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Over the past 4 decades, Southwest China has the fast vegetation growth and aboveground biomass carbon (AGC) accumulation, largely attributed to the active implementation of ecological projects. However, Southwest China has been threatened by frequent extreme drought events recently, potentially countering the expected large AGC increase caused by the ecological projects. Here, we used the L-band vegetation optical depth to quantify the AGC dynamics over Southwest China during the period 2013-2021. Our results showed a net AGC sink of 0.064 [0.057, 0.077] Pg C year−1 (the range represents the maximum and minimum AGC values), suggesting that Southwest China acted as an AGC sink over the study period. Note that the AGC loss of 0.113 [0.101, 0.136] Pg C year−1 was found during 2013-2014, which could mainly be attributed to the negative influence of extreme droughts on AGC changes in Southwest China, particularly in the Yunnan province. For each land use type (i.e., dense forests, persistent forests, nonforests, afforestation, and forestry), the largest AGC stock increase of 0.032 [0.028, 0.036] Pg C year−1 was found in nonforests, owing to their widespread land cover rate over Southwest China. For AGC density (i.e., AGC per unit area), the afforestation areas showed the largest AGC density increase of 0.808 [0.724, 0.985] Mg C ha−1 year−1, reflecting the positive effect of afforestation on AGC increase. Moreover, the karst areas exhibited a higher increasing rate of AGC density than nonkarst areas, suggesting that the karst ecosystems have a high carbon sink capacity over Southwest China.

Disturbance, vegetation productivity, and recovery are crucial for aboveground biomass carbon (AGC) dynamics. Here, we use multiple satellite-based datasets to analyze the drivers of AGC dynamics in Central Africa. During 2010–2019, deforestation induced a gross AGC loss of 102.2 ± 17.1 Tg C year−1, which was counterbalanced by an AGC increase of 116.9 ± 41.1 Tg C year−1, leading to a net gain of 14.6 ± 3.8 Tg C year−1. Compared to anthropogenic and soil factors, changes in climate-related factors (e.g., radiation) are more important for the non-deforestation AGC changes. A large AGC increase was found in the northern savannas. In moist forests, strong biomass recovery and growth largely compensated the carbon loss from deforestation and degradation. Considering the increasing resource demand due to rapid population growth, reconciling natural conservation and economic development in Central Africa remains challenging and depends on climate changes and country-specific social-economic conditions., Disturbance, vegetation productivity, and recovery are crucial for aboveground biomass carbon (AGC) dynamics. Here, we use multiple satellite-based datasets to analyze the drivers of AGC dynamics in Central Africa. During 2010–2019, deforestation induced a gross AGC loss of 102.2 ± 17.1 Tg C year−1, which was counterbalanced by an AGC increase of 116.9 ± 41.1 Tg C year−1, leading to a net gain of 14.6 ± 3.8 Tg C year−1. Compared to anthropogenic and soil factors, changes in climate-related factors (e.g., radiation) are more important for the non-deforestation AGC changes. A large AGC increase was found in the northern savannas. In moist forests, strong biomass recovery and growth largely compensated the carbon loss from deforestation and degradation. Considering the increasing resource demand due to rapid population growth, reconciling natural conservation and economic development in Central Africa remains challenging and depends on climate changes and country-specific social-economic conditions.

Vegetation dynamics in the African continent play an important role in the global terrestrial carbon cycle. Above-ground biomass carbon (AGC) stocks in Africa are sensitive to drought, fires and anthropogenic disturbances, and can be increased from forest restoration and tree plantation. However, there are large uncertainties in estimating changes that have occurred in AGC stocks in Africa over the past decades. Here, we used a microwave remote sensing-based vegetation index named Vegetation Optical Depth produced from X-band observations by INRAE Bordeaux (IB X-VOD) to describe the AGC dynamics in Africa covering recent decades. From 2003 to 2021, African AGC showed a net increase at a rate of +0.06 [+0.04, +0.07] PgC·yr−1 (the range represents the minimum and maximum AGC changes estimated by four calibrations), resulting from a large carbon gain of +0.55 [+0.46, +0.60] PgC·yr−1 during the first decade of the twenty-first century (period 1: 2003–2010) and a much weaker increase of +0.05 [+0.04, +0.07] PgC·yr−1 over the recent decade (period 2: 2013–2021). AGC gains were mainly found in non-forest woody areas, which contributed the most to the AGC changes during 2003–2021. Rainforests showed a minor AGC loss of −0.02 [−0.03, −0.02] PgC·yr−1, which emphasizes the need for forest conservation in Africa. Relationships between the AGC changes and potential forcing climate or anthropogenic variables suggested that human-induced deforestation and water stress (especially the vapor pressure deficit (VPD)) are the most important variables explaining the spatial and temporal AGC variations, respectively. For areas of rainforests, we identified a strong relationship between AGC and VPD (negative), soil moisture (positive) and radiation (positive). For areas of sparse vegetation (mainly located in drylands), AGC changes are largely dominated by changes in the soil water conditions. This study presents a new dataset for monitoring

