And there you are, in the middle of nowhere, face to face with a snorting reindeer charging straight at you. Of course, not all fieldwork days looked like that; mostly we were just surrounded by small Arctic plants, which are substantially less intimidating.
We were in Abisko (northern Sweden) to study snowbed communities. Seventy-five years ago, the botanist Olav Gjærevoll did plant surveys in snowbeds all across the area, and we wanted to compare his findings with the communities we find nowadays, considering the impact of climate change. On top of that, I am using satellite data to understand how the melt characteristics of each snowbed have changed over the last decades. This brings us to the methods! Nine satellite pixels of 10 × 10 m were chosen per snowbed, and within this area we randomly surveyed five plots of 0.5 × 0.5 m, documenting the species and their abundances.
So, what did a fieldwork day look like? It really depended on the day and the mountain. Three snowbeds were surveyed on Nuolja. We would take a ski lift to get higher up and then hike further to reach the right snowbed. There we would stand in the middle of the snowbed and throw four sticks to randomly select the placement of the plots. We worked with a great team, and each pair surveyed one plot, working together and sometimes struggling to identify the many tiny sprouts…
It was super cool: we were often so focused on these tiny plants that we forgot we were on a mountain with the best view in Sweden!
This was, however, not the case when it started pouring. We were wet through and through, with nowhere to go! Very much aware of our location…
One time we went to Laktatjakko and left the trail, leaving all hikers in the area behind. The coordinates led us to a beautiful place; I even got tears in my eyes to be there. A spot where, perhaps, since Olav Gjaerevoll no other hikers had been. A rare fieldwork day in the sun! The season had been mostly cloudy, so the sunshine felt like a nice surprise. While we were working, a reindeer ran toward us and we had no idea what it would do. But it was not charging at us; it was heading for the herd behind us. She got separated from her calf, and they reunited right before our eyes.
After collecting all the data, we made camp close by, eating pesto pasta and listening to fun stories. That was the most plant-diverse and memorable snowbed we visited.
Now, after two amazing months in Abisko, it’s time to analyse the data. It is difficult to understand how snowmelt patterns have changed under the influence of climate change, but I hope to find a correlation between the change in snowmelt timing and the communities we find per pixel. Even though it would be the worst-case scenario, we expect to find less species-rich communities at pixels where snowmelt has shifted over the last decade.
This research could serve as an extra argument that climate change negatively influences biodiversity, even in environments that seem less affected by rising global temperatures.
A super cool project that is currently taking place in Zeeland is the Groene Revolutie (translating to Green revolution) organized by IVN Zeeland. The goal? To greenify all school yards within one school generation!
Currently, many school yards are characterized by monotonous tiling with very little greenery. Not only does this create a rather uninspiring, non-imaginative location for kids to play and learn, but it also turns schoolyards into heat traps during summer, with little room to escape the heat. A striking example was shared by a teacher who saw kids seeking shelter from the heat underneath a ping pong table. A greener schoolyard creates a more interactive environment to learn from, as well as a place where kids can actually relax and play during summer.
The Green Revolution, doing what it does best: bringing green AND fun to formerly grey playgrounds!
To measure the effects of this greening, we (Kyra and Olivia) visited multiple schools to conduct both microclimate and biodiversity monitoring. Depending on the stage of the school’s greening journey, we carried out either baseline measurements (before greening) or follow-up measurements (after greening).
Sensors & biodiversity monitoring
Microclimate sensors were installed at locations that would be greenified to see how temperature and moisture levels change. Sometimes a bit tricky, as you can’t exactly place a sensor in a tile! Kids also helped us find suitable spots for the sensors. At schools that had already been greenified, some sensors had gotten lost during the process. Therefore, we sometimes had to reinstall sensors at their original locations.
We measured biodiversity using a grid, recording the different plant species and their coverage in different parts of the schoolyard. Even the youngest children, who did not take part in the lessons, where curious about what we were doing and came to look at the different plants in the grid. They were very eager to help us look for new spots they thought we should measure, including one area where they claimed to have found 100 plant species!\
From grey to green – the various shades of those playgrounds as seen through our monitoring project
Teaching
Besides doing the monitoring, we also gave lessons to the kids, where we not only explained the topics we study but also did activities to bring the theory to life: installing sensors together, looking for soil life, or searching for plants in the schoolyard. An extra bonus of teaching is that it makes kids feel more involved in the science, for example by feeling responsible for keeping the sensors safe. We would love to highlight two of the lessons we gave.
Plant biodiversity
For children aged 9–10, we went on a mission to discover plant diversity in their own schoolyard.
