Search Results (465)

Rising temperatures, driven by global climate change, are profoundly altering high-latitude ecosystems, influencing vegetation phenology and productivity. However, understanding the long-term, nuanced responses of these ecosystems remains a critical challenge. Soil warming experiments have served as useful tools for understanding these shifts. However, many of these studies have relied on a single measure, predominantly the Normalized Difference Vegetation (NDVI), measured at a single level of warming. This approach often fails to separate structural greening from underlying physiological responses. To address these gaps, this study provided a comprehensive snapshot assessment of growing season vegetation dynamics in a subarctic grassland ecosystem in Iceland that had been exposed to continuous geothermal soil warming for over 60 years. Using high-resolution multispectral drone imagery, twelve different vegetation indices (VIs) were derived to assess not only greenness but also physiological stress and photosynthetic efficiency across a range of mean annual soil temperatures (MATs). Using linear regression and redundancy analysis (RDA), the responses of these indices to warming and their relationships with other environmental drivers, such as standing biomass and plant nutrient concentrations (nitrogen and phosphorus), were analyzed. The results revealed significant positive linear relationships between most of the indices and MATs across the 5 to 11 °C range. This indicated that higher MATs led to increased biomass and structural growth, without revealing any significant thresholds or tipping points in vegetation response within the observed warming range. However, the Photochemical Reflectance (PRI) showed a significant negative relationship with warming, suggesting a decoupling between structural greening and photosynthetic light-use efficiency. Furthermore, RDA results indicated that, while most of the VIs were primarily driven by biomass, the decline in PRI was likely a compounding effect of physical canopy self-shading and plant phosphorus constraints. Ultimately, this study demonstrated that, while these subarctic grasslands exhibited local evidence of “Arctic greening” under further warming, multispectral drone remote sensing could detect underlying physiological adjustments and nutrient constraints that traditional greenness indices might overlook, providing a more nuanced understanding of ecosystem response. Full article

The “New Arctic” regime represents a prominent climatic feature of the Arctic Ocean under global warming, characterized by persistently low summer sea ice extent, a marked reduction in sea ice thickness, and an expansion of open water areas at high latitudes. As a key indicator of the Arctic sea ice system, the spatiotemporal evolution of sea ice thickness and its underlying driving mechanisms remain incompletely understood. Using reanalysis datasets and remote sensing observations, this study identifies major abrupt shifts in Arctic sea ice thickness under the New Arctic regime, reveals the spatiotemporal distribution characteristics of winter sea ice thickness, and examines the driving factors from both thermodynamic and dynamic perspectives. The results show that the evolution of Arctic sea ice thickness can be divided into three phases: a high-level period during the “Traditional Arctic” (1979–1992), a rapid thinning period during the New Arctic transition (1993–2012), and a low-level stabilization period in the New Arctic regime (2013–2023). The first EOF mode of winter sea ice thickness depicts a spatially consistent thinning pattern across the entire Arctic, with the most significant reduction occurring in the multi-year ice regions north of the Canadian Arctic Archipelago and Greenland. The second EOF mode exhibits an out-of-phase variation between the Atlantic and Pacific sectors of the Arctic, accompanied by a shrinking amplitude and weakened regional oscillations. The coupling between surface air temperature and sea ice thickness displays distinct phase dependence: their negative correlation is strongest during the transition period (r = −0.78, p < 0.001) but becomes statistically insignificant in the New Arctic regime. Sea ice motion speed exhibits an overall accelerating trend, which extends from the marginal seasonal ice zones toward the high-latitude multi-year ice regions, accompanied by a notably enhanced sensitivity of sea ice motion to wind forcing. Sea ice volume flux through the Fram Strait is primarily controlled by ice motion speed, whose contribution to the flux is approximately 2.6 times that of ice thickness. The recovery of ice drift speed offsets the thinning of sea ice cover, leading to a partial rebound in volume flux during the New Arctic steady state. This study identifies the evolutionary patterns and drivers of Arctic sea ice thickness under the New Arctic regime, providing a scientific basis for further understanding the changes in the Arctic climate system and associated air–sea ice interactions. Full article

