Search Results (141)

Small and medium-sized (SMS) lakes in cold–arid regions are highly sensitive to climate change and play critical roles in regional hydrological and ecological processes. However, their long-term dynamic evolution along aridity–humidity gradients remains insufficiently understood. This study aims to reveal the spatiotemporal variations in SMS lakes on the Inner Mongolia Plateau and clarify their climatic driving mechanisms. Based on Landsat imagery and meteorological data (1984–2021) on the Google Earth Engine (GEE) platform, this study quantified the spatiotemporal variations in SMS lakes and adopted an ecological–geographical zoning framework to characterize lake responses across aridity–humidity gradients. Results indicate that, from 1984 to 2021, the total area of SMS lakes showed an insignificant linear trend but a net increase of 117% (396.50–860.33 km²), while the lake number increased by 155%, with 59 new lakes. The dynamics followed four stages: expansion (1984–1993), fluctuation (1994–2002), low-level stability (2003–2011), and recovery (2012–2021). Notably, recovery levels remained below the pre-2003 peak, with 2003 identified as a critical turning point. Lake numbers responded to climatic stress earlier than area changes. Spatially, lake variations in arid regions were primarily controlled by energy-related factors (e.g., temperature and potential evapotranspiration), while lake changes in semi-humid regions were dominated by precipitation-regulated water availability. Semi-arid regions presented transitional characteristics constrained by both energy and water factors. Although extreme weather events did not dominate long-term lake evolution, they significantly exacerbated short-term lake fluctuations. Overall, the controlling mechanism of SMS lakes shifted from energy limitation to water regulation under ongoing climate warming, highlighting pronounced regional differences in climate–lake interactions. Full article

Extreme high-temperature events driven by global climate change are occurring with increasing frequency, posing a serious threat to the stability of aquatic ecosystems. The Tibetan schizothoracin (Gymnocypris eckloni), a cold-water fish species endemic to the Qinghai–Tibet Plateau, is highly sensitive to temperature fluctuations and serves as an ideal model for studying the effects of climate change on fish. As a key organ for fish to perceive environmental changes, the gills’ comprehensive response mechanism has not yet been fully elucidated. This study investigated the effects of acute heat stress on the gill tissue of G. eckloni. The results showed that acute heat stress caused severe histopathological damage in the gills, including lamellar curling, epithelial cell detachment, and edema, with a significant increase in apoptosis. Biochemical analysis revealed elevated levels of cortisol, glucose, and ATPase activity in serum, as well as increased MDA content and CAT activity in the gills. Transcriptomic analysis identified 2304 DEGs. Upregulated DEGs were significantly enriched in pathways related to inflammatory response, TNF signaling, ferroptosis, and apoptosis, while downregulated DEGs were primarily involved in peroxisome metabolism, cell cycle, and steroid biosynthesis. This study confirms that acute heat stress induces structural damage and functional impairment in the gills by activating inflammatory and apoptotic pathways and disrupting redox homeostasis. It elucidates the immediate molecular and physiological responses of G. eckloni gills to acute heat stress. Follow-up experiments will be conducted at multiple time points, across different temperature gradients, and under chronic stress conditions to gain a more comprehensive understanding of the adaptive potential of high-altitude fish to climate warming, thereby providing a scientific basis for the development of conservation strategies. Full article

