Search Results (136)

The transition from MIS3 interstadial to the coldest stadial of the last glacial (MIS 2) marked a rapid change in the climate. Findings of multiproxy (sedimentological, MS, geochemical (AAS, XRD), micromorphological, anthracological, phytolith and malacological) studies from a loess/paleosol sequence in northeastern Hungary highlighted the transformation of a reddish-brown fossil soil layer (cambisol) to a podzolic soil with signs of iterative wildfires during the terminal part of MIS3. According to our findings, a Scots pine (Pinus sylvestris) dominated open parkland emerged on the northern slopes during the second phase of MIS3 hosted by a special reddish-brown soil. Then the last phase of MIS3 was marked by the development of spruce (Picea abies) dominated open parkland. Results further suggest that vegetation change passed a critical threshold leading to an unusually rapid expansion of spruce (within ca. 100 yr). This rapid expansion of spruce, changing the geochemistry of the litter to a more acidic state likely caused the initiation of podzolization and the transformation of the original soil. The opening of MIS2 marked not only intensive dust accumulation but also a steady decline of arboreal elements as well, leading to the emergence of a cold tundra on top of the podosol with charcoal remains. Full article

Recent studies have shown that lidar observations from the Ice, Clouds, and Land Elevation Satellite-2 (ICESat-2) enable seasonal snow depth retrieval over land through two primary approaches. The snow-on–off method estimates snow depth by differencing surface elevations acquired during snow-covered and snow-free periods, while the pathlength method derives it from multiple-scattering photon distributions within the snowpack. In this study, we cross-validate ICESat-2-derived surface elevations and snow depths against in situ measurements from SnowEx field campaigns. ICESat-2 surface elevations agree closely with SnowEx data, which we consider closest to the truth, achieving centimeter-level accuracy (e.g., 1 cm) over flat, sparsely vegetated terrain, with larger biases in vegetated and steep areas. Snow depth estimates from both methods show comparable performance in the tundra area, with typical errors on the order of tens of centimeters; however, in vegetated or steep terrain, the pathlength method yields more reliable snow depth results, being less affected by slope and vegetation than the snow-on–off method. These findings show that ICESat-2 is a reliable tool for measuring snow depth from space. Full article

The response of Arctic vegetation to climate warming exhibits pronounced spatial heterogeneity, driven partly by widespread permafrost degradation. However, the role of thermokarst lake development in mediating vegetation-climate interactions remains poorly understood, particularly across heterogeneous landscapes of northeastern Siberia. This study integrated multi-source remote sensing data (2001–2021) with trend analysis, partial correlation, and a Shapley Additive Explanation (SHAP)-interpreted random forest model to examine the drivers of normalized difference vegetation index (NDVI) variability across five levels of thermokarst lake coverage (none, low, moderate, high, very high) and two vegetation types (forest, tundra). The results show that although greening dominates the region, browning is disproportionately observed in areas with high thermokarst lake coverage (>30%), highlighting the localized reversal of regional greening trends under intensified thermokarst activity. Air temperature was identified as the dominant driver of NDVI change, whereas soil temperature and soil moisture exerted secondary but critical influences, especially in tundra ecosystems with extensive thermokarst lake development. The relative importance of these factors shifted across thermokarst lake coverage gradients, underscoring the modulatory effect of thermokarst processes on vegetation-climate feedbacks. These findings emphasize the necessity of incorporating thermokarst dynamics and landscape heterogeneity into predictive models of Arctic vegetation change, with important implications for understanding cryospheric hydrology and ecosystem responses to ongoing climate warming. Full article

