Posts tagged ‘spectral reflectance’

Dec 15

Despite Drawbacks, Scientific Collaboration Pays Off

Though collaboration can fuel innovation and increase the relevance and complexity of the scientific questions we study, I’ve noticed it does have its ups and downs. The highs and lows we’ve run into on our research projects may help others avoid some of the pitfalls we experienced as many diverse groups tried to learn how to work together.

Researchers discussing science at the Lytle Ranch Preserve, a remarkable desert laboratory located at the convergence of the Great Basin, Colorado Plateau, and Mojave Desert biogeographical regions.

There can be bumps in the road when collaborating with companies who want to test their product. Being at the forefront of innovation means that untested sensors may require patience as you work out all the bugs together. But from my perspective, this is part of the fun. If we are late adopters of technology, we wouldn’t get to have a say in creating the sensors that will best fit our projects as scientists.

Collaborating scientists can also sometimes run into problems in terms of the stress of setting up an experiment in the time frame that is best for everyone. During our experiment on the Wasatch Plateau, we had six weeks to get together soil moisture and water potential sensors, but our new GS3 water content, temperature, and EC sensors had never been outside of the lab. In addition, we planned to use an NDVI sensor concept that came out of a workshop idea my father Gaylon had. We’d made ONE, and it seemed to work, but that is a long way from the 20 we needed for a long-term experiment in a remote location at 3000 meters elevation. In the end, it all worked out, but not without several late nights and a bit of luck. I remember students holding jackets over me to protect me from the rain as I raced to get the last sensor working. Then we shut the laptop and ran down the hill, trying to beat a huge thunderstorm that started to pelt the area.

Desert-FMP Researchers at the Lytle Ranch Preserve

Other challenges of scientific collaboration present organizational hardships. One of the interesting things about the interdisciplinary science in the Desert FMP project is the complexity of the logistics, and maybe that’s a reason why some people don’t do interdisciplinary projects. We are finding in order to get good data on the effects of small mammals and plants you need to coordinate when you are sampling small mammals and when you’re sampling plants. Communicating between four different labs is complicated. Each of the rainout shelters we use cover an area of approximately 1.5 m2 . That’s not a lot of space when we have two people interested in soil processes and two people interested in plants who all need to know what’s going on underneath the shelter. Deciding who gets to take a destructive sample and who can only make measurements that don’t change the system is really hard. The interesting part of the project where we’re making connections between processes has required a lot of coordination, collaboration, and forward-thinking.

In spite of the headaches, my colleague and I continue to think of ways we can help each other in our research. Maybe we’re gluttons for punishment, but I think the benefits far outweigh the trouble we’ve had. For instance, in the above-mentioned Desert FMP project we’ve been able to discover that small mammals are influential in rangeland fire recovery (read about it here). We only discovered that piece of the puzzle because scientists from differing disciplines are working together. In our Wasatch Plateau project, my scientist colleague said it was extremely helpful for him to be working with an instrumentation expert who could help him with setup and technical issues. Also, we’ve been able to secure some significant grants in our Cook Farm Project (you can read about it in an upcoming post) and answer some important questions that wouldn’t have occurred to either one of us, if we hadn’t been working together. In addition, solving problems that have cropped up in our projects has spurred us on to a new idea for analyzing enormous streams of data in near-real time. (read about it here).

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Nov 17

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Near Real-Time Data Analysis

We are entering an era of cheap data. Sensor technology has advanced to the point where it has become easy to collect large amounts of measurement data at high spatiotemporal resolution.

Hydroserver map screen: Using an off-the-shelf open source informatics system like Hydroserver kept us from reinventing what’s already out there, but allowed flexibility to program to our own needs.

We are now to the point where we have gigabytes worth of data on soil moisture, plant canopy processes, precipitation, wind speed, and temperature, but the amount of data is so overwhelming that we are having a difficult time dealing with it. The cost of measurement data is dropping so quickly, people are forced to change from a historical mindset where they analyzed individual data points to the mindset of turning gigabytes of data into knowledge.

Because Bioinformatics students are used to working with DNA data, they understand how to write computer programs that analyze large amounts of data in near real-time.

One approach suggested by my colleague Rick Gill, a BYU Ecologist, is to collaborate with bioinformatics students. Because they are used to working with DNA data, these students understand how to write computer programs that analyze large amounts of data in near real-time. Rick came up with the idea to tap these students’ expertise in order to analyze the considerable information he anticipates collecting in our Desert FMP Project, an experiment which will use TEROS 21 and SRS sensors to determine the role of varying environmental and biological factors involved in rangeland fire recovery.

Rick and I are predicting that near real-time data analysis will give us several advantages. First, we need readily available information so we can tell that sensors and systems are working at the remote site. Large gaps in data are common for sites that aren’t visited often, and sensor failures are missed when data are collected but never analyzed. With our new approach, all data are databased instantly, and the results are visualized as we go. Not only that, we’ll be able to control what’s being analyzed as we see what’s happening. We can tell the bioinformatics students what we need as we begin to see the results come in. If we see important trends, we can assign them to analyze new data that may be relevant right away.

These techniques have the potential to help scientists from all disciplines become more efficient at collection and analysis of large data streams. Although we’ve started the process, we have yet to determine its effectiveness. I will post more information as we see how well it is working and as new developments arise.

Watch Dr. Gill’s data analysis webinar: Finding Insights in Big Data Sets

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Nov 13

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Complex Scientific Questions Yield Better Science in Desert FMP Project

The Desert FMP project originated from a discussion between pretty divergent scientists: Rick Gill, a BYU ecologist, another scientist who works on soil microbes, a plant physiologist, and a mammalogist who researches small mammals.

