Average Warming Research Articles

Evaluating and Improving the Connectivity of China's Protected Area Networks for Facilitating Species Range Shifts under Climate Change

Contemporary climate change is causing spatial redistributions of many species, potentially undermining the effectiveness of existing protected areas (PAs). This raises concerns about whether current PAs are connected enough to capture climate-induced range shifts and how to expand PAs to support this ecological process. Hence, we conducted a national-scale assessment of climate connectivity for the terrestrial PAs across mainland China. We found that most PAs are structurally connected to cool ones through low human impact (LHI) areas along temperature gradients. The connected PA networks could enable species to migrate and avoid an average climate warming of 2.9°C under moderate emission scenario. Nevertheless, less than half (46.2%) of the PAs have achieved successful climate connectivity. To facilitate climate-induced range shifts, we identified priority areas for conservation based on their importance in supporting connections between PAs. Our study provides spatially explicit assessments of the connectivity of PA networks for range shifts and emphasizes the necessity to consider climate connectivity in the planning of PAs at regional scales.

150-year daily data (1870–2021) in lakes and rivers reveals intensifying surface water warming and heatwaves in the Pannonian Ecoregion (Hungary)

Study regionPannonian Ecoregion, Hungary. Study focusBridging the gap between atmospheric influences and aquatic environments, this study embarked on a comprehensive reconstruction of daily surface water temperatures across lakes and rivers within the Pannonian Ecoregion over an extensive period of 150 years (1870–2021). New hydrological insights for the regionThe analysis revealed a clear warming trend in waters over the past 150 years, and majority of this warming occurred in recent three to four decades (average warming rate: 0.317 °C/decade). Seasonal patterns indicated that winter and spring exhibited faster warming rates, followed by autumn and summer. There has been a significant increase in the number, duration, and intensity of heatwaves in both lakes and rivers, particularly pronounced in the last 30–40 years, and with the rise of air temperatures, river and lake heatwaves tend to intensity. These findings underscore the escalating impact of climate change on freshwater systems in the Pannonian Ecoregion, emphasizing the urgent need for mitigation measures. As the first study on river and lake heatwaves in Hungary and one of the few studies on river heatwaves worldwide, this study will provide reference for analysing extreme thermal events in aquatic systems.

Advances in breeding phenology outpace latitudinal and elevational shifts for North American birds tracking temperature.

Terrestrial species can respond to a warming climate in multiple ways, including shifting in space (via latitude or elevation) and time (via phenology). Evidence for such shifts is often assessed independent of other temperature-tracking mechanisms; critically, no study has compared shifts across all three spatiotemporal dimensions. Here we used two continental-scale monitoring databases to estimate trends in the breeding latitude (311 species), elevation (251 species) and phenology (111 species) of North American landbirds over 27 years, with a shared pool of 102 species. We measured the magnitude of shifts and compared them relative to average regional warming (that is, shift ratios). Species shifted poleward (1.1 km per year, mean shift ratio 11%) and to higher elevations (1.2 m per year, mean shift ratio 17%), while also shifting their breeding phenology earlier (0.08 days per year, mean shift ratio 28%). These general trends belied substantial variation among species, with some species shifting faster than climate, whereas others shifted more slowly or in the opposite direction. Across the three dimensions (n = 102), birds cumulatively tracked temperature at 33% of current warming rates, 64% of which was driven by advances in breeding phenology as opposed to geographical shifts. A narrow focus on spatial dimensions of climate tracking may underestimate the responses of birds to climate change; phenological shifts may offer an alternative for birds-and probably other organisms-to conserve their thermal niche in a warming world.

Addressing the Urgent Need for Direct Climate Cooling: Rationale and Options

Abstract Emissions reduction and removal are not proceeding at a pace that will limit global average warming to less than the Paris Agreement targets of 1.5 °C or 2.0 °C. Accelerating global warming is indicated by record high 2023-24 monthly temperatures and annual 2023 global mean surface temperatures around 1.5 °C above pre-industrial levels. Only direct climate cooling has the potential to avert continued temperature rise in the near term and moderate at least some projected climate change disruption including extreme weather, sea level rise, loss of sea ice, glacier and permafrost melting, and coral reef die-off. Strategically deployed at scale, starting in the near term, several cooling measures have the potential to reduce or reverse global warming. Others can exert local or regional cooling influences. The world needs an approach to climate change that extends beyond sole reliance on emission reductions and removal. We propose a) researching, field testing and deploying one or more large-scale cooling influence(s) perhaps initially in polar regions and applying local and regional cooling measures that also support adaptation, b) accelerating emissions reductions with an early prioritization of short-lived climate drivers, and c) deploying large scale carbon removal to draw down legacy greenhouse gas. The authors make no attempt to determine what measures or mix of measures is optimal. That will depend on modeling and experimentation. Only by including properly researched emergency cooling “tourniquets,” in the near-term to our “bleeding” Earth can we slow and then reverse ongoing and increasingly severe climate change in the 21st Century.

