This would normally be the season where we take the students to the beautiful Hallerbos, close to Brussels, to teach them all about forest types and keystone plant species. This trip would importantly also involve stunning purple fields of bluebells all the way to the horizons.
None of that this year, though.
Bluebells popping up in an abandoned meadow close to my home
So this year, I’ll have to do with those few scattered bluebells popping up in the woods and fields close to my home, and the pictures and memories from last year’s course. The students – even worse – will have to do with a theoretical course on forest types.
Acer pseudoplatanus, the sycamore maple
For those finding that notion of missed nature opportunities a tad sad, I’m happy to take you back on a trip down memory line with some pictures of this amazing forest.
For more pictures, check out all ‘bluebell’-related posts on here!
For us scientists, it is tempting to throw our expertise into the fight against COVID-19. For spatial ecologists, this often means: predicting the risk of spread of the virus based on species distribution models, trying to identify its climatic niche – and thus where it is likely to show up as the season develops. After all, we have heaps of papers proving the validity of our modelling approaches for a whole range of species (and many diseases do indeed have a biogeography). This has already resulted in a myriad of preprints linking the spread of COVID-19 to climate, as summarized here.
Unfortunately, our ecological modelling techniques might not be sufficient in this case, for a variety of reasons. Many of these reasons are neatly summarized in the fantastic work from Chipperfield et al. , including the facts that 1) the distribution data for the virus is uncertain at best and highly biased at worst, due to undertesting, and 2) that the virus is far from its (climatic) equilibrium. These models might thus not only be unhelpful, but also perhaps counter-productive (think about the hopes that warm spring weather will easily get rid of the virus).
There is one problem with these models that I would like to stress a bit more, based on my own experiences as a microclimate ecologists: the climate we have at hand to model the distribution of the virus is just plain wrong. The coronavirus does not have much of a link with longterm averages in free-air temperatures measured by weather stations, and will thus not behave accordingly. We have been hammering on this nail for years now for a variety of organisms, like tundra plants (Lembrechts et al. 2019) and soil microbes (Lembrechts et al. 2020).
The problems might be even more acute for a virus than for these organisms, and they boil down to this: the spatiotemporal scale at which the organism operates, is so different from the climate data we have at hand, that there are likely several degrees of mismatch between the climate we use to model, and the climate as experienced by the organism.
It will likely not help to switch from long-term averages to current weather data, although that does take away the error caused by the fact that spring might have been much warmer this year than the average in many parts of the northern hemisphere. It will also not suffice to take into account urban heat island effects, even though the virus is spreading fastest in cities – which are indeed warmer than the average climate predicted by weather stations. The main issue lies in the fact that the coronavirus spends so little of its ‘lifetime’ in free-air: a lot of its time is spend either in human bodies, or indoors (where most of the transmissions take place) and on objects (gloves and mond masks, to name a few). None of these ‘habitats’ has temperatures only remotely near to what a weather station would give. Only for free-air transmission, this might be the case.
And this is an important note: humans are actively trying to make microclimates in their habitats – the indoor world – as comparable as possible across the whole world. We are warming our houses there where it’s cold, and cooling them where climate is warming. The effective result is a globally homogenised climate that is much more similar between human habitats across the globe than between these habitats and the weather stations closed to them.
So let that be a take-home message: modelling and predicting the climatic niche of any organism is tremenduously tricky, as long as we do not have the actual climate it experiences. This means that for so many organisms, we are far from ready to accurately predict their future distributions. And the coronavirus is just one example.
Remember my post from early 2019, where I put my R-skills to good use for society? The idea was to visualise the number of kittens in our local animal shelter throughout the season to get an idea of when the peaks could be expected.
This has turned out to be a crucial excercise for the animal shelters and the foster families taking care of the kittens: they used it to await patiently the peak to come in spring, to ensure they stocked enough kitten milk and other amenities for when the peak would be there, and prepared them for the second peak, right when after summer everything seems to cool down.
Number of kittens throughout the season in 2018 (black line) and 2019 (red line)
Yet one year of data is only that much. If we truly want to predict accurately how kitten numbers will evolve throughout the season, we’ll need to build a long-term monitoring scheme. As you can see in the graph, indeed, there were some surprises in 2019s’ red line: the peak came quite a bit later, with the mass of the kittens being dropped at the shelter only mid July, instead of mid June as in 2018.
Please love me!
Moreover – and that caused special burden on the animal shelter – the second (and third!) peak in autumn far exceeded those of 2018, with both in October and November more than 120 kittens at the same time sheltered in foster families.