The small freshwater lakes of Spitsbergen remain poorly studied compared to surrounding marine ecosystems despite their sensitivity to rapid environmental changes. During the short ablation season, these shallow lakes exhibit physicochemical variability influenced by the harsh Arctic climate, local geology, and hydrology. This study analyzed six lakes located on marine terraces, moraine areas, and outwash plains in the Bellsund region to assess how physicochemical variability in their waters affects phytoplankton development. The lakes exhibited local and temporal variations in temperature, conductivity, ion composition, and nutrient levels, with generally low nutrient availability limiting biological productivity. Phytoplankton communities were quantitatively and qualitatively poor, dominated by green algae, either flagellates or mixed communities, including cyanobacteria. Green algae clearly dominated in lakes closest to the fjord shoreline, while dinoflagellates and cryptophytes dominated in inland lakes. Phytoplankton abundance and biomass were extremely low in one of the lakes situated on the raised marine terraces within the tundra vegetation zone (3 × 10³ ind L⁻¹ and 0.004 mg L⁻¹, respectively). In contrast, the much larger lake situated within the tundra zone nearer the fjord shoreline had values that were comparable to fertile lakes in the temperate zone (~30 thousand × 10³ ind L⁻¹ and ~28 mg L⁻¹, respectively). It should be noted that Monoraphidium contortum and Rhodomonas minuta dominated some of the lakes almost entirely. Phytoplankton abundance was related to physicochemical conditions: green algae increased with increasing ion concentrations (Cl⁻, Na⁺, K⁺, SO₄²⁻), P_min, Fe, and Mn; flagellates preferred colder waters with higher N_min and low TOC; cyanobacteria occurred in waters with lower COND, TOC, Ca²⁺, Si, Cu, and Zn. Phytoplankton biomass increased in July with increasing water temperature. Bird activity likely facilitated phytoplankton dispersal, increasing taxonomic diversity in frequently visited lakes. Full article

The sustainability of Arctic ecosystems that are extremely vulnerable is contingent upon the state of cryosoils. Understanding the principles of ecosystem stability in permafrost conditions, particularly under external natural or human-induced influences, necessitates an examination of the thermal and moisture regimes of the seasonally thawed soil layer. The study concentrated on the variability in the soil’s thermophysical properties in Central Siberia’s permafrost zone (the northern part of Krasnoyarsk Region, Taimyr, Russia). In the industrially affected area of interest, we evaluated and contrasted the differences in the thermophysical properties of soils between two opposing types of landscapes. On the one hand, these are soils that are characteristic of the natural landscape of flat shrub tundra, with a well-developed moss–lichen cover. An alternative is the soils in the landscape, which have exhibited significant degradation in the vegetation cover due to both natural and human-induced factors. The heat-insulating properties of background areas are controlled by the layer of moss and shrubs, while its disturbance determines the excessive heating of the soil at depth. In comparison to the background soil characteristics, degradation of on-ground vegetation causes the active layer depth of the soils to double and the temperature gradient to decrease. With respect to depth, we examine the changes in soil temperature and heat flow dynamics (q, W/m²). The ranges of thermal conductivity (λ, W/(m∙K)) were assessed using field-measured temperature profiles and heat flux values in the soil layers. The background soil was discovered to have lower thermal conductivity values, which are typical of organic matter, in comparison to the soil of the transformed landscape. Thermal diffusivity coefficients for soil layers were calculated using long-term temperature monitoring data. It is shown that it is possible to use an adjusted model of the thermal conductivity coefficient to reconstruct the dynamics of moisture content from temperature dynamics data. A satisfactory agreement is shown when the estimated ($W_{calc}$, %) and observed ($W_{exp}$, %) moisture content values in the soil layer are compared. The findings will be employed to regulate the effects on landscapes in order to implement sustainable nature management in the region, thereby preventing the significant degradation of ecosystems and the concomitant risks to human well-being. Full article

Climate change is accelerating, and the monitoring of plant phenology is becoming increasingly important. In response to this need, many vegetation indices (VIs) and analytical methods have been developed. However, many VIs are vulnerable to uncertainties caused by snowmelt, making them potentially unsuitable for monitoring spring phenology in forested regions where leaf flush (start of season, SOS) begins simultaneously with snowmelt. Although several VIs for snowy regions have been proposed, most of them were designed for tundra vegetation, such as grasslands. Currently, no VI or analytical method specifically suited for snowy forested regions has been firmly established. Similarly, there is still no well-established method for continuously monitoring autumn coloration. In this study, we propose the use of hue, one of the components of the HSV model, for remote sensing of plant phenology. Hue quantifies differences in object color and is expected to facilitate clearer distinction of snow influence. It may also enable accurate detection of canopy color transitions, such as autumn coloration. We evaluate the applicability of hue to remote sensing using in situ spectroradiometer observations collected from five sites of the Phenological Eyes Network (PEN), which represent a range of ecosystems—including forests, grasslands, and paddy fields—as well as the relative spectral response (RSR) of the Second-generation Global Imager (SGLI) onboard the GCOM-C satellite operated by JAXA (Japan Aerospace Exploration Agency). The results suggest that hue is more robust to snow-related uncertainties than traditional VIs (NDVI, EVI, CCI, NDGI) and may also be effective for quantifying autumn coloration. Hue is calculated solely from blue, green, and red reflectance, without relying on near-infrared (NIR) or shortwave infrared (SWIR) channels. Since blue, green and red channels are available on almost all optical satellite sensors, hue may offer broader applicability than many traditional VIs. Full article

