**2.2 Field sampling for the 2011 NWCA**

NWCA protocols for sampling each site were designed to be completed by a four-person field crew during a single day during peak growing season when most plants are in flower or fruit to optimize species identification and characterization of species abundance. This typically occurs between April and September depending on the status of the vegetation for sampling at the location of the site [10, 20]. The standard assessment area (AA) was a 0.5-ha circular plot with a 40-m radius, centered on the site location from the design (**Figure 2**). A buffer extended 100 m from the edge of the AA. If the wetland size and shape made the standard, circular

#### **Figure 2.**

*Diagram of a standard layout for a 0.5-ha assessment area and surrounding 100-m buffer (adapted from USEPA [10]). Locations of the coordinates for the site location generated by the survey design, of vegetation and buffer plots, and of soil pits are indicated.*

**157**

*Wetland Assessment: Beyond the Traditional Water Quality Perspective*

ated with physical, chemical, and biological aspects of each site.

AA unfeasible, alternate configurations of the AA and buffer were established using a rule-based system [10]. Sample plots were established in the AA and buffer according to standardized protocol to collect observational data and samples associ-

and on hydrologic alterations throughout the entire AA (**Figure 2**) [10, 21].

Physical aspects of the site were characterized by evidence of human activities in the AA and buffer. Using a standardized checklist of 52 predefined human activities, field crews collected observational data associated with anthropogenic distur-

Chemical aspects of the site were characterized using nutrient and heavy metal data associated with soil and surface water samples. To collect soil samples, field crews first excavated four soil pits (**Figure 2**), describing each soil horizon to a depth of 60 cm [10]. Crews chose the pit that best reflected the soils on the site based on the descriptions of the soil horizons and expanded it to 125 cm, collecting soil samples for each horizon. Soil samples were analyzed for heavy metals and phosphorus, among other analytes, by the US Department of Agriculture, Natural Resource Conservation Service, Kellogg Soil Survey Laboratory, Lincoln, Nebraska, using standard procedures [11, 22]. Surface water samples were collected as close to the center of the AA as possible at sites where adequate (≥15 cm deep) surface water was present in the AA and prior to conducting other sampling activities to avoid disturbance of the water and substrate, and before 1100 h to avoid diurnal changes in the chemistry [10]. The characteristics of the location from which the water sample was collected were recorded, including the stage of tide for tidal sites. Biological aspects of the site were characterized using vegetation data. Field crews recorded plant species identity and abundance data in five, systematically

plots (one in the center of the AA; 12 in the buffer),

vegetation plots within the AA (**Figure 2**) [10, 11, 23, 24]. A variety

of information describing attributes of vegetation structure was also collected

The value of the probability design used in the NWCA is that the wetland sites sampled represent the larger population of wetlands that meet the target definition. In other words, data that were collected at the 967 wetland sites sampled in 2011 can

Most kinds of data were collected at all wetland sites; however only a portion of the sites had surface water during the 2011 field visits, so water chemistry samples could be collected from just 537 sites of the 967 sampled sites. Factoring in the design weights from the sites with water samples, only 41%, or 10,408,004 ha of the 25,153,681 ha of total sampled population was represented by surface water chemistry. In addition, the 10,408,004 ha represented by water chemistry data do not represent the total sampled population. This is most evident in the proportion of wetland area with water chemistry data in each of the five ecoregions (**Figure 3a**). Surface water chemistry was most commonly sampled in the Tidal Saline (TSL) and Interior Plains (IPL) regions, and represented 72 and 62%, respectively, of the total sampled wetland area. Water chemistry data for the Coastal Plains (CPL), Eastern Mountains and Upper Midwest (EMU), and West (W) represented, respectively, 33, 34, and 47% of the estimated wetland area in each of these ecoregional subpopulations. The proportion of wetlands with surface water in each ecoregion is driven by climatic differences [25], and by characteristics of the landscape [26–29].

Characteristics of the landscape that drive wetland structure and function are embodied in the hydrogeomorphic (HGM) classification [30, 31]. HGM wetland

**3. Understanding what** *wetland water chemistry* **represents**

be inferred to 25,153,681 ha of wetland area across the conterminous US.

