Early drought

Europe is suffering from extremely early spring drought. And again, as every year, our water use is back on the agenda. And it should be: water availability might become one of our society’s biggest problems. In fact, it already is: a Flemish municipality already had no water coming out of the tap at all, with even the firefighters getting in trouble to put out fires.

An extreme case, but it should serve as a warning: here in Flanders the water management is still focussed on the idea that the region is getting TOO MUCH rain. Let me tell you, if it ever was true, it is not anymore. We should stop managing our land to get rainwater removed as fast as possible. And, importantly, we should get rid of this attitude that water is an endless resource, and react surprised when we run out of it. Drought is our future, and we should all adapt our mindsets to this.


Our cities are concrete jungles where rain water is supposed to run off into the drainage system as fast as possible. Here: a non-native Buddleja next to the A12 highway, Flanders

The impact of this dry weather can be seen clearly in the trial of our drought- and heat citizen science project, running in my garden (see figure).


The current drought spell is already drying out lawns since early April, with only two little showers and one rain spell to reduce the losses. The problem is that it is still so early in the summer season and already soil moisture levels dropped extremely low. As you can see by the rainy days beginning of May, we will need more than a week of continuous raining to get the lawn water back on track. While soil moisture in the cool and shadowy spot under the shrubs (blue line) was holding on till early May, the flushing leaves of the shrubs now brings down the moisture even faster. Plants are needing all the water they can get, and not much is coming in to compensate.

And there is no salvation on the horizon: there seems to be another ten days of little rain on the way, draining the lawns even more. You might want to brace for dry lawns in summer. Don’t worry about those, though, lawns are resilient and very often grow back!

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Uncertainty surrounding the prediction of microclimate change

We need to gear up the search for correct climate predictions to tackle the biodiversity crisis. In a recent perspective piece in the journal Science, we argue that our climate predictions do not take into account local changes in land use. Tackling this problem will require our new SoilTemp climate database and the joint collaboration of scientists from all over the globe. 

 Artificial temperatures

Weather stations serve well to monitor our daily weather and the changes in our climate. However, such data are much less relevant for nature. What is even worse: the predicted warming of our nature itself could also be very different from what the climate models predict.

The problem is simple: Weather stations measure the temperature at 1.5 to 2 meters above the ground, in well-ventilated rooms, above a neatly mown lawn. However, this is a very artificial situation, resulting in temperatures quite distinct from those that nature itself experience. Most animals and plants (insects, soil organisms, herbs, small mammals…) indeed spend a large part of their lives much closer to the ground, where temperatures can vary from a few to even dozens of degrees from that weather station temperature. You can experience this so-called ‘microclimate’ yourself when you put your hand on the hot beach sand on a summer day, or on a cool bed of moss in the forest.

Picture microclimate stations

Mini weather stations – like here in a lawn – give ecologists the climate where it matters for the ecosystem.

Faster warming

These big differences that we feel on the beach and in the forest over the years accumulate into a long-term climate that is on average several degrees warmer or cooler respectively than what a weather station indicates. We argue this week in Science that these differences are already crucial to understanding nature in the present, but that climate change is making them all the more crucial. A predicted increase in temperature of 2 °C could feel completely different on the forest floor, especially if mankind interferes. For example, another study in the same edition of Science, led by Florian Zellweger, reports that the climate on the forest floor in forests with more intensive logging has warmed up much faster than average in recent decades, with major consequences for the future of forest biodiversity.

Ecologists have been aware of this problem for a while, but no good solution had been found yet. Until now. Researchers from all over the world – we already united scientists from more than 50 countries – are joining forces to finally obtain climate data that can also be used to tackle the biodiversity crisis. We did set up ‘SoilTemp’, a database of climate data that is relevant for nature itself. By using temperature measurements there where it matters, we can gain insight into how strongly that microclimate can deviate from the measurements in the weather station in ecosystems across the globe. In doing so, we hope to answer the ultimate question: how large is the impact of climate change on our biodiversity?


  1. Lembrechts and I. Nijs, Microclimate change in a dynamic world. Science, (2020).
  2. Zellweger et al., Forest microclimate dynamics drive plant responses to warming. Science, (2020).
  3. Lembrechts et al., SoilTemp: call for data for a global database of near-surface temperatures. Global change biology, (2020).
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Trial in the village

Our citizen science project on garden microclimates (see this post) is slowly taking up speed. For now, it is trials-trials-trials, making sure all the gaps and holes are filled and all the questions are answered, before we launch the full 5000-logger strong program next summer.

