SmartReForest

Smart Solutions for Resilient Reforestation: Securing Ecosystem Services in a Changing Climate

Bavaria’s forests are under immense pressure. Heat, drought, storms, and pests are leaving visible marks—entire landscapes are being transformed. What may appear as isolated patches of damaged woodland is, in reality, a systemic problem: intact forest ecosystems are indispensable for biodiversity, water supply, and climate protection. However, their stability is increasingly faltering.

This is where SmartReForest comes in. The project develops a scientifically sound yet practical concept for the climate-resilient reforestation of damaged forests in Bavaria. The goal is not merely to plant trees, but to rethink forests: as multifunctional, resilient ecosystems capable of thriving under altered climatic conditions.

In three closely intertwined subprojects, SmartReForest combines cutting-edge technology with forestry and ecophysiological expertise:

• Subproject 1 identifies and prioritizes current and future high-risk areas. Using multispectral satellite data, AI-supported image processing, and time-series modeling, precise risk maps are generated to serve as a basis for strategic decision-making.
• Subproject 2 develops climate-resilient reforestation and management strategies. Using the vegetation model LPJ-GUESS, scenarios are simulated under various climatic conditions—focusing on biodiversity, water balance, and sustainable timber production. The role of emergency irrigation as a key factor for successful sapling establishment is also systematically considered.
• Subproject 3 ensures the long-term success of these measures. AI-supported monitoring and irrigation systems, based on remote sensing and ecophysiological measurements, enable the early detection of drought stress and targeted water supply down to the individual tree level.

The result is an integrated, data-driven Decision Support System (DSS) that combines site prioritization, optimized reforestation strategies, and adaptive management into a single tool.

Added value is generated through the close collaboration of researchers from forest science, ecophysiology, vegetation modeling, and AI-based remote sensing at the Weihenstephan campus. Networking with the Bavarian State Institute of Forestry (LWF) and existing partnerships in the Franconian Forest (Frankenwald) model region ensure practical relevance. Simultaneously, SmartReForest is deeply integrated into the bayklif2 network, actively utilizing synergies with other AI and remote-sensing-oriented projects.

Background

Forests are silent high-performers. They store carbon, regulate water cycles, protect soils, and provide habitats for an enormous diversity of species. However, the limits of their resilience have been reached in many places.

In the Franconian Forest alone, nearly 20 percent of forest areas are damaged. Nationwide in Germany, over 500,000 hectares are in need of reforestation. Many clear-cut areas already face extreme microclimatic conditions: high temperatures, low humidity, and intense solar radiation. The survival rate of young trees is dropping drastically—a trend likely to worsen as climate change progresses. Despite these dynamics, key research gaps remain:

• Which areas are particularly vulnerable now and in the future?
• Which reforestation strategies will secure biodiversity, water balance, and timber production in the long term?
• How can the establishment of young trees be stabilized under increasingly arid conditions?

SmartReForest builds on existing preliminary work, particularly in the advancement and application of the LPJ-GUESS vegetation model. The consortium brings together complementary expertise in forest science, ecophysiology, and AI-driven data analysis—a combination that allows for the merging of scientific depth with operational feasibility.

Methods and Objectives

SmartReForest pursues an integrative research approach that systematically links remote sensing, vegetation modeling, AI-based data analysis, and ecophysiological experiments.

• In SP1, multispectral satellite data are analyzed using deep learning techniques. Time-series models, coupled with climate scenarios and biogeographical information on habitat connectivity, enable the identification and spatial prioritization of high-risk areas.
• In SP2, the LPJ-GUESS model is used to simulate different reforestation and management strategies under varying climate scenarios. Through robust multi-criteria optimization, strategies are developed to best secure biodiversity, water cycles, and timber production even under conditions of uncertainty.
• In SP3, greenhouse and field experiments are combined with modern sensor technology and AI-supported remote sensing. The goal is to derive species-specific irrigation corridors and predict water requirements at the individual tree level.

The overarching goal: An operational Decision Support System that is data-driven, adaptive, and practical – realigning forest management strategically for a changing climate.

Immediate Added Value for the Free State of Bavaria

The reforestation of damaged forests is not only an ecological necessity but also a legal obligation. SmartReForest provides the evidence-based foundations for this task.

The benefit is direct: approximately two-thirds of Bavaria’s water protection zones are located in forests. Stabilizing forest ecosystems therefore directly protects the drinking water supply. The developed Decision Support System enables the efficient allocation of limited resources and can be integrated into existing instruments, such as forest management funding programs.

The combination of AI, remote sensing, and vegetation modeling creates an innovative leap with high “translatability” into forestry practice. The involvement of the Waldbesitzervereinigung Kronach-Rothenkirchen (Forest Owner Association) as a practical partner ensures direct application in the heavily affected Franconian Forest region.

Furthermore, the methods and tools are transferable to other regions of Bavaria, Germany, and beyond. Finally, the project strengthens the research landscape at the Weihenstephan site through interdisciplinary capacity building and targeted support for early-career researchers.

Potential Synergies within bayklif2

Within bayklif2, SmartReForest centrally addresses the themes of “Biodiversity” and “Water.” The subprojects mesh like gears:

• SP1 provides spatial decision bases for SP2.
• SP3 feeds empirical survival data back into strategy optimization.
• All results flow into a shared Decision Support System.

The physical proximity and established cooperation at the Weihenstephan campus foster rapid knowledge transfer and true interdisciplinarity. Beyond the funding period, further perspectives emerge:

• The developed AI models and data infrastructures can be established as permanent operational tools for use by forest authorities.
• Transferring these methods to urban contexts—such as climate-adaptive urban greening—is also highly promising.

In the long term, SmartReForest does more than just replant trees. It creates a data-driven foundation for resilient forest ecosystems—helping to secure their services for generations to come.