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

bance from thirteen 100-m2

placed, 100-m2

within each plot.

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

*Water Quality - Science, Assessments and Policy*

Olsen [19], and Olsen et al. [17].

**2.2 Field sampling for the 2011 NWCA**

As part of the design process, weights were assigned to each of the 1800 potential site locations that indicate the wetland area (i.e., the number of hectares) of the NWCA target population represented by the site (Olsen et al. [17]). After the 967 sites were visited, the weights were adjusted to account for the inability to sample sites, for example, due to denial of access, a site being inaccessible (i.e., safety issues), or a site failing to meet the target criteria (i.e., non-target). Finally, the adjusted weights were used to calculate the extent estimates of the wetland resource, expressed as hectares or percent of the wetland area, for different groupings (or subpopulations) of wetlands. The subpopulations presented in the 2011 NWCA final report (USEPA [8]) were ecoregion and wetland type. For a more detailed description of how this was done, see Diaz-Ramos et al. [18], Kincaid and

NWCA protocols for sampling each site were designed to be completed by a four-person field crew during a single day during peak growing season when most plants are in flower or fruit to optimize species identification and characterization of species abundance. This typically occurs between April and September depending on the status of the vegetation for sampling at the location of the site [10, 20]. The standard assessment area (AA) was a 0.5-ha circular plot with a 40-m radius, centered on the site location from the design (**Figure 2**). A buffer extended 100 m from the edge of the AA. If the wetland size and shape made the standard, circular

*Diagram of a standard layout for a 0.5-ha assessment area and surrounding 100-m buffer (adapted from USEPA [10]). Locations of the coordinates for the site location generated by the survey design, of vegetation and* 

**156**

**Figure 2.**

*buffer plots, and of soil pits are indicated.*

AA unfeasible, alternate configurations of the AA and buffer were established using a rule-based system [10]. Sample plots were established in the AA and buffer according to standardized protocol to collect observational data and samples associated with physical, chemical, and biological aspects of each site.

Physical aspects of the site were characterized by evidence of human activities in the AA and buffer. Using a standardized checklist of 52 predefined human activities, field crews collected observational data associated with anthropogenic disturbance from thirteen 100-m<sup>2</sup> plots (one in the center of the AA; 12 in the buffer), and on hydrologic alterations throughout the entire AA (**Figure 2**) [10, 21].

Chemical aspects of the site were characterized using nutrient and heavy metal data associated with soil and surface water samples. To collect soil samples, field crews first excavated four soil pits (**Figure 2**), describing each soil horizon to a depth of 60 cm [10]. Crews chose the pit that best reflected the soils on the site based on the descriptions of the soil horizons and expanded it to 125 cm, collecting soil samples for each horizon. Soil samples were analyzed for heavy metals and phosphorus, among other analytes, by the US Department of Agriculture, Natural Resource Conservation Service, Kellogg Soil Survey Laboratory, Lincoln, Nebraska, using standard procedures [11, 22]. Surface water samples were collected as close to the center of the AA as possible at sites where adequate (≥15 cm deep) surface water was present in the AA and prior to conducting other sampling activities to avoid disturbance of the water and substrate, and before 1100 h to avoid diurnal changes in the chemistry [10]. The characteristics of the location from which the water sample was collected were recorded, including the stage of tide for tidal sites.

Biological aspects of the site were characterized using vegetation data. Field crews recorded plant species identity and abundance data in five, systematically placed, 100-m2 vegetation plots within the AA (**Figure 2**) [10, 11, 23, 24]. A variety of information describing attributes of vegetation structure was also collected within each plot.

## **3. Understanding what** *wetland water chemistry* **represents**

The value of the probability design used in the NWCA is that the wetland sites sampled represent the larger population of wetlands that meet the target definition. In other words, data that were collected at the 967 wetland sites sampled in 2011 can be inferred to 25,153,681 ha of wetland area across the conterminous US.