Wind energy is an important form of clean energy, and its rational utilization represents a crucial solution for mitigating the energy crisis and global warming. In this study, wind energy potential and its long-term changes in the South China Sea (SCS) are evaluated using ERA5 100 m wind data from 1944 to 2023, validated against ASCAT observations. High wind speeds and high wind power density (WPD) are concentrated southwest of Taiwan and southeast of Vietnam. Annual wind availability exceeds 6457 h across most regions, reaching up to 8283 h in optimal locations. WPD and capacity factor peak in winter (up to 2.4 × 10⁸ Wh·m⁻² and >50% capacity factor), with the most stable conditions occurring in the southwestern Taiwan Strait, southeast of the Pearl River Delta, and the Beibu Gulf. Empirical orthogonal function analysis reveals that the first mode of winter WPD accounts for 65.7% of the total variance, with a statistically significant increasing trend since 1990. The interannual variation in wind energy resources in the SCS during winter is controlled by the combined effects of sea surface temperature (SST) anomalies in the tropical Pacific and the Arctic Barents Sea. Specifically, in the years with strong wind anomalies in the SCS, mega-La Niña-type SST patterns in the tropical Pacific trigger anomalous cyclonic circulation in the SCS and the eastern Philippine Sea, while warm anomalies in the Arctic Barents Sea surface drive a wave-like structure of “anticyclone–cyclone–anticyclone” from Siberia to South China. The coupling of the two systems jointly promotes the strengthening of the South China Sea monsoon, leading to increased wind speeds and elevated WPD in the northern SCS. These findings provide a scientific basis for wind farm siting and long-term operational planning in the region. Full article

The effects of environmental factors on zooplankton within the marginal ice zone (MIZ) of the Barents Sea remain poorly understood. To address this knowledge gap, we investigated mesozooplankton communities across the central, northern, and northeastern regions in April 2016. Abundance and biomass ranged from 90 to 997 individuals m⁻³ and from 1.1 to 48.6 mg dry mass m⁻³ (0.3 to 13.6 g dry mass m⁻²), respectively. Oithona similis was the most abundant taxon, while calanoid copepods, including Calanus spp., Metridia longa, and Pseudocalanus spp., dominated total biomass. The spatial distribution of mesozooplankton communities was closely linked to the physical properties of water masses. Cluster analysis identified two distinct assemblages associated with Polar Front Water and Arctic Water. Redundancy analysis and generalized linear models identified temperature, mean salinity, mean chlorophyll a concentration, and sea ice concentration as significant predictors of abundance and biomass. The dominance of older life stages within major copepod taxa indicated a winter status for the mesozooplankton community. Regional and temporal comparisons of mesozooplankton biomass with prior May–June data from central and northwestern areas highlighted higher productivity in the northern and northeastern MIZ. This increase is potentially related to the warming trends observed in the Arctic since the 2000s. Our research provides novel insights into Arctic marine zooplankton assemblages and serves as a valuable baseline for future ecological monitoring and modeling of the Barents Sea ecosystem in the context of global climate change. Full article

Arctic–boreal wetlands and lakes are among the most significant and most uncertain natural sources of atmospheric methane. Rapid Arctic amplification, permafrost thaw, hydrological change, and increasing ecosystem productivity are expected to intensify methane emissions from high-latitude landscapes. Yet, significant uncertainties persist in quantifying their magnitude, seasonality, and spatial distribution. This review synthesizes the current state of the art in monitoring methane emissions from Arctic–boreal wetlands and lakes through complementary bottom-up and top-down approaches. We examine Earth observation (EO) capabilities, including optical, thermal infrared (TIR), and synthetic aperture radar (SAR) missions, as well as new emerging satellite platforms. We also assess in situ measurement networks, wetland and lake inventories, empirical and process-based models, and atmospheric inversion frameworks. Key gaps remain in representing small waterbodies, shoreline heterogeneity, winter emissions, inventory harmonization, and integration between atmospheric retrievals and surface-based flux models. Moreover, advances in multi-sensor data fusion, explainable artificial intelligence (XAI), physics-informed inversion methods, and geospatial foundation models offer strong potential to reduce these uncertainties. A coordinated integration of satellite observations, field measurements, and transparent modeling frameworks is essential to improve Arctic–boreal methane budgets and strengthen projections of climate feedback in a rapidly warming region. Full article

