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Posts by Leo Rivera

Climate Change, Genetics, and the Future World

Climate change scientists face a particular challenge— how to simulate climate change without contributing to it. Paul Heinrich, a Research Informatics Officer associated with the Southwest Experimental Garden Array (SEGA) remembers looking at the numbers for a DOE project that would have used fossil fuel to measure forests’ response to temperature change. “It would have been very, very expensive in fossils fuels to heat a hectare of forest,” he says.

The alternative is, “to use elevation change as a surrogate for climate change so we could do climate change manipulations without the large energy costs.”

SEGA Vegetation Zones diagrams

An overview of the SEGA sites using elevation change as a surrogate for climate change. For more information on these sites, visit Photo credit Paul Heinrich

By monitoring organisms across a temperature gradient it is possible to identify genetic variation and traits within a species that could contribute to a species survival under projected future climates.

Control and Monitoring Infrastructure

SEGA is an infrastructure project started in 2012 after researchers at Northern Arizona University’s Merriam-Powell Center for Environmental Research were awarded a $2.8 million dollar NSF grant with a $1 million match from NAU. Consisting of ten fenced garden sites for genetics-based climate change research, SEGA is set on an elevation gradient from 4000 to 9000 feet in the Southwestern United States. Each SEGA site has an elaborate data collection and control system with meteorological stations and site-specific weather information. Custom-engineered Wireless Sensing Actuating and Relay Nodes (WiSARDs) send data packets to a hub which then send the data back to a centralized server.

Because there is inherent moisture content variability from site to site, volumetric water content and soil water potential sensors have been installed to monitor and maintain moisture levels. If there is a change in soil moisture at one site, soil sensors will detect the difference. Software on the server notes the difference and sends a signal to the other sites, turning on irrigation until the soil moisture matches across sites.

SEGA Cyberinfrastructure Major Components diagram

An illustration of SEGA’s cyberinfrastructure and data management system. Photo credit Paul Heinrich.

Having such an elaborate infrastructure creates an opportunity for researchers looking to conduct climate change research. By offering access to the pre-permitted SEGA sites, the hope is that research will generate much-needed data for climate projections and land management decisions.

When asked if the data stream was overwhelming to manage Heinrich said, “Well, not yet. We are just getting started. The system is designed for what SEGA is expected to look like in ten years, where we expect to have 50 billion data points.”

Research Considerations

Climate change projections show temperatures increasing rapidly over the next 50 to 100 years, bringing drought with it. The impact of these changes will be dramatic. Temperature and drought tolerant species will survive, those that are not will die, drastically changing the landscape in areas that are currently water stressed. Pests like the pine beetle and invasive species like cheatgrass will do well in a drier environment where water-stressed natural species will not be able to compete.

Red canyon called Soap Creek AZ from an Aerial view

Soap Creek, AZ from above. With climate change projections it is likely that more land will become marginal. Photo credit Paul Heinrich.

“Foundational species,” or species that have a disproportionate impact on the ecosystem, are the primary focus of the research efforts at SEGA sites. These are the species that drive productivity, herbivore habitat, and carbon fixation in the ecosystem. Unlike forests in other parts of the United States, forests in the Southwest can be dominated by one or two species, which makes potential research subjects easier to identify.

Genetic Variance

Amy Whipple, an Assistant Professor in Biology and the Director of the Merriam-Powell Research Station who oversees the day-to-day activities at SEGA, has been conducting some of her own research at the garden sites. Whipple has studied Piñon Pine, Southwestern White Pine, and has a proposal to study Cottonwood in process.

Whipple says that models currently suggest that Piñon Pine will be gone from Arizona within the next 50 years, adding that the models do not take into account possibilities for evolution or genetic variance that might help the Piñon survive. Her research is largely asking, will trees from hotter, drier locations have a better chance of surviving climate change? “We’re trying to do that with a number of different species to look for ways to mitigate the effects of climate change in the Southwest.”

