Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
Abstract
The Working Group I contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) provides a comprehensive assessment of the physical science basis of climate change. It considers in situ and remote observations; paleoclimate information; understanding of climate drivers and physical, chemical, and biological processes and feedbacks; global and regional climate modelling; advances in methods of analyses; and insights from climate services. It assesses the current state of the climate; human influence on climate in all regions; future climate change including sea level rise; global warming effects including extremes; climate information for risk assessment and regional adaptation; limiting climate change by reaching net zero carbon dioxide emissions and reducing other greenhouse gas emissions; and benefits for air quality. The report serves policymakers, decision makers, stakeholders, and all interested parties with the latest policy-relevant information on climate change. Available as Open Access on Cambridge Core.
... SSP2-4.5, SSP3-7.0, and SSP5-8.5. These SSPs combine socioeconomic development pathways and radiative forcing levels of 2.6, 4.5, 7.0, and 8.5 W m −2 , which will be reached by the end of the century [55]. Furthermore, they include future concentrations and emissions of polluting gases and changes in land use [39]. ...
... All projected scenarios show TOC increase at mid-latitudes (30°-60°), except for SSP1-2.6. TOC decline in the SSP1-2.6 scenario is related to lower tropospheric ozone concentrations in response to the decrease in precursor emissions [55,59]. In 2041-2060, the spatial distributions of projected changes for SSP3-7.0 and SSP5-8.5 scenarios are similar. ...
... AOD reductions close to 60% are observed under low radiative forcing scenario (SSP1-2.6) in both months throughout the twenty-first century. In this scenario, AOD decreases may be related to implementing of air quality policies [55]. ...
... Climate change is viewed today as the greatest threat to humanity's survival [1,2]. Despite the 2015 International Paris Agreement aimed at reducing greenhouse gas emissions, global temperatures have risen primarily due to the increased global reliance on fossil fuels. ...
... Step 5 Calculate r 1 , and for each Salp, if the number of Salps is less than the population size divided by 2, update their positions employing the SSA operator expressed in Eq. (1). In cases where this condition doesn't apply, make adjustments using Sine Cosine perturbation expressed in Eq. (19). ...
This research presents the utilization of an enhanced Sine cosine perturbation with Chaotic
perturbation and Mirror imaging strategy-based Salp Swarm Algorithm (SCMSSA), which incorporates three improvement mechanisms, to enhance the convergence accuracy and speed of
the optimization algorithm. The study assesses the SCMSSA algorithm’s performance against
other optimization algorithms using six test functions to show the efficacy of the enhancement
strategies. Furthermore, its efficacy in improving Support Vector Regression (SVR) models for
CO2 prediction is assessed. The results reveal that the SVR-SCMSSA hybrid model surpasses other
hybrid models and standard SVR in terms of training and prediction accuracy by obtaining 95 %
accuracy. Its swift convergence, precision, and resistance to local optima position make it an
excellent choice for addressing complex problems such as CO2 prediction, with critical implications for sustainability efforts. Moreover, feature importance analysis by SVR-SCMSSA offers
valuable insights into the key contributors to CO2 prediction in the dataset, emphasizing the
significance and impact of factors such as fossil fuel, Biomass, and Wood as major contributors to
CO2 emission. The research suggests the adoption of the SVR-SCMSSA hybrid model for more
accurate and reliable CO2 prediction to researchers and policymakers, which is essential for
environmental sustainability and climate change mitigation.
... The net global warming potential (Kg CO2-eq ha −1 season −1 ) was calculated using the warming potential coefficient (CO2 equivalent) of 298 for N2O, 34 for CH4 and 1 for soil CO2 emissions, based on a 100-year time scale of IPCC AR6 [35]. ...
Incorporating crop residues into the soil is an effective method for improving soil carbon sequestration, fertility, and crop productivity. Such potential benefits, however, may be offset if residue addition leads to a substantial increase in soil greenhouse gas (GHG) emissions. This study aimed to quantify the effect of different crop residues with varying C/N ratios and different nitrogen (N) fertilizers on GHG emissions, yield, and yield-scaled emissions (GHGI) in winter wheat. The field experiment was conducted during the 2018–2019 winter wheat season, comprising of four residue treatments (no residue, maize residue, soybean residue, and maize-soybean mixed residue) and four fertilizer treatments (control, urea, manure, and manure + urea). The experiment followed a randomized split-plot design, with N treatments as the main plot factor and crop residue treatments as the sub-plot factor. Except for the control, all N treatments received 150 kg N ha−1 season−1. The results showed that soils from all treatments acted as a net source of N2O and CO2 fluxes but as a net sink of CH4 fluxes. Soybean residue significantly increased soil N2O emissions, while mixed residue had the lowest N2O emissions among the three residues. However, all residue amendments significantly increased soil CO2 emissions. Furthermore, soybean and mixed residues significantly increased grain yield by 24% and 21%, respectively, compared to no residue amendment. Both soybean and mixed residues reduced GHGI by 25% compared to maize residue. Additionally, the urea and manure + urea treatments exhibited higher N2O emissions among the N treatments, but they contributed to significantly higher grain yields and resulted in lower GHGI. Moreover, crop residue incorporation significantly altered soil N dynamics. In soybean residue-amended soil, both NH4+ and NO3− concentrations were significantly higher (p < 0.05). Conversely, soil NO3− content was notably lower in the maize-soybean mixed residue amendment. Overall, our findings contribute to a comprehensive understanding of how different residue additions from different cropping systems influence soil N dynamics and GHG emissions, offering valuable insights into effective agroecosystems management for long-term food security and soil sustainability while mitigating GHG emissions.
