INNATURE: Building biodiversity and belonging in urban spaces

By Olivia van der Weiden

Over the past months, we’ve been working hard on the preparations for INNATURE, an EU-funded project on nature based solutions in urban areas. The mission of this project is straightforward: co-create nature-based solutions to promote both biodiversity and social inclusion in Europe’s urban living spaces.

What makes INNATURE unique is how many people with different backgrounds are included.

Local communities, researchers, artists, designers, policy-makers, and ecologists all share their knowledge and perspectives. Combining all these strengths, we aim to provide sustainable, beautiful, and inclusive solutions in order to help cities respond to climate change and strengthen people’s connection to nature close to home. A complex web of voices and opinions to navigate, but – we hypothesize – resulting in more robust and beneficial solutions at the end.

Five locations, five stories

We’re trying out this co-creation experiment through five demonstration cases across Europe: Belgium, the UK, Denmark, Finland, and Romania. Each case faces its own ecological challenges.

The demo case of Borgerhout, a city investing a lot in urban greening

Some of the cases focus on climate change-induced effects, such as stormwater floods or droughts, while others tackle biodiversity loss, for example, supporting endangered species whose habitats are disappearing. But ecological challenges rarely come alone. In several of the cases, people feel disconnected from nature. We see things like landscape blindness (not noticing the nature that is there) and the loss of local knowledge, such as how rainwater can be captured and used wisely. Tackling the biodiversity loss thus needs to come as much from ecological decisions as from social action.

Each different case requires widely different nature-based solutions, reflecting the complexity and uniqueness of our urban areas. Across the demonstration cases, interventions range from greenifying streets, to planting zigzag clover to support an endangered moth, to vertical storm management, storing floodwater in aboveground measures. While some cases already have a clear plan and focus, others are still brainstorming options and are defining what they want to achieve.

Preparations: more than choosing solutions

Greening the city needs to start small, but can create a beautiful ripple effect if implemented well

But planning nature-based solutions is not only about deciding what you want to implement. It is also about agreeing on:

  • When to implement
  • Where exactly implementations will take place
  • How we will measure whether they work

That’s also where monitoring enters the picture, and that’s exactly where we take the wheel.

Monitoring

In most of the cases, there are two phases you go through when monitoring:

  • Baseline monitoring before implementation (what is the situation right now?)
  • Follow-up monitoring after implementation (what has changed?)

To know if these changes were indeed the effect of the interventions, you also need comparison areas:

  • A negative control site: a similar area where nothing changes, and/or
  • A positive control site: an area that already has the conditions we want to achieve

Part of the preparation work has been to map these control sites, but it’s also about deciding what we measure there. Across all cases, monitoring microclimate (both local temperature and humidity) is the main focus of interest, together with monitoring biodiversity (plants, insects), and sometimes soil health. While microclimate can be measured using sensors and soil health with soil samples, for biodiversity monitoring we need people, and that’s when social engagement becomes important.

Social engagement: turning monitoring into participation

INNATURE is not only about the ecological side: it’s also about making the local community feel involved and engaged with the nature in their surroundings. That’s why we have been carefully thinking about how monitoring can become a moment of connection.

In these cases, residents will be involved in measuring microclimate in these implementation and control sites, and in several cases also in backyards, with results visible on a digital platform. By seeing data change over time, such as seeing their own street getting cooler after greening, the impact becomes more tangible.

Simultaneously, this platform also supports biodiversity registration, not only during events like a bioblitz (where people try to document as many species as possible in a certain area), but also over the longer term. One idea we’re exploring is gamification: using gaming elements, such as receiving points when you register five species, to make participation fun and motivating. In this way, residents can become aware of the actual biodiversity that their neighbourhood harbours. They get curious about it, learn what species are called, and see it as something they care for.

Beyond microclimate and biodiversity, this platform could also become a space where people share experiences and observations about their neighbourhood, such as highlighting beautiful locations or reporting fly-tipping. In this way, the project can support nature stewardship and strengthen the feeling that urban nature is something shared and protected together.

So, what’s next?

Preparations: there’s more to it than you first see. We have our hands full with ordering sensors, meetings with each case to co-create and fine-tune our plans, and preparing upcoming site visits where sensors will be placed and monitoring will begin.

