Biology subjects

Astrup, R.

Publications and source records attributed to Astrup, R..

3 recordsLinked to original sources

bioRxiv2025

Factors influencing birch (Betula spp.) age distribution in Norway: Insights from tree ring data

The age-class distribution of forests is a key indicator of both carbon stock potential and biodiversity conservation, playing a vital role in sustainable forest management. In Norway, birch (Betula spp.) is the most abundant tree species, covering 42% of the forest area. Understanding the factors that shape the age structure of birch is essential for developing management practices that balance timber production, carbon sequestration, and biodiversity conservation. Using data from the Norwegian National Forest Inventory (NFI), we examined the age-class distribution of birch trees across various site conditions. Our analysis revealed that middle-aged trees (50-100 years) were prevalent in most regions, while older trees were notably scarce, particularly in highly productive areas. This pattern reflects management strategies prioritizing younger, fast-growing trees to maximize economic returns. In contrast, less productive sites, which are often managed less intensively, tend to support older trees. Additionally, younger birch trees revealed significantly greater radial growth than older generations when evaluated at the same biological age (e.g., at 10 years old), particularly under favorable site conditions. These findings underscore the combined effects of site productivity, forest management, and environmental factors on growth dynamics and age-class distribution.

ecology↗

bioRxiv2025

A high-resolution, country-wide scenario analysis of forest susceptibility to spruce bark beetle damage in Norway

The European spruce bark beetle (Ips typographus (L.)) poses a growing threat to Norways forests under climate change, particularly in extensive spruce-dominated forests. Because controlling active outbreaks is notoriously difficult, reducing forest susceptibility through proactive management is essential. In this study, we used high-resolution simulations covering all of Norways forested land ([~]120,000 km2) to explore how different harvesting strategies affect long-term forest susceptibility to SBB damage. We compared a no-harvest baseline, a business-as-usual regime guided by economic criteria, and a risk-informed strategy that prioritizes harvesting of the most susceptible stands. Across two climate trajectories, we found that susceptibility-guided harvesting significantly reduced average forest susceptibility and fragmented high-risk areas, particularly in southern Norway. However, our results also reveal limitations to this approach: even with aggressive susceptibility-guided harvesting, long-term risk reductions plateau due to the homogenizing effects of even-aged forestry. Spatial connectivity analysis using electrical circuit theory further showed that susceptibility-guided harvesting disrupted landscape continuity among high-risk patches, suggesting a potential to constrain outbreak spread. These findings highlight the value of integrating susceptibility indicators and spatial connectivity metrics into forest planning to support adaptive, risk-informed management under climate uncertainty.

ecology↗

bioRxiv2024

deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, not standardized and not spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map tree mortality over time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Drones provide a cost-effective source of training data by capturing high-resolution orthophotos of tree mortality events at sub-centimeter resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than a thousand centimeter-resolution orthophotos, covering already more than 300,000 ha, of which more than 58,000 ha are fully annotated. This community-sourced and rigorously curated dataset shall serve as a foundation for a global initiative to gather comprehensive reference data. In concert with Earth observation data and machine learning it will serve to uncover tree mortality patterns from local to global scales. This will provide the foundation to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. Thus, the open and interactive nature of deadtrees.earth together with the collective effort of the community is meant to continuously increase our capacity to uncover and understand tree mortality patterns.

ecology↗