The Northern Tibetan Plateau is among the most climate-sensitive alpine regions globally. To address the limited applicability of the traditional Remote Sensing Ecological Index (RSEI) in sparsely vegetated areas, this study developed a Soil-Adjusted Remote Sensing Ecological Index (SRSEI) tailored to cold and arid environments. The ecological quality of the Northern Tibetan Plateau from 2000 to 2025 was systematically evaluated and analyzed. The results indicate that: (1) The improved SRSEI achieved a first principal component (PC1) contribution of 72.76%, a significant enhancement over traditional models that effectively mitigates noise from soil backgrounds and anthropogenic features. (2) Between 2000 and 2025, ecological quality was predominantly moderate, following a characterized east-to-west declining spatial gradient. Overall mean SRSEI values fluctuated between 0.420 and 0.476, exhibiting a marginal downward trend. (3) Ecological degradation affected 50.17% of the region, with 26.14% facing risks of sustained decline. Conversely, 40.11% of the area displayed potential recovery trends, suggesting potential spatial divergence in future ecological trajectories. (4) Regional ecological dynamics are governed by a topographic-thermal compound driving mechanism. Elevation (DEM), temperature (TEMP), and surface shortwave radiation (SRAD) emerged as the dominant explanatory variables. Furthermore, dual-factor interactions exhibited significant enhancement effects, while the influence of anthropogenic factors was comparatively weak at the regional scale. These findings provide a scientific basis for the long-term monitoring of fragile alpine ecosystems and the strategic development of the Qiangtang National Park. Full article

Land-use/land-cover change (LULC) fundamentally alters regional ecosystem service provisioning, necessitating multi-scenario simulations coupled with multi-objective optimization (MOP) to inform territorial spatial governance. This study develops an integrated PLUS-InVEST-MOP framework to simulate land-use dynamics and their ecological consequences in the Haibei Tibetan Autonomous Prefecture, a critical ecological barrier on the northeastern Qinghai–Tibet Plateau. Utilizing GlobeLand30 data (2000–2020), we projected 2030 land-use patterns under four scenarios (natural development, ecological conservation, economic development, and climate change) and quantified spatiotemporal variations in carbon storage and habitat quality. Results showed that grassland degradation accelerated during 2010–2020, with 1202.43 km² converted primarily to bare ground, contrasting with restoration gains observed in 2000–2010. Elevation emerged as the predominant natural driver of glacial and forestland expansion, whereas demographic and economic factors governed land encroachment on artificial surfaces. Under the climate change scenario, habitat quality declined by 3.78% (to 0.596), and carbon storage decreased by 70.04 Tg relative to 2020, underscoring the vulnerability of alpine ecosystems to warming. Conversely, the MOP-optimized scenario achieved synergistic improvements in carbon sequestration (+1.8% vs. 2020) and habitat quality (+2.3% vs. 2020) while adhering to arable land preservation targets (≥54,800 ha) and constraints on artificial surfaces. These findings provide quantitative decision support for balancing ecological conservation and sustainable development in high-altitude cold regions. Full article

In the construction of conventional concrete high arch dams in high-altitude regions with large temperature variations, the prolonged and cold winters often force the suspension of concrete pouring, severely constraining the overall schedule. To address this limitation, this paper breaks away from the conventional winter-shutdown scheme by proposing a new technique: continuous construction under low-temperature conditions. It can adapt to large temperature variations, and this study develops a corresponding construction schedule simulation model for quantitative evaluation and scheme optimization. First, the influence of large diurnal temperature variations on high-altitude concrete pouring was analyzed. Based on this, a dynamic pouring technique for sub-blocks is proposed—thin-layer pouring during positive temperatures and insulation curing during negative temperatures—with the aim of transforming discrete climatic windows into a continuous construction period. Second, to accurately simulate this complex spatial partitioning and temporal scheduling process, a customized schedule simulation model based on discrete-event simulation (DES) theory was developed. The model incorporated meteorological recognition at low temperatures, dynamic dam-block partitioning, and sub-block pouring scheduling. Finally, a high arch dam on a plateau in Southwest China was used as an engineering case to compare two construction schemes: the low-temperature shutdown scheme and the continuous construction scheme. After validating the simulation model under parameter assumptions such as ideal resource availability and stable annual climate patterns, the results showed that the continuous construction scheme achieves a monthly average pouring volume of 33,721 m³ during the period with large diurnal temperature variations, which accounts for 42.48% of the average monthly pouring volume during the normal construction period. Compared to the low-temperature shutdown scheme, the coefficient of variation of the monthly pouring intensity decreases by about 40%, and the total construction period is shortened by approximately ten months. This demonstrates the potential for schedule optimization for continuous winter construction in simulation. Full article