Glaciers in the Canadian Arctic Archipelago (CAA) contribute significantly to sea-level rise, yet sparse in situ data limit regional climate assessments. This study presents the first decadal (2013–2024) satellite-derived time series of late-summer snowline altitude (SLA) for six CAA glaciers, utilising 9920 Landsat 8/9 and Sentinel-2 scenes. Glacier surface cover types (snow and bare ice) were mapped via machine learning, and SLA was extracted using elevation-binning and Snow-Elevation Histogram Analysis (SEHA). Elevation data were obtained from ArcticDEM v3; positive degree days (PDD) from Eureka, Pond Inlet, and Pangnirtung were used to characterize melt-season forcing. Satellite-derived SLA was validated against equilibrium-line altitude (ELA) observations from White Glacier. All glaciers exhibit a characteristic seasonal SCA cycle: maximum extent in June, minimum in August, and partial recovery in September, with extreme anomalies in 2020. Annual peak SLA correlates positively with summer warmth; sensitivities to PDD were 2.56, 0.67, and 0.83 m (°C d)⁻¹ for White, Highway, and Turner glaciers, respectively. Hypsometry strongly modulates climatic sensitivity: glaciers with limited high-elevation area (e.g., BylotD20s, Turner) frequently lose their accumulation zones in warm years. At White Glacier, SLA replicates interannual ELA variability with high correlation and lower error using the elevation-bin method (mean bias +53 m; RMSE 177 m) compared with SEHA (+165 m; 339 m). Meteorological records indicate significant summer and winter warming at Eureka, with increasing PDD; precipitation trends are spatially variable. A regionally calibrated, quality-assured elevation-bin method produces objective and transferable SLA time series, suitable for ELA estimation in data-sparse Arctic settings. The SLA–PDD relationship and hypsometry-dependent responses highlight increasing stress on accumulation zones under continued warming. Reporting SLA uncertainty and image quality, alongside expanded field observations, will enhance Arctic-wide glacier monitoring. Full article

Arctic regions are experiencing accelerated environmental change, yet integrated assessments of terrain-scale responses remain limited. This study quantifies the spatial-temporal variability of glaciers, shorelines, and outwash plains in Kaffiøyra, Svalbard, Norway, over four decades (1985–2023) using cross-evaluated Landsat and Sentinel imagery. Our results reveal systematic retreat across all eight glaciers (R² = 0.83–0.96), with tidewater glaciers experiencing substantially greater terminus area loss (62.8% and 72.1%) compared to land-terminating glaciers (34.5–69.0%). Coastal changes were highly variable: erosion (up to −3.2 m/yr) was most pronounced on shores exposed to southwesterly summer waves, while significant accretion (+13.0 m/yr) occurred near the tidewater glacier terminus. The insignificant outwash changes (−6.4% to +2.7%) despite substantial land-terminating glacier retreat indicate these systems respond to different controls. A moderate negative correlation between glacier terminus area and summer temperatures (r = −0.55 to −0.69) enabled a simple projection model. Diagnostic projections to 2020–2039 showed that both downscaled climate models and extrapolated local data overestimated retreat. However, extrapolated local data proved more accurate, with its projection gap averaging 11% for land-terminating and 46% for tidewater glaciers. The study provides crucial insights into Arctic terrain behaviors, highlighting complex and divergent responses. These findings emphasize the need for enhanced localized monitoring systems through ongoing high-resolution image surveys and planned modeling to understand accelerating polar environmental changes. Full article

This study investigates whether long-term global warming is associated with fertility decline across 195 countries from 1960 to 2023, and whether this relationship varies by economic development and adaptive capacity. We analyze Total Fertility Rate (TFR) data from the World Bank alongside temperature anomaly measures from NOAA and NASA using Pearson correlations and ordinary least squares (OLS) regression models. Regional analyses include Africa, Asia, Europe, the Middle East, and the Arctic, with GDP per capita serving as a proxy for economic development and adaptive capacity. Globally, temperature anomalies and fertility exhibit a strong negative correlation ($r\approx -0.90$, $p<0.001$). However, substantial regional heterogeneity emerges after controlling for GDP. In Africa ($r=-0.89$) and the Middle East, temperature anomalies remain statistically significant predictors of fertility decline even after GDP adjustment ($\beta =-0.99$, $p<0.001$; $\beta =-1.27$, $p<0.001$, respectively). In contrast, temperature effects become statistically insignificant in South Asia, East Asia, Europe, and the Arctic once GDP is controlled, indicating that fertility decline in these regions is driven primarily by socioeconomic modernization rather than climatic stress. These findings suggest that global warming functions as a conditional demographic stressor whose impact depends critically on adaptive capacity. In regions with limited infrastructure, including constrained access to air conditioning, healthcare, and occupational heat protection, rising temperatures remain significant predictors of fertility decline, potentially mediated through heat-sensitive biological mechanisms such as impaired spermatogenesis. By contrast, in higher-income regions, high adaptive capacity appears to buffer reproductive systems from thermal stress, allowing socioeconomic factors to dominate fertility dynamics. Full article

