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To study the influence of vegetation on shadow extraction, an anti-interference DCNN was developed to extract shadows and vegetation from QuickBird images. The vegetation features, color and geometric information were analyzed qualitatively and quantitatively, and the regression equation of shadow extraction accuracy was obtained. We got that the average brightness value of vegetation in R and G band and the standard deviation of brightness in G band are significantly negatively correlated with the recall rate of shadow extraction, P>0.05;and the standard deviation of the inner edge ratio of vegetation boundary complexity is significantly positively correlated with the recall rate. [ABSTRACT FROM AUTHOR]

Fire plays a pivotal role in driving ecological shifts between Mediterranean‐type vegetation and subtropical ecosystems in South Africa. This study investigates long‐term environmental dynamics and ecological regime changes at the Mediterranean‐type vegetation /subtropical boundary using a 6000‐year palaeoecological sequence from the Baviaanskloof – a region of South Africa characterized by high levels of biodiversity and climate dynamism. Combining fossil pollen and microcharcoal data from a rock hyrax Procavia capensis midden, we analyse vegetation responses to environmental changes. Our findings reveal that Mediterranean‐type vegetation resilience prevailed until ca 2800 cal year BP when a major fire event triggered a transition to a subtropical thicket‐dominated environment. This abrupt ecological turnover underscores the significance of fire as a major driver of vegetation change at the Mediterranean‐type vegetation /subtropical boundary. Our study emphasizes the vulnerability of Mediterranean‐type vegetation ecosystems to global environmental change, suggesting potential implications for similar biome boundaries worldwide. By integrating multi‐proxy palaeoecological evidence, we gain insights into the resilience and vulnerability of these ecosystems, aiding in understanding future responses to climate change scenarios. [ABSTRACT FROM AUTHOR]

Altered fire regimes, combined with a warmer and drier climate, have been eroding the resilience of temperate rainforests and peatlands worldwide and leading to alternative post-fire vegetation communities. Chronic anthropogenic burning of temperate rainforests at the forest-peatland ecotone in western Patagonia appears to have shifted vegetation communities in poorly-drained sites from forests dominated by the threatened conifer, Pilgerodendron uviferum, to peat-accumulating wetlands covered by Sphagnum mosses. We collected and modeled post-reburn field data using ordinations and hierarchical Bayesian regressions to examine mechanisms through which P. uviferum forests may recover following fire or become locked into alternative development pathways by comparing biophysical factors of a reburned ecotone to those of an unburned (control) ecotone. We found that, (1) the significantly higher densities of P. uviferum trees and seedlings in the forested patches at both the reburned and control sites were associated with significantly lower seasonal water tables, lower cover of Sphagnum mosses and higher cover of other mosses (i.e., not in the Sphagnum or Dicranaloma genera); (2) despite abrupt boundaries in vegetation at both sites, successive fires homogenized the environment at the reburned site; and (3) the distinct life forms and individual species that characterized the understory plant communities across the ecotones affected seedling abundance by shaping microtopography and the substrates available for establishment. Together, our results suggest that fire can push edaphically wet P. uviferum-dominated sites towards a non-forested state by reducing the diversity of microsite structure and composition, thereby placing P. uviferum seedlings in direct competition with Sphagnum mosses and potentially limiting the availability of microsites that are protected from both seasonal inundation and seasonal drought. If wildfires continue under increasingly warmer and drier conditions, the forestpeatland ecotone of western Patagonia may be susceptible to large-scale transformation towards a non-forested state. [ABSTRACT FROM AUTHOR]

Coal mining in regions characterized by high groundwater table markedly predisposes to surface subsidence and water accumulation, thereby engendering substantial harm to surface vegetation, soil, and hydrological resources. Developing effective methods to extract surface disturbance information aids in quantitatively assessing the comprehensive impacts of coal mining on land, ecology, and society. Due to the shortcomings of traditional indicators in reflecting mining disturbance, vegetation aboveground biomass (AGB) is introduced as the primary indicator for extracting the mining disturbance range. Taking the Huaibei Coal Base as an example, Sentinel-2 MSI imagery is firstly used to calculate spectral factors and vegetation indices. Multiple machine learning algorithms are coupled to perform remote sensing estimation and spatial inversion of vegetation AGB based on measured samples of vegetation AGB. Secondly, an Orientation Distance-AGB (OD-AGB) curve is constructed outward from the center of subsidence water areas (SWA), with the Boltzmann function used for curve fitting. According to the location of the inflection point of the curve, the boundary points of vegetation disturbance are identified, and then the disturbance range is divided. The results show that (1) the TV-SVM model, utilizing total variables and support vector machine, achieves the highest estimation accuracy, with σMAE and σRMSE values of 208.47 g/m2 and 290.19 g/m2, respectively, for the validation set. (2) Thirty-six effective disturbance areas, totaling 29.89 km2, are identified; the Boltzmann function provides a good fit for the OD-AGB curve, with an R2 exceeding 0.8 for typical disturbance areas. (3) Analysis of general statistical laws indicates that disturbance distance conforms to the general characteristics of normal distribution, exhibiting boundedness and directional heterogeneity. The research is expected to provide scientific guidance for hierarchical zoning management, land reclamation, and ecological restoration in coal mining areas with high groundwater table. [ABSTRACT FROM AUTHOR]

Public satellite platforms offer regular observations for global coastal monitoring and climate change risk management strategies. Unfortunately, shoreline positions derived from satellite imagery, representing changes in intertidal topography, are noisy and subject to tidal bias that requires correction. The seaward‐most vegetation boundary reflects a change indicator which shifts on event–decadal timescales, and informs coastal practitioners of storm damage, sediment availability and coastal landform health. We present and validate a new open‐source tool VedgeSat for identifying vegetation edges (VEs) from high (3 m) and moderate (10–30 m) resolution satellite imagery. The methodology is based on the CoastSat toolkit, with streamlined image processing using cloud‐based data management via Google Earth Engine. Images are classified using a newly trained vegetation‐specific neural network, and VEs are extracted at subpixel level using dynamic Weighted Peaks thresholding. We performed validation against ground surveys and manual digitisation of aerial imagery across eroding and accreting open coasts and estuarine environments at a site in Scotland. Smaller‐than‐pixel vegetation boundary detection was achieved across 83% of Sentinel‐2 imagery (Root Mean Square Error of 9.3 m). An overall RMSE of 19.0 m was achieved across Landsat 5 & 8, Sentinel‐2 and PlanetScope images. Performance varied by coastal geomorphology, with highest accuracies across sandy open coasts owing to high spectral contrast and less false positives from intertidal vegetation. The VedgeSat tool can be readily applied in tandem with waterlines near‐globally, to support adaptation decisions with historic coastal trends across the whole shoreface, even in normally data‐scarce areas. [ABSTRACT FROM AUTHOR]

Cities play a crucial role in the carbon cycle. Measuring urban aboveground biomass (AGB) is essential for evaluating carbon sequestration. Satellite remote sensing enables large-scale AGB inversion. However, the apparent differences between forest and grassland biomass pose a significant challenge to the accurate estimation of urban AGB using satellite-based data. To address this limitation, this study proposed a novel AGB estimation method using the eastern part of the Zhahe mining area in Huaibei City as the study area, which integrates land cover classification, feature selection, and machine learning modelling to generate high quality biomass maps of different vegetation types in an urban area with complex feature distribution. Utilizing the GEE platform and Sentinel-2 image, we developed an object-oriented machine learning classification algorithm, combining SNIC and GLCM to extract vegetation information. Optimal feature variables for forest and crop-grass AGB inversion were selected using the Pearson–mRMR algorithm. Finally, we constructed nine machine learning models for AGB inversion and selected the model with the highest accuracy to generate the AGB map of the study area. The results of the study are as follows: (1) Compared with the pixel-based classification method, the object-oriented classification method can extract the boundaries of different vegetation types more accurately. (2) Forest AGB is strongly correlated with vegetation indices and physiological parameters, while agri-grass AGB is primarily associated with vegetation indices and vegetation physiological parameters. (3) For forest AGB modelling, the RF-R model outperforms other machine learning models with an R2 of 0.77. For agri-grass AGB modelling, the XGBoost-R model is more accurate, with an R2 of 0.86. (4) The mean forest AGB in the study area was 4.60 kg/m2, while the mean agri-grass AGB was 0.71 kg/m2. High AGB values were predominantly observed in forested areas, which were mainly distributed along roads, waterways, and mountain ranges. Overall, this study contributes to a better understanding of the health of local urban ecosystems and provides valuable insights for ecosystem protection and the sustainable use of natural resources. [ABSTRACT FROM AUTHOR]

Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by is nowadays seen as a standard approach for classifying any zone according to a set of urban canopy parameters. While many methods already exist to map the LCZ, only few tools are openly and freely available. This paper presents the algorithm implemented in the GeoClimate software to identify the LCZ of any place in the world based on vector data. Six types of information are needed as input: the building footprint, road and rail networks, water, vegetation, and impervious surfaces. First, the territory is partitioned into reference spatial units (RSUs) using the road and rail network, as well as the boundaries of large vegetation and water patches. Then 14 urban canopy parameters are calculated for each RSU. Their values are used to classify each unit to a given LCZ type according to a set of rules. GeoClimate can automatically prepare the inputs and calculate the LCZ for two datasets, namely OpenStreetMap (OSM, available worldwide) and the BD TOPO® v2.2 (BDT, a French dataset produced by the national mapping agency). The LCZ are calculated for 22 French communes using these two datasets in order to evaluate the effect of the dataset on the results. About 55 % of all areas have obtained the same LCZ type, with large differences when differentiating this result by city (from 30 % to 82 %). The agreement is good for large patches of forest and water, as well as for compact mid-rise and open low-rise LCZ types. It is lower for open mid-rise and open high-rise, mainly due to the height underestimation of OSM buildings located in open areas. Through its simplicity of use, GeoClimate has great potential for new collaboration in the LCZ field. The software (and its source code) used to produce the LCZ data is freely available at 10.5281/zenodo.6372337 ; the scripts and data used for the purpose of this article can be freely accessed at 10.5281/zenodo.7687911 and are based on the R package available at 10.5281/zenodo.7646866. [ABSTRACT FROM AUTHOR]

Climate change has induced substantial shifts in vegetation boundaries such as alpine treelines and shrublines, with widespread ecological and climatic influences. However, spatial and temporal changes in the upper elevational limit of alpine grasslands ("alpine grasslines") are still poorly understood due to lack of field observations and remote sensing estimates. In this study, taking the Tibetan Plateau as an example, we propose a novel method for automatically identifying alpine grasslines from multi‐source remote sensing data and determining their positions at 30‐m spatial resolution. We first identified 2895 mountains potentially having alpine grasslines. On each mountain, we identified a narrow area around the upper elevational limit of alpine grasslands where the alpine grassline was potentially located. Then, we used linear discriminant analysis to adaptively generate from Landsat reflectance features a synthetic feature that maximized the difference between vegetated and unvegetated pixels in each of these areas. After that, we designed a graph‐cut algorithm to integrate the advantages of the Otsu and Canny approaches, which was used to determine the precise position of the alpine grassline from the synthetic feature image. Validation against alpine grasslines visually interpreted from a large number of high‐spatial‐resolution images showed a high level of accuracy (R2,.99 and.98; mean absolute error, 22.6 and 36.2 m, vs. drone and PlanetScope images, respectively). Across the Tibetan Plateau, the alpine grassline elevation ranged from 4038 to 5380 m (5th–95th percentile), lower in the northeast and southeast and higher in the southwest. This study provides a method for remotely sensing alpine grasslines for the first‐time at large scale and lays a foundation for investigating their responses to climate change. [ABSTRACT FROM AUTHOR]

Blowouts are integral features of coastal dune fields. Their presence enhances both geomorphological and ecological diversity and enables the movement of sand by wind. Their role as a 'transport corridor' may be, however, considered negative from a coastal management perspective in heavily touristic areas, where the existence of blowouts close to the foredune can enhance the loss of sediment from the beach. This paper investigated the relationship between airflow dynamics and patterns of sediment transport from the beach to established dunes through a trough blowout located on the foredune. Seven three-cup anemometers were used to measure wind speed and direction over a 24 h sampling period at a frequency of 1 min under onshore (parallel to the blowout axis) medium and high wind speeds (max of 17.9 ms−1). To measure sediment transport, a total of 12 vertical sand traps were located at three positions along the length of the deflation basin. The results indicated that small amounts of sediments went into the blowout from the beach and that the highest rates of sediment remobilization took place within the deflation basin. These results highlight two processes: (a) flow channelization induced by the blowout topography caused an increase in wind speed and sediment transport toward the depositional lobe, and (b) the presence of embryo dunes and herbaceous vegetation at the beach–blowout boundary effectively reduced the amount of sediment transport from the beach to the landform. The results confirmed the significant role that vegetation plays in controlling sediment movement and conserving the beach–dune system. [ABSTRACT FROM AUTHOR]

Aim: The global relationship between treeline elevation and temperature (or latitude as a proxy) is well established. However, additional large‐scale and regional abiotic influences such as mass elevation effect (MEE), continentality and isolation are superimposed onto the latitude‐treeline relationship. To quantify these effects, we apply globally applicable measures and test the effects of MEE, an aspect of continental climate and isolation on treeline elevation. Location: Global treeline elevations (n = 629). Methods: We sampled treeline sites using earth observation. We calculated MEE as the distance to the nearest mountain chain limits. Continentality was assessed by the distance to the nearest coastline. Isolation was calculated by the nearest distance of a mountain chain to another mountain chain within a comparable elevational band. Results: The global latitudinal pattern showed a distinct bimodal latitude‐treeline elevation relationship. Treeline elevations increased substantially with increased MEE and distance to coastlines while isolation even decreased treeline elevations. Main Conclusions: Our study shows a globally consistent effect of MEE and distance to the coastline on treeline elevation, contributing to our basic understanding of large‐scale biogeographic processes governing treeline formation. MEE and continentality reduce cloudiness and increase solar radiation, resulting in higher treeline elevations. Isolation effects are not consistent and may be influenced by immigration and speciation. Understanding global treeline formation using comprehensive measures contributes to a better understanding of how environmental conditions determine vegetation boundaries at large spatial scales. [ABSTRACT FROM AUTHOR]

Precipitation patterns and their variations over the Tibetan Plateau (TP) are mainly dominated by the Asian summer monsoon, westerlies, and their interactions. The exact extent of the Asian summer monsoon's influence, however, remains undetermined. Referencing the climatological northern boundary index of the East Asian summer monsoon, we demonstrate that the 300 mm precipitation isoline from May to September can be utilized as an indicator of the northern boundary of the Asian summer monsoon over the TP, allowing for an analysis of the spatial distribution characteristics of the climatological and interannual northern boundary. Our results indicate that the climatological northern boundary of the Asian summer monsoon over the TP lies along the eastern Qilian Mountains-Tanggula Mountains-Qiangtang Plateau-Gangdise Mountains-Western Himalayas during 2001–2020. This position corresponds well with the position of the convergence of westerly (westerlies) and southerly wind (monsoon) in the lower troposphere, representing the interface between dry and wet regions in the rainy season over the TP. There is a significant positive correlation between changes in the zonal/meridional water vapor budget and variations in precipitation to the north/south of the climatological northern boundary, respectively. Additionally, a close relationship exists between the interannual fluctuation range of the northern boundary and the distribution of vegetation across the TP. Compared to the northern boundary of the summer monsoon defined by meteorological criteria, which is established based on 5-day (pentad) mean precipitation (exceeding 4 mm day−1), our climatological northern boundary offers a more objective portrayal of the region that experiences persistent influence from the summer monsoon. These indicate that climatological northern boundary has a clear significance for natural geographical distribution such as the westerlies-monsoon circulation, ecology, and climate. Based on the interannual fluctuation range of the northern boundary, we divided the TP into domains of westerlies, monsoon, and westerlies-monsoon transition. This study could serve as a foundation for further investigation into the interactions between westerlies and monsoon, variations in precipitation patterns and hydrological-ecological systems over the TP. [ABSTRACT FROM AUTHOR]

Geographical features may have a considerable effect on local climate. The Local Climate Zone (LCZ) system proposed by Stewart and Oke (2012) is nowadays seen as a standard referential to classify any zone according to a set of urban canopy parameters. While many methods already exist to map the LCZ, only few tools are openly and freely available. This manuscript presents the algorithm implemented in the GeoClimate software to identify the LCZ of any place in the world based on vector data. Seven types of information are needed as input: building footprint, road and rail networks, water, vegetation and impervious surfaces. First the territory is partitioned into Reference Spatial Units (RSU) using the road and rail network as well as the boundaries of large vegetation and water patches. Then 14 urban canopy parameters are calculated for each RSU. Their values are used to classify each unit to a given LCZ type according to a set of rules. GeoClimate can automatically prepare the inputs and calculate the LCZ for two datasets: OpenStreetMap (OSM - available worldwide) and the BD Topo v2.2 (BDT - a French dataset produced by the national mapping agency). The LCZ are calculated for 22 French communes using these two datasets in order to evaluate the effect of the dataset on the results. About 55 % of all areas has obtained the same LCZ type with large differences when differentiating this result by city (from 30 % to 82 %). The agreement is good for large patches of forest and water as well as for compact mid-rise and open low-rise LCZ types. It is lower for open mid-rise , open high-rise mainly due to height underestimation for OSM buildings located in open areas. By its simplicity of use, Geoclimate has a great potential for new collaboration in the LCZ field. The software (and its source code) used to produce the LCZ data is freely available at https://zenodo.org/record/6372337 , the scripts and data used for the purpose of this manuscript can be freely accessed at https://zenodo.org/record/7687911 and are based on the R package available at https://zenodo.org/record/7646866. [ABSTRACT FROM AUTHOR]

