Using a vegetation index to assess wetland condition in the Prairie Pothole Region of North America.

Wetlands deliver a suite of ecosystem services to society. Anthropogenic activities, such as wetland drainage, have resulted in considerable wetland loss and degradation, diminishing the intrinsic value of wetland ecosystems worldwide. Protecting remaining wetlands and restoring degraded wetlands are common management practices to preserve and reclaim wetland benefits to society. Accordingly, methods for monitoring and assessing wetlands are required to evaluate their ecologic condition and outcomes of restoration activities. We used an established methodology for conducting vegetation-based assessments and describe a case study consisting of a wetland condition assessment in the Prairie Pothole Region of the North American Great Plains. We provide an overview of an existing method for selecting wetlands to sample across broad geographic distributions using a spatially balanced statistical design. We also describe site assessment protocols, including vegetation survey methods, and how field data were applied to a vegetation index that categorized wetlands according to ecologic condition. Results of the case study indicated that vegetation communities in nearly 50% of the surveyed wetlands were in very poor or poor condition, while only about 25% were considered good or very good. Approximately 70% of wetlands in native grasslands were categorized as good or very good compared to only 12% of those in reseeded grasslands (formerly cropland). In terms of informing restoration and management activities, results indicated that improved restoration practices could include a greater focus on establishing natural vegetation communities, and both restored and native prairie wetlands would benefit from enhanced management of invasive species.

δ15N of Chironomidae: An index of nitrogen sources and processing within watersheds for national aquatic monitoring programs.

Nitrogen (N) removal along flowpaths to aquatic ecosystems is an important regulating ecosystem service that can help reduce N pollution in the nation's waterways, but can be challenging to measure at large spatial scales. Measurements that integrate N processing within watersheds would be particularly useful for assessing the magnitude of this vital service. Because most N removal processes cause isotopic fractionation, δ15N from basal food-chain organisms in aquatic ecosystems can provide information on both N sources and the degree of watershed N processing. As part of EPA's National Aquatic Resource Surveys (NARS), we measured δ15N of Chironomidae collected from over 2000 lakes, rivers and streams across the continental USA. Using information on N inputs to watersheds and summer total N concentrations ([TN]) in the water column, we assessed where elevated chironomid δ15N would indicate N removal rather than possible enriched sources of N. Chironomid δ15N values ranged from -4 to +20‰, and were higher in rivers and streams than in lakes, indicating that N in rivers and streams underwent more processing and cycling that preferentially removes 14N than N in lakes. Chironomid δ15N increased with watershed size, N inputs, and water chemical components, and decreased as precipitation increased. In rivers and streams with high watershed N inputs, we found lower [TN] in streams with higher chironomid δ15N values, suggesting high rates of gaseous N loss such as denitrification. At low watershed N inputs, the pattern reversed; streams with elevated chironomid δ15N had higher [TN] than streams with lower chironomid δ15N, possibly indicating unknown sources elevated in δ15N such as legacy N, or waste from animals or humans. Chironomid δ15N values can be a valuable tool to assess integrated watershed-level N sources, input rates, and processing for water quality monitoring and assessment at large scales.

Improved wetland soil organic carbon stocks of the conterminous U.S. through data harmonization.

Wetland soil stocks are important global repositories of carbon (C) but are difficult to quantify and model due to varying sampling protocols, and geomorphic/spatio-temporal discontinuity. Merging scales of soil-survey spatial extents with wetland-specific point-based data offers an explicit, empirical and updatable improvement for regional and continental scale soil C stock assessments. Agency-collected and community-contributed soil datasets were compared for representativeness and bias, with the goal of producing a harmonized national map of wetland soil C stocks with error quantification for wetland areas of the conterminous United States (CONUS) identified by the USGS National Landcover Change Dataset. This allowed an empirical predictive model of SOC density to be applied across the entire CONUS using relational %OC distribution alone. A broken-stick quantile-regression model identified %OC with its relatively high analytical confidence as a key predictor of SOC density in soil segments; soils less than 6% OC (hereafter, mineral wetland soils, 85% of the dataset) had a strong linear relationship of %OC to SOC density (RMSE = 0.0059, ~4% mean RMSE) and soils greater than 6% OC (organic wetland soils, 15% of the dataset) had virtually no predictive relationship of %OC to SOC density (RMSE = 0.0348 g C cm-3, ~56% mean RMSE). Disaggregation by vegetation type, or region did not alter the breakpoint significantly (6% OC) nor improve model accuracies for inland and tidal wetlands. Similarly, SOC stocks in tidal wetlands were related to %OC, but without a mappable product for disaggregation to improve accuracy by soil class, region or depth. Our layered, harmonized CONUS wetland soil maps revised wetland SOC stock estimates downward by 24% (9.5 vs. 12.5Pg C) with the overestimation being entirely an issue of inland, organic wetland soils, (35% lower than SSURGO-derived SOC stocks). Further, SSURGO underestimated soil carbon stocks at depth, as modeled wetland SOC stocks for organic-rich soils showed significant preservation downcore in the NWCA dataset (<3% loss between 0-30 cm and 30-100 cm depths) in contrast to mineral-rich soils (37% downcore stock loss). Future CONUS wetland soil C assessments will benefit from focused attention on improved organic wetland soil measurements, land history, and spatial representativeness.