While the first trials started simply in my own garden, we now had a nice little expansion: our neighbours were intrigued by the funny little mushroom in our front yard, and said they would love to have one too. Why not, I thought, the global pandemic is keeping all my loggers locked indoors for now anyway! So out we went: we mobilised the street’s WhatsApp group, and brought mushrooms and instructions to everybodies doorsteps. Now the neighbourhood is filled with garden daggers in a first example of what this citizen science project can do!

Garden loggers

Our little white mushrooms spread across our own garden, and the whole ‘Saliestraat’ street. 

This first ‘microcosm’ of the citizen science project we want to roll out across the whole of Flanders already thought us a lot: cats and dogs like playing with the little top hats of our mushrooms, for example, and lawn mowers are no friends of the bottom shield. People do find them very intriguing, though, and happily welcome the intruder in their lawns. And robust as they are, all of them did survive for now.

And then there is the data, of course, which is of course the best part! Just imagine this graph below rolling in from 5000 gardens across the region, telling us everything one wants to know about what’s driving our garden microclimates, and if and how can improve this ourselves, to make them a better place for humans and nature.


Example of heat (at the soil surface) and drought measurements in my own garden, revealing an extraordinary dry and warm spring. 

For now, we’ll leave it at this first impression. We’ll leave detailed analyses of all the cool insights that are in their for later, when our project truly takes off!


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The virtual lab in lockdown

We are all at home, unfortunately. That means: reduced social interactions, much less scientific discussion, and the loss of the support system of colleagues and friends. It’s tough for all.

Luckily, our virtual lab has some experience with running remotely, as we have been virtual from the start; scattered across the world yet connected by science.

So all of us now have their office at home, which involves a lot of good home office-snacks, the never-seizing support of cats and babies, and a wide variety of laptop set-ups and improvised desks.

Home offices

Impressions from all over the world of our virtual lab in lockdown

We try to keep in touch, with bilateral meetings, virtual ‘shut up and write’-sessions, and even joint projects (like this one). We are alone, but still together. We all hope desparately that the lockdown ends soon – and that as much as possible of this summers’ field season can be salvaged. But whatever the case, our virtual lab will remain to keep us strong!

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The holy trinity of global change ecology


A few weeks ago, the journal Annals of Botany asked me to write a commentary pieceon a new paper coming out on the effect of climate change on grass species on a subantarctic island. An intriguing paper, as they compared the response of native and non-native grasses to climate warming, a thread that we see rapidly unfolding in front of our eyes, especially in such cold environments.

Their findings? The species with the greatest rate of spread over the last decades – the non-native, warm-adapted newcomers – showed much higher adaptability to cimate change than their native counterparts.

What I found most interesting about this study – and what triggered me to write this Commentary piece – is that it elegantly highlights the new ways in which we will have to do ecology from now into the future, a new way that pivots around what I would like to call ‘the holy trinity of spatial climate change ecology’. This ‘holy trinity’ is the type of data that we need to tackle this rapidly accelerating problem, before it is too late: 1) high-resolution environmental data, 2) long-term biodiversity monitoring and 3) physiological experiments.


Vegetation monitoring in extreme environments – here in a volcanic landscape at high elevations in the Andes

In this commentary paper, I argue that, when collected in tandem, on large scales, at high resolutions and in interaction with each other, these three data types can provide the critical baseline data to answer questions on why species are moving and adapting, and predict their fate in a rapidly changing future. And while all three are advancing rapidly in these times, it is in their interaction that most merit can be found.

Figure AoB

The holy trinity of spatial climate change ecology: if we have 1) high-resolution climate data (both in space and over time), 2) long-term species distribution surveys and ideally 3) the actual performance of the organism as a function of the climate, we can model their distribution in past, present and future.

Indeed, as biodiversity starts to react more and more to these accelerating climate changes, we need long-term biodiversity data, linked with high-resolution climate data from there where it matters for the organisms. Strengthening them even further with physiological experiments on how these organisms actually react to said climate, allows stepping away from correlative models only and build those models on known mechanisms. The latter can give those future predictions the extra credibility they need.

It is thus the integration of these three data types that will allow climate change ecology to move forward. And that is exactly  what we should be aiming for, if we want to tackle the complex and multi-dimensional issues of biodiversity conversation under accelerating global change, as the rate of change demands rapid understanding of and action on species (re)distributions.


Ecological fieldwork in the dry Andes, Argentina

Further reading

Lembrechts JJ, The Holy Trinity of spatial climate change ecology: high-resolution climate data, long-term biodiversity monitoring and physiological experiments. A commentary on: ‘Invasive grasses of sub-Antarctic Marion Island respond to increasing temperatures at the expense of chilling tolerance’, Annals of Botany, Volume 125, Issue 5, 8 April 2020, Pages ix–x, https://doi.org/10.1093/aob/mcaa057

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Same data – different analysts

So here is an important question: if you give the same dataset to different scientists, will the outcomes be the same?

