Project description:This report provides a detailed set of historical stressor data for 60 watersheds comprising the Laurentian Great Lakes basin. Archival records were transcribed from public records to create quantitative data on human activities: population, mining, deforestation, and agriculture. Yearly records of stressors are provided from 1780 through 2010. These data may be used to track historical impacts on Great Lakes coastal and open water conditions. They may further be used to examine corresponding effects on response variables such as biological communities quantified during monitoring and palaeoecological programmes.Open practicesThis article has earned an Open Data badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.1594/PANGAEA.885879. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.
Project description:Cleanup of Great Lakes Areas of Concern (AOCs) restores environmental benefits to waterfront communities and is an essential condition for revitalization. We define waterfront revitalization as policies or actions in terrestrial waterfront or adjacent aquatic areas that promote improvements in human socioeconomic well-being while protecting or improving the natural capital (the stocks of natural assets, biodiversity) that underlies all environmental, social, and economic benefits. Except for economic measures such as development investments, visitation rates, or commercial activity, evidence of waterfront revitalization in the Great Lakes is mostly anecdotal. We offer a perspective on waterfront revitalization that links indicators and metrics of sustainable revitalization to community goals and human beneficiaries. We compiled environmental, social, economic, and governance indicators and metrics of revitalization, many of which are based on or inspired by Great Lakes AOC case studies and community reutilization or sustainability plans. We highlight the role of indicators in avoiding unintended consequences of revitalization including environmental degradation and social inequity. Revitalization indicators can be used in planning for comparing alternative designs, and to track restoration progress. The relevancy of specific indicators and metrics will always depend on the local context.
Project description:Relative valuation of potentially affected ecosystem benefits can increase the legitimacy and social acceptance of ecosystem restoration projects. As an alternative or supplement to traditional methods of deriving beneficiary preference, we downloaded from social media and classified ≈21,000 photographs taken in two Great Lakes Areas of Concern (AOC), the St. Louis River and the Milwaukee Estuary. Our motivating presumption was that the act of taking a photograph constitutes some measure of the photographer's individual preference for, or choice of, the depicted subject matter among myriad possible subject matter. Overall, 17% of photos downloaded from the photo-sharing sites Flickr, Instagram, and Panoramio depicted an ecosystem benefit of the AOC. Percent of photographs depicting a benefit and the photographs' subject matter varied between AOCs and among photo-sharing sites. Photos shared on Instagram were less user-gender biased than other photo-sharing sites and depicted active recreation (e.g., trail use) more frequently than passive recreation (e.g., landscape viewing). Local users shared more photos depicting a benefit than non-local users. The spatial distribution of photograph locations varied between photos depicting and not depicting a benefit, and identified areas within AOCs from which few photographs were shared. As a source of beneficiary preference information, we think Instagram has some advantages over the other photo-sharing sites. When combined with other information, spatially-explicit relative valuation derived from aggregate social preference can be translated into information and knowledge useful for Great Lakes restoration decision making.
Project description:Nutrient input to the Laurentian Great Lakes continues to cause problems with eutrophication. To reduce the extent and severity of these problems, target nutrient loads were established and Total Maximum Daily Loads are being developed for many tributaries. Without detailed loading information it is difficult to determine if the targets are being met and how to prioritize rehabilitation efforts. To help address these issues, SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were developed for estimating loads and sources of phosphorus (P) and nitrogen (N) from the United States (U.S.) portion of the Great Lakes, Upper Mississippi, Ohio, and Red River Basins. Results indicated that recent U.S. loadings to Lakes Michigan and Ontario are similar to those in the 1980s, whereas loadings to Lakes Superior, Huron, and Erie decreased. Highest loads were from tributaries with the largest watersheds, whereas highest yields were from areas with intense agriculture and large point sources of nutrients. Tributaries were ranked based on their relative loads and yields to each lake. Input from agricultural areas was a significant source of nutrients, contributing ∼33-44% of the P and ∼33-58% of the N, except for areas around Superior with little agriculture. Point sources were also significant, contributing ∼14-44% of the P and 13-34% of the N. Watersheds around Lake Erie contributed nutrients at the highest rate (similar to intensively farmed areas in the Midwest) because they have the largest nutrient inputs and highest delivery ratio.