Assessing the relative and attributable risk of stressors to wetland condition across the conterminous United States.

We analyzed data from 967 randomly selected wetland sites across the conterminous United States (US) as part of the 2011 National Wetland Condition Assessment (NWCA) to investigate the relative and attributable risk of various stressors on wetland vegetation condition. Indicators of stress included six physical stressors (damming, ditching, filling/erosion, hardening, vegetation removal, and vegetation replacement) and two chemical stressors (soil phosphorus and heavy metals) that represent a wide range of human activities. Risk was evaluated nationally and within four aggregate ecoregions and four aggregate wetland types. Nationally, all of the stressors except soil heavy metals and phosphorus had a significant relative risk but values were always < 2 (a relative risk of two indicates that it's twice as likely to have poor vegetation condition when the stressor is present relative to when it is absent). Among the different ecoregions or wetland types, no one stressor was consistently riskier; all of the stressors were associated with poor vegetation condition in one or another of the subpopulations. Overall, hardening had the highest attributable and relative risks in the most different subpopulations. Attributable risks above 25% were observed for vegetation removal in the Coastal Plain, hardening and ditching in the West, and hardening in Estuarine Woody wetlands. Relative risks above 3 were noted for heavy metals and soil phosphorus in the Interior Plains, and vegetation removal, vegetation replacement, and damming in Estuarine Woody wetlands. Relative and attributable risk were added to the data analyses tools used in the NWCA to improve the ability of survey results to assist managers and policy makers in setting priorities based on conditions observed on the ground. These analyses provide useful information to both individual site managers and regional-national policy makers.

Use of national-scale data to examine human-mediated additions of heavy metals to wetland soils of the US.

Soil concentrations of 12 heavy metals that have been linked to various anthropogenic activities were measured in samples collected from the uppermost horizon in approximately 1000 wetlands across the conterminous US as part of the 2011 National Wetland Condition Assessment (NWCA). The heavy metals were silver (Ag), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), vanadium (V), tungsten (W), and zinc (Zn). Using thresholds to distinguish natural background concentrations from human-mediated additions, we evaluated wetland soil heavy metal concentrations in the conterminous US and four regions using a Heavy Metal Index (HMI) that reflects human-mediated heavy metal loads based on the number of elements above expected background concentration. We also examined the individual elements to detect concentrations of heavy metals above expected background that frequently occur in wetland soils. Our data show that wetland soils of the conterminous US typically have low heavy metal loads, and that most of the measured elements occur nationally in concentrations below thresholds that relate to anthropogenic activities. However, we found that soil lead is more common in wetland soils than other measured elements, occurring nationally in 11.3% of the wetland area in concentrations above expected natural background (> 35 ppm). Our data show positive relationships between soil lead concentration and four individual landscape metrics: road density, percent impervious surface, housing unit density, and population density in a 1-km radius buffer area surrounding a site. These relationships, while evident on a national level, are strongest in the eastern US, where the highest road densities and greatest population densities occur. Because lead can be strongly bound to wetland soils in particular, maintenance of the good condition of our nation's wetlands is likely to minimize risk of lead mobilization.

The response of wetland quality indicators to human disturbance indicators across the United States.

We analyzed data from 1138 wetland sites across the conterminous United States (US) as part of the 2011 National Wetland Condition Assessment (NWCA) to investigate the response of indicators of wetland quality to indicators of human disturbance at regional and continental scales. The strength and nature of these relationships in wetlands have rarely been examined over large regions, due to the paucity of large-scale datasets. Wetland response indicators were a multimetric index of vegetation condition (VMMI), percent relative cover of alien plant species, soil lead and phosphorus, and water column total nitrogen and total phosphorus. Site-level disturbance indices were generated from field observations of disturbance types within a circular 140-m radius area around the sample point. Summary indices were calculated representing disturbances for ditching, damming, filling/erosion, hardening, vegetation replacement, and vegetation removal. Landscape-level disturbance associated with agricultural and urban land cover, roads, and human population were based on GIS data layers quantified in 200, 500, and 1000-m circular buffers around each sample point. Among these three buffer sizes, the landscape disturbance indicators were highly correlated and had similar relationships with the response indictors. Consequently, only the 1000-m buffer data were used for subsequent analyses. Disturbance-response models built using only landscape- or only site-level disturbance variables generally explained a small portion of the variance in the response variables (R2 < 0.2), whereas models using both types of disturbance data were better at predicting wetland responses. The VMMI was the response variable with the strongest relationship to the disturbances assessed in the NWCA (national model R2 = 0.251). National multiple regression models for the soil and water chemistry and percent alien cover responses to disturbance indices were not significant. The generally low percentage of significant models and the wide variation in predictor variables suggests that stressor-response relationships vary considerably across the diversity of wetland types and landscape settings found across the conterminous US. Logistic regression modeling was more informative, resulting in significant national and regional models predicting site presence/absence of alien species and/or the concentration of lead in wetland soils above background.

