A multiscale landscape approach for prioritizing river and stream protection and restoration actions.

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

Genus-level, trait-based multimetric diatom indices for assessing the ecological condition of rivers and streams across the conterminous United States.

Taxonomic inconsistency in species-level identifications has constrained use of diatoms as biological indicators in aquatic assessments. We addressed this problem by developing diatom multimetric indices (MMIs) of ecological condition using genus-level taxonomy and trait-based autecological information. The MMIs were designed to assess river and stream chemical, physical and biological condition across the conterminous United States. Trait-based approaches have the advantage of using both species-level and genus-level data, which require less effort and expense to acquire than traditional species-based approaches and eliminate the persistent taxonomic biases introduced over vast geographic extents. For large-extent assessment programs that require multiple taxonomic laboratories to process samples, such as the United States Environmental Protection Agency's (U.S. EPA's) National Rivers and Streams Assessment (NRSA), the trait approach can eliminate discrepancies in species-level identification or nomenclature that hinder diatom data interpretation. We developed trait-based MMIs using NRSA data for each of the three large ecoregions across the U.S. - the East, Plains, and West. All three MMIs performed well in discriminating least-disturbed from most-disturbed sites. The MMI for the East had the greatest discrimination ability, followed by MMIs for the Plains and West, respectively. The performance of the MMIs was comparable to that observed in existing NRSA fish and macroinvertebrate MMIs. Our research shows that trait-based diatom indices constructed on genus-level taxonomy can be effective for large-scale assessments, and may also allow programs such as NRSA to assess trends in freshwater condition retrospectively, by revisiting older diatom datasets. Moreover, our genus-based approach facilitates including of diatoms into other assessment programs that have limited monitoring resources.

The use of multiscale stressors with biological condition assessments: A framework to advance the assessment and management of streams.

Incorporating information on landscape condition (or integrity) across multiple spatial scales and over large spatial extents in biological assessments may allow for a more integrated measure of stream biological condition and better management of streams. However, these systems are often assessed and managed at an individual scale (e.g., a single watershed) without a larger regional multiscale context. In this paper, our goals were: (1) To develop a conceptual framework that could combine stream biological condition to abiotic landscape integrity (or, conversely, stressor) data at three spatial scales: watershed, catchment and stream-reach scale, to enable more targeted management actions. Measures of landscape integrity and stressors are negatively related, i.e., integrity on a 0-1 scale is equal or equivalent to stressors on a 1-0 scale. (2) To develop the framework in such a way that allows operational flexibility, whereby different indicators can be used to represent biological condition, and landscape integrity (or stressors) at various scales. (3) To provide different examples of the framework's use to demonstrate the flexibility of its application and relevance to management. Examples include stream biological assessments from different regions and states across the U.S. for fish, macroinvertebrates and diatoms using a variety of assessment tools (e.g., the Biological Condition Gradient (BCG), and an Index of Biotic Integrity (IBI)). Landscape integrity indicators comprise U.S. EPA's nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI), and state and regional derived watershed and stream-reach scale integrity indicators. Scatterplots and a landscape integrity map were used to relate samples of stream condition classes (e.g., good, fair, poor) to watershed, catchment and stream-reach scale integrity. This framework and approach could provide a powerful tool for prioritizing, targeting, and communicating management actions to protect and restore stream habitats, and for informing the spatial extent at which management is applied.

Development of a diatom-based multimetric index for acid mine drainage impacted depressional wetlands.

Acid mine drainage (AMD) from coal mining in the Mpumalanga Highveld region of South Africa has caused severe chemical and biological degradation of aquatic habitats, specifically depressional wetlands, as mines use these wetlands for storage of AMD. Diatom-based multimetric indices (MMIs) to assess wetland condition have mostly been developed to assess agricultural and urban land use impacts. No diatom MMI of wetland condition has been developed to assess AMD impacts related to mining activities. Previous approaches to diatom-based MMI development in wetlands have not accounted for natural variability. Natural variability among depressional wetlands may influence the accuracy of MMIs. Epiphytic diatom MMIs sensitive to AMD were developed for a range of depressional wetland types to account for natural variation in biological metrics. For this, we classified wetland types based on diatom typologies. A range of 4-15 final metrics were selected from a pool of ~140 candidate metrics to develop the MMIs based on their: (1) broad range, (2) high separation power and (3) low correlation among metrics. Final metrics were selected from three categories: similarity to reference sites, functional groups, and taxonomic composition, which represent different aspects of diatom assemblage structure and function. MMI performances were evaluated according to their precision in distinguishing reference sites, responsiveness to discriminate reference and disturbed sites, sensitivity to human disturbances and relevancy to AMD-related stressors. Each MMI showed excellent discriminatory power, whether or not it accounted for natural variation. However, accounting for variation by grouping sites based on diatom typologies improved overall performance of MMIs. Our study highlights the usefulness of diatom-based metrics and provides a model for the biological assessment of depressional wetland condition in South Africa and elsewhere.