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Floristic Quality Assessment
Floristic Quality Assessment (FQA) provides a standardized way to rapidly assess the condition of a vegetated area based on the plant species that are present. FQA works by assigning each plant species a value from 0 to 10. This value is called a Coefficient of Conservatism, or C Value. Values of 0 indicate species that are highly tolerant of human activities and have general environmental needs, while higher values represent higher fidelity to a specific habitat and low tolerance to anthropogenic disturbances. Generally, C values are assigned to either an entire inventory or selected plant species in a region, which may be an entire state (e.g., IN), biome (e.g., Interior Plateau), or specific location (e.g., Middle Rio Grande floodplain) by a group of expert regional botanists. As a result, there are numerous regional FQA databases of flora and their associated C Values covering various geographic areas.
FQA Databases
In 2022, published, accessible (e.g., Universal FQA Calculator or via Google search with key terms) regional FQA databases were reviewed by the U.S. Army Engineer Research and Development Center’s Environmental Laboratory for use during the planning phase of water resource projects. FQA databases that had clear documentation of their methodology of assigning and testing/validating their C Values were recommended for planning model certification. Then the U.S. Army Corps of Engineers’ Center of Ecosystem Restoration Expertise certified recommended regional FQA databases for USACE planning purposes. Certified regional FQA databases have been compiled and made available for rapid and consistent calculation of FQA metrics within this web application.
Note that some of the certified regional FQA databases have been altered slightly from their initial lists to reduce redundancies, indicate which species names are synonyms, or otherwise clarify the data. For a full description of data alterations, see Herman et al., 2023 (in review).
Common floristic quality metrics include Mean C (the mean of C Values for all species present in an inventory or along a transect) and the Floristic Quality Index (FQI, the Mean C multiplied by the square root of the total number of species).
Take a look at what regional FQA database might be applicable in your area:
Our Mission
The mission of the U.S. Army Corps of Engineers is to deliver vital public and military engineering services; partnering in peace and war to strengthen our nation’s security, energize the economy and reduce risks from disasters.
About This Application
This is an official public web application developed by the U.S. Army Engineer Research and Development Center (ERDC), the premier research and development facility of the U.S. Army Corps of Engineers.
This web application was created with funding from the Aquatic Nuisance Species Research Program (ANSRP) under the Next Generation Ecological Modeling Program (Next Gen). ANSRP was was established to address all invasive aquatic animals, as well as, harmful algae species that are problematic to the nation’s waterways, infrastructure, and associated resources. Next Gen is an overarching collaboration between ERDC and Texas State University to develop both future modeling efforts and comprehensive data sets. There are many individual projects funded through Next Gen, led by both ERDC and our university partners.
Last Updated: 2024-10-28
To report a mistake or unexpected issue on this webpage, contact - ecomodteam@usace.army.mil
Non Cover-Weighted Equations
In this set of equations, species \(i\) has been assigned a coefficient of conservatism \(C_{i}\) and a wetness coefficient \(W_{i}\).
Species Richness
The total number of unique species in the site assessment.
$$ N_{t} $$
Native Species Richness
The total number of unique native species in the site assessment.
$$ N_{n} $$
Mean Wetness
The mean wetness coefficient for all species in the site assessment. The wetness coefficient is based on Wetland Indicator Status ratings. Negative wetness coefficients indicate a stronger affinity for wetlands, while positive wetland coefficients indicate an affinity for upland.
$$ \overline{W_{t}} = \sum_{i=0}^{t} W_{i}\bigg/N_{t} $$
Native Mean Wetness
The mean wetness coefficient for native species in the site assessment.
$$ \overline{W_{n}} = \sum_{i=0}^{n} W_{i}\bigg/N_{n} $$
Mean C
The mean coefficient of conservatism of all species in the site assessment.
$$ \overline{C_{t}} = \sum_{i=0}^{t} C_{i} \bigg/ N_{t} $$
Native Mean C
The mean coefficient of conservatism of native species in the site assessment.
$$ \overline{C_{n}} = \sum_{i=0}^{n} C_{i}\bigg/N_{n} $$
FQI
Mean C multiplied by the square root of Species Richness.
$$ I_{t} = \overline{C_{t}} \sqrt{N_{t}} $$
Native FQI
Native Mean C multiplied by the square root of Native Species Richness.
