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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One protocol to track them all

It was the year 2005. A group of mountain ecologists gathered in Vienna, Austria, for what would turn out to be an appointment with history. Their topic? Plant invasions in mountains! A consensus was soon reached that there was an important research gap to fill. While the overall view was, up till then, that mountains had been spared from invasion by non-native plant species, global change and increasing land-use pressures in mountains across the globe were rapidly changing that reality. However, there was very little global information on these patterns, with only a fairly recent regionally scattered literature emerging. Time was ripe, so they decided on a globally coordinated protocol. The Mountain Invasion Research Network (MIREN) was born.

The next year, the team gathered again in Oregon, and it is there that the MIREN road survey protocol saw the light of day. The idea was to monitor non-native plant species along mountain roads, with a standardized survey design in the form of a T, and repeat that survey every five years – till eternity, so one might hope – to get the critical baseline information on how quickly non-native species are spreading along mountain roads.

MIREN road survey in action on a steep slope in the Argentinean Andes near Mendoza. Picture by Maika Bilbao

Soon after, the protocol got expanded, and now it includes native species as well, allowing the study of range shifts of all plant species along elevational gradients, and the impacts of climate and roads on these, over time. In a recent paper, published in the open access journal Ecology & Evolution, we finally present the survey methodology and the summary of achievements to the world, hoping that it can become a standard monitoring tool in mountain regions across the globe.  

What we present is a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN), designed to 1) systematically quantify global patterns of native and non-native species distributions along elevation gradients and 2) shifts in these distributions arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation, in the characteristic T-shaped design. In each of these plots, presence, cover and abundance of all vascular plant species are noted down. 

Layout of the MIREN survey design. (a) Equal elevational distribution of 20 sample sites along a mountain road, of which three are selected in each region; (b) Each sample site consists of 3 plots of 2 m x 50 m, plot 1 – parallel to the roadside (starting at the first occurrence of roadside vegetation), plot 2 – centred 25 m from the roadside plot, plot 3 – centred 75 m from the roadside plot; (c) exemplary photograph of monitoring a mountain roadside in Tenerife, Canary Islands, Spain, depicting a survey of plot 1.

The protocol has been successfully used in 18 regions worldwide from 2007 to the present. So far, analyses of the data already generated salient results, both in regional studies and global assessments. For example, we found region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series – in some regions we now have three timesteps, over a 10 year period, and the 4th one will be collected this year – even more exciting results can be expected. Indeed, as the covered time frame gets longer, our assessment of species range changes will further improve. 

Regions worldwide participating in the MIREN vegetation survey along mountain roads. Red symbols indicate the founding regions from the first survey in 2007. In regions with unfilled symbols, only roadside plots, but not intermediate and interior plots in natural vegetation were sampled. For each region, the name of the mountain range, the sampled elevation gradient and the year(s) of sampling are given. Years in bold indicate that both native and non-native species were recorded, while in years with normal font only non-native species were recorded. Note that some regions did not follow the 5-year sampling frequency. In the last row, the total number of species and, in parentheses, the proportion of non-native species are summarized. 

Think all of this sounds fun and important? Perhaps you can join us!

Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. By publishing our protocol for all to read, we hope to enthuse the global ecological community to join forces with us and apply the protocol in your own region. With the MIREN protocol, you would have a unique tool in hand to monitor the impact of climate, climate change and anthropogenic disturbance on the vegetation in your mountain, with interesting patterns bound to emerge from the first sampling onwards. Feeding your data into our increasingly large database can then generate interesting comparisons about how your region compares to plant species diversity patterns in mountain regions across the world. This information can – and already does – inform conservation policy in mountain ecosystems worldwide, where some conservation policies remain poorly implemented.

Examples of roads in the landscape (a-c) and key non-native species (d-f) across a range of MIREN regions. (a) Harsh mountain climates (here the Cañadas del Teide on Tenerife (Canary Islands, Spain) have traditionally been seen as an adequate barrier against non-native plant invasion; (b) the direct local impact of roadside disturbance on mountain plants is visible on native Azorella cushion plants along a road in the dry Andes near Mendoza, Argentina; (c) interactive effects of climate and land use, exemplified by dramatic differences in snow cover on versus beside a mountain road in northern Norway; (d) Taraxacum officinale, one of the most widespread non-native plant species along MIREN mountain roads, in a sample plot on a volcanic gravel slope in the Argentine Andes; (e) non-native Verbascum thapsus on a roadside in the highly invaded lowlands of the Andes in central Chile; (f) Trifolium pratense in northern Norway, where the species is rapidly moving uphill along mountain roadsides.