With five demonstration cases running in parallel, coordination is a project in itself, but it’s also one of the fun parts. With each case being unique and contributing its own insights, together they build a broader understanding of how nature-based solutions can support both biodiversity and belonging in the spaces where we live.

– To be continued! –

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Where the soundscape is pleasant

So, where in Flanders does it still sound nice?

A simple question, perhaps. But one for which the data has long remained elusive. Sound is a complex, multi-dimensional beast, and capturing how people actually experience it is not straightforward.

In a new paper stemming from De Oorzaak and led by Ablenya Barros, we now take a stab at answering that question. We asked close to 4000 citizens across Flanders to take a short walk outside, listen closely, and report how they perceived the soundscape around them, including which sound sources they heard.

Pretty simple, right?

Set-up of the paper, from soundwalks over machine learning models to key findings about the role of roads and green spaces.

For participants it took only a few minutes, but the resulting dataset is a gift that keeps on giving. In this newest paper, we threw a machine-learning model at the data to disentangle the spatiotemporal context behind people’s perception: why do some places and moments sound pleasant, while others do not?

Spatial distribution of our soundwalks across Flanders, with each observation coloured by the perceived ‘pleasantness’ as reported by the participant. The map itself is coloured by population density.

In essence, we ran two analyses.

The first focused on the role of sound sources in defining two key soundscape metrics: pleasantness and eventfulness (the official descriptors used in soundscape research). As expected – and consistent with earlier work – these models performed quite well. Pleasantness correlated strongly and negatively with traffic, industry, construction noise, alarms, and priority vehicles. On the positive side, natural sounds and silence clearly improved perceived pleasantness. Human sounds and music were more divisive: a little can be enjoyable, but a lot of either was often perceived as unpleasant.

The relationship between reported sound sources and perceived pleasantness, coloured by the relationship.

The second analysis looked at the geospatial context of these soundscape experiences. This is where the real novelty lies, because it helps us identify where problems occur and which spatial factors might help solve them.

These models were less predictive than the first ones, which makes sense. It has shown to be much easier to link people’s subjective soundscape experience to the sound sources they report themselves than to the messy complexity of the real world. Still, similar patterns emerged. Proxies of traffic, such as road network density and distance to highways, explained a large portion of the variation in soundscape experience. Meanwhile, a higher percentage of green space in the surrounding area increased perceived pleasantness.

Interestingly, road density and nearby green space also influenced eventfulness. More nature and fewer roads generally resulted in a less eventful environment – and those quieter environments were typically perceived as more pleasant. One could think that eventfulness would be appreciated as well, but in general, we’re all really looking for the sound of ‘boring, quite nature’.

Where the sound is pleasant

Putting all this together allows us to do something pretty cool: predict where in Flanders soundscapes are likely to be most pleasant.

The role of nature is clearly crucial. More green space within a 500-metre radius around you significantly improves the soundscape experience. But there is an important catch: if that same 500-metre buffer is filled with roads, the positive effect of green space essentially disappears, as shown in the figure below.

Pleasantness (colours) as a function of the ratio not green and the length of the road network within a 500 m area. Green was beneficial (yellow), but only in areas with few roads.

So yes – green helps. But only when it is sufficiently far from road traffic.

Again and again we thus see the disruptive effect of traffic on our soundscapes. But we also repeatedly see the positive role of greenery – even if it often struggles to compete with the dominance of traffic noise.

Clearly, there is still work to be done to improve our soundscapes. Luckily, we have not only identified the problems but also proposed solutions. Recently, we published the 200-page final report of De Oorzaak (in Dutch, unfortunately). It contains an extensive section with policy advice and recommendations on how to create healthier and more pleasant soundscapes across Flanders.

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From plants to smartphones: how I wandered through science

New paper out! –> Decorte et al. in PLOS Digital Health

This paper might be the furthest I have ever ventured from my core scientific discipline. And honestly? That feels very much right.

I started my academic life as an ecologist, fascinated by where plants live, why they live there, and how small-scale environmental variation shapes those patterns. That curiosity gradually pulled me toward microclimate: the fine-grained temperature, moisture, and radiation conditions organisms actually experience. From forests and mountains, it was only a small step to start asking similar questions in cities. And from there, to realize that if we really want dense, high-resolution environmental data, we cannot do it alone.

Alpine plants – where it all started for me

Enter citizen science.