Temperature and dissolved oxygen trends in English estuaries over the past 30 years

Water temperature and dissolved oxygen are two important parameters which affect the ecosystem functions which estuaries provide. As such, we need to understand the long-term change of these parameters in English estuaries to better understand those areas which may be vulnerable in the present and future. Detecting these trends in monitoring data is difficult however, since temporally and spatially heterogeneous sampling has the potential to obscure any long-term component of change. In this study, we use a generalized additive model (GAM) approach to isolate the inter-annual change of water temperature and dissolved oxygen in spot sampled monitoring data across English estuaries. This technique can account for the potentially non-linear variability caused by temporal and spatial variations in sampling throughout the day and year. We find that water temperature in all modelled estuaries has warmed, with an average warming of 0.037 °C/yr between 1990 and 2022, in line with temperature change in rivers and the sea surface around England. For the same period, dissolved oxygen has increased for roughly half of modelled estuaries and decreased for the other half. The variation across English estuaries in these two conditions is best explained by the geographical location of an estuary. Many of the estuaries warming at the greatest rate are those where sea surface temperature increase has also been greatest. We suggest the observed distribution of changes in dissolved oxygen can be explained by three processes: (1) temperature driven change, (2) dissolved oxygen improvement (e.g., reduced nutrient inputs through wastewater management regulation) and (3) changes in the number of primary productivity-induced super saturation events. This study provides a comprehensive look at temperature and dissolved oxygen change across English estuaries over the past ∼30 years, which may provide information on the processes behind how these water quality parameters have changed and will continue to do so.

Assessing the Impact of Climate Change on Global Biodiversity: Trends and Predictions

Global warming which is as a result of human activities such as burning of fossil fuels and deforestation is a major threat to species diversity. This study is based on species in the climate change hotspots, using the SSDM, phenology, species traits, responses of ectotherms, and vegetation activity. We evaluate shifts in the distribution and numbers of species and their probabilities of dying out. An average Global warming of 1.1°C since the end of the nineteenth century has altered precipitation, deteriorated habitats, and increased the rate of species’ disappearance. If emissions are not reduced, 20-30% of species like the American Pika and many amphibians could be wiped out by end of the century. Phenological activities are taking place 2.5 days earlier per decade, which affects the balance of ecosystems. This study also stresses the importance of flexibility in conservation approaches like connecting the fragmented habitats, rehabilitating the disturbed ones, and the protection of ecological connectivity to reduce the impacts of climate change on species.

65% cover is the sustainable vegetation threshold on the Loess Plateau

Global temperatures will continue to increase in the future. The ∼640,000-km2 Loess Plateau (LP) is a typical arid and semi-arid region in China. Similar regions cover ∼41% of the Earth, and its soils are some of the most severely eroded anywhere in the world. It is very important to understand the vegetation change and its ecological threshold under climate change on the LP for the sustainable development in the Yellow River Basin. However, little is known about how vegetation on the LP will respond to climate change and what is the sustainable threshold level of vegetation cover on the LP. Here we show that the temperature on the LP has risen 0.27 °C per decade over the past 50 years, a rate that is 30% higher than the average warming rate across China. During historical times, vegetation change was regulated by environmental factors and anthropogenic activities. Vegetation coverage was about 53% on the LP from the Xia Dynasty to the Spring and Autumn and Warring States period. Over the past 70 years, however, the environment has gradually improved and the vegetation cover had increased to ∼65% by 2021. We forecast future changes of vegetation cover on the LP in 2030s, in 2050s and in 2070s using SDM (Species Distribution Model) under Low-emission scenarios, Medium-emission scenarios and High-emission scenarios. An average value of vegetation cover under the three emission scenarios will be 64.67%, 62.70% and 61.47%, respectively. According to the historical record and SDM forecasts, the threshold level of vegetation cover on the LP is estimated to be 53–65%. Currently, vegetation cover on the LP has increased to the upper limit of the threshold value (∼65%). We conclude that the risk of ecosystem collapse on the LP will increase with further temperature increases once the vegetated area and density exceed the threshold value. It is urgent to adopt sustainable strategies such as stopping expanding vegetation area and scientifically optimizing the vegetation structure on the LP to improve the ecological sustainability of the Yellow River Basin.