The morphology and variation of braided channel at the confluence reach of Yarlung Tsangpo River (YTR) and Niyang River are affected by the inflow of Niyang River, valley boundary and vegetation conditions. The spatiotemporal variation and complexity of of the braided river are of importance to further study. The remote sensing images from 1986 to 2021 were used to extract the morphological features of braided channels, sandbar and vegetation (channel migration rate, sinuosity, area, et al). We further analyze the morphological characteristics and evolution processes of complex braided channels. The results show that maximum migration rate of the main channel is 483 m/a, the sinuosity reduces by 3. 43%, and the vegetation cover area increases up to 8. 05 km². Owing to the difference of boundary conditions and hydrological conditions, the main channel of the Milin-Paizhen reach oscillates laterally before the Niyang River flows into the YRT, and migrates laterally and longitudinally after Niyang River flows into the channel. Since 2013, 11. 8% of the vegetation coverage in the river channel has a positive feedback of erosion inhibition and deposition promotion, and enhanced the stability of the sandbars. [ABSTRACT FROM AUTHOR]

It is a challenge to scale‐up from simplified proxies to ecosystem functioning since the inherent complexity of natural ecosystems hinders such an approach. One way to address this complexity is to track ecosystem processes through the lens of plant functional traits. Elevational gradients with diverse biotic and abiotic conditions offer ideal settings for inferring functional trait responses to environmental gradients globally. However, most studies have focused on differences in mean trait values among species, and little is known on how intraspecific traits vary along wide elevational gradients and how this variability reflects ecosystem productivity.We measured functional traits of the sub‐shrub Koenigia mollis (Basionym: Polygonum molle; a widespread species) in 11 populations along a wide elevational gradient (1515–4216 m) considering from subtropical forest to alpine treeline in the central Himalayas. After measuring different traits (plant height, specific leaf area, leaf area, length of flowering branches, leaf carbon isotope (δ13C), leaf carbon and leaf nitrogen concentrations), we investigated drivers on changes of these traits and also characterized their relationships with elevation, climate and ecosystem productivity.All trait values decreased with increasing elevation, except for δ13C that increased upwards. Likewise, most traits showed strong positive relationships with potential evapotranspiration, while δ13C exhibited a negative relationship. In this context, elevation‐dependent water–energy dynamics is the primary driver of trait variations. Furthermore, six key traits (plant height, length of flowering branch, specific leaf area, leaf carbon, leaf nitrogen and leaf δ13C) explained 90.45% of the variance in ecosystem productivity.Our study evidences how elevation‐dependent climate variations affect ecosystem processes and functions. Intraspecific variability in leaf functional traits is strongly driven by changes in water–energy dynamics, and reflects changes in ecosystem productivity over elevation. K. mollis, with one of the widest elevational gradients known to date, could be a model species to infer functional trait responses to environmental gradients globally. As inferred from K. mollis, the water–energy dynamics can be a hydrothermal variable to understand the formation of vegetation boundaries, such as alpine treeline. This study sheds new insight on how plants modify their basic ecological strategies to cope with changing environments. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) integrate previously separate models of the ocean, atmosphere and vegetation into one comprehensive modelling system enabling the investigation of interactions between different components of the Earth system. Global isoprene and monoterpene emissions from terrestrial vegetation, which represent the most important source of volatile organic compounds (VOCs) in the Earth system, need to be included in global and regional chemical transport models given their major chemical impacts on the atmosphere. Due to the feedback of vegetation activity involving interactions with weather and climate, a coupled modelling system between vegetation and atmospheric chemistry is recommended to address the fate of biogenic volatile organic compounds (BVOCs). In this work, further development in linking LPJ-GUESS, a global dynamic vegetation model, to the atmospheric-chemistry-enabled atmosphere–ocean general circulation model EMAC is presented. New parameterisations are included to calculate the foliar density and leaf area density (LAD) distribution from LPJ-GUESS information. The new vegetation parameters are combined with existing LPJ-GUESS output (i.e. leaf area index and cover fractions) and used in empirically based BVOC modules in EMAC. Estimates of terrestrial BVOC emissions from EMAC's submodels ONEMIS and MEGAN are evaluated using (1) prescribed climatological vegetation boundary conditions at the land–atmosphere interface and (2) dynamic vegetation states calculated in LPJ-GUESS (replacing the "offline" vegetation inputs). LPJ-GUESS-driven global emission estimates for isoprene and monoterpenes from the submodel ONEMIS were 546 and 102 Tg yr -1 , respectively. MEGAN determines 657 and 55 Tg of isoprene and monoterpene emissions annually. The new vegetation-sensitive BVOC fluxes in EMAC are in good agreement with emissions from the semi-process-based module in LPJ-GUESS. The new coupled system is used to evaluate the temperature and vegetation sensitivity of BVOC fluxes in doubling CO 2 scenarios. This work provides evidence that the new coupled model yields suitable estimates for global BVOC emissions that are responsive to vegetation dynamics. It is concluded that the proposed model set-up is useful for studying land–biosphere–atmosphere interactions in the Earth system. [ABSTRACT FROM AUTHOR]

The study was conducted in south-eastern Poland, in three apple orchards where integrated pest management was applied, and in one ecological orchard and in their surroundings. In total, 1,677 individuals of Syrphidae belonging to 37 species, 21 genera, and two subfamilies were collected in the yellow traps. The most numerous were zoophagous syrphids - they constituted 94.5% of all the collected specimens and about 70% of the noted species. Among them, one species - Episyrphus balteatus (Deg.) - was the eudominant in the orchards and their surroundings. Comparing the occurrence of Syrphidae in the three IPM apple orchards and in their surroundings, it can be stated that more syrphids were caught in the boundary vegetation than within the orchards, whereas on the ecological site, more hoverflies were collected within the apple orchard than on the neigbouring plants. In most cases, in the orchard under IPM the syrphid species abundant in the surroundings of the orchards also appeared in great numbers in the orchards themselves, which indicated their movement from the boundaries into the orchards. The study has shown that the surroundings of orchards with species-rich, flowering plants positively influenced the species richness and the abundance of hoverflies occurring in the orchards. [ABSTRACT FROM AUTHOR]

Arthropods at high latitudes and elevations are likely to be vulnerable to effects from climate change such as increased temperatures and shifting vegetation boundaries. Though range shifts northwards and upslope have been reported for many arthropod taxa in temperate latitudes, baseline data needed to track such changes are scarce at northern latitudes. We investigated the influence of climate and vegetation cover on the abundance, diversity, and species composition of pollinators and epigeic arthropods along an elevation gradient in Denali National Park and Preserve, Alaska. We compared arthropods across three habitat types: low-elevation forest, mid-elevation shrubs, and high-elevation tundra along five replicate transects over three years. We collected 35,473 arthropods representing 510 species. Arthropod communities differed distinctly across the three habitat types, with tundra having the highest number of strong indicators and unique species. Elevation, air temperature, and vegetation structure were strong drivers for the ordination of sites. As treeline and shrubline shift upslope with climate change, we predict that distributions of some arthropods will shift to track these habitat boundaries and that tundra-associated arthropods will be most vulnerable as their habitat shrinks. Long-term monitoring of arthropods along elevation gradients at northern latitudes is needed to detect such declines. [ABSTRACT FROM AUTHOR]

• Steppe vegetation migrated towards more arid regions over the past 20 years. • Precipitation improvement was the main driver for the steppe zone migration. • Human activities were not significant drivers for vegetation boundary shift. • Woody desert and forest vegetation hardly shifted under climate change. Vegetation is sensitive to climate changes. Many studies have been done on the boundary transition of vegetation types in response to climate changes along elevation gradient in mountain areas, but less on the boundary transition of zonal vegetation types in vast plain areas. The forest, meadow steppe, typical steppe, desert steppe, and desert vegetation are successively distributed on the 2400 km long transect with climate aridity increasing from the northeast to the southwest in Inner Mongolia. While the climate change impacts on vegetation functions have been assessed, no information is available on if these vegetation types migrate under climate changes. Based on MODIS and Landsat remote sensing data and vegetation type partition data, we first used the random forest classification method to derive the spatiotemporal distribution of these five vegetation types in Inner Mongolia for the period from 2001 to 2020. Then we explored the boundary transitions between the successively distributed vegetation types, and elucidated the causes of the boundary transitions using partial correlation and Spearman's rank correlation analyses between the NDVI and climate data (temperature and precipitation). We found a general and gradual migration of steppe vegetation towards drier area along climatic gradient. Notably, meadow steppe shifted approximately 11,396 km2 into the original typical steppe areas, and desert steppe shifted approximately 22,548 km2 into the original desert areas. This boundary shift phenomenon was primarily influenced by the increase in growing season precipitation over the 20-year period. Our study provides the evidence for the migration of vegetation types along climate gradients in response to climate changes, and provides a method for analyzing vegetation transitions under environmental changes. [ABSTRACT FROM AUTHOR]

