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The article discusses the importance of accurately quantifying wood resources, especially trees outside closed canopy forests, at both national and local levels for sustainable forest management, carbon stock estimates, and various ecological and economic considerations. It highlights that many countries tend to focus their forest inventories on closed canopy forests leading to potential biases in national inventories and climate models.

'Black etching' has been proposed previously as a method for the nanoscale texturing of silicon surfaces, which results in an almost complete suppression of reflectivity in the spectral range of absorption relevant for photovoltaics. The method modifies the topmost 150 to 300 nm of the material and thus also is applicable for thin films of silicon. The present work is focused on the optical effects induced by the black-etching treatment on hydrogenated amorphous and microcrystalline silicon thin films, in particular with respect to their application in solar cells. In addition to a strong reduction of the reflectivity, efficient light trapping within the modified thin films is found. The enhancement of the optical absorption due to the light trapping is investigated via photometric measurements and photothermal deflection spectroscopy. The correlation of the texture morphology (characterized via atomic force microscopy) with the optical effects is discussed in terms of an effective medium with gradually varying optical density and in the framework of the theory of statistical light trapping. Photoconductivity spectra directly show that the light trapping causes a significant prolongation of the light path within the black silicon films by up to 15 μm for ∼1 μm thick films, leading to a significant increase of the absorption in the red. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Funding provided by the World Bank for research into carbon sequestration and building on more than a decade of work. Topics include identifying possible onshore and offshore repositories within South Africa conforming to the prerequisites for carbon capture and storage; and extensive nature of such geological substrates and the mineral trapping properties.

Kinnell and Dennis (2012) showed that the list length effect in recognition memory is only observed for homogeneous stimulus material. On the basis of the global matching model MINERVA 2 (Hintzman, 1986, 1988), we offer a theoretical explanation for this finding. According to our analysis, homogeneous material immunizes against the disruptive influence of preexperimental items, which might mask the intralist interference predicted by global matching models for familiar heterogeneous material. We tested our approach in three experiments. In Experiment 1, we found list length effects for homogeneous photographs of flowers and landscapes. In Experiment 2 and 3, we presented heterogeneous photographs of scenes (Experiment 2) and faces (Experiment 3). List length effects were only found if these photographs were homogenized by the use of image-processing filters. We further show that our explanation is also in line with the results of Dennis and Chapman (2010) who found an inverse list length effect. Overall, our results provide evidence for a global matching account of familiarity. [ABSTRACT FROM AUTHOR]

Introduces the Constant Degradation Method (CDM) as an experimental scheme to study the kinetics of metastable defect creation in amorphous hydrogenated silicon. Information on amorphous hydrogenated silicon; Kinetic theories for defect creation; Increase in light intensity needed to keep the photoconductivity constant during the CDM experiment.

Presents a study which described results for deuterium effusion from undoped and doped crystalline silicon treated in a D[sub2] plasma under different conditions. Measurement of effusion spectra; Characteristics of the form of effusion spectrum for the dopant concentration; Description of the effusion spectra of silicon.

As offshore fish farms are established farther away from the shore, increased exposure to the elements prevents regular operations from being performed safely with vessels moored alongside the flexible fish cage and personnel performing tasks standing on the collar. Due to the higher environmental impact at more exposed locations, new concepts and solutions for automating daily aquaculture operations need to be developed. One solution that has been proposed is to carry out operations using a robotic arm mounted on the main deck of a service vessel while it does stationkeeping next to the cage. The purpose of this article is to summarise our research on the viability of this concept. Vessel motions are simulated for a representative vessel model and realistic sea states, and a robotic arm does motion-compensated trajectory tracking while mounted on a hexapod platform moving according to the simulated vessel motions. Relevant challenges in marine aquaculture operations are summarised, the method used to obtain realistic simulated vessel motions is documented, the results of the experiments are presented, and the remaining open questions to evaluate the potential of the proposed system are discussed. • Simulated station-keeping performance of a vessel at an exposed aquaculture site. • Modelled autonomous fish cage operations with vessel-mounted robotic arm. • Performed motion-compensated tracking with robotic arm mounted on hexapod platform. [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]

The greening in the Senegalese Sahel has been linked to an increase in net primary productivity, with significant long-term trends being closely related to the woody strata. This study investigates woody plant growth and mortality within greening areas in the pastoral areas of Senegal, and how these dynamics are linked to species diversity, climate, soil and human management. We analyse woody cover dynamics by means of multi-temporal and multi-scale Earth Observation, satellite based rainfall and in situ data sets covering the period 1994 to 2015. We find that favourable conditions (forest reserves, low human population density, sufficient rainfall) led to a rapid growth of Combretaceae and Balanites aegyptiaca between 2000 and 2013 with an average increase of 4% woody cover. However, the increasing dominance and low drought resistance of drought prone species bears the risk of substantial woody cover losses following drought years. This was observed in 2014-2015, with a die off of Guiera senegalensis in most places of the study area. We show that woody cover and woody cover trends are closely related to mean annual rainfall, but no clear relationship with rainfall trends was found over the entire study period. The observed spatial and temporal variation contrasts with the simplified labels of "greening" or "degradation". While in principal a low woody plant diversity negatively impacts regional resilience, the Sahelian system is showing signs of resilience at decadal time scales through widespread increases in woody cover and high regeneration rates after periodic droughts. We have reaffirmed that the woody cover in Sahel responds to its inherent climatic variability and does not follow a linear trend. [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]