Projects like CurieuzeNeuzen in de Tuin showed me how powerful large-scale public participation can be for environmental monitoring. Thousands of gardens suddenly became part of a distributed sensor network.

From ecology to microclimate monitoring, to citizen science – largely with those ‘garden daggers’, as our citizen participants called the TOMST microclimate loggers

This hard-core citizen science project is what eventually brought me to De Oorzaak, a similarly large citizen science project on environmental noise. While noise itself is an environmental variable, the project deliberately went much further – into perception, experience, and health. Working in this space meant exciting collaborations with psychologists, communication scientists, and health researchers, and learning new ways of thinking about data, causality, and impact.

Installing environmental sensors with citizens – the clear connection between my microclimate work and De Oorzaak.

Perhaps not a surprise: much of this scientific “wandering” happened during my postdoc years – a phase that is, for many young(is) scientists, defined by short contracts, shifting funding opportunities, and a constant need to adapt. Each new position came with its own thematic focus, and rather than resisting that, I embraced it. And it’s only slowly that I started to realise: the uncertainties around funding did not just shape where I worked, but also what I worked on. Looking back, this period pushed me to become far more interdisciplinary than I would ever have planned on paper.

It also means that I now find myself as a co-author on a paper in PLOS Digital Health.


Smartphones, sleep, and a more nuanced story

Smartphones are often portrayed as the villains of modern sleep. We have all heard the narrative: screens keep us awake, notifications fragment our nights, and scrolling in bed equals bad sleep.

What I find refreshing about this study is that it steps away from that simple storyline.

Smartphone use per day (left) and in bed per day (right) among our participants, as obtained objectively from their iPhone and Apple Watch tracking data

Using donated data from participants’ own iPhones and Apple Watches, the ‘De Oorzaak’-team followed 68 participants across 14 consecutive days, tracking:

  • Total sleep duration
  • Sleep stages (REM, core, deep)
  • Total smartphone use
  • Smartphone use while in bed

And the patterns that emerged were nicely nuanced.

More total smartphone use during the day predicted more smartphone use in bed – no big surprise there for anyone, I guess. But more in-bed smartphone use was associated with slightly more total sleep that same night. That does not mean scrolling causes better sleep. But it does challenge the automatic assumption that phone use in bed is always harmful.

One interpretation is that some people may use their phone as part of a wind-down routine. Another is that longer sleep following in-bed phone use reflects compensation after poorer sleep earlier. This, we can’t say based on the limited data we have. What we can say, however, is the following: the relationship is more complex than “phones ruin sleep.”

Perhaps even more important, the strongest effects were not day-to-day fluctuations but stable differences between people. In other words, habits matter. Some individuals consistently combine higher phone use with particular sleep patterns, and understanding those habitual profiles may be more informative than focusing only on nightly variation.


Back in ecology – but not the same ecology

Today, I am firmly back in the ecology camp. I once again spend most of my time thinking about biodiversity, microclimate, and how organisms experience their environment.

But I am doing so with a very different toolbox than when I started.

Those postdoc detours into citizen science, environmental monitoring, and human-centered data have fundamentally reshaped how I approach ecology. I now see interdisciplinarity not as a side quest, but as core infrastructure, which is very helpful to make the necessary change happen to save that precious biodiversity I’m working on.

So yes, I now co-author a paper about sleep and smartphones.

And I see all this not as a detour from my scientific trajectory, but as one of the stepping stones that made me a better (perhaps more practical) ecologist.

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De Oorzaak’s final report

We’ve written before on The 3D Lab about De Oorzaak as an ambitious citizen science effort to understand urban soundscapes in Flanders. This week marks an important milestone – the cherry on the cake: the project’s integrated scientific final report is finally out! It brings together years of work into a single synthesis that combines environmental measurements, citizen experiences, and health research.

You can find the mastodont of a report – of which we’re super proud – here: https://www.uantwerpen.be/nl/projecten/de-oorzaak/ (it’s in Dutch, though).

De Oorzaak – for those who missed it so far – is a collaboration between Universiteit Antwerpen, Universitair Ziekenhuis Antwerpen (UZA) and De Morgen, and has grown into the largest citizen science project on environmental noise ever conducted in Flanders. Hundreds of smart sensors, deployed across more than a thousand locations, were paired with ten thousand questionnaire responses to move beyond a simple “how loud is it?” question. Instead, the report asks what kinds of sound environments people actually inhabit, and how these relate to sleep, fatigue, stress, and well-being.

