Sub-continental-scale carbon stocks of individual trees in African drylands.

The distribution of dryland trees and their density, cover, size, mass and carbon content are not well known at sub-continental to continental scales1-14. This information is important for ecological protection, carbon accounting, climate mitigation and restoration efforts of dryland ecosystems15-18. We assessed more than 9.9 billion trees derived from more than 300,000 satellite images, covering semi-arid sub-Saharan Africa north of the Equator. We attributed wood, foliage and root carbon to every tree in the 0-1,000 mm year-1 rainfall zone by coupling field data19, machine learning20-22, satellite data and high-performance computing. Average carbon stocks of individual trees ranged from 0.54 Mg C ha-1 and 63 kg C tree-1 in the arid zone to 3.7 Mg C ha-1 and 98 kg tree-1 in the sub-humid zone. Overall, we estimated the total carbon for our study area to be 0.84 (±19.8%) Pg C. Comparisons with 14 previous TRENDY numerical simulation studies23 for our area found that the density and carbon stocks of scattered trees have been underestimated by three models and overestimated by 11 models, respectively. This benchmarking can help understand the carbon cycle and address concerns about land degradation24-29. We make available a linked database of wood mass, foliage mass, root mass and carbon stock of each tree for scientists, policymakers, dryland-restoration practitioners and farmers, who can use it to estimate farmland tree carbon stocks from tablets or laptops.

An unexpectedly large count of trees in the West African Sahara and Sahel.

A large proportion of dryland trees and shrubs (hereafter referred to collectively as trees) grow in isolation, without canopy closure. These non-forest trees have a crucial role in biodiversity, and provide ecosystem services such as carbon storage, food resources and shelter for humans and animals1,2. However, most public interest relating to trees is devoted to forests, and trees outside of forests are not well-documented3. Here we map the crown size of each tree more than 3 m2 in size over a land area that spans 1.3 million km2 in the West African Sahara, Sahel and sub-humid zone, using submetre-resolution satellite imagery and deep learning4. We detected over 1.8 billion individual trees (13.4 trees per hectare), with a median crown size of 12 m2, along a rainfall gradient from 0 to 1,000 mm per year. The canopy cover increases from 0.1% (0.7 trees per hectare) in hyper-arid areas, through 1.6% (9.9 trees per hectare) in arid and 5.6% (30.1 trees per hectare) in semi-arid zones, to 13.3% (47 trees per hectare) in sub-humid areas. Although the overall canopy cover is low, the relatively high density of isolated trees challenges prevailing narratives about dryland desertification5-7, and even the desert shows a surprisingly high tree density. Our assessment suggests a way to monitor trees outside of forests globally, and to explore their role in mitigating degradation, climate change and poverty.

Dominant role of the non-forest woody vegetation in the post 2015/16 El Niño tropical carbon recovery.

The extreme dry and hot 2015/16 El Niño episode caused large losses in tropical live aboveground carbon (AGC) stocks. Followed by climatic conditions conducive to high vegetation productivity since 2016, tropical AGC are expected to recover from large losses during the El Niño episode; however, the recovery rate and its spatial distribution remain unknown. Here, we used low-frequency microwave satellite data to track AGC changes, and showed that tropical AGC stocks returned to pre-El Niño levels by the end of 2020, resulting in an AGC sink of 0.18 0.14 0.26 $$ {0.18}_{0.14}^{0.26} $$ Pg C year-1 during 2014-2020. This sink was dominated by strong AGC increases ( 0.61 0.49 0.84 $$ {0.61}_{0.49}^{0.84} $$ Pg C year-1) in non-forest woody vegetation during 2016-2020, compensating the forest AGC losses attributed to the El Niño event, forest loss, and degradation. Our findings highlight that non-forest woody vegetation is an increasingly important contributor to interannual to decadal variability in the global carbon cycle.

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions.

Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor-pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water-related stress as compared to areas not exposed to water-related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non-stressed systems. Conversely, opposite relationships were found for soil parameters such as root-zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water-related stress (or no stress) is important, for example within management strategies to maintain and restore dryland vegetation.

Response to concerns about the African fire trends controlled by precipitation over recent decades.

Croplands expanded in Africa over recent decades, even though the increasing trends are spatially heterogeneous.

A physiology-based Earth observation model indicates stagnation in the global gross primary production during recent decades.

Earth observation-based estimates of global gross primary production (GPP) are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. In this study, we attempt an ecosystem-level physiological approach of estimating GPP using an asymptotic light response function (LRF) between GPP and incoming photosynthetically active radiation (PAR) that better represents the response observed at high spatiotemporal resolutions than the conventional light use efficiency approach. Modelled GPP is thereafter constrained with meteorological and hydrological variables. The variability in field-observed GPP, net primary productivity and solar-induced fluorescence was better or equally well captured by our LRF-based GPP when compared with six state-of-the-art Earth observation-based GPP products. Over the period 1982-2015, the LRF-based average annual global terrestrial GPP budget was 121.8 ± 3.5 Pg C, with a detrended inter-annual variability of 0.74 ± 0.13 Pg C. The strongest inter-annual variability was observed in semi-arid regions, but croplands in China and India also showed strong inter-annual variations. The trend in global terrestrial GPP during 1982-2015 was 0.27 ± 0.02 Pg C year-1 , and was generally larger in the northern than the southern hemisphere. Most positive GPP trends were seen in areas with croplands whereas negative trends were observed for large non-cropped parts of the tropics. Trends were strong during the eighties and nineties but levelled off around year 2000. Other GPP products either showed no trends or continuous increase throughout the study period. This study benchmarks a first global Earth observation-based model using an asymptotic light response function, improving simulations of GPP, and reveals a stagnation in the global GPP after the year 2000.

Nonlinear dynamics of fires in Africa over recent decades controlled by precipitation.

Dynamics of fires in Africa are of critical importance for understanding changes in ecosystem properties and effects on the global carbon cycle. Given increasing fire risk from projected warming on the one hand and a documented human-driven decline in fires on the other, it is still unknown how the complex interplay between climate and human factors affects recent changes of fires in Africa. Moreover, the impact of recent strong El Niño events on fire dynamics is not yet known. By applying an ensemble empirical mode decomposition method to satellite-derived fire burned area, we investigated the spatio-temporal evolution of fires in Africa over 2001-2016 and identified the potential dominant drivers. Our results show an overall decline of fire rates, which is continuous over the time period and mainly caused by cropland expansion in northern sub-Saharan Africa. However, we also find that years of high precipitation have caused an initial increase in fire rates in southern Africa, which reversed to a decline in later years. This decline is caused by a high frequency of dry years leading to very low fuel loads, suggesting that recent drought causes a general reduction of burned areas, in particular in xeric savannas. In some mesic regions (10°-15°S), solar radiation and increased temperature caused increase in fires. These findings show that climate change overrules the impact of human expansion on fire rates at the continental scale in Africa, reducing the fire risk.

Acceleration of global vegetation greenup from combined effects of climate change and human land management.