The children first investigated a potato plant growing in a small pot and discussed what plants need to thrive; sunlight, water, nutrients and enough space to grow. This sparked a conversation about how removing paving stones from schoolyards can create more space for plants and provide a valuable habitat for insects, in which some schools already succeeded as a result of the recent greening projects.
Equipped with a map of the schoolyard and the ObsIdentify app, the children searched for as many different plant species as they could find, where they observed that even their schoolyard can have a large variety of plant species.
Along the way, some children came across the anise hyssop (Agastache foeniculum and were especially excited to discover its unique smell of mint and liquorice. The Chinese fountain grass (Pennisetum alopecuroides) also sparked interest due to its Dutch name; Lampenpoetsergras, which literally translates to lamp cleaner grass, something they found very funny.
Soil life
For children aged 6-8 and 11-12 we went on the hunt for soil fauna to discover what species live in the soil of schoolyards. First, we brainstormed about different species living in the soil and the important work they do; breaking down organic matter, providing nutrients for plants and helping to keep the soil healthy. We also discussed microclimate and how local temperatures can vary across their schoolyard. We asked where they would look for shelter during a heatwave and how these locations often overlap with the places where soil life likes to hang out. After the heated-discussion (quite literally!), it was time to go outside and look for small creatures to put in their magnifying glass jar.
To start off, the kids created a nice little living space for soil life in their jars, filling them with soil and leaves. Once the mini-environments were ready, the hunt could begin! Some started to dig and stomp the ground (mimicking the rain) to look for rain worms, while others decided to look underneath tiles and planters, finding, to their amazement, many centipedes and isopods. Ants, slugs, spiders, and shiny beetles were also collected. One kid even managed to catch a bee (although not officially part of the soil life). During the search for insects the children also discovered a larva of the harlequin ladybird, or multi-coloured Asian lady beetle (Harmonia axyridis). One child asked us whether it had come all the way from Asia for its holiday, which was a funny, and very smart question that led to a conversation about how species can spread to new places.
Another great moment was with a child who initially seemed a bit hesitant to touch the ground, only digging with a small twig because she saw soil as something dirty. After some encouragement to join the digging session with bare hands, showing how nice it actually feels and explaining that you can always wash your hands afterwards, it was lovely to see that by the end of the lesson, she had her hands completely covered in soil and was smiling (one second later, followed by a high five with equally soil-covered hands). It felt like a small victory in helping someone feel more connected to nature and see soil as something other than just “dirty”.
And an extra bonus: all the schools can access their own schoolyard’s microclimate and biodiversity data, allowing them to track changes over time and continue collecting more data!
Once you have gone through the effort of collecting a global database, you can start playing with it. And one of the most fun things to play with, I’d say, is general ecological theories – the kind that you would think hold everywhere, but that usually play out differently depending on where and how you test them. We’ve done a few of those with our MIREN plant survey database from along mountain roads, and here’s another important one, just published in the Journal of Vegetation Science (Buhaly et al. 2026).
This time, the theory on the chopping block is biotic resistance: the old and intuitive idea, going back to Elton in 1958, that a diverse, well-established native community should be harder for a newcomer to break into. More species already occupying the available niches, competing for light, water and space, should mean fewer open doors for a non-native plant trying to move in. It’s one of the most-cited explanations in invasion biology, but it rests on the assumption that competition is what dominates plant-plant interactions. And we’ve known for a while that this assumption gets shakier the harsher the environment gets: in stressful places, facilitation (plants actually helping each other, via shelter, warmth or moisture) tends to take over from competition. High-elevation, alpine environments are about as stressful as it gets. So does biotic resistance survive the trip up to the treeline and beyond?
The scenery of this paper – one of our Norwegian mountain roads
Testing an old idea
Together with the whole consortium, and led by Meike Buhaly, we used our MIREN road survey data to find out, using 15 mountain regions on six continents. At each site, a plot runs along the roadside, and a second one starts 50 m off the road and heads into the (semi-)natural vegetation behind it, the same paired design we’ve used since 2007, and that has featured oftentimes on this blog here. On top of that, we (well, mostly the lead author team in Germany, I just collected the leaves) built a proper trait dataset, with nearly 1,500 leaf samples, run through a near-infrared spectrometer back in the lab, to calculate not just how many native species a plot holds, but how functionally different those species actually are from one another.
Spelling out our expectations for this paper, based on conflicting theories: in Hypothesis 1 (H1), we expected that at low elevations, fewer non-native species would be found in communities with high native diversity due to competition. We hypothesized the opposite at high elevations (H2), with diverse native communities facilitating the establishment of non-native species. In Hypothesis 3 (H3), we anticipated a steeper slope of the relationship between non-native species richness and native diversity in natural habitats. Additionally, in Hypothesis 4 (H4), we hypothesized that the ratio of non-native species in natural versus disturbed roadside habitats would be higher in high-elevation environments than at low.
