Continuous Vegetation Research Articles

Productivity experienced a more rapid enhancement trend than greenness across the Tibetan Plateau

Satellite-derived products and field measurements verify that Tibetan Plateau (TP) has been experiencing continuous vegetation greening and productivity increase; however, it remains unclear how this greening translates into productivity and how long-term productivity variations depend on greenness across the TP. Moreover, ignoring the accuracy evaluation of satellite-derived greenness and productivity products may mislead the understanding of TP vegetation changes. Thus, we initially assessed the accuracy of three widely used leaf area index (LAI, proxy of greenness) products (i.e., MODIS, GLASS and GEOV2 LAI) and three gross primary productivity (GPP, proxy of productivity) products (i.e., MODIS, GLASS and PML-V2 GPP) to selected robust products to represent greenness and productivity respectively. Then, we explored the dependence of spatiotemporal GPP dynamics on greenness variations during 2000–2020. Results indicated that PML-V2 GPP and MODIS LAI were more robust and reliable than other satellite-derived products when compared to the reference values. They revealed a prevailing increase in GPP over the past two decades, with a regional average of 71 % higher than that of LAI. Notably, the area proportion of significant productivity enhancement was 31.6 % higher than that of significant greening. About 24.7 % of the TP displayed significantly inconsistent trends. The dependency of GPP on LAI gradually decreased with the increasing water availability, the complexity of vegetation structures, and dense canopy community. By calculating leaf photosynthetic capacity, we found that this indicator greatly regulated the velocity discrepancy between GPP and LAI, and the contribution of only greening to productivity is limited, only occupying 11.9 % of the TP, which was helpful in understanding the inter-annual changes of vegetation dynamics under varying environment conditions. We therefore reveal an unexpected rapid increase in productivity than greening during 2000–2020 on the TP, as well as highlight the caution of only using satellite-derived greenness indicators for assessing long-term changes in vegetation productivity dynamics, especially over mesic ecosystems with complex vegetation structures and dense canopies of TP.

Producing annual Australia-wide vegetation height images from GEDI and Landsat data

ABSTRACT Vegetation height, and its spatial and temporal changes, is an important environmental parameter required for understanding natural habitats, estimating carbon stores and monitoring forestry activities. Recent satellite LiDAR altimetry sensors have discontinuous spatial coverage but can be combined with spatially complete remote sensing data to extrapolate to large regions. Earlier studies have focused on producing a single spatially continuous vegetation height product. This research builds on past studies, using Landsat (annual surface reflectance and fractional cover products) and the Global Ecosystem Dynamics Investigation (GEDI) data to generate annual vegetation height layers from 1988 to 2022. GEDI data for 2019 were used to train and validate the model, resulting in a root mean square error (RMSE) of 5.45 m, mean absolute error (MAE) of 3.82 m, and coefficient of determination (R2) of 0.63. This accuracy reduces when the modelled height for 2020, 2021, and 2022 is compared to GEDI data for the same years (RMSE = 6.08–6.29 m, MAE = 4.36–4.73 m, and R2 = 0.48–0.54). Validation with independent field measurements across Australia from 2011 to 2021 shows an RMSE, MAE, and R2 of 8.2 m, 5.2 m, and 0.48, respectively. One source of error is the saturation of the Landsat signal in tall, closed canopy vegetation. While model accuracy is correlated with plot-based vegetation height measurements, results indicate that accuracy reduces for the years outside of the model calibration year (i.e. 2019). When compared to other vegetation height products (also produced using GEDI and spatial remote sensing data) from three independent published studies (one for 2009, one for 2019, and one for 2020), the model developed here tends to estimate 2–4 m taller than the first two studies and around 5 m shorter when compared to the third study. This investigation demonstrates the potential to produce multiyear vegetation height at a continental scale but also highlights the large uncertainty in modelled estimates especially when extrapolating to years other than the model calibration year.

