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Research about Indiana

Source-linked reports with geographic coverage including Indiana.

At least 19 recordsLinked to original sources
USGS2026

Groundwater nutrient contributions to surface water in the upper Maumee River basin

Harmful algal blooms triggered by nutrient loading have negatively affected Lake Erie water quality for decades, but the role groundwater plays in transporting nutrients to tributary streams is unclear. Here, we apply a multi-scale approach to investigate groundwater nitrogen (N) and phosphorus (P) dynamics at the field scale, along a groundwater flow path, and at the Maumee River basin scale. Unsaturated zone monitoring indicates that macropore flow is the primary mechanism for N and P leaching with nitrate and orthophosphate (OP) concentrations from macropore samplers more than double those from soil-matrix samplers. Shallow (< 4.5 m) groundwater nitrate concentrations indicate the timing of saturated-zone nitrate fluxes is crop dependent with more nitrate mobilized during the maize growing season whereas concentrations below soybeans can remain elevated (> 3 mg/L) through winter months. A three-end-member hydrograph analysis for the upper Maumee River basin indicates that tile drains transport most subsurface N and P with greater than 15,000 kg per day of nitrate transported between January and May. Orthophosphate concentrations in tile drainage at an edge-of-field site correlate well with concentrations in a nearby tributary of the Maumee River. While runoff is the dominant source of OP loading, tile drainage and groundwater discharge contributed an estimated 36% of OP load during a 2018–2022 analysis period with most subsurface loading occurring between January and March. These findings highlight how best management practices (such as cover crops and tile drainage control structures) can be used to help limit leaching and tile effluent during the nongrowing season.

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USGS2026

Water in, no water out—How a rain garden reduced stormwater at City Hall in Gary, Indiana

Introduction Urban stormwater runoff can be an issue in many communities because it may cause flooding, overwhelm sewage treatment plants, and negatively affect water quality in local streams, lakes, and other waterbodies. Stormwater runoff can be controlled by using "green infrastructure," which consists of engineered structures that imitate nature to collect stormwater runoff, reduce the amount of runoff, and improve water quality. In 2014, the city of Gary, Indiana implemented green infrastructure to reduce the negative effects of urban stormwater on Lake Michigan and its tributaries. From November 2016 to June 2017, the mostly impermeable parking lot in front of Gary City Hall was removed and rebuilt with a rain garden. The U.S. Geological Survey studied how the rain garden reduced stormwater runoff and published results in Scientific Investigations Report 2022–5101.

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USGS2026

3D Elevation Program—Indiana

Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.

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USGS2026

Topography-aware registration refinement of Landsat 8/9 L1TP products with Sentinel-2 L1C and NAIP orthoimages

Satellite orthoimage products are widely available, yet residual geometric misregistration across independently processed products remains common, limiting their direct interoperability for multi-source and multi-temporal analysis. This paper introduces a residual Multi-Layer Perceptron (MLP)–based, topography-aware framework to further increase the registration quality of existing orthoimages based on dense matching without requiring any sensor-specific metadata or physical imaging parameters. We evaluate our approach by precisely co-registering 26 Landsat 8/9 Collection 2 Level-1 Terrain Precision (L1TP) scenes across Indiana (USA) and Berlin (Germany) with Sentinel-2 L1C and National Agriculture Imagery Program (NAIP) orthoimages. The baseline Landsat misregistration to Sentinel-2 or NAIP typically ranges from 3 to 10 m, which is reduced to 2–4 m after applying our MLP-based refinement, outperforming conventional polynomial and Rational Polynomial Coefficient (RPC) models. Further empirical evaluation demonstrates that consistent registration precision can be achieved across various terrain datasets; specifically, 30 m global digital elevation models (DEMs) yield comparable performance to that of high resolution (1–10 m) national or regional DEMs. The developed MLP approach provides a precise and reliable framework that transcends Landsat-specific tasks. It is readily adaptable to other registration applications requiring high-fidelity geometric alignment and consistent integration of heterogeneous image sources.