... Climate change has caused a demonstrable shift in average temperatures across the world, characterized by more frequent, intense, and longer-lasting heatwaves [1,2] affecting millions of people worldwide [3]. Extreme heat events pose severe health risks, particularly for vulnerable population groups such as the elderly and those with pre-existing health conditions [4,5,6]. ...
... Methane (CH 4 ) is a greenhouse gas with a global warming potential 80 times that of CO 2 on 20-year time scales, and an atmospheric abundance that has been increasing at an accelerated pace in recent years (IPCC, 2021). Uncertainty in the methane budget makes it difficult to identify drivers of methane's recent growth (Kirschke et al., 2013;Saunois et al., 2020;Turner et al., 2017). ...
Plain Language Summary
The amount of methane, a powerful greenhouse gas, has been growing in Earth's atmosphere during the last decade, and scientists disagree about which methane sources and sinks are responsible for the growth. One clue into understanding methane's sources and sinks is their seasonality—their month‐to‐month cycles that happen every year. Measurements of atmospheric methane taken at the Earth's surface and using satellite instruments show a steep increase each summer in the Northern Hemisphere that is not replicated when methane is simulated in a global chemical transport model, indicating missing information about source and sink seasonalities. To investigate, we use that model to simulate 24 representations of methane's largest source, emissions from wetlands, and 22 representations of its largest sink, chemical loss by the hydroxyl radical (OH). We find that OH is unlikely to cause the summer increase and model bias, but the amount, spatial distribution, and seasonal cycles of global wetland emissions are the strongest drivers. We suggest that these characteristics are linked to the underlying mechanisms determining wetland area and methane production in wetland models. The results unveil the role of global wetlands in driving methane's seasonality and inform research to analyze methane's long‐term trends.
... But it explicitly refers to the best available science, which at the time of its adoption was summarised in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change 5,6 . Further, the UNFCCC provides additional guidance as set out below. ...
The question of if or when the 1.5°C Paris Agreement threshold is crossed is of great public and scientific interest. A single year above 1.5°C does not necessarily imply that the Paris Agreement threshold is reached but may provide warning of crossing 1.5°C. We find that, under current emissions policies, annual temperatures exceeding 1.5°C in three individual years suggests that it is very likely (90-100% chance) that human-induced global warming has reached 1.5°C. A single year above 1.5°C could occur up to 12 years (very likely range) before the Paris Agreement threshold is reached. A single year above 1.4°C, as occurred in 2023, suggests a crossing of the Paris Agreement threshold within 7-14 years (likely range) under current policies. The observed global temperature change in 2023 is an urgent warning of the need for stringent emissions reductions in this critical decade to keep the Paris Agreement 1.5°C threshold within reach.
The great Himalayan region covers approximately 2000 km from east to west. It is referred to as the Asian water tower as it feeds water to 1.9 billion people in Asia. The range extends to several Asian countries like Afghanistan, Bangladesh, Bhutan, China, India, Nepal, and Pakistan. The Himalayan glaciers provide water to numerous sizeable Asian river systems, i.e., Amu Darya, Brahmaputra, Ganges, Indus, Irrawaddy, Mekong, Salween, Tarim, Yangtze, and Yellow. These glaciers significantly alter stream flow in quantity and timing, as annual basin run-off could be increased or decreased depending on annual negative or positive glacier mass balance, respectively. Although glacial expansions and retreats are natural phenomena, the melting rate has recently accelerated due to changes in climatic conditions due to an excess concentration of greenhouse gases in the atmosphere. The rate of glacier melting is significant, and this accelerated melting may not only cause natural hazards such as landslides and glacier lake outburst floods but also increase the phantom of shrinking water resources in the long run. This threatens the low-line population’s freshwater supply and other essential services like food, energy, and livelihood security.
Messages regarding climate change that are intended to stimulate responsible engagement can impact our mental health in both positive and negative ways, which in turn can increase or limit the potential engagement being sought through those very messages. Increasingly alarmist environmental metaphors are being brought into question due to their possibly detrimental impact on mental health and well-being, and in their place, relational environmental metaphors are proffered to instill hopeful and constructive individual and collective engagement for responsible climate action. This article discusses how both alarmist and relational environmental metaphors interact with eco-emotions. It proposes, in light of concepts arising from Porges’ Polyvagal Theory − on the psychophysiology of autonomic states created in contexts of threatening cues and feelings of safety and connection −, that relational environmental metaphors are preferable for stimulating responsible collective engagement and fostering global well-being in the midst of climate change.
Uncertainty in climate sensitivity has been shown to warrant early-on mitigation to limit global warming while anticipating future carbon dioxide removal creates mitigation deterrence. Here we use an integrated assessment model to quantify the impacts of under- or overestimating the cost and availability (feasibility) of carbon dioxide removal when limiting warming to 1.5 °C by 2100 under uncertain climate sensitivity. If climate sensitivity uncertainty is disregarded, initial assumptions on the feasibility have only minor effects on mitigation costs. However, the climate sensitivity risk compounds the impact of prior assumptions. Wrong assumptions on carbon dioxide removal feasibility can lead to lower costs under extreme realizations of climate sensitivity. Moreover, scenarios considering uncertainty in climate sensitivity rely less on carbon dioxide removal. A prudential strategy assuming low feasibility for carbon dioxide removal reduces the “double whammy” risk of overestimating carbon dioxide removal in combination with a realization of high climate sensitivity.