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992–2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r 2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r 2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas. [ABSTRACT FROM AUTHOR]

Quality factor Q, which describes the attenuation of seismic waves with distance, was determined for South Africa using data recorded by the South African National Seismograph Network. Because of an objective paucity of seismicity in South Africa and modernisation of the seismograph network only in 2007, I carried out a coda wave decay analysis on only 13 tectonic earthquakes and 7 mine-related events for the magnitude range 3.6 ≤ M ≤ 4.4. Up to five seismograph stations were utilised to determine Q for frequencies at 2, 4, 8 and 16 Hz resulting in 84 individual measurements. The constants Q and α were determined for the attenuation relation Q( f) = Q f. The result was Q = 396 ± 29 and α = 0.72 ± 0.04 for a lapse time of 1.9*( t − t) (time from origin time t to the start of coda analysis window is 1.9 times the S-travel time, t) and a coda window length of 80 s. This lapse time and coda window length were found to fit the most individual frequencies for a signal-to-noise ratio of at least 3 and a minimum absolute correlation coefficient for the envelope of 0.5. For a positive correlation coefficient, the envelope amplitude increases with time and Q was not calculated. The derived Q was verified using the spectral ratio method on a smaller data set consisting of nine earthquakes and one mine-related event recorded by up to four seismograph stations. Since the spectral ratio method requires absolute amplitudes in its calculations, site response tests were performed to select four appropriate stations without soil amplification and/or signal distortion. The result obtained for Q was Q = 391 ± 130 and α = 0.60 ± 0.16, which agrees well with the coda Q result. [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]

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]

Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables--large seasonal integral (LINTG), length of growing season, and end of season decreasing rate--performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999-2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77), indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51) and should improve the operational monitoring of forage resources in Sahelian rangelands. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The assessment of land degradation and the quantification of its effects on land productivity have been both a scientific and political challenge. After four decades of Earth Observation (EO) applications, little agreement has been gained on the magnitude and direction of land degradation in the Sahel. The large number of EO datasets and methods associated with the complex interactions among biophysical and social drivers of ecosystem changes make it difficult to apply aggregated EO indices for these non-linear processes. Hence, while many studies stress that the Sahel is greening, others indicate no trend or browning. The different generations of sensors, the granularity of studies, the study period, the applied indices and the assumptions and/or computational methods impact these trends. Consequently, many uncertainties exist in regression models between rainfall, biomass and various indices that limit the ability of EO science to adequately assess and develop a consistent message on the magnitude of land degradation. We suggest several improvements: (1) harmonize time-series data, (2) promote knowledge networks, (3) improve data-access, (4) fill data gaps, (5) agree on scales and assumptions, (6) set up a denser network of long-term field-surveys and (7) consider local perceptions and social dynamics. To allow multiple perspectives and avoid erroneous interpretations, we underline that EO results should not be interpreted without contextual knowledge. [ABSTRACT FROM AUTHOR]

In the past 50 years, the Sahel has experienced significant tree- and land cover changes accelerated by human expansion and prolonged droughts during the 1970s and 1980s. This study uses remote sensing techniques, supplemented by ground-truth data to compare pre-drought woody vegetation and land cover with the situation in 2011. High resolution panchromatic Corona imagery of 1967 and multi-spectral RapidEye imagery of 2011 form the basis of this regional scaled study, which is focused on the Dogon Plateau and the Seno Plain in the Sahel zone of Mali. Object-based feature extraction and classifications are used to analyze the datasets and map land cover and woody vegetation changes over 44 years. Interviews add information about changes in species compositions. Results show a significant increase of cultivated land, a reduction of dense natural vegetation as well as an increase of trees on farmer's fields. Mean woody cover decreased in the plains (−4%) but is stable on the plateau (+1%) although stark spatial discrepancies exist. Species decline and encroachment of degraded land are observed. However, the direction of change is not always negative and a variety of spatial variations are shown. Although the impact of climate is obvious, we demonstrate that anthropogenic activities have been the main drivers of change. [ABSTRACT FROM AUTHOR]

