Ecosystem services in the Great Lakes

Feasibility of implementing an integrated long-term database to advance ecosystem-based management in the Laurentian Great Lakes basin

The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.

Potential risk of eutrophication in the deepest lake of Southwest China: Insights from phosphorus enrichment in bottom water

Large deep lakes in plateau regions provide crucial ecosystem services but are susceptible to eutrophication due to their long water residence time. To date, the water quality of deep lakes has not received as much attention as that of shallow lakes owing to logistical challenges. This study investigated the seasonal variation and vertical distribution of phosphorus and related environmental variables in a large deep lake in the Yunnan Plateau, China (Fuxian Lake). Generally, the concentrations of total phosphorus (TP, R² = 0.862), total dissolved phosphorus (TDP, R² = 0.922), and dissolved inorganic phosphorus (DIP, R² = 0.889) exhibited a linear increase with the greater water depth, whereas the pH and dissolved oxygen (DO) showed decreasing trends. The TP, TDP, and DIP values were 0.012, 0.006, and 0.004 mg/L, respectively, in surface waters (0.5 m depth), and increased to 0.074, 0.065, and 0.062 mg/L, respectively, at 140.0 m depth. The averaged over ordering method demonstrated that DO and air temperature accounted for a higher proportion of the explained variance of TP, TDP, and DIP in the shallow water layer (0.5-20.0 m). In contrast, DO and pH accounted for a higher proportion of the explained variance of TP, TDP, and DIP in deeper water layers (40.0-150.0 m). As a warm monomictic lake, the higher observed phosphorus concentrations in deeper water and sediment potentially pose a risk of future eutrophication in the Fuxian Lake. Our findings demonstrate that more efficient technical and management measures should be taken to reduce the external phosphorus load to Fuxian Lake, so that the load to and from the sediment will decrease eventually.

Identifying important ecosystem service areas based on distributions of ecosystem services in the Beijing-Tianjin-Hebei region, China

Water conservation, soil conservation, biodiversity importance, and sandstorm prevention are important ecosystem services (ES) and the core challenges to sustainable economic and societal development in the Beijing-Tianjin-Hebei (BTH) region. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and observation data, we identified high-value ES areas in the BTH region. The high-value ES areas were mainly found in the northern and southwestern parts of the region, like the Yanshan Mountain Range and the Taihang Mountain Range. The ecosystem in the northern mountains is dominated by forest and grassland, and generally provides more valuable ES than does the eastern agricultural plain. Greater species richness was mainly found in the northern mountains with low human activity intensity. Due to its proximity, the Yanshan Mountain Range is critical to the health of the local ecosystem of Beijing. High biodiversity was present in the vicinity of the national nature reserves. Compared with other regions of China, changes in the BTH region are highly intense. Reinforcement of biodiversity conservation and ecosystem restoration in areas with a high degree of ES in the BTH region are capable of effectively improving habitat quality and regional ES.

Gut Microbiota of Wild Fish as Reporters of Compromised Aquatic Environments Sleuthed through Machine Learning

Human-generated negative impacts on aquatic environments are rising. Despite wild fish playing a key role in aquatic ecologies and comprising a major global food source, physiological consequences of these impacts to them are poorly understood. Here we address the issue through the lens of interrelationship between wild fish and their gut microbiota, hypothesizing that fish microbiota are reporters of the aquatic environs. Two geographically separate teleost wild-fish species were studied (Lake Erie, Ohio and Caribbean Sea, US Virgin Islands). At each geo-location, fresh fecal samples were collected from fish in areas of presence or absence of known aquatic compromise. Gut microbiota was assessed via microbial 16S-rRNA gene sequencing and represents the first complete report for both fish species. Despite marked differences in geography, climate, water type, fish species, habitat, diet and gut microbial compositions, the pattern of shifts in microbiota shared by both fish species was nearly identical due to aquatic compromise. Next, these data were subjected to Machine Learning (ML) to examine reliability for using the fish-gut microbiota as an eco-marker for anthropogenic aquatic impacts. Independent of geo-location, ML predicted aquatic compromise with remarkable accuracy (>90%). Overall, this study represents the first multi-species stress-related comparison of its kind and demonstrates the potential of artificial intelligence via ML as a tool for bio-monitoring and detecting compromised aquatic conditions.

