No abstract

In intensively managed landscapes, interactions between surface (tillage) and subsurface (tile drainage) management with prevailing climate/weather alter landscape characteristics, transport pathways, and transformation rates of surface/ subsurface water, soil/sediment, and particulate/dissolved nutrients. To capture the high spatial and temporal variability of constituent transport and residence times in the critical zone (between the bedrock and canopy) of these altered landscapes, both storm event and continuous measurements are needed. The Intensively Managed Landscapes Critical Zone Observatory (IML-CZO) is comprised of three highly characterized, well instrumented, and representative watersheds (i.e., Clear Creek, Iowa; Upper Sangamon River, Illinois; and Minnesota River, Minnesota). It is organized to quantify the heterogeneity in structure and dynamic response of critical zone processes to human activities in the context of the glacial and management (anthropogenic) legacies. Observations of water, sediment, and nutrients are made at nested points of the landscape in the vertical and lateral directions during and between storm events (i.e., continuously). The measurements and corresponding observational strategy are organized as follows. First, reference measurements from surface soil and deep core extractions, geophysical surveys, lidar, and hyperspectral data, which are common across all Critical Zone Observatories, are available. The reference measurements include continuous quantification of energy, water, solutes, and sediment fluxes. The reference measurements are complemented with event-based measurements unique to IML-CZO. These measurements include water table fluctuations, enrichment ratios, and roughness as well as bank erosion, hysteresis, sediment sources, and lake/floodplain sedimentation. The coupling of reference and event-based measurements support testing of the central hypothesis (i.e., system shifts from transformer to transporter in IML-CZO due to the interplay between management and weather/climate). Data collected since 2014 are available through a data repository and through the Geodashboard interface, which can be used for process-based model simulations.

Intensively managed land increases the rate of nutrient and particle transport within a basin, but the impact of these changes on microbial community assembly patterns at the basin scale is not yet understood. The objective of this study was to investigate how landscape connectivity and dispersal impacts microbial diversity in an agricultural-dominated watershed. We characterized soil, sediment and water microbial communities along the Upper Sangamon River basin in Illinois-a 3600 km2 watershed strongly influenced by human activity, especially landscape modification and extensive fertilization for agriculture. We employed statistical and network analyses to reveal the microbial community structure and interactions in the critical zone (water, soil and sediment media). Using a Bayesian source tracking approach, we predicted microbial community connectivity within and between the environments. We identified strong connectivity within environments (up to 85.4 ± 13.3% of sequences in downstream water samples sourced from upstream samples, and 44.7 ± 26.6% in soil and sediment samples), but negligible connectivity across environments, which indicates that microbial dispersal was successful within but not between environments. Species sorting based on sample media type and environmental parameters was the dominant driver of community dissimilarity. Finally, we constructed operational taxonomic unit association networks for each environment and identified a number of co-occurrence relationships that were shared between habitats, suggesting that these are likely to be ecologically significant.

Quantitative monitoring of water conditions in a field is a critical ability for environmental science studies. We report the design, fabrication and testing of a low cost, miniaturized and sensitive electrochemical based nitrate sensor for quantitative determination of nitrate concentrations in water samples. We have presented detailed analysis for the nitrate detection results using the miniaturized sensor. We have also demonstrated the integration of the sensor to a wireless network and carried out field water testing using the sensor. We envision that the field implementation of the wireless water sensor network will enable "smart farming" and "smart environmental monitoring".