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Remote sensing helps in monitoring arctic vegetation for climate clues

Posted on 22 August 2022 by Guest Author

This is a re-post from Yale Climate Connections by Kristen Pope

Beneath the arctic tundra, a massive reservoir of carbon lies locked in frozen peat. Scientists are using remote sensing tools to keep an eye on that tundra from afar, monitoring it for changes that may provide insight about climate change.

Climate change is causing the Arctic to heat rapidly, warming its permafrost and releasing heat-trapping carbon dioxide and methane to the atmosphere.

“When the material thaws, it is a major concern,” said Peter Nelson, forest ecology director at the Schoodic Institute at Acadia National Park in Maine. Nelson is among the scientists studying the region via remote sensing.

Clues in the vegetation

Monitoring vegetation shifts in the Arctic can help scientists understand how the area is changing as the world warms. Already, researchers have documented expansion of boreal forests into the tundra. And at many sites in the region, the tundra is greening up, according to recent satellite observations

NASA postdoctoral fellow Andy Maguire says these vegetation changes provide insights on key questions, such as learning about whether carbon may be escaping from the region’s frozen storehouse.

“Dramatic changes in plant community composition and productivity in permafrost-dominated landscapes, which often are linked to permafrost degradation and thaw, can indicate a transition of the Arctic from a net carbon sink to a net carbon source,” he wrote in an email.

But it is difficult to study vegetation changes in the vast, remote, lightly populated Arctic tundra, where research expeditions often are costly and resource intensive. Plants in the tundra can be tiny — some just a fraction of an inch high — and one small area can harbor significant biodiversity, further complicating study efforts. 

To learn more about what’s happening in these remote regions, scientists are using a remote sensing technology called imaging spectroscopy to measure reflected light, chronicle changes in Arctic tundra vegetation, and bridge data gaps. Imaging spectroscopy collects data on reflected light, which it can measure in small color bands.

Spectrometers can collect data from towers, drones, aircraft, or even space satellites. In 2027-2028, when NASA expects to launch the  Earth System Observatory, the satellite group is to include an imaging spectrometer. Researchers say the system will provide valuable data, as the new technology can collect far more bands of light than previously possible. 

“This has many, many bands, so it can measure really nuanced color changes in the light that’s being reflected off the surface of the Earth,” Maguire said. “What we do as remote sensing scientists is we try to translate that reflected light to information about what types of plants are down there. How well are they functioning? Are they photosynthesizing efficiently? Are they stressed? Are they dormant?”

‘Ground truth’ still important in addressing challenges

Remote sensing can provide insight into vegetation in the vast Arctic, but it also comes with challenges. Light, ground cover, and the make-up of plant vegetation can make data difficult to interpret. In some plant communities in the arctic, the dominant species may be tiny — less than half an inch tall — requiring very fine-scale measurements. Interspersed with these diminutive mosses and lichens are much larger plants, making analysis difficult. 

In addition, the arctic growing season is just a few months long, with continuous light during the summer months, making it difficult to keep track of rapidly occurring changes such as plant growth and flowering. Come winter, the region is plunged into months of darkness, further complicating light-related measurements.

When measuring light reflection, anything on the ground — like snow, ice, and pools of water — or in the air — like wildfire smoke, clouds, and humidity — can interfere with image collection and impair the reflective signature. Snow typically covers the ground in this region between eight and 11 months out of the year, further complicating data collection.

These issues underscore that collecting data on the ground remains critical for accurately interpreting remotely collected data. Using backpack scanners, ground probes, and on-the-ground observation, researchers collect soil cores, measure ground saturation, and gas measurements to learn about what plants are doing, such as respiration and decomposition. Additionally, on-the-ground researchers chart vegetative cover, species prevalence, plant attributes, and an array of biogeochemical measurements. They also measure the reflective signatures of different plants and leaves and obtain chemical data about them.

“You need to have some ground measurements,” Nelson said. “While remote sensing is going to be useful, there’s going to be stuff that we won’t understand what’s in the data because we don’t have a reference measurement to point to.”

Using a combination of remote and on-the-ground data, researchers then can make observations about which types of plants are in a location, from mosses and tussock grasses to shrubs and other tundra species. This data is expected to provide new insights into how the plants are faring – and crucial clues about the future of the region.

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Comments 1 to 5:



    interesting study on the tree lines in russian artic region during the holecene period. 

    this should provide some context and comparison with the common era past with respect to the current warming

    The is some indication that the tree line is a better proxy for temp than proxies such as tree rings.  

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  2. David-acct @1,

    The subject is evidently not that interesting as the lead author has not continued the work, at least not in the last decade. (The paper dates to 2007). As for tree-line records being "a better proxy for temp than proxies such as tree rings," in what way is that?

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  3. MA Rodger - you raise a good point on why the tree line records can be better proxies for temps than tree rings.  


    The primary reason is that the tree line is a good cross check against the tree ring proxies.  The location of the tree line in the past is a strong indicator of warmer or lower temps.  So if the tree ring proxies show colder temps (or comparable temps) with present day, but the tree line is farther north (or higher), then most likely, the calibration of the tree rings is off.    


    If nothing else, the tree line serves as a basis for reconciliation.  partly noted in the yamal controversy

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  4. Any vegetation-based measure of "climate" needs to address three factors:

    1. What is it about vegetation that you are measuring? The remote sensing disucssion in the post will be looking at changes in radiation that are linked to changes in physical characteristics of some sort. Ground-truthing can assess physical characterisitcs directly.
    2. How does that physical characteristic change with respect to weather or climate? What other factors affect that physical characteristic?
    3. How long does it take for that physical characteristic to respond?

    In the case of tree rings vs. treeline, the response time is very different. Rings show annual effects, while tree line takes decades or longer to change. That means that tree line has a built-in "climate" averaging - less affected by extremes in a single year, or other short-term factors such as insect outbreaks. It will not respond quickly to rapid shifts in climate, though.

    Tree rings can be measured as changes in width, or density, or other structural characteristics of the wood. Both temperature and moisture will have an effect, as will insect or disease outbreaks. Rate of growth also changes as a tree ages, so this is factored into the analysis. And data will be collected from trees of varying ages, to look for consistency.

    In addition to tree line, things like pollen analysis in local sediments can tell about species abundance and changes over time.

    And as David-acct says, reconcilliation across multiple sources of analysis is important. That's why reconstructions of past climates from proxy data bring together large numbers of proxies of different types - to search for common signals.

    An old post here at SkS talks about some of this:

    It is also worth noting that the common Koppen Climate Classification system -  where we get terms such as "continental", "maritme", "temperate" etc. that are part of the common language of climate - was originally developed to explain vegetation patterns. The links between climate and vegetation are strong.

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  5. David-acct @3,

    So you are actually saying that tree-line records assist in providing "a better proxy for temp," not that they are better relative to "proxies such as tree-rings," although you still suggest tree-line data would "most likely" have precedence over tree-ring data when the two datasets show differing results, but I'm not sure why that would be.

    As for that 'Yamal controversy', I don't think there was anything that would have abated that particular denyospheric storm because the last thing the perpetrators were seeking was "reconciliation." 

    The subject review of tree-lines of Harsch et al (2009) 'Are treelines advancing? A global meta-analysis of treeline response to climate warming' is still a good start to understand the value of tree-line records as temperature proxies, to which we can now also add Hannson et al (2021) 'A review of modern treeline migration, the factors controlling it and the implications for carbon storage'

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