Temporal scope influences ecosystem driver-response relationships: A case study of Lake Erie with implications for ecosystem-based management

Understanding environmental driver-response relationships is critical to the implementation of effective ecosystem-based management. Ecosystems are often influenced by multiple drivers that operate on different timescales and may be nonstationary. In turn, contrasting views of ecosystem state and structure could arise depending on the temporal perspective of analysis. Further, assessment of multiple ecosystem components (e.g., biological indicators) may serve to identify different key drivers and connections. To explore how the timescale of analysis and data richness can influence the identification of driver-response relationships within a large, dynamic ecosystem, this study analyzed long-term (1969-2018) data from Lake Erie (USA-Canada). Data were compiled on multiple biological, physical, chemical, and socioeconomic components of the ecosystem to quantify trends and identify potential key drivers during multiple time intervals (20 to 50 years duration), using zooplankton, bird, and fish community metrics as indicators of ecosystem change. Concurrent temporal shifts of many variables occurred during the 1980s, but asynchronous dynamics were evident among indicator taxa. The strengths and rank orders of predictive drivers shifted among intervals and were sometimes taxon-specific. Drivers related to nutrient loading and lake trophic status were consistently strong predictors of temporal patterns for all indicators; however, within the longer intervals, measures of agricultural land use were the strongest predictors, whereas within shorter intervals, the stronger predictors were measures of tributary or in-lake nutrient concentrations. Physical drivers also tended to increase in predictive ability within shorter intervals. The results highlight how the time interval examined can filter influences of lower-frequency, slower drivers and higher-frequency, faster drivers. Understanding ecosystem change in support of ecosystem-based management requires consideration of both the temporal perspective of analysis and the chosen indicators, as both can influence which drivers are identified as most predictive of ecosystem trends at that timescale.

Synthesis of Two Decades of US EPA's Ecosystem Services Research to Inform Environmental, Community, and Sustainability Decision Making

A conceptual framework is helpful to understand what types of ecosystem services (ES) information is needed to support decision making. Principles of structured decision making are helpful for articulating how ES consideration can influence different elements in a given decision context resulting in changes to the environment, human health, and well-being. This article presents a holistic view of an ES framework, summarizing two decades of the US EPA's ES research, including recent advances in final ES, those ES that provide benefits directly to people. Approximately 150 peer-reviewed publications, technical reports, and book chapters characterize a large ES research portfolio. In introducing framework elements and the suite of relevant US EPA research for each element, both challenges and opportunities are identified. Lessons from research to advance each of the final ES elements can be useful for identifying gaps and future science needs. Ultimately, the goal of this article is to help the reader develop an operational understanding of the final ES conceptual framework, an understanding of the state of science for a number of ES elements, and an introduction to some ES tools, models, and frameworks that may be of use in their case-study applications or decision-making contexts.

Costs and benefits of automated high-frequency environmental monitoring - The case of lake water management

Freshwater lakes are dynamic ecosystems and provide multiple ecosystem services to humans. Sudden changes in lake environmental conditions such as cyanobacterial blooms can negatively impact lake usage. Automated high-frequency monitoring (AHFM) systems allow the detection of short-lived extreme and unpredictable events and enable lake managers to take mitigation actions earlier than if basing decisions on conventional monitoring programmes. In this study a cost-benefit approach was used to compare the costs of implementing and running an AHFM system with its potential benefits for three case study lakes. It was shown that AHFM can help avoid human health impacts, lost recreation opportunities, and revenue losses for livestock, aquaculture and agriculture as well as reputational damages for drinking water treatment. Our results showed that the largest benefits of AHFM can be expected in prevention of human health impacts and reputational damages. The potential benefits of AHFM, however, do not always outweigh installation and operation costs. While for Lake Kinneret (Israel) over a 10-year period, the depreciated total benefits are higher than the depreciated total costs, this is not the case for Lough Gara (Ireland). For Lake Mälaren in Sweden it would depend on the configuration of the AHFM system, as well as on how the benefits are calculated. In general, the higher the frequency and severity of changes in lake environmental conditions associated with detrimental consequences for humans and the higher the number of lake users, the more likely it is that the application of an AHFM system is financially viable.