We will keep monitoring what comes in and goes out this year, to add a third time series to our graph. The ultimate goal would be to come up with a predictive model of those peaks in the season. I have high hopes, for example, that warm weather in springtime will be a decent predictor of the number of kittens coming in two to three months later.
But we should all know the dangers of correlative predictive modelling by now, especially for topics where we lack the expertise. Finding patterns is easy, deciphering the mechanisms behind them often needs four years of dedicated study. So, for now I’ll stick to my descriptive curves, and some broad generalisations.
But that limited expertise can tell you one more thing: with the ongoing social distancing, the peak in kittens will be severily delayed this year (as very few people will either find or save abandoned kittens), yet will hit us twice as hard after summer (when all abandoned kittens of the spring time will profit from the warm autumn weather to make new nests themselves).
Guest post by Sara Vicca (UA, dept. Biologie), Ann Crabbé (UA, dept. Sociologie) and Steven Van Passel (UA, FBE). This blog appeared earlier in Dutch on www.globalchangeecology.blog and in English on www.scientists4climate.be.Translated by Jonas Lembrechts with DeepL.
Is the coronavirus good news for the climate? It’s a recurring question these days. Not incomprehensible, because the impact of the measures on our emissions is clearly noticeable. Car traffic and energy consumption are decreasing and in the meantime it has been calculated that CO2 emissions in China decreased by a quarter in February. But these decreases are limited in time. In China, emissions are already rising and history teaches us that a decrease in CO2 emissions due to a crisis is usually short-lived. Emissions also fell during the oil crisis in the 1970s and during the banking crisis in 2008-2009, but after the crisis emissions rose again each time to break new emission records.
Will it be the same this time, too? Will CO2 emissions rise rapidly again after the corona crisis until the end of the year up till the level from before the crisis? Let’s hope not. Governments and all those who (rightly) take measures to re-launch the economy after the crisis, hopefully opt for measures that contribute to a ‘sustainable’ relaunch of the economy. This crisis may be an opportunity to take further steps on the transition path that some people have chosen very deliberately before.
Which aspects are most important here? What should we, as a society, do to turn the corona crisis into a turning point in greenhouse gas emissions? A recent study on social tipping dynamicsoffers more insight into this. In February of this year, a group of scientists (including some big names such as Johan Rockström and Hans Joachim Schellnhuber) published a study in which they discuss so-called social tipping interventions (STIs). These are social and technological changes that, through a snowball effect, can greatly accelerate the necessary social transition to a climate-neutral society. These social tipping interventions concern the following social aspects: (1) energy production and storage, (2) residential and living environment, (3) financial markets, (4) standards and values, (5) education, and (6) information. Below we briefly summarise what the study indicated and discuss some possibilities in the light of climate action in the (post-)corona era.
Energy production and storage
The energy transition takes a central stand in tackling the issue of climate change: fossil fuels must be used in such a way that be replaced by renewable energy sources as soon as possible. The most important factor influencing the switch to fossil-free energy production is the financial return of the sustainable alternatives. The experts indicate that the tipping point here is likely to be reached when fossil fuel energy production becomes more expensive than the alternatives. Data shows that we are on the verge of reaching this critical threshold; renewable energy prices have fallen sharply in recent years and in many regions renewable energy has already become thecheapest energy source.
However, significant investments are still needed to adapt the existing electricity system to renewable sources such as wind and solar. An important action point of STI put forward here is the reorientation of fossil fuel subsidies towards subsidies for a decentralised energy system with the necessary energy storage and a better matching of supply and demand (smart grid).
Our homes and buildings account for about 20% of global CO2 emissions through direct and indirect emissions and reducing these emissions is a significant challenge for the transition to a climate-neutral society. An example of an STI here is setting up large-scale demonstration projects such as carbon neutral cities. Such projects are important as a source of information and inspiration for the general public, and as a stimulus for the development of sustainable building materials and technologies.
One of the plans in the Green Deal for Europe is a so-called renovation wave, which will aim for 3% renovation per year (instead of the current 1%). This will require technological, organisational, social and financial innovation . In addition to climate and health benefits, the renovation wave can also offer many opportunities for economic growth and job creation. At the moment, however, it is still unclear to what extent the corona crisis will lead to delayed implementation of the European Green Deal, or rather a flywheel effect: the economic recovery measures can also go hand in hand with the implementation of the Green Deal and mutually reinforce each other.
The 2008-2009 financial and economic crisis showed how quickly an event in one sector (the banking sector) can destabilize society and bring about changes in individual investment and consumption behaviour as well as in policy actions. In order to limit global warming to well below 2°C (as agreed in Paris), 33% of oil, 49% of gas and 82% of coal reserves should not be burned. This suggests a risk of a so-called carbon bubble or carbon soap bubble, which means that investments in fossil fuels will be insufficient if we comply with the Paris Climate Agreement.
