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Late-successional unmanaged forests (or old-growth forests) are important terrestrial carbon sinks. Their structurally complex features have been hypothesized to strongly affect forest productivity. However, the mechanisms through which structural complexity influences forest productivity remain unresolved. Here, we report a set of idealised simulations in boreal, sub-boreal, cool-temperate, warm-temperate and tropical forests using a dynamic model of atmosphere and vegetation interactions (Multilayered Integrated Numerical Model of Surface Physics–Growing Plants Interaction, MINoSGI). We aimed to elucidate the effects of tree–size and canopy structural complexity on stand-scale gross primary productivity (GPP) of old-growth forests over 300-year time series. We assumed the tree-size structures of mature old-growth forests as the initial conditions of the simulations. We focused on three different developmental phases of the forests: 29–48 years (phase I), 77–96 years (phase II) and 277–296 years (phase III) from the start of the simulations. Phase I corresponds to an old-growth forest because of our settings of the initial conditions of the simulations, and phase III to a long-term resultant forest without recruitment or mortality. We show that, for a given biome-specific leaf area index (LAI) and individual foliage shape (η), the greatest difference in GPP (ΔGPP) between forests with the most and least structurally complex canopies was 263 g C/m−2(-|-) year−1 in phase I and II when old-growth forests with the most complex canopy structures sustained their complexity, equivalent to almost 13 % of the annual GPP. By contrast, the maximum difference in ΔGPP was reduced to 153 g C/m−2(-|-) year−1 in phase III, equivalent to 8 % of the annual GPP total because the complex canopy structures of old-growth forests without recruitment or mortality approached less multi-layered ones similar to those of less complex and managed forests. Our simulation results indicate that greater tree–size and canopy structural complexity is associated with a broader vertical distribution of foliage, supporting the localisation of leaves in multiple layers. This increases the efficacy of light usage, particularly for shaded leaves receiving only diffuse light within the canopy. As a consequence, for all forest biomes, an increase in in-canopy diffuse light increases GPP in forests with complex canopy structures due to an enhancement of light use efficiency (LUE) of shaded leaves. Overall, our results quantify one of the mechanisms underlying the effects of canopy structural complexity on forest productivity. Moreover, differences in foliage shape between forest biomes can add to uncertainties when predicting GPP based on simulation models. We, therefore, suggest that precise values of the biome-specific factors associated with canopy structure should be employed into simulation models of global carbon budgets.

The area-wide estimation of aboveground biomass (AGB) and its changes as a proxy for the sequestration and emission of carbon are currently associated with high uncertainties. Here we combined interferometric synthetic aperture radar (InSAR) height models derived from TanDEM-X with repeated ground-based inventories from the years 2012 and 2019 to estimate InSAR height and AGB changes in a structurally diverse and dynamic landscape in Sumatra, Indonesia. The results suggested that the InSAR height models were highly accurate and the relationship between InSAR height and AGB change resulted in a coefficient of determination R 2 of 0.65 and a cross-validated root mean square error (RMSE) of 2.38 Mg ha−1 year−1, equivalent to 13.32% of the actual AGB difference range. The estimated AGB changes with TanDEM-X were further related to the initial canopy height and fire activities in the study area. Initial canopy heights and the occurrences of fires had a significant effect on the AGB change. In general, low canopy heights tend to be associated with increasing AGB over time, whereas high canopy heights tend to be associated with stable or decreasing AGB. As expected, fires had a negative impact on the AGB changes being more pronounced in forest areas compared to oil palm concessions. The results of this study are relevant for the utilization of spaceborne InSAR height models and its potential to estimate canopy height and AGB change on large spatial scales. It was demonstrated that these changes can be related to their sources and ecosystem processes. This AGB change estimation technique can be used to model the impacts of fires on AGB change and carbon emissions, which are important for sustainable forest management.

International audience

Deadwood is a fundamental structural and functional component of forests, with a crucial role in supporting forest biodiversity, nutrient and carbon cycling. Precise deadwood density estimates and its relation to envi-ronmental factors are necessary to evaluate the biomass and carbon stocked in this component. In this study, we estimated dry deadwood density for two different tree species, silver fir (Abies alba) and European beech (Fagus sylvatica) and for three snags and five logs decomposition classes in a virgin mixed beech-fir forest in the Southern Carpathians. The goal was to assess how deadwood density is influenced by different abiotic (moisture, elevation, slope, aspect) and wood-related factors (rottenness, position along the piece, contact with the soil). For snags, the mean dry density showed a reduced variability within decomposition classes (484-326 kg.m- 3 for beech and 374-319 kg.m- 3 for fir), compared to the logs (486-139 kg.m- 3 for beech and 359-161 kg.m- 3 for fir). While the mass moisture varied slowly in the first three decay classes (around 60-80 %), it increased sharply in the last two decay classes of logs (>140 % in the fourth class and > 350 % in the last one). The rottenness increased with the decay class in a similar way for both species. The contact of logs with the soil influenced positively the moisture, but the position of the sampling within the piece did not play any significant role in the variability of density. Based on density estimates per decay classes we estimated that the carbon (C) stored in deadwood varied greatly among the 21 plots from 0.36 to 41.16 MgC ha-1, with a mean value of 15.96 +/- 2.36 (+/- SE) MgC ha-1. Our study suggests that volume-based calculations might yield biased quantitative estimates of C stored in deadwood unless a local estimate of dead wood density corrected per species and decomposition class is applied. Moreover, the use of an averaged value of dry density instead of value for each decay class may result in an overestimation of 22% on the estimation of C stock. Thus, our study emphasises the importance of considering decay class-specific values in future inventories of C stocks in other forests and for other species. Furthermore, it could serve as a methodological basis for more specific research designed to uncover the potential influence of different forest management practices on dry deadwood density.