Climate Zones In China Research Articles

The impact of residential winter HVAC usage behavior on arthritis in older adults: A PLS-SEM analysis

Environmental factors like temperature and humidity have been shown to influence arthritis symptoms in older adults, and HVAC equipment can regulate indoor environmental parameters. This study aimed to explore the pathways and effectiveness of residential HVAC usage behavior during winter on arthritis conditions. Conducted across four major climate zones in China, this cross-sectional study involved 3579 older adults aged 60–74 years and collected data on demographics, residential environments, lifestyles, and health outcomes. Utilizing Partial Least Squares - Structural Equation Modeling (PLS-SEM), a complex structural equation model (SEM) and an HVAC-Health mediation model was developed to analyze the relationships among influencing factors and health outcomes. Results revealed that socio-economic status, building characteristics, lifestyles, HVAC usage behavior, and indoor environmental exposure significantly affect the frequency of arthritis flare-ups (p < 0.05). Specifically, lifestyles, indoor wet and cold exposures have strong direct effects on health outcomes, with path coefficients of 0.178, 0.155 and 0.143, respectively. Moreover, HVAC usage indirectly influences health through mediators, with cold exposure (β = 0.045, p < 0.001), air pollution (β = 0.025, p < 0.001), and wet exposure (β = 0.012, p = 0.001) ranked in terms of their mediating effects. This research underscores the crucial role of HVAC systems in mitigating arthritis symptoms in older adults, advocating for enhanced implementation of HVAC technologies in senior housing to promote health and well-being. The originality of this study lies in employing the PLS-SEM method to elucidate how the indoor environment—particularly under the premise of HVAC usage—affect arthritis symptoms in older adults.

The impact of climate change on variations in rutting resilience of asphalt pavement across the climate zones in China

This study aims to investigate resilience differences of asphalt pavements across China's climate zones in response to climate change. The impacts of climate change on rutting depth (RD), influence degree on rutting resilience, and Greenhouse Gas emissions in various climate zones were evaluated, and adaptation measures were proposed. The findings indicate that the warmer climate zones will be significantly affected. Freeways in these zones, serving for 10 years under projected climate conditions 40 years ahead, are expected to have RD increments exceeding 2 mm. Carbon dioxide equivalent emissions could increase by 23.1 million tons (a 39.4% increase) compared to current conditions. The degree of influence of climate change on rutting resilience will significantly differentiate among the climate zones. Four potential adaptation measures have been proposed to urgently enhance rutting resilience in response to climate change.

Application of PVT Coupled Solar Heat Pump System in the Renovation of Existing Campus Buildings

A photovoltaic thermal panel (PV/T) is an integrated module that harnesses both photovoltaic and solar thermal technologies to convert solar energy into electricity and heat, thereby enhancing overall energy efficiency. This paper aims to explore the suitability of PV/T solar heat pump systems across various climate zones and assess their potential for widespread application. By analyzing the operating principles of an indirect expansion PV/T solar heat pump system in conjunction with the climate characteristics of different regions, MATLAB R2019b/Simulink software was employed to evaluate the photoelectric performance of PV and PV/T systems in representative cities across five distinct climate zones in China during typical winter days. Key metrics, such as power generation, hot water storage tank temperature, indoor temperature, and system COP, were chosen to assess the heating performance of the PV/T solar heat pump system. The findings indicate that the winter ambient temperature significantly affects the photoelectric efficiency of both the PV and PV/T systems. While higher latitudes with lower ambient temperatures yield greater photoelectric efficiency, the southern regions exhibit higher power generation during winter. The winter heating effectiveness of the PV/T solar heat pump system is mainly influenced by indoor and water tank temperatures, with Harbin’s system performing the poorest and failing to meet heating demands, whereas Nanjing’s system shows the best results.

Site-based climate-smart tree species selection for forestation under climate change

Global climate change threatens ecosystem functions and resilience, prompting large-scale planting initiatives to mitigate its impacts. To ensure new plantations are adaptive to future climates, it is crucial to consider climate mismatches resulting from climate change when selecting tree species. However, current research is all species-based, which is not effective for species selection across species at specific plantation sites. Our research developed a novel site-based approach that can identify optimal tree species for specific planting sites under projected future climates. We evaluated the feasibility and effectiveness of this method across 10 representative sites in diverse climatic zones in China based on climate niche projections for 100 key tree species. Our findings demonstrated the necessity and effectiveness of this approach, which can select a suit of suitable tree species tailored for any potential planting site across China under different climate change scenarios. For instance, at Tibet Dongjiu Forest farm, Aibes densa and Quercus pannosa currently showed high suitability scores above 0.8 (on a scale of 0–1). However, by the 2080s, Aibes densa's suitability was projected to drop to 0.25, while Quercus pannosa was expected to maintain its suitability. Conversely, Quercus aquifolioides currently had a low suitability of 0.08, but it was projected to increase to 0.74 by the 2080s. These findings demonstrate the importance of using this approach to avoid selecting the wrong species or overlooking potentially suitable species. In addition, our simulation analysis suggests that a dataset of 40–50 species is necessary to ensure that most planting sites can identify 2–3 suitable species. This advancement significantly enhances the precision and effectiveness of tree species selection strategies for local practitioners, offering vital insights for forestry, conservation, and ecological restoration projects. These results highlight the tremendous potential and practical applicability of our site-based approach in enhancing forestry adaptation and ecological functions in response to global climate change.