Establishment of Regional Phytoremediation Buffer Systems for Ecological Restoration in the Great Lakes Basin, USA. I. Genotype × Environment Interactions

Poplar remediation systems are ideal for reducing runoff, cleaning groundwater, and delivering ecosystem services to the North American Great Lakes and globally. We used phyto-recurrent selection (PRS) to establish sixteen phytoremediation buffer systems (phyto buffers) (buffer groups: 2017 × 6; 2018 × 5; 2019 × 5) throughout the Lake Superior and Lake Michigan watersheds comprised of twelve PRS-selected clones each year. We tested for differences in genotypes, environments, and their interactions for health, height, diameter, and volume from ages one to four years. All trees had optimal health. Mean first-, second-, and third-year volume ranged from 71 ± 26 to 132 ± 39 cm3; 1440 ± 575 to 5765 ± 1132 cm3; and 8826 ± 2646 to 10,530 ± 2110 cm3, respectively. Fourth-year mean annual increment of 2017 buffer group trees ranged from 1.1 ± 0.7 to 7.8 ± 0.5 Mg ha−1 yr−1. We identified generalist varieties with superior establishment across a broad range of buffers (‘DM114’, ‘NC14106’, ‘99038022’, ‘99059016’) and specialist clones uniquely adapted to local soil and climate conditions (‘7300502’, ‘DN5’, ‘DN34’, ‘DN177’, ‘NM2’, ‘NM5’, ‘NM6’). Using generalists and specialists enhances the potential for phytoremediation best management practices that are geographically robust, being regionally designed yet globally relevant.

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave-current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria-sediment interactions, and bacteria-sand-sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria-sand-sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Are the shoreline and eutrophication of desert lakes related to desert development?

Desert lakes are unique ecosystems found in oases within desert landscapes. Despite the numerous studies on oases, there are no reports regarding the spatiotemporal distribution and causes of eutrophication in the desert lakes that are located at the edge of the Linze Oasis in northwestern China. In this study, the seasonal shoreline and eutrophication of a desert lake were monitored using an unmanned aerial vehicle (UAV) and water sampling during three crop growth stages. The spatial extents of the shoreline and algal blooms and the chromophoric dissolved organic matter (CDOM) absorption coefficient were derived through UAV images. The desert lake shoreline declined during the crop growing stage, which exhibited the largest water demand and began to expand after this stage. The estimated CDOM absorption coefficient measurements and classified algal bloom area showed seasonal variations that increased from spring to late summer and then decreased in autumn. The first two crop growth stages accounted for most of the water and fertilizer requirements of the entire growth period, which may have contributed to large amounts of groundwater consumption and pollution and resulted in peak eutrophication of the lake in the second growth stage. However, the CDOM absorption coefficient of the third stage was not well correlated with that of the first two stages, suggesting that the lake may be affected by the dual effects of groundwater and precipitation recharge in the third stage. These results indicate that the water quality of desert lakes may be affected by agricultural cultivation. The agricultural demands for water and fertilizer may change the spatiotemporal changes in water quality in the lake, especially in the middle and early stages of crop growth.