Natural phenomena boundaries and complexity of features in an urban area due to the low spatial resolution, lead to more pixels of satellite images included in reflectance of multiple land-cover/object components. The sub-pixel information extracting model outputs are fractional cover maps of interested class (end-member), with membership values between zero and one. These maps represented gradient change in only one fuzzy phenomenon boundaries such as vegetation cover. However, in multiple fuzzy class area or complex fuzzy phenomena such as mangrove forests, in the northwest of the Qeshm Island, Hormozgan, Iran, displaying several fractional covers may cause confusion and misunderstanding for the end-user. In this study, an additive color composite and spectral mixture analysis method is utilized for multiple fractional cover representation. The proposed method is implemented on images acquired from Operational Land Imager (OLI) sensor in the Landsat 8 satellite to extract three fractional covers (water, vegetation, and soil). An RGB color composite was used for each type and percentage of fractional cover for given pixel to display fractional cover separately. Based on such RGB color composite represented both quantitative and qualitative information, we used the RGB color solid cube as map legend for better understanding and map interpretation. The result of this study showed that suggested sub-pixel visualization method, gives new vision to the end-user understanding of fuzzy phenomena. [ABSTRACT FROM AUTHOR]

This study examined synoptic impacts on the occurrence of boundaries and their associated convection during summers from 2012 to 2016 over Hetao Irrigation District in North China, where there is a sharp vegetation contrast. Objective synoptic‐pattern classification showed that boundary days, especially convective boundary days, were more frequent under a mid‐troposphere high‐pressure ridge or pre‐trough pattern. Such patterns featured a warmer near‐surface environment, stronger southerly winds, larger convective available potential energy (CAPE), and low‐level moisture convergence. Relative to unfavorable patterns, boundaries under favorable patterns showed more apparent arid‐area dependence, more dominant orientation along the line of vegetation contrast, more moved northward, formed and matured earlier, and triggered convection more dispersedly. Under each pattern, compared with nonboundary days, boundary days possessed higher near‐surface temperatures and stronger ambient flows against the vegetation‐contrast‐induced circulations near the surface; plus, compared with nonconvective boundary days, convective boundary days possessed stronger updrafts, larger CAPE, and higher moisture and K index. Plain Language Summary: Boundary layer convergence lines (boundaries), which often manifest as fine lines of clear‐air radar echoes, are an important mesoscale mechanism of convective initiation. Mesoscale boundaries induced by vegetation heterogeneity are far less well understood than those induced by the contrast between sea or lakes and land, particularly in terms of synoptic impacts on the occurrence of such boundaries and their associated convection. Based on a boundary data set during the five summers from 2012 to 2016 over Hetao Irrigation District (HID)—an area in North China with a sharp contrast in vegetation, mainly between desert and irrigation areas—the aim of the present study was to link these boundaries and their associated convection with different synoptic features via objective synoptic‐pattern classification. Results showed that the boundaries were more likely to occur and trigger convection on days when HID was under a high‐pressure ridge or pre‐trough pattern. The favorable patterns had a warmer environment with stronger southerly flows for boundaries to develop, along with larger convective available potential energy and moisture convergence for boundaries to trigger convection. Their associated boundaries showed more apparent arid‐area dependence, more dominant orientation along the vegetation interface, more northward movements, earlier formation and maturity, and more dispersed convection initiation timing. Key Points: Boundaries and their convection over Hetao Irrigation District prefer mid‐level high‐pressure‐ridge or pre‐trough synoptic patternsThe favorable patterns have a warmer boundary layer with more frequent southerly flows, larger CAPE, and stronger moisture convergenceInstability and moisture effectively distinguish convective from nonconvective boundary days but not boundary from nonboundary days [ABSTRACT FROM AUTHOR]

The mixing-layer analogy is due to Raupach, Finnigan & Brunet (Boundary-Layer Meteorol., vol. 25, 1996, pp. 351382). In the analogy, the flow in the roughness sublayer of a homogeneous deep vegetation canopy boundary layer is analogous to a plane mixing layer rather than a surface layer. Evidence for the analogy includes the inflected velocity profile, which resembles the velocity profile in a plane mixing layer, and, most notably, the following estimate as a result of the Kelvin--Helmholtz instability:Λx = 8.1Ls, where Λx is the spacing of the large-scale eddies, and Ls is the shear length. The mixing-layer analogy has been very successful in vegetation canopy flow research, but has received only limited support in urban-canopy flow research. This work revisits Raupach et al.'s mixing-layer analogy, and we present the evidence for the mixing-layer analogy in urban-canopy flows: the exponential velocity profile in the canopy layer, i.e. (U -- Uc)/(Uh -- Uc) = exp(z/Lm), and Lm ~ [(Uh/Uc -- 1)(Uh/Uc + 3)]-1. Here, z is the vertical coordinate, Lm is the attenuation length and is a measure of the largest eddy in the canopy layer, Uh is the wind speed at the canopy crest and Uc is the velocity in the inactive layer. We conduct direct numerical simulations of various deep homogeneous urban-canopy flows and test the above two scalings. We also discuss why Raupach et al.'s analogy has not seen as many successes in urban-canopy flows as in vegetation canopy flows. [ABSTRACT FROM AUTHOR]

Based on remote sensing and tree-ring chronology data, the ecological state of the extrazonal sparse larch forest in the Mongayurbey River valley (Taz Peninsula) has been studied. This area is one of the northernmost enclaves of taiga vegetation in Western Siberia. An analysis of Terra-MODIS satellite images from 2000 to 2020 shows that the value of the normalized difference vegetation index (NDVImean), which reflects the average amount of photosynthetically active phytomass for the summer period, most strongly depends on air temperature (correlation coefficient R = 0.69). However, despite the steady trend towards an increase in the avarage annual summer temperatures, no statistically significant trend in the vegetation index is found, which is due to the inertness of the shrub–moss–lichen ground cover. An analysis of the relationship between the maximum normalized difference vegetation index NDVImax and the absolute tree ring width (TRW) in Larix sibirica Ledeb. shows a strong correlation (R = 0.72) in the marginal, near-watershed area, where a young forest stand with the highest crown density and abundant undergrowth is located. In the valley areas, conversely, forest-stand digression associated with the deterioration of natural conditions is seen (changes in drainage, soil characteristics, and permafrost-geochemical conditions). With continued warming, the spread of the larch forest from the river floodplain to the watershed can be expected, which confirms the current shift of the forest vegetation boundary to the north. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) integrate previously separate models of the ocean, atmosphere and vegetation in one comprehensive modelling system enabling the investigation of interactions between different components of the Earth system. Global isoprene and monoterpene emissions from terrestrial vegetation, which represents the most important source of VOCs in the Earth system, need to be included in global and regional chemical transport models given their major chemical impacts on the atmosphere. Due to the feedbacks of vegetation activity involving interactions with the weather and climate, a coupled modelling system between vegetation and atmospheric chemistry is a recommended tool to address the fate of biogenic volatile organic compounds (BVOCs). In this work, we present further development in linking LPJ-GUESS, a global dynamic vegetation model, to the atmospheric chemistry-enabled atmosphere-ocean general circulation model EMAC. We evaluate ter10 restrial BVOC emission estimates from the submodels ONEMIS and MEGAN in EMAC with (1) prescribed climatological vegetation boundary conditions at the land-atmosphere interface; and (2) dynamic vegetation states calculated in LPJ-GUESS (replacing the "offline" vegetation inputs). LPJ-GUESS-driven global emission estimates for isoprene and monoterpenes from the submodel ONEMIS were found to be 546 Tg yr-1 and 102 Tg yr-1, respectively. MEGAN prescribed 657 Tg and 55 Tg of isoprene and monoterpene emissions annually. We also evaluated the sensitivity of the new coupled system in doubling CO2 scenarios. This work provides evidence that the new coupled model yields suitable estimates for global BVOC emissions that are responsive to vegetation dynamics. We conclude that the proposed model setup is a useful tool for studying land-biosphere-atmosphere interactions in the Earth system. [ABSTRACT FROM AUTHOR]

Vegetation detection aims to find the area which should be attributed with the labels of vegetation on the captured images, such as forest, grass land etc., and nowadays it is a key research topic in the field of remote sensing information processing and application. Over the last few years, the deep learning method based on convolutional neural network (CNN) has become the mainstream method for vegetation detection. However, due to the peculiarities of the underlying encoding and decoding structures, it is common for some CNN methods to loss some boundary details of vegetation when employing high-resolution images with rich details and clear boundaries. In order to improve the boundary localization capability of vegetation, this paper proposes a hybrid solution, i.e., an MLP (MultiLayer Perceptron)-based high-resolution image adaptive superpixels vegetation detection method. Compared with the traditional watershed transform algorithm, this method adopts the two-step boundary marching criterion to generate superpixels with more adherent boundary and compact regularity which contains adaptive neighborhood information by design. Based on the generated superpixels with boundary detail information, this paper applies MLP for binary predictions, i.e., vegetation or non-vegetation. The experimental results show that our method has more precise vegetation boundary localization and higher accuracy compared with several state-of-the-art methods on the UAV image data set and ISPRS data set. [ABSTRACT FROM AUTHOR]