This question is not trivial. It’s actually one of the most important assumptions in the way we currently do science, and thus the base of so much of our knowledge: any decent analysis is going to uncover the truths hiding in a dataset, whoever looked at it first.

However, this critical assumption is rarely tested, so we pretty much don’t know if this assumption actually holds! Let’s solve that, shall we? So I stumbled upon this fantastic initiative from Hannah Fraser and others (here) aimed at filling that void in our knowledge. Their plan is as simple as it is brilliant: just give exactly the same dataset to ecologists from all over the world, let them all analyse it as they would do for their own papers, and carefully compare the outcomes.

See, this is the kind of science that gets me excited: building on global collaboration, challenging the foundations of our scientific understanding, and building towards a better science in the future. So obviously we are playing along.

Hallerbos - 11

Our experimental questions will deal with how grass cover influences Eucalyptus seedling recruitment (yes, I have no relevant pictures for that, I have never been to Australia, but that doesn’t mean we can’t analyze the data!)

What is even better about this initiative, is the fact that we can make this a team excercise! We can bring our Virtual Lab together and all work as a team on a shared research question. It is the perfect opportunity to organize that ‘practical statistics and paper writing course’ that students often crave for in their masters or early PhD: get a dataset, and work your way through the whole process of analyzing and writing up the results, without the extra pressure you get when it is your thesis work and you are the lea author. Learning from each other, taking along the new students and having the established one lead the way. This is what our Virtual Lab was waiting for!

So let’s see where this brings us. We are looking forward to do this teambuilding excercise, and in the meantime contribute important knowledge to the scientific community. We’ll keep you posted…

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SoilTemp: a database of near-surface temperatures

Let me tell you something important – which won’t be a surprise to regular followers of this blog: weather station data doesn’t do the trick for ecologists. It is just too different from the climate as experienced by most organisms, and relates to it in non-linear ways.

Yet, and that is the most important part, we made a huge step forward to solve that mismatch! We published the concept of our SoilTemp-database just now in Global Change Biology, introducing our ambitious plan to the scientific community and calling on all who want to listen to submit their microclimate data to our growing database (yes, that’s you as well! Do you have microclimate measurements? Then get in touch! More on our website).

And growing it does!

Graphical abstract

Overview figure of the database at the moment of paper acceptance (as it keeps growing!): a) shows the geographical spread of the 7538 (!) loggers from 51 (!!) countries we already have processed, while b) gives the spread in the worlds’ climatic space (the blue smear in the background indicates all types of combinations of temperature and precipitation that exist in the world, and we are covering quite a bunch of them).

The paper also explains why it is that this microclimate is so different from the macroclimate as interpolated from weather stations. In short, there is two things that together constitute that offset between micro- and macroclimate:  horizontal and vertical features.

Figure 1

The difference between coarse-grained free-air temperature and fine-grained soil temperature is driven by horizontal andvertical features. 

The horizontal features relate to the spatial resolution of the climatic data. They include features at a specific site (like effects of slope and aspect on local radiation balances, with south-facing slopes much warmer than their north-facing counterparts), and those where temperatures are also affected by neighboring locations (like topographic shading, cold-air drainage and atmospheric temperature inversions, which are landscape context dependent).


With horizontal features we capture the temperature differences between the left and right side of this picture, where local temperatures are driven by a difference in solar radiation input on a cold winter morning

The vertical features are what drives the difference between air and soil temperature and include the effects of vegetation characteristics (e.g. structure and cover), snow cover and soil characteristics (like moisture content, geological types, and soil texture). They cause an instantaneous temperature offset between air and soil temperatures, but also a buffering effect, i.e. the temporal variability in temperature changes is lower in the soil than in the air.


Vertical features involve those explaining why temperatures close to the soil are so different from those at the height of weather stations

It is the role of these two types of features that we hope to disentangle using our global database initiative. If we succeed, we will finally have the correct global climate data at hand to tackle the biodiversity and ecosystem crisis we are facing. And succeeding we will, just look at the fantastic list of co-authors on this first paper, showing the enthusiasm from all over the world for this question.

We’ll keep working frantically now, bringing together even more people from all over the world (our author list of the ‘real deal’ papers will hopefully be even longer!), and working towards tackling these questions. You bet you will hear more from us soon!


Further reading:

Lembrechts JJ et al. (2020). SoilTemp: a global database of near-surface temperatures. Global Change Biology. https://doi.org/10.1111/gcb.15123. 

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