**4. Measuring** *wetland resource quality* **through the 2011 NWCA**

Surface water chemistry as an indicator of chemical integrity is limited to wetland types that have permanent or recurrent surface water or require continuous monitoring throughout the year to capture wetland types that have ephemeral or infrequent surface water. Collecting surface water samples from some wetland types that rarely have surface water, like flats and slopes (**Figure 4**), may be unfeasible. Water chemistry is not a consistently available, readily interpretable, indicator for wetlands across the nation.

Fortunately, there are physical, chemical, and biological indicators of integrity that can be measured consistently and are easily interpreted. Using a suite of

physical, chemical, and biological indicators to describe condition also directly addresses the recommendations in the CWA. The 2011 NWCA illustrates how physical, chemical, and biological indicators were employed as the basis for assessing condition.

### **4.1 Use of condition to report on the state of** *wetland resource quality*

Condition of an ecosystem can be expressed in different ways—ecological, or by individual components (biological, chemical, physical). Biological condition of the wetland resource at national and regional scales in the 2011 NWCA was used to report on the state of *wetland resource quality*. To evaluate the biological condition of wetlands, a multimetric index was developed based on plant species and trait data collected as part of the NWCA [12, 23]. Although the Vegetation Multimetric Index (VMMI) is biological in nature, it is calibrated using physical, chemical, and biological data that reflect the level of anthropogenic disturbance at a site.

Physical, chemical, and biological data resulting from information collected in the field were used to construct 10 measures of anthropogenic disturbance [10, 34]. Eight indices utilized observational data to describe physical disturbance [21]; one index used concentrations of heavy metals in the wetland soils to describe chemical disturbance [22]; and one metric for relative cover of alien plant species was used to describe biological disturbance. For each of the 10 measures, thresholds were established to reflect the degree of human impact to the site. A screening approach was used to categorize sites as least disturbed, moderately disturbed, or most disturbed based on the frequency at which thresholds were exceeded [12, 34]. Least disturbed sites, which represented the best attainable conditions given the state of the landscape [35], were used as a measure of physical, chemical, and biological reference condition in developing the VMMI.

Development of the VMMI is described in detail in Magee et al. [23] and began with calculation of 405 candidate metrics describing different vegetation properties with probable relationships to biological condition. The potential efficacy of each metric in reflecting biological condition was evaluated using a variety of objective screening tests with cut-offs appropriate to wetland data including: (1) sufficient range in values to allow detection of signals in response to disturbance; (2) repeatability, quantified using a signal to noise ratio (S:N) based on repeat sampling of a subset of sites (see Magee et al. [23] for a discussion of S:N); and (3) responsiveness, that is, how well a metric distinguished least disturbed from most disturbed wetland sites sampled in the NWCA. Candidate metrics that passed the screening criteria were examined for utility as components of potential VMMIs. Many thousands of potential VMMIs combining from 4 to 10 individual metrics were calculated and evaluated using approaches similar to Van Sickle [36] and Stoddard et al. [37], but adapted for wetlands, to identify the VMMIs with the best performance and with limited redundancy (correlation) among metrics included in a particular VMMI [23]. The final national-scale VMMI for the 2011 NWCA was based on the combination of four metrics, all broadly applicable across major classes of wetlands (**Table 1**). The VMMI is scaled from 0 to 100, with higher values representing better biological condition. To translate the continuous VMMI scores to condition categories, thresholds for delineating "good," "fair," and "poor" condition were determined based on the distribution of VMMI values in least-disturbed sites [23] using the percentile approach described in Paulsen et al. [38].

Biological condition of wetlands, reported as "good," "fair," and "poor" by the 2011 NWCA, reflects the state of the *wetland resource quality* as measured at all 967 sampled wetland probability sites, representing 25,153,681 ha of wetlands across

**161**

*Wetland Assessment: Beyond the Traditional Water Quality Perspective*

**Metric name Metric description Calculation**

Based on all species observed

taxa at each site

Combines relative cover and relative frequency for native

Tolerance to disturbance defined as coefficient of conservatism (C-value) ≤ 4

Relative cover of native monocot species at each site

the conterminous US. Specifically, results from the survey showed that 48% of the target sampled wetland area in the nation was in good condition, 20% was in fair

*The four metrics, and equations for their calculation at each sampled site, that were included in the 2011 National Wetland Condition Assessment (NWCA) vegetation multimetric index (VMMI) as described in* 