Abstract: Climatic changes and human activities have caused major environmental change in the Sahel. Remote sensing studies detect various vegetation trends; however, explanations are rarely studied in detail. We present a methodology using time series, high-resolution imagery and fieldwork to validate trend analyses for two regions in the Sahel of Mali and Senegal. Both study areas show significant greening trends from 1982 to 2010. Reasons can be very site-specific, but several factors are valid for both research areas: (1) farmer-managed agro-forestry, (2) planting programs and protection laws, (3) widespread dispersion of robust species, which replace the former diverse woody vegetation and simulate a greening which conceals a shift in biodiversity and (4) an increase of annual rainfall. However, the situation is still far from the pre-drought conditions, which are reconstructed by Corona imagery (1965) and interviews with the local population. Rather a transformation is observed: a decrease in natural vegetation, tree density and diversity. Reasons are climatic and anthropogenic: (1) drought events, less rain and higher temperatures, (2) increased demand for cropping areas and wood, especially in times of droughts. Our example validates that climatic factors are important drivers of change, but much of today's environment and vegetation composition is controlled by humans. [Copyright &y& Elsevier]

Local vegetation trends in the Sahel of Mali and Senegal from Geoland Version 1 (GEOV1) (5 km) and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g) (8 km) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series are studied over 29 years. For validation and interpretation of observed greenness trends, two methods are applied: (1) a qualitative approach using in-depth knowledge of the study areas and (2) a quantitative approach by time series of biomass observations and rainfall data. Significant greening trends from 1982 to 2010 are consistently observed in both GEOV1 and GIMMS3g FAPAR datasets. Annual rainfall increased significantly during the observed time period, explaining large parts of FAPAR variations at a regional scale. Locally, GEOV1 data reveals a heterogeneous pattern of vegetation change, which is confirmed by long-term ground data and site visits. The spatial variability in the observed vegetation trends in the Sahel area are mainly caused by varying tree- and land-cover, which are controlled by human impact, soil and drought resilience. A large proportion of the positive trends are caused by the increment in leaf biomass of woody species that has almost doubled since the 1980s due to a tree cover regeneration after a dry-period. This confirms the re-greening of the Sahel, however, degradation is also present and sometimes obscured by greening. GEOV1 as compared to GIMMS3g made it possible to better characterize the spatial pattern of trends and identify the degraded areas in the study region. [ABSTRACT FROM AUTHOR]

Multi-purpose Faidherbia albida trees represent a vital component of agroforestry parklands in West Africa as they provide resources (fodder for livestock, fruits and firewood) and support water lifting and nutrient recycling for cropping. Faidherbia albida trees are characterized by their inverse phenology, growing leaf flowers and pods during the dry season, thereby providing fodder and shedding leaves during the wet season, which minimizes competition with pastures and crops for resources. Multi-spectral and multi-temporal satellite systems and novel computational methods open new doors for classifying single trees and identifying species. This study used a Multi-Layer Perception feedforward artificial neural network to classify pixels covered by Faidherbia albida canopies from Sentinel-2 time series in Senegal, West Africa. To better discriminate the Faidherbia albida signal from the background, monthly images from vegetation indices were used to form relevant variables for the model. We found that NDI54/NDVI from the period covering onset of leaf senescence (February) until end of senescence (leaf-off in June) to be the most important, resulting in a high precision and recall rate of 0.91 and 0.85. We compared our result with a potential Faidherbia albida occurrence map derived by empirical modelling of the species ecology, which deviates notably from the actual species occurrence mapped by this study. We have shown that even small differences in dry season leaf phenology can be used to distinguish tree species. The Faidherbia albida distribution maps, as provided here, will be key in managing farmlands in drylands, helping to optimize economic and ecological services from both tree and crop products. [ABSTRACT FROM AUTHOR]

The paper deals with the influence of core magnetization on its frequency response analysis. Remanent magnetization is a characteristic property of ferromagnetic materials. The core cans acquire different value of remanent magnetization in the process of diagnostic measurements. This fact is very important from the point of view of good representation of results from measurements. In the past, we made a couple of measurements on 3-phase dry transformer (3000VA). Nowadays, we had the possibility to measured 25MVA distribution transformer by SFRA method. This transformer has been connected in the network before the measurement and we have also results of measurements they were done one year before. That time the transformer was out of the operation for 9 months, so we have an anticipation to see some differences. [ABSTRACT FROM AUTHOR]

A new method for the approximation of multivariate scalar probability density functions (PDFs) in turbulent reacting flow by means of a joint presumed discrete distribution (jPDD) is presented. The jPDDs can be generated with specified mean values and variances as well as covariances. Correlations between variables – e.g. fluctuating mixture fractions and/or reaction progress – can thereby be taken into account. In this way the new approach overcomes an important limitation of ordinary presumed PDF methods, where statistical independence between the variables is often assumed. Different methods are presented to generate discrete distributions, based either on biased random number generators or on mixing models familiar from PDF transport models. The new approach is extensively validated on a turbulent flow configuration with simultaneous mixing and reaction. Large eddy simulation data as well as results from a transported PDF model are used for the validation of the jPDD approach. The comparison shows that in particular distributions generated with mixing models are able to predict mean reaction rates accurately. For the configuration considered, the neglect of correlations results in significant underestimation of reaction rates. Moreover it is found that higher statistical moments (e.g. the skewness) can influence reaction rates. The consequences for the generation of jPDDs are discussed. In summary, the new jPDD model has the potential to be significantly more accurate than established presumed PDF methods, because correlations between fluctuating variables can be taken into account. At the same time, the new approach is nearly as efficient as standard presumed PDF formulations, since mean rates are computed in a pre-processing step and stored in look-up tables as a function of the first and second moments of the relevant variables. [ABSTRACT FROM AUTHOR]