Comparison of change-based and shape-based data fusion methods in fine-resolution land surface phenology monitoring with Landsat and Sentinel-2 data

Fine-resolution land surface phenology (LSP) is urgently required for applications on agriculture management and vegetation-climate interaction, especially over heterogeneous areas, such as agricultural lands and fragmented forests. The critical challenge of fine-resolution LSP monitoring is how to reconstruct the spatiotemporal continuous vegetation index time series. To solve this problem, various data fusion methods have been devised; however, the comprehensive inter-comparison is lacking across different spatial heterogeneity, data quality, and vegetation types. We divide these methods into two main categories: the change-based methods fusing satellite observations with different spatiotemporal resolutions, and the shape-based methods fusing prior knowledge of shape models and satellite observations. We selected four methods to rebuilt two-band enhanced vegetation index (EVI2) series based on the harmonized Landsat and Sentinel-2 (HLS) data, including two change-based methods, namely the Spatial and temporal Adaptive Reflectance Fusion Model (STARFM), the Flexible Spatiotemporal DAta Fusion (FSDAF), and two shape-based methods, namely the Multiple-year Weighting Shape-Matching (MWSM), and the Spatiotemporal Shape-Matching Model (SSMM). Four phenological transition dates were extracted, evaluated with PhenoCam observations and the 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) phenology product. The 30 m transition dates show more spatial details and reveal more apparent intra-class and inter-class phenology variation compared with 500 m product. The four transition dates of SSMM and FSDAF (R2>0.74, MAD<15 days) show better agreement with PhenoCam-derived dates. The performance difference between fusion methods over various application scenarios are then analyzed. Fusion results are more robust when temporal frequency is higher than 15 observations per year. The shape-based methods are less sensitive to temporal sampling irregularity than change-based methods. Both change-based methods and shape-based methods cannot perform well when the region is heterogeneous. Among different vegetation types, SSMM-like methods have the highest overall accuracy. The findings in this paper can provide references for regional and global fine-resolution phenology monitoring.

Study of assessment and monitoring of pastures land areas in hills based on GIS technologies (case study Southern Uzbekistan)

In this study, we have undertaken a comprehensive exploration of vegetation monitoring and biomass assessment in the mountainous and sub-mountainous regions of southern Uzbekistan, leveraging the capabilities of Geographic Information System (GIS) technologies and remote sensing data. Our research has focused on the critical analysis of biomass levels during the primary plant season, as well as continuous plant monitoring. Our methodology involved the utilization of Landsat 9 satellite image data, further analyzed through the application of two essential vegetation indices, namely the Normalized Difference Vegetation Index (NDVI) and the Soil- Adjusted Vegetation Index (SAVI). One of the key objectives of our investigation was to assess the potential for extrapolating the biomass model for plant cover using GIS technologies. This extrapolation aims to extend our understanding to encompass the period of continuous vegetation coverage monitoring. The combination of GIS, remote sensing data, and advanced vegetation indices serves as a powerful framework for gaining insights into the dynamics of plant growth and biomass variations. Such research not only enhances our understanding of the ecological landscape but also provides valuable information for sustainable land management and agriculture practices in the region

Temporal and spatial variability of physical and chemical properties in reclaimed soil after sulphur borehole mining