Reference: Haider, S., Lembrechts, J.J., McDougall, K., Pauchard, A., Alexander, J.M., Barros, A., Cavieres, L.A., Rashid, I., Rew, L.J., Aleksanyan, A., Arévalo, J.R., Aschero, V., Chisholm, C., Clark, V.R., Clavel, J., Daehler, C., Dar, P.A., Dietz, H., Dimarco, R.D., Edwards, P., Essl, F., Fuentes-Lillo, E., Guisan, A., Gwate, O., Hargreaves, A.L., Jakobs, G., Jiménez, A., Kardol, P., Kueffer, C., Larson, C., Lenoir, J., Lenzner, B., Padrón Mederos, M.A., Mihoc, M., Milbau, A., Morgan, J.W., Müllerová, J., Naylor, B.J., Nijs, I., Nuñez, M.A., Otto, R., Preuk, N., Ratier Backes, A., Reshi, Z.A., Rumpf, S.B., Sandoya, V., Schroder, M., Speziale, K.L., Urbach, D., Valencia, G., Vandvik, V., Vitková, M., Vorstenbosch, T., Walker, T.W.N., Walsh, N., Wright, G., Zong, S. & Seipel, T. (2022). Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients. Ecology & Evolution, 12, e8590. https://doi.org/https://doi.org/10.1002/ece3.8590.

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What’s up, vegetation science?

If I had some ideas about the emerging challenges for vegetation science, they asked. I sure did! If I wanted to join a virtual workshop with 21 other early-career vegetation scientists to discuss those challenges? You bet!

It was a very ‘2020’ kind of thing the Young Scientists of the International Association of Vegetation Scientists (IAVS) proposed. As Covid had effectively brought social gatherings to a standstill, opportunities for scientific brainstorming as often happen over coffee-and-cake at conferences had taken a big hit. A blow for new scientific ideas and research avenues, for sure. The IAVS Young Scientists figured that this issue had hit the next generation of scientists the hardest: even in the best of times, it was hard for a young scientists to get their good ideas heard. Nevertheless, it is the young ones from now who would be answering the scientific questions of the future.

Now, we would let our voices and ideas be heard, pandemic or not! We gathered – on Zoom, of course – with 22 young and enthusiastic vegetation scientists from a wide range of backgrounds to perform our Horizon scan. Each of us submitted their own idea of what they thought was the next big research avenue for vegetation science, the sub-field of biology that studies the ecology of plant communities.

Word cloud of the recurring topics coming out of our horizon scan for vegetation science. ‘Vegetation’ is there, of course, but you can see terms like the ‘monitoring’ of ‘change’, the ‘dynamics’ and ‘climate’ pop out big, highlighting how vegetation science will increasingly have to move from what vegetation is and how it can be conserved, to what vegetation can be and can become in a rapidly changing world.  

Our horizon scan took place in the form of a two-day online workshop held in October 2020. Of the 24 topics originally proposed and discussed by participants, 15 topics were ranked as the most emergent and impactful for vegetation science.

This week, the outcome of this fun two-day workshop got published in the Journal of Vegetation Science (where else would you want it, right?). In this contribution, we present the selection of 15 topics that were ranked by our workshop participants as the most emergent and impactful for vegetation science.

Fifteen topics considered to be emergent and most impactful by the horizon scan for vegetation science. Each topic was identified to contribute to at least two of the goals we recognized for the field (i.e.: to understand processes, describe patterns, integrate different knowledge systems and communicate science); the goals are represented as symbols (see legend in the lower right corner), so that the outer part of the graph shows, for each topic, its contribution in terms of specific goals. Different colours indicate the different ways that each topic can develop in the field (i.e., developing new frontiers and data types, improving predictions, or advancing research and policy-making).

The topics contain methodological tools such as next-generation sequencing, plant spectral imaging, process-based range models and resurveying studies, and permanent plots, which we expect will need to be integrated into vegetation science to lead it into the future.

Overarching, there is the looming impact of global changes, for which we stress the need to integrate long-term monitoring, the study of novel ecosystems, below-ground traits, and pollination interactions, and the creation of global networks of near-surface microclimate data.

Finally, we also emphasize the need to integrate traditional forms of knowledge and a diversity of stakeholders into research, teaching, management, and policy-making to advance the field of vegetation science, a research field that will more and more be intertwined with society as a whole as natural areas remain under pressure.