**FQAI =Σ CC***ij***/√N***j*

unique species *i* at site *j* N = number of species at site *j*

where for each unique species *i*: absolute cover = 0–100%,

plots in which it occurred

**a site**

where CC*ij* = coefficient of conservatism for each

**((Σ Absolute Cover native species***i***/Σ Absolute Cover all species***i***) × 100 + (Σ Frequency native species***i***/Σ Frequency all species***i***) × 100)/2**

frequency = 0–100% calculated as the percent of

**Number of taxa with C-value ≤ 4 occurring at** 

**(Σ Absolute Cover native monocot species***i***/Σ**

**Absolute Cover all species***i***) × 100**

While condition describes the state of *wetland resource quality*, it is equally important to understand factors that negatively affect *wetland resource quality* in making policy and resource management decisions. This requires an evaluation using physical, chemical, and biological stressor data [3]. The concepts of relative extent and relative risk were used to report the magnitude of six physical indicators of stress [21], two chemical indicators of stress [22], and one biological indicator of stress across wetlands of the US [24] to evaluate the impact of the chemical and

Using observational data collected in the buffer and in the assessment area (AA), an Anthropogenic Stress Index (ASI) was developed for six physical stressor categories: vegetation removal, vegetation replacement, damming, ditching, hardening, and filling/erosion (**Table 2**). Thresholds that indicate the degree of physical stress associated with each physical stressor were established [12, 21]. Each site was assigned to either low, moderate, or high stressor levels for each of the six stressor

Soil chemistry data were examined to identify chemical indicators of stress. Ultimately, only heavy metals and total phosphorus concentrations were used in the NWCA analysis (**Table 2**). Twelve heavy metals, each (1) with high signal-tonoise ratios [40], (2) a close relation to anthropogenic impacts, and (3) occurring in consistently measurable quantities, were used to develop a Heavy Metals Index (HMI) [12, 22]. The metals were: silver, cadmium, cobalt, chromium, copper, nickel, lead, antimony, tin, vanadium, tungsten, and zinc. The HMI is the sum of the number of metals present in the uppermost layer of the soil with concentrations above expected natural background levels. Background levels were based on published values primarily from Alloway [41] and used directly or slightly modified.

condition, and 32% was in poor condition (**Figure 5**) [8].

**4.2 Evaluation of** *wetland resource quality* **using indicators of stress**

physical stressors on the state of the *wetland resource quality* [39].

categories based on its ASI score.

*DOI: http://dx.doi.org/10.5772/intechopen.92583*

Floristic Quality Assessment Index (FQAI)

Relative importance of native species

Richness of disturbancetolerant species

**Table 1.**

*Magee et al. [23].*

Relative cover of native monocots

*Wetland Assessment: Beyond the Traditional Water Quality Perspective DOI: http://dx.doi.org/10.5772/intechopen.92583*


#### **Table 1.**

*Water Quality - Science, Assessments and Policy*

reference condition in developing the VMMI.

ing condition.

physical, chemical, and biological indicators to describe condition also directly addresses the recommendations in the CWA. The 2011 NWCA illustrates how physical, chemical, and biological indicators were employed as the basis for assess-

Condition of an ecosystem can be expressed in different ways—ecological, or by individual components (biological, chemical, physical). Biological condition of the wetland resource at national and regional scales in the 2011 NWCA was used to report on the state of *wetland resource quality*. To evaluate the biological condition of wetlands, a multimetric index was developed based on plant species and trait data collected as part of the NWCA [12, 23]. Although the Vegetation Multimetric Index (VMMI) is biological in nature, it is calibrated using physical, chemical, and

Physical, chemical, and biological data resulting from information collected in the field were used to construct 10 measures of anthropogenic disturbance [10, 34]. Eight indices utilized observational data to describe physical disturbance [21]; one index used concentrations of heavy metals in the wetland soils to describe chemical disturbance [22]; and one metric for relative cover of alien plant species was used to describe biological disturbance. For each of the 10 measures, thresholds were established to reflect the degree of human impact to the site. A screening approach was used to categorize sites as least disturbed, moderately disturbed, or most disturbed based on the frequency at which thresholds were exceeded [12, 34]. Least disturbed sites, which represented the best attainable conditions given the state of the landscape [35], were used as a measure of physical, chemical, and biological