[Display omitted] • An overview of progress in aeolian landform dynamics utilizing CFD are reviewed. • Turbulence and particle motion modeling techniques promote sand transport simulation. • Key factors of simulation are wind regimes, surface roughness and bedform morphology. • CFD has advantages in controlled, accessible, visualized, and detailed simulation. • Three topics are proposed for future CFD researches on aeolian landforms dynamics. Relationships and feedback between airflow dynamics, sand transport and underlying surface characteristics play significant roles in the formation and evolution of aeolian landforms. Studies that apply Computational Fluid Dynamics (CFD) modeling have increasingly provided insights into the influence of wind dynamics and characteristics of wind-blown sand. However, there is a lack of systematic review on modeling airflow and sand transport over aeolian landforms. This paper reviews 105 relevant CFD studies from the literature up to 2023 and summarizes methods of modeling airflow and sand transport. Additionally, it reviews their implementations of these methods and findings on how wind regimes and underlying surface characteristics, including surface roughness conditions and bedform morphology, affect wind dynamics and the behavior of wind-blown sand. This review aims to provide a comprehensive review of CFD modeling methods and their application to better understand the utilization of CFD simulations of aeolian landforms. CFD approach provides a valuable alternative to study related filed in a controlled, accessible, visualized, and detailed manner. We conclude this review by recommending three topics for future research to improve the accuracy of modeling and promote applications of CFD to aeolian landforms, i.e., modeling critical and comprehensive turbulent flow, developing robust and accurate models of particle motion, and investigating the effects of vegetation and boundary layers. [ABSTRACT FROM AUTHOR]

• Weathered bedrock layers improved profile water storage and conservation. • Rock moisture alleviated upper soil moisture deficiency and desiccation. • Deep-rooted plants modified soil and rock moisture spatiotemporal distribution. • Rock moisture increased vegetation available water under scarcity condition. Rock moisture is rarely deliberated but crucial for hydrologic regulation in semiarid loess hilly regions. In this study, using in-situ monitoring observation and simulation, soil and rock moisture spatiotemporal variations under planting alfalfa and caragana were analyzed and sketched, and the water storage contributions by weathered bedrock layers (WBLs) under different rainwater scenarios were then simulated and estimated. The results showed that WBLs had apparent spatiotemporal changes in water distribution and storage with rainfall events. Under water scarcity scenarios, WBLs increased the variabilities of water storage, with an average increase of 89.9 % in alfalfa and 14.2 % in caragana, providing wider water supply boundaries for vegetation. However, higher volumetric water content was presented under relatively abundant water scenarios. The average soil water content was 0.08 cm3 cm−3 in alfalfa and 0.09 cm3 cm−3 in caragana, while the average rock water content was 0.12 cm3 cm−3 in alfalfa and 0.13 cm3 cm−3 in caragana. Profile water consumption goes to surface soil evaporation and plant transpiration over an entire growing season, while extrawater would be stored in WBLs to maintain vegetation growth during the water-scarce seasons. Moreover, water storage had a positive linear relationship with the thickness of WBLs. Rock water storage increased by 6.9 % in alfalfa and 3.7 % in caragana after adding 20 cm WBLs, while it increased by 23.6 % in alfalfa and 9.9 % in caragana after adding 50 cm WBLs. Furthermore, various exogenous rainwater simulations showed that differences in water storage were significantly increased with WBLs thickness. This study would provide new insights into the deep-rooted plant distribution planning in semiarid loess hilly regions, and could also be helpful for the rational water resources utilization and management in shallow soil areas. [ABSTRACT FROM AUTHOR]

The large area estimation of forest canopy closure (FCC) using remotely sensed data is of high interest in monitoring forest changes and forest health, as well as in assessing forest ecological services. The accurate estimation of FCC over the regional or global scale is challenging due to the difficulty of sample acquisition and the slow processing efficiency of large amounts of remote sensing data. To address this issue, we developed a novel bounding envelope methodology based on vegetation indices (BEVIs) for determining vegetation and bare soil endmembers using the normalized differences vegetation index (NDVI), modified bare soil index (MBSI), and bare soil index (BSI) derived from Landsat 8 OLI and Sentinel-2 image within the Google Earth Engine (GEE) platform, then combined the NDVI with the dimidiate pixel model (DPM), one of the most commonly used spectral-based unmixing methods, to map the FCC distribution over an area of more than 90,000 km2. The key processing was the determination of the threshold parameter in BEVIs that characterizes the spectral boundary of vegetation and soil endmembers. The results demonstrated that when the threshold equals 0.1, the extraction accuracy of vegetation and bare soil endmembers is the highest with the threshold range given as (0, 0.3), and the estimated spatial distribution of FCC using both Landsat 8 and Sentinel-2 images were consistent, that is, the area with high canopy density was mainly distributed in the western mountainous region of Chifeng city. The verification was carried out using independent field plots. The proposed approach yielded reliable results when the Landsat 8 data were used (R2 = 0.6, RMSE = 0.13, and 1-rRMSE = 80%), and the accuracy was further improved using Sentinel-2 images with higher spatial resolution (R2 = 0.81, RMSE = 0.09, and 1-rRMSE = 86%). The findings demonstrate that the proposed method is portable among sensors with similar spectral wavebands, and can assist in mapping FCC at a regional scale while using multispectral satellite imagery. [ABSTRACT FROM AUTHOR]

Fragments of birch (Betula pubescens ssp. tortuosa (Ledeb.) Nyman) and spruce (Picea obovata Ledeb.) trunks with traces of gnawing by the Eurasian beaver (Castor fiber Linnaeus, 1758) were found in the modern tundra zone on the Yamal Peninsula. Tree fragments were dated by the radiocarbon and tree-ring methods. At the beginning of the Middle Holocene, the northern boundary of the beaver's range was at 68°39′ N. At the end of the Middle Holocene, it was at 67°33′ N. At the beginning of the Late Holocene, it was 66°33′ N. Changes of the boundary followed the formation of closed forests on the Yamal Peninsula. As they became established, the beaver's range moved northward. As the woody vegetation boundary retreated to the south, the beaver's range also retreated to the south. Stabilization of the northern boundary of the beaver range took place at the beginning of the Subatlantic climatic stage of the Late Holocene following the stabilization of the southern boundary of the forest–tundra zone. [ABSTRACT FROM AUTHOR]

Coastal wetlands are highly sensitive to changes occurring at the coastline. It is critically important to determine region‐specific projections for these areas due to their specificities and vulnerabilities to climate change. This work aimed to value the impacts of recent climate changes at West Africa Sahara coastland, southern Morocco, at Khnifiss Lagoon. We have applied a combined approach using remote sensing techniques and environmental reconstructions based on high‐resolution analysis of sediment cores, covering the current warm period. Remote sensing highlighted changes to the lagoon inlet, accompanied by a greater meandering character of the tidal channels. As a response, the sediment cores have recorded a predominant vegetation substitution due to changes in the tidal limit, and an increase in organic carbon accumulation was observed. For the current climatology, during positive phases of the North Atlantic Oscillation, winds reaching the coast strengthen in an east‐to‐west direction. In the Khnifiss Lagoon, whose inlet is dominated by the ebb tide, the intensity and direction of the winds on the coast at surface level modifies its connection to the ocean by increasing sediment transport toward the interior of the lagoon. Locally biological responses to wind intensification, and possibly sea‐level rise, exemplify the lagoon sensitivity to large‐scale processes. Coastal vegetated wetlands are considered to be highly dynamic environments. However, we expect a loss of the upper tidal vegetation due to boundary conditions limiting the accommodation space in this arid environment in a possible future scenario of continuously inland tidal line displacement. [ABSTRACT FROM AUTHOR]

The spatiotemporal image fusion technique is regarded as an effective and efficient remedy to blend two or more geometrically registered remote sensing images of the same scene acquired from different sensors into a single image with both high temporal and high spatial resolutions. A number of existing fusion methods developed for generating Landsat-like images from the Moderate Resolution Imaging Spectroradiometer (MODIS) have successfully solved limitations on vegetation dynamics monitoring. However, these methods either treat the weighting parameters as constants or adopt insufficient linear regression coefficients (considering only spatial, temporal or spectral weights), which may contribute to blocky artefacts and dissimilar pixels in the predicted image. In this study, a boundary finding-based vegetation index spatiotemporal fusion model (BESFM) is newly proposed to generate high spatial and high temporal resolutions Enhanced Vegetation Index (EVI) images in homogeneous and heterogeneous regions with rapid vegetation changes. The cloud-free Landsat-8 Operational Land Imager (OLI) and the MODIS (MOD09GA) data acquired from two study sites, located in Queensland and New South Wales and Australia, were selected to evaluate the performance of the proposed method. Compared with the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) and flexible spatiotemporal data fusion (FSDAF), the BESFM outperforms in both visible image quality (reducing the spatial distortion and blocky artefacts in prediction caused by abrupt land cover changes) and quantitative indices (with RSME minimum to 0.011 and R2 maximum to 0.956). Since the BESFM method not only uses adjustable linear regression assumptions for heterogeneous and homogeneous regions differently but also implements boundary detection-based spatial weight with temporal and spectral weights together to enhance the predicted spatial details, it has the potential to increase the availability of fine spatial resolution data. [ABSTRACT FROM AUTHOR]