A growing number of analysts believe that such a financial carbon bubble is emerging and that it could burst if a critical group of investors see it and act upon it. Simulations show that only 9% of investors can already topple the system. Other investors would then quickly follow. An example of an STI that could play an important role here is the divestment movement, where money is desinvested from fossil fuels, and instead invested in sustainable projects: “divest from what harms, invest in what helps”. A snowball effect could be caused when banks and insurers would warn about this carbon bubble. These concerns are already growing in Europe, and according to the study, the reduction in financial support for coal projects could indicate that a tipping point is near.
The corona crisis also shows how an event can disrupt the financial markets. On 12 March 2020, the Brussels stock market index Bel20 experienced its biggest fall ever (-14.21%), since the start of the index in 1991. Investors are uncertain about the economic impact of the coronavirus. Arrangements have been drawn up for deferring payment of loans for both companies and private individuals, in addition to, among other things, guarantee schemes, annoyance premiums and deferral of payment. In the longer term, it is very unclear whether the corona crisis will strengthen the carbon bubble or just slow it down. An important recommendation is that the recommendations of the TCFD (Task Force on Climate-related Financial Disclosures) should be followed thoroughly in order to avoid exactly that carbon bubble.
Standards and values
Some argue (perhaps rightly) that it is immoral to extract and burn more fossil fuels than the objectives of the Paris Climate Change Agreement allow. After all, this leads to a lot of unnecessary suffering and damage. Moreover, we know that the most vulnerable social groups are disproportionately affected by climate change. And then there is intergenerational inequality: future generations will be hardest hit, while they have no voice in the debate today.
Fortunately, norms and values can change. Global climate protests and school climate strikes may be an indication that such a change in norms and values is taking place. A recent study showed that a dedicated minority of about 25% of a group can change the opinion of the majority and thus change established norms and values. If dominant norms and values in society change, the pressure on policymakers to change existing institutions (regulatory systems) will increase. Policy initiatives such as the European Green Deal are in turn an important incentive to change the behaviour of companies, among others, a self-reinforcing process of change can be set in motion, in favour of climate neutrality.
Who knows, the corona crisis may lead to a shift in dominant values and norms in society. While many are concerned about the economic impact of the corona measures, others underline the extent to which the stagnation of social and economic life offers room to live differently, with less consumption pressure, more time for what counts (the family) and with the mental relief of being able to step out of the ‘rat race’ for a while. Political scientists are waiting, but anticipate shifts in dominant political values: more willingness to invest in ‘soft sectors’ (such as care), more room for solidarity, while denouncing globalisation and dependence on international markets. The latter may give rise to the strengthening of solidarity within Europe, including in the joint development of a greener economy that is less dependent on ‘external’ fossil fuels.
General knowledge about the causes, consequences, and solutions of climate change has often been lacking, and this knowledge gap is at least often one of the reasons why people often do not feel addressed or involved in the climate story. On the other hand, recent school climate strikes show that younger generations are waking up to the climate problem. It is estimated that the number of school strikers grew to 1.5 million pupils in 125 countries in six months’ time. Many educational initiatives have now been set up to inform pupils and other target groups about climate change. Quality education not only supports and strengthens knowledge about climate, but can also inspire climate action and changes in individual and collective behaviour.
The big challenge, during the corona crisis and afterwards, is to reduce school and learning delays among pupils and students. Specialists are already worried about the proportionally greater learning disadvantages that vulnerable pupils are suffering as a result of the prolonged closure of schools. Digital distance learning may work for children who are doing well at home, but it does not offer a fully-fledged alternative for everyone.
If we want to reduce greenhouse gas emissions, we naturally need to know where the emissions come from, which products cause more/less emissions, and how we can make sustainable choices. Such information can be provided to consumers, for example through product labelling programmes. On the other hand, the population also needs to be clearly informed about the purpose and impact of certain measures, such as shifts in subsidies and taxes. Sufficient communication about the impact of individual choices on emissions can encourage societal changes, although we know that knowledge alone will not suffice.
In these Corona times, Belgium excels in informing the population objectively, correctly and serenely. We were even praised for this by the British newspaper The Financial Times. Every day, experts give an update on the state of affairs: number of infections, hospital admissions, intensive care units, the number of people who were allowed to leave the hospital and the number of deaths. These moments of information are also used to comment on events, rumours and other events.