Most kinds of data were collected at all wetland sites; however only a portion of the sites had surface water during the 2011 field visits, so water chemistry samples could be collected from just 537 sites of the 967 sampled sites. Factoring in the design weights from the sites with water samples, only 41%, or 10,408,004 ha of the 25,153,681 ha of total sampled population was represented by surface water chemistry. In addition, the 10,408,004 ha represented by water chemistry data do not represent the total sampled population. This is most evident in the proportion of wetland area with water chemistry data in each of the five ecoregions (**Figure 3a**). Surface water chemistry was most commonly sampled in the Tidal Saline (TSL) and Interior Plains (IPL) regions, and represented 72 and 62%, respectively, of the total sampled wetland area. Water chemistry data for the Coastal Plains (CPL), Eastern Mountains and Upper Midwest (EMU), and West (W) represented, respectively, 33, 34, and 47% of the estimated wetland area in each of these ecoregional subpopulations. The proportion of wetlands with surface water in each ecoregion is driven by climatic differences [25], and by characteristics of the landscape [26–29].

Characteristics of the landscape that drive wetland structure and function are embodied in the hydrogeomorphic (HGM) classification [30, 31]. HGM wetland

#### **Figure 3.**

*Proportional area of the 2011 National Wetland condition assessment (NWCA) sampled wetland population represented (solid wedges) and not represented (hatched wedges) by surface water chemistry data. The sampled wetland population is presented using three different wetland groupings: (a) Ecoregion (TSL = Tidal Saline, CPL = Coastal Plains, EMU = Eastern Mountains and Upper Midwest, IPL = Interior Plains, and W = West), (b) hydrogeomorphic (HGM) type, and (c) Cowardin Class (E2EM = Estuarine Intertidal Emergent, E2SS = Estuarine Intertidal Forested/Scrub Shrub, PUBPAB = Palustrine Unconsolidated Bottom/ Aquatic Bed, PEM = Palustrine Emergent, Pf = Palustrine Farmed, PSS = Palustrine Scrub Shrub, and PFO = Palustrine Forested). For HGM type, unknown represents wetland area that was unable to be classified by the field crews. Note that solid and hatched wedges within the same color together represent 100% of the sampled wetland area within the subpopulation.*

types are flats, slopes, depressions, riverine, fringe, and tidal [30–33]. These types are arranged along a hydrologic gradient from the least to the most surface water in **Figure 4**. Perhaps, unsurprisingly given that flats have the least surface water, water chemistry data only represented 20% of the total area of flats in the sampled population (**Figure 3b**). Conversely, tidal and fringe HGM types, which tend to have the most surface water throughout the year, had water chemistry data for 77 and 71% of their sampled wetland area, respectively. Slopes, depressions, and riverine wetlands encompass a wide range of varying hydrologic regimes; about half of the wetland area each of these HGM types were represented by water chemistry data (51, 44, and 52%, respectively).

While HGM classifies wetlands based on a hydrologic gradient, Cowardin wetland classes [4], used in the NWCA design, characterizes wetlands by the type of dominant vegetation. Again, the water chemistry does not equally represent the total sampled wetland area associated with each class. Wetland classes dominated by floating and rooted submerged vegetation (PUBPAB) and emergent herbaceous vegetation (E2EM, PEM) are better represented by the water chemistry data than are wetland classes dominated by forest (PFO) and shrub scrub (E2SS, PSS).

**159**

try data.

**Figure 4.**

*by the NWCA field crews.*

is problematic.

for wetlands across the nation.

*Wetland Assessment: Beyond the Traditional Water Quality Perspective*

**Figure 3c** shows that 94% of PUBPAB, 76% of E2EM, 66% of PEM wetland area was represented by surface water chemistry data, while only 30% of PFO, 33% of E2SS, and 34% of PSS wetland area were represented by surface water chemis-

*The gradient of hydrologic conditions associated with hydrogeomorphic (HGM) wetland types as characterized by their dominant water sources and water outputs. Photos exemplifying each HGM wetland type were taken* 