Development of the VMMI is described in detail in Magee et al. [23] and began with calculation of 405 candidate metrics describing different vegetation properties with probable relationships to biological condition. The potential efficacy of each metric in reflecting biological condition was evaluated using a variety of objective screening tests with cut-offs appropriate to wetland data including: (1) sufficient range in values to allow detection of signals in response to disturbance; (2) repeatability, quantified using a signal to noise ratio (S:N) based on repeat sampling of a subset of sites (see Magee et al. [23] for a discussion of S:N); and (3) responsiveness, that is, how well a metric distinguished least disturbed from most disturbed wetland sites sampled in the NWCA. Candidate metrics that passed the screening criteria were examined for utility as components of potential VMMIs. Many thousands of potential VMMIs combining from 4 to 10 individual metrics were calculated and evaluated using approaches similar to Van Sickle [36] and Stoddard et al. [37], but adapted for wetlands, to identify the VMMIs with the best performance and with limited redundancy (correlation) among metrics included in a particular VMMI [23]. The final national-scale VMMI for the 2011 NWCA was based on the combination of four metrics, all broadly applicable across major classes of wetlands (**Table 1**). The VMMI is scaled from 0 to 100, with higher values representing better biological condition. To translate the continuous VMMI scores to condition categories, thresholds for delineating "good," "fair," and "poor" condition were determined based on the distribution of VMMI values in least-disturbed

sites [23] using the percentile approach described in Paulsen et al. [38].

Biological condition of wetlands, reported as "good," "fair," and "poor" by the 2011 NWCA, reflects the state of the *wetland resource quality* as measured at all 967 sampled wetland probability sites, representing 25,153,681 ha of wetlands across

**4.1 Use of condition to report on the state of** *wetland resource quality*

biological data that reflect the level of anthropogenic disturbance at a site.

**160**

*The four metrics, and equations for their calculation at each sampled site, that were included in the 2011 National Wetland Condition Assessment (NWCA) vegetation multimetric index (VMMI) as described in Magee et al. [23].*

the conterminous US. Specifically, results from the survey showed that 48% of the target sampled wetland area in the nation was in good condition, 20% was in fair condition, and 32% was in poor condition (**Figure 5**) [8].

## **4.2 Evaluation of** *wetland resource quality* **using indicators of stress**

While condition describes the state of *wetland resource quality*, it is equally important to understand factors that negatively affect *wetland resource quality* in making policy and resource management decisions. This requires an evaluation using physical, chemical, and biological stressor data [3]. The concepts of relative extent and relative risk were used to report the magnitude of six physical indicators of stress [21], two chemical indicators of stress [22], and one biological indicator of stress across wetlands of the US [24] to evaluate the impact of the chemical and physical stressors on the state of the *wetland resource quality* [39].

Using observational data collected in the buffer and in the assessment area (AA), an Anthropogenic Stress Index (ASI) was developed for six physical stressor categories: vegetation removal, vegetation replacement, damming, ditching, hardening, and filling/erosion (**Table 2**). Thresholds that indicate the degree of physical stress associated with each physical stressor were established [12, 21]. Each site was assigned to either low, moderate, or high stressor levels for each of the six stressor categories based on its ASI score.

Soil chemistry data were examined to identify chemical indicators of stress. Ultimately, only heavy metals and total phosphorus concentrations were used in the NWCA analysis (**Table 2**). Twelve heavy metals, each (1) with high signal-tonoise ratios [40], (2) a close relation to anthropogenic impacts, and (3) occurring in consistently measurable quantities, were used to develop a Heavy Metals Index (HMI) [12, 22]. The metals were: silver, cadmium, cobalt, chromium, copper, nickel, lead, antimony, tin, vanadium, tungsten, and zinc. The HMI is the sum of the number of metals present in the uppermost layer of the soil with concentrations above expected natural background levels. Background levels were based on published values primarily from Alloway [41] and used directly or slightly modified.

#### **Figure 5.**

*State of the* wetland resource quality *as indicated by the vegetation multimetric index (VMMI) for the 2011 National Wetland Condition Assessment (NWCA). Condition classes are reported as the percent area of the sampled wetland population. Error bars are 95% confidence intervals (figure adapted from USEPA [8]).*

Because no published thresholds for anthropogenic impacts to wetlands were available, thresholds for chemical stressor levels were set based on the background concentrations from Alloway [12, 22, 41]. The threshold for the low HMI stressor level required that all metals were less than or equal to background concentrations, and the threshold for the high HMI stressor levels was ≥3 metals above background. All values falling between the high and low stressor levels were termed moderate. In the case of phosphorus, concentration of total phosphorus in the uppermost layer with soil chemistry was used as a chemical indicator of stress. The thresholds for low and high phosphorus stressor levels were set using the 75th and 95th percentiles observed in least-disturbed sites [42, 43].