Perhaps certain aspects of this crisis communication can serve as a source of inspiration for those who want to share information about the climate problem? Inform people objectively and calmly about what works and what doesn’t, what has already been achieved and what we still have ahead of us. This strengthens the feeling that we have to work together on the transition to a climate-neutral world, that the climate transition will not only cost money, but will also bring financial benefits and that we will have a more pleasant and liveable world in its place.
In conclusion. Rockström, Schellnhuber and their co-authors also point out the importance of institutional changes in their article. Government subsidies and tax systems need to be reformed in order to stabilise the emerging more sustainable system. Without the necessary adjustments concerning financing, taxation and regulation, the transition will be slowed down. The authors of the study indicate that extreme climate-related events, such as extreme heat waves and floods, can create a ‘window of opportunity’ to make such adjustments. The corona crisis can also lead to reforms, including in financial flows and regulations. When that happens, let’s take advantage of that opportunity to, in one fell swoop, also tackle the climate problem.
 Ilona M. Otto, Jonathan F. Donges, Roger Cremades, Avit Bhowmik, Richard J. Hewitt, Wolfgang Lucht, Johan Rockström, Franziska Allerberger, Mark McCaffrey, Sylvanus S. P. Doe, Alex Lenferna, Nerea Morán, Detlef P. van Vuuren, Hans Joachim Schellnhuber. Social tipping dynamics for stabilizing Earth’s climate by 2050. Proceedings of the National Academy of Sciences Feb 2020, 117 (5) 2354-2365. https://www.pnas.org/content/117/5/2354
Yesterday, we had a new member joining the team! It was a virtual first day at work, but we are very happy nonetheless to have her on board now: Camille will be managing our citizen science project on garden microclimates, and will ensure we roll smoothly through the test phase this summer while building towards the full project for next year.
We are tremenduously happy to have her strengthen our team while we are frantically working backstage on getting everything ready for this ambitious plan.
In the meantime, our first batch of TMS4 ‘garden daggers’ for the season – introduced here– is happily logging microclimate data from crispy frozen April mornings and sunny afternoons. Keep an eye out on this place for some first data on the microclimate variability in my own backyard soon!
Our TMS-logger catching the first sun of the morning with their feet in a crispy frozen lawn
As we are all locked up now anyway, we decided to spread the love for garden sciencing across the world, and launched a call on Twitter for our fellow scientists with idle microclimate loggers to start measuring their own gardens as well.
There was a lucky few for which the loggers were not inaccessible in the office, just enough to give our trial project the global flare that it deserves.
That said, we really hope to see all in person again soon in the future! Luckily, the 3D Lab has already gained quite some experience with ‘virtual labbing’, so we are not going to let this homeworking get us down!
Another guest post from 3DLab-member Ronja Wedegärtner on how we can do better science in these times of global change, and include the whole of society from the start.
We are producing much science, but not using it effectively enough – this is how I would summarize my last blogpost after the OIKOS 2020 conference, which left me wondering what we can do as ecologists to find answers to global issues. “Knowledge synthesis is the key to changing the world.”, was a statement in the final discussion that has kept my head spinning through the last weeks. (At those moment when the COVID-19-the-world-is-breaking-down-and-I-am-in-quarantine spinning came to a brief rest.)
The wonderful thing is that there are many of us out there think along these lines. I was therefore super-excited when I saw the article “A new ecosystem for evidence synthesis” by Shinichi Nakagawa and colleagues that proposes a new framework for knowledge synthesis.
They are envisioning a community of empiricists (data collectors) and synthesists working together from the start, thereby making sure that data is meaningful to answer big questions, is not pre-filtered by publication bias and synthesized in a timely manner.
The authors suggest a web-based synthesis platform to connect researchers and to communicate the findings of this “living system of synthesis” to the interested public.
And now I am going to venture in into an adventure. I am going to share my thoughts about the solution they propose. Much of my thinking on how we can solve global challenges as a collective has gone into similar directions. I see the building of communities as a central foundation for finding the solution for global challenges as well. And I completely agree with the authors that a web platform that connects people might be an integral part of finding solutions.
But one thing struck me when reading through the article – stakeholder engagement was through consumption of synthesized data only. Maybe the engagement of stakeholders in identifying the most pressing questions for which we need knowledge synthesis is implicit for them. But I think that this is a key foundation of making synthesis that matters. I think that we need to extend the community framework to include the non-scientific community. This is challenging and we need to think as a community about how we can do this and still gather our synthesis about pressing global issues at the speed that is necessary to actually face them and not only do an autopsy of a collapsed system.