Despite significant development in the Earth system models (ESMs) and releases of several coupled model intercomparison projects (CMIPs), the evolving patterns of Indian summer monsoon rainfall and its future trajectory is still uncertain, with low confidence in its direction. This could be because of differential impacts from increasing greenhouse gas (GHG) and aerosol concentrations. We found that the observed pre-2000 (1951–2000) declining monsoon was likely attributed to the increasing aerosol concentrations. On the contrary, the reported revival of post-2000 monsoon rainfall is due to GHG dominance. These are spatiotemporally consistent with individual CMIP Phase 6 (CMIP6) ESM simulations with GHG and aerosols separately. Similar results were obtained for temperature in India, which showed no to low warming signal in pre-2000 due to aerosol-driven cooling. The dominance of GHG impacts has increased India’s warming trend in post-2000. This research highlights a notable trend in temperature and precipitation across the Indian subcontinent during the past two decades, emphasizing the dynamic character of climate change explained by contrasting anthropogenic influences, including GHGs and aerosols.
High expectations are placed on Climate Change Education (CCE), ranging from emotionally and practically preparing young people for the changes ahead, to supporting them in becoming climate-friendly actors. To address these challenges and inspire new approaches, this paper introduces a typology of utopian knowledge into the practice of CCE. It starts by linking utopia and the climate crisis noting that both are oriented to complex futures which are uncertain and simultaneously open to desires for alternatives. We describe forms in which learners can get to know themselves and their worlds in utopian ways-in ways that are informed by the desire for a better way of living. To render the theoretical elaboration more vivid, we present exemplary reflections on how the modes of utopian knowledge might be practiced in CCE. The result are new perspectives on living in the climate crisis, and, hopefully, new ways of being.
An uncrewed aerial system (UAS) has been developed for observations of aerosol and cloud properties relevant to aerosol direct and indirect forcing in the marine atmosphere. The UAS is a Hybrid Quadrotor–fixed-wing aircraft designed for launch and recovery from a confined space such as a ship deck. Two payloads, clear sky and cloudy sky, house instrumentation required to characterize aerosol radiative forcing effects. The observing platform (UAS plus payloads) has been deployed from a ship and from a coastal site for observations in the marine atmosphere. We describe here details of the UAS, the payloads, and first observations from the TowBoatU.S. Richard L. Becker (March 2022) and from the Tillamook UAS Test Range (August 2022). The development of this UAS technology for flights from ships and coastal locations is expected to greatly increase observations of aerosol radiative effects in the marine boundary layer over both temporal and spatial scales.
The study investigates variabilities and trends in the onset, peak, and retreat of Intertropical Discontinuity (ITD) annual migrations over West Africa between 1979 and 2020, using reanalysis data of the daily mean surface location of ITD of longitudes 15°W to 15°E. The ITD migration peaks are determined from its migration pentad graphs, while its migration onsets and retreats are detected using the ogive. ITD attains peak from August 4 to 28 at latitudes 17°N to 23°N. The percentage cumulative migrations of ITD perfectly exhibit the ogive/sigmoid curve that reflects changes in ITD’s migration speed and direction. A new precision method is developed for the determination of the onsets and retreats on the ogive. The ITD periods of onset are between April 26 and May 5 in the west and April 21 and 25 in the east while their corresponding periods of retreats are between October 27 and November 1 and October 18 and 22. The locations of ITD at the onset and retreat periods increase from approximately 11°N and 12°N to 17°N and 20°N in the east and west, respectively. The peak period exhibits the highest variability (5.5–8.6% Coefficient of Variation (CV) and 45–85 days ranges), followed by the onset (4.9–7.2% CV and 20–35 days ranges) and the retreat (1.8–2.9% CV and 20–40 days ranges). However, the latitudinal location of the onset shows the highest variability (9.4–19.7% CV and 8.3–13° latitudinal ranges), followed by the retreat (9.0-15.3% CV and 4.7–11.8° latitudinal ranges) and lastly, the peak (1.6–7.8% CV and 1.4–7.9° latitudinal ranges). There are significant upward trends in the ITD’s latitudinal location at the onset, peak and retreat along longitudes 5°E, 0°-15°E, and 10°E, respectively. The trends are attributed to the deepening of the Sahara Heat Low, which in turn is due to its enhanced heating in association with climate change. Direct relationships are observed between the pairs of ITD onset, peak and retreat periods. The ITD migration speed increases from the beginning of the year to the end and displays a gradual advance but rapid retreat.
Recent Greenland ice-sheet melt constitutes a considerable contribution to global sea-level rise. Observations indicate an approximate zero mass balance of the ice sheet until the late 1990s, after which a strong increase in melting occurred. This cannot be attributed linearly to gradually-increasing global warming. Instead the abrupt shift has been linked to atmospheric circulation changes, although causality is not fully understood. Here we show that changes of atmospheric waves over Greenland have significantly contributed to the shift into a strong melting state. This is evident after having applied a newly-developed methodology effectively decomposing atmospheric flow patterns into parts associated with waves of different scales such as Rossby waves and smaller perturbations. The onset of a westerly-flow reduction, consistent with anthropogenic Arctic warming, affected transports by atmospheric waves and led to a decrease in precipitation and an increase in surface warming, contributing to ice-sheet mass loss, in particular over the southwestern regions. As such, the Greenland ice-sheet melt is an example of a climate response non-linearly coupled to global warming.