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices. Full article

Under global warming, vegetation composition changes induced by plant encroachment have a significant impact on the carbon balance of tundra ecosystems. The encroachment of herbaceous plants into indigenous shrub communities has changed the aboveground and belowground litter carbon input and the characteristics in the shrub tundra of the Changbai Mountains. However, the impact of variations in litter characteristics and litter carbon input on the dynamics of soil organic carbon (SOC) pool concentrations and SOC stability remains ambiguous. In this study, aboveground and belowground litter and soil samples were collected for lab experiments. Our results showed that the increase in aboveground litter and belowground litter due to Deyeuxia purpurea encroachment increased the SOC concentration. Simultaneously, D. purpurea encroachment decreased the soil C/N by decreasing the components of both aboveground and belowground litter that were resistant to decomposition (C/N and lignin/N) and increased the soil mineralization ability and available N concentrations, increased the CO₂ release rate, and ultimately decreased the SOC concentration. D. purpurea encroachment enhanced soil decomposition capacity by increasing the concentration of organic carbon molecular structures, such as carbohydrates, in the aboveground and belowground litter, thereby increasing the concentration of decomposable organic carbon molecular structures and active organic carbon in the soil, while simultaneously reducing the concentration of recalcitrant organic carbon. Even more, D. purpurea encroachment reduced the recalcitrant components of the aboveground and belowground litter enhanced soil mineralization capability and increased soil nitrogen concentration, which collectively increased the carbon oxidation state (COX) and decreased SOC stability. In general, global warming has led to herbaceous plant encroachment, which changes the aboveground and belowground litter carbon inputs and properties in the tundra, in turn reducing the SOC concentration and soil carbon pool stability, enhancing soil carbon emission capacity, and increasing atmospheric CO₂ concentration, forming a vicious cycle. Full article

We explore a new approach for the parsimonious, generalizable, efficient, and potentially automatable characterization of spectral diversity of sparse targets in spectroscopic imagery. The approach focuses on pixels which are not well modeled by linear subpixel mixing of the Substrate, Vegetation and Dark (S, V, and D) endmember spectra which dominate spectral variance for most of Earth’s land surface. We illustrate the approach using AVIRIS-3 imagery of anthropogenic surfaces (primarily hydrocarbon extraction infrastructure) embedded in a background of Arctic tundra near Prudhoe Bay, Alaska. Computational experiments further explore sensitivity to spatial and spectral resolution. Analysis involves two stages: first, computing the mixture residual of a generalized linear spectral mixture model; and second, nonlinear dimensionality reduction via manifold learning. Anthropogenic targets and lakeshore sediments are successfully isolated from the Arctic tundra background. Dependence on spatial resolution is observed, with substantial degradation of manifold topology as images are blurred from 5 m native ground sampling distance to simulated 30 m ground projected instantaneous field of view of a hypothetical spaceborne sensor. Degrading spectral resolution to mimicking the Sentinel-2A MultiSpectral Imager (MSI) also results in loss of information but is less severe than spatial blurring. These results inform spectroscopic characterization of sparse targets using spectroscopic images of varying spatial and spectral resolution. Full article

Permafrost thawing is potentially a crucial but poorly investigated factor that influences vegetation dynamics in the Arctic. We studied the permafrost thaw rate beyond the Polar Circle in Siberia. We analyzed its influence on the larch (Larix spp.) growth and Arctic vegetation (sparse larch forests, tundra, and forest–tundra communities) productivity (NPP). We checked the following hypotheses: (1) satellite gravimetry is valid for permafrost thawing analysis; (2) meltwater runoff stimulated trees’ growth and NPP. We used satellite (GRACE, Terra/MODIS) and field data, and larch tree radial growth index measurements. We found a continuous negative trend in the terrestrial water content (r² = 0.67) caused by permafrost thawing beyond the Polar Circle. Runoff is maximal in West and Mid Siberia (9.7 ± 2.9 kg/m²/y) and decreases in the eastward direction with minimal values in the Chukotka Peninsula sector (−2.9 ± 3.2 kg/m²/y). We found that the growth increment of larch trees positively correlated with meltwater runoff (0.5…0.6), whereas the correlation with soil water content was negative (−0.55…−0.85). Permafrost thawing leads to an increase in the Arctic vegetation productivity. We found a positive trend in NPP throughout the Siberian Arctic (r² = 0.30). NPP negatively correlated with soil water content (r = −0.55) and positively with meltwater runoff (West Siberia, r = 0.7). An increase in VPD (vapor pressure deficit) and air and soil temperatures stimulated the larch growth and vegetation NPP (r = 0.5…0.9 and r = 0.6…0.9, respectively). Generally, permafrost degradation leads to improved hydrothermal conditions for trees and vegetation growth and contributes to the preservation of the Arctic as a carbon sink despite the increase in burning rate. Full article