Project description:Stakeholder participation is now widely viewed as an essential component of environmental management projects, but limited research investigates how practitioners perceive the major challenges and strategies for implementing high-quality participation. In order to address this gap, we present findings from a survey and interviews conducted with managers and advisory committee leaders in a case study of United States and binational (US and Canada) Great Lakes Areas of Concern. Our findings suggest that recruiting and integrating participants and sustaining participation over the long term present distinctive ongoing challenges that are not fully recognized in existing conceptualizations of the process of implementing participation. For example, it can be difficult to recruit active stakeholders to fill vacant "slots," to integrate distinctive interests and perspectives in decision-making processes, and to keep participants involved when activity is low and less visible. We present strategies that emerged in the survey and interviews for addressing these challenges, emphasizing the building and leveraging of relationships among stakeholders themselves. Such strategies include balancing tight networks with an openness to new members, supplementing formal hearings with social gatherings, making participation socially meaningful, and dividing labor between managers and advisory committees.
Project description:An international effort to restore contaminated areas across the Great Lakes has been underway for over 50 years. Although experts have increasingly recognized the inherent connections between ecological conditions and community level benefits, Great Lakes community revitalization continues to be a broad and complex topic, lacking a comprehensive definition. The purpose of this study was to generate a testable "AOC-Revitalization Framework" for linking remediation and restoration success, represented by Beneficial Use Impairment (BUI) removal in U.S. Great Lakes Areas of Concern (AOC), to community revitalization. Using directed content analysis, we conducted a literature review and identified 433 potential revitalization metrics and indicators and grouped them into 15 broader community revitalization attributes to develop the following definition of Great Lakes community revitalization: "locally driven community resurgence resulting in resilient and equitable enhancements to social, economic, and environmental community structures." We surveyed experts within the Great Lakes AOC program on the likelihood remediation and restoration success, would positively impact revitalization attributes. Focus groups triangulated survey results. Results identified BUI removal was expected to positively affect revitalization, but the type of revitalization outcome was based on the BUI being removed. The AOC-Revitalization Framework is the first to empirically outline these possible linkages, providing a clear testable structure for future research; it can be used to better understand how environmental improvements are or are not leading to community revitalization and more accurately identify components of revitalization impacted, thus supporting more equitable representation, communication, and measurement of the relationship.
Project description:The Great Lakes Areas of Concern (AOC) program was created through amendments to the Great Lakes Water Quality Agreement (GLWQA) in 1987 to restore contaminated sites using an ecosystem-based approach. This program represents one of the first instances of ecosystem-based management (EBM) in the Great Lakes region with a specific focus on the inclusion of the public and local stakeholders in the process. Despite official language incorporating EBM in the AOC program, implementation of these practices has not been consistent across AOCs given differences in local arrangements of Public Advisory Councils (PACs), approaches to community engagement, and environmental problems. To better understand community engagement in these complex AOCs, this research investigated community, PAC, and state agency perspectives in three AOCs in Michigan: the Kalamazoo River, Saginaw River and Bay, and Rouge River AOCs. We gathered data through interviews, focus groups, and participatory observations with community members, PAC members, and state officials in each AOC. Findings indicate that communities in these areas have minimal connection to the AOC program and PACs. Community members tended to have greater connection to local organizations that provide a variety of opportunities for community members to engage with their environment in ways they value. To better connect the public to the AOC program, PACs may benefit from intentional partnerships with community organizations to increase community engagement. To consistently bolster community engagement in AOCs, we further recommend that state agencies provide additional resources to improve connection to local communities.