Robust, reliable, and trustworthy ground observation datasets are the preliminary requirement for assessing the impact of climate change over regions. Principal testing to assess the quality of ground observation rely on the missing data and homogeneity result. The study used 40 years of monthly rainfall documented from different topographical features in the monsoonal region of East Java, Indonesia. The test included annual rainfall, early rainy season (October-November-December), and primary rain season (January-February-March). The homogeneity of rainfall determined by absolute technique: Pettitt’s test, the Standard Normal Homogeneity Test, the Buishand Rank Test, and the von Neumann Ratio. Among the time series, October-November-December observation results in better homogeneity. However, the rainfall datasets during primary rainy season showed the worst homogeneity. By performing annual and seasonal homogeneity test from 67 rainfall stations: 5 stations out of data length required, 5% stations ‘rejected’, 11% ‘suspect’, 11% ‘doubtful’, and 73% were ‘trusted’. Therefore, a total of 45 stations can be used as metadata for relative comparison and 7 stations can be considered to be useful for analysis despite ‘doubtful’. The remaining 10 stations need careful consideration to be used for future water management. Change point detected particularly between the year of 1997 through 2000. Pettitt’s test has outstanding results in the case of extreme climatic anomaly, but less sensitive of continuous abrupt change. The von Neumann test could detect abnormal data, but was not suitable for datasets containing few extreme values. The insights from homogeneity testing were: a) it is important to remove any outliers in the datasets before conducting homogeneity testing, b) both parametric and nonparametric homogeneity tests should be performed, and c) comparisons should be made with surrounding rainfall stations. Comparison with trusted long-term rainfall data is valuable for stations labeled as ‘doubtful’ or ‘suspect’ to mitigate false detections in individual homogeneity tests. The identified ‘useful’ rainfall data can then serve as reference stations for relative homogeneity tests. These findings suggest that reference stations should be assessed within similar rainfall zones.
Aims
The cycling of nutrients from plant litter has key implications for the functioning of terrestrial ecosystems by controlling nutrient availability and net primary production. Despite extensive research on the effects of global change on ecosystem functioning, the direct implications of global change on stoichiometry and nutrient dynamics during litter decomposition remain poorly understood. To address this gap, we conducted a meta-analysis.
Methods
We analysed 178 experiments that simulated (i) warming, (ii) drought, (iii) increased water availability, (iv) N enrichment, (v) P enrichment, and (vi) combined N and P (N + P) enrichment. We compared earlier (approximately six months) and later (approximately one year) stages of decomposition and analysed the specific effects taking into account climate and plant type.
Results
The C:N and C:P ratios decreased in most warming and nutrient enrichment scenarios, leading to losses of litter C content, while the N:P ratio remained more resilient and affected by water availability. Furthermore, the abundance of resources (water and N + P) fosters the decomposition of litter. The nutrient mobilisation increases for both P and N under non-limited nutrient enrichment and it is faster for N than for P when water increases its availability. Nutrient enrichment was relevant in later stages of decomposition.
Conclusions
Our study provides insights into the fate of litter decomposition and its stoichiometric dynamics in response to drivers of global change. Concerning scenarios of C release and N and P immobilisation were identified. However, further experimentation and analysis are necessary to consider all interacting drivers.
Within the ongoing controversy regarding the orogeny of the Tibetan Plateau region, two directly-conflicting endmember frameworks have emerged, where either: 1) a high central ‘proto-plateau’ existed prior to the onset of India-Asia continental collision, or 2) the early Paleogene central Tibet comprised a wide E-W oriented lowland ∼1-2 km above sea level, bounded by high (> 4.5 km) mountain systems. Reconstructing plateau development correctly is fundamental to running realistic Earth system models that explore monsoon and biodiversity evolution in the region. Understanding the interplay between monsoon dynamics, landscape and biodiversity are critical for future resource management. We explore the strengths and weaknesses of different palaeoaltimetric methodologies as applied across the Tibetan region. Combining methodologies, appreciating the vulnerabilities arising from their underlying assumptions and testing them using numerical climate models, produces consilience (agreement) allowing further refinement of both models and proxies. We argue that an east-west oriented Paleogene Central Tibetan Valley was a cradle and conduit for thermophilic biota seeding the modern regional biodiversity. The rise of eastern Tibet intensified regional rainfall and erosion, which increased topographic relief and biodiversification. Gradual monsoon development reflected the evolving topography, but modern-like Asian monsoons developed only after a plateau formed in the Miocene.
The study of cryoconite – a specific organomineral sediment on the glacier surface – is essential to estimate environmental processes and sustainability, biogeochemical cycles, pollution rate and degree of human influence under conditions of climate change and diverse anthropogenic activities. Key chemical and physical features such as pH values, total organic carbon and hot-water extractable carbon content, microbial respiration, and particle-size distribution, as well as the content of some trace elements and pollution indices have been determined in materials sampled at the Mt. Elbrus region. The results obtained showed accumulation of easily decomposable carbon and correlated with it high rate of microbial respiration at the Garabashi Glacier, despite the low content of total organic carbon (max. 0.92%) due to its redistribution. Cryoconites at the Garabashi Glacier also efficiently accumulated trace elements, especially Zn (max. 55.40 mg kg− 1) and Pb (max. 26.03 mg kg− 1), up to high pollution level. Domination of silt and sand fractions indicated major role of autochthonous transfer to the glacial zone both from anthropogenic and natural geologic sources. Translocation of cryoconite material to the periglacial zone and anthropogenic activities led to accumulation of both total organic carbon and hot-water extractable carbon as well as trace elements such as Zn (max. 64.40 mg kg− 1) and Cd (max. 0.41 mg kg− 1) in studied Leptosols. Migration of elements from the glacial to the periglacial zone at the Elbrus region can accelerate developments of soils after glacier retreat, while intensification of human activity may pose additional pollution risks for agriculture, tourism and environmental sustainability.
Background and aims
Global warming is a major global issue that may affect nutrient cycling in terrestrial ecosystems. Plants usually employ the strategy of nutrient resorption to conserve resources. Over the past few decades, there has been widespread attention given to how warming affects the nutrient resorption efficiency (NuRE) in leaves. Twig is another important component of plant. The unique physiological characteristics of twig may make its NuRE response to warming different from that of leaf. However, there is insufficient knowledge regarding how warming affects NuRE in twigs.