Researchers documenting a Piñon Pine

Researchers documenting a Piñon Pine. Photo credit Paul Heinrich.

In some of her research on Piñon Pine, it was discovered that four different species were grouped morphologically and geographically from southern Arizona to Central Mexico. While this suggests that the divergence of species has occurred, it also suggests a low migration rate for these tree species. Migration rates of drought and temperature tolerant species is an important consideration when modeling for a future climate. If the migration of genetically adapted species cannot keep up with climate, the land could become marginal as a foundational species dies off.

Climate Change Predictions and Considerations

In the Southwest, there are entire forests that could become grassland in 50 years because the genetic characteristics of the foundational species currently in those regions will not adapt to higher temperatures and drought stress. But what does this mean from a land management perspective?

Ponderosa pine tree hanging off the side of a rocky cliff in the desert

Ponderosa pine trees, a foundational species in some area of the Southwestern United States.

Environmental conservationists maintain that we should protect the unique species that are in a place and that introducing other organisms or genetic material would be an ethical violation. Environmental interventionists make the argument that climate change has been caused by humans, so we have lost the option of remaining bystanders.

Research, Land Management and Policy

Paul Heinrich says that the route we take to manage the land will depend on our end goals. “Places that have trees now, if you want them to have trees 50 years from now, you are going to have to do something about it. The trees that are on the landscape right now are locally adapted to the past climate. They are not necessarily adapted to the future climate. They are probably maladapted to the future climate.”

To be clear, SEGA’s goal is not to promote or implement assisted migration. Instead, Amy Whipple says, SEGA can test what the effects of assisted migration might be. “In a smaller experimental context, we’re asking: how will these plants do if we move them around? What will happen to them if we don’t move them around?’” The goal is to provide decision makers with the data they need to make informed decisions about how to manage the land.

Image of a Meadow with trees in the distance and a set of mountains

The Arboretum Meadow in Flagstaff, AZ. Home of one of the SEGA research sites. Photo credit Paul Heinrich.

Whipple’s own view is that we may no longer have the option of doing nothing. “Unless major changes are made for the carbon balance of the planet, keeping things the same is not a viable option. Managing for a static past condition is not viable anymore.”

Remaining Questions

Both Heinrich and Whipple acknowledge that these are inherently difficult questions. Ultimately the public and land managers must make these decisions. In the meantime, data from SEGA research may help ensure better predictions, better decisions, and better outcomes.

To find out more about conducting your own climate change research using SEGA go to:

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Accurate Field Saturated Hydraulic Conductivity—Why is it so difficult?

Inaccurate saturated hydraulic conductivity (Kfs) measurements are common due to errors in soil specific alpha estimation and inadequate 3D-flow buffering.  Leo Rivera, METER research scientist, explains why getting an accurate saturated hydraulic conductivity (Kfs) measurement is so difficult.

Farming driving tractor spraying his field

Water infiltrates the soil in three dimensions; it spreads laterally, as well as downward.

“Sorptivity, or the ability of soil to absorb water, has traditionally been a complex measurement for scientists to make.  This is because water infiltrates the soil in three dimensions; it spreads laterally, as well as downward.  The problem is, the value which represents sorptivity, Kfs, is a one-dimensional value.  Scientists use Kfs in modeling as the basis of their decision-making, but they have to remove the effects of the three-dimensional flow to get that value.  

“The traditional method for removing those effects is to look at a table of alphas or the soil macroscopic capillary length.  But since alpha is an estimate of the sorptivity effect, or how much the soil is going to pull the water laterally, if you use the wrong value, your estimate is going to be significantly off.

“The other problem with making this measurement is that most researchers have found the double ring infiltrometer does not buffer three-dimensional flow perfectly. Thus, if you are operating on the assumption that you’re getting one-dimensional flow in the center ring, you will overestimate your field saturated conductivity (Kfs) values.  This can be disastrous, particularly if you’re working with a soil that has been engineered to have a very low permeability.  If you overestimate Kfs, you could incorrectly assume your cover is ineffective (Ks is over 10-5 cm s-1).  But really, you’ve overestimated Kfs, and the cover may actually be compliant.”