Siberian forests are generally thought to have acted as an important carbon sink over recent decades, but exposure to severe droughts and fire disturbances may have impacted their carbon dynamics. Limited available forest inventories mean the carbon balance remains uncertain. Here we analyse annual live and dead above-ground carbon changes derived from low-frequency passive microwave observations from 2010 to 2019. We find that during this period, the carbon balance of Siberian forests was close to neutral, with the forests acting as a small carbon sink of +0.02+0.01+0.03 PgC yr−1. Carbon storage in dead wood increased, but this was largely offset by a decrease in live biomass. Substantial losses of live above-ground carbon are attributed to fire and drought, such as the widespread fires in northern Siberia in 2012 and extreme drought in eastern Siberia in 2015. These live above-ground carbon losses contrast with ‘greening’ trends seen in leaf area index over the same period, a decoupling explained by faster post-disturbance recovery of leaf area than live above-ground carbon. Our study highlights the vulnerability of large forest carbon stores in Siberia to climate-induced disturbances, challenging the persistence of the carbon sink in this region of the globe.

Southwest China has been the largest terrestrial carbon sink in China over the past 30 years, but has recently experienced a succession of droughts caused by high precipitation variability, potentially threatening vegetation productivity in the region. Yet, the impact of precipitation anomalies on the vegetation primary productivity is poorly known. We used an asymmetry index (AI) to explore possible asymmetric productivity responses to precipitation anomalies in Southwest China from 2003 to 2018, using a precipitation dataset, combined with gross primary productivity (GPP), net primary productivity (NPP), and vegetation optical depth (VOD) products. Our results indicate that the vegetation primary productivity of Southwest China shows a negative asymmetry, suggesting that the increase of vegetation primary productivity during wet years exceeds the decrease during dry years. However, this negative asymmetry of vegetation primary productivity was shifted towards a positive asymmetry during the period of analysis, suggesting that the resistance of vegetation to drought, has increased with the rise in the occurrence of drought events. Among the different biomes, grassland vegetation primary productivity had the highest sensitivity to precipitation anomalies, indicating that grasslands are more flexible than other biomes and able to adjust primary productivity in response to precipitation anomalies. Furthermore, our results showed that the asymmetry of vegetation primary productivity was influenced by the effects of temperature, precipitation, solar radiation, and anthropogenic and topographic factors. These findings improve our understanding of the response of vegetation primary productivity to climate change over Southwest China.

Vegetation optical depth (VOD) from satellite passive microwave sensors has enabled monitoring of aboveground biomass carbon dynamics by building a relationship with static carbon maps over space and then applying this relationship to VOD time series. However, uncertainty in this relationship arises from changes in water stress, as VOD is mainly determined by vegetation water content, which varies at diurnal to interannual scales, and depends on changes in both biomass and relative moisture content. Here, we studied the reliability of using VOD from various microwave frequencies and temporal aggregation methods for estimating decadal biomass carbon dynamics at the global scale. We used the VOD diurnal variations to represent the magnitude of vegetation water content buffering caused by climatic variations for a constant amount of dry biomass carbon. This magnitude of VOD diurnal variations was then used to evaluate the likelihood of VOD decadal variations in reflecting decadal dry biomass carbon changes. We found that SMOS-IC L-VOD and LPDR X-VOD can be reliably used to estimate decadal carbon dynamics for 76.7% and 69.9% of the global vegetated land surface, respectively, yet cautious use is warranted for some areas such as the eastern Amazon rainforest. Moreover, the annual VOD aggregated from the 95% percentile of the nighttime VOD retrievals was proved to be the most suitable parameter for estimating decadal biomass carbon dynamics among the temporal aggregation methods. Finally, we validated the use of annual VOD for estimating interannual carbon dynamics by comparing VOD changes between adjacent years against eddy covariance estimations of gross primary production from flux sites over several land cover classes across the globe. Despite the large difference in spatial scales between them, the positive correlation obtained supports the capability of satellite VOD in quantifying interannual carbon dynamics.

