Cross-scale convergence in the carbon balance of managed boreal forests in Northern Sweden

• Multi-scale comparison of bottom-up and top-down estimates of boreal forest NEP. • Three-year mean NEP estimates converged across plot, landscape, and regional scales. • Inter-annual NEP trends varied across measurement approaches and spatial scales. • NEP response to 2018 drought differed between bottom-up and top-down estimates. • Results consolidate the strong C sink-strength of actively managed boreal forests. Boreal forests are globally important carbon (C) sinks, but strategies for maximising their climate benefit remain under debate. Major uncertainties in this discussion arise from contrasting sink-source estimates, which largely emanate from inherent limitations of standard measurement techniques to distinct spatio-temporal scales. Here, we use a spatially-nested measurement framework that integrates bottom-up (forest-plot inventory and chamber-based fluxes) and top-down (eddy-covariance; atmospheric observations and atmospheric transport modelling) approaches to reconcile the C balance of actively managed boreal forests in Northern Sweden across plot-, ecosystem-, landscape-, and regional scales during 2016–2018. We found that 3-year mean estimates of the net ecosystem production (NEP) across plot-, landscape-, and regional scales did not differ significantly, converging into a mean (± 95 % confidence interval) C sink of 118 ± 27 g C m -2 yr -1 . We also noted a convergence across these scales for the 3-means of the NEP components, i.e., gross primary production (908 ± 48 g C m -2 yr -1 ) and ecosystem respiration (790 ± 40 g C m -2 yr -1 ). However, estimates of the inter-annual variations in NEP and its components were inconsistent among most scales and measurement approaches. Furthermore, our results indicate a scale-dependency in the NEP response to the 2018 European summer drought, with a greater reduction of NEP observed in bottom-up compared to top-down estimates. Thus, this study consolidates the C sink-strength of managed boreal forests and advocates the need for cross-scale assessments to constrain forest C cycle-climate feedbacks.

Authors

Institutions

Publication Details

Journal
Agricultural and Forest Meteorology
Published
2025-11-21
DOI
https://doi.org/10.1016/j.agrformet.2025.110926
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cross-scale convergence in the carbon balance of managed boreal forests in Northern Sweden

Natascha Kljun, Jinshu Chi, Anne Klosterhalfen, Tomas Lundmark et al.
Agricultural and Forest Meteorology
Plant Water Relations and Carbon Dynamics
article

Cross-scale convergence in the carbon balance of managed boreal forests in Northern Sweden

Natascha Kljun, Jinshu Chi, Anne Klosterhalfen, Tomas Lundmark, Hjalmar Laudon, Zhao Pen, Guillaume Monteil, Mats B. Nilsson, Eduardo Martínez García, Matthias Peichl, Jörgen Wallerman, Johannes Larson, Marko Scholze, Anusha Sathyanadh
article en

Abstract

• Multi-scale comparison of bottom-up and top-down estimates of boreal forest NEP. • Three-year mean NEP estimates converged across plot, landscape, and regional scales. • Inter-annual NEP trends varied across measurement approaches and spatial scales. • NEP response to 2018 drought differed between bottom-up and top-down estimates. • Results consolidate the strong C sink-strength of actively managed boreal forests. Boreal forests are globally important carbon (C) sinks, but strategies for maximising their climate benefit remain under debate. Major uncertainties in this discussion arise from contrasting sink-source estimates, which largely emanate from inherent limitations of standard measurement techniques to distinct spatio-temporal scales. Here, we use a spatially-nested measurement framework that integrates bottom-up (forest-plot inventory and chamber-based fluxes) and top-down (eddy-covariance; atmospheric observations and atmospheric transport modelling) approaches to reconcile the C balance of actively managed boreal forests in Northern Sweden across plot-, ecosystem-, landscape-, and regional scales during 2016–2018. We found that 3-year mean estimates of the net ecosystem production (NEP) across plot-, landscape-, and regional scales did not differ significantly, converging into a mean (± 95 % confidence interval) C sink of 118 ± 27 g C m -2 yr -1 . We also noted a convergence across these scales for the 3-means of the NEP components, i.e., gross primary production (908 ± 48 g C m -2 yr -1 ) and ecosystem respiration (790 ± 40 g C m -2 yr -1 ). However, estimates of the inter-annual variations in NEP and its components were inconsistent among most scales and measurement approaches. Furthermore, our results indicate a scale-dependency in the NEP response to the 2018 European summer drought, with a greater reduction of NEP observed in bottom-up compared to top-down estimates. Thus, this study consolidates the C sink-strength of managed boreal forests and advocates the need for cross-scale assessments to constrain forest C cycle-climate feedbacks.

Agricultural and Forest MeteorologyVol. 377
Lund University (SE), Norwegian University of Science and Technology (NO), Barcelona Supercomputing Center (ES), Swedish University of Agricultural Sciences (SE), Natural Resources Institute Finland (FI), University of Göttingen (DE), University of Hong Kong (HK), Northwest A&F University (CN), South China University of Technology (CN), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 67%
Plant Water Relations and Carbon Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.