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Projection of future woody cover is essential to understand potential changes in structure and functioning of terrestrial ecosystems. Previous studies mapped woody cover during historical periods observed by satellites, however, it remains unclear how woody cover is expected to change in response to future climate change. Here, we develop data‐driven models to predict woody cover in Africa using multiple environmental predictors and show that woody cover can be accurately modeled using Random Forest. Empirically‐based simulations forced by precipitation from CMIP6 project an overall increase in woody cover at the continental scale by 2100. However, increases are mainly occurring in regions with annual precipitation less than ∼1,600 mm y−1, whereas woody cover is predicted to decrease in areas of higher rainfall. Our results suggest that climate change may alter the functioning of dryland ecosystems by continued woody encroachment and cause a loss of carbon stocks in humid areas. Plain Language Summary: Future climate changes pose a severe threat on the structure and functioning of terrestrial ecosystems and thereby threaten human well‐beings. Forests play a critical role in mitigating climate changes by absorbing atmospheric CO2, but undergo large losses during last three decades due to a range of disturbance, such as wildfires and extreme climate events. In particular, forest and non‐forest trees are largely impacted by changing precipitation regimes in Africa, but the knowledge on this is limited to current periods observed by satellites. Here, we establish a data‐driven model by linking woody cover to environmental variables, the developed model was further forced by future precipitation from the Sixth Coupled Model Intercomparison Project. We predict an increase in woody cover in drylands by the year 2100, while a decrease in humid areas across African continent. This study thus provides a feasible data‐driven approach for the prediction of woody cover without the temporal limitation of satellites and allows for a better understanding of changes in ecosystem structure, composition and functioning in the context of future climate change. Key Points: Woody cover can be accurately predicted with environmental variablesMean annual precipitation explains the most spatial variability in woody cover in AfricaPredicted precipitation changes will increase woody cover in drylands but decrease woody cover in humid areas by 2100 [ABSTRACT FROM AUTHOR]

Vapor pressure deficit (VPD) is of great importance to control the land‐atmosphere exchange of water and CO2. Here we use in situ observations to assess the performance of monthly VPD calculated from state‐of‐the‐art data sets including CRU, ERA5, and Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA2). We investigate trends in VPD at global scale and for different climatic zones for 1981–2020 and future trends (2021–2100) from Coupled Model Inter‐comparison Project phase 6 (CMIP6) outputs. The results show that monthly VPD estimated from CRU, ERA5, and MERRA2 correlated well against in situ estimates from 15,531 World Meteorological Organization stations, with R2 ranging between 0.92 and 0.96. Moreover, robust correlations were also found across in situ stations and when analyzing different months separately. During 1981–2020, VPD increased in all climatic zones, with the strongest increase in the arid zone, followed by tropical, temperate, cold and polar zones. CMIP6 simulations show a continuously increasing trend in VPD (0.028 hPa year−1), with the largest increase in the arid zone (0.063 hPa year−1). The magnitudes of trends are found to increase following the magnitude of CO2 increases in the future emission scenarios. We highlight that atmospheric aridification will continue under global warming, which may pose an increasing threat to terrestrial ecosystems and particularly dryland agricultural systems. Plain Language Summary: This study uses in situ observations to assess the performance of vapor pressure deficit (VPD) derived from CRU, ERA5‐land and Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), and investigates trends in ensemble mean VPD at global scale and for different climatic zones for 1981–2020 and future trends (2021–2100) from Coupled Model Inter‐comparison Project phase 6 (CMIP6) outputs. We found that VPD estimated from CRU, ERA5 and MERRA2 correlated well (R2 = 0.915–0.954) against in situ estimates. An increase in VPD was found in all climatic zones for 1981–2020. CMIP6 simulations showed a continuous increase in VPD (3.61 hPa), with the largest increase in the arid zone (6.44 hPa). The increased VPD suggests the potential impacts of atmospheric aridity on terrestrial ecosystems and particularly on the agricultural water supply‐demand and ultimately food security. Key Points: We find high performance of vapor pressure deficit (VPD) estimates from CRU, ERA5, and Modern‐Era Retrospective analysis for Research and Applications, Version 2 data sets when evaluated against in situ observationsWidespread increasing trend in VPD is found globally during 1981–2020, using the ensemble mean VPDIntensified increase in VPD is projected using the outputs from Coupled Model Inter‐comparison Project phase 6, potentially threatening future dryland vegetation ecosystems [ABSTRACT FROM AUTHOR]