Mining contributes to the creation of degraded areas that are difficult to rehabilitate because they are subject to various transformations. Specifically, sulphur mining using the Frasch borehole method causes multidirectional changes of soil properties and thus presents challenges for post-mining rehabilitation. The aim of the current study was to evaluate the effectiveness of agricultural (meadow-type) reclamation and to understand how the soil recovers over time by assessing the spatio-temporal variability of the reclaimed soil after borehole sulphur mining. Selected soil properties and spectral indices based on satellite data were analysed: before reclamation, 3 years after reclamation and 15 years after reclamation. Texture, bulk density, porosity, water capacity, total organic carbon (TOC) and pH were measured and distribution maps of these parameters were generated using kriging. Additionally, maps of spectral indices (Green Normalized Difference Vegetation Index, Normalized Difference Soil Moisture Index, Soil Adjusted Vegetation Index, Enhanced Vegetation Index and Red–Green Index) based on Landsat imagery were created to support the field survey data. The soil revealed high temporal and spatial variability, as evidenced by the distributions of measured parameters and their coefficients of variation at different reclamation stages. Multidirectional remodelling of the soil structure occurred, resulting in changes in the differential porosity, field water capacity, texture, reaction and TOC. Statistically confirmed differences in soil parameters between sampling points were observed. The variability of the physical and chemical parameters at the individual sampling point also differed between the reclamation stages. We observed a general trend towards homogenisation of the spatial distributions of the soil parameters. This was also confirmed by the maps of spectral indices, which showed establishment and development of a continuous vegetation cover and the subsequent improvement of its condition.

A Unified Physically Based Method for Monitoring Grassland Nitrogen Concentration with Landsat 7, Landsat 8, and Sentinel-2 Satellite Data

The increasing number of satellite missions provides vast opportunities for continuous vegetation monitoring, crucial for precision agriculture and environmental sustainability. However, accurately estimating vegetation traits, such as nitrogen concentration (N%), from Landsat 7 (L7), Landsat 8 (L8), and Sentinel-2 (S2) satellite data is challenging due to the diverse sensor configurations and complex atmospheric interactions. To address these limitations, we developed a unified and physically based method that combines a soil–plant–atmosphere radiative transfer (SPART) model with the bottom-of-atmosphere (BOA) spectral bidirectional reflectance distribution function. This approach enables us to assess the effect of rugged terrain, viewing angles, and illumination geometry on the spectral reflectance of multiple sensors. Our methodology involves inverting radiative transfer model variables using numerical optimization to estimate N% and creating a hybrid model. We used Gaussian process regression (GPR) to incorporate the inverted variables into the hybrid model for N% prediction, resulting in a unified approach for N% estimation across different sensors. Our model shows a validation accuracy of 0.35 (RMSE %N), a mean prediction interval width (MPIW) of 0.35, and an R2 of 0.50, using independent data from multiple sensors collected between 2016 and 2019. Our unified method provides a promising solution for estimating N% in vegetation from L7, L8, and S2 satellite data, overcoming the limitations posed by diverse sensor configurations and complex atmospheric interactions.

CONSIDERATIONS ABOUT HABITAT LOSS IN CHAPADA DIAMANTINA, BAHIA, BRAZIL

Habitat fragmentation is characterised by reducing a continuous vegetation area in isolated patches. The objective was to evaluate if there is a process of fragmentation or habitat loss in the Chapada Diamantina and to report the first impressions on how local biodiversity is affected. We used Geoprocessing techniques and elaborated a map of vegetation cover and land use with Sentinel satellite images. We also used QGIS 3.10, visual analysis, photo interpretation, and classification techniques supervised by the Dzetsaka algorithm. The results indicate that the Morro do Chapéu State Park (MCSP) is not yet fragmented, and there is an intermediate level of habitat loss; if it persists, it could lead to the fragmentation of the protected area and further impact biodiversity. For this problem to be repaired or mitigated, it is necessary to think of priority areas for land regularisation and increased supervision, an attempt to repress illegal activities in this conservation area.

Temporal and spatial changes of soil erosion under land use and land cover change based on Chinese soil loss equation in the typical watershed on the Loess Plateau

