The Great Lakes coastal region is a dynamic area at the interface between land and water. It is heavily influenced by the magnitude of the large lakes themselves, by natural abiotic and biotic processes in the watershed, and especially by human activity. This special issue contains a series of 21 papers that are organized into four major themes: 1) landscape characterization and coastal linkage, 2) integration, 3) indicator development, and 4) supporting information. The results of these papers emphasize that many environmental response signals are linked to their physiobiogeographic location in the basin and with human activity in coastal watersheds or in the immediate coastal margin. If lake levels continue to fluctuate and decline, if the climate continues to warm, if agricultural activity expands, if exotic species continue to invade, and if the human population density in the watershed increases, then environmental indicators of the Great Lakes coastal region reported here will point to further degradation of water quality and native amphibian, bird, diatom, fish, macroinvertebrate, and wetland plant communities. These environmental indicators are benchmarks for the current conditions of the Great Lakes coastal region and provide measurable endpoints to assess the success of future management, conservation, protection, and restoration of this important resource.

Watersheds represent spatially explicit areas within which terrestrial stressors can be quantified and linked to measures of aquatic ecosystem condition. We delineated thousands of Great Lakes watersheds using previously proven and new watershed delineation techniques. These were used to provide summaries for a variety of anthropogenic stressors within the Great Lakes. All delineation techniques proved useful, but each had applications for which they were most appropriate. A set of watershed delineations and stressor summaries was developed for sampling site identification, providing relatively coarse strata for selecting sites along the U.S. Great Lakes coastline. Subsequent watershed delineations were used for high-resolution site characterization of specific sites and characterizing the full coastal stressor gradient. For these delineations we used three general approaches: 1) segmentation of the shoreline at points midway between adjacent streams and delineation of a watershed for each segment; 2) specific watershed delineations for sampled sites; and 3) a Great Lakes basin-wide, high-resolution approach wherein sub-basins can be agglomerated into larger basins for specific portions of the coast. The third approach is unique in that it provides a nested framework based on hierarchies of catchments with associated stressor data. This hierarchical framework was used to derive additional watershed delineations, and their associated stressor summaries, at four different scales. Providing anthropogenic stressor metrics in such a format that can quickly be summarized for the entire basin at multiple scales, or specifically for particular areas, establishes a strong foundation for quantifying and understanding stressor-response relationships in these coastal environments.

As populations and human activities increase in coastal watersheds, an understanding of the connections of aquatic ecosystems to the adjacent terrestrial landscape is necessary to identify, monitor, and protect vulnerable coastal habitats. This study investigates the relationships between land-use patterns and δ¹⁵N values of aquatic organisms in coastal ecosystems, across a defined watershed gradient for the U.S. portion of the Great Lakes shoreline. δ¹⁵N measured in plankton and benthic invertebrates reflects a range of basin wide land-use gradients and demonstrates a strong connection between watershed-based anthropogenic activities and exposure in aquatic biota. For example, benthos δ¹⁵N values range over 12‰ across sites in our study, but regression analyses suggest that over 50% of the variability is explained by the regional landscape. Further, multiple taxa at comparable trophic position showed similar patterns in relation to watershed-scale land use. Our results suggest that within the coastal environment, the expression of landscape in aquatic biota is stronger in habitats such as embayments and wetlands than open nearshore. These results support the use of δ¹⁵N in Great Lakes coastal biota as an exposure indicator of watershed-scale N loading.

