Use of Scale Invariance in Evaluating Judgement Indicators

Indicators are used to draw conclusions about ecological endpoints when these endpoints cannot be measured directly. In many cases, inferences about an endpoint are only possible because assumptions have been made about the relationship between indicator and endpoint; we refer to such indicators as judgement indicators. The validity of inferences made using a judgement indicator can be gauged by examining the known or assumed form of the general relationship between indicator and endpoint. The rules for this kind of inference are a consequence of scale invariance, which originates from measurement theory. For simple indicators comprised of a single indicator measurement, the inferences allowed – equivalence, rank, equality of intervals, and equality of ratios – depend on whether the data are nominal, ordinal, interval, or ratio scaled. For composite indicators containing two or more simple indicators, inferences are also affected by the mathematical form of combination; e.g., whether the terms are summed or multiplied. Standardizing simple or composite indicators can allow inferences about the relative importance of observations, based on the natural range of occurrence. Scale invariance is a particularly important consideration in landscape assessments, since these often make use of judgement indicators.     

Wetland Flowpaths Mediate Nitrogen and Phosphorus Concentrations across the Upper Mississippi River Basin

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, “wetland hydrological transport variables,” to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape-to-aquatic nutrient multilinear regression models (from R² = 0.89 to 0.91 for TN; R² = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed-scale TN and TP concentrations. Specifically, flowpath variables describing flow-attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters.     

Comparing the Extent and Permanence of Headwater Streams From Two Field Surveys to Values From Hydrographic Databases and Maps

Supreme Court cases have questioned if jurisdiction under the Clean Water Act extends to water bodies such as streams without year‐round flow. Headwater streams are central to this issue because many periodically dry, and because little is known about their influence on navigable waters. An accurate account of the extent and flow permanence of headwater streams is critical to estimating downstream contributions. We compared the extent and permanence of headwater streams from two field surveys with values from databases and maps. The first used data from 29 headwater streams in nine U.S. forests, whereas the second had data from 178 headwater streams in Oregon. Synthetic networks developed from the nine‐forest survey indicated that 33 to 93% of the channel lacked year‐round flow. Seven of the nine forests were predicted to have >200% more channel length than portrayed in the high‐resolution National Hydrography Dataset (NHD). The NHD and topographic map classifications of permanence agreed with ~50% of the field determinations across ~300 headwater sites. Classification agreement with the field determinations generally increased with increasing resolution. However, the flow classification on soil maps only agreed with ~30% of the field determination despite depicting greater channel extent than other maps. Maps that include streams regardless of permanence and size will aid regulatory decisions and are fundamental to improving water quality monitoring and models.     

Hydrologic Landscape Characterization for the Pacific Northwest,USA

We update the Wigington et al. (2013) hydrologic landscape (HL) approach to make it more broadly applicable and apply the revised approach to the Pacific Northwest (PNW; i.e., Oregon, Washington, and Idaho). Specific changes incorporated are the use of assessment units based on National Hydrography Dataset Plus V2 catchments, a modified snowmelt model validated over a broader area, an aquifer permeability index that does not require preexisting aquifer permeability maps, and aquifer and soil permeability classes based on uniform criteria. Comparison of Oregon results for the revised and original approaches found fewer and larger assessment units, loss of summer seasonality, and changes in rankings and proportions of aquifer and soil permeability classes. Differences could be explained by three factors: an increased assessment unit size, a reduced number of permeability classes, and use of smaller cutoff values for the permeability classes. The distributions of the revised HLs in five groups of Oregon rivers were similar to the original HLs but less variable. The improvements reported here should allow the revised HL approach to be applied more often in situations requiring hydrologic classification and allow greater confidence in results. We also apply the map results to the development of hydrologic landscape regions.     

ENVIRONMENTAL AUDITING: A Synoptic Approach for Assessing Cumulative Impacts to Wetlands