AbstractLand use and land cover change (LULCC) directly affect the temporal and spatial change of soil erosion. As a typical governance watershed in the hilly and gully area of the Loess Plateau, the Jiuyuangou watershed has experienced significant LULCC in the past 10 years due to conversion of farmland to forests, economic construction, and cropland abandonment. However, the evolution process of soil erosion change and LULCC in the watershed is unclear, as is the relationship between the two. This study used satellite images to extract information on LULCC in the watershed and the Chinese soil loss equation (CSLE) model to evaluate the temporal and spatial evolution of soil erosion in the watershed from 2010 to 2020. The main results showed that (1) the continuous vegetation restoration project in the watershed reduced soil erosion from 2010 to 2015; however, the increased frequency of extreme rainfall events after 2015 reduced its impact. The annual average soil erosion modulus decreased from 10.85 t ha−1 year−1 in 2010 to 8.03 t ha−1 year−1 in 2015 but then increased to 10.57 t ha−1 year−1 in 2020; (2) the main land use and land cover (LULC) type in the Jiuyuangou watershed is grassland, accounting for 62% of the total area, followed by forestland, cropland, buildings, and water. Cropland has the largest multi‐year average soil erosion modulus, followed by grassland and buildings, with forestland having the smallest; (3) significant spatial correlations occurred between soil erosion change and LULCC for common ‘no change’ and common ‘gain’ in the settlements, roads, and areas near the human influences with good soil and water conservation, but not other regions due to the influence of climatic factors (heavy rain events). Thus, we should repair terraces, control dams in the watershed, and actively conserve water and soil. This study provides a scientific reference for planning and managing water and soil conservation and ecological environment construction in the watershed.

Bee richness and abundance in small fruit farms from semiarid landscape, NE, Brazil

Bee diversity and current status of native populations is barely known in cropland from semiarid Sergipe, where fruit production is a growing activity among small farmers. Psidium guajava L. (Myrtaceae) is spread among small growers in Canindé de São Francisco and Poço Redondo in Sergipe state, Northeastern Brazil, in semiarid Caatinga, causing landscape change and habitat loss. Available evidences support that cross-pollination provided by bees may increase seed set and fruit production, despite self-pollination. We aimed to access bee richness and abundance within Guava orchard and identify landscape parameters important to these patterns. Survey was conducted in ten Guava orchards during the flowering period (n=10) from May to December 2017. Nine bee species were recorded and the high density and generalist bees Trigona spinipes and Apis mellifera comprised 92% of the flower visitors. No other social native bees were found, and solitary bees were scarce. No significant influence of landscape structure was found for bee richness, while bee abundance was affected by environmental diversity, isolation, and distance to caatinga patches and continuous vegetation reserves. Landscape simplification threatened bee diversity and pollination services. These results highlight the importance of providing bee habitat within farmlands, rearing stingless bees and restoring natural habitats along streams to increase wild bee populations within crops.

Distribution Characteristics of the Alpine Treeline and Vegetation Response to Climate Change of Taibai Mountain, China

Climate change significantly affects global forest ecosystems, and the alpine treeline is sensitive to global warming. The alpine treeline data using high-resolution remote sensing images during four periods from 1987 to 2020 at Taibai Mountain are extracted. The dynamic change process of the alpine treeline and the response of vegetation near the alpine treeline to climate change are analyzed. The results showed that the alpine treeline of Taibai Mountain was primarily distributed in the range of 2266-3692 m, and the average elevation of the alpine treeline showed a trend of “rising-decreasing.” The elevation of the alpine treelines of the sunny slopes were much higher than that of the shady slopes, and the highest values typically appeared on slopes and steep slopes of 15-35°. Vegetation is sensitive to temperature changes, and it typically displays a synchronous increase and decrease. However, there was a lag in the precipitation of approximately one year, and the rising temperatures of the sunny slopes were not conducive to vegetation growth. The vegetation will be dominated by a trend of unsustainable improvement in the future, and there exists a risk of continuous vegetation degradation on the northern slopes. However, a warm and humid climate will be conducive to vegetation growth above the alpine treeline.