A consistent pattern emerges: higher noise annoyance is associated with poorer sleep quality, more fatigue, and higher stress levels. At the same time, these relationships are not strictly one-way. Being stressed or fatigued for other reasons can also lower tolerance to sound, highlighting that cities function as coupled human–environment systems rather than as collections of isolated stressors.

Reported noise annoyance (subjective) correlated significantly with measured decibels (here: Lden) – one of the many relationships between soundscape experience and sound itself we could unearth in the report.

What resonates most with me in this report is – of course – the strong signal around the role of nature in shaping soundscapes. Natural sounds such as birdsong, rustling leaves, or flowing water are systematically evaluated as more pleasant than mechanical or technical sounds. Crucially, nature does not need to drastically reduce decibel levels to have a restorative effect. Improving the quality of the soundscape already matters.

The report also aims to translate science into action. One of the most concrete ideas perhaps is the proposal for an acoustic label for housing, analogous to the energy performance certificate, alongside recommendations on acoustic renovations, building design, coordinated reporting of noise nuisance and, of course, more nature! Together, these suggestions treat acoustic quality as a fundamental component of healthy living environments rather than an afterthought.

We hope this report can really support and create actual change. Of course, such a citizen science project is about much more than just doing science, we actually want to put the topic front and center in our collective mind, and as such accelerate change.

So, give it a read, and get doing!

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A hell of a nuisance

Non-native species can be, pardon my words, a hell of a nuisance sometimes.

Case in point: invasive pine species in the Southern Hemisphere. Did you know that there are no (none!) native pine species south of the equator? Given how common pines are here in Western Europe, I always found that hard to fathom. But given how common they are in the Southern Hemisphere, it becomes downright mind-boggling.

For over a century, pines have been among the most widely used genera in plantation forestry across many Southern Hemisphere countries, including Chile and Argentina, but also South Africa and New Zealand. The problem is: once they’re there, they start spreading. And many types of native vegetation – such as the iconic Araucaria forests of Chilean Patagonia, or the grasslands of the Patagonian steppe – are highly vulnerable to pine invasion. You can almost see the invasion front creep forward.

The forefront of the Pine invasion, with the Lonquimay-volcano in the background

Even worse, once they’re established, these pines are devastating for native biodiversity. They grow into complex, tangled forests that are extremely hard to get through (“unleashed” pines don’t need straight lines anymore – let alone straight stems). They acidify the soils and smother out the light, resulting in near-deserts underneath their needly branches.

A dense stand of expanding lodgepole pines, with stems growing in all directions, creating an understory that is almost impossible to pass

For nature conservation in places like Patagonia, this is a nightmare. And to make matters worse, it’s pretty tough to get rid of them once they’re established. When I had the opportunity to visit Malalcahuello National Reserve in central Chile (home to the famous ‘monkey puzzle tree’ (Araucaria araucana) forests), I got to see the trouble in action. Pine removal is simply a lot of manual labour, and the end result is far from pretty.

But when they’re gone, they’re gone, right?
…Right?

Experimental sites in the Patagonian steppe before (left) and after (right) pine removal. The left picture shows the density and complexity of the pine canopy, the right picture the ‘desert’-like emptiness that remains here after pine removal.

That’s exactly what we set out to test in a paper just published in the Journal of Vegetation Science, led by our colleagues from the University of Concepción in Chile. From previous work, we already knew how bad pines are for native ecosystems: they significantly reduce the richness and abundance of native species, and cause major changes in microclimatic conditions (air and soil temperature) and soil properties (reductions in nitrogen, potassium, and pH). The big question was: do those systems recover after pine removal?

First, a little good news. Yes, we did see a recovery of microclimatic conditions to levels close to uninvaded control sites, driven by the reduction in pine canopy cover and litter. But… that’s where the good news ended.

Strong effects of pine removal (green) on microclimate conditions, as compared with pre-removal conditions (orange). Where pine canopy reduced maximum temperatures significantly, its removal resulted in consistently high maxima.

We also looked at how native understory diversity responded to pine removal, two years after the intervention. The result? It didn’t do shit. The desert remained just as deserted after pine removal as it was before – especially in the sites that had been most heavily invaded.