Characterizing nonnative plants in wetlands across the conterminous United States.

Nonnative plants are widely recognized as stressors to wetlands and other ecosystems. They may compete with native plant species or communities and alter ecosystem properties, which can affect ecological condition, posing challenges to resource managers. As part of the United States Environmental Protection Agency's National Wetland Condition Assessment (NWCA), we characterized the status of nonnative plants in wetlands across the conterminous United States (US). Our primary goals were to (1) document the composition of nonnative taxa at 1138 NWCA sites sampled in 2011 and (2) estimate the areal extent of wetland under stress from nonnative plants within the NWCA 2011 sampled population of ~ 25 million ha of wetland (represented by 967 sampled probability sites and the NWCA survey design). A total of 443 unique nonnative taxa were observed, encompassing a species pool adapted to diverse ecological conditions. For individual sites, the number of nonnative taxa ranged from 0 to 29, and total absolute cover of nonnatives ranged from 0 to 160%. We devised the nonnative plant indicator (NNPI) as a categorical indicator of stress (low to very high) from the collective set of nonnative plant taxa occurring at a particular location, based on a decision matrix of exceedance values for nonnative richness, relative frequency, and relative cover. Wetland area of the sampled population occurring in each NNPI category was estimated at the scale of the conterminous US and within five large ecoregions and four broad wetland types. Potential stress from nonnative plants, as indicated by the NNPI category, was low for approximately 61% (~ 15.3 million ha), moderate for about 20% (~ 5.2 million ha), high for about 10% (~ 2.48 million ha), and very high for about 9% (~ 2.2 million ha) of the wetland area in the entire sampled population. Percent of wetland area with high and very high NNPI varied by ecoregional subpopulations: greater within interior and western ecoregions (~ 29 to 87%) than within ecoregions in the eastern half of the nation (~ 11%). Among wetland type subpopulations, greater percent of wetland area with high and very high NNPI was observed for herbaceous vs. woody types and for inland vs. estuarine types. Estimates of wetland area by NNPI categories are expected to be useful to policy makers or resource managers for prioritizing management actions by identifying situations where stress from nonnative plants is most extensive. We also considered four exploratory analyses aimed at providing ecological information useful in interpreting NNPI extent results. We conducted three population-scale analyses examining ecoregional and wetland type population means for (1) the three NNPI metrics, (2) absolute cover of growth-habit groups of nonnative plants, and (3) metrics describing human-mediated disturbance. Finally, we examined ecological relationships with site-level NNPI status using a random forest (RF) analysis with NNPI as the response variable and predictor variables including ecoregion, wetland type, and a variety of characteristics describing natural vegetation structure, environment, and human-mediated disturbance.

Striving for consistency in the National Wetland Condition Assessment: developing a reference condition approach for assessing wetlands at a continental scale.

One of the biggest challenges when conducting a continental-scale assessment of wetlands is setting appropriate expectations for the assessed sites. The challenge occurs for two reasons: (1) tremendous natural environmental heterogeneity exists within a continental landscape and (2) reference sites vary in quality both across and within major regions of the continent. We describe the process used to set reference expectations and define a disturbance gradient for the United States (US) Environmental Protection Agency's National Wetland Condition Assessment (NWCA). The NWCA employed a probability design and sampled 1138 wetland sites across the conterminous US to make an unbiased assessment of wetland condition. NWCA vegetation data were used to define 10 reporting groups based on ecoregion and wetland type that reduced the naturally occurring variation in wetland vegetation associated with continent-wide differences in biogeography. These reporting groups were used as a basis for defining quantitative criteria for least disturbed and most disturbed conditions and developing indices and thresholds for categories of ecological condition and disturbance. The NWCA vegetation assessment was based on a reference site approach, in which the least disturbed reference sites were used to establish benchmarks for assessing the condition of vegetation at other sites. Reference sites for each reporting group were identified by filtering NWCA sample data for disturbance using a series of abiotic variables. Ultimately, 277 least disturbed sites were used to set reference expectations for the NWCA. The NWCA provided a unique opportunity to improve our conceptual and technical understanding of how to best apply a reference condition approach to assessing wetlands across the US. These results will enhance the technical quality of future national assessments.