Leo discusses solutions to these and other infiltrometer difficulties the webinar “Advances in Lysimeter Technology“. 

Watch the webinar

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Examining Plant Stress using Water Potential and Hydraulic Conductivity

Many scientists rely on water potential alone to measure plant water stress.  Leo Rivera, a METER soil scientist, shows how a two-pronged approach, using hydraulic conductivity as well as water potential, can make those measurements more powerful.  

Green tomato plant with three bright red tomatoes

Measuring hydraulic conductivity in nursery plants shows why plants are stressed.

Soil moisture release curves can give you incredible detail about water movement, allowing you to understand not only that plants are stressed, but WHY they are not getting the water they need.

Recently, we ran into a mystery where this method was useful.  Growers at a Georgia nursery noticed that plants growing in a particular soilless substrate were beginning to show signs of stress at about -10 kPa water potential, which is still really wet. They wanted to know why.

We decided to create the unsaturated hydraulic conductivity and soil moisture release curves  for the substrate (using the Wind Schindler technique [HYPROP lab instrument]) and found that it had a dual porosity curve: essentially, a curve with a “stair step” in it. The source of the “stair step” can be explained by considering the substrate, which was made up of bark mixed with some other fine organic materials. In the bark material there were a lot of large and small pores, but no medium-sized pores (this is called a “gap-graded” pore size distribution).  This gap in the pore size distribution reduced the unsaturated hydraulic conductivity and caused the stress. Even though there was available water in the soil, it couldn’t flow to the plant roots.

Blue crates with lots of green nursery seedlings in each crate

Nursery seedlings

That would have been pretty hard to understand without detailed hydraulic conductivity and soil moisture release curves—curves with more detail than most traditional techniques can provide.  Our measurements showed that unsaturated hydraulic conductivity can have a major effect on how available water is to plants.  Our theory about the soilless substrate was that as the roots were taking up water, they dried the soil around them pretty quickly. In a typical mineral soil, the continuous pore size distribution would allow water to flow along a water potential gradient from the surrounding area to the soil adjacent to the roots. In the bark, the roots dried the area around them in the same way, but the gap in pore size distribution created low hydraulic conductivity and prevented water from moving into the soil adjacent to the roots. This caused plants to start stressing even though the substrate was still quite wet. 

We were pretty excited about this discovery. It shows that water potential, though critical, may not always tell the whole story. Using technology to measure the full soil moisture release curve and the hydraulic conductivity in one continuous test, we discovered the real reason plants were wilting even when surrounded by water. In the past, it took three or four different instruments and several months to take these measurements.  We can now do it in a week. For more information about creating these kinds of curves, check out the app guide:  “Tools and Tips for Measuring the Full Soil Moisture Release Curve.”

Download the “Researcher’s complete guide to water potential”—>

Download the “Researcher’s complete guide to soil moisture”—>

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Double Ring Infiltrometers Versus DualHead Infiltrometers

Several years ago I had the chance to work at the USDA ARS Research Watershed in Riesel, Texas. The goal of my research was to look at the effects of land use and landscape position on water infiltration.  Within the research watershed there is preserved and maintained native prairie, improved pasture, and conventional tilled areas, which have been in existence for 75 years. Thus we were able to use infiltrometers to study the long-term effects of those different land uses, along with the effect of landscape position within the same soil type.

Double Ring Lysimeters

Texas Infiltrometer setup

My research focused on the Houston Black Soil Series, which is a clay-rich soil with a high shrink-swell capacity. This soil type has key economic importance, as it is present in much of Texas’ USDA prime farmland.  To achieve our objectives, we began by mapping soil bulk electrical conductivity using an EM38 device (electromagnetic geo-surveying instrument).  The maps we created allowed us to look for areas of variability in water content, depth to parent material, clay content, and salinity.  Then we randomly selected three zones within the catinas (full hill slope including summit, back slope, and front slope) and flagged them with GPS points.  Our goal was to make infiltration measurements at all of the landscape positions on the slope and compare them to the same landscape positions within each land use type.