$$ I_{n} = \overline{C_{n}} \sqrt{N_{n}} $$
Adjusted FQI
100 multiplied by the Native Mean C over 10, multiplied by the square root of Native Species Richness over Total Species Richness.
$$ I’ = 100\bigg(\frac{\overline{C_{n}}}{10}\bigg)\bigg(\frac{\sqrt{N_{n}}}{\sqrt{N_{t}}}\bigg) $$
Cover-Weighted Equations
In this set of equations, species \(i\) has been assigned a coefficient of conservatism \(C_{i}\). Species \(i\) also has a percent cover \(\gamma_i\).
Plot-Level Cover-Weighted Mean C
The sum of percent cover multiplied by the C value per each species, divided by the sum of cover values for all species.
$$ \overline{C_{t\gamma}} = \sum_{i=0}^{t} C_{i}\gamma_{i} \bigg/ \sum_{i=0}^{t}\gamma_{i} $$
Plot-Level Native Cover-Weighted Mean C
The sum of percent cover multiplied by the C value per each native species, divided by the sum of cover values for all native species.
$$ \overline{C_{n\gamma}} = \sum_{i=0}^{n} C_{i}\gamma_{i} \bigg/ \sum_{i=0}^{n}\gamma_{i} $$
Transect-Level Cover-Weighted Mean C
The sum of each species’ C value multiplied by the species’ mean cover and divided by the sum of each species’ mean cover.
$$ \overline{C_{t\gamma}} = \sum_{i=0}^{t} C_{i}\overline{\gamma_{i}} \bigg/ \sum_{i=0}^{t}\overline{\gamma_{i}} $$
Transect-Level Native Cover-Weighted Mean C
The sum of each native species’ C value multiplied by the species’ mean cover and divided by the sum of each native species’ mean cover.
$$ \overline{C_{n\gamma}} = \sum_{i=0}^{n} C_{i}\overline{\gamma_{i}} \bigg/ \sum_{i=0}^{n}\overline{\gamma_{i}} $$
Cover-Weighted FQI
Cover-Weighted Mean C multiplied by the square root of Species Richness.
$$ I_{t\gamma} = \overline{C_{t\gamma}}\sqrt{N_{t}} $$
Native Cover-Weighted FQI
Cover-Weighted Native Mean C multiplied by the square root of Native Species Richness.
$$ I_{n\gamma} = \overline{C_{n\gamma}}\sqrt{N_{n}} $$
Relative Frequency
The frequency of a species, family, or physiognomic group multiplied by 100 and then multiplied by the frequency of all species, families, or physiognomic groups.
$$ \mu_{r} = \bigg(\mu_{i}\bigg/\sum_{i =0}^{t}\mu_{i}\bigg) $$
Relative Coverage
The total cover per group of interest (species, taxonomic family, or physiognomic group) multiplied by 100 and divided by the total cover for all observations.
$$ \mu_{r} = \bigg(\gamma_{i}\bigg/\sum_{i =0}^{t}\gamma_{i}\bigg) $$
Relative Importance
Relative Frequency added to Relative Coverage, over two.
$$ RIV = \bigg(\mu_{r} + \gamma_{r}\bigg)\bigg/2 $$
Braun-Blanquet
Braun-Blanquet, Josias. “Plant sociology. The study of plant communities.” Plant sociology. The study of plant communities. First ed. (1932).
| Braun-Blanquet Classes | % Cover Range | Midpoint |
|---|---|---|
| + | <1% | 0.1 |
| 1 | <5% | 2.5 |
| 2 | 5-25% | 15 |
| 3 | 25-50% | 37.5 |
| 4 | 50-75% | 62.5 |
| 4 | 75-100% | 87.5 |
Carolina Veg Survey
Lee, Michael T., Robert K. Peet, Steven D. Roberts, and Thomas R. Wentworth. “CVS-EEP protocol for recording vegetation.” Carolina Vegetation Survey. Retrieved August 17 (2006): 2008.