Methods
We assessed the response of nutrient concentrations (nitrogen, phosphorus, potassium, calcium, and magnesium) and NuREs in leaves and twigs to warming, by using plant samples (Cunninghamia lanceolata) from a manipulative field warming experiment (+ 5 °C).
Results
The nutrient concentrations and NuREs of leaves remained unchanged under warming. In contrast, warming significantly decreased nitrogen concentration (− 13%) and increased calcium (+ 21%) and magnesium (+ 44%) concentrations in mature twigs. Warming significantly decreased NRE (− 10%), KRE (− 15%), and CaRE (− 7%), and increased MgRE (+ 12%) in twigs. It was also found that warming decreased the water content of twigs, and there were significant negative correlations between NuREs and nutrients in senesced organs.
Conclusion
The nutrient concentrations and NuRE of twigs are more vulnerable to warming than those of leaves. The regulation of NuRE response to warming is influenced by water and nutrients. Incorporating plant twig NuRE into nutrient cycling modeling and ecosystem productivity predictions may improve the accuracy of predictions under future warming conditions.
The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species’ ecological amplitude.
Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees’ rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled
from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech’s drought sensitivity, which needs to be taken into consideration when assessing this species’ response to climate change.
Climate change and anthropogenic stressors affect the distribution, abundance, and diversity of fish communities across the world. To understand rapidly changing biotic communities, resource managers need a method to quickly and efficiently document temporal and spatial changes in community assemblages across various spatial scales. In this study, we describe the use of new video lander tools to survey fish communities in rocky marine habitats on the continental shelf and slope in California, USA. We evaluate how fish diversity metrics determined by video surveys vary among geographically distinct areas. Our results demonstrate that species diversity, evenness, and richness vary spatially across the coast. Furthermore, community assemblages differ at both broad and fine spatial scales because of differences among habitats. Length frequencies and densities of species in this study were similar to those reported in previous studies. As community assemblages and biodiversity metrics shift in response to changing stressors, it is increasingly important to develop tools and methodologies to detect and rapidly monitor these changes.
Among Southamerican countries Chile is highly susceptible to Climate Change impacts on water resources and ecosystems. Also, Chilean lakes and rivers have been impacted by anthropogenic activities leading to chemical pollution and eutrophication.
Concerns for hydric resources conservation and management has led to current
development of environmental quality secondary laws for Nord Patagonian lakes. In
this context, we analyze historical limnological databases (1979-2022) for 18 Chilean
lakes utilizing Random Forest (RF). After filtering, we retained suitable data for 11
lakes including key features: Dissolved Oxygen, Electric Conductivity, Transparency,
Temperature, pH, Total Nitrogen, Total Phosphorus and Chlorophyll-a. This dataset
yielded robust results with RF, accurately predicting Chlorophyll-a as a trophic state
parameter. Furthermore, we added lake geomorphological parameters, enhancing the performance of the model. Our study demonstrates the need to improve the long-term monitoring programs, optimizing environmental data recording and decreasing costs.
Moreso, we conclude that studied lakes generally maintain their oligotrophic
characteristics, however further analysis of feature behavior suggest that these lakes are more sensitive to Nitrogen fertilization versus Phosphorus. Our results highlight the need to implement adaptative management plans at the watershed level to regulate anthropogenic Nitrogen contamination (through agriculture, pisciculture and urbanization). The features selected by RF, coupled with the assessment of historical trophic state variation, would allow the establishment of permissible concentration thresholds for major nutrients and other sentinel parameters, aiding the enforcement of environmental norms. Lastly, the coupling of in situ measurements with spatial data unveils promising perspectives to improve the monitoring capacity for Chilean lakes.
Background
Aloe ankoberensis M.G. Gilbert & Sebsebe and A. debrana Christian are Ethiopian endemic species currently classified as endangered and least concern, respectively under International Union for Conservation of Nature (IUCN) categories. Recent studies indicate that climate change is anticipated to significantly influence the distribution of plant species. Therefore, this study aimed to model the distribution of A. ankoberensis and A. debrana under different climate change scenarios in the North Shewa Zone, Amhara National Regional State of Ethiopia. Thirty-six and 397 georeferenced presence points for A. ankoberensis and A. debrana , respectively, and 12 environmental variables were used to simulate their current and future distributions. The ensemble model approach was used to examine the current and future (2050 and 2070) climatic suitability for both species under three shared socio-economic pathway (SSP) climate scenarios (SSP 2.6, 4.5 and 8.5).
Results
The performance of ensemble model was excellent for A. ankoberensis with score of area under curve (AUC) 0.96 and true skill statistics (TSS) 0.88, and good for A. debrana with score of AUC 0.87 and TSS 0.63. The main variables that affected the species' distributions were mean diurnal range of temperature, annual precipitation, and elevation. According to the model, under the current climate conditions, 98.32%, 1.01%, 0.52%, and 0.15% were not suitable, lowly, moderately, and highly suitable areas, respectively for A. ankoberensis , and 63.89%, 23.35%, 12.54%, and 0.21% were not suitable, lowly, moderately and highly suitable areas, respectively for A. debrana . Under future climate scenarios, suitable habitats of these species could shrink. In addition, under all climate change scenarios, it is anticipated that highly suitable areas for both species and moderately suitable areas for A. ankoberensis will be lost completely in the future unless crucial interventions are done on time.
Conclusions
The results indicate that the future may witness a decline in suitable habitat for A. ankoberensis and A. debrana , which leads to increasing threat of extinction. Therefore, it is crucial to develop a conservation plan and enhance climate change adaptation strategies to mitigate the loss of suitable habitats for these highland and sub-Afroalpine endemic Aloe species.