Objective: A series of experiments assessed biases in perceived distance that occur while driving as a function of the backlight position of the car ahead and fog density.Background: V. Cavallo, M. Colomb, and J. Doré (2001) have shown that smaller horizontal backlight separation and fog may result in increased estimates of the distance between an observer and a car of which only the backlights are visible. They also predicted that raising the height of the car backlights would lead to increasing distance estimates.Method: Distance perception was assessed in both static and dynamic computer-simulated scenarios in which the distance estimates were performed using a familiarized analog scale or using time-to-collision judgments for both pairs of backlights and single backlights.Results: In a series of five experiments, the horizontal separation and fog density effects were replicated. In addition, distance estimates were consistently larger with higher than with lower vertical backlight positions.Conclusion: There is reason to believe that biases in distance perception may be augmented by car backlight positions and by low-visibility weather conditions.Application: Car designers should take backlight placement seriously. Speed-dependent car-to-car distance control systems seem desirable to counteract biases in distance perception. [ABSTRACT FROM AUTHOR]

Meier and Perrig (2000) as well as Buchner and Wippich (2000) have shown that simple dissociations between explicit and implicit memory measures need not reflect functional dissociations of hypothetical underlying memory systems. Instead, such dissociations may also result from the fact that some widely used implicit memory measures are simply less reliable than the explicit measures with which they have been compared. We extend this argument in two ways. First, we show that illusion-based memory measures such as the priming measures derived from fame and preference judgement tasks are also subject to the reliability problem. Second, we show that yes-no and two-alternative forced-choice paradigms should, and in fact do, yield virtually identical results as far as the reliability of the memory tests is concerned. [ABSTRACT FROM AUTHOR]

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 0.180.140.26$$ {0.18}_{0.14}^{0.26} $$ Pg C year−1 during 2014–2020. This sink was dominated by strong AGC increases (0.610.490.84$$ {0.61}_{0.49}^{0.84} $$ 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. [ABSTRACT FROM AUTHOR]

Monitoring spatio-temporal changes in winter wheat planting areas is of high importance for the evaluation of food security. This is particularly the case in China, having the world's largest population and experiencing rapid urban expansion, concurrently, it puts high pressure on food demands and the availability of arable land. The relatively high spatial resolution of Landsat is required to resolve the historical mapping of smallholder wheat fields in China. However, accurate Landsat-based mapping of winter wheat planting dynamics over recent decades have not been conducted for China, or anywhere else globally. Based on all available Landsat TM/ETM+/OLI images (~28,826 tiles) using Google Earth Engine (GEE) cloud computing and a Random Forest machine-learning classifier, we analyzed spatio-temporal dynamics in winter wheat planting areas during 1999–2019 in the North China Plain (NCP). We applied a median value of 30-day sliding windows to fill in potential data gaps in the available Landsat images, and six EVI-based phenological features were then extracted to discriminate winter wheat from other land cover types. Reference data for training and validation were extracted from high-resolution imagery available via Google Earth™ online mapping service, Sentinel-2 and Landsat imagery. We ran a sensitivity analysis to derive the optimal training sample class ratio (β = 1.8) accounting for the unbalanced distribution of land-cover types. We mapped winter wheat planting areas for 1999–2019 with overall accuracies ranging from 82% to 99% and the user's/producer's accuracies of winter wheat range between 90% and 99%. We observed an overall increase in winter wheat planting areas of 1.42 × 106 ha in the NCP as compared to the year 2000, with a significant increase in the Shandong and Hebei provinces (p < 0.05). This result contrasts the general discourse suggesting a decline in croplands (e.g., rapid urbanization) and climate change-induced unfavorable cropping conditions in the NCP. This suggests adjustments of the winter wheat planting area over time to satisfy wheat supply in relation to food security. This study highlights the application of Landsat images through GEE in documenting spatio-temporal dynamics of winter wheat planting areas for adequate management of cropping systems and assessing food security in China. [ABSTRACT FROM AUTHOR]