Investigating the spatio-temporal variation of vegetation water content in the western United States by blending GNSS-IR, AMSR-E, and AMSR2 observables using machine learning methods

Vegetation water content (VWC) is an important parameter when evaluating vegetation growth and climate change. The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has provided us with an effective approach for the monitoring of VWC. The normalized microwave reflection index (NMRI) was defined to reflect the change of VWC, based on the fact that the amplitude of the direct and reflected GNSS interferometric signal is related to the variation of VWC. However, the sparse distribution of the ground-site-based observation stations restricts the application of NMRI. Fortunately, microwave vegetation optical depth (VOD) is a dimensionless parameter that describes the rate of attenuation of microwaves as they pass through the vegetation canopy, which can provide spatially continuous vegetation information. In this study, we integrate the GNSS-IR NMRI dataset with Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) VOD datasets by using three machine learning models: the generalized regression neural network (GRNN) model, the back-propagation neural network (BPNN) and multiple linear regression (MLR) models. This method can overcome the drawbacks of sparse distribution and spatial discontinuity of GNSS-IR site data, and obtains spatio-temporally continuous NMRI products that can more intuitively and accurately reflect the variability of VWC in the study area. The results showed that the GRNN model has the best retrieval accuracy, with model fitting and cross-validation R values of 0.76 and 0.74, and root-mean-square error (RMSE) values of 0.034 and 0.035, respectively. Based on the GRNN model, we obtained a spatio-temporally continuous NMRI product to further analyze the changes in VWC from 2007 to 2018. The results indicated that the effects of ENSO events with different intensities on vegetation and precipitation are different, and the response of VWC with different vegetation types to ENSO are also different. The anomalies of VWC show a lag phenomenon and is more stable, not as sensitive as precipitation to the ENSO events.

Forest Soils: Functions, Threats, Management

The specific characteristic of forest soils is their long-term development under a more-or-less continuous vegetation cover [...]

Riparian ecosystems mapping at fine scale: a density approach based on multi‐temporal UAV photogrammetric point clouds

AbstractIn recent years, numerous directives worldwide have addressed the conservation and restoration of riparian corridors, activities that rely on continuous vegetation mapping to understand its volumetric features and health status. Mapping riparian corridors requires not only fine‐scale resolution but also the coverage of relatively large areas. The use of Unmanned Aerial Vehicles (UAV) allows for meeting both conditions, although the cost‐effectiveness of their use is highly influenced by the type of sensor mounted on them. Few works have so far investigated the use of photogrammetric sensors for individual tree crown detection, despite being cheaper than the most common Light Detection and Ranging (LiDAR) ones. This work aims to improve the individual crown detection from UAV‐photogrammetric datasets in a twofold way. Firstly, the effectiveness of a new approach that has already achieved interesting results in LiDAR applications was tested for photogrammetric point clouds. The test was carried out by comparing the accuracy achieved by the new approach, which is based on the point density features of the analysed dataset, with those related to the more common local maxima and textural methods. The results indicated the potentiality of the density‐based method, which achieved accuracy values (0.76 F‐score) consistent with the traditional methods (0.49–0.80 F‐score range) but was less affected by under‐ and over‐fitting. Secondly, the potential improvement of working on intra‐annual multi‐temporal datasets was assessed by applying the density‐based approach to seven different scenarios, three of which were constituted by single‐epoch datasets and the remaining given by the joining of the others. The F‐score increased from 0.67 to 0.76 when passing from single‐ to multi‐epoch datasets, aligning with the accuracy achieved by the new method when applied to LiDAR data. The results demonstrate the potential of multi‐temporal acquisitions when performing individual crown detection from photogrammetric data.

Extrapolating continuous vegetation water content to understand sub-daily backscatter variations