Much work to do, we believe, as nature is increasingly under pressure by climate and other global changes. We hope that our horizon scan can help identify the ways forward to tackle the issues that are and will come. But most of all, we hope it can become an inspiration, and energize ecologists and vegetation scientists, especially the young ones, with the knowledge that their work is of uttermost importance to save our planet.

The fern ‘Asplenium scolopendrium’ growing at the bottom of a large cave in France, a symbol of the complexity and resilience of vegetation

Reference: Yanelli et al. (2022) Fifteen emerging challenges and opportunities for vegetation science – A horizon scan by early career researchers. https://doi.org/10.1111/jvs.13119

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The Light Fantastic: Summoning Ghosts from the Past

Cutting-edge modern technology has brought us so far that scientists can now find ghostly prints from former human activities with breath-taking accuracy. Ghosts from the past, that is, and that modern technology is called LiDAR (light detection and ranging).

LiDAR feels like a magical way of looking at things and revealing hidden artefacts. It is basically a laser scan of an environment with extreme precision (often up to centimetres in accuracy), which allows us to recreate environments such as forests in 3 dimensions. LiDAR scans can be made from the ground or from the air, and in its simplest form consists of sending out a laser beam, The Light Fantastic, and capturing it again when it bounced back from an object.

The magic of LiDAR. Top left, a: principles of laser scanning from the air. The lower panels (d, e) visualize a cloud of raw LiDAR points extracted from both a stationary terrestrial LiDAR system and a drone, covering the exact same study area in the Aigoual forest (France). Upper-right panels (b, c): basic principles of time-of-flight vs. phase-shift LiDAR.

In a new review paper recently published in Journal of Ecology, we summarize the exciting potential of LiDAR for forest research. Indeed, when we can map a forest in 3D at the centimetre scale, we can find back structures that are impossible to see with the naked eye, and that hide former land uses, management practices or impacts of climate change.

An impressive example of this potential can be seen in the Compiègne forest, in northern France, where LiDAR data allows us to trace back hidden structures in the forest all the way to the Roman times, much and much further than historical maps can ever do.

An example of digging up ghosts from the past using aerial photography (1937-2000), old maps (18th-19th century) and finally LiDAR data to go back to antiquity. LiDAR scanning of the forest floor shows typical patterns of agricultural activities from the Middle Ages (bottom left), as well as linear microreliefs corresponding to a network of Gallo-Roman agrarian fields and secondary roads (bottom right). Data coming from a flight with an airplane over the forest in February 2014, getting a 3D image with on average 12 points per m²!

While digging up such ghosts of the past is obviously extremely fascinating, it has also important consequences for ecology; the main point we want to hammer home in this new paper. Indeed, such past management practices and land-use changes have big impacts on current species distributions. Basically, they can explain why you found certain plants in certain – sometimes weird – spots. Some barley on the forest floor? Perhaps there has been a medieval farm there!

These confounding effects of past land use can obscure the impacts of ongoing global changes such as climate change or atmospheric pollution on species distributions. And that is exactly why it is so critical to know about them. For example, Roman agricultural practices can still result in elevated nutrient concentrations in a forest soil, with consequently a higher presence of nitrogen-loving species in the forest understory. Without the technology to look back that far into the past, the presence of these species might mistakenly be attributed to nitrogen-deposition from the air during the 1980s, overestimating the impact of the latter on forest diversity.

Given how forest cover is increasing in Western Europe (France has seen its forest cover double since the 18th century!) there is bound to be a lot of historical artefacts and past land use hidden underneath our forests. Knowing these patterns will be critical for smart management decisions. Now LiDAR is there to reveal them.

LiDAR data (obtained on the left via aircraft, drone or terrestrial laser scanning) can be used to assess micro-topographic variation (e.g., skid trails) and forest structure (e.g., vertical layering of vegetation) at a landscape level, and thus highlight legacy effects still affecting the current composition of understory plant communities and their responses to macro-environmental changes through time-lag dynamics. For instance, it is possible to not only capture the imprints of historical forest management practices (e.g., ancient coppice-with-standards converted to high forests after World War II or the more recent intensification of heavy vehicles’ traffic to harvest timber) but also to unveil past land uses (e.g., ancient settlements or agricultural fields).
Image
The past can be hidden in forests in surprising ways: this lush green cover of quaking sedge (Carex brizoides) in the French Morman forest, for example, could be an important sign. Indeed, this species was well known in World War I, when it was used by German soldiers to make their mattresses. As a typical species from Central Europe, populations like this in France might very well have been established there unknowingly by German soldiers during the war. Picture by Jonathan Lenoir.