Developing indicators of ecosystem condition is a priority in the Great Lakes, but little is known about appropriate spatial scales to characterize disturbance or response for most indicators. We surveyed birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms at 276 coastal wetland locations throughout the U.S. Great Lakes coastal region during 2002–2004. We assessed the responsiveness of 66 candidate indicators to human disturbance (agriculture, urban development, and point source contaminants) characterized at multiple spatial scales (100, 500, 1,000, and 5,000 m buffers and whole watersheds) using classification and regression tree analysis (CART). Non-stressor covariables (lake, ecosection, watershed, and wetland area) accounted for a greater proportion of variance than disturbance variables. Row-crop agriculture and urban development, especially at larger spatial scales, were about equally influential and were more explanatory than a contaminant stress index (CSI). The CSI was an important predictor for diatom indicators only. Stephanodiscoid diatoms and nest-guarding fish were identified as two of the most promising indicators of row-crop agriculture, while Ambloplites rupestris (fish) and Aeshna (dragonflies) were two of the strongest indicators of urban development. Across all groups of taxa and spatial scales, fish indicators were most responsive to the combined influence of row-crop and urban development. Our results suggest it will be critical to account for the influence of potentially important non-stressor covariables before assessing the strength of indicator responses to disturbance. Moreover, identifying the appropriate scale to characterize disturbance will be necessary for many indicators, especially when urban development is the primary disturbance.

We present water quality data from 58 coastal wetlands, sampled as part of a larger effort investigating effects of nutrient enrichment and habitat disruption in the Laurentian Great Lakes. Our sampling design selected sites from across a gradient of agricultural intensity within combinations of biogeographic ecoprovince and wetland hydromorphic type and captured a large range in water quality. Levels of total nutrients (N and P), and various measures of particulate concentration, water clarity, and ionic strength were strongly associated with agricultural intensity in the watershed, and could be effectively aggregated into an overall principal component-based water quality descriptor. Lake Erie wetlands had the highest nutrient levels and lowest water clarity, while wetlands in Lakes Superior and Huron had the lowest nutrient levels and clearest water. Lake Ontario wetlands had clearer water than would be expected from their nutrient levels and position on the agricultural intensity gradient. Dissolved oxygen, silica, pH, and dissolved organic carbon (DOC) were independent of agricultural intensity but DOC was responsible for low water clarity in some Lake Superior wetlands. Simple classification by hydromorphic type (riverine or protected) did not explain water quality differences among wetlands exposed to similar agricultural intensity levels, so finer hydrologic classification may be desirable. Results are used as a basis for discussing research and information needs underlying development of water quality criteria and monitoring programs for coastal wetlands of the Great Lakes.

Diatom-based models to infer nutrient concentrations are proven robust indicators, but evidence suggests that in the future these models will be little improved by using larger training sets. I present a simple means to summarize the water quality (WQ) data from a suite of coastal Great Lakes locations and develop a diatom-based WQ model using standard weighted-averaging methods. A one-dimensional WQ index was derived by summarizing measured environmental data (nutrients, pigments, solids) using dimension-reducing ordination and calculating the primary WQ gradient of interest. Evaluations of weighted-averaging diatom model predictions (WQ index model: r²_jackknife = 0.62, RMSEP = 1.32) indicate that the model has reconstructive power similar to a comparative model for total phosphorus concentrations (TP model: r²_jackknife = 0.65, RMSEP = 0.26 log[μg/L 1]), but that predictive bias was lower for the WQ model. Also, inferred WQ index data had a higher correlation to adjacent watershed characteristics than inferred TP data. We attribute this to the ability of an integrated WQ index to better characterize the overall quality of a site than a single nutrient variable such as phosphorus. The diatom-based WQ model may be advantageous for management where it is necessary to provide a summary inference of water quality condition at a coastal locale.

We use bird distributions in non-forested coastal wetlands of the Great Lakes to illustrate a new, conceptually explicit method for developing biotic indicators. The procedure applies a probabilistic framework to derive an index that best “fits” an observed assemblage of species, based on preliminary information about species' responses to human environmental disturbance. Among 215 coastal wetland complexes across the U.S. portion of the Great Lakes, 23 bird species were particularly sensitive (positively or negatively) to a multivariate environmental disturbance gradient ranging from 0 (maximally disturbed) to 10 (minimally disturbed). Species like Sandhill Crane (Grus canadensis) and Sedge Wren (Cistothorus platensis) showed strong negative relationships with human disturbance, while others like Common Grackle (Quiscalus quiscula), American Robin (Turdus migratorius), and European Starling (Sturnus vulgaris), showed strong positive relationships with disturbance. The functional shapes of these biotic responses were used to determine indices of ecological condition (IEC) for new sites. Values of IEC were highly correlated with the environmental gradient, but deviations from a 1:1 relationship reveal novel insights about local ecological conditions. For example, sites dominated by invasive plant species like Phragmites australis tended to yield IEC values that were lower than expected based on the environmental gradient. This framework for calculating ecological indicators holds significant potential for other applications because it is flexible, explicitly linked to a disturbance gradient, and easy to calculate once standardized biotic response functions are documented and made available for a region of interest.

