Marta Vergarechea
Forsker
(+47) 453 94 023
marta.vergarechea@nibio.no
Sted
Ås - Bygg H8
Besøksadresse
Høgskoleveien 8, 1433 Ås
Forfattere
Ignacio Sevillano Aksel Granhus Clara Antón Fernandéz Heleen de Wit Fride Høistad Schei Rannveig Margrete Jacobsen Ulrika Jansson Asplund Heikki Korpunen Christian Wilhelm Mohr Jenni Nordén Jørund Rolstad Svein Solberg Ken Olaf Storaunet Marta VergarecheaSammendrag
There is an increasing interest in continuous cover forestry (CCF) as an alternative to clearcutting to promote multi-objective forests and preserve continuous maintenance of forest cover. Here, we assessed the effect that an increased use of CCF harvesting methods (shelterwood and selection cutting) in Norwegian forests can have on carbon sequestration. Thus, we simulated CO2 uptake in Norwegian forest stands throughout the 21st century under three scenarios that represent different levels of clearcutting and CCF harvesting methods, keeping the annual harvest volumes constant across all scenarios. The three scenarios are: 1) Business-as-usual (reference scenario where 3.5% of the harvested volume is obtained using CCF harvesting methods); 2) Harvested volume using CCF harvesting methods is increased to 15%; 3) Harvested volume using CCF harvesting methods is increased to 25%. Increasing the proportion of CCF would increase CO2 removals in the long-term (2100), resulting in an additional uptake of nearly 32 and 24 Tg CO2 when increasing CCF up to 25% and 15%, respectively. However, the simulations also showed that to be able to harvest the same timber volume as in the reference scenario that reflects current practice, an increased proportion of CCF would also require logging on a larger proportion of the forest area. CCF could have also positive implications for certain aspects of biodiversity, such as species that require shaded conditions, but harvesting across a larger total area could negatively impact other animals, plants and fungi.
Forfattere
Fulvio Di Fulvio Tord Snäll Pekka Lauri Nicklas Forsell Mikko Mönkkönen Daniel Burgas Clemens Blattert Kyle Eyvindson Astor Toraño-Caicoya Marta Vergarechea Clara Antón-Fernández Julian Klein Rasmus Astrup Jani Lukkarinen Samuli Pitzén Eeva PrimmerSammendrag
The EU Biodiversity Strategy (EUBDS) for 2030 aims to conserve and restore biodiversity by protecting large areas throughout the European Union. A target of the EUBDS is to protect 30 % of the EU’s land area by 2030, with 10 % being strictly protected (including all primary and old growth forests) and 20 % being managed ‘closer to nature’. Even though this will have a positive impact on biodiversity, it may negatively impact the EU’s wood-based bioeconomy. In this study, we analyze how alternative interpretations and distributions of the EU’s protection targets may affect future woody biomass harvest levels, exports of wood commodities, and the spatial distribution of managed areas under wood demands aligned with SSP2-RCP1.9. Using the model GLOBIOM-Forest, we simulate scenarios representing a variety of interpretations and geographic distributions of the EUBDS targets. The EUBDS targets would have a limited impact on EU harvest levels since the EU can still increase its wood harvest between 21 % and 24 % by 2100. With strict protection of 30 % of the area, the EU harvest level can still be increased by 10 %. Moreover, the most likely scenario (10 %/20 % protection within each MS) will result in increased net exports in the coming decades, but a slight decline after 2050. However, if protection is intended to also represent site productivity or to re-establish a green infrastructure, then EU net exports will also decline before 2050. With the decreased EU roundwood harvest, increased harvest will occur in other biomes and mostly leaking into boreal regions.
Sammendrag
Det er ikke registrert sammendrag
Divisjon for skog og utmark
REell GENEtisk FRemgang I SKogplanteforedlingen
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
A Decision Support System for emerging forest management alternatives
This project aims to develop advanced tree growth models using LiDAR-derived, high-density point cloud data to improve the simulation of forest dynamics under close-to-nature silvicultural practices. By modeling tree-level growth in structurally complex and heterogeneous stands, these models will support more accurate, spatially explicit forest simulations and inform sustainable and diversified forest management decisions.