| Carolina Veg Survey Classes | % Cover Range | Midpoint |
|---|---|---|
| 1 | <0.1 | 0.1 |
| 2 | 0-1% | 0.5 |
| 3 | 1-2% | 1.5 |
| 4 | 2-5% | 3.5 |
| 5 | 5-10% | 7.5 |
| 6 | 10-25% | 17.5 |
| 7 | 25-50% | 37.5 |
| 8 | 50-75% | 62.5 |
| 9 | 75-95% | 85 |
| 10 | 95-100% | 97.5 |
Daubenmire Classes
R. F. Daubenmire. “A canopy-cover method of vegetational analysis”. Northwest Science 33:43–46. (1959)
| Daubenmire Classes | % Cover Range | Midpoint |
|---|---|---|
| 1 | 0-5% | 2.5 |
| 2 | 5-25% | 15 |
| 3 | 25-50% | 37.5 |
| 4 | 50-75% | 62.5 |
| 5 | 75-95% | 85 |
| 6 | 95-100% | 97.5 |
USFS Ecodata Classes
Barber, Jim, and Dave Vanderzanden. “The Region 1 existing vegetation map products (VMap) release 9.1.” USDA Forest Service, Region 1 (2009): 200.
| USFS Ecodata Classes | % Cover Range | Midpoint |
|---|---|---|
| 1 | <1% | 0.5 |
| 3 | 1.1-5% | 3 |
| 10 | 5.1-15% | 10 |
| 20 | 15.1-25% | 20 |
| 30 | 25.1-35% | 30 |
| 40 | 35.1-45% | 40 |
| 50 | 45.1-55% | 50 |
| 60 | 55.1-65% | 60 |
| 70 | 65.1-75% | 70 |
| 80 | 75.1-85% | 80 |
| 90 | 85.1-95% | 90 |
| 98 | 95.1-100% | 98 |
Academic Publications
Bauer, Jonathan T, Liz Koziol, and James D Bever. “Ecology of Floristic Quality Assessment: Testing for Correlations between Coefficients of Conservatism, Species Traits and Mycorrhizal Responsiveness.” AoB PLANTS 10, no. 1 (February 1, 2018). https://doi.org/10.1093/aobpla/plx073.
DeBerry, Douglas A., and James E. Perry. “Using the Floristic Quality Concept to Assess Created and Natural Wetlands: Ecological and Management Implications.” Ecological Indicators 53 (June 2015): 247–57. https://doi.org/10.1016/j.ecolind.2015.02.003.
Freyman, William A., Linda A. Masters, and Stephen Packard. “The Universal Floristic Quality Assessment ( FQA ) Calculator: An Online Tool for Ecological Assessment and Monitoring.” Edited by Timothée Poisot. Methods in Ecology and Evolution 7, no. 3 (March 2016): 380–83. https://doi.org/10.1111/2041-210X.12491.
Matthews, Jeffrey W., Greg Spyreas, and Colleen M. Long. “A Null Model Test of Floristic Quality Assessment: Are Plant Species’ Coefficients of Conservatism Valid?” Ecological Indicators 52 (May 2015): 1–7. https://doi.org/10.1016/j.ecolind.2014.11.017.
Spyreas, Greg. “Floristic Quality Assessment: A Critique, a Defense, and a Primer.” Ecosphere 10, no. 8 (August 2019): e02825. https://doi.org/10.1002/ecs2.2825.
Spyreas, Greg, Scott J. Meiners, Jeffrey W. Matthews, and Brenda Molano-Flores. “Successional Trends in Floristic Quality: Successional Trends in Floristic Quality.” Journal of Applied Ecology 49, no. 2 (April 2012): 339–48. https://doi.org/10.1111/j.1365-2664.2011.02100.x.
Swink, Floyd, and Gerould Wilhelm. Plants of the Chicago Region: A Checklist of the Vascular Flora of the Chicago Region, with Keys, Notes on Local Distribution, Ecology, and Taxonomy, a System for the Qualitative Evaluation of Plant Communities, a Natural Divisions Map, and a Description of Natural Plant Communities. 4th ed. Indianapolis: Indiana Academy of Science, 1994.
Zinnen, Jack, Greg Spyreas, David N. Zaya, and Jeffrey W. Matthews. “Niche Ecology in Floristic Quality Assessment: Are Species with Higher Conservatism More Specialized?” Ecological Indicators 121 (February 2021): 107078. https://doi.org/10.1016/j.ecolind.2020.107078.