Nighttime Warming Reduced Copper Concentration and Accumulation in Wheat Grown in Copper-Contaminated Soil by Affecting Physiological Traits

The changes in biomass (including yield), copper (Cu) concentration, and the accumulation of wheat (Triticum aestivum. L) in response to soil Cu pollution under nighttime warming had still not been explored. Hence, this study was carried out, and these variations were analyzed from a physiological perspective. Pot trials were performed at two levels of ambient temperatures (no-warming (NT) and average nighttime warming of 0.28 °C (WT)) and two levels of soil Cu concentrations (control check without Cu application (CK) and 100 mg/kg Cu application (Cu)). Soil was collected from the carbonate cinnamon soil region of central China. The warming effects of the passive nighttime warming system were prominent, and the average increment was 0.28 °C. Antioxidant enzyme activities were promoted by warming (p < 0.05) and Cu. The highest yield was achieved in NT-Cu, mainly attributed to relatively strong root activity and photosynthesis caused by supplemental Cu, but the Cu concentration in its grains was close to the threshold (10 mg/kg) for Cu concentration in foodstuff and could present a potential food safety risk. Though nighttime warming did not increase the total biomass and yield of wheat, it decreased the Cu accumulation of wheat grown in Cu-contaminated soil, especially in grains. Moreover, WT-CK and WT-Cu increased the Cu concentration in the roots and glumes and reduced the Cu concentration in grains by 13.09% and 55.84%, respectively, probably because of a lower transpiration rate. Among them, the Cu concentration of grains in WT-Cu was the lowest and significantly lower than other applications. Our findings reveal that nighttime warming has the potential to reduce the Cu risk of grains in wheat grown in the Cu-contaminated carbonate cinnamon soil region of central China and could then provide a theoretical reference for risk assessment of food quality for wheat subjected to dual stress from nighttime warming and Cu pollution.

More to offer from the Montreal protocol: how the ozone treaty can secure further significant greenhouse gas emission reductions in the future

ABSTRACT Action under the Montreal Protocol has contributed to climate change mitigation for almost 35 years. The phase-out of ozone-depleting substances (ODS) has set the ozone layer on a path to recovery, protecting the world’s biosphere from harmful ultraviolet radiation. The 2016 Kigali Amendment to the Montreal Protocol is expected to avoid 5.6–8.7 gigatonnes of carbon-dioxide equivalent (GtCO2e) emissions of hydrofluorocarbons (HFC) per year by 2100, reducing the impact of HFCs on global average warming by up to 0.4°C. Despite its successes, unexpected emissions of phased out ODS – notably the chlorofluorocarbon, CFC-11 - have brought attention to shortcomings in the Protocol’s monitoring, reporting, verification and enforcement (MRV+E) which must be addressed to guarantee its controls are sustained. Meanwhile, additional significant mitigation could be achieved by accelerating the phase-down of HFCs under the Kigali Amendment, by tackling ODS and HFC emissions from leaking banks of equipment and products and by controlling feedstocks, which are not subject to Montreal Protocol phase-out controls. Recent scientific papers have linked almost 870 million tCO2 per year of greenhouse gases (GHG) and ODS to fluorochemical industrial processes and illegal fluorochemical production. Expanding the scope of the Montreal Protocol to address nitrous oxide (N2O), itself an ODS and GHG, would also contribute substantial ozone and climate benefits. This perspective essay discusses new and strengthened policy measures that governments can consider under the Montreal Protocol in order to maximize early, cost-effective reductions in emissions of non-CO2 greenhouse gases and ensure future implementation.

