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Per- and Polyfluoroalkyl substances (PFAS) have been widely used in various industries, including pesticide production, electroplating, packaging, paper making, and the manufacturing of water-resistant clothes. This study investigates the levels of PFAS in fish tissues collected from four target waterways (15 sampling points) in the northwestern part of Illinois during 2021-2022. To assess accumulation, concentrations of 17 PFAS compounds were evaluated in nine fish species to potentially inform on exposure risks to local sport fishing population via fish consumption. At least four PFAS (PFHxA, PFHxS, PFOS, and PFBS) were detected at each sampling site. The highest concentrations of PFAS were consistently found in samples from the Rock River, particularly in areas near urban and industrial activities. PFHxA emerged as the most accumulated PFAS in the year 2022, while PFBS and PFOS dominated in 2021. Channel Catfish exhibited the highest PFAS content across different fish species, indicating its bioaccumulation potential across the food chain. Elevated levels of PFOS were observed in nearly all fish, indicating the need for careful consideration of fish consumption. Additional bioaccumulation data in the future years is needed to shed light on the sources and PFAS accumulation potential in aquatic wildlife in relation to exposures for potential health risk assessment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Extensive tile drainage usage combined with excess nitrogen fertilization has triggered nutrient loss and water quality issues in Illinois, which over time endorsed the hypoxia formation in the Gulf of Mexico. Past research reported that the use of cereal rye as a winter cover crop (CC) could be beneficial in reducing nutrient loss and improving water quality. The extensive use of CC may aid in reducing the hypoxic zone in the Gulf of Mexico. The objective of this study is to analyze the long-term impact of cereal rye on soil water‑nitrogen (N) dynamics and cash crops growth in the maize-soybean agroecosystem in the state of Illinois. A gridded simulation approach was developed using the DSSAT model for the CC impact analysis. The CC impacts were estimated for the last two decades (2001-2020) for two fertilization scheduling (FA-SD = Fall and side-dress N and SP-SD = Spring pre-plant and side-dress N) comparing between CC scenario (FA-SD-C/SP-SD-C) with no CC (NCC) scenario (FA-SD-N/SP-SD-N). Our results suggest that the nitrate-N loss (via tile flow) and leaching reduced by 30.6 % and 29.4 %, assuming extensive adaptation of cover crop. The tile flow and deep percolation decreased by 20.8 % and 5.3 %, respectively, due to cereal rye inclusion. The model performance was relatively poor in simulating the CC impact on soil water dynamics in the hilly topography of southern Illinois. Generalizing changes in the soil properties (due to cereal rye inclusion) from the field scale to whole state (regardless of soil type) could be one of the possible limitations in this research. Overall, these findings substantiated the long-term benefits of cereal rye as a winter cover crop and found the spring N fertilizer application reduced nitrate-N loss compared to fall N application. These results could be helpful in promoting the practice in the Upper Mississippi River basin., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Side channels in large floodplain rivers serve a variety of important ecological roles, particularly in reaches where habitat conditions have been degraded or diminished. We developed hypotheses regarding side channel ecological structure whereby we expected species richness of young-of-year fishes to generally be higher in shallower, more physically heterogeneous side channels with lower velocities, with differences based on reproductive guild. We also hypothesized species richness of adult fishes to be higher in side channels with greater heterogeneity that could support diverse foraging resources and provide refugia during extreme flow conditions. To test these hypotheses, we used a 28-year fish community dataset from the Upper Mississippi and Illinois Rivers. Across six study reaches, we assessed metrics of side channel physical size, heterogeneity, and connectivity that were hypothesized to explain variance of fish community response, while accounting for site-level factors across 52 side channels using multilevel models. We then used these side channel-level characteristics in a K-means cluster analysis to classify 1126 side channels across 32 reaches of the river system. Our results indicated that the relative explanatory contributions of physical metrics varied by response variable, providing varying evidence in support of our hypotheses, and indicating that different forms of heterogeneity matter in different ways. Side channel-level factors were more explanatory of fish community responses in side channels of upstream reaches compared to downstream reaches and percent wet forest was the most explanatory side channel-level factor of fish community responses across all models. Our classification of side channels indicated strong spatial contrasts in the abundance and diversity of side channels across reaches. Scaling up to understand how the diversity and abundance of different types of