Global warming and human land management have greatly influenced vegetation growth through both changes in spring phenology and photosynthetic primary production. This will presumably impact the velocity of vegetation greenup (Vgreenup, the daily rate of changes in vegetation productivity during greenup period), yet little is currently known about the spatio-temporal patterns of Vgreenup of global vegetation. Here, we define Vgreenup as the ratio of the amplitude of greenup (Agreenup) to the duration of greenup (Dgreenup) and derive global Vgreenup from 34-year satellite leaf area index (LAI) observations to study spatio-temporal dynamics of Vgreenup at the global, hemispheric, and ecosystem scales. We find that 19.9% of the pixels analyzed (n = 1,175,453) experienced significant trends toward higher greenup rates by an average of 0.018 m2  m-2  day-1 for 1982-2015 as compared to 8.6% of pixels with significant negative trends (p < 0.05). Global distribution and dynamics of Vgreenup show high spatial heterogeneity and ecosystem-specific patterns, which is primarily determined by the high spatial variation in Agreenup, while the temporal dynamics of Vgreenup are directly controlled by both changes in Dgreenup and Agreenup. Areas with the largest Vgreenup and largest positive trends are both observed in deciduous and mixed forests as compared to nonforest ecosystems showing both lower Vgreenup and trends. For nonforest ecosystems, human-managed ecosystems (e.g., rangelands and rainfed croplands) exhibited higher Vgreenup and positive trends than those of natural counterparts, suggesting strong imprints of human land management on terrestrial ecosystem functioning. Globally, warming has accelerated Vgreenup in temperature-constrained high latitude forest ecosystems and arctic regions, but decelerated Vgreenup in temperate and arid/semiarid areas. These results suggest that the combined effects of climate change and human land management have greatly accelerated global vegetation greenup, with important implications for changes in terrestrial ecosystem functioning and global carbon cycling.

Mapping gains and losses in woody vegetation across global tropical drylands.

Woody vegetation in global tropical drylands is of significant importance for both the interannual variability of the carbon cycle and local livelihoods. Satellite observations over the past decades provide a unique way to assess the vegetation long-term dynamics across biomes worldwide. Yet, the actual changes in the woody vegetation are always hidden by interannual fluctuations of the leaf density, because the most widely used remote sensing data are primarily related to the photosynthetically active vegetation components. Here, we quantify the temporal trends of the nonphotosynthetic woody components (i.e., stems and branches) in global tropical drylands during 2000-2012 using the vegetation optical depth (VOD), retrieved from passive microwave observations. This is achieved by a novel method focusing on the dry season period to minimize the influence of herbaceous vegetation and using MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data to remove the interannual fluctuations of the woody leaf component. We revealed significant trends (P < 0.05) in the woody component (VODwood ) in 35% of the areas characterized by a nonsignificant trend in the leaf component (VODleaf modeled from NDVI), indicating pronounced gradual growth/decline in woody vegetation not captured by traditional assessments. The method is validated using a unique record of ground measurements from the semiarid Sahel and shows a strong agreement between changes in VODwood and changes in ground observed woody cover (r2  = 0.78). Reliability of the obtained woody component trends is also supported by a review of relevant literatures for eight hot spot regions of change. The proposed approach is expected to contribute to an improved assessment of, for example, changes in dryland carbon pools.

Revealing turning points in ecosystem functioning over the Northern Eurasian agricultural frontier.

The collapse of the Soviet Union in 1991 has been a turning point in the World history that left a unique footprint on the Northern Eurasian ecosystems. Conducting large scale mapping of environmental change and separating between naturogenic and anthropogenic drivers is a difficult endeavor in such highly complex systems. In this research a piece-wise linear regression method was used for breakpoint detection in Rain-Use Efficiency (RUE) time series and a classification of ecosystem response types was produced. Supported by earth observation data, field data, and expert knowledge, this study provides empirical evidence regarding the occurrence of drastic changes in RUE (assessment of the timing, the direction and the significance of these changes) in Northern Eurasian ecosystems between 1982 and 2011. About 36% of the study area (3.4 million km(2) ) showed significant (P < 0.05) trends and/or turning points in RUE during the observation period. A large proportion of detected turning points in RUE occurred around the fall of the Soviet Union in 1991 and in the following years which were attributed to widespread agricultural land abandonment. Our study also showed that recurrent droughts deeply affected vegetation productivity throughout the observation period, with a general worsening of the drought conditions in recent years. Moreover, recent human-induced turning points in ecosystem functioning were detected and attributed to ongoing recultivation and change in irrigation practices in the Volgograd region, and to increased salinization and increased grazing intensity around Lake Balkhash. The ecosystem-state assessment method introduced here proved to be a valuable support that highlighted hotspots of potentially altered ecosystems and allowed for disentangling human from climatic disturbances.

Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models.

Vietnam's forest transition in retrospect: demonstrating weaknesses in business-as-usual scenarios for REDD.

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity.

Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio-temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time-series of Normalized Difference Vegetation Index (NDVI). Drought spatio-temporal variability was analyzed using a Principal Component Analysis, leading to the identification of four major drought events between 1999 and 2010 in Europe. Correspondence Analysis showed that at the continental scale the productivity and phenology reacted differently to the identified drought events depending on ecosystem and land cover. Northern and Mediterranean ecosystems proved to be more resilient to droughts in terms of vegetation phenology and productivity developments. Western Atlantic regions and Eastern Europe showed strong agglomerations of decreased productivity and shorter vegetation growing season length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.

Facing the challenge of NDVI dataset consistency for improved characterization of vegetation response to climate variability.

Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019. By applying the Break For Additive Season and Trend (BFAST01) method, we conducted a classification typology based on vegetation dynamics which was spatially consistent between the datasets for 40.86 % (459,669 km2) of the study area. When considering also the timing of the TPs, 27.09 % of the pixels showed consistent results between datasets, suggesting that careful interpretation was needed for most of the areas of detected vegetation dynamics when applying BFAST to a single dataset. Notably, for these areas showing identical typology we found that interrupted decreases in vegetation productivity were dominant in the transition zone between desert and steppes. Here, a strong link with changes in water availability was found for >80 % of the area, indicating that increasing drought stress had regulated vegetation productivity in recent years. This study shows the necessity of a cautious interpretation of the results when conducting advanced characterization of vegetation response to climate variability, but at the same time also the opportunities of going beyond the use of single dataset in advanced time-series approaches to better understanding dryland vegetation dynamics for improved anthropogenic interventions to combat vegetation productivity decrease.

Critical thresholds for nonlinear responses of ecosystem water use efficiency to drought.

Climate change is expected to lead to greater variability in precipitation and drought in different regions. However, the responses of ecosystem carbon and water cycles (i.e., water use efficiency, WUE) to different levels of drought stress are not fully understood. Here, we examined the relationship between WUE and precipitation anomalies and identified the critical drought threshold (DrCW) above which WUE showed substantial decrease. The results revealed that 85.56 % of the study area had nonlinear WUE responses to drought stress; that is, the WUE decreased sustainably and steeply when the precipitation deficit exceeded the DrCW. DrCW indicates inflection points for changing ecosystem responses from relatively resistant to vulnerable to drought stress, thus providing an instructive early warning for intensifying suppressive impacts on vegetation growth. Additionally, DrCW varies across aridity gradients and among vegetation types. Based on the DrCW at the pixel level, the future eco-drought is projected to increase in >67 % of the study area under both the SSP2&RCP4.5 and SSP5&RCP8.5 scenarios by the end of the 21st century. Our study elucidates the response of the ecosystem function to drought and supports the development of accurate ecosystem adaptation policies for future drought stress.

The success of ecological engineering projects on vegetation restoration in China strongly depends on climatic conditions.