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USGS2026

Variability of discharge, nutrients, and Escherichia coli from tile drains in a small agricultural stream, a synoptic study in the School Branch watershed, Hendricks County, Indiana

The U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, sampled a 1-mile stream reach of School Branch in Hendricks County, Indiana. Sampling consisted of 24 tile drain sites and surface-water sites both upstream and downstream from the tile drains. This study intended to (1) assess the variability of discharge, nutrients, and Escherichia coli ( E. coli ) among tiles within a stream reach in variable conditions; (2) define how the tiles affect the stream hydrology and water quality; and (3) determine potential management implications. Samples were collected on three dates—round 1 on June 12, 2018, after fertilizer was applied; round 2 on September 11, 2018, in fall harvest conditions; and round 3 on April 16, 2019, before fertilizer was applied—to encompass differing precipitation events, multiple seasons, and field conditions. Sites were sampled for water-quality parameters, dissolved and total nutrients (ammonia, nitrate plus nitrite, total nitrogen, orthophosphate, and total phosphorus), E. coli , and instantaneous discharge. Instantaneous nutrient loads were calculated from tiles and at the upstream and downstream surface-water sites. Nutrient concentrations and instantaneous loads varied depending on the tile and the sampling date. Tiles contributed between 26.5 and 66.0 percent of increased discharge between the surface-water sites. Tiles contributed between 34.7 and 87.4 percent and between 19.7 and 65.9 percent of the increased total nitrogen and phosphorus loads, respectively, for the downstream site relative to the upstream site. Most of the total nitrogen and total phosphorus from the tiles was in the dissolved forms (nitrate plus nitrite and orthophosphate). Surface-water samples had a nitrate plus nitrite to total nitrogen ratio of 71 to 93 percent, with an average of 82 percent; tile samples ranged from 44 to nearly 100 percent, with an average of 91 percent dissolved nitrogen. Surface-water samples had an orthophosphate to total phosphorus ratio of 30 to 65 percent, with an average of 53 percent; tile samples ranged from 32 to nearly 100 percent, with an average of 85 percent dissolved phosphorus. E. coli was detected in all but 5.79 percent of tile and surface-water samples. The E. coli results indicated the possibility of human or animal fecal contamination by way of septic systems leaking or directly linked to the tiles draining into the study area. Consequently, five microbial source tracking samples were collected from the upstream and downstream surface-water sites between August 3, 2021, and May 18, 2022. Human, canine, ruminant, and avian sources of fecal contamination were evaluated. The microbial source tracking samples indicated that human-specific sources are likely consistently contributing to elevated fecal contamination. Differences in discharge, nutrient concentrations, nutrient loads, and E. coli concentrations show that many factors affect how tiles alter the hydrology and water quality of receiving waters. The timing and severity of precipitation events, season, and the antecedent conditions of the field or watershed before sampling can affect the results. Tiles with the largest discharge rate had the most potential effect on the water quality and quantity of the stream. Targeting high-flowing tiles may affect efforts to improve overall water quality.

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USGS2026

Evaluation of a eutrophication Beneficial Use Impairment in the Grand Calumet River Area of Concern in northwest Indiana, 2021–22

Eutrophication has been regularly documented in the Grand Calumet River and Indiana Harbor Canal in northwest Indiana. The area has undergone various remediation efforts since the development of a Remedial Action Plan for the area in response to a 1987 amendment to the Great Lakes Water Quality Agreement of 1978 between the United States and Canada and the designation of the Grand Calumet River Area of Concern by the U.S. Environmental Protection Agency. To address concerns of eutrophication and its effects, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the Indiana Department of Environmental Management, collected data from the Grand Calumet River and Indiana Harbor Canal in 2021 and 2022 to document the effects of remediation and combined sewer overflow releases on water quality. This study used continuous monitors to collect real time data for dissolved oxygen, water temperature, chlorophyll fluorescence, specific conductance, and pH. Discrete sample analysis included biological oxygen demand, chemical oxygen demand, nutrients, nitrogen and oxygen isotopes in nitrate, nitrogen isotopes in ammonia, hydrogen and oxygen isotopes in water, and identification of algal communities (cyanobacteria and eukaryotic algae) by metabarcoding. Eutrophic conditions were found throughout the area. Isotopic results indicated the source of nitrate in samples was either from soil organic nitrogen or combined sewer overflows. Combined sewer overflows were shown to have considerable effects on the sites, and remediation status did not have a great effect. Algal community results identified several taxa capable of becoming nuisance species, including Microcystaceae (cyanobacteria) and Chrysophyceae, Cryptophyceae, and Bacillariophyceae (all eukaryotic algae). When sites with irregular flow patterns were excluded from datasets, minimum dissolved oxygen concentrations were often higher downstream from remediated sites than from unremediated sites. This study shows the potential for further and more targeted exploration into the unusual conditions found throughout the Grand Calumet River and Indiana Harbor Canal area.

