When does your elderberry bloom?

Have you ever noticed that trees seem to green up earlier in cities than in the countryside? If yes, it is not just a feeling. Urban areas have higher temperatures earlier during the spring. Moreover, it is already known that plants have the tendency to leaf out and bloom earlier in cities.

The phenology of plants refers to the timing of events important in the life cycle of plants such as the bud bursting, leaf development, or the opening of flowers. Phenological studies aim to better understand how the timing of such events is influenced by variations in environmental conditions. However, phenological studies in urban environments usually rely on measurements of temperature and soil moisture at regional scales.

Phenological stages of the elderberry flower, from 0% open on the left to fully blooming on the right.

That’s a big limitation, but we realized that we were having a unique opportunity at hand: we could benefit from the incredible level of precision of the data acquired by the thousands of participants in the ‘CurieuzeNeuzen in de Tuin‘ citizen science project in Flanders and let them track phenology in their garden. This way, we can link the precise temperature and soil moisture data provided by the 3000 mini weather stations spread throughout Flanders to the exact timing of flowering of plants close to them.

Will these local patterns in daytime (left) or nighttime (right) temperatures be reflected in the timing of flowering onset? We’re going to find out!

The set-up is simple: participants with a mini weather station ánd an elderberry (Sambucus nigra) or butterfly bush (Buddleja davidii) in their garden are asked to report on the unfolding of the flowers of these shrubs every three days, until they are fully in bloom. This data on flowering time will then be linked to the actual temperatures in their garden.

Flower stages of the butterfly bush

What we hope to find? For example, we want to determine at what degree the temperature differences between the city environment and the countryside become sufficient to trigger earlier blooms.

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What microclimate sensor to use?

I often get the question what microclimate sensor I would recommend. To facilitate my answer to that, I decided to summarize my ideas on the matter here. Note that this is a far from exhaustive musing on the different factors to take into account. And most importantly: I would love to hear from YOU what worked and what didn’t, and would gladly update this information here with your insights!

In SoilTemp, we are not using one standard sensor type, we are accepting data from all different kinds of sensors, as long as they measure with 4 hour intervals or less. Most common brands are TOMST, iButton, HOBO and Lascar, yet there is a myriad of other sensors, for example those integrated in weather stations, flux towers, or other long-term monitoring. My personal recommendation is still the TOMST TMS4, a sensor designed by and for ecologists that solves many of the issues one could have.

Some features:

  • Around 10 year memory space. This is the game changer for me! The TMS4 measures when it leaves the factory and never stops. It doesn’t overwrite data and simply keeps it all. You can always read out data from only your last measurement campaign or the whole thing. So no data losses as is ever so common with other sensors! Also, they easily measure every 15 minutes, whereas the cheap iButtons and HOBOs wouldn’t survive a whole year with their memory at ~60 minutes, even.
  • 4 sensors for the price of 1 (or 2-ish 🙂 ): the TMS4 mimics a little plant, measures temperature just above, at and just below the soil surface, and also measures soil moisture. This has proven véry useful, as the three temperature levels show highly different patterns and drivers in virtually all ecosystems (e.g. related to snow cover).
  • Around 10 year battery life, so no issues of sudden breakdown (without option to retrieve data) as with iButtons, and no struggling with replacing batteries as in HOBO
  • Standardization: no messing with home-made shields or installation methods, making measurements much more comparable between different studies.
  • Free software! iButton software is free as well, but I don’t like that I have to pay for HOBO software.
  • Rugged. The TMS4 is fully waterproof (no wrapping in Parafilm as with iButtons or fumbling with dessicant as in Hobo Pendant). The solar shields are the most vulnerable; TOMST provides rings now to secure it to the sensor, but the result is now that instead of disappearing they tend to break under duress). We still have some sensor deaths despite their ruggedness, which mostly relates to them sticking above the soil (e.g. mown down or burned).
  • The sensors unique number is written super clearly on the sensor, so messing up sensors and plots has become much less common. Perhaps more importantly even: the output file has a standardized naming that includes the sensor name, so you really have to put in effort to screw this up :).
  • Easy to handle data format: all datafiles are (mostly) exactly the same, so less of a mess than I’ve had with HOBOs but especially iButtons to get the data processed.
  • They look good. Admit it, it’s much more attractive to have this little mushroom in your plot than it is to have a buried soil temperature sensor.
The TOMST TMS4 can measure from -40 to +60°C, so that should be sufficient for most use cases

Some drawbacks, unavoidably:

  • Accuracy: as with most cheap sensors, the accuracy is not super high; I usually work with trusting it at 0.5°C. However, especially aboveground and on sunny days, there could be MASSIVE errors on the temperature readings, as the sensor heats up (see Maclean et al. 2021). As with all cheap sensors, extreme caution is thus warranted for interpretation of air temperature measurements. Soil temperatures shouldn’t have that issue. If you want to avoid this, you should work with small thermocouples, which don’t heat up (much) in the sun as they are so small. These are usually substantially more expensive, however. I heard of development of such a sensor within a similar price range, but haven’t seen it commercialized yet.
    The sensors come with optional solar shields, yet these don’t solve the issue (except that they are at least standardized, which is a great jump forward compared with homemade shielding). I especially am not that big of a fan of the lowest shield and prefer installing the sensor sufficiently deep so the middle-temperature sensor is just below the soil surface and as such avoids solar radiation. Here again, however, there is a risk of comparability with other studies, so it is tricky. Note also that having a different installation height of only a centimeter or so can dramatically change the readings on that surface sensor, as so much variation is happening close to the soil surface.
  • I’ve gotten repeated messages about read-out issues. Most of these seem to be software-related and TOMST is working very hard at solving those, but you have to stay on top of the software updates and if your sensor doesn’t respond, there is only so much you can do yourself to find the issue. TOMST has been very helpful in solving issues, though, and I have the feeling things have improved (we had a bunch of sensors in Congo that didn’t read out over there, but I managed reading out all of them back home).
  • This brings me to failure rates: I have the feeling the TMS4 is doing better than other sensors regarding percentage of erroneous measurements, but there is still a non-trivial amount of sensors that still provides erroneous data (e.g. all readings at -100°C, or sudden outliers of +80°C).
  • As for all sensors, you have to buy a reader as well. The TMD-adapter is the price of one sensor (so not better of worse than for the others, but you shouldn’t forget about it and it adds up if you can only buy a few sensors).
  • Visibility: the TMS4 sticks out of the soil. This makes it prone to damage by animals (e.g. wild boars are horrible). This can be solved by installing a metal wire frame around the sensor. But it also invites vandals. The latter in its turn can be solved by installing it out of sight of most humans or putting information signs next to it. In extreme cases (e.g., roadsides or agricultural fields), you could install the sensor fully belowground (TOMST even has shorter ‘dwarf’ versions of the sensor for this goal), but be warned that you then loose the important feature of comparability with other studies. They also have a (cheaper also!) smaller version called the ‘Thermologger’ which only measures one temperature. In theory, I think you can also install this one belowground and use it as you would a HOBO temperature logger, but I haven’t tried this. TOMST affirmed me, however, that it is sufficiently waterproof for this.
  • The soil moisture measurement is not super accurate. This is a whole big story on its own, but it boils down that there are different levels of uncertainty piling up onto each other (sensor-based, calibration, installation, soil heterogeneity, weather…) which in the end result in the fact that a measurement of 20% could be anything between 10% and 30%. However (!) we do get good result when looking at patterns across hundreds of sensors, so the noise seems mostly random, and we feel we can trust relative measurements (e.g. the slope of the curve when drying out, or the difference in moisture generated by a rain event). So, care is needed, but data still has many good uses. And again, very importantly, this issue is there for virtually all cheap soil moisture sensors.
  • Sending sensors across the globe: I’ve had DHL speak up against sending more than two sensors at once due to the Lithium content of the batteries. This made shipping very difficult and/or expensive. As the batteries cannot be removed, there wasn’t much I could do about that. I now however found a small local company who claims that DHL is misguided on the matter and that it’s actually ‘not worse than shipping a bunch of laptops’, so my shipping has resumed without much extra cost. I’ve heard of most collaborators that they simply don’t declare the Lithium when shipping, which solves the issue of course as well.
  • TOMST is a small company and the sensor has become very popular. Combine that with the global shortage in electronic equipment and the end result is that delivery could not always be guaranteed. I have the feeling that these issues (e.g. the shortage in equipment) has cleared up now and the company is on top of orders again. Also, I’ve had plenty of delivery issues with iButtons as well, despite the size of the Maxim Integrated company, so these hiccups simply exist.
iButtons

Some alternatives:

  • If you really only need one temperature, you can go cheaper than the TMS4. TOMST has the thermologger for that, as mentioned above, which could be of great help! But things like HOBO or iButton can go even cheaper. For example, I recently heard about iButtons (DS1921G) at a little bit over €20 which is of course unrivaled [UPDATE: looks like they sold out, which makes sense! Now they are much closer to TMS-prices]. However, failure rate is significantly higher there so you should take that into account, and you’d have to boost the measurement interval (we often used 4 hour intervals) to limit the amounts of time you have to go read them out.
  • If you want to measure air humidity, there are some good HOBO loggers out there that can do that job for you. They have proven robust to colleagues in the tundra, yet are significantly more expensive than alternatives from iButton and Kestrel. Rumours have been positive and negative about all options, so I can’t make any hard recommendations. In any case, be careful with relative humidity values close to 100%, as these are rarely accurate (and can show things like ‘drift’ in the data).
  • If you want to measure at >2 soil depths, you could obviously simply bury your TMS sensor (3 depths) or one of the dwarf versions. However, this limits you to the specific sensor depths of those. I haven’t tried anything else, yet I asked Twitter and got some good responses. I especially like the flexibility of the UGT, which can handle a temperature profile of up to 8 depths. However, I know nothing about the price.
  • The ultimate dream is of course remote data transmission using the Internet of Things. This allows you to track sensors on a daily basis, see when there are failures, dramatically reduces data loss due to sensor malfunctions, ánd ensures you are much more on top of microweather events, which in my opinion greatly improves mechanistic understanding of what’s happening. We have been working with TOMST to develop the TMS-NB for our citizen science project www.curieuzeneuzen.be, and these are truly game-changers to me. They are not commercialized yet as it is tricky to get them to work in other countries, and your price adds up (extra hardware, SIM-card, roaming costs, database connectivity…). We have a few secondhand available, though. We have also teamed up with the group of Pieter De Frenne (UGhent) on commercializing their modular (i.e., add whatever microclimate sensor you want) IoT-connected forest microclimate sensor MIRRA. NOT available yet for real usage, though!
  • If you want higher accuracy, especially above ground, or higher temporal resolution, you should consider thermocouples. I have little expertise there myself, however. Ilya Maclean (University of Exeter) is developing ‘the ultimate near-surface air temperature sensor’ using thermocouples and is close to commercializing this, but it’s not out in the open yet.

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Citizen science – part 2

This week, we are kicking off season two of our citizen science campaign! 3000 die-hard participants (from the 4400 we had last year), will again install a garden dagger in their garden to monitor extreme weather events across summer.

So how is the weather looking at the start of this second season? For this, we can take a look at the sensor in the garden of CuriousNoses scientist Jonas Lembrechts, who keeps track of temperature and soil moisture in his backyard all year round (originally posted in Dutch on the website of the project).

‘This particular sensor works offline, which means that it has no connection to the Internet of Things but I have to go and read it periodically with a special device to retrieve the measurement data,’ Jonas said. ‘This kind of offline TMS-4 sensor is also used in the international SoilTemp network I am involved in. They collect climate data in the most remote places, from Congo to Antarctica. But also in my garden!

So during the past winter months, the sensor has been faithfully monitoring the temperature and soil moisture in his garden in Zemst. If we look back at the first three months of this year, we see that they were quite similar in terms of temperatures to what we got at the beginning of last year. Remarkable is the very warm New Year’s period at the beginning of 2022, where the soil temperature rose to as much as 9°C.

Temperature patterns in the soil in one garden in Zemst, comparing 2021 (black) with 2022 (orange)

Despite the dry and sunny weather of recent weeks, soil moisture also still seems to be at a reasonable level for the season. This is largely due to the fact that our lawns do not yet consume much water in early spring, thus tapping much fewer of the resource. Nevertheless, the stubbornly declining green line does stand out in the figure: the soil has not received a solid rainfall for a few weeks now. No surprise: March was record-breakingly sunny in Belgium!

Soil moisture patterns in the soil in one garden in Zemst, comparing 2021 (black) with 2022 (green). Note the steady decline throughout March 2022, a record-breakingly sunny month

“We are thus starting this measuring season in my lawn with a healthy soil moisture,” Jonas explains. “But since we are measuring the moisture in the upper part of the soil here, these values can change very quickly in a hot, dry summer.” For the soil moisture in their own garden, participants will have to wait a little longer: the soil sensor always needs to settle for a few weeks to get good contact with the soil.

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Soils!

Heaps of soil in the sun, that is our view this week!

A pile of highly sandy soil, which will be mixed with various amounts of pure silt and clay to create a range of soils.

We are starting a little sensor calibration experiment, where we create a variety of soils as we find in our garden experiment across Flanders to test the soil moisture sensor of our garden dagger in.