No resistance from richness – sometimes the opposite
The graph supporting the conclusions here. A bit counterintuitive: the y-axis shows the slope of the relationship between natives and non-natives. Positive values suggest more non-natives in species rich plots, which we unexpectedly see happening at low elevations (top panel). At high elevation, the relationship is neutral rather than positive. For functional diversity (bottom panel), the pattern is very different
The short version: using native species richness as the classic proxy for biotic resistance, the expected resistance pattern didn’t show up anywhere in this dataset. If anything, it was reversed at low-to-mid elevations, where non-native richness was consistently higher with native richness. This was true, unexpectedly, both at the roadside and in the natural vegetation, plausibly because species-rich, structurally complex lowland communities simply offer more niches and microsites, for natives and non-natives alike, than their species-poor counterparts.
Looking at functional diversity told a different story, however. At low elevations, functionally diverse natural communities did host fewer non-natives – that’s one piece of actual biotic resistance we did find! But climb the elevation gradient, and that relationship weakens, then flips: at the highest elevations, functionally diverse native communities host more non-native species again. Exactly what you’d expect if facilitation, not competition, is running the show up there, as has been shown before for native cushion plants acting as “nurse plants” for exotic invaders in the high Andes.
So: some evidence for biotic resistance at low elevations, when using functional diversity, but overall a fairly strong case for the opposite to be happening.
Going back to Norway 2012
Then, at the end of the paper, there’s a part that I am a big fan of personally. Back in 2012, as a master’s student doing the first MIREN survey in northern Norway, I found that the ratio of non-native to native species in the roadside – compared to the untouched vegetation right behind it – increased steeply with elevation. My reading at the time: weaker resistance up high lets a disproportionate share of whatever non-natives do arrive spill off the road into the natural vegetation. That finding did get published, in my first ever peer-reviewed publication, but I always felt a bit hesitant. I trusted the pattern and process, but I felt like we just didn’t have enough data – very low invasion levels in Norway – to confidentially accept the claim as proven.
The global dataset now shows that this ratio does indeed climb toward high elevations, as we saw in Norway. However, it’s not a simple upward slope. It’s a U: the ratio of non-natives in natural vegetation relative to the roadside is highest at both ends of the elevation gradient (around 0.6 at each extreme), and dips in the middle. The high-elevation arm of that U is the one I stumbled onto in Norway — non-natives that make it up the road managing to spread into the surrounding alpine vegetation surprisingly easily, either helped along by exactly the facilitation signal described above, or by an overall reduction in interactions (my reading). The low-elevation arm is a different story, though: lowland sites are where most non-natives arrive in the first place, have had by far the longest time to build up a presence, and can draw on a far bigger regional species pool, so plenty of them eventually work their way off the road there too, just through sheer numbers and time, and regardless of the resistance levels.
The famous U-shaped graph of the ratio of non-native species in the natural vegetation versus the roadside
Which also explains, rather neatly, why my Norwegian roads never showed that low-elevation bump: Norway’s cold climate, isolation and modest regional species pool have always made it something of an outlier when it comes to that kind of long-term, low-elevation invasion build-up. What I picked up on in 2012 was thus really just one half of a much bigger, two-sided global pattern, and it took fourteen years and a lot of collaborating mountains to see the other half. Glad!
The native Angelica archangelica in a Norwegian roadside
Reference: Buhaly, M., Turner, S.C., Kreuz, N.K., Vandvik, V., Veltmann, B., Alexander, J.M., Lembrechts, J.J., et al. (2026). No signal of biotic resistance to non-native species establishment in high-elevation communities. Journal of Vegetation Science, 37, e70174. https://doi.org/10.1111/jvs.70174
For decades, climate change ecology has mostly been a story about shifts: species moving upslope, poleward, tracking the climate they’re adapted to as it slides out from under them. It’s one of the best-documented fingerprints of warming in nature.
What we’ve been much worse at showing is what happens at the far end of these shifts: actual extinction. Not “the range is contracting”, but the species being gone, locally, for good. That’s surprisingly hard to prove, and that for two good reasons. First, a single before-and-after comparison – the kind most historical resurvey studies rely on – have a hard time telling a real decline apart from population fluctuations or missed observations; you need repeated resurveys over time, at the same place, to separate signal from noise. Such standardized long-term surveys are rare. Second, alpine specialists are tough, long-lived plants that respond to a changing climate with a considerable lag, so a species can be quietly suffering in silence for decades before it actually disappears. So even though we’ve had every reason to expect that warming is pushing cold-adapted specialists off the top of mountains, actually catching that happening – at scale, and in relation to how much a place has warmed – has remained tricky.
