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Macroinvertebrate and fish metrics are an essential tool in freshwater biomonitoring. Yet, many well-known stream metrics do not perform well as indicators of anthropogenic stress in lakes and wetlands, and there is a need to better understand the role of potential confounding factors such as latitude or environmental variables acting at regional scales. We attempt to untangle the relationships among metrics and watershed stressors while accounting for potential confounding factors using hierarchical partitioning, and test metric consistency across time, focusing on the Laurentian Great Lakes wetland monitoring programs conducted 10 years apart. Our results show that many frequently used metrics have high temporal variability and are significantly affected by spatial factors, most notably richness-type metrics used in numerous regional monitoring studies. Only a few metrics (invasive fish species richness and relative abundance, mayfly family richness and the relative abundance of Ephemeroptera, Trichoptera, Sphaeriidae and Odonata) had slightly better and more consistent correlations with watershed land use. We suggest that explicit consideration of confounding factors is essential in the context of large-scale monitoring programs, and focus on the less general (such as habitat-specific) metrics may be a more promising approach.

We describe development anthropogenic stress indices for coastal margins of the Laurentian Great Lakes basin. Indices were derived based on the response of species assemblages to watershed-scale stress from agriculture and urbanization. Metrics were calculated for five groups of wetland biota: diatoms, wetland vegetation, aquatic invertebrates, fishes, and birds. Previously published community change points of these assemblages were used to classify each watershed as ‘least-disturbed’, ‘at-risk’, or ‘degraded’ based on community response to these stressors. The end products of this work are an on-line map utility and downloadable data that characterize the degree of agricultural land use and development in all watersheds of the US and Canadian Great Lakes basin. Discrepancies between the observed biological condition and putative anthropogenic stress can be used to determine if a site is more degraded than predicted based on watershed characteristics, or if remediation efforts are having beneficial impacts on site condition. This study provides a landscape-scale evaluation of wetland condition that is a critical first step for multi-scale assessments to help prioritize conservation or restoration efforts.

Stressor gradients and spatial narratives of the St. Louis River Estuary, a joint Minnesota and Wisconsin Sea Grant study, connected aquatic science research with spatially-explicit stories of local resource issues and place-based geo-quests to enhance spatial awareness and stewardship of the estuary. The goal of this paper is to report and reflect on an integrated study that combined environmental humanities and technology with aquatic science in a spatial context. Our study was organized into three objectives around research, outreach, and evaluation. First, we summarized anthropogenic stressors within high resolution watersheds and linked the watershed stress estimates to aquatic habitats within the estuary. Second, we designed tools to deliver place-based environmental science and technology to targeted users to increase awareness, learning, and the potential for long-term stewardship. And third, we evaluated the responses of targeted end users to their interaction with the project’s integrated science and innovative delivery methods. Finally, central to all three objectives, we created a dynamic website to facilitate regional to national coastal outreach and education goals. We found significant correlations between the stressor index and the water quality and biotic data, along with variability attributed to landscape elements. Connecting this science with the place-based experiences we collected is expected to expand the scope and reach of state, bi-national and non-governmental outreach programs. The project also has direct applications to classroom science education. Developing this integrated project contributed to our shared knowledge of environmental and cultural aspects of the estuary for place-based education, and offers several lessons for future work of this nature.

The St. Louis River drains an area of 9412 km 2 into the western arm of Lake Superior. The river's lower section, including a 48.5 km 2 estuary, was designated as a Great Lakes Area of Concern due to degradation from industrial activities. Part of the estuary is occupied by the largest port in the Great Lakes. A GIS-based stressor index was previously developed to characterize anthropogenic stress within the watershed. The components of the stressor index were road density, point-source pollution permit density, population density, and percent agricultural and developed land. Water quality sampling was conducted at 27 sites in the estuary in tributaries and associated nearshore areas during multiple flow regimes in 2010–2011. Additional data were analyzed from 34 upper watershed sites sampled in 2009–2010. Stressor scores were significantly (p 2 − /NO 3 − -N, dissolved oxygen saturation, pH, specific electrical conductivity, chloride, sulfate, and E. coli in the upper watershed. In the estuary, the index was significantly and positively correlated with NO 2 − /NO 3 − -N, NH 4 + -N, and chloride at multiple flow regime and location combinations. Soil K factor (an erosivity index from recent NRCS SSURGO soil surveys) was found to have stronger relationships with sediment related parameters than the stressor gradient. Although originally designed to help stratify sampling across a gradient of landscape stress and identify reference areas for restoration projects, the stressor index was shown to have substantial predictive power for multiple water quality parameters.

Context Green infrastructure may improve water quality and mitigate flooding in forest-urban watersheds, but reliably quantifying all benefits is challenging because most land cover maps depend on moderate- to low-resolution data. Complex and spatially heterogeneous landscapes that typify forest-urban watersheds are not fully represented with these types of data. Hence important questions concerning how green infrastructure influences water quality and quantity at different spatial scales remain unanswered. Objectives Demonstrate the feasibility of creating novel high-resolution land cover maps across entire watersheds and highlight deficiencies of standard land cover products. Methods We used object-based image analysis (OBIA) to create high-resolution (0.5 m) land cover maps and detect tree canopy overlapping impervious surfaces for a representative forest-urban watershed in Duluth, MN, USA. Unbiased estimates of accuracy and area were calculated and compared with similar metrics for the 30-m National Land Cover Database (NLCD). Results Mapping accuracies for the high-resolution land cover and canopy overlap maps were ~90 %. Error-adjusted estimates of area indicated that impervious surfaces comprised ~21 % of the watershed, tree canopy overlapped ~10 % of impervious surfaces, and that three high-resolution land cover classes differed significantly from similar NLCD classes. Conclusions OBIA can efficiently generate high-resolution land cover products of entire watersheds that are appropriate for research and inclusion in the decision-making process of managers. Metrics derived from these products will likely differ from standard land cover maps and may produce new insights, especially when considering the unprecedented opportunity to evaluate fine-scale spatial heterogeneity across watersheds.