Structure-based led optimisation of orally active reversible Methionine Aminopeptidase-2 (MetAP-2) inhibitors utilising a 'molecular budget' medicinal chemistry strategy is described. The key physicochemical parameters of target molecules (cLogP, molecular size and H-bond donor count) were monitored through straightforward and intuitive use of atom count and distribution. The balance between structure-based design and an awareness of the physicochemical properties of the compounds synthesised enabled the rapid identification of a potent molecule with good oral pharmacokinetic (PK) characteristics by making fewer, higher quality compounds. The resulting candidate quality molecule was validated in a mechanistic cellular assay and a rodent secondary immunisation model. [ABSTRACT FROM AUTHOR]

• We quantify large scale afforestation projects impact on forest spatial patterns. • Remote sensing time series is used to analyze the effects of restoration projects. • Clear footprints were observed on the forest landscape of the Loess Plateau. • Core and fragmented forests greatly increased following afforestation projects. • Analysis of spatial pattern dynamics offers a new view on forest ecosystems. The spatial pattern of forests impacts on biodiversity, stability and sustainability of forest ecosystems. Afforestation and reforestation projects have massively increased forested areas on the Chinese Loess Plateau, however, the spatial pattern of the new and old forests, as well as their interaction, remains unknown. Here we study the spatiotemporal dynamics of old and new forests for the period 2001–2016, and found that 84.21% of the old forests existed throughout the study period. Moreover, core forests (defined as a forest area which is surrounded by other forest areas) significantly increased (2585 km2 yr−1, in total 39, 597 km2). Two ecological restoration projects have left clear footprints on the forest landscape of the Loess Plateau: (1) The Natural Forest Conservation Project, aiming at expanding old forest, has resulted in the establishment of considerable areas of new forest surrounding old forest. Consequently, this has promoted new core forest areas to emerge. (2) The Grain for Green Project has mainly caused a fragmented landscape of forest islets which gradually connect to core forest areas. The general increase in core forest areas can be considered an ecological improvement, and the assessment method presented here may guide stakeholders in measuring the success of forest restoration activities that goes beyond a classical quantification of forest cover. [ABSTRACT FROM AUTHOR]

Confined arrays of highly ordered microchannels in silicon with apertures as small as 100 nm and flat ridges between them are manufactured using electrochemically defined Si macropores whose orifices are reduced by deposition of dielectric SiOx thin films. The formation of continuous fluid lipid membranes over these channel arrays is achieved by vesicle fusion. This structure should allow a large choice of lipid membranes to be investigated by spatially resolved ion current measurements. [ABSTRACT FROM AUTHOR]

Dryland ecosystems are frequently struck by droughts. Yet, woody vegetation is often able to recover from mortality events once precipitation returns to pre-drought conditions. Climate change, however, may impact woody vegetation resilience due to more extreme and frequent droughts. Thus, better understanding how woody vegetation responds to drought events is essential. We used a phenology-based remote sensing approach coupled with field data to estimate the severity and recovery rates of a large scale die-off event that occurred in 2014–2015 in Senegal. Novel low (L-band) and high-frequency (Ku-band) passive microwave vegetation optical depth (VOD), and optical MODIS data, were used to estimate woody vegetation dynamics. The relative importance of soil, human-pressure, and before-drought vegetation dynamics influencing the woody vegetation response to the drought were assessed. The die-off in 2014–2015 represented the highest dry season VOD drop for the studied period (1989–2017), even though the 2014 drought was not as severe as the droughts in the 1980s and 1990s. The spatially explicit Die-off Severity Index derived in this study, at 500 m resolution, highlights woody plants mortality in the study area. Soil physical characteristics highly affected die-off severity and post-disturbance recovery, but pre-drought biomass accumulation (i.e., in areas that benefited from above-normal rainfall conditions before the 2014 drought) was the most important variable in explaining die-off severity. This study provides new evidence supporting a better understanding of the "greening Sahel", suggesting that a sudden increase in woody vegetation biomass does not necessarily imply a stable ecosystem recovery from the droughts in the 1980s. Instead, prolonged above-normal rainfall conditions prior to a drought may result in the accumulation of woody biomass, creating the basis for potentially large-scale woody vegetation die-off events due to even moderate dry spells. [ABSTRACT FROM AUTHOR]

• Missing context features in the retrieval cue cause the revelation effect. • A decrease in false alarm and hit rates for low-frequency materials is predicted. • An increase in false alarm and hit rates for high-frequency materials is predicted. • A formal model has been successfully fitted to a series of three new experiments. Interrupting a sequence of episodic recognition decisions by a problem-solving task will change the hit and false alarm rate for the following item in a recognition test (Watkins & Peynircioglu, 1990). The mechanisms of this revelation effect have not yet been understood completely. We offer a new explanation based on the global matching model MINERVA 2 (Hintzman, 1984, 1986, 1988). The main mechanism in our approach is that the interrupting problem-solving task eliminates some context features in the retrieval cue for the next recognition decision. Assuming a constant decision criterion, this shifts the means of the underlying familiarity distributions and produces a revelation effect. The means of the familiarity distributions decrease for low-frequency stimuli but can shift to more positive values for high-frequency stimuli. We show how this approach explains established empirical findings. We also test new predictions within three experiments. The first two experiments show that the revelation effect disappears if context features are made more available at test. The third experiment confirms the prediction that the revelation effect increases as a function of pre-experimental frequency. Overall, our approach explains findings that have been difficult to explain so far, provides a framework for new predictions, and shows connections to other memory paradigms via the underlying model. [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]