A framework to quantify the strength of ecological links between an environmental stressor and final ecosystem services.

Anthropogenic stressors such as climate change, increased fire frequency, and pollution drive shifts in ecosystem function and resilience. Scientists generally rely on biological indicators of these stressors to signal that ecosystem conditions have been altered. However, these biological indicators are not always capable of being directly related to ecosystem components that provide benefits to humans and/or can be used to evaluate the cost-benefit of a change in health of the component (ecosystem services). Therefore, we developed the STEPS (STressor - Ecological Production function - final ecosystem Services) Framework to link changes in a biological indicator of a stressor to final ecosystem services. The STEPS framework produces "chains" of ecological components that explore the breadth of impacts resulting from the change of a stressor. Chains are comprised of the biological indicator, the ecological production function (EPF; which uses ecological components to link the biological indicator to a final ecosystem service), and the user group who directly uses, appreciates, or values the component. The framework uses a qualitative score (High, Medium, Low) to describe the Strength of Science (SOS) for the relationship between each component in the EPF. We tested the STEPS Framework within a workshop setting using the exceedance of critical loads of air pollution as a model stressor and the Final Ecosystem Goods and Services Classification System (FEGS-CS) to describe final ecosystem services. We identified chains for four modes of ecological response to deposition: aquatic acidification, aquatic eutrophication, terrestrial acidification, and terrestrial eutrophication. The workshop participants identified 183 unique EPFs linking a change in a biological indicator to a FEGS; and when accounting for the multiple beneficiaries, we ended with 1104 chains. The SOS scores were effective in identifying chains with the highest confidence ranking as well as those where more research is needed. The STEPS framework could be adapted to any system in which a stressor is modifying a biological component. The results of the analysis can be used by the social science community to apply valuation measures to multiple or selected chains, providing a comprehensive analysis of the effects of anthropogenic stressors on measures of human well-being.

Using ecological production functions to link ecological processes to ecosystem services.

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem services (ES) production. Although EPFs are acknowledged as being essential to improve environmental management, their use in ecological risk assessment has received relatively little attention. Ecological production functions may be defined as usable expressions (i.e., models) of the processes by which ecosystems produce ES, often including external influences on those processes. We identify key attributes of EPFs and discuss both actual and idealized examples of their use to inform decision making. Whenever possible, EPFs should estimate final, rather than intermediate, ES. Although various types of EPFs have been developed, we suggest that EPFs are more useful for decision making if they quantify ES outcomes, respond to ecosystem condition, respond to stressor levels or management scenarios, reflect ecological complexity, rely on data with broad coverage, have performed well previously, are practical to use, and are open and transparent. In an example using pesticides, we illustrate how EPFs with these attributes could enable the inclusion of ES in ecological risk assessment. The biggest challenges to ES inclusion are limited data sets that are easily adapted for use in modeling EPFs and generally poor understanding of linkages among ecological components and the processes that ultimately deliver the ES. We conclude by advocating for the incorporation into EPFs of added ecological complexity and greater ability to represent the trade-offs among ES. Integr Environ Assess Manag 2017;13:52-61. © 2016 SETAC.

The effect of river pulsing on sedimentation and nutrients in created riparian wetlands.

Sedimentation under pulsed and steady-flow conditions was investigated in two created flow-through riparian wetlands in central Ohio over 2 yr. Hydrologic pulses of river water lasting for 6 to 8 d were imposed on each wetland from January through June during 2004. Mean inflow rates during pulses averaged 52 and 7 cm d(-1) between pulses. In 2005, the wetlands received a steady-flow regime of 11 cm d(-1) with no major hydrologic fluctuations. Thirty-two sediment traps were deployed and sampled once per month in April, May, June, and July for two consecutive years in each wetland. January through March were not sampled in either year due to frozen water surfaces in the wetlands. Gross sedimentation (sedimentation without normalizing for differences between years) was significantly greater in the pulsing study period (90 kg m(-2)) than in the steady-flow study period (64 kg m(-2)). When normalized for different hydrologic and total suspended solid inputs between years, sedimentation for April through July was not significantly different between pulsing and steady-flow study periods. Sedimentation for the 3 mo that received hydrologic pulses (April, May, and June) was significantly lower during pulsing months than in the corresponding steady-flow months. Large fractions of inorganic matter in collected sediments indicated that allochthonous inputs were the main contributor to sedimentation in these wetlands. Organic matter fractions of collected sediments were consistently greater in the steady-flow study period (1.8 g kg(-1)) than in the pulsed study period (1.5 g kg(-1)), consistent with greater primary productivity in the water column during steady-flow conditions.