1. Fire is commonly identified as strong driver of alternative stable states such as adjacent open-versus closed-canopy vegetation types. The absence of open-canopy species from closed-canopy understoreys, where light availability is low and dynamic, however, suggests shade tolerance is an integral determinant of such vegetation boundaries. While the importance of light dynamics between alternative stable states has been acknowledged, the physiological mechanisms behind sun versus shade tolerance are unclear. Here we investigated the differences in light interception and carbon assimilation of open- and closed-canopy species, and whether this contributes to the maintenance of alternative stable states. 2. Evergreen forest and fynbos species were grown under three light availability treatments (24%, 54% and 100%) in a glasshouse with their photosynthetic response to continuous and fluctuating light, dark respiration, root respiration, biomass and leaf traits quantified. 3. Fynbos species displayed smaller, thicker and tightly aggregated leaves compared to forest species. Under low light, fynbos species experienced some mortality, and showed lower light-use efficiency with fluctuating light and lower in situ photosynthetic rates under the 54% light treatment compared to forest species (0.8 vs. 3.4 µmol CO2 m-2 s-1). 4. Synthesis. Contrasting light availability in forest and fynbos selects for dissimilar traits, where fynbos species are unable to efficiently intercept light and maintain a positive carbon balance under low, dynamic light compared to forest species. This shade intolerance is exacerbated by divergent nutrient and fire regimes in forest and fynbos environments, requiring incompatible trait specialisations that promote the emergence and maintenance of alternative stable states. [ABSTRACT FROM AUTHOR]

Identifying physical and ecological boundaries that limit where species can occur is important for predicting how those species will respond to global change. The island of Borneo encompasses a wide range of habitats that support some of the highest richness on Earth, making it an ideal location for investigating ecological mechanisms underlying broad patterns of species distribution. We tested variation in richness and range‐size in relation to edaphic specialization and vegetation zone boundaries using 3060 plant species from 193 families centered around the elevational gradient of Mt Kinabalu, Borneo. Across species, average range‐size increased with elevation, consistent with Rapoport's rule. However, plants associated with ultramafic soil, which is low in nutrient and water availability and often has high concentrations of heavy metals, had larger range‐sizes and greater richness than expected along the elevational gradient, as compared to a null model with randomization of edaphic association. In contrast, non‐ultramafic species had smaller range‐sizes and lower richness than expected. These results suggest that tolerance of resource limitation may be associated with wider range‐sizes, whereas species intolerant of edaphic stress may have narrower range‐sizes, possibly owing to more intense competition in favorable soil types. Using elevation as a predictor of average range‐sizes, we found that piece‐wise models with breakpoints at vegetation zone transitions explained species distributions better than models that did not incorporate ecological boundaries. The greatest relative increases in range‐size with respect to elevation occurred mid‐elevation, within the montane cloud forest vegetation zone. Expansion of average range‐size across an area without physical boundaries may indicate a shift in ecological strategy and importance of biotic versus abiotic stressors. Our results indicate that elevational range‐size patterns are structured by ecological constraints such as species' edaphic association, which may limit the ability of species to migrate up or down mountains in response to climate change. [ABSTRACT FROM AUTHOR]

The propagation and hydrodynamic processes of lock-exchange gravity current through vegetation regions were investigated experimentally. Experimental results show that the presence of vegetation can prominently advance the transition position of the gravity current from the slumping phase to the self-similar phase. The process of two-heads propagation can be divided into three stages: the coordinated advance stage (vegetation height controls), the overtaking stage (entrainment process and vegetation friction dominate), and the merge stage (vegetation density controls). After an adjustment period, the bulk slope angle β b of the triangular gravity current converges to a constant terminal value. A modified empirical equation is fitted to better meet the stable convergence of the terminal bulk slope angle β b . The mixing layer formed at the transverse boundary between the vegetation and no-vegetation part can promote fluid entrainment. For the submerged vegetation, the gravity current flows over a new "wall boundary", i.e. the top of the vegetation region, and causes the negative vorticity. The changes in the vorticity field indicate the presence of vegetation can significantly affect the internal flow-field structure of gravity currents. Article Highlights: The process of two-heads propagation for gravity current flowing within submerged vegetation can be divided into three stages: the coordinated advance stage (vegetation height controls), the overtaking stage (entrainment process and vegetation friction dominate), and the merge stage (vegetation density controls). A modified empirical equation is fitted to better meet the stable convergence of the terminal slope angle β b for lock-exchange gravity current within vegetation. The vegetation exerts resistance on the gravity current and suppresses the K-H instability at the interface, which weakens the entrainment process, but the mixing layer formed at the transverse boundary of the vegetation region promotes fluid entrainment. [ABSTRACT FROM AUTHOR]

Questions: Forest–grassland boundaries in the tropics are primarily interpreted as driven by fire and herbivory. So far, frost has received little attention as driver of tropical vegetation boundaries. Here, we study mid‐altitudes in south‐central Africa and ask the following questions: (a) is there a lower treeline between grasslands and forests on the Angolan Plateau; (b) if so, do topoclimatic differences play a role in it; and (c) what do our results imply for tropical highlands globally? Location: The Angolan Plateau (10°–16°S and 13°–21° E). Methods: We mapped vegetation by applying a supervised support vector machine‐based classification on a Landsat satellite image. We used a 1,000‐m spaced point grid to extract the mean vertical distribution of the vegetation units from a digital elevation model. The topographic position of each point was calculated using a channel network approach. Microclimatic data were collected across topographic gradients at two sites along the Plateau. Analyses focussed on the number of nights where temperature dropped below 0℃, median and minimum temperatures, and diurnal temperature ranges. Results: Lower treelines separate Miombo forests from geoxyle grasslands in all major valley systems. Treelines are located 150–200 m below the headwater divides. Nocturnal outgoing net long‐wave radiation and resulting cold‐air pooling cause frequent frosts in the valleys during the dry season. Topography controls frost patterns, with minima of down to −7.5℃ and diurnal temperature amplitudes up to 40℃. Conclusions: The results show that vegetation patterns in central Angola are shaped by frost. The processes causing frost depend on air humidity. Drier atmosphere and lower global temperatures indicate a longer frost season, lower minima and frost extending to lower elevations and latitudes for the Pleistocene. Pleistocene forest fragmentations and the rise of endemism‐rich grasslands in comparable tropical highlands worldwide may be explained by crossing thermic thresholds via increasing seasonal aridity. [ABSTRACT FROM AUTHOR]

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest‐grassland ecotone in the southcentral United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad‐scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest‐breeding passerines from 30‐year average climate conditions from 1980 to 2010. During this time, the southern Great Plains experienced an unprecedented wet period without periodic multi‐year droughts that characterized the region's long‐term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952–1958 and 1966–1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest‐grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980–2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966–1972 range limit projections. Periods of lower precipitation in the forest‐grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years. [ABSTRACT FROM AUTHOR]

Laboratory and field measurements made over the past decade have shown the presence of a strong wave-driven mean current in submerged vegetation canopies. Luhar et al. (2010, https://doi.org/10.1029/2010jc006345) suggested that this mean current is analogous to the streaming flow generated in wave boundary layers over bare beds, and developed a simple energy and momentum balance model to predict its magnitude. However, this model predicts that the magnitude of the mean current does not depend on canopy spatial density, which is inconsistent with the measurements made by Abdolahpour et al. (2017, https://doi.org/10.1002/2016jc012446) in recent laboratory experiments. Motivated by observations that the wave-driven mean flow is most pronounced at the canopy interface, Abdolahpour et al. (2017, https://doi.org/10.1002/2016jc012446) proposed an alternate explanation for its origin: It is driven by the vertical heterogeneity in orbital motion created by canopy drag. Such heterogeneity can give rise to incomplete particle orbits near the canopy interface and a Lagrangian mean current analogous to Stokes drift in the direction of wave propagation. A model guided by this physical insight and dimensional analysis is able to generate much more accurate predictions. This comment aims to reconcile these two different models for the wave-driven mean flow in submerged canopies. [ABSTRACT FROM AUTHOR]