Understory plant species diversity parameters as a function of the ton per hectare of pine biomass that was removed, before (orange) versus after (green) pine removal for the Araucania forest site. The graph shows the complete lack of change in understory vegetation, despite the substantial change in pine canopy.

This tells us that the legacy effects of pine invasion are strong, at least up to two years after removal. If anything bounced back at all, it was pine seedlings. Native species barely benefited from the improved microclimate conditions.

Pine seedling

So is this a gloomy story?
Yeah – maybe this time it is.

But that doesn’t make it any less important. It’s crucial to know that some conservation problems are simply a pain in the ass. At least now we know, and we can keep searching for better solutions. Our paper suggests that effective management of invasive conifers must move beyond tree removal alone, and include complementary restoration actions that address persistent abiotic and biotic legacies.

Scattered pine trees in between a few old and persistent Araucaria trees

And perhaps this is, once again, a warning: if you can prevent those pines from establishing in the first place, it’s a whole lot cheaper (and far less annoying) than trying to get rid of them later.
But that’s a different story altogether. Because first we need to know which species to act on before they become annoying… and that’s simply not how we humans tend to work.

An impressive Araucaria-tree, looking out at the volcano

Reference

Fuentes-Lillo et al. (2026) Beyond Control: Short-Term Legacy Effects of Invasive Nonnative Trees May Halt Biodiversity Recovery. Journal of Vegetation Science. https://onlinelibrary.wiley.com/doi/10.1111/jvs.70110

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Don’t mess with physics

Gather ‘round, my friends, because this one is important! A few years ago, we released our Global maps of soil temperature – a project that brought climate data much closer to the conditions that actually matter for the organisms living in and on the soil. However, and this is the important bit: some of our maps are physically impossible.

While defying physics sounds like a big no, I’d say it’s not truly a surprise (I already wrote about similar issues in a warning here). The first version of these maps was always meant as a stepping stone, a workable product that could get our data into the hands of ecologists worldwide, and would be a step up – but not yet a leap – from what we were using up till then. But now, thanks to some careful detective work by Tomas Uxa, we can actually quantify just how our maps break one of the basic rules of heat transfer in soils. His opinion paper on the matter in Global Change Biology is thus a must-read.

Here’s the deal: heat in soils behaves predictably. One key rule is that temperature fluctuations get smaller as you go deeper. Simple, right? Not (always) so in our maps. When comparing two soil depths, an average of 26% of the grid cells – and up to 46% for certain bioclimatic variables – showed reversed patterns. In other words, deeper soils sometimes had bigger temperature swings than shallower ones. Physically impossible (and also only present in less than 5% of the raw data).

Breakdown of the physically impossible differences between the two soil layers of our global mpas, for the relevant bioclimatic variables

Why did this happen? To create our maps, we trained independent machine learning models for each soil depth. Separate models. Separate datasets. And while ML is amazing, it doesn’t inherently respect the laws of physics. The result: maps that are mostly useful, but occasionally rebellious.

Global breakdown of the number of bioclimatic variables per grid cell that is physically impossible. Note that the areas of ‘worst offence’ don’t match with the areas that are suggested to be excluded based on the extrapolation outside of the environmental space of the training data (b-c)

Uxa’s recommendation is practical: the maps are still incredibly useful, but when working with multiple depths, use each depth separately and keep this caution in mind. Any analysis that relies on comparing the two depths directly may produce physically impossible results and should be avoided.

Regional distribution of the proportion of suspicious grid cells among the seven considered soil bioclimatic variables (a) in the European Alps and (b) on the southern margin of the Congolian rainforest. Note that the mismatch closely relates to environmental complexity and steep environmental gradients, such as distinct topography changes or sharp biome transitions. The white areas represent glaciers and water bodies.

And the timing couldn’t be better. We’ve just in earnest started the work on the follow-up: Global maps of soil temperature 2.0, a new version that will hopefully solve many of the problems of its predecessor. The new version will incorporate over three times the data we had before, cover environmental variation better, and – crucially – move toward a one-model approach across depths and months. This should align our predictions more closely with physical reality. We’re also planning higher spatial resolution thanks to the explosion of computing power – so ecologists can finally get the detail that matters at scales that matter.

Up till then, a note of caution: handle our first-generation global soil maps (and really, any global maps) with care, and read Uxa’s piece to understand the quirks. And stay tuned… 2.0 promises to be a big leap forward.

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