The Nonnative Plant Indicator (NNPI) was developed as a biological indicator of stress [12, 24]. Nonnative plants are widely recognized as (1) indicators of stress (e.g., their presence is often associated with human-mediated disturbances that negatively affect biological condition), or as (2) direct stressors to the condition of wetlands and other ecosystems (e.g., by inducing structural changes in vegetation, competing with native plant species, altering species interactions, community composition, or ecosystem properties); see Magee et al. [24] and citations therein. The NNPI is a categorical indicator based on three metrics describing different pathways of potential effects from the collective set of nonnative taxa occurring at each site (**Table 2**). The three NNPI metrics (nonnative relative cover, nonnative richness, and nonnative relative frequency) were used together in a decision matrix to assign each sampled site to a stressor-level category (low, moderate, or high) based on exceedance values for each metric [12, 24]. Note, that the high stressor-level category presented here combines the high and very-high stressor levels defined in Magee et al. [24].

Relative extent describes the frequency at which indicators of stress occur in wetlands and can be used to identify the most common indicators of stress occurring at high levels likely affecting wetland resource quality. Using the low, moderate, and high stressor-level thresholds for each of the indicators of stress, the wetland area associated with each stressor level and indicator was determined using the weights from the sampled sites [39]. Relative extent is reported as the proportion of wetland area sampled with high stressor levels for each of the indicators of stress (**Figure 6**). The most frequently encountered indicators of stress at high stressor levels were associated with physical indicators and include vegetation removal, hardening, and ditching, at 27, 27, and 23% of the sampled wetland area, respectively. The NNPI had 19% area associated with the high stressor level, while the chemical indicators, soil phosphorus, and heavy metals, had 6 and 2% of the sampled wetland area associated with the high stressor level.

Relative risk can be used to evaluate the proportional effect of factors that have an impact on wetland resource quality and is defined as the probability of having

**163**

**Table 2.**

*USEPA [12]).*

*Wetland Assessment: Beyond the Traditional Water Quality Perspective*

Any field observation related to loss, removal, or damage of wetland

Any field observation of altered vegetation within the site due to anthropogenic activities

related to impounding or impeding water flow from or within the site

related to draining water

related to soil compaction, including activities and infrastructure that primarily result in soil

related to soil erosion or

Heavy metals with concentrations above background concentrations in soil

Soil phosphorus concentrations relative to

reference sites

A categorical indicator based on three metrics that describe different avenues of potential impact to biological condition

vegetation

**Indicators Description Observations/measurements included**

*Gravel pit, oil drilling, gas wells, underground mine, forest clear cut, forest selective cut, tree canopy herbivory, shrub layer browsed, highly grazed grasses, recently burned forest, recently burned grassland, herbicide use,* 

*Golf course, lawn/park, row crops in small amounts in the Assessment Area, row crops in the buffer, fallow field,* 

*Dike/dam/road/RR bed, water level control structure, wall/riprap, dikes, berms, dams, railroad beds, sewer* 

*Ditches, channelization, inlets/outlets, point source/pipe, irrigation, water supply, field tiling, standpipe outflow, corrugated pipe, box culvert, outflowing ditches*

*Gravel road, two-lane road, four-lane road, parking lot/pavement, trails, soil compaction, off road vehicle damage, confined animal feeding, dairy, suburban residential, urban/multifamily, rural residential, impervious surface input, animal trampling, vehicle* 

*Excavation/dredging, fill/spoil banks, freshly deposited sediment, soil loss/root exposure, soil erosion, irrigation, landfill, dumping, surface mine, recent sedimentation,* 

*Antimony, cadmium, chromium, cobalt, copper, lead, nickel, silver, tin, tungsten, vanadium, zinc concentrations from the uppermost layer with soil* 

*Phosphorus concentration from the uppermost layer within 10 cm of the soil surface with soil chemistry*

*Relative cover of nonnative species, richness of nonnative species, relative frequency of nonnative species*

*mowing/shrub cutting, pasture/hay, range*

*nursery, orchard, tree plantation*

*ruts, roads, concrete, asphalt*

*excavation/dredging*

*chemistry*

*outfalls*

poor condition when stressor levels are high relative to when stressor levels are low [12, 39, 44–46]. Relative risk was calculated for the six physical and two chemical indicators of stress. Because condition of wetlands is based on vegetation data (i.e., the VMMI) and the biological indicator of stress (i.e., the NNPI) also uses the vegetation data, relative risk is not reported for the NNPI (see [12] for details). **Figure 6** shows the relative risk for the physical and chemical stressors. The likelihood of poor condition (compared to good condition) was 1.8 times higher when

*Description and components of the biological, physical, and chemical indicators of stress (adapted from* 

*DOI: http://dx.doi.org/10.5772/intechopen.92583*

Damming Any field observation

Ditching Any field observation

Hardening Any field observation

Filling/erosion Any field observation

**Chemical indicators** Heavy Metal Index

Soil phosphorus concentration

**Biological indicator** Nonnative Plant Indicator (NNPI)

hardening

deposition

samples

**Physical indicators**

Vegetation removal

Vegetation replacement


*Wetland Assessment: Beyond the Traditional Water Quality Perspective DOI: http://dx.doi.org/10.5772/intechopen.92583*

#### **Table 2.**

*Water Quality - Science, Assessments and Policy*

**Figure 5.**

observed in least-disturbed sites [42, 43].