The Arctic, characterised by severe climatic conditions and sparse vegetation, is experiencing rapid warming, with temperatures increasing by up to four times the global rate since 1979. Extensive impacts from these changes have far-reaching consequences for the global climate and energy balance. Satellite remote sensing is a valuable tool for monitoring Arctic vegetation dynamics, particularly in regions with limited ground observations. To investigate the ongoing impact of climate change on Arctic and sub-Arctic vegetation dynamics, a review of 162 studies published between 2000 and November 2024 was conducted. This review analyses the research objectives, spatial distribution of study areas, methods, and the temporal and spatial resolution of utilised satellite data. The key findings reveal circumpolar tendencies, including Arctic greening, lichen decline, shrub increase, and positive primary productivity trends. These changes impact the carbon balance in the tundra and affect specialised fauna and local communities. A large majority of studies conducted their analysis based on multispectral data, primarily using AVHRR, MODIS, and Landsat sensors. Although the warming of the Arctic is linked to greening trends, increased productivity, and shrub expansion, the diverse and localised ecological shifts are influenced by a multitude of complex factors. Furthermore, these changes can be challenging to observe due to difficult cloud cover and illumination conditions when acquiring optical satellite data. Additionally, the difficulty in validating these changes is compounded by the scarcity of in situ data. The fusion of satellite data with different spatial–temporal characteristics and sensor types, combined with methodological advancements, may help mitigate data gaps. This may be particularly crucial when assessing the Arctic’s potential role as a future carbon source or sink. Full article

The circumpolar Taiga–Tundra Ecotone significantly influences the feedback mechanism of global climate change. Achieving large-scale individual tree crown (ITC) extraction in the transition zone is crucial for estimating vegetation biomass in the transition zone and studying plants’ response to climate change. This study employed aerial images and airborne LiDAR data covering several typical transitional zone regions in northern Finland to explore the ITC delineation method based on deep learning. First, this study developed an improved multi-scale ITC delineation method to enable the semi-automatic assembly of the ITC sample collection. This approach led to the creation of an individual tree dataset containing over 20,000 trees in the transitional zone. Then, this study explored the ITC delineation method using the Mask R-CNN model. The accuracies of the Mask R-CNN model were compared with two traditional ITC delineation methods: the improved multi-scale ITC delineation method and the local maxima clustering method based on point cloud distribution. For trees with a height greater than 1.3 m, the Mask R-CNN model achieved an overall recall rate ($A_r$) of 96.60%. Compared to the two conventional ITC delineation methods, the $A_r$ of Mask R-CNN showed an increase of 1.99 and 5.52 points in percentage, respectively, indicating that the Mask R-CNN model can significantly improve the accuracy of ITC delineation. These results highlight the potential of Mask R-CNN in extracting low trees with relatively small crowns in transitional zones using high-resolution aerial imagery and low-density airborne point cloud data for the first time. Full article