It has been widely asserted that a high grazing pressure has led to a reduction in vegetation production at decadal time scales, implying land degradation, in African drylands, and in the Sahel in particular. We test this hypothesis by analyzing spatiotemporal patterns of vegetation production in the northwestern Ferlo in Senegal. Normalized difference vegetation index (NDVI) patterns, here used to represent vegetation production, were determined on the basis of Earth observation MODIS and PROBA‐V data. Furthermore, woody cover was assessed by very high spatial resolution (VHR) imagery. Because livestock is concentrated around deep wells in the dry season for watering, while for management they concentrate daily around pastoral family settlements or camps all year round, we studied the dependence of NDVI on distance from deep wells and camps. Locations of wells and camps were determined by visual inspection of VHR images. We found that 'inverse grazing gradients,' defined as decreasing NDVI/production with increasing distance, dominated both around wells and camps. Further, we found neither decrease nor increase in woody cover with distance to wells. Both positive and negative trends in wet season NDVI over the period 2000–2016 were identified within the study area, yet temporal trends were predominantly positive in proximity to deep wells. Around pastoral camps, positive NDVI trends were generally elevated relative to the regional average. The results question the validity of claims that high grazing pressure causes land degradation at the landscape scale, yet they show that grazing does lead to substantial spatial redistribution of vegetation production. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The impact of human activities via land use/cover changes on NDVI trends is critical for an improved understanding of satellite-observed changes in vegetation productivity in drylands. The dominance of positive NDVI trends in the Sahel, the so-called re-greening, is sometimes interpreted as a combined effect of an increase in rainfall and cropland expansion or agricultural intensification. Yet, the impact of changes in land use has yet to be thoroughly tested and supported by empirical evidence. At present, no studies have considered the importance of the different seasonal NDVI signals of cropped and fallowed fields when interpreting NDVI trends, as both field types are commonly merged into a single ‘cropland’ class. We make use of the distinctly different phenology of cropped and fallowed fields and use seasonal NDVI curves to separate these two field types. A fuzzy classifier is applied to quantify cropped and fallowed areas in a case study region in the southern Sahel (Fakara, Niger) on a yearly basis between 2000 and 2014. We find that fallowed fields have a consistently higher NDVI than unmanured cropped fields and by using two seasonal NDVI metrics (the amplitude and the decreasing rate) derived from the MODIS time series, a clear separation between classes of fields is achieved ( r = 0.77). The fuzzy classifier can compute the percentage of a pixel (250 m) under active cultivation, thereby alleviating the problem of small field sizes in the region. We find a predominant decrease in NDVI over the period of analysis associated with an increased area of cropped fields at the expense of fallowed fields. Our findings couple cropping abandonment (more frequent fallow years) with positive NDVI trends and an increase in the percentage of the cropped area (fallow period shortening) with negative trends. These findings profoundly impact our understanding of greening and browning trends in agrarian Sahelian drylands and in other drylands of developing countries characterized by limited use of fertilizers. [ABSTRACT FROM AUTHOR]

Woody plants play a major role for the resilience of drylands and in peoples' livelihoods. However, due to their scattered distribution, quantifying and monitoring woody cover over space and time is challenging. We develop a phenology driven model and train/validate MODIS (MCD43A4, 500 m) derived metrics with 178 ground observations from Niger, Senegal and Mali to estimate woody cover trends from 2000 to 2014 over the entire Sahel. The annual woody cover estimation at 500 m scale is fairly accurate with an RMSE of 4.3 (woody cover %) and r 2 = 0.74. Over the 15 year period we observed an average increase of 1.7 (± 5.0) woody cover (%) with large spatial differences: No clear change can be observed in densely populated areas (0.2 ± 4.2), whereas a positive change is seen in sparsely populated areas (2.1 ± 5.2). Woody cover is generally stable in cropland areas (0.9 ± 4.6), reflecting the protective management of parkland trees by the farmers. Positive changes are observed in savannas (2.5 ± 5.4) and woodland areas (3.9 ± 7.3). The major pattern of woody cover change reveals strong increases in the sparsely populated Sahel zones of eastern Senegal, western Mali and central Chad, but a decreasing trend is observed in the densely populated western parts of Senegal, northern Nigeria, Sudan and southwestern Niger. This decrease is often local and limited to woodlands, being an indication of ongoing expansion of cultivated areas and selective logging. We show that an overall positive trend is found in areas of low anthropogenic pressure demonstrating the potential of these ecosystems to provide services such as carbon storage, if not over-utilized. Taken together, our results provide an unprecedented synthesis of woody cover dynamics in the Sahel, and point to land use and human population density as important drivers, however only partially and locally offsetting a general post-drought increase. [ABSTRACT FROM AUTHOR]

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years. This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483 kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity. In addition, the date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall however, was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year. [ABSTRACT FROM AUTHOR]