Global climate change has altered temperature regimes, hydrological stability, and redox dynamics in inland waters, yet the continental-scale impact of these alterations on sediment microbiomes remains poorly understood. Here, we compiled 562 publicly available 16S rRNA gene datasets from lake sediments across five major climatic zones in China to examine how climatic gradients influence microbial diversity, community assembly, and interaction networks, as well as their associated taxonomic composition and environmental responses. Sediment microbiomes showed clear spatial differentiation in both α- and β-diversity, accompanied by climatic zone-specific taxonomic signatures and biomarker taxa. Community assembly also varied markedly across climatic zones, with stochasticity and dispersal limitation dominating in colder regions, transitional assembly in the south temperate zone, and stronger selective or high-turnover dynamics in the warm subtropics. Importantly, random forest models revealed a clear transition from climate-dominated to anthropogenic-dominated control in sediment microbiome organization: microbial variation in the plateau and temperate regions was primarily associated with climatic and geographic constraints, whereas anthropogenic factors played a more important role in shaping community differentiation in the central subtropical zone. By integrating diversity patterns, taxonomic composition, assembly processes, and network topology, we further propose a three-stage conceptual pattern of sediment microbial community organization along climatic gradients, shifting from a persistence-dominated regime in the cold plateau regions, to an efficiency-dominated regime in the temperate zones, and finally to a plasticity-dominated regime in the warm subtropical regions. These findings would provide a continental-scale framework for understanding sediment microbiome responses to coupled climatic and anthropogenic forcing in inland waters, with implications for future water quality management and ecosystem conservation. Full article

The Source Region of the Yangtze River is a high-altitude area with extensive permafrost on the Tibetan Plateau. While temperature, precipitation, and radiation significantly affect vegetation phenology, the influence of permafrost changes remains unclear. Using the daily Long-term Seamless NOAA AVHRR NDVI Dataset of China (2003–2022), we extracted the start (SOS) and end (EOS) of the growing season in the Source Region of the Yangtze River (SRYR). Soil thawing date (SOT) was obtained from freeze–thaw state products, while active layer thickness (ALT) was estimated using the Stefan model based on MODIS land surface temperature (LST). Partial least squares regression and mediation analysis quantified the direct and indirect effects of permafrost degradation. Results show: (1) The end of the growing season (EOS) became significantly earlier in 64.33% of the region, while the start of the growing season (SOS) showed little change. (2) The effect of SOT on SOS depends on moisture conditions. Earlier SOT leads to earlier SOS in wetter areas by supplying meltwater, but delays SOS in cold–dry areas by increasing soil water loss. (3) Thicker ALT strongly promotes earlier EOS, accounting for up to 42.61% of EOS variation in cold–dry zones, because a deeper active layer potentially promotes downward movement of water, which may further lead to the potential leaching of nutrients from the shallow root zone, limiting resources for shallow-rooted plants. (4) Alpine meadows respond more strongly to permafrost changes than alpine grasslands. Overall, water loss caused by permafrost degradation may reduce the potential lengthening of the growing season under climate warming, highlighting the key role of soil water in linking permafrost and vegetation dynamics. Full article

Hippophae tibetana Schltdl. is a cold-tolerant deciduous shrub endemic to the Tibetan Plateau, playing a vital ecological role in high-altitude environments. This study utilized the Biomod2 platform to model its current and future potential distribution under climate change, integrating 34 environmental variables across bioclimatic, topographic, edaphic, anthropogenic, and ultraviolet (UV) dimensions. Among ten candidate species distribution models (SDMs), the random forest (RF) algorithm exhibited the highest predictive accuracy and stability. An ensemble model (EM) combining RF, GBM, MARS, and FDA further improved predictive performance (ROC = 0.992, TSS = 0.923, and Kappa = 0.886). Key determinants of habitat suitability included altitude, temperature, UV radiation, and biodiversity, with RF response curves revealing distinct nonlinear thresholds. Optimal suitability occurred at around a 4000 m elevation, decreasing beyond this range, while temperature and UV exhibited similar unimodal responses. Under the SSP2-4.5 climate scenario, the suitable habitat is projected to expand from the 2050s to the 2090s, particularly in eastern Qinghai, southwestern Gansu, northwestern Sichuan, and central–southern Tibet. The species’ distribution centroid is anticipated to shift southwestward toward Qinghai Province, with more rapid migration projected after the 2050s. These findings underscore the complex interplay of environmental factors shaping H. tibetana distribution and offer valuable insights for conservation planning in the ecologically fragile Tibetan Plateau. Full article