/ The US Environmental Protection Agency's Wetlands ResearchProgram has developed the synoptic approach as a proposed method forassessing cumulative impacts to wetlands by providing both a general and acomprehensive view of the environment. It can also be applied more broadly toregional prioritization of environmental issues. The synoptic approach is aframework for making comparisons between landscape subunits, such aswatersheds, ecoregions, or counties, thereby allowing cumulative impacts tobe considered in management decisions. Because there is a lack of tools thatcan be used to address cumulative impacts within regulatory constraints, thesynoptic approach was designed as a method that could make use of availableinformation and best professional judgement. Thus, the approach is acompromise between the need for rigorous results and the need for timelyinformation. It is appropriate for decision making when quantitative,accurate information is not available; the cost of improving existinginformation or obtaining better information is high; the cost of a wronganswer is low; there is a high demand for the information; and the situationcalls for setting priorities between multiple decisions versus optimizing fora single decision. The synoptic approach should be useful for resourcemanagers because an assessment is timely; it can be completed within one totwo years at relatively low cost, tested, and improved over time. Anassessment can also be customized to specific needs, and the results arepresented in mapped format. However, the utility of a synoptic assessmentdepends on how well knowledge of the environment is incorporated into theassessment, relevant to particular management questions.KEY WORDS: Cumulative impact assessment; Landscape ecology; Regionalprioritization     

JSEM: A Framework for Identifying and Evaluating Indicators

There are two issues in indicator development that have not been adequately addressed: (1) how to select an optimal combination of potentially redundant indicators that together best represent an endpoint, given cost constraints; (2) how to identify and evaluate indicators when the endpoint is unmeasured. This paper presents an approach to identifying and evaluating combinations of indicators when the mathematical relationships between the indicators and an endpoint may not be quantified, a limitation common to many ecological assessments. The approach uses the framework of Structural Equation Modeling (SEM), which combines path analysis withmeasurement models, to formalize available informationabout potential indicators and to evaluate their potential adequacy for representing an endpoint. Unlike traditional applications of SEM which require data on all variables, our approach – judgement-based SEM (JSEM) – can utilize expert judgement regarding the strengths and shapes of indicator-endpoint relationships. JSEM is applied in two stages. First, a conceptual model that relates variables in a network of direct and indirect linkages is developed, and is used to identify indicators relevant to an endpoint. Second, an index of indicator strength – i.e., the strength of the relationship between the endpoint and a set of indicators – is calculated from estimates of correlation between the modeled variables, and is used to compare alternative sets of indicators. The second stage is most appropriate for large, long-term assessments. Although JSEM is not a statistical technique, basing JSEM on SEM provides a structure for validating the conceptual model and for refining the index of indicator strength as data become available. Our main objective is to contribute to a rigorous and consistent selection of indicators even when knowledgeabout the ability of indicators to represent an endpoint is limited to expert judgement.     

Featured Collection Introduction: Connectivity of Streams and Wetlands to Downstream Waters

Connectivity is a fundamental but highly dynamic property of watersheds. Variability in the types and degrees of aquatic ecosystem connectivity presents challenges for researchers and managers seeking to accurately quantify its effects on critical hydrologic, biogeochemical, and biological processes. However, protecting natural gradients of connectivity is key to protecting the range of ecosystem services that aquatic ecosystems provide. In this featured collection, we review the available evidence on connections and functions by which streams and wetlands affect the integrity of downstream waters such as large rivers, lakes, reservoirs, and estuaries. The reviews in this collection focus on the types of waters whose protections under the U.S. Clean Water Act have been called into question by U.S. Supreme Court cases. We synthesize 40+ years of research on longitudinal, lateral, and vertical fluxes of energy, material, and biota between aquatic ecosystems included within the Act's frame of reference. Many questions about the roles of streams and wetlands in sustaining downstream water integrity can be answered from currently available literature, and emerging research is rapidly closing data gaps with exciting new insights into aquatic connectivity and function at local, watershed, and regional scales. Synthesis of foundational and emerging research is needed to support science‐based efforts to provide safe, reliable sources of fresh water for present and future generations.     

Use of Hydrologic Landscape Classification to Diagnose Streamflow Predictability in Oregon

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape (OHL) classification. OHL is used to identify the physio‐climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash‐Sutcliffe efficiency of (NS) > 0.75) are mainly classified as rain dominated with very wet climate, low aquifer permeability, and low to medium soil permeability. Most of them are located west of the Cascade Mountain Range. Conversely, most low prediction catchments (NS < 0.6) are classified as snow‐dominated with high aquifer permeability and medium to high soil permeability. They are mainly located in the volcano‐influenced High Cascades region. Using a subset of 36 catchments, we further test if class‐specific model parameters can be developed to predict at ungauged catchments. In most catchments, OHL class‐specific parameters provide predictions that are on par with individually calibrated parameters (NS decline < 10%). However, large NS declines are observed in OHL classes where predictability is not high enough. Results suggest higher uncertainty in rain‐to‐snow transition of precipitation phase and external gains/losses of deep groundwater are major factors for low prediction in Oregon. Moreover, regionalized estimation of model parameters is more useful in regions where conditions favor good streamflow predictability.