Substantial Warming of the Atlantic Ocean in CMIP6 Models

Abstract The storage of anthropogenic heat in oceans is geographically inhomogeneous, leading to differential warming rates among major ocean basins with notable regional climate impacts. Our analyses of observation-based datasets show that the average warming rate of 0–2000-m Atlantic Ocean since 1960 is nearly threefold stronger than that of the Indo-Pacific Oceans. This feature is robustly captured by historical simulations of phase 6 of Coupled Model Intercomparison Project (CMIP6) and is projected to persist into the future. In CMIP6 simulations, the ocean heat uptake through surface heat fluxes plays a central role in shaping the interbasin warming contrasts. In addition to the slowdown of the Atlantic meridional overturning circulation as stressed in some existing studies, alterations of atmospheric conditions under greenhouse warming are also essential for the increased surface heat flux into the North Atlantic. Specifically, the reduced anthropogenic aerosol concentration in the North Atlantic since the 1980s has been favorable for the enhanced Atlantic Ocean heat uptake in CMIP6 models. Another previously overlooked factor is the geographic shape of the Atlantic Ocean which is relatively wide in midlatitudes and narrow in low latitudes, in contrast to that of the Indo-Pacific Oceans. Combined with the poleward migration of atmospheric circulations, which leads to the meridional pattern of surface heat uptake with broadly enhanced heat uptake in midlatitude oceans due to reduced surface wind speed and cloud cover, the geographic shape effect renders a higher basin-average heat uptake in the Atlantic.

First Analyses of the TIMELINE AVHRR SST Product: Long-Term Trends of Sea Surface Temperature at 1 km Resolution across European Coastal Zones

Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R > 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions.

Widespread warming of Earth's estuaries

AbstractWater temperature responses to climate change may vary across Earth's estuaries. To understand how climate change influences estuarine surface water temperature, we need global, long‐term records of estuarine temperature. Here, we generated surface water temperature data over 1060 estuaries globally using Landsat 5, 7, and 8 from 1985 to 2022 and compared water warming rates with local air temperature warming rates. Forty‐seven percent of Earth's estuaries are warming, with a global average warming rate of 0.070 ± 0.004°C yr−1 (median = 0.060°C yr−1). Estuaries at higher latitudes showed rapid warming. A 1°C increase in air temperature could lead to a 0.81°C increase in estuarine surface water warming and 1.3°C increase in estuaries above 60.5°N. We inferred the potential influences over estuarine warming based on distinct global spatial patterns in water and air warming and discussed the effects of warming water temperature on estuarine metabolism and water quality.

Spatiotemporal characteristics and variability in the thermal state of permafrost on the Qinghai–Tibet Plateau

AbstractPermafrost degradation on the Qinghai–Tibet Plateau (QTP) has significant impacts on climate, hydrology, and engineering and environmental systems. To understand the temporal and spatial characteristics of permafrost on the QTP, we quantified the variation in active layer thickness (ALT), permafrost thermal state, and future permafrost change under different scenarios using observational data, reanalysis data, and the numerical permafrost model. Generally, ALT ranged from 0.5 to 6.0 m with an average of 2.39 m, and mean annual ground temperature (at a depth of zero annual amplitude for ground temperature) mainly ranged between 0 and −3°C with an average of −0.85°C. The soil temperatures in different layers based on the ERA5‐Land data revealed even stronger increasing trends, for example, 0.245, 0.245, 0.244, and 0.238°C/decade at depths of 0–7, 7–28, 28–100, and 100–289 cm from 1980 to 2021, compared to those during the period from 1960 to 2021, which were 0.153, 0.156, 0.155, and 0.149°C/decade, respectively. The average warming trends in annual mean soil temperature were 0.153 and 0.243°C/decade from 1960 to 2021 and 1980 to 2021, respectively. The average rate of thickening of the ALT among the 10 active layer observation sites was 2.84 cm/year. There was a significant warming trend in ground temperature above ~15 m with warming of 0.063 to 0.120, 0.026 to 0.182, 0.101 to 0.314, and 0.189 to 0.303°C/decade at the QTB01, QTB06, QTB08, and XDTGT sites, respectively, and yearly minimum ground temperatures exhibited stronger warming trends than maximum ground temperatures. In addition, the simulation revealed significant increases in ground temperature at the Xidatan (XDT) and Tanggula (TGL) sites under both historical and future Representative Concentration Pathway (RCP) scenarios, but the increases in ground temperature were significantly greater at TGL than XDT. These findings provide important information for understanding the variability in permafrost degradation processes and improving simulations of permafrost change under climate change on the QTP.