Controlling operation-stage carbon emissions (CE) from transport buildings is crucial for China’s dual-carbon goals and the ecological security of the Qinghai–Tibet Plateau (QTP), and the sustainable development of plateau transport infrastructure. For plateau railway passenger stations (RPS), limited monitoring and distinctive high-altitude, cold-climate operations make daily CE prediction difficult with conventional measurement- or simulation-based methods. This study develops a machine-learning approach based on a Monte Carlo synthetic database and derives engineering-standard formulas for direct use. Building scale, meteorology and passenger flow volume (PFV) were compiled for 12 representative RPS, and a large synthetic database of daily carbon emission was generated under multiple distribution constraints. With daily mean temperature, heating degree days, altitude, station floor area and PFV as inputs, four models were trained and assessed using mean absolute error, root mean square error, mean absolute percentage error (MAPE) and R². The results show that random forest (RF) performed best, achieving ~6% MAPE and R² > 0.99 on the test set, and markedly lower errors than multivariable linear regression. Interpretation of RF via feature importance and partial dependence shows that floor area, altitude and PFV dominate emissions and exhibit nonlinear response patterns. To improve transparency and transferability, ridge regression was used to fit a linear surrogate to RF predictions, producing engineering-standard formulas for daily and annual operation-stage CE. The formulas retain most predictive accuracy while requiring only readily obtainable variables, enabling rapid estimation and scenario analysis for cold, high-altitude RPS. The proposed workflow provides a replicable pathway for operational CE assessment in data-scarce regions and supports low-carbon planning, design and operation of RPS on the QTP, thereby contributing to more sustainable infrastructure development in high-altitude regions. Full article

The terrain and climate of the Qinghai–Tibetan Plateau make it hard to assess satellite precipitation. GSMaP (Global Satellite Mapping of Precipitation) is a widely used rainfall dataset, but direct comparisons of its versions and products over the Plateau are still limited. In this study, we evaluate four GSMaP products—Gauge, GNRT, MVK and NRT—across four versions (v05–v08) using daily station precipitation data from 2001 to 2022 as the reference. We assess both precipitation amount and precipitation event detection. The analysis is carried out at the station scale and then examined by month, season, year, rainfall intensity and space. We also compare regional patterns across the Plateau. The results show that GSMaP performance generally improves in later versions. Among them, v08 is usually more stable and more consistent, especially for gauge-corrected products. This improvement appears not only in better agreement with station data but also in smaller differences among stations for some products. Still, the size of the improvement is not the same for all products, seasons, rainfall classes and regions. The improvement is more clear in wetter areas and in warm seasons. By contrast, uncertainty is still relatively large in cold seasons, under strong rainfall and in the high-elevation interior of the Plateau. Non-gauge products also show wider variation than the Gauge product, which suggests that gauge correction still plays an important role in improving consistency. In general, version updates help improve GSMaP performance under some conditions, but the gains are not the same across different climate settings, rainfall intensities, or elevation zones. This study provides a systematic evaluation of GSMaP over the Qinghai–Tibetan Plateau for 2001–2022 and offers practical support for choosing and using GSMaP products in complex terrain. Full article