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USGS2025

The interface between rare plant management and genetics: Conserving Pitcher’s thistle (Cirsium pitcheri) in the Great Lakes region, USA

Background and Aims Tools showing best conservation practices are becoming critical for rare plant conservation as populations become isolated through habitat fragmentation and changing ecosystem processes. We illustrate the importance of reintroduction and assisted gene flow, using reintroduction of the USA federally threatened Pitcher’s thistle ( Cirsium pitcheri ), a monocarpic perennial endemic to the western Great Lakes sand dunes. We evaluate the success of experimental reintroductions of this species into its dynamic coastal environment and address fundamental issues for rare plant reintroduction, including questions of maintenance of genetic diversity, founder size, introduction methods and assisted gene flow effectiveness. Methods In 1994 we initiated experimental reintroductions at three new locations along a habitat successional gradient using 4200 seeds collected from 54 maternal lines. At each site, seed sources were distributed among replicate blocks that were split by sowing method (sowing vs broadcasting) to examine establishment success. We monitored population demography for 30 years, assessing genetic variation in 2009 and regionally from 1997 to 2014. Key Results Two of three populations persisted for 30 years from a single-seeding founder event. Reintroduction populations had greater expected heterozygosity than regional native populations. Despite persistence, moderate inbreeding coefficients showed that reintroduction populations have not achieved an effective size to reduce the likelihood of inbreeding depression. However, the mid-successional reintroduction had the lowest kinship of all populations sampled, indicating a healthy restoration. Seed sowing produced three times as many seedlings as broadcasting, but seed source did not affect germination success. Persistence has been facilitated by local migration to suitable habitat patches, an important metapopulation process. Conclusions Seeds can be an effective method for reintroducing monocarpic plants in high-quality habitats. However, low numbers of reproductive adults and moderate inbreeding illustrate the need for repeated additions of plants or seed to reduce inbreeding to improve rare plant genetic evolutionary potential.

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USGS2025

A comparison of ground flora sampling methods to assess recovery of bottomland forest restorations

We compared ground flora sampling methods for assessing the state of multiple bottomland forest restorations 6–21 years after restoration implementation in northeast Indiana, United States. Data from standard fixed-area plots of appropriate size and complexity for forest assessments were compared with data from smaller fixed-area plots of different shapes and plotless sampling methods. The methods were compared for their ability to (1) assess species richness and abundance, (2) detect and monitor invasive and dominant species, and (3) understand community composition. We assessed the biases of the compared methods, identified the training and skills needed to conduct sampling, and examined sampling costs in relation to total monitoring costs. Results show that smaller plots are able to detect more species per unit area sampled without significant differences in floristic quality measures. Data from smaller plots were sufficient for comprehensively describing site conditions even when less of the total site area was sampled. Although multivariate analyses of data from smaller plots yielded greater within-group dissimilarity than data from larger plots, multiple response permutation procedure analyses indicated no significant differences between nonmetric multidimensional scaling solutions based on data from the different sampling methods. Regardless of the sampling methods used to collect data, use of multivariate analyses identified a gradient of time since restoration was implemented as the dominant factor relating to differences between community composition. Sampling costs spanned a range of one order of magnitude but generally represented less than 6% of total assessment costs. Results suggest that when selecting sampling methods, matching monitoring effort to specific measurable management endpoints is more important than sampling cost.