In a new paper out this week in Science, driven by Johannes Wessely, Stefan Dullinger, and a long list of GLORIA colleagues, we finally got to prove what everyone already feared.
Where we looked for extinctions. The map shows the 16 mountain regions in our study, with circle size showing how much local extinction we found there – bigger circles, more species lost. On each of the 62 summits, researchers return to the same 16 permanent 1×1 m plots every seven years, arranged just below the peak (right), so we’re always comparing exactly the same patch of ground over time.
The reason that I – as an ecologists from the ‘lowlands’ – am so drawn to the mountains for my research, is that these mountains are close as we get to a clean experiment. The mountain summits we looked at here experience very little land-use change, no fertilization, none of the usual confounders that make biodiversity loss so hard to pin on any one cause. The GLORIA network has resurveyed the same 1×1 m plots on 62 summits across 16 European ranges every seven years since 2001, resulting in four surveys, 21 years of data from 896 permanent plots. If a species disappears from a mountaintop, warming is one of the few plausible suspects left.
High-elevation plants, like this Gentiana, are increasingly under pressure
Summit plant diversity has been rising for years, as lowland species colonize newly hospitable ground. We knew that, and that obviously remains true. But behind that increasing richness, local extinctions have been rising too. What’s more: these extinctions are getting faster with each survey, and this at every scale we checked: plots, summits, whole mountain ranges. Richness went up because colonization outpaced extinction, but that fact was hiding the losses. And what we are loosing, unfortunately, are exactly the cold-adapted specialists that make high mountains botanically unique.
Extinctions on the rise! Each dot is one mountain summit, showing what share of its species disappeared between one survey and the next. Color shows how much that summit had warmed till then – yellow is more warming, purple is less. Two things are important to note here: dots (and the trendline) clearly get higher over the three survey periods, and the warmest summits tend to sit toward the top.
Importantly, what predicted these extinctions was more than just time. Where the paper gets scarily elegant is where it shows that these extinctions truly correlate with how much a summit had actually warmed. Every extra 0.1°C over the preceding 14 years came with a measurable rise in extinction rate, and warming actually explained far more of the pattern than time alone. Species were also more likely to disappear from their warm, low-elevation range margin, and from communities shifting hardest toward warmth-loving species. Good to know, perhaps, as well: a preceding decline in cover was – while noisy – an early warning signal of extinction.
An extinction debt coming due?
Alpine specialists are tough, slow-growing, long-lived and thus often lagging behind the changing climate. That raises an uncomfortable possibility: what we’re seeing may be the first instalment of an “extinction debt” built up over decades of past warming. Now, that extinction debt is starting to be paid, which means that more losses could already be written in stone.
We’re not claiming climate change is the biggest driver of biodiversity loss everywhere; land-use change and nitrogen deposition still dwarf it in most human-dominated landscapes. But on summits, where those confounders barely exist, the fingerprint of warming on real local extinctions is now about as clear as it gets. And it’s growing. Measurably.
I’ve spent over a decade now sticking small microclimate loggers into the ground, mostly to talk about temperature. Soil moisture has always been the awkward third wheel in that story: TOMST loggers measure it too, our CurieuzeNeuzen in de Tuin citizen-science project collected it by the thousands, and yet I’ll be honest – until recently we had done remarkably little with it. Soil temperature is intuitive, comparable across studies, and (relatively) forgiving. Soil moisture is none of those things. It depends on soil type, on calibration, on what exactly you mean by “moisture” in the first place, is extremely variable and rarely statistically ‘normal’. So it sat there in our growing database, a bit unloved and ignored.
CurieuzeNeuzen in de Tuin citizen scientist collecting a soil sample, next to their TOMST TMS-NB ‘garden dagger’
That changed, fortunately, when the hydrologists at the Vrije Universiteit Brussel came knocking with a very interesting question: can our garden sensors tell us anything about groundwater?
Borrowing eyes from a different field
The premise of the collaboration (now published here!) was nicely elegant. They had already built and run mHM, a proper physically-based hydrological model, for the whole of Flanders. The kind of model that needs detailed climate forcing, soil maps, land use, and a fair chunk of computing time, and that spits out things one actually cares about for water management: groundwater recharge, evapotranspiration, degree of saturation. Variables for which you cannot simply stick a sensor into the ground and read off directly at the same low cost we do for temperature and soil moisture.