Remote sensing-based woody biomass quantification in sparsely-vegetated areas is often limited when using only common broadband vegetation indices as input data for correlation with ground-based measured biomass information. Red edge indices and texture attributes are often suggested as a means to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data. Model performance was evaluated based on cross-validation bias, standard deviation and Root Mean Square Error (RMSE) at the logarithmic and non-logarithmic scales. Both models achieved rather limited performances in wood volume prediction. Nonetheless, model performance increased with red edge indices and texture attributes, which shows that they play an important role in semi-arid regions with sparse vegetation. [ABSTRACT FROM AUTHOR]

From in situ measured woody cover we develop a phenology driven model to estimate the canopy cover of woody species in the Sahelian drylands at 1 km scale. The model estimates the total canopy cover of all woody phanerophytes and the concept is based on the significant difference in phenophases of dryland trees, shrubs and bushes as compared to that of the herbaceous plants. Whereas annual herbaceous plants are only green during the rainy season and senescence occurs shortly after flowering towards the last rains, most woody plants remain photosynthetically active over large parts of the year. We use Moderate Resolution Imaging Spectroradiometer (MODIS) and Satellite pour l'Observation de la Terre (SPOT) — VEGETATION (VGT) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series and test 10 metrics representing the annual FAPAR dynamics for their ability to reproduce in situ woody cover at 43 sites (163 observations between 1993 and 2013) in the Sahel. Both multi-year field data and satellite metrics are averaged to produce a steady map. Multiple regression models using the integral of FAPAR from the onset of the dry season to the onset of the rainy season, the start date of the growing season and the rate of decrease of the FAPAR curve achieve a cross validated r 2 /RMSE (in % woody cover) of 0.73/3.0 (MODIS) and 0.70/3.2 (VGT). The extrapolation to Sahel scale shows agreement between VGT and MODIS at an almost nine times higher woody cover than in the global tree cover product MOD44B which only captures trees of a certain minimum size. The derived woody cover map of the Sahel is made publicly available and represents an improvement of existing products and a contribution for future studies of drylands quantifying carbon stocks, climate change assessment, as well as parametrization of vegetation dynamic models. [ABSTRACT FROM AUTHOR]

Remote sensing-derived cropland products have depicted the location and extent of agricultural lands with an ever increasing accuracy. However, limited attention has been devoted to distinguishing between actively cropped fields and fallowed fields within agricultural lands, and in particular so in grass fallow systems of semi-arid areas. In the Sahel, one of the largest dryland regions worldwide, crop-fallow rotation practices are widely used for soil fertility regeneration. Yet, little is known about the extent of fallow fields since fallow is not explicitly differentiated within the cropland class in any existing remote sensing-based land use/cover maps, regardless of the spatial scale. With a 10 m spatial resolution and a 5-day revisit frequency, Sentinel-2 satellite imagery made it possible to disentangle agricultural land into cropped and fallow fields, facilitated by Google Earth Engine (GEE) for big data handling. Here we produce the first Sahelian fallow field map at a 10 m resolution for the baseline year 2017, accomplished by designing a remote sensing driven protocol for generating reference data for mapping over large areas. Based on the 2015 Copernicus Dynamic Land Cover map at 100 m resolution, the extent of fallow fields in the cropland class is estimated to be 63% (403,617 km2) for the Sahel in 2017. Similar results are obtained for five contemporary cropland products, with fallow fields occupying 57–62% of the cropland area. Yet, it is noted that the total estimated area coverage depends on the quality of the different cropland products. The share of cropped fields within the Copernicus cropland area is found to be higher in the arid regions (200–300 mm rainfall) as compared to the semi-arid regions (300–600 mm rainfall). The woody cover fraction within cropped and fallow fields is found to have a reversed pattern between arid (higher woody cover in cropped fields) and semi-arid (higher woody cover in fallow fields) regions. The method developed, using cloud-based Earth Observation (EO) data and computation on the GEE platform, is expected to be reproducible for mapping the extent of fallow fields across global croplands. Future applications based on multi-year time series is expected to improve our understanding of crop-fallow rotation dynamics in grass fallow systems being key in teasing apart how cropland intensification and expansion affect environmental variables, such as soil fertility, crop yields and local livelihoods in low-income regions such as the Sahel. The mapping result can be visualized via a web viewer (https://buwuyou.users.earthengine.app/view/fallowinsahel). • Mapping of the land use class "fallow field" was developed. • An RS-based approach for creating large-scale reference data was designed. • A Sahel-scale crop/fallow field map was produced at a 10 m resolution for 2017. • Fallow fields, remarkably occupy 60 ± 3% of Sahelian cropland areas. • Shares of crop/fallow fields were analyzed using rainfall and woody cover. [ABSTRACT FROM AUTHOR]