We present a wet chemical process for nanoscale texturing of Si surfaces, which results in an almost complete suppression of the reflectivity in a broad spectral range, leading to black Si surfaces. The process affects only the topmost 200–300 nm of the material and is independent of the surface orientation and doping. Thus, it can be applied to various structural forms of bulk silicon (single, poly-, or multicrystalline) as well as to thin Si films (amorphous or microcrystalline). The optical properties of various black Si samples are presented and discussed in correlation with the surface morphology. [ABSTRACT FROM AUTHOR]

Woody vegetation is a central component of savanna ecosystems providing ecosystem services for local livelihoods. Accurate monitoring of woody vegetation in savannas is therefore desirable, yet large scale mapping approaches rely on relatively coarse spatial resolution satellite data, which cannot directly capture the scattered nature of savanna trees. Studies at regional scale thus estimate the fractional cover of woody plants for a given area, whereas binary tree/no-tree estimates are restricted to the use of very high-resolution (VHR) images at local scales. With the launch of the Sentinel satellite systems (Sentinel-1 and Sentinel-2), the spatial resolution of images approaches the size of medium/large tree crowns, providing the opportunity to map the presence/absence of tree canopies, rather than the fraction of woody cover or forested areas. Here, we used a support vector machine (SVM) to classify the presence/absence of woody canopies from Sentinel-1 and Sentinel-2 data at a 10-m spatial resolution for the entire African Sahel. Training samples for the SVM classifier were collected from VHR images provided by Google Earth and Sentinel satellite data were processed in Google Earth Engine. Accuracy assessment was performed based on independent VHR images, showing an overall accuracy of 93% (71% and 98% for producer's accuracy of woody and non-woody pixels, 91% and 93% for user's accuracy of woody and non-woody pixels) when combining Sentinel-1 and Sentinel-2 data (overall accuracy of 89% using Sentinel-1 only and 91% using Sentinel-2 only). The combined use proved to perform significantly better (p < 0.05) than the single use of any of the two. A comparison with existing tree cover maps (by aggregating presence/absence of tree canopies into fractional cover) showed noticeable differences, reflecting the need for new woody cover products adapted to the nature of savanna ecosystems. The Sentinel woody canopy map was able to reproduce the general pattern of scattered woody canopies, but generally overestimated the woody coverage (11.37 ± 26.13% (mean ± sd) when aggregating to 250 m resolution) due to the 10 × 10-m spatial resolution which exceeds the crown size of a typical savanna tree. The cloud-based Sentinel-1 and Sentinel-2 analysis presented is a step towards large scale mapping of woody canopy (tree/no-tree) in savannas. Ultimately, such direct assessment of woody canopy areas will allow monitoring of temporal dynamics of woody canopies in future studies as Sentinel time-series expands to multiple years. • Mapping of woody vegetation in savannas was advanced using Copernicus data in GEE. • Woody canopies were mapped superseding conventional fractional cover estimates. • Mapping was done by Sentinel-1 & −2 temporal signatures (10-m resolution) using SVM. • A map of Sahel showed an overall accuracy of 93%, but overestimated woody coverage. • A comparison with existing tree cover maps showed the added value of this approach. [ABSTRACT FROM AUTHOR]

Sacred forests are increasingly disappearing due to increasing land pressure and a decline in cultural values. Protecting the remaining sacred forests plays a crucial role in preserving biodiversity. The existence of remaining old forests often related to local people and their culture, but this relationship has rarely been quantified at large regional scales. This study analyzes the relationship between old forest and ethnic minorities based on the location of the old forest at a high spatial resolution (2 m). We found a significantly positive correlation (p < 0.01) between the proportion of ethnic minority population and old forest patch number, area, aggregation, and maximum patch area. However, there was no correlation with the connectivity of the old forest (p = 0.14). We further show that both environmental and anthropogenic factors are important for the distribution of old forests. Hydrothermal conditions contribute to the growth of forests, and local ethnic customs and the corresponding ecological wisdom contributes to the preservation of old forest remnants (r = 0.12, p < 0.05). Our findings highlight the significance of social dimensions for the conservation of old forests. We encourage that forest management should consider the role of indigenous people and their cultural wisdom for a better conservation and restoration of degraded ecosystems. • We find a positive correlation between the presence of old forests and the distribution of ethnic minorities. • Hydrothermal conditions contribute to the growth of forests, and traditional knowledge contributes to the preservation of old forests. • The ecological wisdom of local people can improve the conservation of old trees. [ABSTRACT FROM AUTHOR]

Studies excitonic states involved in light-induced degradation of amorphous hydrogenated silicon. Spin-dependent photoconductivity spectrum of low defect density undoped amorphous hydrogenated silicon; Change in conductivity at resonance for a given recombination channel; Creation of metastable defects resulting from excitonic states.