Plant taxa identified in 90 U.S. Great Lakes coastal emergent wetlands were evaluated as indicators of physical environment. Canonical correspondence analysis using the 40 most common taxa showed that water depth and tussock height explained the greatest amount of species-environment interaction among ten environmental factors measured as continuous variables (water depth, tussock height, latitude, longitude, and six ground cover categories). Indicator species analysis was used to identify species-environment interactions with categorical variables of soil type (sand, silt, clay, organic) and hydrogeomorphic type (Open-Coast Wetlands, River-Influenced Wetlands, Protected Wetlands). Of the 169 taxa that occurred in a minimum of four study sites and ten plots, 48 were hydrogeomorphic indicators and 90 were soil indicators. Most indicators of Protected Wetlands were bog and fen species which were also organic soil indicators. Protected Wetlands had significantly greater average coefficient of conservatism (C) values than did Open-Coast Wetlands and River-Influenced Wetlands, but average C values did not differ significantly by soil type. Open-Coast and River-Influenced hydrogeomorphic types tended to have sand or silt soils. Clay soils were found primarily in areas with Quaternary glaciolacustrine deposits or clay-rich tills. A fuller understanding of how the physical environment influences plant species distribution will improve our ability to detect the response of wetland vegetation to anthropogenic activities.

Dominant species play key roles in shaping community structure, but their behavior is far from uniform. We speculated that recognition of different behaviors (determined objectively) would be an indicator of the condition of plant communities. We developed a species dominance index (SDI) to identify dominant species and compare their behavior across multiple spatial scales. The SDI is based on three attributes (mean cover, mean species suppression, and tendency toward high cover), and it identifies up to 38 dominants within 74 Great Lakes coastal wetlands. Dichotomizing each of the attributes in a 2×2×2 matrix produced seven dominant behaviors, or forms, all of which occurred in Great Lakes wetlands. Species showed different dominant forms among locations and aggregation scales. Showing predominantly “monotype” form, invasive Typha was the taxon that was most often dominant in the samples. By quantitatively measuring dominance and describing dominance form, SDI can add insight into community change and is a useful addition to indicators of community condition.

In an evaluation of diatoms as indicators of human disturbance in coastal ecosystems of the Laurentian Great Lakes, we characterized assemblage specificity to lake and habitat type to identify non-anthropogenic factors influencing indicator models. Surface sediment assemblages and environmental variables were collected along the U.S. coastline at 191 sample sites, which were classified by lake and geomorphic type: high-energy (HE), embayment (EB), coastal wetland (CW), riverine wetland (RW), protected wetland (PW), and open water (OP). Diatom inferred (DI) total phosphorus (TP) transfer functions (models) were developed for each lake and geomorphic type. Robust models included: the overall model (RMSEP; r²_jack = 0.65; RMSEP = 0.005), Lake Superior (r²_jack = 0.73; RMSEP = 0.003), Lake Ontario (r²_jack = 0.73; RMSEP = 0.007), PW (r²_jack = 0.64; RMSEP = 0.003), and EB (r²_jack = 0.64;RMSEP = 0.007). Weaker models, indicating poorer diatom-TP relationships, included: RW (r²_jack =0.03; RMSEP = 0.005), OP (r²_jack = 0.15; RMSEP = 0.059), and Lake Michigan (r²_jack = 0.38; RMSEP =0.006). DI TP data were regressed against landscape characteristics to quantify the relationships to adjacent watershed stressors. RW data were further scrutinized as a case study to investigate the suitability of diatom-based approaches in systems with poor diatom-TP relationships. Despite poor performance of the RW model, DI phosphorus data for riverine wetlands, derived from the overall model, were strongly related to watershed characteristics (r² = 0.61), indicating the overall model's ability to integrate stressors from the surrounding watershed in areas where measured phosphorus did not adequately characterize prevailing conditions. This study confirms that physical properties (e.g., lake or habitat type) can influence indicator models; however, weaknesses may be overcome by robust calibration techniques.

