The impact of biofilms and dissolved organic matter on the transport of nanoparticles in field-scale streams.

The fate and transport of nanoparticles (NPs) in streams is critical for understanding their overall environmental impact. Using a unique field-scale stream at the Notre Dame-Linked Experimental Ecosystem Facility, we investigated the impact of biofilms and the presence of dissolved organic matter (DOM) on the transport of titanium dioxide (TiO2) NPs. Experimental breakthrough curves were analyzed using temporal moments and fit using a mobile-immobile model. The presence of biofilms in the stream severely reduced the transport of the TiO2 NPs, but this was mitigated by the presence of DOM. Under minimal biofilm conditions, the presence of DOM increased the mass recovery of TiO2 from 4.2% to 32% for samples taken 50 m downstream. For thriving biofilm conditions only 0.5% of the TiO2 mass was recovered (50 m), but the presence of DOM improved the mass recovery TiO2 to 36%. The model was suitable for predicting early, peak, tail, and truncation time portions of the breakthrough curves, which attests to its ability to capture a range of processes in the mobile and immobile domains of the stream. The model outcomes supported the hypothesis that DOM changed the interaction of NP-biofilm from an irreversible to a reversible process. Collectively, these outcomes stress the importance of considering biogeological complexity when predicting the transport of NPs in streams.

Anthropogenic stressors compound climate impacts on inland lake dynamics: The case of Hamun Lakes.

Inland lakes face unprecedented pressures from climatic and anthropogenic stresses, causing their recession and desiccation globally. Climate change is increasingly blamed for such environmental degradation, but in many regions, direct anthropogenic pressures compound, and sometimes supersede, climatic factors. This study examined a human-environmental system - the terminal Hamun Lakes on the Iran-Afghanistan border - that embodies amplified challenges of inland waters. Satellite and climatic data from 1984 to 2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3809 km2 versus 410 km2), coincident with a basin-wide, multi-year meteorological drought. The lakes continued to shrink afterwards and desiccated in 2012, despite the above-average precipitation in the upstream basin. Rapid growth in irrigated agricultural lands occurred in upstream Afghanistan in the recent decade, consuming water that otherwise would have fed the Hamun Lakes. Compounding upstream anthropogenic stressors, Iran began storing flood water that would have otherwise drained to the lakes, for urban and agricultural consumption in 2009. Results from a deep Learning model of Hamun Lakes' dynamics indicate that the average lakes' surface area from 2010 to 2019 would have been 2.5 times larger without increasing anthropogenic stresses across the basin. The Hamun Lakes' desiccation had major socio-environmental consequences, including loss of livelihood, out-migration, dust-storms, and loss of important species in the region.

Climate change and the opportunity cost of conflict.

A growing empirical literature associates climate anomalies with increased risk of violent conflict. This association has been portrayed as a bellwether of future societal instability as the frequency and intensity of extreme weather events are predicted to increase. This paper investigates the theoretical foundation of this claim. A seminal microeconomic model of opportunity costs-a mechanism often thought to drive climate-conflict relationships-is extended by considering realistic changes in the distribution of climate-dependent agricultural income. Results advise caution in using empirical associations between short-run climate anomalies and conflicts to predict the effect of sustained shifts in climate regimes: Although war occurs in bad years, conflict may decrease if agents expect more frequent bad years. Theory suggests a nonmonotonic relation between climate variability and conflict that emerges as agents adapt and adjust their behavior to the new income distribution. We identify 3 measurable statistics of the income distribution that are each unambiguously associated with conflict likelihood. Jointly, these statistics offer a unique signature to distinguish opportunity costs from competing mechanisms that may relate climate anomalies to conflict.

A Process-Based Model for Bioturbation-Induced Mixing.

Bioturbation refers to the transport processes carried out by living organisms and their physical effects on soils and sediments. It is widely recognized as an important mixing mechanism, particularly at the sediment-water interface in many natural systems. In order to quantify its impact on mixing, we propose a process-based model based on simple assumptions about organism burrowing behavior. Specifically, we consider burrowing events to be stochastic but memoryless, leading to exponential inter-burrow waiting times and depths. We then explore the impact of two different transport mechanisms on the vertical concentration distributions predicted by the model for a conservative (inert) tracer. We compare the results of our model to experimental data from a recent laboratory study of bioturbation by the freshwater oligochaete worm Lumbriculus variegatus, and find good quantitative agreement.

An Integrated Experimental and Modeling Approach to Predict Sediment Mixing from Benthic Burrowing Behavior.

Bioturbation is the dominant mode of sediment transport in many aquatic environments and strongly influences both sediment biogeochemistry and contaminant fate. Available bioturbation models rely on highly simplified biodiffusion formulations that inadequately capture the behavior of many benthic organisms. We present a novel experimental and modeling approach that uses time-lapse imagery to directly relate burrow formation to resulting sediment mixing. We paired white-light imaging of burrow formation with fluorescence imaging of tracer particle redistribution by the oligochaete Lumbriculus variegatus. We used the observed burrow formation statistics and organism density to parametrize a parsimonious model for sediment mixing based on fundamental random walk theory. Worms burrowed over a range of times and depths, resulting in homogenization of sediments near the sediment-water interface, rapid nonlocal transport of tracer particles to deep sediments, and large areas of unperturbed sediments. Our fundamental, parsimonious random walk model captures the central features of this highly heterogeneous sediment bioturbation, including evolution of the sediment-water interface coupled with rapid near-surface mixing and anomalous late-time mixing resulting from infrequent, deep burrowing events. This approach provides a general, transferable framework for explicitly linking sediment transport to governing biophysical processes.

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation.

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute transport in rivers and many important biogeochemical processes. To improve understanding of these processes through visual demonstration, we created a hyporheic flow simulation in the multi-agent computer modeling platform NetLogo. The simulation shows virtual tracer flowing through a streambed covered with two-dimensional bedforms. Sediment, flow, and bedform characteristics are used as input variables for the model. We illustrate how these simulations match experimental observations from laboratory flume experiments based on measured input parameters. Dye is injected into the flume sediments to visualize the porewater flow. For comparison virtual tracer particles are placed at the same locations in the simulation. This coupled simulation and lab experiment has been used successfully in undergraduate and graduate laboratories to directly visualize river-porewater interactions and show how physically-based flow simulations can reproduce environmental phenomena. Students took photographs of the bed through the transparent flume walls and compared them to shapes of the dye at the same times in the simulation. This resulted in very similar trends, which allowed the students to better understand both the flow patterns and the mathematical model. The simulations also allow the user to quickly visualize the impact of each input parameter by running multiple simulations. This process can also be used in research applications to illustrate basic processes, relate interfacial fluxes and porewater transport, and support quantitative process-based modeling.