Project description:Human activities introduce a variety of chemicals to the Laurentian Great Lakes including pesticides, pharmaceuticals, flame retardants, plasticizers, and solvents (collectively referred to as contaminants of emerging concern or CECs) potentially threatening the vitality of these valuable ecosystems. We conducted a basin-wide study to identify the presence of CECs and other chemicals of interest in 12 U.S. tributaries to the Laurentian Great Lakes during 2013 and 2014. A total of 292 surface-water and 80 sediment samples were collected and analyzed for approximately 200 chemicals. A total of 32 and 28 chemicals were detected in at least 30% of water and sediment samples, respectively. Concentrations ranged from 0.0284 (indole) to 72.2 (cholesterol) μg/L in water and 1.75 (diphenhydramine) to 20,800 μg/kg (fluoranthene) in sediment. Cluster analyses revealed chemicals that frequently co-occurred such as pharmaceuticals and flame retardants at sites receiving similar inputs such as wastewater treatment plant effluent. Comparison of environmental concentrations to water and sediment-quality benchmarks revealed that polycyclic aromatic hydrocarbon concentrations often exceeded benchmarks in both water and sediment. Additionally, bis(2-ethylhexyl) phthalate and dichlorvos concentrations exceeded water-quality benchmarks in several rivers. Results from this study can be used to understand organism exposure, prioritize river basins for future management efforts, and guide detailed assessments of factors influencing transport and fate of CECs in the Great Lakes Basin.
Project description:Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River located near Green Bay, WI, USA and the Milwaukee Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged at four sites within each AOC (eight sites total). Following 4d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4d composite water samples were collected concurrently at each caged fish site and analyzed for 132 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge in the Lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic activity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated by the lack of alterations in ex vivo steroid production, circulating steroid concentrations, or vitellogenin mRNA expression in males. Induction of hepatic cyp1a mRNA expression was detected at several sites, suggesting the presence of chemicals that activate the aryl hydrocarbon receptor. To expand the scope beyond targeted investigation of endpoints selected a priori, several bio-effects prediction approaches were employed to identify other potentially disturbed biological pathways and related chemical constituents that may warrant future monitoring at these sites. For example, several chemicals such as diethylphthalate and naphthalene, and genes and related pathways, such as cholinergic receptor muscarinic 3 (CHRM3), estrogen receptor alpha1 (esr1), chemokine ligand 10 protein (CXCL10), tumor protein p53 (p53), and monoamine oxidase B (Maob), were identified as candidates for future assessments at these AOCs. Overall, this study demonstrates that a better prioritization of contaminants and associated hazards can be achieved through integrated evaluation of multiple lines of evidence. Such prioritization can guide more comprehensive follow-up risk assessment efforts.
Project description:Today, many contaminants of emerging concern can be measured in waters across the United States, including the tributaries of the Great Lakes. However, just because the chemicals can be measured does not mean that they necessarily result in harm to fish and other aquatic species. Complicating risk assessment in these waters is the fact that aquatic species are encountering the chemicals as mixtures, which may have additive or synergistic risks that cannot be calculated using single chemical hazard and concentration-response information. We developed an in vitro effects-based screening approach to help us predict potential liver toxicity and cancer in aquatic organisms using water from specific Great Lakes tributaries: St. Louis River (MN), Bad River (WI), Fox River (WI), Manitowoc River (WI), Milwaukee River (WI), Indiana Harbor Canal (IN), St. Joseph River (MI), Grand River (MI), Clinton River (MI), River Rouge (MI), Maumee River (OH), Vermilion River (OH), Cuyahoga River (OH), Genesee River (NY), and Oswego River (NY). We exposed HepG2 cells for 48hrs to medium spiked with either field collected water (final concentration of environmental samples in the exposure medium were 75% of the field-collected water samples) or purified water. Using a deep neural network we clustered our collection sites from each tributary based on water chemistry. We also performed high throughput transcriptomics on the RNA obtained from the HepG2 cells. We used the transcriptomics data with our Bayesian Inferene for Sustance and Chemical Toxicity (BISCT) Bayesian Network for Steatosis to predict the probability of the field samples yielding a gene expression pattern consistent with predicting steatosis as an outcome. Surprisingly, we found that the probability of steatosis did not correspond to the surface water chemistry clustering. Our analysis suggests that chemical signatures are not informative in predicting biological effects. Furthermore, recent reports published after we obtained our samples, suggest that chemical levels in the sediment may be more relevant for predicting potential biological effects in the fish species developing tumors in the Great Lakes basin.