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USGS2025

Increased soil greenhouse gas emissions from the combined use of cover crops and no‐tillage in producer‐ managed fields

Cover crop adoption offers multiple benefits and climate mitigation potential for agroecosystems, but is still an underutilized conservation practice. Recently, the combined use of cover cropping plus no-tillage (CCNT) has been increasingly promoted to achieve its synergistic effectiveness. Yet, how this combined practice affects soil greenhouse gas (GHG) emission remains a topic of debate. Existing studies are predominantly based on research-managed settings and often fail to assess all three major GHGs of carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ). To address these knowledge gaps, this study conducted a 30-month monitoring from producer-managed fields to quantify the soil greenhouse gas responses to CCNT compared to no-tillage (NT) alone. The findings showed that CCNT increased the soil global warming potential (GWP) by 15.2% relative to NT. CO 2 is the main contributor, accounting for over 91.7% of the total GWP. On average, the daily fluxes of CO 2 , N 2 O, and CH 4 were increased by 16.2%, 32.3%, and 55.6% under CCNT, respectively. Meteorological variables explained 85.3% of the CO 2 increase and 46.1% of the N 2 O increase associated with CCNT. Furthermore, two types of CCNT practices differed in GHG emission responses, though both strategies significantly reduced nitrogen losses. These quantitative results, derived from actual production systems, provide informed decision-making among local producers regarding the adoption of cover crops. Moreover, this field-based evidence offers a robust empirical foundation for future modeling efforts aimed at assessing the ecological benefits of cover crops under varying climatic and soil conditions.

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USGS2025

Bacterial community structure across a sand dune chronosequence at the Indiana Dunes National Park

The microbial role in dune succession along the Great Lakes freshwater sand dunes remains poorly understood. A chronosequence study was conducted to understand the relationships among soil bacterial communities, soil chemistry, and prescribed burning at the Indiana Dunes National Park. Soil bacterial communities and chemistry, as well as groundlayer vegetation were sampled during 2015 and 2017 from seven successional stages from the beach (contemporary) to the 14,000-year-old oak forest. Bacterial communities from unburned and burned sites among stages were determined by 16S rRNA gene amplicon sequencing. Soil pH and cations decreased from early (beach, foredune, secondary dune, and woodland transition) to late (oak savanna, woodland, and oak forest) successional stages, while organic matter and organic carbon concentrations increased in the late successional stages. Bacterial alpha diversity showed no significant differences among stages, but a significant interaction was found between stage and prescribed burning (H = 39.7, p < 0.001). Bacterial communities separated mainly along stage by all four beta diversity metrics used (Bray Curtis, Jaccard, and Weighted and Unweighted UniFrac), with the main difference observed along the primary axis (weighted UniFrac, 48 %). Bacterial phyla were differentially abundant in older soil stages compared to beach (ANCOM-BC, q < 0.05); likewise, differential abundances in genera were evident when burned and unburned sites were compared. A Mantel test indicated stronger congruency between the bacterial communities and soil chemistry than between bacterial communities and vegetation. Collectively, soil chemical and microbial parameters along with management practices contribute to dunal successional patterns in the Great Lakes.

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USGS2025

Road salt collection and redistribution at an urban rain garden on sandy soil, Gary, Indiana

Rain gardens installed as green infrastructure to divert storm runoff from entering combined sewers also collect dissolved constituents and particulates. An urban rain garden in northwestern Indiana, USA, was continuously monitored from November 2019 to May 2021 to evaluate the fate of dissolved constituents entering the rain garden in runoff. Physical and chemical properties of soils in the rain garden were also monitored, along with underlying groundwater. Linear regression models relating specific conductance to chloride concentration indicated that the 0.0371-ha (3998 square feet) rain garden collected approximately 1490 kg (3285 pounds) of road salt from the surrounding 0.2228 ha (24,500 square feet) of impervious surfaces. Soils and groundwater were seasonally affected by road salt application but carryover from year to year was not indicated. Rain garden soil permeability (5.20 × 10 −5 to 9.72 × 10 −5 m/s) remained unchanged during the study period and soil organic carbon generally increased under native vegetation. The results suggest that a rain garden built on sandy soil can divert substantial quantities of runoff and dissolved constituents from combined sewers; however, chloride is transported to sub-infrastructure groundwater that eventually discharges to adjacent waterways with concentrations lower than those observed in runoff.