Dryland ecosystems comprise a balance between woody and herbaceous vegetation. Climate change impacts rainfall timing, which may alter the respective contributions of woody and herbaceous plants on the total vegetation production. Here, we apply 30 years of field-measured woody foliage and herbaceous mass from Senegal and document a faster increase in woody foliage mass (+17 kg ha−1 yr−1) as compared to herbaceous mass (+3 kg ha−1 yr−1). Annual rainfall trends were partitioned into core wet-season rains (+0.7 mm yr-1), supporting a weak but periodic (5-year cycles) increase in herbaceous mass, and early/late rains (+2.1 mm yr−1), explaining the strongly increased woody foliage mass. Satellite observations confirm these findings for the majority of the Sahel, with total herbaceous/woody foliage mass increases by 6%/20%. We conclude that the rainfall recovery in the Sahel does not benefit herbaceous vegetation to the same extent as woody vegetation, presumably favoured by increased early/late rains. Martin Brandt et al. studied foliage mass from Senegal over 30 years, observing the effects of climate change on dryland vegetation. Rainfall caused increases in both herbaceous and woody foliage, but woody vegetation benefits from rainfall timing changes with potential knock-on effects to the local herbivore populations. [ABSTRACT FROM AUTHOR]

Group IV vacancy color centers in diamond are promising spin-photon interfaces with strong potential for applications in photonic quantum technologies. Reliable methods for controlling and stabilizing their charge state are urgently needed for scaling to multiqubit devices. Here, we manipulate the charge state of silicon vacancy (SiV) ensembles by combining luminescence and photocurrent spectroscopy. We controllably convert the charge state between the optically active SiV- and dark SiV2- with megahertz rates and >90% contrast by judiciously choosing the local potential applied to in-plane surface electrodes and the laser excitation wavelength. We observe intense SiV- photoluminescence under hole capture, measure the intrinsic conversion time from the dark SiV2- to the bright SiV- to be 36.4(67) ms, and demonstrate how it can be enhanced by a factor of 105 via optical pumping. Moreover, we obtain previously unknown information on the defects that contribute to photoconductivity, indicating the presence of substitutional nitrogen and divacancies. [ABSTRACT FROM AUTHOR]

The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small stands, requiring 10 to 50 m spatial resolution data to be correctly separated. Further, 35 % of the French forest territory is covered by mountains and Mediterranean forests which are managed very extensively. In this work, we used a deep-learning model based on multi-stream remote-sensing measurements (NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission and ESA's Copernicus Sentinel-1 and Sentinel-2 satellites) to create a 10 m resolution canopy height map of France for 2020 (FORMS-H). In a second step, with allometric equations fitted to the French National Forest Inventory (NFI) plot data, we created a 30 m resolution above-ground biomass density (AGBD) map (Mg ha -1) of France (FORMS-B). Extensive validation was conducted. First, independent datasets from airborne laser scanning (ALS) and NFI data from thousands of plots reveal a mean absolute error (MAE) of 2.94 m for FORMS-H, which outperforms existing canopy height models. Second, FORMS-B was validated using two independent forest inventory datasets from the Renecofor permanent forest plot network and from the GLORIE forest inventory with MAE of 59.6 and 19.6 Mg ha -1 , respectively, providing greater performance than other AGBD products sampled over France. Finally, we compared FORMS-V (for volume) with wood volume estimations at the ecological region scale and obtained an R2 of 0.63 with an MAE of 30 m 3 ha -1. These results highlight the importance of coupling remote-sensing technologies with recent advances in computer science to bring material insights to climate-efficient forest management policies. Additionally, our approach is based on open-access data having global coverage and a high spatial and temporal resolution, making the maps reproducible and easily scalable. FORMS products can be accessed from 10.5281/zenodo.7840108 (Schwartz et al., 2023). [ABSTRACT FROM AUTHOR]

China karst is a global hotspot of increasing vegetation cover, with ecological conservation projects being considered as the main driver. New research using global datasets also indicates that rural outmigration has contributed to increasing biomass at national scale. However, the link between rural outmigration and vegetation cover increase has not been established at regional scale, and it remains unclear as to whether increases in biomass do, in fact, improve the environmental conditions. In this study, we use local field and statistical data on population density and rocky desertification areas to study population movements and changes in aboveground biomass in relation to rocky desertification in South China karst during 2000–2017. Our results show that the urban population in this region increased by 8.3 million people between 2005 and 2015, and the rural population decreased by 4.8 million people. We find that aboveground biomass increased most in rural areas with low human pressure, and that there was an almost linear relationship between increase in biomass and rural outmigration, with the highest increase in aboveground biomass density (1.5 MgC ha−1 yr−1) observed in areas where rural outmigration was highest, and the lowest increase in aboveground biomass density (1.1 MgC ha−1 yr−1) where rural outmigration was lowest. Rocky desertification areas decreased with a higher level of rural outmigration. Using local field data, our study confirmed that rural outmigration can generate a carbon sink at regional scale by reducing rocky desertification. [ABSTRACT FROM AUTHOR]

