Arctic forest futures - An integrative approach to understanding and anticipating ecological transitions in the forest-tundra ecotone

Under climate warming, the border-zone (ecotone) between boreal forest and arctic tundra may exhibit three types of ecological transition involving tall-growing woody vegetation, namely the expansion of trees and tall shrubs into currently treeless tundra, changes in tree species composition in existing forest and recovery of forest following climate-related disturbances like insect outbreaks. Each transition will cause major changes in ecosystem functions, including radiation balance, hydrology and carbon sequestration. In all cases, the recruitment of new trees from seed is a bottleneck that will determine if and how rapidly the transitions occur. Arctic Forest Futures will develop the knowledge and tools that are needed to monitor, understand and anticipate such transitions in the north-Fennoscandian forest-tundra ecotone, using birch and pine in eastern Finnmark as the model system. We will use process-based models to better understand constraints on the growth of young birch and pine under past, present, and expected future climate scenarios. We will also identify key determinants of recruitment success in birch and pine by combining new field data gathered during the project with extensive existing data from the ecosystem-based monitoring program COAT – Climate-ecological Observatory for Arctic Tundra. Finally, we will use new remote sensing and machine learning techniques to develop a semi-automated system for mapping and monitoring changes in forest distribution. In collaboration with a reference group consisting of forest managers and other stakeholders, the results from the various project activities will be complied in a popular synthesis, where the goal is to identify the combinations of manageable and non-manageable drivers that may precipitate the different transition scenarios. The project will thus facilitate planning and adaptation in the face of the pervasive ecological changes that are expected for the forest-tundra ecotone in the coming decades.

The project targets ecological transitions driven by climatic and biotic stressors in a high-latitude system, the ecotone between sub-arctic birch forest and low-arctic tundra. The uniqueness of the system stem from its ecological context as a narrow deciduous belt in between arctic tundra and the vast coniferous taiga, a high exposure and suspected vulnerability to rapid climate change, as well as access to existing ecosystem-based monitoring data and research infrastructure through the long-term monitoring program COAT. We use a multi-transition conceptual framework, based on the anticipation that the system will be labile to multiple fundamental climate-driven transitions related to expansion of trees and shrubs, increased intermixture of birch and pine as well as a recovery of birch forest in woodlands currently disturbed by pest outbreaks. We focus on the recruitment niche of trees as the common bottleneck determining if tree cover will be lost, gained, or change species composition over time. Expanding upon on a successful collaboration with forestry stakeholders, we target pressing knowledge gaps identified by management related to the relative role of manageable and non-manageable drivers of forest changes in the region. Through this we will facilitate more efficient mapping and monitoring of tree cover changes by harnessing new machine learning and remote sensing based methodologies. We will foster ability to understand and anticipate climate driven ecotone transition scenarios by a combination of targeted field surveys addressing both constrainers and facilitators of recruitment, reuse of existing monitoring data from COAT and regional scale modelling of forest growth constraints under past, present, and near future climate regimes. The project will culminate in a knowledge synthesis, targeted to the stakeholders, where multiple lines of evidence underpinning transition scenarios are evaluated according to an established protocol for ecosystem assessment.