What gave me most hope when reading through the article? The fact that initiatives such as the Evidence Synthesis Hackathon exist. After a brief stint in the start-up world before I started my PhD I have come to love hackathons. Hackathons originated in the tech-world and bring together interested people for a purpose – this can be solving a global challenge as much as developing an app. The participants bring their knowledge, experiences and creativity and collaborate over a fixed timeframe (often a weekend) very intensely on this topic and try to find solutions. I think that coming together for a short time, working extremely focused and solution-oriented, is very rewarding, often with great outcomes. The article discussed above is just one point of evidence in that regard.
I am going to keep an eye out for new opportunities to move things quickly on the website of the Evidence Synthesis hackathon: https://www.eshackathon.org and will see if I can secure a spot in their next hackathon.
And I am closing this post with the question: Should we have a have a (digital, socially-distanced) hackathon about how we can involve non-researchers in such knowledge synthesis communities? Having students, policy makers, and holders of Traditional Knowledge involved from the start and throughout the process? – if you think ‘yes, this is exactly what we need!’, then get in touch and we will try to make this happen!
If we want to model where soil microbes are living, and why, traditional distribution models will not do. In a new paper in FEMS Microbiology Ecology, we suggest that accuracy can be achieved, if we just change our mindset and start thinking from the soil microbes’ perspective. Our three key points in that regard: measure hierarchically, interpolate local variability, and don’t forget biotic interactions!
Ecologists are getting increasingly better at describing and predicting where species live, especially thanks to a now widely famous class of models called ‘habitat suitability and distribution models’ (HSDMs). Indeed, we see global databases of species distributions becoming more and more established, and remote sensing data, for example from better and better satellites, adding to our knowledge of the enviroment. This, combined with a wider and better range of modelling tools, has caused an explosion of studies looking at where species live, and why.
Despite this rapid surge in knowledge on species distributions, there is one group of species that has remained particularly underexplored: soil microbes. The reasons for this are perhaps rather obvious: it is just so much more difficult to know what’s happening belowground, let alone model which microbes are living where.
In a new paper in the journal FEMS Microbiology Ecology, we argue however that there is no need anymore to leave soil microbe distributions understudied anymore. We can do this, we just have to approach the question with a local-scale, ‘microbe-specific’ mindset. In our conceptual paper, we provide the necessary details on how that mindset should look.
If we want to model where soil microbes are living, and why, a different approach is needed. Our three key points in that regard: measure hierarchically, interpolate local variability, and don’t forget biotic interactions!
First of all, and perhaps most importantly: soil microbes operate on a much smaller scale than aboveground organisms. That means that the environmental data we link their distributions to needs to be much more local as well. The coarse global climate data at 1 km resolution that is traditionally used for HSDMs is even less useful than it is for aboveground organisms. And even worse, climate measured in standardized weather stations is completely meaningless for soil microbes, where temperatures are often several degrees different from what is measured in that white box above the lawn. And then we are not even including all these other important abiotic variables yet, like soil moisture or acidity.
Overview of our proposed framework to tackle the distribution modelling of soil microbes, including nested sampling, modelling of local variation in environmental conditions, and the inclusion of biotic interactions. For more details, see the paper!
Importantly, however, there is no way that one can increase the resolution of the environmental data to be exactly at the level of what these microbes ‘see’: we can’t plug loggers in every centimeter of soil over a vast area. We argue however that such a dramatic hunt for a higher resolution is not necessary. Using a hierarchical sampling approach, where high resolution data is collected in a selection of plots, which can then be linked to a broad range of plots across the landscape, one can improve the resolution of environmental data, and model and predict the local variation in environmental conditions, without the need to measure it everywhere.
Details of our hierarchical sampling approach for environmental conditions and the microbial community. For more details, see the paper.
Finally, for soil microbes even more than for any other organism group, their distributions are not only affected by the environment, but at least as much by other species living in their neighbourhood. These interactions are a lot harder to incorporate in HSDMs, but are nevertheless critical to really understand where and why these species can be found. Luckily, the necessary modelling tools are now available to incorporate these interactions when modelling distributions, for example using Joint Distribution Models, which analyze the distribution of several species at once, and take their co-occurrence into account.
We hope that our conceptual paper encourages scientists to tackle the spatial distribution of soil microbes, as this knowledge is from critical importance to predict how these important components of our living world are dealing with the challenges of our times.
Lembrechts JJ, Broeders L, De Gruyter J, Radujković D, Ramirez-Rojas I, Lenoir J, Verbruggen E (2020), A framework to bridge scales in distribution modelling of soil microbiota, FEMS Microbiology Ecology, , fiaa051, https://doi.org/10.1093/femsec/fiaa051