• Vegetation canopy shadow was removed in near-ground hyperspectral imagery. • Shadow removal considers shadowed endmembers and classification strategies. • The problems of over-compensation and mis-compensation were solved. • A triple shadow multilinear mixing model-based shadow removal method is proposed. High spatial resolution hyperspectral images are full of spatial and spectral information, which is beneficial to the identification and extraction of small changes in vegetation. The shape of spectra in the vegetation canopy region is changed by illumination and shadow, which affects the accuracy of parameter retrieval and environmental monitoring. However, existing shadow removal methods primarily target buildings, whose three-dimensional structure differs from that of the vegetation canopy. There is a requirement for research on methods of shadow removal for near-ground hyperspectral vegetation canopy regions, as existing models also suffer from over-compensation and mis-compensation when applied to these areas. Therefore, this study proposed a triple shadow multilinear mixing model-based shadow removal method (triple-SMLM). The triple-SMLM method contains three steps. For the first unmixing, the extraction of vegetation and soil endmembers from the sunlit regions served as input for the SMLM model to detect shadowed regions. For the second unmixing, the shadowed endmembers were selected using the Euclidean distance and unmixed based on the SMLM model. The shadowed regions were divided into two parts based on their abundance and vegetation pixel extraction index (VPEI): information-rich and information-poor shadowed regions. For the third unmixing, the former was compensated by spectral reconstruction based on the unmixed parameters of the previous step, while the latter was compensated by spectral reconstruction in combination with the VPEI indices after unmixing in the SMLM model. The results of the experiment are as follows: (1) The accuracy evaluation shows that the STD and RMSE of the shadow-removed image for the triple-SMLM method are 0.47 and 4.93%, and the results are more precise. (2) Compared with other methods, there is a great improvement in the shadowed boundaries of vegetation and the information-poor shadowed regions of the soil. The shadow removal performance of the triple-SMLM has potential in the vegetation canopy region of near-ground hyperspectral imagery. [ABSTRACT FROM AUTHOR]

• A new conceptual framework on germination niche shaped by hydro-thermal traits. • Key inter-relations between quantitative germination traits for almost 500 species. • Patterns and co-correlants in the cardinal values for species' germination niche. • A database to determine the vegetation boundaries of wild or cultivated species. The germination niche of plant species depends primarily on the seeds' responsiveness to temperature and water potential. However, to appreciate future climate risks to natural regeneration through germination, a global level synthesis across species is needed. We performed a meta-regression and phylogenetic patterning of primary data from 377 studies on 486 species, including trees, grasses, crops and wild species, to determine patterns and co-correlants in the cardinal values that define species' germination niches. We found positive correlations between base temperature and other germination traits related to cardinal temperatures suggesting that plant species alter base temperature values in harmony with other thermal traits as a highly efficient adaptation strategy to coping with harsh conditions. A negative correlation was found between thermal time and base temperature, and positive correlations between other cardinal temperatures and base temperature. Mean values of thermal time indicate that annual crops germinate more rapidly compared to wild species, potentially as a consequence of domestication, and tropical tree seeds the slowest. Dryland species (Cactaceae and Agavaceae) have the widest upper thermal and lower moisture niches, indicative of abilities to grow under harsh conditions, while forages have the narrowest thermal and moisture niches, suggesting higher sensitivity to frost or drought. We propose a new conceptual framework for future research on germination niche as shaped by thermal and moisture traits. Our database represents a unique source of information to further determine the vegetation boundaries of wild or cultivated species, including within simulation studies on plant species adaptations under changing land-use and climate. [ABSTRACT FROM AUTHOR]

This paper presents new multi-proxy records of the Holocene environmental and climatic changes in the Western Caucasus revealed from a continuous sediment sequence from mountainous Lake Khuko (Caucasus State Natural Biospheric Reserve, 1744 m a.s.l.). Palaeoecological analyses of a sediment core for grain size, magnetic susceptibility, loss on ignition, and pollen allowed us to determine five principal climatic phases with several subphases since 10.5 ka BP. The age model is based on seven accelerator mass spectrometry 14C dates, supplemented by 210Pb data for the uppermost part of the sediment core. Warm periods (10.5–6.7, 6.7–5.5, 3.5–2.4, 0.8–0.5 ka BP) were characterized by high biological productivity in the lake as indicated by high organic matter content and expansion of forests, typical of modern low and middle mountain zones, as indicated by the increase in abundance of Quercus, Ulmus, Corylus, and Tilia in the pollen assemblages. Cold periods (5.5–3.5, 2.4–0.8, and 0.5 ka BP–present) are marked by a consistent decrease in organic matter content in lake deposits and possibly higher intensity of the catchment erosion. The changes in pollen assemblages (for instance peaks of Abies, Picea, and Pinus) suggested a potential elevational decline in the boundaries of vegetation belts and expansion of high-altitude woodlands. Abrupt changes in the lake ecosystem were identified between 4.2 and 3.5 ka cal BP marked by a short-term variation in sediment regime shown by variation in organic matter content, magnetic susceptibility values, and sediment grain size. This was probably caused by climatic fluctuations in the Western Caucasus region as a result of complex shifts in the ocean-atmosphere system during the 4.2 ka event. Overall, the first Holocene multi-proxy continuous lake sediment record provides new insights into the climate history in the Western Caucasus. [ABSTRACT FROM AUTHOR]

Farming and afforestation in the African Sahel and Great Green Wall (GGW) regions are constrained by climate variability, water scarcity, and degradation of lands. Yet, the debate on dynamics of the Saharan boundary and vegetation productivity in these regions is ongoing. Here, we trace the most unsuitable areas for rainfed agriculture and greening in the two regions over the period 1998–2017 without specifying a crop/vegetation type. A method is devised based on combining June–October rainfall/potential evapotranspiration (aridity index) and integrated normalized difference vegetation index (productivity index). The feasibility of the currently planned GGW is placed in the context of naturally‐sound afforestation. The results show certain features of the suitable zone for planting. A seasonal aridity index of 0.1 is a minimum threshold for vegetation vigour to begin. Given the strong interannual north–south progression and retreat of this seasonal level, the northernmost aridity isoline that dictates feasibility of rainfed productivity is found to correspond to the borderline between the arid and semiarid zones. This borderline is delimited by an average aridity index of 0.2. Accordingly, 1,337,535 km2 (43.5%) and 729,576 km2 (25.6%) of the Sahel and the proposed GGW region, respectively, are not feasible for sustainable planting, that is, under rainfed and natural land fertility conditions. About 93.0% of the impractical GGW area lies east of longitude 10°E. Investing in a green belt east of this longitude is risky without supplementary irrigation. The contrasting productivity behavior across the GGW cautions the progression in this project without rigorous feasibility investigation. [ABSTRACT FROM AUTHOR]

We present results from an ensemble of eight climate models, each of which has carried out simulations of the early Eocene climate optimum (EECO, ∼ 50 million years ago). These simulations have been carried out in the framework of the Deep-Time Model Intercomparison Project (DeepMIP; http://www.deepmip.org , last access: 10 January 2021); thus, all models have been configured with the same paleogeographic and vegetation boundary conditions. The results indicate that these non-CO 2 boundary conditions contribute between 3 and 5 ∘ C to Eocene warmth. Compared with results from previous studies, the DeepMIP simulations generally show a reduced spread of the global mean surface temperature response across the ensemble for a given atmospheric CO 2 concentration as well as an increased climate sensitivity on average. An energy balance analysis of the model ensemble indicates that global mean warming in the Eocene compared with the preindustrial period mostly arises from decreases in emissivity due to the elevated CO 2 concentration (and associated water vapour and long-wave cloud feedbacks), whereas the reduction in the Eocene in terms of the meridional temperature gradient is primarily due to emissivity and albedo changes owing to the non-CO 2 boundary conditions (i.e. the removal of the Antarctic ice sheet and changes in vegetation). Three of the models (the Community Earth System Model, CESM; the Geophysical Fluid Dynamics Laboratory, GFDL, model; and the Norwegian Earth System Model, NorESM) show results that are consistent with the proxies in terms of the global mean temperature, meridional SST gradient, and CO 2 , without prescribing changes to model parameters. In addition, many of the models agree well with the first-order spatial patterns in the SST proxies. However, at a more regional scale, the models lack skill. In particular, the modelled anomalies are substantially lower than those indicated by the proxies in the southwest Pacific; here, modelled continental surface air temperature anomalies are more consistent with surface air temperature proxies, implying a possible inconsistency between marine and terrestrial temperatures in either the proxies or models in this region. Our aim is that the documentation of the large-scale features and model–data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability, and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols. [ABSTRACT FROM AUTHOR]

Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes. These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity, phyto-sociology, boundary detection and even impact of change in land use pattern (anthropogenic activity). The most accepted and widespread technique called as Moving Split Window (MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya. All the four sites were at different distances from the nearest human inhabited area. Anthropogenic activities like grazing, herb collection, wood collection etc. were common at proximal sites. Such activities have led to the change in land use pattern. In this study, we have tried to work out the impact of the change in land use pattern (human interference) on the vegetation and basic environmental parameters like soil pH, electrical conductivity and moisture on forest-grassland ecotone in north-west Himalaya. Data on mountain steepness was also collected and analyzed. The dissimilarity profile using the statistical tool Squared Euclidian Distance (SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements. The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data, however, conditions are reverse in case of the proximal sites. The study also reveals that as the distance between the ecotone and human settlements increases, the complex conditions like multiple vegetation boundaries prevails on the transitions. In this regard, land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study. [ABSTRACT FROM AUTHOR]