Using CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2006 to 2010, the effects of aerosols on ice- and mixed-phase, single-layer, non-precipitating clouds over the Tibetan Plateau during nighttime in the MAM (March to May), JJA (June to August), SON (September to November), and DJF (December to February) seasons were examined. The results indicated the following: (1) The macrophysical and microphysical characteristics of ice- and mixed-phase clouds exhibit a nonlinear trend with increasing aerosol optical depth (AOD). When the logarithm of AOD (lnAOD) was ≤−4.0, with increasing AOD during MAM and JJA nights, the cloud thickness and ice particle effective radius of ice-phase clouds and mixed-phase clouds, the ice water path and ice particle number concentration of ice-phase clouds, and the liquid water path and cloud fraction of mixed-phase clouds all decreased; during SON and DJF nights, the cloud thickness of ice-phase clouds, cloud top height, liquid droplet number concentration, and liquid water path of mixed-phase clouds all decreased. When the lnAOD was >−4.0, with increasing AOD during MAM and JJA nights, the cloud top height, cloud base height, cloud fraction, and ice particle number concentration of ice-phase clouds, and the ice water path of mixed-phase clouds all increased; during SON and DJF nights, the cloud fraction of mixed-phase clouds and the ice water path of ice-phase clouds all increased. (2) Under the condition of excluding meteorological factors, including the U-component of wind, V-component of wind, pressure vertical velocity, temperature, and relative humidity at the atmospheric pressure heights near the average cloud top height, within the cloud, and the average cloud base height, as well as precipitable water vapor, convective available potential energy, and surface pressure. During MAM and JJA nights. When the lnAOD was ≤−4.0, an increase in aerosols may have led to a decrease in the thickness of ice and mixed-phase cloud layers, as well as a reduction in cloud water path values. In contrast, when the lnAOD was >−4.0, an increase in aerosols may contribute to elevated cloud base and cloud top heights for ice-phase clouds. During SON and DJF nights, changes in various cloud characteristics may be influenced by both aerosols and meteorological factors.
This paper examines the role of remanufacturing in healthcare as a key circular design strategy, particularly for medical devices, assessing its socio-technical, environmental, and economic dimensions of sustainability. Through a detailed case of ultrasound catheters, it demonstrates how remanufacturing can lead to resource conservation, cost savings, and enhanced product lifecycles in health care without compromising quality and patient safety. The study argues for systemic changes in healthcare practices to fully integrate remanufacturing, underscoring its role beyond a technical solution.
Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4, a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, which is an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced Hyperspectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in centre wavelength and change in full width at half-maximum (FWHM) from the nominal design values are estimated for all spectral channels, which are used as inputs for retrieving the enhancement of the column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter-based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of the emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 761.78 ± 185.00 to 12 729.12 ± 4658.13 kg h−1. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing them with a ground-based meteorological station. We found a large discrepancy, especially in wind direction, suggesting that incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi.
This paper presents a novel methodology specifically developed for measuring and reducing Greenhouse gas (GHG) emissions in production systems and logistics, named Greenhouse gas Emissions Deployment (GED). Thanks to its step-by-step procedure, it enables industries to systematically identify GHG emissions caused by organizational losses, ineffective usage losses, and design losses that need to be tracked and removed in order to operate in the most efficient and environmentally sustainable way. By customizing the Manufacturing Cost Deployment structured use of matrices, GED can detect losses, evaluate cause-effect relations, and support improvement prioritization. First, the losses affecting emissions are identified and their relationship is analysed to identify the underlying causes. Each causal loss is then evaluated according to the total amount of emissions it generates, which are also converted into appropriate economic terms. Finally, to select the correct improvement actions, a cost/benefit analysis is performed based on technical and economic factors that include both cash flows and the marketing impact on the end customer due to the commitment to sustainability. The proposed approach was applied to a major company operating in the plywood production sector in order to demonstrate its validity and effectiveness in production systems.
The large-scale convection during the Asian summer monsoon plays an important role in the rapid transport of boundary layer aerosols into the Asian summer monsoon anticyclone. Here, using the state-of-the-art ECHAM6–HAMMOZ aerosol-chemistry-climate model, we show that these aerosols are further transported to the Arctic along isentropic surfaces by the Brewer-Dobson-Circulation (BDC) during the monsoon season. Our model simulations show that East and South Asian anthropogenic emissions contribute significantly to the aerosol transported to the Arctic, which causes a higher negative net aerosol radiative forcing at the surface (dimming) of −0.09 ± 0.02 Wm ⁻² and −0.07 ± 0.02 Wm ⁻² , respectively. Over the Arctic, the East Asian anthropogenic aerosols that include large amounts of sulfate cause a seasonal mean net radiative forcing at the top of the atmosphere (TOA) of −0.003 ± 0.001Wm ⁻² and a surface cooling of −0.56 K while the black carbon dominated aerosol from South Asia shows a positive TOA forcing of +0.004 ± 0.001Wm ⁻² with an only minor surface cooling of −0.043 K. Overall, the long-range transport of South Asian aerosols results in a notably warming throughout the atmospheric column but minimal temperature response at the Arctic surface. Conversely, East Asian aerosols cool the troposphere and heat the lower stratosphere in the Arctic. The Asian aerosol thus plays an ambivalent role, with the East Asian sources in particular having the potential to counteract the rapid rise in Arctic temperatures and the associated melting of snow and ice.
Background and aims
An overlooked fraction of the terrestrial carbon (C) pool is that associated with biogenic silica deposited in plants (phytoliths), so-called PhytOC. This fraction is small compared with the main C pools, but is of interest because it could be a long-term C sink as phytoliths may protect organic C from mineralization. However, the topic is hotly contested and unclear due to both methodological and theoretical limitations.
Scope
We aim to review this topic, with specific emphasis on: (i) the range of C concentrations associated with phytoliths; (ii) soil phytolith preservation and subsequent organic C mineralization; and (iii) global estimates of C sequestration within PhytOC.
