Rasmus Astrup
Forskningssjef
Forfattere
Marta Vergarechea C Antón-Fernández J.U Jepsen Ole Petter Laksforsmo Vindstad Nicolas Cattaneo J.J Camarero Rasmus AstrupSammendrag
resilience. In Norway, birch species (Betula pendula and Betula pubescens) dominate large areas of boreal forest, yet large-scale patterns of their age distribution and growth dynamics remain poorly quantified. Using increment core data from 2818 trees sampled across the Norwegian National Forest Inventory, spanning five vegetation zones (58–71◦N) and a broad productivity gradient, we analyzed the drivers of birch age structure and growth variation across age classes and historical cohorts. Intermediate-aged trees (35–80 years) dominated most regions, whereas older individuals were scarce, particularly on productive sites, reflecting the combined effects of forest management and the life-history strategy of fast-growing pioneer species. When compared at equivalent biological ages, younger trees consistently showed higher basal area increment (BAI) than older trees, with differences strongest during early development and on productive sites. Cohort analyses showed a pronounced long-term increase in juvenile growth: mean BAI during the first ten years after reaching breast height increased steadily across successive cohorts over the past 150 years. This increase became more pronounced after ~1960 and was consistent across vegetation zones and site productivity classes. Although sampling and survivor bias cannot be fully excluded, the consistency across environmental gradients points to broad-scale changes in early growth dynamics of birch forests in Norway. These results underscore the importance of considering both age structure and cohort-related variation when interpreting forest dynamics and planning future management.
Forfattere
Xinlian Liang Yinrui Wang Jun Pan Janne Heiskanen Ningning Wang Siyu Wu Ilja Vuorinne Jiaojiao Tian Jonas Troles Myriam Cloutier Stefano Puliti Aishwarya Chandrasekaran James Ball Xiangcheng Mi Guochun Shen Kun Song Guofan Shao Rasmus Astrup Yunsheng Wang Petri Pellikka Mi Wang Jianya GongSammendrag
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Sammendrag
Collection, processing and provision of comprehensive geometric information of forest roads is decisive for its technical classification to facilitate sustainable timber supply chains. An automized classification system based on the mobile proximal sensor platform RoadSens was developed, applied and validated through a case study approach in Eastern Norway. Six sample roads of various vegetation stages were surveyed through RoadSens and complemented through sampled total station measurements for validation purposes. The determined geometric parameters road slope, curvature and width were used for technical classification following the national forest road standard. Road width was identified as the main constraint in meeting the standard, resulting in a general downgrading of the sampled roads according to its technical class. The results showed a root mean square error (RMSE) ranging from ±0.53 to 1.50 m (12–33%) depending on the road and vegetation stage compared to the validation data. Despite these accuracy constraints, the application case study already indicates a general need for improvement of road data acquisition and updating of associated databases. The study underscores that, despite the challenges and limitations, there is a clear need for an automated sensing and classification system, which offers a cost-effective alternative to manual surveying and requires less specialized expertise.
Divisjon for skog og utmark
SPADE: Multi-purpose physical-cyber agri-forest drones ecosystem for governance and environmental observation
The strategic objective of SPADE project is to develop an intelligent ecosystem to address the multiple purposes concept in the light of deploying unmanned aerial vehicles (UAVs alias drones) to promote sustainable digital services for the benefit of a large scope of end users in sectors of crop production, forestry, and livestock. This includes individual UAV usability, UAV type applicability (e.g., swarm, collaborative, autonomous, tethered), UAV governance models availability and UAV-generated data trustworthiness.
Divisjon for skog og utmark
PathFinder - Towards an Integrated Consistent European LULUCF Monitoring and Policy Pathway Assessment Framework
Divisjon for kart og statistikk
A climate for spruce? New forest management to mitigate bark beetle risks under climate change
Divisjon for skog og utmark
PathFinder
Towards an Integrated Consistent European LULUCF Monitoring and Policy Pathway Assessment Framework
Divisjon for skog og utmark
SFI SmartForest: Bringing Industry 4.0 to the Norwegian forest sector
SmartForest will position the Norwegian forest sector at the forefront of digitalization resulting in large efficiency gains in the forest sector, increased production, reduced environmental impacts, and significant climate benefits. SmartForest will result in a series of innovations and be the catalyst for an internationally competitive forest-tech sector in Norway. The fundamental components for achieving this are in place; a unified and committed forest sector, a leading R&D environment, and a series of progressive data and technology companies.