The wetland fish index (WFI), a published indicator of wetland condition that ranks wetlands based on tolerance of fish species to degraded water-quality conditions, had been developed with data from 40 wetlands located exclusively in the southern portion of the Great Lakes basin (Erie, Ontario, and Michigan). No data had been included from wetlands of the northern Great Lakes (Superior and Huron) and especially those of eastern and northern Georgian Bay, where many wetlands are still unaffected by human activities. We demonstrate why application of the WFI for the lower lakes (WFI_Lower) can yield biased scores when applied to data for upper lakes wetlands. We then develop a basin-wide index to include data from 60 other coastal wetlands located in the northern portion of the basin, including 32 from Georgian Bay. Inclusion of northern sites in development of a basin-wide WFI (WFI_Basin) still produced index scores that were positively correlated with water-quality conditions as indicated by water quality index scores. We explain why use of the basin-wide WFI is better than one developed specifically for upper lakes (WFI_Upper). Overall, WFI_Basin scores were higher in the northern lakes (Superior 3.49, Georgian Bay 3.67, Huron 3.62) than in the southern lakes (Michigan 3.33, Erie 3.12, Ontario 3.09). WFI scores are only minimally affected by inter-annual variation, which allows for its use for long-term monitoring. We recommend that the WFIBasin be used when managers need to manage at a scale across the entire Great Lakes basin.

Indices have been developed with invertebrates, fish, and water quality parameters to detect the impact of human disturbance on coastal wetlands, but a macrophyte index of fish habitat for the Great Lakes does not currently exist. Because wetland macrophytes are directly influenced by water quality, any impairment in wetland quality should be reflected by taxonomic composition of the aquatic plant community. We developed a wetland macrophyte index (WMI) with plant presence/absence data for 127 coastal wetlands (154 wetland-years) from all five Great Lakes, using results of a canonical correspondence analysis (CCA) to ordinate plant species along a water quality gradient (CCA axis 1). We validated the WMI with data collected before and after the implementation of remedial actions plans (RAPs) in Sturgeon Bay (Severn Sound) and Cootes Paradise Marsh. Consistent with predictions, WMI scores for Sturgeon Bay were significantly higher after the implementation of the RAP. Historical data from Cootes Paradise Marsh were used to track the declining condition of the plant community from the 1940s to 1990s. Subsequently, when remedial actions had been implemented in 1997, the calculated WMI scores showed improvement, but when the presence of exotic species (WMIadj) was accounted for, improvements in ecological integrity of the aquatic-plant community were no longer evident. We show how WMI scores can be used by environmental agencies to assess the historic, current, and future ecological status of wetland ecosystems in two Canadian national parks, Point Pelee National Park (PPNP) and Fathom Five National Marine Park (FFNMP).

Invasion ecology offers a unique opportunity to examine drivers of ecological processes that regulate communities. Biotic resistance to nonindigenous species establishment is thought to be greater in communities that have not been disturbed by human activities. Alternatively, invasion may occur wherever environmental conditions are appropriate for the colonist, regardless of the composition of the existing community and the level of disturbance. We tested these hypotheses by investigating distribution of the nonindigenous amphipod, Echinogammarus ischnus Stebbing, 1899, in co-occurrence with a widespread amphipod, Gammarus fasciatus Say, 1818, at 97 sites across the Laurentian Great Lakes coastal margins influenced by varying types and levels of anthropogenic stress. E. Ischnus was distributed independently of disturbance gradients related to six anthropogenic disturbance variables that summarized overall nutrient input, nitrogen, and phosphorus load carried from the adjacent coastal watershed, agricultural land area, human population density, overall pollution loading, and the site-specific dominant stressor, consistent with the expectations of regulation by general environmental characteristics. Our results support the view that the biotic facilitation by dreissenid mussels and distribution of suitable habitats better explain E. ischnus' distribution at Laurentian Great Lakes coastal margins than anthropogenic disturbance.