Reference:

Lenoir et al. (2022). Unveil the unseen: Using LiDAR to capture time-lag dynamics in the herbaceous layer of European temperate forests. https://doi.org/10.1111/1365-2745.13837

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Global maps of soil temperature

In a new paper just published in Global Change Biology, we provide the first-ever global maps of soil temperature (0 -15 cm) at a 1 km² resolution, based on the global SoilTemp database of over 8500 in-situ soil temperature time series. We show that over the year, soils in cold and/or dry biomes are on average 3.6°C warmer, whereas soils in warm and humid environments are 0.7°C cooler, than shielded air temperature at standard height (1.25 to 2 m) as measured by weather stations.

SoilTemp has done what it hoped to do from the start: it brought together over 400 scientists and their over 8500 soil temperature time series from across the globe. This humongous collaboration has now resulted in a first and much-anticipated global product: global gridded layers of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. Free for all to use! I can’t emphasize enough how big of a game-changer this can be: now, finally, ecologists working on any pattern or process in, on, or close to the soil surface can use global temperature data that are representative of the soil conditions. 

That such a correction is far from trivial is shown by the mind-boggling numbers in the paper. First of all, we show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons: a 20°C (-10 to +10°C) range across the globe! Over the year, soils in cold and/or dry biomes, such as tundra, boreal forests or subtropical deserts, are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments, such as tropical rainforests, tropical savannas or temperate forests, are on average slightly cooler (-0.7 ± 2.3°C). We also show a significant reduction in the spatial variation in temperature in the soil in cold and cool biomes (and a slight increase in warm biomes). All this implies that soils will warm differently than the air as climate warms. How big that discrepancy will be, that’s a question up for future research, and a challenge SoilTemp is very happy to take up!

Mean annual air (light grey) versus soil (dark grey) temperature across the globe (left) and in each of the worlds’ major biomes (right). Especially in cold regions, soils are annually clearly warmer than the air.

Global maps were created by first calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land. Models, based on machine learning algorithms that linked the offset to predictor variables, come with maps of where predictions are most consistent (top) and where the model is extrapolating (bottom). This way, you can verify model quality in your area of interest and mask regions with higher uncertainty.

Standard deviation (top) and interpolation score (bottom) of our global machine learning models, highlighting regions where our results are still uncertain and more data is thus especially welcome

We hope these maps can mean a major leap forward and finally open up microclimate research to the global scale. But are we done now? Far from! SoilTemp has many other cool things up its sleeve. We are hoping to increase our spatial and temporal resolution, for example, and are working hard to fill the remaining gaps in our global data coverage. Global microclimate networks, it’s still the dream!

The database also has great potential for improving our mechanistic understanding of microclimate across the globe. Most of all, however, we are hoping for a massive surge in applications: if people actually start using our global microclimate products in their ecological analyses, then SoilTemp has achieved what it most dearly wanted.

Reference

Lembrechts JJ, van den Hoogen J et al. (2021). Global maps of soil temperature. Global Change Biology. https://doi.org/10.1111/gcb.16060

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A freshly-minted PhD

Now, that’s what they call a milestone: The3DLab got to celebrate its very first PhD, this week. Charly Géron successfully defended his thesis on plant invasions in urban environments!

What a beauty: Charly’s PhD thesis, all printed and finalized

The defence brought us on a cold and sunny winter solstice to Gembloux in Wallonia, southern Belgium, his home university. There, we could have a covid-beaten version of an in-person defence, where he walked us skillfully through the many investigations he performed to get to the core of that very important question: how are urban environments facilitating plant invasions?

Gembloux AgroBioTech looking particularly dashing on this first day of winter

With that, four years of rigorous research comes to a close – a bittersweet feeling lightened up by the fact that I got to wear a toga for the first time! We’re going to miss Charly in the team; the plant expert, the unstoppable pursuer of goals.

He has made our lab a better lab, and contributed to the worlds’ knowledge: indeed, non-native species from warm origins preferably invade urban environments in Western Europe, while their cool counterparts stick to the countryside. Interestingly, they all suffer when it gets warm, though, a bit of an unexpected find. Finally, it turns out there are some signs of local adaptation to urban conditions, yet mostly there is a lot of plasticity (plants just ‘changing shape’ when conditions shape), and environmental maternal effects (mother plant performance deciding how they offspring will perform, for example through the size of the seeds).

Charly’s work opened a whole new box of research questions, as all good science should!

Me in my toga

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