Conclusions
Recent work has suggested that [PhytOC] could be much greater than currently acknowledged, but also highly variable and dependent on cell silicification types. A short case study using cryo‐Scanning Electron Microscopy (cryo-SEM), X‐ray microanalysis (EDX), plus Focused Ion Beam (FIB) and Scanning Transmission Electron Microscopy (STEM) on the culms of a sedge (Schoenus caespititius) confirmed this thinking. Understanding of both phytolith and PhytOC fates in soil is poor. We suggest that phytolith residence time should be seen as a gradient. Such a continuum is explained by different phytolith sizes, types and chemistry, which will also have contrasting PhytOC. Our estimation of C sequestration as PhytOC each year (11–190 Tg C yr⁻¹) represents between < 1% and 13% of the C that could be sequestered globally in soils (estimated at 1400 Tg C yr⁻¹). We conclude that (1) more research is needed to improve our understanding of the formation and fate of PhytOC in terrestrial ecosystems and (2) it would be unwise to put our faith in PhytOC sequestration or other related methodologies to “solve” the climate crisis.
In recent years, opportunities have opened up to develop and validate glacier models in regions that have previously been infeasible due to observation and/or computational constraints, due to the availability of globally-capable glacier evolution modelling codes and spatially-extensive geodetic validation data. The glaciers in the tropical Andes represent some of the least observed and modelled glaciers in the world, making their trajectories under climate change uncertain. Studies to date, have typically adopted empirical models of the surface energy balance and ice flow to simulate glacier evolution under climate change, but these may miss important non-linearities in future glacier mass changes. We combine two globally-capable modelling codes that provide a more physical representation of these processes: i) JULES which solves the full energy balance of snow and ice; and ii) OGGM which solves a flowline representation of the shallow ice equation to simulate ice flow. JULES-OGGM is applied to over 500 tropical glaciers in the Vilcanota-Urubamba basin in Peru and is evaluated against available glaciological and geodetic mass balance observations to assess the potential for using the modelling workflow to simulate tropical glacier evolution over decadal timescales. We show that the JULES-OGGM model can be parameterised to capture decadal (2000–2018) mass changes of individual glaciers, but that limitations of the JULES prognostic snow model prevent accurate replication of observed surface albedo fluctuations. We conclude that this inhibits the robustness of extrapolating the JULES parameters across multiple glaciers. When driven with statistically-downscaled climate change projections, the JULES-OGGM simulations indicate that, contrary to point-scale energy balance studies, sublimation plays a very minor role in glacier evolution at the basin scale and does not bring about significant non-linearities in the glacier response to climate warming. The ensemble mean simulation estimates that total glacier mass will decrease to 17 % and 6 % of that in 2000 by 2100 for RCP4.5 and RCP8.5 respectively which is more conservative than estimates from some other global glacier models.
In this study, we explored the frequency and occurrence rate of maximum river discharges in the Una and Sana rivers, to understand hydrological variations amidst climate change. We categorized maximum discharges into severe (Una River M1 > 98.2 m3/s; Sana River M1 > 118.2 m3/s) and extreme (Una River, M2, > 123.4 m3/s; Sana River M2 > 246.4 m3/s) events, and identified trends in these events, crucial for assessing environmental impacts. Our findings reveal a nuanced pattern: both rivers experience an increase in severe events from 58 to 55 and 56 to 54 days return period respectively, indicating complex hydrological dynamics. The trends underscore the significant shifts in annual event occurrences, the evolving nature of river systems and underscore the necessity for adaptive management strategies.
Introdução e Objetivo. Este artigo examina as proposições dos Parâmetros Curriculares Nacionais (PCN) para o Ensino Fundamental e as deliberações preconizadas pela Base Nacional Comum Curricular (BNCC) para as instituições e redes de ensino brasileiras. Metodologia. Empregou-se a metodologia de análise de conteúdo e de revisão da literatura correlata, sob perspectiva holística, para avaliar de que forma os temas sobre Ciências da Terra e sobre mudanças do clima são apresentados, abordados e distribuídos nos componentes curriculares. Resultados. Após a homologação da BNCC, há uma concentração de conceitos e elucidações de processos e fenômenos terrestres na disciplina Ciências, ao passo que a disciplina Geografia se incumbe de correlacionar os conceitos à problemática socioambiental e econômica. Verifica-se a grande dispersão e a descontextualização das temáticas geocientíficas, que dificultam a compreensão sistêmica e holística do Sistema Terra e da problemática socioambiental atual. Conclusão. Em concordância com a literatura que sustenta a argumentação deste trabalho, vislumbramos as práticas pedagógicas interdisciplinares e/ou o advento de um componente curricular específico de Ciências da Terra como alternativa para sistematizar e contextualizar as temáticas geocientíficas.
Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.
The acquisition and dissemination of essential information for understanding global biogeochemical interactions between the atmosphere and ecosystems and how climate–ecosystem feedback loops may change atmospheric composition in the future comprise a fundamental prerequisite for societal resilience in the face of climate change. In particular, the detection of trends and seasonality in the abundance of greenhouse gases and short-lived climate-active atmospheric constituents is an important aspect of climate science. Therefore, easy and fast access to reliable, long-term, and high-quality observational environmental data is recognised as fundamental to research and the development of environmental forecasting and assessment services. In our opinion article, we discuss the potential role that environmental research infrastructures in Europe (ENVRI RIs) can play in the context of an integrated global observation system. In particular, we focus on the role of the atmosphere-centred research infrastructures ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure), IAGOS (In-service Aircraft for a Global Observing System), and ICOS (Integrated Carbon Observation System), also referred to as ATMO-RIs, with their capabilities for standardised collection and provision of long-term and high-quality observational data, complemented by rich metadata. The ATMO-RIs provide data through open access and offer data interoperability across different research fields including all fields of environmental sciences and beyond. As a result of these capabilities in data collection and provision, we elaborate on the novel research opportunities in atmospheric sciences which arise from the combination of open-access and interoperable observational data, tools, and technologies offered by data-intensive science and the emerging collaboration platform ENVRI-Hub, hosted by the European Open Science Cloud (EOSC).