Soils are at the crossroads of many existential issues that humanity is currently facing. Soils are a finite resource that is under threat, mainly due to human pressure. There is an urgent need to map and monitor them at field, regional, and global scales in order to improve their management and prevent their degradation. This remains a challenge due to the high and often complex spatial variability inherent to soils. Over the last four decades, major research efforts in the field of pedometrics have led to the development of methods allowing to capture the complex nature of soils. As a result, digital soil mapping (DSM) approaches have been developed for quantifying soils in space and time. DSM and monitoring have become operational thanks to the harmonization of soil databases, advances in spatial modeling and machine learning, and the increasing availability of spatiotemporal covariates, including the exponential increase in freely available remote sensing (RS) data. The latter boosted research in DSM, allowing the mapping of soils at high resolution and assessing the changes through time. We present a review of the main contributions and developments of French (inter)national research, which has a long history in both RS and DSM. Thanks to the French SPOT satellite constellation that started in the early 1980s, the French RS and soil research communities have pioneered DSM using remote sensing. This review describes the data, tools, and methods using RS imagery to support the spatial predictions of a wide range of soil properties and discusses their pros and cons. The review demonstrates that RS data are frequently used in soil mapping (i) by considering them as a substitute for analytical measurements, or (ii) by considering them as covariates related to the controlling factors of soil formation and evolution. It further highlights the great potential of RS imagery to improve DSM, and provides an overview of the main challenges and prospects related to digital

Over the past 2 to 3 decades, Chinese forests are estimated to act as a large carbon sink, yet the magnitude and spatial patterns of this sink differ considerably among studies. Using 3 microwave (L- and X-band vegetation optical depth [VOD]) and 3 optical (normalized difference vegetation index, leaf area index, and tree cover) remote-sensing vegetation products, this study compared the estimated live woody aboveground biomass carbon (AGC) dynamics over China between 2013 and 2019. Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps (mean correlation value R = 0.84), followed by L-VOD (R = 0.83), which outperform the other VODs. An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019. The performance of the AGC estimation model was good (root mean square error = 0.05 Pg C and R2 = 0.90 with a mean relative uncertainty of 9.8% at pixel scale [0.25°]). Results of the AGC estimation model showed that carbon uptake by the forests in China was about +0.17 Pg C year−1 from 2013 to 2019. At the regional level, provinces in southwest China including Guizhou (+22.35 Tg C year−1), Sichuan (+14.49 Tg C year−1), and Hunan (+11.42 Tg C year−1) provinces had the highest carbon sink rates during 2013 to 2019. Most of the carbon-sink regions have been afforested recently, implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

Changes in terrestrial carbon storage under environmental and land-use changes remain a critical source of uncertainty in regional and global carbon budgets. We generated global maps of annual live vegetation biomass using L-band microwave vegetation optical depth. Globally, biomass carbon stocks increased from 2010 to 2019 at a rate of 0.50 ± 0.20 PgC yr−1 with a year-to-year variability, closely mirroring the observations of the global atmospheric CO2 growth rate. The main contributors to the global carbon sink are boreal and temperate forests, while wet tropical forests are small carbon sources, from deforestation and agriculture-related disturbances. We found that the tropical deforested and degraded old-growth forests (>140 yr) are nearly carbon neutral whereas temperate and boreal young (< 50 yr) and middle-aged (50–140 yr) forests are the largest sinks. By contrast, dynamic global vegetation models show that all old-growth forests are large sinks and largely ignore the impacts of deforestation and degradation on tropical biomass. Our findings highlight the importance of forest demography when predicting dynamics of future carbon sink under changing climate.

Tropical Asia has shown a strong greening trend in recent years. However, detailed knowledge about changes in carbon stocks remain uncertain as only few studies have used remotely sensed vegetation products for monitoring spatial and temporal changes of aboveground live biomass carbon (AGC) in that region. This study aims at evaluating optical- and microwave-based vegetation proxies (i.e., LAI, percent tree cover (PTC), L−/X-/C-band vegetation optical depths (VOD)) for understanding the spatio-temporal variations of tropical Asian AGC between 2013 and 2019. Our results indicated that the spatial distributions of L-VOD and PTC were highly spatially correlated with four benchmark AGC maps used for comparison (R > 0.79 and R > 0.75, respectively). By employing L-VOD as the reference data in assessing AGC dynamics, the X-/C-VOD showed advantages in capturing AGC changes for low-medium (20–40 Mg C/ha) carbon density vegetation, respectively, while other vegetation proxies showed limited capabilities. All proxies presented limitations in tracking AGC dynamics at high AGC density (> 60 Mg C/ha). Tropical Asian AGC stocks estimated using the L-VOD product indicated that tropical Asia accumulated carbon in biomass at a rate of +44+39+53 Tg C/yr between 2013 and 2019. This small sink is dominated by non-forest biomes (65.9%). The non-forest regions in southern India, southwest China, and southern Vietnam and southwest China showed a continuous AGC increase while forests in northern Laos, Malaysia, and central Indonesia experienced continuous decreases between 2013 and 2019 caused by deforestation.