Abstract. Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave observations creates a unique opportunity to study vegetation water dynamics and its role in the diurnal water cycle. However, we currently have a limited understanding of sub-daily variations in the VWC and how they affect microwave observations. This is partly due to the challenges associated with measuring internal VWC for validation, particularly non-destructively, and at timescales of less than a day. In this study, we aimed to (1) use field sensors to reconstruct diurnal and continuous records of internal VWC of corn and (2) use these records to interpret the sub-daily behaviour of a 10 d time series of polarimetric L-band backscatter with high temporal resolution. Sub-daily variations in internal VWC were calculated based on the cumulative difference between estimated transpiration and sap flow rates at the base of the stems. Destructive samples were used to constrain the estimates and for validation. The inclusion of continuous surface canopy water estimates (dew or interception) and surface soil moisture allowed us to attribute hour-to-hour backscatter dynamics either to internal VWC, surface canopy water, or soil moisture variations. Our results showed that internal VWC varied by 10 %–20 % during the day in non-stressed conditions, and the effect on backscatter was significant. Diurnal variations in internal VWC and nocturnal dew formation affected vertically polarized backscatter most. Moreover, multiple linear regression suggested that the diurnal cycle of VWC on a typical dry day leads to a 2 (HH, horizontally, and cross-polarized) to almost 4 (VV, vertically, polarized) times higher diurnal backscatter variation than the soil moisture drydown does. These results demonstrate that radar observations have the potential to provide unprecedented insight into the role of vegetation water dynamics in land–atmosphere interactions at sub-daily timescales.

Exploring sandy vegetation sensitivities to water storage in China’s arid and semi-arid regions

Hulunbuir, Otindag, Horqin and Mu Us are the four greater sandy lands in China. They are typical ecologically fragile areas with limited ability to resist interference and are susceptible to changes in the external environment. With climate change in recent decades, these areas have experienced severe land desertification and decreased groundwater levels. The ecological environment is at risk of further deterioration, and continuous vegetation restoration and management should be adapted to the local climate and maintain the water balance with natural precipitation. This paper combines multi-source satellite observations to explore the relationship between vegetation growth and water supply. The results show four main points. (1) Although the vegetation growth in Otindag and Horqin had degraded before 2010, it improved after 2010. The vegetation growth and soil moisture (SM) of the four sandy lands both generally increased from 2003 to 2016. The SM of the Horqin increased significantly (84% anomaly > 1.4 × 10−2 cm3/cm3). Other than the Hulunbuir, the other sandy lands show a downward trend in terrestrial water storage (TWS), especially the Mu Us declined the most (97% anomaly < −40 mm). (2) Solar-induced chlorophyll fluorescence (SIF) has specific advantages in characterizing the sandy vegetation productivity and water composition changes compared to vegetation index (EVI) or gross primary productivity (GPP). (3) The regional pattern of the vegetation-moisture relationship is mainly affected by the precipitation-driven SM and depends on the types of underlying vegetation functions. (4) Both SM and TWS have approximately one-month persistence in the four sandy lands, especially the Mu Us has the longest persistence (0.94 months and 1.1 months). The persistence in the early period is generally longer than that in the late period, implying that the resilience of water components after the mutation year is stronger than before it. This study provides a scientific basis for the management and restoration of sandy lands. It is recommended that different vegetation restoration and protection strategies should be developed for specific sandy land moisture conditions in arid/semi-arid regions of northern China, which includes the improvement of water use efficiency to maintain soil moisture and the reduction of excessive groundwater uses.

Continuous vegetation record of the Greater Cape Floristic Region (South Africa) covering the past 300 000 years (IODP U1479)

Abstract. The Greater Cape Floristic Region (GCFR) of South Africa is a biodiversity hotspot of global significance, and its archeological record has substantially contributed to the understanding of modern human origins. For both reasons, the climate and vegetation history of southwestern South Africa is of interest to numerous fields. Currently known paleoenvironmental records cover the Holocene, the last glacial–interglacial transition and parts of the last glaciation but do not encompass a full glacial–interglacial cycle. To obtain a continuous vegetation record of the last Pleistocene glacial–interglacial cycles, we studied pollen, spores and micro-charcoal of deep-sea sediments from IODP Site U1479 retrieved from SW of Cape Town. We compare our palynological results of the Pleistocene with previously published results of Pliocene material from the same site. We find that the vegetation of the GCFR, in particular fynbos and afrotemperate forest, responds to precessional forcing of climate. The micro-charcoal record confirms the importance of fires in the fynbos vegetation. Ericaceae-rich and Asteraceae-rich types of fynbos could extend on the western part of the Paleo-Agulhas Plain (PAP), which emerged during periods of low sea level of the Pleistocene.