Our results from the NWCA show that using water chemistry to determine whether the wetland resource meets CWA criteria poses a number of issues. Wetland water chemistry data are biased relative to ecoregions, HGM wetland types, and Cowardin wetland classes [4]. This is because water chemistry data tend to capture wetlands that are permanently flooded, clearly under-representing precipitation- and groundwater-driven wetlands and wetland types that drawdown during the summer (i.e., when sites were sampled). Wetlands dominated by herbaceous vegetation were better, but far from completely, represented by the 2011 water chemistry data, compared to wetlands dominated by woody vegetation where only a third of the area was represented. Water chemistry is often seen as a fundamental component for monitoring and evaluating aquatic systems; however, in the case of the majority of wetlands (where the presence of surface water is highly variable) interpreting what water chemistry results represent and what they signify

**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

Fortunately, there are physical, chemical, and biological indicators of integrity

that can be measured consistently and are easily interpreted. Using a suite of

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

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

#### **Figure 4.**

*Water Quality - Science, Assessments and Policy*

types are flats, slopes, depressions, riverine, fringe, and tidal [30–33]. These types are arranged along a hydrologic gradient from the least to the most surface water in **Figure 4**. Perhaps, unsurprisingly given that flats have the least surface water, water chemistry data only represented 20% of the total area of flats in the sampled population (**Figure 3b**). Conversely, tidal and fringe HGM types, which tend to have the most surface water throughout the year, had water chemistry data for 77 and 71% of their sampled wetland area, respectively. Slopes, depressions, and riverine wetlands encompass a wide range of varying hydrologic regimes; about half of the wetland area each of these HGM types were represented by water chemistry data (51, 44,

*Proportional area of the 2011 National Wetland condition assessment (NWCA) sampled wetland population represented (solid wedges) and not represented (hatched wedges) by surface water chemistry data. The sampled wetland population is presented using three different wetland groupings: (a) Ecoregion (TSL = Tidal Saline, CPL = Coastal Plains, EMU = Eastern Mountains and Upper Midwest, IPL = Interior Plains, and W = West), (b) hydrogeomorphic (HGM) type, and (c) Cowardin Class (E2EM = Estuarine Intertidal Emergent, E2SS = Estuarine Intertidal Forested/Scrub Shrub, PUBPAB = Palustrine Unconsolidated Bottom/ Aquatic Bed, PEM = Palustrine Emergent, Pf = Palustrine Farmed, PSS = Palustrine Scrub Shrub, and PFO = Palustrine Forested). For HGM type, unknown represents wetland area that was unable to be classified by the field crews. Note that solid and hatched wedges within the same color together represent 100% of the* 

While HGM classifies wetlands based on a hydrologic gradient, Cowardin wetland classes [4], used in the NWCA design, characterizes wetlands by the type of dominant vegetation. Again, the water chemistry does not equally represent the total sampled wetland area associated with each class. Wetland classes dominated by floating and rooted submerged vegetation (PUBPAB) and emergent herbaceous vegetation (E2EM, PEM) are better represented by the water chemistry data than are wetland classes dominated by forest (PFO) and shrub scrub (E2SS, PSS).

**158**

**Figure 3.**

and 52%, respectively).

*sampled wetland area within the subpopulation.*

*The gradient of hydrologic conditions associated with hydrogeomorphic (HGM) wetland types as characterized by their dominant water sources and water outputs. Photos exemplifying each HGM wetland type were taken by the NWCA field crews.*

**Figure 3c** shows that 94% of PUBPAB, 76% of E2EM, 66% of PEM wetland area was represented by surface water chemistry data, while only 30% of PFO, 33% of E2SS, and 34% of PSS wetland area were represented by surface water chemistry data.

Our results from the NWCA show that using water chemistry to determine whether the wetland resource meets CWA criteria poses a number of issues. Wetland water chemistry data are biased relative to ecoregions, HGM wetland types, and Cowardin wetland classes [4]. This is because water chemistry data tend to capture wetlands that are permanently flooded, clearly under-representing precipitation- and groundwater-driven wetlands and wetland types that drawdown during the summer (i.e., when sites were sampled). Wetlands dominated by herbaceous vegetation were better, but far from completely, represented by the 2011 water chemistry data, compared to wetlands dominated by woody vegetation where only a third of the area was represented. Water chemistry is often seen as a fundamental component for monitoring and evaluating aquatic systems; however, in the case of the majority of wetlands (where the presence of surface water is highly variable) interpreting what water chemistry results represent and what they signify is problematic.