As key headwater regions of the upper Yangtze River, the Yalong and Dadu River basins are expected to experience highly uncertain hydrological responses under climate warming. However, the nonlinear and spatially heterogeneous evolution of streamflow across multiple time-frequency scales remains insufficiently understood. In this study, a SWAT model driven by CMIP6 climate projections under four shared socioeconomic pathways (SSP1-2.6 to SSP5-8.5) was coupled with multivariate wavelet coherence, spatial wavelet transform, and change-point detection methods to investigate the spatiotemporal evolution of streamflow and extreme risks during 2017–2100. Results indicate that precipitation is the primary driver of streamflow variability, with streamflow responding rapidly, while air temperature mainly regulates seasonal intensity via snowmelt. Streamflow seasonal intensity exhibits a northwest-southeast gradient, with low variability upstream and high sensitivity downstream, reflecting precipitation-concentrated, forested canyons where rapid lateral flow and dry-season evapotranspiration amplify flow contrasts. Moreover, hydrological nonstationarity and extreme risks are projected to intensify, with structural regime shifts emerging in the 2040s–2050s and extreme high-flow magnitudes doubling under SSP5-8.5, accompanied by more frequent drought-flood alternations. These findings highlight an upstream buffering-downstream sensitivity pattern, emphasizing the need for spatially differentiated water resources management under nonstationary climate conditions. Full article

Understanding the Holocene environmental history of desert landscapes in northern China contributes to elucidating the mechanisms driving desertification in the mid-latitudes of the Northern Hemisphere (NH). Based on a systematic and comparative analysis on integrated paleoclimatic data from both China and the international community, this paper reviews the environmental evolution history of the Alashan Plateau since the Holocene, drawing upon sedimentary and proxy records from three major sandy deserts on the plateau—the Badanjilin, Tenggeli, Wulanbuhe Deserts. The results indicate that the Alashan Plateau experienced generally humid conditions during the early and middle Holocene, characterized by the development of high-level lakes; in contrast, the late Holocene was marked by aridity and intensified aeolian activity. For the three deserts on the plateau, the environmental evolution of the Tenggeli Desert during the early Holocene diverges from that of the other two. Meanwhile, the mid-Holocene drought event in the Badanjilin Deserts remains debated, centering on whether its spatial scale was local or regional across the plateau. The driving mechanism of environmental evolution in the study area can be fundamentally understood through the atmospheric and oceanic circulation systems, combined with solar insolation in the middle latitudes of NH. This interplay is comprehensively reflected by the interactions between the westerlies and the East Asian summer monsoon (EASM) across different periods. Responses of the Alashan Plateau’s climate to global change involve the combined effects of multiple factors, including the Westerlies, the EASM, the Atlantic-Pacific-Ocean (APO) circulation anomalies, the ‘third polar’ environmental effect of the Qinghai–Tibet Plateau, and the hydrological influence of the Yellow River, etc. The Holocene environmental evolution history of the study area was primarily shaped by climate patterns characterized by cold-dry and cold–wet (or temperate-moist) regimes. Understanding these patterns may provide insights for forecasting future climate trends in the Alashan Plateau under current global warming. Full article

Understanding the coupling mechanisms between vegetation phenology and carbon productivity is essential for assessing ecosystem responses to climate change and guiding sustainable grassland management. This study focuses on stable alpine grasslands on the southern slope of the Qilian Mountains from 2001 to 2020, a climatically sensitive but relatively under-investigated transition zone on the northeastern Tibetan Plateau. We utilized MODIS NDVI time-series (MOD13Q1) and the latest PML V2 gross primary productivity (GPP) product at 500 m resolution to quantify changes in the start (SOS), end (EOS), and length (LOS) of the growing season. A pixel-wise linear regression approach was applied to evaluate the sensitivity of GPP to phenological metrics, explicitly characterizing how much GPP changes in response to unit shifts in SOS, EOS and LOS. Compared with previous studies that mainly described large-scale correlations between phenology and GPP or relied on coarser GPP products, this study provides a pixel-level, sensitivity-based assessment of phenology–carbon coupling in alpine grasslands using a long-term, phenology–GPP dataset tailored to the Qilian alpine region. The results revealed trends of earlier SOS, delayed EOS, and extended LOS, accompanied by a gradual increase in GPP. However, phenology–GPP coupling exhibited notable spatial heterogeneity. In mid- and low-altitude areas, extended growing seasons enhanced GPP, whereas high-altitude zones showed limited or even negative responses, likely due to climatic constraints such as cold stress and thermal–moisture mismatches. To better understand these spatial differences, we constructed a three-dimensional phenology–GPP sensitivity space and applied k-means clustering to delineate three ecological functional zones: (1) high carbon sink potential, (2) ecologically fragile regions, and (3) neutral buffers. This sensitivity-based functional zonation moves beyond traditional correlation analyses and provides a process-oriented and spatially explicit framework for ecosystem service assessment, carbon sink enhancement and adaptive land-use strategies in sensitive mountain environments. Full article