For the last three summers in Canada (2023–2025), and episodically in Siberia over the previous decade and a half, severe consequences from wildfires represent major ecological and societal impacts: the displacement of inhabitants; destruction of buildings, timber and infrastructure; and far-field air pollution. Wildfire occurrence is increasingly supported every summer by persistent surface warming and widespread atmospheric moisture deficits. The two recent major Canadian fire years in 2023 and 2025 show some contrasts: 2023 was dominated by an early June event with preconditioning, whereas 2025 saw repeated single events spanning June to early August, culminating in a significant late-summer event. Events in both years were associated with North Pacific–North American atmospheric blocking regimes. Over the longer term, 2003–2025, normalized June–September wildfire fraction anomalies in the Canadian sector (45–60° N, 150–60° W) show the post-2023 period as having new, clear, record-breaking fire intensities, highlighting wildfires as emerging dominant Arctic–subarctic extremes. Siberia shows an increase after 2010. Although multiple environmental Arctic–subarctic extremes are ongoing—such as sea-ice loss, storms, and glacial ice loss—the impacts from wildfires represent preeminent, growing societal consequences. Full article

Rabies is an acute, progressive, viral encephalitis. Warm-blooded vertebrates are susceptible. Major reservoirs reside in the Chiroptera and Carnivora. Among the latter, representatives include dogs, ferret badgers, foxes, jackals, mongooses, raccoons, and skunks. Within the Carnivora, pinnipeds represent a diverse group of >30 extant species. These marine mammals range from the Arctic to Antarctica, but there is no review about rabies in this group. Apparently, only a single 1980 case of rabies occurred from Svalbard in a ringed seal (Phoca hispida). However, in 2024, incidental cases appeared within South African Cape fur seals (Arctocephalus pusillus). Retrospective testing of archival material identified suspect cases dating back to 2022. Currently, more than 80 cases have been documented in seals. Moreover, a new 2025 focus appeared in Namibia and cases in Angola are predictable. Viral characterization supports spillover infection via rabid black-backed jackals (Lupulella mesomelas). A host shift appears likely, with ongoing seal intraspecific transmission. Given the unique nature of this epizootic, implications for the southern hemisphere abound. Unfortunately, comprehensive data are lacking on pinniped specimens examined outside of southern Africa. For example, although Antarctica is considered ‘rabies-free’, minimal international standards for support are unmet. No routine laboratory-based surveillance occurs. This enzootic rabies focus among seals in southern Africa presents unique challenges for the region and a rare opportunity for considering broader surveillance. Besides targeted parenteral vaccination of fur seals, local engagement involves vagrant species, including elephant (Mirounga leonina) and leopard seals (Hydrurga leptonyx). The void of regional pinniped surveillance, especially encompassing the Southern Ocean would require considerable proactive local resolution and much wider collaboration regarding future concerns to both public health and conservation biology. Full article

This paper explores the intertwined relationship between food systems and climate change, emphasizing their role in achieving the global target of limiting warming to 1.5 °C above pre-industrial levels. Food systems contribute significantly to greenhouse gas emissions; approximately 30% of global CO₂ emanates from agricultural practices, livestock production, and export-oriented supply chains. Conversely, climate change disrupts food production via rising temperatures, sea-level rise, and water scarcity, particularly in vulnerable regions such as Namibia and other parts of the Southern Hemisphere. In contrast, the European Arctic faces unique opportunities and challenges. This paper highlights mitigation and adaptation strategies, including smart agriculture technologies and genetic crop engineering. Behavioural shifts toward plant-based diets and strengthening local food systems are identified as critical for reducing emissions and enhancing resilience. Furthermore, the value of Indigenous knowledge and traditional food systems, which promote biodiversity, minimize fossil fuel use, and offer climate-resilient crops, is highlighted. Institutional capacity and governance frameworks are pivotal for implementing these solutions. The authors advocate for co-production of knowledge between the Northern and Southern Hemispheres, ensuring equitable adaptation rather than one-way technology transfer. Ultimately, integrated strategies combining technological innovation, policy reform, and cultural resilience are essential to break the cycle between food systems and climate change, fostering global cooperation toward the 1.5 °C goal. Full article