Sizing mudsnails: Applying superpixels to scale growth detection under ocean warming

Abstract The expansion of scientific image data holds great promise to quantify individuals, size distributions and traits. Computer vision tools are especially powerful to automate data mining of images and thus have been applied widely across studies in aquatic and terrestrial ecology. Yet marine benthic communities, especially infauna, remain understudied despite their dominance of marine biomass, biodiversity and playing critical roles in ecosystem functioning. Here, we disaggregated infauna from sediment cores taken throughout the spring transition (April–June) from a near‐natural mesocosm setup under experimental warming (Ambient, +1.5°C, +3.0°C). Numerically abundant mudsnails were imaged in batches under stereomicroscopy, from which we automatically counted and sized individuals using a superpixel‐based segmentation algorithm. Our segmentation approach was based on clustering superpixels, which naturally partition images by low‐level properties (e.g., colour, shape and edges) and allow instance‐based segmentation to extract all individuals from each image. We demonstrate high accuracy and precision for counting and sizing individuals, through a procedure that is robust to the number of individuals per image (5–65) and to size ranges spanning an order of magnitude (<750 μm to 7.4 mm). The segmentation routine provided at least a fivefold increase in efficiency compared with manual measurements. Scaling this approach to a larger dataset tallied >40k individuals and revealed overall growth in response to springtime warming. We illustrate that image processing and segmentation workflows can be built upon existing open‐access R packages, underlining the potential for wider adoption of computer vision tools among ecologists. The image‐based approach also generated reproducible data products that, alongside our scripts, we have made freely available. This work reinforces the need for next‐generation monitoring of benthic communities, especially infauna, which can display differential responses to average warming.

Internal Variability Increased Arctic Amplification During 1980–2022

AbstractSince 1980, the Arctic surface has warmed four times faster than the global mean. Enhanced Arctic warming relative to the global average warming is referred to as Arctic Amplification (AA). While AA is a robust feature in climate change simulations, models rarely reproduce the observed magnitude of AA, leading to concerns that models may not accurately capture the response of the Arctic to greenhouse gas emissions. Here, we use CMIP6 data to train a machine learning algorithm to quantify the influence of internal variability in surface air temperature trends over both the Arctic and global domains. Application of this machine learning algorithm to observations reveals that internal variability increases the Arctic warming but slows global warming in recent decades, inflating AA since 1980 by 38% relative to the externally forced AA. Accounting for the role of internal variability reconciles the discrepancy between simulated and observed AA.

The 1996 Mid-Atlantic Winter Flood: Exploring Climate Risk through a Storyline Approach

Abstract This article explores the application of thermodynamic perturbations to a historical midlatitude, wintertime, rain-on-snow flood event to evaluate how similar events may evolve under different climate forcings. In particular, we generate a hindcast of the 1996 Mid-Atlantic flood using an ensemble of 14-km variable-resolution simulations completed with the U.S. Department of Energy’s global Energy Exascale Earth System Model (E3SM). We show that the event is skillfully reproduced over the Susquehanna River Basin (SRB) by E3SM when benchmarked against in situ observational data and high-resolution reanalyses. In addition, we perform five counterfactual experiments to simulate the flood under preindustrial conditions and four different levels of warming as projected by the Community Earth System Model Large Ensemble. We find a nonlinear response in simulated surface runoff and streamflow as a function of atmospheric warming. This is attributed to changing contributions of liquid water input from a shallower initial snowpack (decreased snowmelt), increased surface temperatures and rainfall rates, and increased soil water storage. Flooding associated with this event peaks from around +1 to +2 K of global average surface warming and decreases with additional warming beyond this. There are noticeable timing shifts in peak runoff and streamflow associated with changes in the flashiness of the event. This work highlights the utility of using storyline approaches for communicating climate risk and demonstrates the potential nonlinearities associated with hydrologic extremes in areas that experience ephemeral snowpack, such as the SRB.

Observationally Constrained Projections of Twenty-First-Century Regional Warming in the Extratropical Northern Hemisphere

Abstract Physically based observational constraint methods can effectively reduce uncertainty in global warming projections but have not been widely applied at regional scales. We first develop and apply multivariate linear regression models for constraining projections of surface air temperature averaged over subcontinental regions in the extratropical Northern Hemisphere, based on a set of potential constraints including climatological metrics derived from tropical and subtropical low-level cloud and global average past warming trend, as well as a set of regional climate metrics previously used in the literature. We evaluate the performance of the multivariate linear regression models based on cross-validated tests using output from phases 5 and 6 of the Coupled Model Intercomparison Projects (CMIP). We find that linear regression models using global-scale low-cloud metrics alone perform more robustly than linear regression models using the past global mean warming trend or regional climate metrics as constraints. These results, while favoring global constraints over the set of regional constraints considered, do not preclude the existence of even better regional constraints for particular regions. Through model-based cross-validation, the projections constrained using low-level cloud metrics exhibit more accurate best estimate projections, narrower uncertainty ranges, and more reliable uncertainty estimates in most Northern Hemisphere regions when compared with unconstrained projections. Application of the approach to climate projections based on both Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 using observed low-cloud metrics results in considerably narrower 5%–95% uncertainty ranges of twenty-first-century warming over subcontinental Northern Hemisphere land regions compared to unconstrained projections.