Meanwhile, we had thousands of CurieuzeNeuzen in de Tuin loggers with two summers of near-continuous, low-cost, noisy, wonderfully abundant soil moisture and temperature readings, measured in places a hydrological model would never normally get near: backyards, parks, the occasional forgotten corner behind company head quarters.
We got thousands of temperature and soil moisture sensors, which have up till now been used only for half their potential.
The question the VUB team asked was basically: if we feed a machine learning model nothing but our sensor time series – no rainfall, no radiation, no coordinates, just the lags, rolling means and differences of what the sensor itself reports – can it learn to reproduce what the full hydrological model would have said for that spot? In other words, how much hydrology is already implicitly encoded in a humble soil moisture logger, once you look at it the right way?
Where it all happened: the coloured speckles are individual CurieuzeNeuzen in de Tuin sensors scattered across Flanders, with the three test areas from the paper zoomed in — the whole region, the Demer sub-basin, and the small independent test site in Boechout.
The answer: quite a lot, especially in bulk
Using LightGBM (a fast, tree-based algorithm, chosen after testing a handful of competitors), they could indeed emulate mHM’s estimates of groundwater recharge, evapotranspiration and degree of saturation reasonably well at most sites, capturing the difference between the miserably wet year of 2021 and the properly dry year of 2022, catching the seasonal rhythm, keeping bias low. Not perfect, and definitely not a replacement for the real model (the paper is quite upfront about that), but good enough to be genuinely useful as a diagnostic and extrapolation tool.
One of our better sites: our sensor-based machine learning model (green) tracking the “real” hydrological model’s groundwater recharge estimate (orange) almost peak for peak, in both a wet year (2021, left) and a dry one (2022, right). Not every garden did this well, but this is what it looks like when it worked out nicely!
The part I find most interesting, though, is the following: on their own, individual sensors are a weak signal for this kind of hydrology – a single logger in one garden tells you a bit about that garden, yet very little about regional groundwater dynamics. Not a surprise there, as we knew the soil moisture signal was messy and hard to trust. But once you start aggregating across many sensors, the picture sharpens considerably: the density experiment in the paper shows that as more sensors get pooled together, the bias in the estimate stabilizes and the noise from single quirky locations melts away. It is, in the most literal sense, a case of the network being worth more than the sum of its parts. That’s reassuring to see in print, as that was the point I had been making about these sensors all along!
Pool just a handful of sensors (left side of the graph) and the bias estimate varies wildly depending on which ones you happened to pick (the shaded bands are wide). Add more sensors moving to the right, and average them together, and that uncertainty collapses, even though the mean bias barely moves. One noisy garden sensor tells you little; thirty-five of them, averaged, predict the truth.
There’s a nice practical postscript too: when the model, trained purely on 2021–2022 Flanders data, was applied to an entirely independent site near Boechout (Flanders) the following year, its recharge estimates tracked the ups and downs of actually measured groundwater levels pretty well. That’s the kind of transferability test that is very welcome to see.
Why this matters (to me)
For me personally (selfishly), this paper did two important things. First, it took our soil moisture data out of the drawer we had secretly already put it in (“nice to have, hard to use”) and showed it has real value beyond microclimate ecology – groundwater managers, drought forecasters and agricultural planners could plausibly use dense, low-cost (citizen-science) microclimate networks like this one as a genuine complement to expensive physical models, especially in places where running a full hydrological model isn’t feasible.
Second, it was just refreshing to watch hydrologists do to our data exactly what we do with vegetation or temperature data: squeeze out patterns we hadn’t thought to look for. Another example of where microclimate measurements can inform other disciplines, as we have showed before for many other applications.
There is plenty left to do, of course, and the paper has a whole lists of suggestions: we had no winter data (when most European recharge actually happens), no proper soil calibration (remains a bottleneck for the TOMST sensor soil moisture data), no guarantee the same approach transfers to a different climate or a different model. But as a first demonstration that “yes, there’s real hydrological signal buried in a network of €100 loggers, if you have enough of them and someone willing to dig it out” – I’ll take it!
Can you imagine how many hours of roadside fieldwork went into this?
We’ve just published the MIREN road survey database, and the accompanying paper led together with Sylvia Haider: 170,000 georeferenced plant records, covering 6,854 vascular plant species across 3,364 plots in 25 mountain regions spanning every continent except Antarctica.
If you haven’t heard of the Mountain Invasion Research Network (MIREN) yet, now is the time to pay attention: since 2007, a growing number of dedicated MIRENers have gone out every five years to survey the vegetation along mountain roads in their region, building what has become one of the largest standardized vegetation monitoring datasets of its kind.