Frogs and toads (anurans) are sensitive to a variety of anthropogenic stressors and are widely suggested as indicators of ecological condition. We surveyed 220 coastal wetlands along the U.S. shores of the Laurentian Great Lakes and quantified relationships between presence of anuran species and degree of anthropogenic disturbance. Results were used to derive explicit, functional relationships between environmental condition and anuran occurrences. These functions were subsequently used to calculate a multi-species indicator of ecological condition at other (novel) wetlands. Of 14 anuran species observed, spring peeper (Pseudacris crucifer) exhibited the strongest and most consistent relationship with environmental condition across the entire study area. Other species exhibited significant relationships with the environmental gradient, but the direction of association varied geographically or the overall species abundance was very low (e.g., mink frog, Rana septentrionalis). Even if applied to separate ecological provinces (Laurentian Mixed Forest or Eastern Deciduous Forest), multi-species estimates of wetland condition based on anurans are not much better indicators of environmental condition based on human disturbance than are indices based solely on occurrence of spring peeper. Nevertheless, indicators grounded in explicit relationships with environmental stress are superior to traditional measures (e.g., species richness) that combine species with different responses to the stress gradient. At least one anuran species (spring peeper) can contribute meaningfully to the assessment of ecological condition in Great Lakes coastal wetlands; its value as an indicator will be improved if it can be combined with information from other wetland species such as birds, fishes, and vascular plants.

Fish community composition often varies across ecoregions and hydrogeomorphic types within ecoregions. We evaluated two indices of biotic integrity (IBIs) developed for fish in Great Lakes coastal wetlands dominated (> 50% cover) by Typha (cattail) and Schoenoplectus (formerly Scirpus) (bulrush) vegetation. Thirty-three coastal wetlands dominated by either Typha or Schoenoplectus vegetation were sampled using fyke nets set overnight. These sites were selected to span anthropogenic disturbance gradients based on population density, road density, urban development, point-source pollution, and agricultural inputs (nutrients, sediments), measured using a GIS-based analysis of Great Lakes coastal land use. Sites subject to low levels of anthropogenic influence had high IBI scores. The Typha-specific IBI showed a marginally significant negative correlation with population density and residential development (r = −0.54, p < 0.05; n = 21). The Schoenoplectus-specific IBI negatively correlated most strongly with nutrient and chemical inputs associated with agricultural activity and point-source pollution (r = −0.66 and −0.52, respectively; p < 0.01; n = 30). However, some relationships between IBI and disturbance scores were non-linear and likely exhibit a threshold relationship, particularly for Schoenoplectus dominant sites. Once a certain level of disturbance has been exceeded, a sharp change in fish community's composition and function occurs which is symptomatic of a degraded site. The IBI indices appear to indicate effects of some, but not all classes of anthropogenic disturbance on fish communities. Calibrating these measures against specific stress gradients allows one to interpret the sources of impairment, and thereby use the measures beyond a simple identification of impaired sites.

Synoptic surveys of fish assemblages captured using fyke nets typically use a soak time of one night. We questioned whether enough information was gained from maintaining the nets for a second night to justify both the additional effort and the resulting reduction in sites sampled per field season. We compared fyke net catches from one-night and two-night sets at Great Lakes coastal margin ecosystems. Re-setting nets for a second night increased species richness by an average (± SE) of 12 ± 0.06%. This translated to an average of 2.5 ± 0.25 additional species captured. Ordinations of the assemblage data revealed that one-night and two-night catches from the same site (catch pairs) were much more similar to each other than were catches from different sites: the Kendall's kappa concordance values between one-night catches and their two-night pairs measured along the first three ordination axes were 80%, 88%, and 87%, respectively. Catch pairs plotted more closely, Sorensen's distances were smaller, and assemblages were much more concordant than were pairs of catches randomly selected from different sites. Bootstrap analyses of catch species richness indicated that there was little difference between adding effort by increasing soak time versus adding effort by increasing the number of nets. Our data indicate that one- and two-night sets generally produce comparable assemblage data. For synoptic studies, the increase in statistical power gained by increasing the number of sites sampled will typically be more important than the moderate amount of additional information acquired by fishing sites for a second night.