Analysis of the behavioural capabilities of electric heating loads to participate in power system power regulation

The high proportion of new energy access leads to the scarcity of power system regulation capacity, and it is important to provide regulation capacity for the power system by reasonably regulating the electricity consumption of electric heating temperature-controlled loads. In this paper, in order to analyse the characteristics of the electric heating behaviour and the electric heating load's ability to participate in grid regulation, the differential equations of a typical room temperature change process are constructed first to establish the equation of state model of a two-input system, and then the state equations are discretised into difference equations according to the bilinear discretisation method for iterative solving. This paper analyses that the equivalent heat capacity and thermal resistance parameters of indoor air and wall will affect the temperature response time and the size of the required heating power, with the lowering of the outdoor temperature of a single household room, the average indoor warming time increases, the average cooling time decreases, the average daily power consumption increases, and the total power consumption of the whole community power also rises.

Decoupling the response of vegetation dynamics to asymmetric warming over the Qinghai-Tibet plateau from 2001 to 2020

Global land surface air temperature data show that in the past 50 years, the rate of nighttime warming has been much faster than that of daytime, with the minimum daily temperature (Tmin) increasing about 40% faster than the maximum daily temperature (Tmax), resulting in a decreased diurnal temperature difference. The Qinghai-Tibet Plateau (QTP) is known as the "roof of the world", where temperatures have risen twice as fast as the global average warming rate in the last few decades. The factors affecting vegetation growth on the QTP are complex and still not fully understood to some extent. Previous studies paid less attention to the explanations of the complicated interactions and pathways between elements that influence vegetation growth, such as climate (especially asymmetric warming) and topography. In this study, we characterized the spatial and temporal trends of vegetation coverage and investigated the response of vegetation dynamics to asymmetric warming and topography in the QTP during 2001–2020 using trend analysis, partial correlation analysis, and partial least squares structural equation model (PLS-SEM) analysis. We found that from 2001 to 2020, the entire QTP demonstrated a greening trend in the growing season (April to October) at a rate of 0.0006/a (p < 0.05). The spatial distribution pattern of partial correlation between NDVI and Tmax differed from that of NDVI and Tmin. PLS-SEM results indicated that asymmetric warming (both Tmax and Tmin) had a consistent effect on vegetation development by directly promoting greening in the QTP, with NDVI values being more sensitive to Tmin, while topographic factors, especially elevation, mainly played an indirect role in influencing vegetation growth by affecting climate change. This study offers new insights into how vegetation responds to asymmetric warming and references for local ecological preservation.

Environmental Characteristics of High Ice-Content Permafrost on the Qinghai–Tibetan Plateau

Permafrost areas are sensitive to climate change and have a significant impact on energy and water cycles. Ground ice is a crucial component on the Qinghai–Tibetan Plateau (QTP). Understanding the environmental characteristics of ground ice is vital for accurately modeling its distribution and evolution. In this study, we analyzed 15 environmental characteristics of high ice-content permafrost sites. These attributes were extracted from 400 high ice-content permafrost datasets including 300 drilling boreholes and 100 thaw slumps collected throughout the entire plateau using large-scale remote sensing data and their products. The results are as follows: The mean annual air temperature in areas where high ice-content permafrost exists ranges from −5 to −3.5 °C, with an average warming rate of 0.08 °C/a. Additionally, there was an average increase in precipitation of about 25 mm/10a and an increase in soil moisture of about 4%/10a. Geomorphology strongly influences the occurrence of high ice content permafrost, with 85% of high ice-content permafrost development at altitudes between 4400 and 5100 m. Approximately 86% of high ice-content permafrost were developed in lowland or relatively flat areas, preferably in gently sloping and shady slope regions. Soils exhibit less variability in clay particles and more variability in silt and sand. Key indicators in the high ice content permafrost region include warming rate, active layer thickness, elevation, bulk density, soil thickness, clay content, precipitation, soil moisture, and NDVI. High ice-content permafrost is the result of a combination of environmental factors and is expected to undergo significant changes in the future. This study provides a foundation for comprehending the environmental changes in the high ice-content permafrost areas and modeling the distribution of ground ice. It underscores the urgent need to address the significant environmental changes faced by high ice-content permafrost regions.