We found that the native prairie had the highest infiltration rates because the soil maintained its strong structure and macropores which allowed water to conduct well through the soil.  We also found some differences by landscape position that were consistent within the different catinas.  As water would run down the catina, erosion would transport soil and organic matter off the shoulder and back slope and deposit it on the foot slopes.  Even though they were mapped as the same soil type, the differences in erosion and reduction of organic matter affected the ability of these different positions to transport water.

Double ring infiltrometer chart

We chose to customize existing double ring infiltrometers to make these measurements because there wasn’t anything automated on the market.  If I was going to conduct my research in a reasonable amount of time, I had to come up with a system where I could run a lot of measurements relatively easily.  As a result, we bought three double-ring infiltrometers and modified them with pressure sensors and some larger controlled ports.  The resulting setup was huge; the outer ring on each infiltrometer was 60 cm in diameter and the entire instrument was very heavy.  We were constantly refilling the instrument water reservoirs. In fact, this setup required so much water that we had to pull a 1,900-liter water tank on a trailer wherever we were taking measurements.

Our goal was to save time by running all three infiltrometers concurrently, but it still took a LONG time.  Even though we had automated the instruments, they required a lot of monitoring; sometimes I had to fill our 1,900-liter water tank twice in a day. One measurement at one site took anywhere from 1.5 hours to 3 hours depending on when we reached steady state. We spent so much time out in the field that we were actually caught on film in one of the Google Maps picture flyovers!   Even after all this field time, the data analysis was overwhelming, despite a relatively seamless approach to handle it all.

One huge infiltrometer setup

Our huge setup caught on google maps

I often dreamed of making a tool that would be a lot easier for me and others to use. When I joined Decagon (now METER), it gave me an opportunity to do just that.  Our design goals were to make an infiltrometer that required less water and simplified the data analysis.  We rejected the double ring design in favor of a single ring approach because research has shown that the outer ring doesn’t buffer three-dimensional flow like it’s supposed to. (Swartzendruber D. and T.C. Olson.  “Sand-model study of buffer effects in the double-ring infiltrometer” Soil Sci. Soc. Am. Proc. 25 (1961), 5-8)

We also wanted to simplify the analysis of three-dimensional flow.  With a constant head control in a single ring, there are equations that you use to correct for it.  But you have to guess at things like soil type and structure which leads to inaccuracies.  Multi-head analysis has been around for decades. It involves establishing constant water heights (heads) at multiple levels and looking at the difference in the infiltration rates to calculate the sorptivity. Thus, parameters that are normally estimated from a table can actually be measured, and infiltration results will be independent of users.

Still, there can be problems with the multiple head approach. Increasing the water height when infiltrating into a really low conductivity soil may take 1 to 2 hours to drain back to the original height. We didn’t want to make this measurement take longer than necessary, so instead of using additional water, we used air pressure to simulate higher water levels which can be added or removed very quickly.

So, thanks to the instrument hardships I endured in my past efforts to obtain infiltration measurements, we now have an easy-to-use dual-head infiltrometer (now called the SATURO), that can do the analysis of infiltration rates and saturated hydraulic conductivity on the instrument itself (it gives sorptivity and alpha, based on the soil type and structure, and makes the correction onboard).  Thus, if a scientist needs a value right away, it’s there. But, if like me, they wanted to dig deeper through the data, all the measured values can still be downloaded for more careful analysis.  Together, it’s a simple tool for both scientists and consultants who need to make these measurements.  And they won’t get caught on Google Maps like me, because they’ve had to spend their whole life in the field taking measurements.

Below is a video of the dual-head infiltrometer in action.

Get more information on applied environmental research in our

Download the “Researcher’s complete guide to soil moisture”—>