Figure 1: Location of the regions that have implemented the standardized road survey protocol of the Mountain Invasion Research Network (MIREN). Pie charts are scaled by species richness, with colours indicating the proportion of native and non-native plant species.
That massive dataset is now fully open access, with all data up to 2022 included.
If your first reaction is “wow, I wish I’d been part of that” — good news, this is your lucky day. We’re already preparing for the next round of monitoring in 2027, when virtually all of these regions (and a few new ones) will go out again to see what’s changed. Want to join with your favourite mountain region? Just send us a message!
Our 3,364 plots cover an impressive range of the world’s climatic space — though you can see mountain roads get hesitant once the “real deal” begins, with no plots in the tundra (1).
Lake Törnetrask, Abisko Research Station, Abisko, Sweden
Oenanthe oenanthe, alpine tundra Abisko, Sweden
Lake Törnetrask, Abisko Research Station, Abisko, Sweden
Laktatjakka valley
Lake Torneträsk, Abisko, Sweden
Lake Torneträsk, Abisko, Sweden
Trifolium repens
Lake Torneträsk, Abisko, Sweden
Skjomen valley, northern Norway
Saxifraga aizoides, Narvik, Norway
Lake Torneträsk, Abisko, Sweden
Angelica archangelica
Luscinia svecica, Abisko, Sweden
Narvik, Northern Scandes, Norway
Summer in the Skjomen valley, northern Norway
in the Skjomen valley
Skjomen valley, northern Norway
Seen from Nuolja, Abisko
Laktatjakka valley
Angelica archangelica along mountain road in the northern Scandes, Norway
Skjomen valley, northern Norway
Narvik, Norway
Norway
Narvik, Norway
Norway
Luscinia svecica, Abisko, Sweden
Pinus sylvestris, Narvik, Norway
Little red-and-white lighthouse
Abisko, Sweden
Hallerbos 2017
Young bluebell (Hyacinthoides non-scripta) surrounded by flowers of yellow archangel (Lamium galeobdolon)
The common bluebell (Hyacinthoides non-scripta), the signature flower of the Hallerbos
Single bluebell flower surviving on a wetter spot, as indicated by the field of wild garlic (Allium ursinum)
A really wet patch of forest, with giant horsetail (Equisetum telmateia) in a field of wild garlic (Allium ursinum)
Wild garlic (Allium ursinum) in the Hallerbos flowers a bit later than the bluebells, yet this one was already in full bloom
A bumblebee visiting yellow archangel (Lamium galeobdolon)
A bumblebee visiting yellow archangel (Lamium galeobdolon)
Wild garlic (Allium ursinum)
Wild garlic (Allium ursinum)
Weirdly beautiful, the inflorescence of pendulous sedge (Carex pendula), typical for the wettest spots in the forest
Weirdly beautiful, the inflorescence of pendulous sedge (Carex pendula), typical for the wettest spots in the forest
A little stream in the Hallerbos, surrounded by endless fields of wild garlic (Allium ursinum)
The herb-paris (Paris quadrifolia), less common in the forest
Wild garlic (Allium ursinum)
Bluebells (Hyacinthoides non-scripta)
Weirdly beautiful, the inflorescence of pendulous sedge (Carex pendula), typical for the wettest spots in the forest
Another one from the wet plots: large bitter-cress (Cardamine amara)
Another one from the wet plots: large bitter-cress (Cardamine amara)
Young beech leaves, as soon as they are fully grown, spring in the understory is over
A beech forest without understory, most likely too dry and too acid for any survivors
A young beech seedling (Fagus sylvatica), looking nothing like a beech, yet everything like a tiny dancer
Young beech seedling (Fagus sylvatica)
Bluebells (Hyacinthoides non-scripta)
Bluebells (Hyacinthoides non-scripta)
Bluebells (Hyacinthoides non-scripta)
Mountain melick (Melica nutans), a grass in the most amazing green
Bluebells (Hyacinthoides non-scripta) in a rare patch of mountain melick (Melica nutans), a grass in the most amazing green
Bluebells (Hyacinthoides non-scripta)
Bluebells (Hyacinthoides non-scripta)
Montpellier 2017
The entrance to the cathedral of Montpellier
The cathedral of Montpellier
The entrance to the cathedral of Montpellier
The cathedral of Montpellier
Narcissus poetics
The cathedral of Montpellier
The botanical garden of Montpellier
The botanical garden of Montpellier
The botanical garden of Montpellier
Brackish Camargue vegetation
Brackish Camargue vegetation
Brackish Camargue vegetation
A typical lagune
Brackish Camargue vegetation
Camargue horses
Camargue horses
Camargue horses
Brackish Camargue vegetation
Brackish Camargue vegetation
Brackish Camargue vegetation
Camargue horses
Brackish Camargue vegetation
Little egret in the evening sun
Flamingo’s in the evening sun
A typical lagune
Dandelion fuzz
Grass lily
Grass lily
Dandelion fuzz
Veronica in a sea of poplar fluff
Euphorbia in a sea of poplar fluff
Poplar
Gare du Midi, Brussels
Gare du Midi, Brussels
Gare du Midi, Brussels
Gare du Midi, Brussels
Sweden autumn 2016
Autumn in Abisko
Yellow leaves of mountain birch, with lake Torneträsk in the background.