“Rotten” sea ice, ice in an advanced stage of melt, represents an important but understudied habitat in the rapidly changing Arctic. As Arctic warming accelerates, this late-season ice type will become more prevalent, yet little is known about its microbial inhabitants or their roles in Arctic marine biogeochemical cycles. We examined microbial communities (prokaryote and algal abundance, 16S and 18S rRNA gene and transcript sequencing) and biogeochemical properties of rotten sea ice and earlier-season ice near Utqiaġvik, Alaska, USA. Rotten ice was comparatively warm, isothermal, and largely drained of brine, with extensive, interconnected pore networks linked to melt ponds above and seawater below. Unlike earlier-season ice, fluids saturating rotten ice were vertically homogeneous in pH, dissolved inorganic carbon, prokaryote and phytoplankton abundance, and microbial community composition. However, particulate carbon and nitrogen exhibited strong vertical gradients, with the highest concentrations near the surface. Microbial communities in rotten ice were significantly different from those in earlier-season ice and varied between individual floes. These findings indicate that rotten ice constitutes a distinct microbial habitat and may serve as an important source of nutrient-rich particulate matter in the future Arctic Ocean during the summer melt season. Full article

The main objective of this work is to characterize Sudden Stratospheric Warming (SSW) conditions and their impact on local weather forecasting and climate change, using SSW definition criteria. The SSWs strongly affect Arctic vortex structure and midlatitude weather conditions. This work evaluates the frequency, amplitude, and dynamical–thermal characteristics of SSWs under historical and Representative Concentration Pathway (RCP) 4.5 scenarios, focusing on stratospheric air temperature (T_s) and zonal wind speed (U_h) at the 10° N and 60° N latitudes. The fifth-generation ECMWF atmospheric reanalysis (ERA5) is employed as the reference dataset. Simulations of five Coupled Model Intercomparison Project Phase 5 (CMIP5) models, represented by M1 to M5, are analyzed. The primary group of models included 1) the Australian Community Climate and Earth-System Simulator, version 1.3 (ACCESS1-3, M1), 2) the Hadley Center Global Environmental Model, version 2—Carbon Cycle (HadGEM2-CC, M2), and 3) the Max Planck Institute Earth System Model—Medium Resolution (MPI-ESM-MR, M3). The analysis period covers SSW events related to the Quasi-Biennial Oscillation (QBO) in the Northern Hemisphere (NH) from 1980 to 2100. The key findings indicate that while M1, M2, and M3 simulate SSW occurrence correctly for the 21st century, they exhibit significant systematic deficiencies in capturing the structural dynamics of SSW events. Specifically, the M1, M2, and M3 models underestimate the polar stratospheric temperature amplitude (T_amp) by approximately 75–80% and zonal wind amplitude (U_amp) by more than 60% compared to the ERA5 analysis. Furthermore, ERA5 exhibits a strong negative correlation (R ≈ −0.8) between U_h and T_s that is not estimated accurately using the present models. The importance of the horizontal resolution of the models and wave–mean flow interactions in determining SSW intensity and occurrence is also found to be a critical metric. Results suggest that SSW definition criteria affect Arctic and midlatitude weather system prediction at a rate of 61–82%. It is concluded that the primary configurations of CMIP5 models for accurately capturing the dynamical structure and evolution of QBO–SSW interactions are needed, and that they affect future projections of SSW events. Full article

Background/Objectives: Arctic foxes (Vulpes lagopus) exemplify the vulnerability of Arctic species to global warming and anthropogenic impacts, including habitat loss, interspecific competition with temperate species, pollution (chemical and biological), and declining prey abundance. Despite their ecological importance, the evolutionary and demographic history of the species is still incompletely understood, and the colonization history of isolated island populations, such as the one on Iceland, remains unresolved. Methods: We analyzed 80 mitochondrial genomes from across the Holarctic, including 22 Icelandic individuals. We combined phylogenetic reconstruction, coalescence-dating, haplotype network analysis, and diversity metrics to infer matrilineal relationships and colonization history. Results: Seven distinct haplogroups (Hg.1–Hg.7) were identified, which diverged ≥65 thousand years ago (kya). Two haplogroups were broadly distributed across Fennoscandia, Russia, Iceland, and Canada, while others were region-specific: two in eastern Russia (respectively diverging ~171 kya and ~89 kya), one in central Russia (~66 kya), and two in Iceland (~95 kya and ~66 kya). Three haplogroups were detected in Iceland, and at least four unrelated founding females are required to explain the current matrilineal diversity. One haplogroup contained sufficient representatives for molecular dating, yielding a minimum colonization age of ~5600 years, assuming in situ diversification. Observed matrilineal diversity in Iceland does not uniquely identify a single geographic source. Conclusions: Arctic foxes’ distribution and diversity reflect repeated cycles of isolation and expansion as circumpolar environments shifted. Broader sampling across the Nearctic is critical to clarify the timing, sources, and routes of Iceland’s colonization, as Nearctic sampling was limited to a single Canadian mitogenome. Full article

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment. Full article