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USGS2024

Survey effort and targeted landbird community metrics at Indiana lowland forest restoration sites

Many sampling and analytical methods can estimate the abundance, distributions, and diversity of birds and other wildlife. However, challenges with sample size and analytical capacity can make these methods difficult to implement for resource-limited monitoring programs. To apprise efficient and attainable sampling designs for landbird monitoring programs with limited observational data, we used breeding season bird point survey data collected in 2016 at four forest restoration sites in Indiana, USA. We evaluated three subsets of observed species richness, total possibly breeding landbirds, Partners in Flight Regional Conservation Concern (PIF RCC) landbirds, and interior forest specialists (IFSs). Simulated surveys based on field data were used to conduct Bayesian Michaelis–Menten curve analyses estimating observed species as a function of sampling effort. On comparing simulated survey sets with multiple habitat types versus those with one habitat, we found that those with multiple habitat types had estimated 39%–83% greater observed PIF RCC species richness and required 41%–55% fewer visits per point to observe an equivalent proportion of PIF RCC species. Even with multiple habitats in a survey set, the number of visits per point required to detect 50% of observable species was 30% higher for PIF RCC species than for total breeding landbird species. Low detection rates of IFS species at two field sites made precise estimation of required effort to observe these species difficult. However, qualitatively, we found that only sites containing mature forest fragments had detections of several bird species designated as high-confidence IFS species. Our results suggest that deriving specialized species diversity metrics from point survey data can add value when interpreting those data. Additionally, designing studies to collect these metrics may require explicitly planning to visit multiple habitat types at a monitoring site and increasing the number of visits per survey point.

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USGS2024

Vegetation community recovery on restored bottomland hardwood forests in northeast Indiana, USA

Vegetation communities in restored bottomland hardwood forests in northeast Indiana were studied 6–21 years after restoration to assess progress toward restoration objectives. The study focused on four sites that were restored to compensate for resource injuries after contaminant releases. The restored sites were compared with four reference-site conditions, including crops (prerestoration condition), old field communities representing a no-management alternative, locally sampled second-growth mature forests, and forest community types described by the US National Vegetation Classification (USNVC), which represent ideal or defining conditions of recognized vegetation communities. Fixed-area plots provided data on field-sampled environmental variables, vegetation, soil, and hydrological conditions for crops, old fields, restored areas, and mature forests. The USNVC database provided quantitative data for three historically and geographically relevant reference forest community types for comparison with the sampled communities. Results of nonmetric multidimensional scaling based on species cover revealed clear gradients relating to site age and canopy development. Along those gradients, restored areas demonstrated increasing similarity to mature forest reference communities in terms of floristic composition. Specifically, the floristic quality of restored areas was significantly greater than that of crops and old fields. Furthermore, soil health measurements of physical, chemical, and hydrological conditions indicated significant improvements in restored site soils compared with prerestoration conditions represented by cropland soils. Descriptions and data from the USNVC provided ecological context for restoration target conditions and facilitated the assessment of restoration recovery along a trajectory from starting conditions to those target conditions. Descriptions by USNVC also helped identify deviations from the intended restoration objectives (e.g., invasive species recruitment) and potential adaptive management actions to return sites to their intended trajectories. Integr Environ Assess Manag 2024;00:1–22. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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USGS2024

Hydrology and water quality of a dune-and-swale wetland adjacent to the Grand Calumet River, Indiana, 2019–22

Adverse ecological and water-quality effects associated with industrial land-use changes are common for littoral wetlands connected to river mouth ecosystems in the Grand Calumet River-Indiana Harbor Canal Area of Concern. These effects can be exacerbated by recent high Lake Michigan water levels that are problematic for wetland restoration. Wetlands in the adjacent Clark and Pine Nature Preserve and Pine Station Nature Preserve are intended to mitigate wetland destruction in the area of concern by restoring residual dune-and-swale wetlands and preserving habitat for endangered and threatened plant species. Physical hydrology and water-quality monitoring of restored wetland cells at the preserves were initiated during 2019 to evaluate changes after wetland restoration efforts in 2015 and near record-low water levels in early 2013. Lake Michigan water levels rose steadily between late 2013 and 2018 to record-high water levels in 2019 and 2020. In this report, precipitation, evapotranspiration, and groundwater and surface-water levels are analyzed to better understand wetland inundation controls and flow directions in restored northern dune-and-swale wetland settings relative to the Grand Calumet River. Continuous specific conductance data and discrete water-quality samples were collected and analyzed to provide a synoptic view of water quality for the restored wetlands. High Lake Michigan water levels affected Grand Calumet River stage and shallow groundwater elevations in the study area after the onset of peak lake levels in June 2019, that persisted through summer 2020, before finally receding in September 2020. Grand Calumet River stage peaked soon after lake levels in July 2019, whereas groundwater elevations in the study area peaked in October 2019. Specific conductance values in closed-basin wetland cells in the western and central parts of the nature preserves indicated a dilution trend and contrasted those of interconnected wetland cells along an eastern corridor, where alterations to wetland cells were more pronounced. Monitoring results indicate that varying seasonal wetland inundation trends with low stands in autumn have returned after high water table conditions owing to high water levels on Lake Michigan. Wetland water balance results during the study period indicated that the wetland ecosystem partially moderated flooding during high lake levels through summer evapotranspiration.