Lapporten, the gate to Lapland, in Abisko
Rain blowing over the Abisko National Park
The colours of the north: red fireweed and yellow mountain birches, with lake Torneträsk on the background
Yellow leaves of mountain birch, with lake Torneträsk in the background.
Rain on the background, the ski lift in Abisko on the foreground
The steep slope of mount Nuolja on a dramatic looking morning
The beautiful colors of lake Torneträsk in Abisko
A little stream on top of the mountain, with a view on Lapporten, the gate to Lapland
Well, that is a beautiful table with a nice view on lake Torneträsk in Abisko
Our little experiment on top of the mountain in Abisko, with a view on Lapporten
Autumn in Abisko is extremely colorfull
The ski lift with a view on Abisko National Park and Lapporten
Hiking dowhill towards lake Torneträsk
This green is greener than the greenest green: moss on top of mount Nuolja
Well, that is a beautiful table with a nice view on lake Torneträsk in Abisko
The ski lift with a view on Abisko National Park and Lapporten
The ski lift with a view on Abisko National Park and Lapporten
The most beautiful hiking trail of the world: Nuolja in Abisko
Angelica archangelica, often the biggest plant of the Arctic
The most beautiful hiking trail of the world: Nuolja in Abisko
Cirsium helenioides, the melancholy thistle
Hiking down mount Nuolja
The steep slope of mount Nuolja on a dramatic looking morning
The colours of the north: red fireweed and yellow mountain birches, with lake Torneträsk on the background
The prettiest yellow and blue: autumn in Abisko
Fireweed, Epilobium angustifolium
Campanula or bellflower, I think ‘uniflora’
Vaccinium myrtillus
Cornus suecica, the prettiest red of the world
Hieracium alpinum, alpine hawkweed
Carex atrata, one of my favourite sedges
Alpine clubmoss, Diphasiastrum alpinum
Agrostis capillaris, bentgrass
Common yarrow (Achillea millefolium)
Anthoxanthum odoratum, sweet vernal grass, fully grown and mature
Snow scooter trail
Our plot in the mids of a field of horsetails (Equisetum pratense)
Equisetum pratense
Cliff overlooking the valley with the road to Norway
Seedling of Taraxacum officinale, the dandelion, after two years of growing in bad conditions
Poa alpina, the alpine meadow-grass, with its viviparous seeds
Massive flowerhead of Angelica archangelica
Angelica archangelica
Blueberry (Vaccinium myrtillus) in autumn
A lowland marsh in Abisko in autumn
Installing the plots of our trail observations on top of mount Nuolja
Installing the plots of our trail observations on top of mount Nuolja
Tanacetum vulgare (Tansy), non-native for the high north
Autumn forest down in the valley
The valley of Nuolja to Björkliden
Summer on the Nuolja-side
A full rainbow behind mount Nuolja in Abisko
It’s raining in the west, clouds trapped behind the mountains
A strong wind blowing rain from behind the mountains to our side
A strong wind blowing rain from behind the mountains to our side
Betula nana, the dwarf birch, mini autumn forest
Betula nana, the dwarf birch, mini autumn forest
The valley of Björkliden in autumn
The valley of Björkliden in autumn
The valley of Björkliden in autumn
The valley of Björkliden in autumn
Sweden spring 2016
The valley of the lakes
Bartsia alpina
Western European species like the red clover (Trifolium pratense) here are often listed as non-native species in mountain regions.
Although the alpine zone has been harder for invasives to access than most places, human structures like trails are often an easy gateway for the invaders to get up there. Picture from Abisko, Swedish Lapland.
Melting snowpatch on a lake
Silene suecica
Rubus arcticus
A rainy hike
Trifolium repens
Cornus suecica
Dryas octopetala
Eriophorum vaginatum
Salix reticulata
Trifolium pratense
Silene acaulis
Oxyria digyna
Ranunculus glacialis
Overlooking the valley of Laktajakka
Ranunculus glacialis
Amiens
Cathedral seen from the frozen Parc Saint-Pierre
Frozen mirror
Maria without a shirt
Cathedral at night
The museum behind the beautiful gates
Just outside of Amiens
Frozen to the bone
Colourful mirror
Sun rising above the water
Winter sun on the Place du Don
Enjoying silence and the morning sun
Le Club d’Aviron in winter weather
View from my office window
Cathedral with a glimpse of spring
Amiens is filled with cute little houses
Cathedral at night
Cathedral at night
Sunny but cold, the Quai Bélu
Cold!