The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small stands, requiring 10 to 50 m spatial resolution data to be correctly separated. Further, 35 % of the French forest territory is covered by mountains and Mediterranean forests which are managed very extensively. In this work, we used a deep-learning model based on multi-stream remote sensing measurements (NASA's GEDI LiDAR mission and ESA's 25 Copernicus Sentinel 1 & 2 satellites) to create a 10 m resolution canopy height map of France for 2020 (FORMS-H). In a second step, with allometric equations fitted to the French National Forest Inventory (NFI) plot data, we created a 30 m resolution above-ground biomass density (AGBD) map (Mg ha-1) of France (FORMS-B). Extensive validation was conducted. First, independent datasets from Airborne Laser Scanning (ALS) and NFI data from thousands of plots reveal a mean absolute error (MAE) of 2.94 m for FORMS-H, which outperforms existing canopy height models. Second, FORMS-B 30 was validated using two independent forest inventory datasets from the Renecofor permanent forest plot network and from the GLORIE forest inventory with MAE of 59.6 Mg ha-1 and 19.6 Mg.ha-1 respectively, providing greater performance than other AGBD products sampled over France. These results highlight the importance of coupling remote sensing technologies with recent advances in computer science to bring material insights to climate-efficient forest management policies. Additionally, our approach is based on open-access data having global coverage and a high spatial and temporal resolution, 35 making the maps reproducible and easily scalable. FORMS products can be accessed from https://doi.org/10.5281/zenodo.7840108 (Schwartz et al., 2023). [ABSTRACT FROM AUTHOR]

The sahelian rainfall regime is characterized by a strong spatial as well as intra- and inter-annual variability. The satellite based African Rainfall Climatology Version 2 (ARC2) daily gridded rainfall estimates with a 0.1° × 0.1° spatial resolution provides the possibility for in-depth studies of seasonal changes over a 33-year period (1983–2015). Here we analyze rainfall regime variables that require daily observations: onset, cessation, and length of the wet season; seasonal rainfall amount; number of rainy days; intensity and frequency of rainfall events; number, length, and cumulative duration of dry spells. Rain gauge stations and MSWEP (Multi-Source Weighted-Ensemble Precipitation) data were used to evaluate the agreement of rainfall variables in both space and time, and trends were analyzed. Overall, ARC2 rainfall variables reliably show the spatio-temporal dynamics of seasonal rainfall over 33 years when compared to gauge and MSWEP data. However, a higher frequency of low rainfall events (<10 mm day −1 ) is found for satellite estimates as compared to gauge data, which also causes disagreements between satellite and gauge based variables due to sensitivity to the number of days with observations (frequency, intensity, and dry spell characteristics). Most rainfall variables (both ARC2 and gauge data) show negative anomalies (except for onset of rainy season) from 1983 until the end of the 1990s, from which anomalies become mostly positive and inter-annual variability is higher. ARC2 data show a strong increase in seasonal rainfall, wet season length (caused by both earlier onset and a late end), number of rainy days, and high rainfall events (>20 mm day −1 ) for the western/central Sahel over the period of analysis, whereas the opposite trend characterizes the eastern part of the Sahel. [ABSTRACT FROM AUTHOR]

The karst area in southwest China is, in recent decades, one of the world's regions with the fastest vegetation growth and increase in aboveground biomass. The improvement in the ecological conditions within this region can, to a large extent, be attributed to ecological protection projects. However, it remains unclear whether the observed increase in vegetation cover could mitigate rocky desertification at large scale. In this study, we utilized information from large field campaigns in the years 2005, 2011, and 2016, supported by satellite imagery interpretation and statistics on ecological protection projects, to explore the impact of restoration efforts on rocky desertification mitigation and vegetation resilience/resistance. The results show that restoration efforts caused a net decrease of 26.14% in areas affected by rocky desertification from 2005 to 2016. The larger the restoration efforts, the stronger the decrease in rocky desertification areas, and also the vulnerability of landscapes towards desertification; the probability of rocky desertification occurring decreased almost linearly with increased restoration efforts. In addition, both vegetation resilience and resistance against climate variations increased with restoration efforts. Restoration efforts were mainly responsible for the recovery of the ecosystem, showing that human impact is the main driver for the reversal of rocky desertification. Our study provides scientific evidence on rocky desertification control being an important step towards a sustainable development of the landscapes of Southwest China. [ABSTRACT FROM AUTHOR]