Drought has extensive, far-reaching, and long-lasting asymmetric effects on vegetation growth worldwide in the context of global warming. However, to date, few scholars have attempted the systematic quantification of the temporal effects of drought on global vegetation across various vegetation types and diverse climate zones. Addressing this gap, we quantitatively investigated the effects of drought on global vegetation growth under various scenarios, considering lagged and cumulative effects as well as combined effects in the 1982–2018 period. Our investigation was based on long-term net primary productivity (NPP) and two multiple-timescale drought indices: the standardised precipitation index (SPI) and the standardised precipitation and evapotranspiration index (SPEI). Our main findings were the following: (1) SPI and SPEI exhibited lagged effects on 52.08% and 37.05% of global vegetation, leading to average time lags of 2.48 months and 1.76 months, respectively. The cumulative effects of SPI and SPEI were observed in 80.01% and 72.16% of global vegetated areas, respectively, being associated with relatively longer cumulative timescales of 5.60 months and 5.16 months, respectively. (2) Compared to the scenario excluding temporal effects, there were increases in the explanatory powers of SPI and SPEI for variations in vegetation NPP based on the lagged, cumulative, and combined effects of drought: SPI increased by 0.82%, 6.65%, and 6.92%, respectively, whereas SPEI increased by 0.67%, 5.73%, and 6.07%, respectively. The cumulative effects of drought on global vegetation NPP were stronger than the lagged effects in approximately two-thirds (64.95% and 63.52% for SPI and SPEI, respectively) of global vegetated areas. (3) The effects of drought on vegetation NPP varied according to climate zones and vegetation types. Interestingly, vegetation in arid zones was the most sensitive and resilient to drought, as indicated by its rapid response to drought and the longest cumulative timescales. The vegetation NPP in tropical and temperate zones exhibited a relatively stronger response to drought than that in cold and polar zones. The strongest correlation of vegetation NPP with drought occurred in shrubland areas, followed by grassland, cropland, forest, and tundra areas. Moreover, for each vegetation type, the correlations between vegetation NPP and drought differed significantly among most climate zones. (4) The vegetation NPP in warming-induced drought regions displayed a higher correlation to drought than that in non-warming-induced drought regions, with shorter lagged and longer cumulative timescales. Our findings highlight the heterogeneity of the lagged, cumulative, and combined effects of drought across various climate zones and vegetation types; this could enhance our understanding of the coupling relationship between drought and global vegetation. Full article

The environment of mountain ecosystems can change greatly in short distances as elevation increases. The effects of elevation change on the distribution and body size of carabid beetles were investigated at elevations of 750–2600 m in the Changbaishan Nature Reserve (Northeast China). The richness and abundance of carabid species decreased significantly as elevation increased. However, the change trends are different in forests and tundra. In the broad-leaved Korean pine forest and coniferous forest at low elevations, carabid beetle species have high richness and abundance. The community composition of carabid beetles was significantly different at different elevations and among different vegetation types. Some species only occurred at specific elevations. There were fewer indicator species in high-elevation areas, but Carabus macleayi Dejean, Nebria pektusanica Horratovich and Pterostichus jaechi Kirschenhofer were mainly found in high-elevation areas. The average body size of species in the carabid beetle community was negatively correlated with elevation. The sizes of the larger Carabus canaliculatus Adams and Carabus venustus Morawitz were negatively correlated with elevation. Their body sizes decreased obviously in the tundra at elevations above 2000 m. Changes in vegetation types at high elevations affect the distribution and body sizes of beetles along the elevation gradient. Some large carabid species may be smaller at high elevations where a unique insect fauna has developed. The body size and distribution range of the carabid may be the factors that affect body size reduction at high elevation. Although some high-elevation species also occur in low-elevation areas, the protection of species diversity in high-elevation areas should be emphasized in the context of global climate change. The results illustrate the mechanisms of carabid beetles’ response to elevation change and the need for carabid beetles’ diversity conservation under global climate change. Full article

Accurate and reliable estimation of actual evapotranspiration (AET) is essential for various hydrological studies, including drought prediction, water resource management, and the analysis of atmospheric–terrestrial carbon exchanges. Gridded AET products offer potential for application in ungauged areas, but their uncertainties may be significant, making it difficult to identify the best products for specific regions. While in situ data directly estimate gridded ET products, their applicability is limited in ungauged areas that require FLUXNET data. This paper employs an Extended Triple Collocation (ETC) method to estimate the uncertainty of Global Land Evaporation Amsterdam Model (GLEAM), Famine Early Warning Systems Network (FLDAS), and Maximum Entropy Production (MEP) AET product without requiring prior information. Subsequently, a merged ET product is generated by combining ET estimates from three original products. Furthermore, the study quantifies the uncertainty of each individual product across different vegetation covers and then compares three original products and the Merged ET with data from 645 in situ sites. The results indicate that GLEAM covers the largest area, accounting for 39.1% based on the correlation coefficient criterion and 39.9% based on the error variation criterion. Meanwhile, FLDAS and MEP exhibit similar performance characteristics. The merged ET derived from the ETC method demonstrates the ability to mitigate uncertainty in ET estimates in North American (NA) and European (EU) regions, as well as tundra, forest, grassland, and shrubland areas. This merged ET could be effectively utilized to reduce uncertainty in AET estimates from multiple products for ungauged areas. Full article