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Tropical forests store 40-50% of terrestrial vegetation carbon 1 . Spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests 2 . Owing to climatic and soil changes with increasing elevation 3 , AGC stocks are lower in tropical montane compared to lowland forests 2 . Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC-stock of 149.4 Mg C ha -1 (95% CI 137.1-164.2), comparable to lowland forests in the African Tropical Rainforest Observation Network 4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane 2,5,6 and lowland 7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the IPCC default values for these forests in Africa 8 . We find that the low stem density and high abundance of large trees of African lowland forests 4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million ha of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse 9,10 and carbon-rich ecosystems.

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Abstract. Disturbances, such as extreme weather events, fires, floods, and biotic agents, can have strong impacts on the dynamics and structures of tropical forests. In the future, the intensity of disturbances will likely further increase, which may have more serious consequences for tropical forests than those we have already observed. Thus, quantifying aboveground biomass loss of forest stands due to stem mortality (hereafter biomass loss rate) is important for the estimation of the role of tropical forests in the global carbon cycle. So far, the long-term impacts of altered stem mortality on rates of biomass loss have not been adequately described. This study aims to analyse the consequences of long-term elevated stem mortality rates on forest dynamics and biomass loss rate. We applied an individual-based forest model and investigated the impacts of permanently increased stem mortality rates on the growth dynamics of humid, terra firme forests in French Guiana. Here, we focused on biomass, leaf area index (LAI), forest height, productivity, forest age, quadratic mean stem diameter, and biomass loss rate. Based on the simulation data, we developed a multiple linear regression model to estimate biomass loss rates of forests in different successional states from the various forest attributes. The findings of our simulation study indicated that increased stem mortality altered the succession patterns of forests in favour of fast-growing species, which increased the old-growth forests' gross primary production, though net primary production remained stable. The stem mortality rate had a strong influence on the functional species composition and tree size distribution, which led to lower values in LAI, biomass, and forest height at the ecosystem level. We observed a strong influence of a change in stem mortality on biomass loss rate. Assuming a doubling of stem mortality rate, the biomass loss rate increased from 3.2 % yr−1 to 4.5 % yr−1 at equilibrium. We also obtained a multidimensional relationship that allowed for the estimation of biomass loss rates from forest height and LAI. Via an example, we applied this relationship to remote sensing data on LAI and forest height to map biomass loss rates for French Guiana. We estimated a countrywide mean biomass loss rate of 3.0 % yr−1. The approach described here provides a novel methodology for quantifying biomass loss rates, taking the successional state of tropical forests into account. Quantifying biomass loss rates may help to reduce uncertainties in the analysis of the global carbon cycle.

Abstract. Disturbances can have strong impacts on the dynamics and structure of tropical forests. They often lead to increased tree mortality and affect their behaviour as carbon sinks. In the future, the intensity of disturbances, such as extreme weather events, fires, floods, and biotic agents, will probably even increase, with more serious consequences for tropical forests than we have already observed. However, impacts of altering disturbances on rates of forest biomass loss through tree mortality (hereinafter: biomass mortality) have been little described yet. This complicates progress in quantifying the effects of climate change on forests globally. This study aims to analyse the consequences of elevated tree mortality on forest dynamics and to provide a methodology that can reduce uncertainties in estimating biomass mortality rates at local and country level. We achieved this by linking benefits of individual-based forest model-ling, statistical linear regression, and remote sensing. We applied an individual-based forest model to investigate the impact of varying disturbance regimes on the succession dynamic of a humid Terra Firma forest at the Paracou study site in French Guiana. By simulating increased tree mortality rates, we were able to investigate their influence on several forest attributes, namely biomass, leaf area index, forest height, gross primary production, net primary production, and biomass mortality. Based on simulations of leaf area index and forest height, we developed a linear multivariate regression model to project biomass mortality. Our findings demonstrate that severe disturbances altered the succession pattern of the forests in favour of fast-growing species, which changed gross primary production, but net primary production remained stable. We also observed a strong influence on biomass mortality rates as well as observed complex relationships between these rates and single forest attributes (leaf area index, forest height, and biomass). By combining leaf area index and forest height we obtained relationships that allow an estimation of the biomass mortality. Based on these findings, we mapped the biomass mortality for whole French Guiana. We found a nation-wide biomass mortality of 3 % per year (standard deviation = 1.4 % per year). The approach we describe here, provides a novel methodology for quantifying the spatial-temporal distribution of biomass loss, which has recently been identified as particularly critical for monitoring mortality hot spots. Quantifying biomass mortality rates may help reducing uncertainties in the terrestrial component of the global carbon cycle.

Abstract. Disturbances, such as extreme weather events, fires, floods, and biotic agents, can have strong impacts on the dynamics and structures of tropical forests. In the future, the intensity of disturbances will likely further increase, which may have more serious consequences for tropical forests than those we have already observed. Thus, quantifying aboveground biomass loss of forest stands due to tree mortality (hereafter biomass loss) is important for the estimation of the role of tropical forests in the global carbon cycle. So far, the long-term impacts of altered tree mortality on rates of biomass loss have been described little. This study aims to analyse the consequences of long-term elevated tree mortality rates on forest dynamics and biomass loss. We applied an individual-based forest model and investigated the impacts of permanently increased tree mortality rates on the growth dynamics of humid, terra firme forests in French Guiana. Here, we focused on biomass, leaf area index (LAI), forest height, productivity, forest age, quadratic mean stem diameter, and biomass loss. Based on the simulations, we developed a multiple linear regression model to estimate biomass losses of forests in different successional states from the various forest attributes. The findings of our simulation study indicated that increased tree mortality altered the succession patterns of forests in favour of fast-growing species, which changed the forests’ gross primary production, though net primary production remained stable. Tree mortality intensity had a strong influence on the functional species composition and tree size distribution, which led to lower values in LAI, biomass, and forest height at the ecosystem level. We observed a strong influence of a change in tree mortality on biomass loss. Assuming a doubling of tree mortality, biomass loss increased (from 3.2 % y−1 to 4.5 % y−1). We also obtained a multidimensional relationship that allowed for the estimation of biomass loss from forest height and LAI. Via an example, we applied this relationship to remote sensing data of LAI and forest height and mapped biomass loss for French Guiana. We estimated a mean biomass loss rate of 3.2 % per year. The approach described here provides a novel methodology for quantifying biomass loss, taking the successional state of tropical forests into account. Quantifying biomass loss rates may help to reduce uncertainties in the analysis of the global carbon cycle.

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