Rewilding efforts in Europe currently comprise mostly of small-scale or local initiatives scattered across the continent. However, as European countries continue to look for ways to address the pressing climate and biodiversity crises, large-scale ecosystem restoration is increasingly being considered by governments as a pathway to a more sustainable future.
Whilst we already have a solid understanding of rewilding’s local environmental benefits, such as biodiversity restoration, flood protection and soil health enhancement, expanding these efforts on a continental level requires a more comprehensive understanding of its larger-scale, and even global, impacts.
As part of the wildE project, researchers Almut Arneth and Mark Rounsevell from Karlsruhe Institute of Technology are employing advanced ecosystem and land-use change modelling techniques to better understand rewilding’s potential impacts on biodiversity, the climate and people across Europe, and globally.
The wildE modelling approach
Due to the complexity and scale of the scenarios that must be understood to develop a more comprehensive vision of rewilding’s potential, wildE’s research employs a two-pronged approach to modelling.
In the first component, the modelling team produce spatial maps that identify where potential areas for rewilding are located across Europe. The approach uses datasets to assess land availability, carbon stock potential and ecological potential.
Once these characteristics have been considered, the team go on to map complex scenarios to assess how people use the land in these areas identified for rewilding, and how this may change over time depending on socio-economic considerations. This second component takes into account the human behaviours and processes of cooperation and competition that underpin decision-making choices of individual land users, and how this impacts landscapes, their users and their uses. Then, the team are able to evaluate the biophysical responses of rewilded ecosystems to restoration through models of ecosystem functioning, including carbon sequestration.
Furthermore, by estimating “opportunity-costs” (the economic or productive value of the land if it were to be used for a purpose other than ecological restoration), we are able to gain a more nuanced understanding of the impacts of rewilding. For example, if an area of agricultural land is rewilded, we need to understand where the displaced food production will shift to and what global economic and environmental consequences this may cause. In this case, rewilding could potentially lead to increased food imports, which could result in higher costs, higher emissions and, depending on the food source, could contribute to deforestation in other parts of the world.
Once all this information has been collected, it will be mapped on to models of two different scales: a European scale, which is modelled on a 1km by 1km (or 100 hectare) grid across the continent, and a global scale, which draws on other global modelling technologies to assess the impact of what may happen in Europe on other parts of the world.
Overcoming the challenges of rewilding modelling
This work is harnessing the untouched potential of socio-ecological modelling to gain a more nuanced understanding of rewilding, which will help us to increase its impact continent-wide. Nonetheless, limited existing research in this area has undoubtedly led to some challenges for the team along the way.
Firstly, in order to model the levels of carbon in a certain cropland or forest, we need to understand how this land has been managed throughout history. Whilst this information is available on a country level, for example we can find out how much timber is produced in Germany or how much wheat is grown in the UK, this information is not mapped at a small enough scale to create an individual 1km grid level.
Secondly, despite carbon dioxide uptake through rewilding being considered as a means to mitigate climate change, we must consider the implications that rising global temperatures may have on the areas of land identified for rewilding. As climate change continues to threaten all ecosystems, it is likely to also be a risk for any restored forests. As the climate gets hotter and drier, the risk that rewilded ecosystems die from heat or drought increases. When considering such scenarios, there is a danger that any potential rewilding initiatives may not actually be able to prevail over the next 60 to 80 years.
What’s next?
The uncertainty surrounding some of these scenarios has undoubtedly posed obstacles in the research. However, as Almut, Mark and their team begin to overcome these challenges, the models are starting to take form.
The project is now preparing to share some of these results.