One goal in indicator development is to implement long-term monitoring that will track the relative condition of the indicator over time. Among the first steps in establishing a monitoring program is to develop a sampling design that adequately characterizes the indicator to be monitored as well as the cost-effectiveness of the program. We used breeding bird data collected in Lake Superior and Lake Michigan coastal wetlands (riverine, lacustrine, barrier-protected) to determine: 1) how to select individual wetlands for sampling, 2) optimum number of sample points per wetland, 3) optimal daily sampling period, 4) how many times to sample, and 5) the costs associated with implementing a monitoring program for breeding bird communities of wetlands across the Great Lakes. We found that wetlands selected for sampling should represent the range of wetlands sizes available for monitoring and that the most cost-effective strategy would be to sample a maximum of three points, even in the largest wetlands. Because surveys conducted in the morning recorded a much higher (P < 0.001) number of species and individuals, we recommend that morning surveys should be conducted. Increasing number of wetlands sampled should be the first priority because sample precision is more improved at a higher cost ratio than by adding counts to the same wetland. Multiple visits to wetlands should be considered only after maximizing the number of individual wetlands visited with money available for surveys. We calculated that the average costs would be approximately 50.00 USD/year (2001 dollars) to monitor one wetland using one morning survey for breeding birds.

Land use and land cover (LULC) was mapped using historical aerial photos (1940) and contemporary QuickBird satellite imagery (2003) for a 100 km² area covering portions of Erie Township, Michigan, and Toledo, Ohio on the western end of Lake Erie. This area serves as a microcosm of conditions elsewhere on the Great Lakes coast, containing a range of human-altered to natural landscapes. Geographic information system analysis was used to measure LULC change within the study area based on the 1940 and 2003 maps, and to illustrate the use of historical aerial photos and data to quantify changes in anthropogenic pressures to coastal ecosystems. Agriculture was and is the main land use in the study site, constituting 78% and 55% of upland area in 1940 and 2003, respectively. Most conversions to other land uses originated as agricultural lands. Transportation changes over the time period included the loss of two major railroad yards and the gain of an interstate highway. The area of commercial and industrial development increased 12-fold, from 20 ha in 1940 to 246 ha by 2003. Major industries built after 1940 included an electrical power plant and a sanitary landfill. Residential development approximately doubled from 353 ha in 1940 to 717 ha in 2003, consistent with an 80% increase in population. Coastal ecosystems within the study area included a coastal spit (Woodtick Peninsula) and a large, partially-diked wetland behind it (Erie Marsh), both of which changed extensively over the time period studied. This approach offers a means of incorporating long-term observations into the evaluation of environmental condition in coastal wetlands.

Great Lakes coastal wetlands are subject to water level fluctuations that promote the maintenance of coastal wetlands. Point au Sauble, a Green Bay coastal wetland, was an open water lagoon as of 1999, but became entirely vegetated as Lake Michigan experienced a prolonged period of below-average water levels. Repeat visits in 2001 and 2004 documented a dramatic change in emergent wetland vegetation communities. In 2001 non-native Phragmites and Typha were present but their cover was sparse; in 2004 half of the transect was covered by a 3 m tall, invasive Phragmites and non-native Typha community. Percent similarity between plant species present in 2001 versus 2004 was approximately 19% (Jaccard's coefficient), indicating dramatic changes in species composition that took place in only 3 years. The height of the dominant herbaceous plants and coverage by invasive species were significantly higher in 2004 than they were in 2001. However, floristic quality index and coefficient of conservatism were greater in 2004 than 2001. Cover by plant litter did not differ between 2001 and 2004. The prolonged period of below-average water levels between 1999 and early 2004 exposed unvegetated lagoon bottoms as mud flats, which provided substrate for new plant colonization and created conditions conducive to colonization by invasive taxa. PCR/RFLP analysis revealed that Phragmites from Point au Sauble belongs to the more aggressive, introduced genotype. It displaces native vegetation and is tolerant of a wide range of water depth. Therefore it may disrupt the natural cycles of vegetation replacement that occur under native plant communities in healthy Great Lakes coastal wetlands.

