REU SUBPROJECTS

Examples of research projects that need sensors and sensor development are presented below. REU students may choose one of these projects or from a set of other ongoing projects for their summer research.

The Biogeochemical Cycling of Nutrients in a Natural Water System

The goals of this sub-project are to map the abundance, distribution, and fluxes of nutrients in a highly reactive environment. Geothermal (~80oC and boiling) waters are released from hot springs near Mammoth Mountain, CA into Hot Creek. These waters are a major source of nutrients and arsenic in Hot Creek and, eventually, in drinking water. With our current time- and labor-intensive sampling strategies, we are unable to catalog the complex spatial and temporal trends in As, N and P species. The ability to measure small concentrations of each of the N and P species in situ using sensors should provide, with unprecedented clarity, a picture of the cycling of these nutrients. Commercially available off-the-shelf sensors are either not available or too costly to consider in the context of a sensor network. To our knowledge, redox species-specific P sensors are not available.

Sample REU activities related to this subproject include:

Purchase inexpensive off-the-shelf sensors for temperature, flow, conductivity, and pH
Network and connect (with data acquisition) these sensors and fully test in the laboratory
Deploy sensors in water and in sediments
Develop novel, miniature, field-portable sensors to detect various nutrient species
Lab and field test new sensors

At the end of the three years, we want to answer the following question: What is the abundance, distribution, and persistence of As, N and P species in hot creek CA? Students in this sub-project will be in charge of selecting, developing, constructing, and implementing sensors to answer these questions. These sensors will be tested, calibrated, and validated in the laboratory and will be field-tested when/where appropriate.

Engineering a New Empirical Grounding of Intertidal Ecology

The team develops and tests theories of the interactions among sea shore populations. Sophisticated computer simulations models have been developed to predict the distributions and abundance of shore species such as mussels. The work makes contributions to general ecological theory and the possible effects of humans on the marine environment.

The interactions of seashore species are influenced by flow rates of water across the community. For example, high speeds produce hydrodynamic stresses that hinder predator foraging and also generate greater nutrient exchange, promoting faster prey recruitment and growth.

To date, sub-project activities have included GIS surveys, field experimentation, and computer programming. An area of sampling technology now ripe for development is the description of flow over the intertidal landscapes.

Sample REU activities related to this subproject include:

Purchase or construct wave dynamometers (record highest wave speed) and field and lab test
Develop, purchase, or assemble new sensors to give average, maximum, and total flows across a heterogeneous landscape
Purchase off-the-shelf electronic sensors (e.g., temperature loggers) to obtain additional information

The gathered data will be compared with biologically relevant measures of mussel growth and recruitment, to determine the extent to which a sensor array explains the variation in these parameters.

This subproject combines many fundamental principles of physics, engineering and biology to produce novel data sets for the developing and testing of some of the most advanced theories in ecology. Starting with the simplest of sensors to illustrate the physical and biological principles involved, each year would introduce slightly more complex technology allowing more detailed description of flow over the intertidal landscape. The last years culminate in the deployment of an electronic sensor array to continuously monitor the flow field.

The Ecological and Evolutionary Consequences of Sperm Chemoattraction

Larval recruitment is critical in structuring communities in marine ecosystems. Localized variations in larval settlement are due to interactions between larval behavior and physicochemical properties of the environment (e.g., hydrodynamics, temperature, etc.). External cues can trigger changes in vertical swimming behavior that may concentrate larvae near the bed. Field distributions of water-soluble molecules reflect rates of production and release of these chemicals, followed by transport through advection and mixing. In preliminary sampling, levels of algal metabolites varied spatially and temporally; high-resolution sampling over replicate patches is needed to define where and when soluble cues are available to larvae.

Sample REU activities related to this subproject include:

Use existing samplers to measure chemical cues
Measure flow speed and direction over habitats
Determine velocity profiles (average and fluctuating)
Purchase or develop sensors to determine water temperature, depth and salinity
Develop a high-resolution sampling rig to quantify algal metabolites, larval availability, and flow fields fine scales

Students will be involved in both laboratory and field work with both sensors and engineering tools and traditional biological/chemical methods to study chemical cues and their effects on larval recruitment and settling. For example, incorporation of recently developed carbohydrate probes (which require lab and field testing and validation) into a sensor array (which needs development) is one promising application of new technology that should substantially improve our ability to monitor flux from algal patches. The interdisciplinary nature of this sub-project will ensure that the students will have an enriching experience working at the interface of biology, chemistry, physics, and engineering while contributing significantly to contemporary thinking in supply-side ecological and biogeochemical cycling.

Monitoring Changing Productivity and Diversity using Multi-Scale Remote Sensing

A major goal of this sub-project is to understand the physical and biological factors controlling basic biogeochemical and hydrological processes, including ecosystem carbon flux (photosynthesis and respiration) and water vapor fluxes (evapotranspiration). A primary focus is the development of novel remote sensing and modeling methods for assessing fluxes from large regions. An ultimate goal is to understand the regional carbon and water budgets of the Los Angeles Basin and the larger Southwestern Region. This is an area subject to extreme disturbance (e.g. ENSO events, wildfires, and land-use change due to an expanding human population), thus providing a good model for exploring disturbance impacts on basic ecosystem processes. An understanding of these processes is essential if we are to achieve a sustainable society and economy over the next several decades, particularly given the water shortages and population growth expected for this region. Blending engineering approaches with biology is essential to the goals of this sub-project for several reasons. For example, undersampling is a huge problem in ecology, and engineering approaches (e.g., robotics, wireless networked sensing, etc.) can be effectively applied to improve the temporal and spatial coverage of field sampling.

Sample REU activities related to this subproject include:

Design, fabricate and assemble remote sensing “robots”
Laboratory and field test these robots against known measures of ecosystem function
Design, build, purchase and network sensors to study soil respiratory fluxes
Develop ecoinformatic tools to analyze spatially and temporally explicit data sets

Engineers and scientists will collaborate closely in developing and deploying these sensors. The sensors will be lab-tested against known measures of ecosysmte function. They will also be field-tested in local environments (e.g., Santa Monica Mountains), where ongoing studies provide a rich dataset and a thorough understanding of ecosystem function in this area. Future deployments of these sensors will include more remote regions.