the degree to which these species reflect nondegraded conditions tells you the quality of the habitat.
Here’s how this is done:
- Each species is assigned a subjective Coefficient of Conservatism (CoC) — a value on a 0-10 scale based on how indigenous, endemic, sensitive, unique, representative, or important the species is for the specific area under study. A CoC of 0 is “weediest/worst” and 10 is “most important/best” for a given locale. These CoCs are typically determined by a committee/consensus approach of expert botanists who understand the local ecology.
- Surveys are conducted by knowledgeable botanists who simply record every species that they find — both native and non-native (“adventive”).
- The resulting species list undergoes some simple arithmetic to produce a variety of calculated results.
The primary results include:
- Mean Coefficient of Conservatism (Cm) = the sum of all the species’ CoCs divided by the number of species)
- Floristic Quality Index (FQI) = the Mean Coefficient of Conservatism divided by the square root of the number of species
These values can be calculated for all discovered species and for natives only. In fact, there are a lot more ways to slice&dice the information if you have additional details about each species — as Craig Freeman and his colleagues at the Kansas Biological Survey have collected. Check out many parameters reported in one of our demo FQAs.
The FQI is the single number most people have relied upon, and here is how it has typically been interpreted:
- < 20 => definitely degraded
- 20-25 => possibly degraded; restoration potential
- 25-30 => quality natural area
- > 35 => really special natural area
However, more recently the FQI has come under some criticism. Basically the problem is that FQIs conflate two orthogonal factors: species richness and species importance. It is possible for two very different areas to have equivalent FQIs if one has high quality but lower diversity, while the other has lower quality but higher diversity. The single FQI measure doesn’t adequately report the distinction by itself.
There are additional potential sources of bias in doing FQAs:
- Size of sampled area — larger areas have higher FQIs because the number of identified species increases with area (an unavoidable sampling phenomenon)
- Number of surveys — more frequent surveys find more plants as they change through the seasons
- Timing of surveys — species richness varies moving through the seasons
- Botanical taxonomic competence of surveyors — especially their ability to ID plants in vegetative states (probably the most important limiting factor, certainly for us landowners)
- Specificity of identification (identifying to the species as opposed to lumping into genera)
- Comprehensiveness of plant lists (even knowledgeable botanists only find what they’re looking for)
- Different community types — wetlands vs prairies vs forests cannot be compared using these numeric techniques
All these issues can be dealt through proper knowledge, preparation, and execution. The statistical problem of FQIs conflating species richness and quality can be approached simply by not using FQIs but instead simply sticking with the mean absolute CoCs. Note that in our web tool, we report both the mean CoCs and the adjusted FQIs on our summary pages so distinctions and trends can be easily spotted.
Reasonably implemented, FQAs can be used to:
- Identify high-value natural areas
- Assist decisions regarding land acquisitions
- Guide restoration/reconstruction planning
- Set mitigation/restoration standards
- Perform serial, long-term monitoring
Since doing FQAs is as simple as recording what you see in your prairies (and then entering the data here via our web tools), there’s really no reason why land owners/managers of remnant prairies shouldn’t routinely track their lands!
Created: July 18, 2009 18:27
Last updated: May 26, 2019 17:03