Applying best-worst scaling to rank ecosystem and economic benefits of restoration and conservation in the Great Lakes

Since 2010, over $2.4 billion in public funds have been invested in the cleanup and restoration of the Great Lakes Basin through the Great Lakes Restoration Initiative. Efforts have targeted restoration of Areas of Concern and other degraded sites. While the ecological benefits of Great Lakes restoration have been highlighted by the Environmental Protection Agency, and the economic benefits studied by the binational International Joint Commission, public preferences for Great Lakes conservation and restoration have not been well studied. Using best-worst scaling and a seven-preference choice set, 1,215 Basin residents quantitatively ranked their preferred reasons to restore and conserve Great Lakes shorelines and waterways, with a focus on restoration at Areas of Concern and National Park Service sites. The analysis shows the most preferred reason for restoration and conservation is to promote human health, followed by the protection of native species, and the prevention of new invasive species from entering the Great Lakes. The least preferred reason for restoration and conservation is to improve local property values. Although respondents' top reason was human-centered, respondents' preferred ecosystem conservation over the benefits of economic revitalization, recreational use, and improved property values. Preferences analyzed by gender, income, and home location followed these same rankings. Preferences for habitat restoration and the prevention of invasive species align with the focus areas guiding the Great Lakes Restoration Initiative, providing evidence of public support for this expansive, publicly funded restoration effort.

Goals, beneficiaries, and indicators of waterfront revitalization in Great Lakes Areas of Concern and coastal communities

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.

Estimating the economic costs of algal blooms in the Canadian Lake Erie Basin

Over the past two decades there has been a re-emergence of regular harmful algal blooms in Lake Erie due to increasing phosphorus loading, mainly from non-point agricultural sources. The Canadian and United States governments have jointly agreed to reduce phosphorus loadings to the lake in order to control the extent and severity of the blooms. Citizens on both sides of the border face a number of economic costs, both market and non-market, as a result of the blooms. This study values these costs for the Canadian portion of the Lake Erie basin economy using standard economic approaches that are widely applied within the world of cost-benefit analysis. The results suggest that algal blooms will impose equivalent annual costs equal to $272 million in 2015 prices over a 30-year period if left unchecked. The largest market costs will be imposed on the tourism industry ($110 million in equivalent annual costs) and the largest non-market costs will be borne by recreational users and those who place inherent value on the lake's quality ($115 million in equivalent annual costs). Management action to reduce phosphorus loadings is found to be justified on economic grounds if the 30-year net present value of the reduction program is less than $1294 million (2015 Canadian dollars).

Bacterial Community 16S rRNA Gene Sequencing Characterizes Riverine Microbial Impact on Lake Michigan

Restoration of degraded aquatic habitats is critical to preserve and maintain ecosystem processes and economic viability. Effective restoration requires contaminant sources identification. Microbial communities are increasingly used to characterize fecal contamination sources. The objective was to determine whether nearshore and adjacent beach bacterial contamination originated from the Grand Calumet River, a highly urbanized aquatic ecosystem, and to determine if there were correlations between pathogens/feces associated bacteria in any of the samples to counts of the pathogen indicator species Escherichia coli. Water samples were collected from the river, river mouth, nearshore, and offshore sites along southern Lake Michigan. Comparisons among communities were made using beta diversity distances (weighted and unweighted Unifrac, and Bray Curtis) and Principal Coordinate Analysis of 16S rRNA gene Illumina sequence data that indicated river bacterial communities differed significantly from the river mouth, nearshore lake, and offshore lake samples. These differences were further supported using Source Tracker software that indicated nearshore lake communities differed significantly from river and offshore samples. Among locations, there was separation by sampling date that was associated with environmental factors (e.g., water and air temperature, water turbidity). Although about half the genera (48.1%) were common to all sampling sites, linear discriminant analysis effect size indicated there were several taxa that differed significantly among sites; there were significant positive correlations of feces-associated genera with E. coli most probable numbers. Results collectively highlight that understanding microbial communities, rather than relying solely on select fecal indicators with uncertain origin, are more useful for developing strategies to restore degraded aquatic habitats.

Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media

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.