Temporal Shape-Based Fusion Method to Generate Continuous Vegetation Index at Fine Spatial Resolution

In this study, a temporal shape–based fusion method using a spatially and temporally moving window is proposed to incorporate time lag of fine and coarse resolution observations, and to fully utilize target fine resolution pixel and similar coarse resolution pixels in the process. This method provides high accuracy fused images with Pearson’s r of ~0.95, root mean square error of ~0.04, and bias of ~0.01 for commonly used fine spatial resolution satellites, including Landsat 7 and 8, Sentinel 2, and Gaofen 1, over different heterogeneous regions, such as urban, mountain, forest, and savanna regions. The fused fine resolution Enhanced Vegetation Index (EVI) time series using different fine spatial resolution satellites data as input are all highly correlated with the PhenoCam monitored green chromatic coordinate, with no temporal lag. Compared with commonly used data fusion method, this method provides equivalent and slightly higher accuracy because both neighboring similar pixels and the annual temporal variation are fully considered. This temporal shape–based fusion method does not require each input fine resolution image to be cloud-free; therefore, it can be used at a large spatial scale without further preprocessing and generates continuous datasets over a long-time range with only one input preparation process. The factors that could affect the method accuracy are the cloud detection accuracy of fine resolution data and the temporal continuity of the coarse resolution data. The method may also be used to produce spatially and temporally continuous surface reflectance and other surface reflectance derived indices.

Флора сосудистых растений порта Ямбург

The data on the flora of the port of Yamburg (67° 54' s. w., 74° 48' v. d.) on the Taz Peninsula, 148.5 km north of the Arctic Circle, in the Yamalo-Nenets Autonomous Okrug of the Tyumen Region are presented. The port area is about 4 hectares. The whole area is covered with sand. There is no continuous vegetation cover, it is very sparse. 42 species of vascular plants were found (28.07.2013). During 3 years of forwarding work in the Arctic (2012-2014), Poa lanata Scribn. et Merrt, Lathyrus quinquenervis (Miq.) Litv. ex Kom. and Lathyrus pilosus Cham. ´ L. quinquenervis (Miq.) Litv. ex Kom. were collected only in the port of Yamburg. It is established that these species are the result of repeated migrations. They are rare, so they have not been noted elsewhere. It is revealed that all other species are introduced from adjacent natural territories and are at different stages of the apophitization process. In the course of the conducted studies, it was noted that representatives of the Poaceae family (17 species) predominate, Fabaceae (5 species) are in second place, followed by Asteraceae and Polygonaceae (4 species each). The most widespread species were Artemisia tilesii, Crepis multicaulis, Tripleurospermum hookeri. There are only 3 drift species: Poa angustifolia, Puccinellia distans, Puccinellia hauptiana. The small number of species is explained by the northern location, a thick layer of sand and the weak role of river transport as a source of drift.

Stratigraphie dans la Galerie Ouest de la Grotte de Lorette (Rochefort, Belgique) : Apport de la coupe des gours suspendus