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USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

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USGS2023

Comparison of turbidity sensors at U.S. Geological Survey supergages in Indiana from November 2018 to December 2021

Beginning in September 2010, the U.S. Geological Survey installed continuous water-quality monitors at several streamgages across Indiana as part of a network of supergages to meet cooperator information needs. Two types (or models) of water-quality monitors deployed at each site measured and recorded water temperature, dissolved oxygen, specific conductance, pH, and turbidity every 15 minutes during the study period. Associated discrete water samples were collected at regular intervals and analyzed for concentrations of suspended sediment and total phosphorus. Surrogate regression models were developed between the continuously measured turbidity values and turbidity values in the associated samples to compute continuous concentrations and loads of suspended sediment and total phosphorus. Starting in November 2018, the original extended deployment system monitors were replaced with the newest model of multiparameter water-quality monitors and were equipped with turbidity smart sensors because the older monitors were phased out of production. The updated monitor and smart sensor yield different but relatable turbidity values. Turbidity data collected concurrently by the two sensors from November 2018 to December 2021 were compared and analyzed to quantify the relation between them at six supergage sites in northwestern Indiana and one site in the town of Zionsville in central Indiana. Ordinary least squares regression was used to calculate site-specific conversion factors so that turbidity data from the newer monitors can be used in published surrogate models based on the older monitor data. Regression analyses explained approximately 98 percent of the variation in turbidity readings between the two sensors. From these analyses, conversion factors were developed that may be applied to older turbidity readings to calculate near real-time concentrations of phosphorus and suspended sediment.

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USGS2023

Targeted metabolomics characterizes metabolite occurrence and variability in stable freshwater mussel populations

Freshwater mussels (order Unionida) play a key role in freshwater systems as ecosystem engineers and indicators of aquatic ecosystem health. The fauna is globally imperilled due to a diversity of suspected factors; however, causes for many population declines and mortality events remain unconfirmed due partly to limited health assessment tools. Mussel-monitoring activities often rely on population-level measurements, such as abundance and age structure, which reflect delayed responses to environmental conditions. Measures of organismal health would enable preemptive detection of declining condition before population-level effects manifest. Metabolomic analysis can identify shifts in biochemical pathways in response to stressors and changing environmental conditions; however, interpretation of the results requires information on inherent variability of metabolite concentrations in mussel populations. We targeted metabolites in the haemolymph of two common mussels, Lampsilis cardium and Lampsilis siliquoidea , from three Indiana streams (USA) using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectroscopy. The influence of species, stream and sex on metabolite variability was examined with distance-based redundancy analysis. Metabolite variability was most influenced by species, followed by site and sex. Inter- and intraspecies metabolite variability among sexes was less distinct than differences among locations. We further categorized metabolites by occurrence and variability in mussel populations. Metabolites with high occurrence (Categories 1 and 2) included those indicative of energy status (catabolism versus anabolism; arginine, proline, carnitine, nicotinic acid, pantothenic acid), oxidative stress (proline, glutamine, glutamate) and protein metabolism (thymidine, cytidine, inosine). Metabolites with lower occurrence (Category 3) are constituents of assorted metabolic pathways and can be important biomarkers with additional temporal sampling to characterize their variability. These data provide a reference for future temporal (before/after) monitoring and for studies of stressor–metabolite linkages in freshwater mussels.

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