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Causes and consequences of forest reorganization: Towards understanding forest change

Project description

Studying the future of our forests

Climate change, the loss of biological diversity and the rapid introduction of alien species are changing the structure and composition of forest ecosystems. Since little is known about the emerging novel ecosystems, forest policy and management are challenging issues. The ERC-funded FORWARD project will shed light on the causes and consequences of reorganisation in forest ecosystems. It will investigate why reorganisation takes place, when and where reorganisation is likely to happen, and what impacts reorganisation will have on biodiversity and ecosystem services. The results will assist in the formulation of early warning indicators of ecosystem reorganisation. Also, a map of hotspots of forest reorganisation will be created using a machine learning synthesis of big data sets.

Objective

Forest ecosystems around the globe are undergoing rapid reorganization. The unabated continuation of climate change, the accelerating rate of alien species introductions, and the precipitous loss of biological diversity are altering the structure and composition of forest ecosystems. As a consequence, novel ecosystems are emerging. However, the trajectories to novelty and the consequences thereof remain widely unknown. This limits the ability of forest policy and management to counteract undesired developments and safeguard the supply of ecosystem services to society. Here I will investigate the causes and consequences of reorganization in forest ecosystems. I will use a concerted combination of complementary methodological approaches to understand why reorganization takes place, when and where reorganization is likely to happen, and what impacts reorganization will have on biodiversity and ecosystem services. Replicated experiments will be conducted both in the field and in walk-in climate chambers to answer whether compounding climatic extremes could result in bottlenecks of forest regeneration. A next-generation forest landscape model will be developed to investigate how invasive alien species alter forest development. Based on these insights the FORWARD project will derive operational early warning indicators of reorganization, and test their generality and applicability in the field for landscapes on three continents. Subsequently, a machine-learning aided synthesis of big datasets will be used to compile the first map of global hotspots of forest reorganization. Finally, robust management strategies for addressing reorganization will be developed. Jointly studying the effects of global change on tree mortality and regeneration across scales, the FORWARD project will bring about a new level of understanding of forest change, and will provide the data, tools and strategies to tackle one of the most pressing challenges of current forest policy and management.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

ERC-COG - Consolidator Grant

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Call for proposal

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(opens in new window) ERC-2020-COG

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Host institution

TECHNISCHE UNIVERSITAET MUENCHEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 965 293,00
Address
Arcisstrasse 21
80333 Muenchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 965 293,00

Beneficiaries (1)

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