The southern side
House on the square before the cathedral
Sunny but cold, the Quai Bélu
Cathedral at night
Gargoyle planning to eat the cathedral
Almost cold enough for ice-skating
View from my office window
Nice architectural curve
Sweden autumn 2015
Lichen
Sweden summer 2015
View on the 1000 meter plots
Doing research on a cold Arctic morning
Plots flooded by the snowmelt
Flooded by the snowmelt
Meltwater river, racing down the mountain
After a hike, even the most basic house looks cosy. Little hut in the mountains, open for everybody
Snowbridge, maybe don’t cross…
Snowbridge
View from a cliff
Silene acaulis or cushion pink, cutest plant of the Arctic
Two seasons in one image
Steep slope
Hiking down
Narvik Kirche, church of the subarctic
Narvik Kirche
Reindeer on top of the mountain
Narvik Kirche
Summer at the church
Summer flowers
Massive waterfall
Young willow catkins
View from Narvik’s hospital, with lilac flowers
Building a bridge over the fjord will gain al drivers at least an hour
Norwegian fjord
Posing with the water, getting soaked
Minimalistic mountains
Insect investigating our reindeer antler
Catching mosquitoes with our license plate, harvest of the year!
Posing with the plot
Fieldwork on the most beautiful spot of the world
Fieldwork on the most beautiful spot of the world
Summer bridge – still next to the sadly impassable river
Rhinanthus flower in the mountains
Plateau in the valley, beautiful brown
Experimental view from my favourite plot
Salix catkins
Extremely old Betula tree
Waterfall from a cliff
Buttercup is the earliest in spring, here
Rocks!
Alpine views
Views!
Fieldwork
Jumping over rivers
Plot
Golden plover
Angry lemming
Green, the whole north is green!
Snow, so much snow left!
Minimalistic mountain moments
Fieldwork
The research center
Red clover – focal invader
Look at this tiny cute snail!
Massive floods of melting water
Bartsia alpina
Hooray, a toilet!
Dryas octopetala
Lowest elevation plots
Butterball!
That’s a lot of water
Midnight sun is the best
At the lakeside
Beautiful Bistorta vivipara
Don’t fall in the water
Midnight sun
Wild river
Art – made by ages of wild rivers
Baby firework for America’s independence day
Midnight sun at the lake
The Abisko canyon was wilder than ever
That’s a crazy amount of water!
The Abisko canyon was wilder than ever
The Abisko canyon was wilder than ever
Black and white
Stone-man overlooking Abisko
Nothing as soft as a willow catkin
Label and soil temperature sensor attached
I’d drive to the top every day
Reflections
Rocks and clouds
Brave little birch
Brewing our camping poison
Basic camping stuff
Camping in Norway
Home-made temperature houses
Roadside research at its best
Norway is crazy
Horsetail is so funny
Little creek in magical forest
Birches, birches everywhere
Beautiful rock, a gift from the river
Another roadside fellow
Lichen
Ready to rock the summer
Collecting mosses
That’s a crazy old lichen
Tiny tiny piny trees, but old, so old!
Ready to jump into the fjord?
Ready to jump into the fjord?
That’s a spiky stone!
Views on Norwegian fjords
Silene in the mountains
Cute little orchid
Skua
Attacking skua, mind your heads!
Watch out for the attack of the fierce skua!
Black snail
New plot!
Still a lot of snow to melt, but this spot was free for a new plot
Reindeer are better than people
Two seasons in one picture
Let’s see what is happening to the balance in mountains! Is this a starting avalanche, or will it last a bit longer?
Cute little hut
Climbing mountains by car
Softest moss in history
Drosera in the marsh
Hiking in no-man’s land
The clouds are coming
Abisko valley
‘Butterball’
Fieldwork in the tundra
Abisko valley
Little plot
Clouds and sun and mountains
Making soup on a campfire with a view
Little creek on high elevations
Skua on the look-out
Melting snow in a river
Rhodiola rosea and the Törnetrask lake
Beginning of spring
Flooded plots, melting snow, impassible wetness
Ferns and horsetails
Chile 2015
Lunch made by our local colleague, with funny bread (tasty as well!)
Trips to the field sites were sometimes a real adventure, especially right after snowmelt