Summary: Vegetation–fire feedbacks are important for determining the distribution of forest and savanna. To understand how vegetation structure controls these feedbacks, we quantified flammability across gradients of tree density from grassland to forest in the Brazilian Cerrado.We experimentally burned 102 plots, for which we measured vegetation structure, fuels, microclimate, ignition success and fire behavior.Tree density had strong negative effects on ignition success, rate of spread, fire‐line intensity and flame height. Declining grass biomass was the principal cause of this decline in flammability as tree density increased, but increasing fuel moisture contributed. Although the response of flammability to tree cover often is portrayed as an abrupt, largely invariant threshold, we found the response to be gradual, with considerable variability driven largely by temporal changes in atmospheric humidity. Even when accounting for humidity, flammability at intermediate tree densities cannot be predicted reliably.Fire spread in savanna–forest mosaics is not as deterministic as often assumed, but may appear so where vegetation boundaries are already sharp. Where transitions are diffuse, fire spread is difficult to predict, but should become increasingly predictable over multiple fire cycles, as boundaries are progressively sharpened until flammability appears to respond in a threshold‐like manner. [ABSTRACT FROM AUTHOR]

In remote sensing, land cover classification of vegetation and water area from satellite image play a vital role for rural and urban planning and development. Existing algorithms of land cover classification require more sample image datasets for training. For existing algorithms, land cover classification of vegetation and water area is a challenging task because of mixed pixel and geometric distortion over boundary and curvature region. Mixed pixel affects the precise classification and measurement of land cover. Geometric distortion arises due to frame of isotropic and angular selectivity during image acquisition and affects the contour of land cover. In this paper, the proposed transverse dyadic wavelet transform (TDyWT) enhances and classifies vegetation and water area in land cover from LANDSAT image without training datasets. The proposed TDyWT uses Haar wavelet for decomposition and Burt 5 × 7 wavelet for reconstruction. The TDyWT enhances the contour, curvature, and boundary of vegetation and water area in LANDSAT image due to reversible and lifting properties of wavelet. TDyWT removes geometric distortion and spatial scale error of mixed pixel. In traditional land surveying spatial scale error reduction eliminates through total station and error modeling techniques. From the results, the proposed TDyWT algorithm classifies the area of subclass of vegetation and water with the 95% of accuracy with respect to ground truth survey methods. [ABSTRACT FROM AUTHOR]

Observational data from two field campaigns in the Amazon forest were used to study the vertical structure of turbulence above the forest. The analysis was performed using the reduced turbulent kinetic energy (TKE) budget and its associated two-dimensional phase space. Results revealed the existence of two regions within the roughness sublayer in which the TKE budget cannot be explained by the canonical flat-terrain TKE budgets in the canopy roughness sublayer or in the lower portion of the convective ABL. Data analysis also suggested that deviations from horizontal homogeneity have a large contribution to the TKE budget. Results from LES of a model canopy over idealized topography presented similar features, leading to the conclusion that flow distortions caused by topography are responsible for the observed features in theTKEbudget. These results support the conclusion that the boundary layer above the Amazon forest is strongly impacted by the gentle topography underneath. [ABSTRACT FROM AUTHOR]

On the background of climate dynamics during last decade, the Baikal Region manifests considerable changes in the whole biota structure. It is seen in the structural-dynamic organization, trends of forests development due to considerable variability of vertical and horizontal structures in the coenoses. Especially this is characteristic for the forests formation at the contact of different environments – at the boundary of zonal vegetation types and height belts in Pre-Baikal. Projects of protective forests in the basins of the rivers flowing into Lake Baikal in forests management for water protection and establishment of forests site under special protection within near-shore protective shelter belts excludes industrial forest cutting and limits other forms of forests use. Accounting of environment protection functions of forests at forests management and establishment of validity categories (not only for utility) will allow to stabilize hydroregimes and functioning of Lake Baikal basin’ ecosystem in the whole. [ABSTRACT FROM AUTHOR]

The Great Lakes–St. Lawrence Forest Region in Canada occupies a narrow band of mixed forest from the Gaspé Peninsula to southeastern Manitoba. The westernmost extent of this forest region in Manitoba is expected to support at least some of the bryophyte species that occur further east within the climatic and vegetation boundaries of the region. However, very few bryophytes have been reported from this area in Manitoba either in the scientific literature or herbaria, necessitating further investigation. This study provides the first assessment of bryophytes from mixed forests and treed swamps within the Great Lakes forest in Manitoba and relates them to physiography and habitat, including the first documented bryophytes for Buffalo Point First Nation on Lake of the Woods. Reported here are 153 bryophyte taxa, including 40 liverworts from 29 genera in 23 families, and 113 mosses from 77 genera in 31 families. Among these, 27 bryophytes (9 liverworts and 18 mosses) are new to Manitoba, and an additional 7 bryophytes (1 liverwort and 6 mosses) that previously had incomplete information or were equivocal are now confirmed for Manitoba. These findings expand substantially the provincial bryophyte flora. A further 35 bryophytes are re-discovered for Manitoba after more than 40 years since they were last reported in the literature. The surveyed flora is characterized as predominantly boreal (61.7% of taxa) in terms of world phytogeographic distributions. However, more than one quarter of taxa (27.9%) are temperate and frequently associated with habitats containing Fraxinus nigra (Black Ash) or Fraxinus pennsylvanica (Green Ash) trees. Many of the temperate taxa reported have widespread distributions in eastern North America but approach their western and/or northern distribution limits in the study area. Herein I identify bryophytes of high conservation value for Great Lakes forest in Manitoba using nested subsets of taxa. Additional documentation of bryophytes in the area is needed to help inform the conservation and management of lands that support a high diversity of Great Lakes-associated bryophytes. [ABSTRACT FROM AUTHOR]

The complex, dynamic and narrow boundaries between vegetation types make wetland mapping challenging. Hereafter the case study of the Hamoun-e-Hirmand wetland is considered by analysing eight Synthetic Aperture Radar (SAR) Images acquired in dry and wet periods with three wavelengths (X-band ~ 3 cm, C-band ~ 6 cm, and L-band ~ 25 cm), three polarizations (HH, VV and VH), and four incidence angles (22°, 30°, 34° and 53°). Then, the Support Vector Machine (SVM) classification method was applied to classify TerraSAR-X, Sentinel-1, and ALOS-PALSAR images. The final wetland land cover map was created by combining the classification results obtained from each sensor. In the case in question, results show that TerraSAR-X (X-band, HH-53°) and Sentinel-1 data (C-band, VV-34°) were useful for determining the flooded vegetation area in the wet period. This is crucial for the conservation of water bird habitats since flooded vegetation is an ideal environment for the nesting and feeding of water birds. PALSAR data (L-band in both HH and VH polarizations, 30°) were capable of separating the classes of vegetation density in the wetland. In the dry period, Sentinel-1 (VV and VH, 34°) and TerraSAR-X (HH, 22° and 53°) had higher potential in land cover mapping than PALSAR (HH and VH, 30°). Based on these results, Sentinel-1 in VV and VH provides the highest ability to discriminate between dry and green plants. TerraSAR-X is better for separating meadow and bare land. The results obtained in this paper can reduce the ambiguity in selecting satellite data for wetland studies. The results can also be used to produce more accurate data from satellite images and to facilitate wetland investigation, conservation and restoration. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is an indicator of sustainable land management as stated in the global indicator framework of the United Nations Sustainable Development Goals (SDG Indicator 15.3.1). Improved forecasting of future changes in SOM is needed to support the development of more sustainable land management under a changing climate. Current models fail to reproduce historical trends in SOM both within and during transition between ecosystems. More realistic spatio‐temporal SOM dynamics require inclusion of the recent paradigm shift from SOM recalcitrance as an 'intrinsic property' to SOM persistence as an 'ecosystem interaction'. We present a soil profile, or pedon‐explicit, ecosystem‐scale framework for data and models of SOM distribution and dynamics which can better represent land use transitions. Ecosystem‐scale drivers are integrated with pedon‐scale processes in two zones of influence. In the upper vegetation zone, SOM is affected primarily by plant inputs (above‐ and belowground), climate, microbial activity and physical aggregation and is prone to destabilization. In the lower mineral matrix zone, SOM inputs from the vegetation zone are controlled primarily by mineral phase and chemical interactions, resulting in more favourable conditions for SOM persistence. Vegetation zone boundary conditions vary spatially at landscape scales (vegetation cover) and temporally at decadal scales (climate). Mineral matrix zone boundary conditions vary spatially at landscape scales (geology, topography) but change only slowly. The thicknesses of the two zones and their transport connectivity are dynamic and affected by plant cover, land use practices, climate and feedbacks from current SOM stock in each layer. Using this framework, we identify several areas where greater knowledge is needed to advance the emerging paradigm of SOM dynamics—improved representation of plant‐derived carbon inputs, contributions of soil biota to SOM storage and effect of dynamic soil structure on SOM storage—and how this can be combined with robust and efficient soil monitoring. [ABSTRACT FROM AUTHOR]