The Tibetan Plateau is highly sensitive to global climate change and characterized by pronounced ecological fragility, making vegetation net primary productivity (NPP) a key indicator for assessing ecosystem functioning and regional ecological security. This study aims to characterize the spatiotemporal dynamics of NPP and to disentangle the multiple natural and land-use drivers shaping its variability across the Tibetan Plateau. MODIS-derived NPP data for the period 2001–2022 are integrated with multi-source datasets on climate, topography, normalized difference vegetation index (NDVI), and land use (CLCD), and analyzed using trend and correlation analyses, land-use transfer matrices, an optimal-parameter geographical detector, and partial least squares structural equation modeling (PLS-SEM). The results indicate that NPP exhibits a significant but fluctuating upward trend (0.52 gC·m⁻²·a⁻¹, p < 0.01), with higher values in the southeast and lower values in the northwest, the Yunnan Plateau evergreen broadleaf and pine forest region (VA5) and the southern Himalayan montane forest region (VA6) function as high-value centers, and regions such as the Kunlun high-cold desert region (HID1) represent low-value centers. The mutual conversion between forestland and grassland and bare land constitutes a key process driving regional NPP changes, with the net expansion of forestland making a substantial contribution to NPP increases (net gain of 2606.88 TgC). Geographic detector analysis indicates that NDVI (q = 0.741) and land use type (q = 0.741) are the primary factors governing the spatial differentiation of NPP, followed by precipitation, slope, and temperature. Moreover, interactions between any two factors enhance their explanatory power, with the interaction between aspect and land use type exhibiting the strongest effect (q approaching 1). PLS-SEM path analysis further quantifies the driving pathways, revealing that mean annual precipitation and land use type are the most direct drivers of NPP, while climatic and topographic factors influence NPP indirectly through their effects on vegetation cover and land use type. This study advances the understanding of the multifactorial driving mechanisms of ecosystem productivity on the Tibetan Plateau and provides a scientific basis for zoned and differentiated ecological restoration and climate adaptation strategies. Full article

Bark is a multifunctional organ critical for tree survival, yet its functional plasticity in response to micro-environmental heterogeneity at alpine timberlines remains poorly understood. Here, we investigated the variations in bark physical traits (thickness, density), allometric scaling, and stoichiometric characteristics (C, N, P) of Abies georgei var. smithii (Viguie & Gaussen) W. C. Cheng & L. K. Fu on contrasting sunny and shady slopes in the Sygera Mountains, southeastern Tibetan Plateau. Despite the relative homogeneity of soil physicochemical properties between slope aspects, bark traits exhibited remarkable phenotypic plasticity. Trees on the shady slope possessed significantly thicker bark with higher nitrogen concentrations, adopting a “resource-acquisitive strategy”. Standardized Major Axis (SMA) regression indicated isometric scaling ($b\approx 1.03$) for trees on the shady slope, reflecting a sustained investment in bark thickness to provide thermal insulation against cold stress. Conversely, trees on the sunny slope exhibited negative allometry ($b \approx 0.87$), characterized by denser tissues and elevated C/N ratios. This shift represents a conservative strategy geared toward hydraulic safety and resistance to high radiation and evaporative loss. Crucially, our results show that bark traits are largely decoupled from soil nutrient gradients, being shaped instead by microclimate. The distinct trade-off—prioritizing insulation on shady slopes versus conservation on sunny slopes—underscores the importance of phenotypic plasticity for the persistence of timberline species in a changing climate. Full article