Because no published thresholds for anthropogenic impacts to wetlands were available, thresholds for chemical stressor levels were set based on the background concentrations from Alloway [12, 22, 41]. The threshold for the low HMI stressor level required that all metals were less than or equal to background concentrations, and the threshold for the high HMI stressor levels was ≥3 metals above background. All values falling between the high and low stressor levels were termed moderate. In the case of phosphorus, concentration of total phosphorus in the uppermost layer with soil chemistry was used as a chemical indicator of stress. The thresholds for low and high phosphorus stressor levels were set using the 75th and 95th percentiles

*State of the* wetland resource quality *as indicated by the vegetation multimetric index (VMMI) for the 2011 National Wetland Condition Assessment (NWCA). Condition classes are reported as the percent area of the sampled wetland population. Error bars are 95% confidence intervals (figure adapted from USEPA [8]).*

The Nonnative Plant Indicator (NNPI) was developed as a biological indicator of stress [12, 24]. Nonnative plants are widely recognized as (1) indicators of stress (e.g., their presence is often associated with human-mediated disturbances that negatively affect biological condition), or as (2) direct stressors to the condition of wetlands and other ecosystems (e.g., by inducing structural changes in vegetation, competing with native plant species, altering species interactions, community composition, or ecosystem properties); see Magee et al. [24] and citations therein. The NNPI is a categorical indicator based on three metrics describing different pathways of potential effects from the collective set of nonnative taxa occurring at each site (**Table 2**). The three NNPI metrics (nonnative relative cover, nonnative richness, and nonnative relative frequency) were used together in a decision matrix to assign each sampled site to a stressor-level category (low, moderate, or high) based on exceedance values for each metric [12, 24]. Note, that the high stressor-level category presented here combines

the high and very-high stressor levels defined in Magee et al. [24].

sampled wetland area associated with the high stressor level.

Relative extent describes the frequency at which indicators of stress occur in wetlands and can be used to identify the most common indicators of stress occurring at high levels likely affecting wetland resource quality. Using the low, moderate, and high stressor-level thresholds for each of the indicators of stress, the wetland area associated with each stressor level and indicator was determined using the weights from the sampled sites [39]. Relative extent is reported as the proportion of wetland area sampled with high stressor levels for each of the indicators of stress (**Figure 6**). The most frequently encountered indicators of stress at high stressor levels were associated with physical indicators and include vegetation removal, hardening, and ditching, at 27, 27, and 23% of the sampled wetland area, respectively. The NNPI had 19% area associated with the high stressor level, while the chemical indicators, soil phosphorus, and heavy metals, had 6 and 2% of the

Relative risk can be used to evaluate the proportional effect of factors that have an impact on wetland resource quality and is defined as the probability of having

**162**

*Description and components of the biological, physical, and chemical indicators of stress (adapted from USEPA [12]).*

poor condition when stressor levels are high relative to when stressor levels are low [12, 39, 44–46]. Relative risk was calculated for the six physical and two chemical indicators of stress. Because condition of wetlands is based on vegetation data (i.e., the VMMI) and the biological indicator of stress (i.e., the NNPI) also uses the vegetation data, relative risk is not reported for the NNPI (see [12] for details). **Figure 6** shows the relative risk for the physical and chemical stressors. The likelihood of poor condition (compared to good condition) was 1.8 times higher when

#### **Figure 6.**

*Evaluation of the factors that affect wetland resource quality as indicated by relative extent (percent area of the wetland resource) and relative risk from chemical, physical, and biological indicators of stress for the 2011 National Wetland Condition Assessment (NWCA). NA indicates "not applicable" for relative risk of the nonnative plan indicator to avoid circularity (see text for details). Error bars are 95% confidence intervals (figure adapted from USEPA [8]).*

vegetation removal and hardening are present at high stressor levels and 1.6 times higher when vegetation replacement, damming, ditching, and filling/erosion are present at high stressor levels. A relative risk of 1.0 indicates that there is no association or relationship between the indicator of stress and condition, and a relative risk less than 1.0, indicates a positive relationship between high stressor level of the indicator and good condition.