Rapid assessments are used as qualitative approaches to evaluate wetland quality in the absence of quantitative data and adequate time to assess wetland structure and function. To examine how rapid assessment methods assess bird assemblages in wetlands, we compared bird communities with both the Ohio Rapid Assessment Method (ORAM) and detailed data gathered from 51 coastal riverine wetlands in the western Great Lakes region. We found that birds did not choose wetlands at random but responded to vegetative structure and the degree of anthropogenic disturbance within and surrounding the wetland. ORAM scores adequately reflected the degree of anthropogenic disturbance affecting the wetlands but were insufficient to explain bird species richness or the abundance of several bird species that were obligates of these wetlands. Bird assemblages in the western Great Lakes region spanned a wider range of wetland conditions than were reflected in the ORAM scores. Modification of ORAM scores with a focus on submetrics related to anthropogenic disturbance and vegetative structure improved the ability of ORAM to reflect conditions important to wetland birds. ORAM could be improved for use in the western Great Lakes with a greater emphasis on the landscape context and anthropogenic disturbance of the wetland.

Nest predation has been identified as the primary mechanism contributing to reduction of reproductive success for the marsh-breeding red-winged blackbird (Agelaius phoeniceus). Differences in rates of nest predation have been linked to nest site characteristics within a wetland, primarily water depth. However, the relationship between the landscape surrounding these habitats and the probability of nest predation is uncertain. Moreover, factors associated with reproductive success could be a potentially powerful indicator of ecological condition in wetland habitats. We investigated the influence of landscape pattern on nest success by monitoring 366 red-winged blackbird nests in 11 coastal wetlands along the south shore of Lake Superior. Of the 366 nests, 39% were successful, 56% failed, and 5% were abandoned or lacked sufficient evidence to determine nest fate. Nest predation accounted for over 93% of total failures. Predation rates ranged from 31% to 97% among the 11 wetland sites. We modeled nest predation using multi-model logistic regression analysis and the Akaike information criterion to identify and parameterize influential variables derived from the nest site, wetland, and landscape surrounding each wetland. Our results indicated that landscape variables comprised over 50% of model prediction weight in 15 of the 17 models. Nest failure was highest at sites within an urban/residential landscape matrix. Reproductive success could be a good indicator of the ecological health of Great Lakes wetlands.

Upland breeding bird communities were sampled from 225 points in 15 survey routes in the coastal region of western Lake Superior to examine relationships to human land use. Eighty-four species were detected and 50 were abundant enough to be included in data analysis. Monotonic quadratic regression models were constructed for these 50 species by using species counts as the dependent variable and the proportion of human conversion of the landscape (residential, agriculture, and commercial/industrial land uses) within each study area as the independent variable. Twenty-seven bird species had significant regressions (P < 0.05), 18 of which generally avoided areas developed by humans and 9 of which were attracted to development. Detrended correspondence analysis using counts of these 27 bird species was used to investigate multivariate, community responses to development. The first DCA axis was interpreted as a gradient from urban avoiding to urban exploiting bird species and was strongly correlated with land cover variables related to human development. Our results advance the idea that breeding bird communities can be used as indicators of ecological condition and can diagnose potential causes for changes in these conditions. Further, our study points out the usefulness of bird monitoring data in regional planning efforts that incorporate goals for maintaining native biological diversity.