China has implemented extensive ecological engineering projects (EEPs) during recent decades to restore and enhance ecosystem functioning. However, the effectiveness of these interventions can vary due to factors such as local climate and specific project objectives. Here, we used two independent satellite remote sensing datasets, including the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) and vegetation optical depth from Ku-band (Ku-VOD), to investigate the vegetation trends in two hotspot regions of EEPs characterized by different climate conditions, i.e., the xeric/semi-xeric Loess Plateau and mesic southwest China. We found diverging vegetation greenness/biomass trend shift patterns in these two regions as a result of the combined effects of EEPs and climate variations, as indicated by changes in the Standardized Precipitation Evapotranspiration Index (SPEI). In the Loess Plateau, where no significant climate variations were observed, NDVI/Ku-VOD increased continuously after the implementation of key EEPs in 2000. Conversely, southwest China has experienced persistent drying since 2000, and vegetation greenness/biomass showed an increasing trend during the initial stages of ecological engineering implementation but subsequently reversed towards a decline due to the continued dry climatic conditions. We used the residual trend method to separate the influence of EEPs from climate variations on vegetation trends and found a positive effect of the ecological management practices in the Loess Plateau, yet a predominantly negative effect in the southwest China region, which means that projects implemented in southwest China did not lead to a long-term improvement in vegetation growth under the given climate conditions in southwest China. This adverse impact suggests that ecological engineering practices could potentially increase the ecosystem's vulnerability to droughts, owing to the increased transpirational water demands introduced by ecological engineering interventions. Our study highlights the importance of considering the expected occurrence and magnitude of climatic variability when implementing large-scale EEPs.

Changes in vegetation-water response in the Sahel-Sudan during recent decades.

Study region: The Africa Sahel-Sudan region, defined by annual rainfall between 150 and 1200 mm. Study focus: Understanding the mechanism of vegetation response to water availability could help mitigate the potential adverse effects of climate change on global dryland ecosystems. In the Sahel-Sudan region, spatio-temporal changes and drivers of the vegetation-water response remain unclear. This study employs long-term satellite water and vegetation products as proxies of water availability and vegetation productivity to analyze changes in vegetation-water sensitivity and the cumulative effect duration (CED) representing a measure of the legacy effect of the impact of water constraints on vegetation. A random forest model was subsequently used to analyze potential climatic drivers of the observed vegetation response. New hydrological insights for the region: During 1982-2016 we found a significant decrease (p < 0.05) in the sensitivity of vegetation productivity to water constraints in 26% of the Sahel-Sudan region, while 9% of the area showed a significantly increased sensitivity, mainly in the sub-humid zone. We further showed that CED significantly increased and decreased, respectively in around 9% of the study area in both cases. Our climatic driver attribution analysis suggested the existence of varying underlying mechanisms governing vegetation productivity in response to water deficit across the Sahel-Sudan dryland ecosystems. Our findings emphasize the need for diverse strategies in sustainable ecosystem management to effectively address these varying mechanisms.

Global area boom for greenhouse cultivation revealed by satellite mapping.

Greenhouse cultivation has been expanding rapidly in recent years, yet little knowledge exists on its global extent and expansion. Using commercial and freely available satellite data combined with artificial intelligence techniques, we present a global assessment of greenhouse cultivation coverage and map 1.3 million hectares of greenhouse infrastructures in 2019, a much larger extent than previously estimated. Our analysis includes both large (61%) and small-scale (39%) greenhouse infrastructures. Examining the temporal development of the 65 largest clusters (>1,500 ha), we show a recent upsurge in greenhouse cultivation in the Global South since the 2000s, including a dramatic increase in China, accounting for 60% of the global coverage. We emphasize the potential of greenhouse infrastructures to enhance food security but raise awareness of the uncertain environmental and social implications that may arise from this expansion. We further highlight the gap in spatio-temporal datasets for supporting future research agendas on this critical topic.

Mapping every adult baobab (Adansonia digitata L.) across the Sahel and relationships to rural livelihoods.

The baobab tree (Adansonia digitata L.) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources. Here we use sub-metre-resolution satellite imagery to identify the presence of nearly 2.8 million (underestimation bias 27.1%) baobab trees in the Sahel, a dryland region of 2.4 million km2. This achievement is considered an essential step towards an improved management and monitoring system of valuable woody species. Using Senegal as a case country, we find that 94% of rural buildings have at least one baobab tree in their immediate surroundings and that the abundance of baobabs is associated with a higher likelihood of people consuming a highly nutritious food group: dark green leafy vegetables. The generated database showcases the feasibility of mapping the location of single tree species at a sub-continental scale, providing vital information in times when deforestation and climate change cause the extinction of numerous tree species.