Transporting the experimental pots to our drying chambers, where they will be wetted and left to dry, while we track their soil moisture

The idea is to test how the raw measurements from the sensor (counting electromagnetic fluxes through the soil) can be converted into actual soil moisture measurements in different soil types.

Such conversions exist and are provided by the developers of the sensor, but we were eager to test this for ourselves, to get a better understanding of how the sensor work, to get a calibration specifically for the range of conditions in our project, and to potentially contribute to that global classification.

Master student Jens will spend the coming weeks installing sensors in these pots, monitoring them and analyzing the soils.

Getting pure (and world-famous) ‘Boomse clay’ at the quarry of the local rooftile company
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The tastiest sensor

Case in point that community science has so much more dimensions than we’re used to: we now have our ‘garden dagger’ microclimate sensor turned into chocolate! A tasty treat to all participants of the citizen science project who join us for the second season of monitoring.

Are we playing it dirty to pump up the love for science? Maybe! Will the participants be extra enthusiastic to take good care of their sensor over the coming summer? Definitely!

But this fits in perfectly with our philosophy that science needs to be close to the community, especially when the scientific topic of interest is so close to the community itself, as here: private gardens.

Sensor consumption ongoing

In any case, stay tuned for how our new measurement season enfolds!

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What we know about snow

We’re going to have to talk about snow. Snow is fabulous, it is unique, it is beautiful. But it also turns ecological processes and principles on their head: snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the start and the end of the growing season, and plant access to moisture and nutrients. And that critical role, which can give ecologists a bit of a headache, as snow is also highly elusive, and very tricky to measure (and not only because it is SO COLD to go out to measure in the Arctic tundra in winter).

While a blanket of snow often looks like it softens all the edges, this smoothing is far from true from an ecological perspective, especially not at the beginning and the end of the snowy season. Pictured: a sunny spring day in Iceland, just before the snowmelt takes off.

The number of studies on snow has increased considerably in recent years, yet we still lack a good overview of how altered snow conditions will affect ecosystems. In a recent review, spearheaded by Christian Rixen from the WSL Institute for Snow and Avalanche Research SLF in Davos, Switzerland – as the name suggests quite the experts on the matter – we tried for the first time to create such a comprehensive summary.

We provided a ‘state-of-the-art’ of what we currently know about the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. With topics ranging from snow effects on temperature (buffering frost, but shortening the growing season), over light (increasing reflection of light away from the earth, and darkening the vegetation underneath it) to moisture (meltwater can provide vital but also short-lived water sources), we paint a picture of how snow is often the defining factor in cold-region ecology.

Measuring temperatures above and under a rare winter snow cover in Belgium using a TOMST TMS4.

We also dive into the depths and complexities of what is happening (and will happen) with our tundra ecosystems as climate changes. Changes in snowfall and snow cover across the cold environments will be (and is) substantial, with both increases and decreases in amounts of snow. Effects of these changes are also not intuitive: less snow in winter may for example lead to colder soils as climate changes, as soils lose their insulating blanket. More snow in winter, on the other hand, generally has the opposite effect and causes warmer winter soils.

For a plant, it matters quite significantly if it spends the winter above or below the protective yet light-absorbing snow blanket.

Finally, we took a good look at the ways in which scientists are currently experimenting with snow effects. Interestingly, we found that experimental research aiming to manipulate snowmelt timing worked with much smaller changes in snowmelt than those observed over spatial gradients (e.g. across a mountain slope). Indeed, experiments managed to change snowmelt on average 7.9 days (when aiming for faster melt-out) or 5.5 days (when aiming for delays). On the other hand, spatial variation in snowmelt easily reached up to 56 days, ten times higher! Similarly, snowmelt timing in the same location over time on average differed 32 days. Additionally, great differences could be found depending on WHEN in the season snow was manipulated. Here again, the main conclusion is: snow is complicated, even to manipulate!

Spatial variability in snowmelt in a tundra landscape, showing the extreme variation in snowmelt dates (and thus the resulting differences in growing season length).

If we want to get a better hold of snow and its mysteries, we will have to ensure a better comparability between studies. In this review, we have taken the first steps in that regard, by providing an improved baseline for future studies of the influence of snow. Differences between snow study approaches need to be accounted for when one wants to generalize conclusions and, especially, when projecting snow dynamics and their impact into the future.

Snowy vista in Hjerkinn, Norway

Reference

Rixen et al. (2022) Winters are changing: snow effects on Arctic and alpine tundra ecosystems. Arctic Science. https://doi.org/10.1139/AS-2020-0058

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