Tree fire in Rush Valley

In an interview Rick said, “We started talking one day about the transformations that have occurred in the arid West over the past 100 years. One of the things we are really interested in is fire. How do ecosystems recover after fire? What’s the role of water in rangeland recovery? And the unique piece of this is: what’s the role of small mammals in this process? We may never have thought of that question, or the complexity of researching how all of our questions work together in a system, if scientists from different disciplines hadn’t decided to collaborate.”

Rush Valley research site. Five replications with four treatments: burned/unburned and small mammal/no small mammal. What’s interesting for us is that you can see that in the burned plots (the light brown) there are strong differences in the amount of the bright green plant—halogeton—that was present and it is systematically associated with the presence of small mammals. Here is the logic: In the spring, the presence of small mammals suppressed the cheatgrass and to some extent halogeton; in the absence of halogeton, cheatgrass ran wild. The cheatgrass transpired away all of the water and the halogeton that had germinated all died before it could flower.

As the experiment unfolds it is becoming clear that small mammals play a larger role in ecosystem recovery from fire than originally thought. The scientists have used their observations to hypothesize that small mammals eat the seeds and seedlings of two invasive species. This ends up setting the vegetation along a very different trajectory than when small mammals are absent following fire. Rick says, “We have discovered this complex but interesting interaction between water, fire, and small mammals. The first year after the fire, a really nasty range forb moved in called halogeton, which is toxic to livestock. Halogeton also accumulates salts in the upper soil profile that will cause failure in native plant germination. Cheatgrass has also moved in which makes the area more prone to fire as it connects the sagebrush plants with flammable material. But what’s interesting is in treatments where mammals were present, the densities of both halogeton and cheatgrass were much lower than where small mammals were absent.

Plot water potential comparison using matric potential sensors between Mammal (blue) and no mammal (red) over time. With no mammals to control cheatgrass, it depleted soil water availability below no mammal treatment and consequently halogeten was not able to grow.

“The other really important thing is that cheatgrass and halogeton have different growth patterns. Cheatgrass germinates in the Fall. It reaches peak biomass early in the growing season and then dies off leaving a blanket of dead, highly flammable vegetation. Halogeton germinates early in the growing season and remains relatively small until early Autumn when it bolts. These are things that will be really easy to pick up using NDVI sensors, which are sensitive to the amount of green vegetation within the field of view of the sensor. We are also using a system that we’ve designed to manipulate precipitation input. This will enable us to connect water availability to the success of two invasive plants that have negative impacts on rangelands. And with these same treatments we’re going to be able to tease out when in the year and to what extent small mammals are influencing the ecosystem by eating the seeds or the plant and at what stage.”

“Until I saw it in the field, the question of mammals being influential in rangeland fire recovery had never occurred to me. We only discovered that piece of the puzzle because scientists from differing disciplines are working together.”

Below are two virtual tours of the site:

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Nov 1

Spectral Reflectance and Water Content in the Wasatch Plateau Experiment

We chose to collaborate with Brigham Young University in an experiment on the Wasatch Plateau in 2009 because a scientist friend of ours had been working in that area the previous five years, and he noticed there were big grazing responses. The plants growing in the long-term grazed areas were all drought tolerant, while ungrazed plots had plants that were often found only in wetter areas. The only difference was the fence that kept sheep on one side and not on the other. The big question was: how does water influence plants in this ecosystem that we understand relatively well? The story had always been the influence of grazers, when in fact, maybe the indirect consequence of grazing was mediated by water.

The Wasatch Plateau above Ephraim Canyon, UT, USA.

METER donated some sensors in order to set up an experiment where we changed the amount of water in various plots of land. We had rain exclusion plots, and we had treatments where we collected all incoming rainfall and reapplied it either once a week or every three weeks. This allowed us to say to what extent this system was controlled by water during the growing season. To do this, we took measurements with our prototype NDVI Spectral Reflectance Sensor to measure canopy greenness. We also used our prototype volumetric water content sensors to measure soil moisture (this was a few years ago and the sensors were prototypes at the time). Using these sensors, we found that water is critical in a system people have dismissed as being climate-controlled because it’s at the top of a mountain.

A very early prototype of a NDVI sensor measuring canopy greenness in experimental plots on the Wasatch Plateau.

It turns out the amount and timing of precipitation makes a big difference. We were able to directly connect plant survival, not just to the grazing treatment, but to the actual amount of water that was in the soil. Also, using continuous NDVI data, we were able to look closely at the role of grazing on plant canopies. When we looked at our NDVI data, we were able to see a seasonal signal, not just a single snapshot sample in time. So by having the richer data from the data loggers, we obtained a more nuanced understanding of the impact of land use on these important ecological processes.

One of the mistakes we made was failure to include redundancy in the system. We only had two replicates, so when one of them went down we ended up having just one little case study. However, that mistake gave us new ideas on how to set up a better system using the right sensors for the job, and it generated a new idea on how to get real-time analysis of data. In our new Desert FMP project, we have a much better-replicated system where more is invested in the number of sensors that we’re putting out. Each treatment combination will have five to ten water potential sensors. We are also developing a system where we can analyze data in real-time, so this time we will know when a sensor goes out if a student accidentally kicks it.

For more details on the Wasatch Plateau Experiment, watch for our published paper that we’ll link to when it comes out.

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