The Lorette Cave contains a wide variety of deposits within various stratigraphical contexts. This cave is a part of the complex underground meander cut-off of the Wamme and Lomme rivers, between some swallow-holes along their two talwegs near On, Jemelle and Rochefort, and the general resurgence at Eprave. The Lorette Cave is embedded within the Givetian limestone formations of the Calestienne. This cave displays the first part with a labyrinthic structure. Some parts of the karstic network are affected by recent tectonic activity, which dislocates some galleries and provokes collapses. The second part of the cave comprises the West Gallery, which contains the most complete sedimentary series. The “gours suspendus” (hanging gours) section is located at the western end of the gallery. The cave contains numerous and rich detrital deposits. The oldest sedimentary unit is a diamictite found in several galleries (e.g. Galerie Fontaine-Bagdad, Salle du Cataclysme). It is composed of large decametric-sized quartz and sandstone pebbles coming from the erosion of the Lower Devonian formations of the Ardenne. This deposit is older than the U/Th dating limit, i.e. 350 ka. The West Gallery exposes an area of collapsed blocks and ends in a vast room. This gallery is filled with a thick fluvial series of upper Pleistocene age and capped by speleothems of Tardiglacial to Holocene age. The large terminal chamber is clogged by flooded pits. A tributary gallery shows a sedimentary series in a subsiding pit, the “Fosse aux Lions” (Lions’ Pit). These deposits are made of a diamictite interbedded between two fluvial units, the upper part of which displays oblique stratifications. The dating of a summit stalagmite places this set at 120 ka. The present paper analyses a section made in the southern flank of the terminal room, close to the junction with the West Gallery: the “gours suspendus” section. A large part of this section consists of a complex fluvial deposit disconformably resting on top of a compact lower clay formation. This fluvial deposit is stratified, comprising mostly diamictites interstratified with thin levels of gravel and clay. It is capped by an upper clay unit and sealed by a flowstone. Thin strata of finer-grained size sediments (coarse sand), as well as clay lenses, occur within the lower clay. The diamictites indicate a torrential origin of the sediment. At the base, just above the lower clay, some sandy channelling strata testify that one or several fluvial deposition episodes occurred. Then, torrential and probably very short-living events are separated by decantation phases. The pebbles and smaller particles are made of quartz, sandstone and muscovite that most probably originated in the Lower Devonian formations. The “gours suspendus” section provides a new illustration of the succession of sedimentation and erosion phases in Belgian caves. It is now well demonstrated that speleothems grow mainly during temperate to hot and humid climatic phases and detrital infills are deposited in caves during cold/glacial phases. The physical erosion of sediments with ravine formations should be placed in the climatic history of the region. A gullying by a coarse detrital formation like that of the new section is due to a powerful heavy-loaded current. The deposits within caves were therefore available, which can only occur during a cold phase due to the absence of continuous vegetation cover. The sand and clay levels interstratified between levels of pebbles indicate nevertheless distinct flow regimes. However, this torrential lava in the new section seems different from the old diamictite. The deposition of the sedimentary units in the West Gallery seemingly happened during a glacial–interglacial transition. This sedimentological study sets a future perspective for dating flowstones and stalagmites at the top of or embedded within the deposit levels in order to propose a more robust chronological frame for the evolution dynamics of the cave infilling of the Lorette Cave in relation to the climatic history of the region.

Climate, topography and anthropogenic effects on desert greening: A 40-year satellite monitoring in the Tengger desert, northern China

Vegetation is usually sparse in the desert regions, but it plays important roles in stabilizing sand dunes and combating desertification. Establishing how desert vegetation responds to changes in both natural forcing and anthropogenic interference is essential for better understanding desertification processes and their future dynamics. In this study, a comprehensive analysis of NDVI time series data in combination with climate reanalysis data and topographic data was conducted to investigate the possible effects of different external factors on desert vegetation in the Tengger desert, one of the largest deserts in northern China. The results show that vegetation is mostly distributed near the desert margins and in the interdune areas with relatively low and flat topography. Multiple NDVI datasets indicate a consistently greening trend over the entire desert during the last forty years, and the greening rates are higher at sites with sand fixation and vegetation restoration practices. After a few decades of restoration practices, vegetation greenness in these sites is approaching their natural states, but they still show large interannual variability associated with precipitation fluctuations. Therefore, the greening trend of the entire desert could be related to recent climate change towards wetter, warmer and less windy conditions, while human efforts have accelerated the rate of vegetation recovery in the restoration sites. Our study implies that the present climate change has produced conditions favorable for continued vegetation increase in the drylands of northern China, and this trend has been facilitated by policy-driven restoration projects. The combined effects of climate change, topography and human interference on desert vegetation should be considered in future restoration practices.