side channels contributes to landscape-scale ecological functions and processes would be useful for establishing targets for reach-scale physical heterogeneity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Quantifying spatiotemporal dynamics of soil organic carbon (SOC) stocks is needed to understand the impact of land use change and can help target carbon sequestration efforts. In the recently and radically transformed landscapes of the state of Illinois, U.S.A., we evaluated surface SOC stocks under land use change using a space-for-time substitution method over 167 years. Additionally, we determined SOC stocks for the A horizon vs 0-30 cm depth to evaluate pedogenically-informed vs more commonly used fixed depth approaches. Legacy soil datasets from 1980 to 2012 were combined with environmental covariates using a random forest algorithm. To more accurately estimate pre-agricultural land use SOC stocks (i.e., pre-1845), SOC observations collected from soils under native prairie and forest were extracted from peer-reviewed publications. The model was validated on 25 % of the total 627 test data (R A-hor 2 : 0.59 and R 0-30 2 : 0.56; RMSE A-hor : 20.5 and RMSE 0-30 :19.3 Mg/ha) independent of the 75 % of data for calibration (R 2 :9.6 Mg/ha). SOC stocks were largest under prairie (A horizon: 156.1 Mg/ha; 0-30 cm: 152.4 Mg/ha) and lowest under pasture (A horizon: 33.2, 0-30 cm: 44.6 Mg/ha). SOC stocks varied less by soil order than by land use. Between 1845 and 2012, surface SOC stocks decreased for most of Illinois, with greatest losses in central (-16.3 Mg/ha) and east-central Illinois (-47.0 Mg/ha) where approximately 80 % of prairie was converted to cropland. A slight increase in surface SOC stocks occurred in the unglaciated northwest region and the less recently glaciated south region, as well as in alluvial corridors. This study (i) highlights how estimating spatiotemporal dynamics of surface SOC stocks over centennial timescales can benefit from including measures of SOC under native land use not usually contained in legacy pedon datasets, and (ii) illustrates the potential of identifying localized hotspots of historical SOC loss and thus deficits that can be prioritized for carbon sequestration efforts.A-hor :10.1 and RMSE 0-30 :9.6 Mg/ha). SOC stocks were largest under prairie (A horizon: 156.1 Mg/ha; 0-30 cm: 152.4 Mg/ha) and lowest under pasture (A horizon: 33.2, 0-30 cm: 44.6 Mg/ha). SOC stocks varied less by soil order than by land use. Between 1845 and 2012, surface SOC stocks decreased for most of Illinois, with greatest losses in central (-16.3 Mg/ha) and east-central Illinois (-47.0 Mg/ha) where approximately 80 % of prairie was converted to cropland. A slight increase in surface SOC stocks occurred in the unglaciated northwest region and the less recently glaciated south region, as well as in alluvial corridors. This study (i) highlights how estimating spatiotemporal dynamics of surface SOC stocks over centennial timescales can benefit from including measures of SOC under native land use not usually contained in legacy pedon datasets, and (ii) illustrates the potential of identifying localized hotspots of historical SOC loss and thus deficits that can be prioritized for carbon sequestration efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

As we face today's large-scale agricultural issues, the need for robust methods of agricultural forecasting has never been clearer. Yet, the accuracy and precision of our forecasts remains limited by current tools and methods. To overcome the limitations of process-based models and observed data, we iteratively designed and tested a generalizable and robust data-assimilation system that systematically constrains state variables in the APSIM model to improve forecast accuracy and precision. Our final novel system utilizes the Ensemble Kalman Filter to constrain model states and update model parameters at observed time steps and incorporates an algorithm that improves system performance through the joint estimation of system error matrices. We tested this system at the Energy Farm, a well-monitored research site in central Illinois, where we assimilated observed in situ soil moisture at daily time steps for two years and evaluated how assimilation impacted model forecasts of soil moisture, yield, leaf area index, tile flow, and nitrate leaching by comparing estimates with in situ observations. The system improved the accuracy and precision of soil moisture estimates for the assimilation layers by an average of 42% and 48%, respectively, when compared to the free model. Such improvements led to changes in the model's soil water and nitrogen processes and, on average, increased accuracy in forecasts of annual tile flow by 43% and annual nitrate loads by 10%. Forecasts of aboveground measures did not dramatically change with assimilation, a fact which highlights the limited potential of soil moisture as a constraint for a site with no water stress. Extending the scope of previous work, our results demonstrate the power of data assimilation to constrain important model estimates beyond the assimilated state variable, such as nitrate leaching. Replication of this study is necessary to further define the limitations and opportunities of the developed system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)