The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations.
The negative trend of PM2.5 in southwestern Taiwan could be offset in the future because of the stabilisation of the atmospheric layer with the decreasing strength of the East Asian winter monsoons. However, phenomena such as changes in the moisture source and the washout effect can help reduce PM2.5 levels. To assess these phenomena, hourly PM2.5 levels, weather parameters, and surface weather maps were obtained from the relevant government authorities in Taiwan. Trend, multiregression, and basic statistical methods were used in this study. The study period was divided into two separate parts. P1 (1959–1976) represents the averaged period, and P2 represents the warming period (1977–2021). The rainy-day weather patterns suggested that the percentage of moisture in the weak continental high area south of the Yangtze River basin in China and the southern region outside Taiwan Island was more substantial during P2 (28.3%) than during P1 (7.3%) because the frequency and intensity of rainfall increased in P2. The rainfall pattern in the Kaoping area from 2005 to 2021 changed from low rainfall and decreasing rainfall frequency to high rainfall and increasing rainfall frequency. Multiregression models showed that the negative contribution of the washout effect to the variation in the annual mean PM2.5 was more significant than the positive contribution of air dispersion. This suggests that in tropical regions with poor air dispersion and winter monsoons, the frequency and type of rainfall affect the variations in PM2.5 under climate change.
The Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut (74°55′N, 109°34′W) was established in 2003 to examine Arctic ecosystem processes that would be impacted by climate warming and permafrost degradation. This paper provides a synthesis of how remote sensing has contributed to biogeophysical modelling and monitoring at the CBAWO from 2003 to 2023. Given the location and isolated nature of the CBAWO in the Canadian High Arctic, remote sensing data and derivatives have been instrumental for studies examining ecosystem structure and function at local and landscape scales. In combination with field measurements, remote sensing data facilitated mapping and modelling of vegetation types, % vegetation cover and aboveground phytomass, soil moisture, carbon exchange rates, and permafrost degradation and disturbance. It has been demonstrated that even in an environment with limited vegetation cover and phytomass, spectral vegetation indices (e.g., the normalized difference vegetation index) are able to model various biogeophysical variables. These applications are feasible for research sites such as the CBAWO using high spatial resolution remote sensing data across the visible, infrared, and microwave regions of the electromagnetic spectrum. Furthermore, as the satellite record continues to expand, we will gain a greater understanding of the impacts arising from the expected continued warming at northern latitudes. Although the logistics for research in the Arctic remain challenging, today's technologies (e.g., high spatial resolution satellite remote sensing, automated in situ sensors and data loggers, and wireless communication systems) can support a host of scientific endeavours in the Arctic (and other remote sites) through modelling and monitoring of biogeophysical variables and Earth surface processes with limited but critical field campaigns. The research synthesized here for the CBAWO highlights the essential role of remote sensing of terrestrial ecosystems in the Canadian Arctic.
This project makes use of the ARIMA (AutoRegressive integrated moving common) model to forecast web site visitors on weather-related web sites, analyzing how temperature fluctuations affect tourist numbers. ancient web visitors and temperature records are amassed, preprocessed, and analyzed. The ARIMA version is enhanced by way of incorporating temperature as an external regressor, optimizing forecasting accuracy via cautious parameter tuning. This method is evaluated towards traditional models to assess its effectiveness. The findings reveal that integrating temperature records notably improves predictive overall performance, supplying precious insights for managing web content based totally on environmental elements and predicting visitors developments with more precision.
Qiongzhuea tumidinoda stands out as an endemic bamboo species of significant conservation importance in Southwest China, particularly in the upper reaches of the Yangtze River. It holds a pivotal role in poverty alleviation through the commercialization of its wood and bamboo shoots. However, the suitable area of this species is undergoing rapid changes due to climate change, resulting in species redistribution and potential losses for bamboo farmers. We utilized 209 presence records and 25 environmental variables from 1987 to 2012 to predict the potentially suitable habitats for Q. tumidinoda using MaxEnt, ArcGIS, and R. We rigorously screened the recorded data for reliability and accuracy through expert consultations and observer interviews. We performed pre-processing to select the variables with high contributions for modeling, and 11 variables were selected for the final modeling. Our findings reveal that the top three most influential variables associated with Q. tumidinoda's distribution were the mean monthly potential evapotranspiration (Pet), annual range of air temperatures (Bio7), and mean diurnal air temperature range (Bio2), and the rates of contributions from 1987 to 2012 were 4.8333, 3.5833, and 1.7000. There was a southeastward shift and an elevation increase in the potentially suitable habitats for Q. tumidinoda. The area of potentially suitable habitats in the study region exhibited fluctuating growth, expanding from 3063.42 km2 to 7054.38 km2. The mean monthly potential evapotranspiration (Pet) emerged as a critical determinant shaping the distribution of potentially suitable habitats for Q. tumidinoda. Our study sheds light on the response of Q. tumidinoda to climate change, offering valuable insights for the development and management of plantation industries associated with this species. In the future, to enhance prediction accuracy, researchers could equally consider both organic and inorganic environmental variables. For better preservation of environment and development, Q. tumidinoda could be introduced into nature restoration projects in areas with a suitable habitat or as a commodity that participates in forest carbon sink trading.
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