Machine learning models for daily net radiation prediction across different climatic zones of China

Net radiation (Rn), a critical component in land surface energy cycling, is calculated as the difference between net shortwave radiation and longwave radiation at the Earth’s surface and holds significant importance in crop models for precision agriculture management. In this study, we examined the performance of four machine learning models, including extreme learning machine (ELM), hybrid artificial neural networks with genetic algorithm models (GANN), generalized regression neural networks (GRNN), and random forests (RF), in estimating daily Rn at four representative sites across different climatic zones of China. The input variables included common meteorological factors such as minimum and maximum temperature, relative humidity, sunshine duration, and shortwave solar radiation. Model performance was assessed and compared using statistical parameters such as the correlation coefficient (R2), root mean square errors (RMSE), mean absolute errors (MAE), and Nash–Sutcliffe coefficient (NS). The results indicated that all models slightly underestimated actual Rn, with linear regression slopes ranging from 0.810 to 0.870 across different zones. The estimated Rn was found to be comparable to observed values in terms of data distribution characteristics. Among the models, the ELM and GANN demonstrated higher consistency with observed values, exhibiting R2 values ranging from 0.838 to 0.963 and 0.836 to 0.963, respectively, across varying climatic zones. These values surpassed those of the RF (0.809–0.959) and GRNN (0.812–0.949) models. Additionally, the ELM and GANN models showed smaller simulation errors in terms of RMSE, MAE, and NS across the four climatic zones compared to the RF and GRNN models. Overall, the ELM and GANN models outperformed the RF and GRNN models. Notably, the ELM model's faster computational speed makes it a strong recommendation for Rn estimates across different climatic zones of China.

Research on the contribution rate of photovoltaic power in indoor ice arenas across different climatic zones: A case study in China

With the increasing construction of ice arena facilities, addressing their energy consumption issues has become crucial, emphasizing the need for renewable energy utilization. This study aims to determine the contribution rate of photovoltaic (PV) power generation in indoor ice arenas across different climate zones in China and proposes corresponding PV application strategies. By modeling the vertical zoning above the ice arena, energy consumption in indoor ice arenas across six typical cities was simulated, calculating annual and monthly renewable energy contribution rates and proposing utilization strategies. The research reveals a growing proportion of cooling energy consumption due to climate warming, exceeding half of the total energy even in cold cities. Differences in energy consumption and renewable energy contribution rates among cities highlight the impact of local climate conditions. Favorable climates and abundant solar resources in some cities enable more energy-efficient ice arena construction, while high energy consumption and limited solar resources pose challenges in others. The study identifies seasonal variations in renewable energy contribution rates, emphasizing the need to optimize power generation seasonally. In colder cities, summer power generation is essential, while in hotter climates, winter power generation is more advantageous. This study provides insights for designing energy-efficient and sustainable ice arenas.

Thermophysical properties and energy-saving efficiency of phase change microcapsule foamed cement composite insulation materials

The addition of phase change materials (PCMs) to building envelopes can improve building thermal stability and reduce energy consumption. In this study, phase change paraffin microcapsules are combined with foamed cement to create composite thermal insulation materials with varying mass ratios of microcapsules. A heat transfer characterization experimental platform was established to investigate the heat transfer laws. The incorporation of phase change microcapsules (MPCMs) into foamed cement resulted in a reduction in thermal conductivity. The thermal conductivity of the test blocks exhibited a linear relationship with the mass ratio of MPCMs, with an average thermal conductivity of 0.053 W/(m-K) observed for 20 % MPCMs. The impact of foamed cement containing MPCMs on building energy consumption was analyzed in five different climate zones in China using EnergyPlus. The results show that energy savings are more significant in cities with higher heating demand. In non-cold regions, energy savings are highest when the phase change temperature is close to the local annual average temperature. The optimal energy saving program is evaluated by energy consumption simulation. The results show that it achieves the highest energy savings in Harbin, which saves a total of 1074,007 kWh. Additionally, it has the highest energy saving rate in Beijing, with a rate of 14.66 %.

Tackling the modifiable areal unit problem: Enhancing urban sustainability through improved land surface temperature and its influencing factors analysis

Exploring the modifiable areal unit problem (MAUP) in land surface temperature (LST) and its influencing factors is crucial for understanding LST variation patterns and quantifying the factors' impact. Neglecting the MAUP could lead to an incomplete understanding of LST changes and their driving mechanisms. This study used optimal parameters-based geographical detector and gradient boosting regressor models to investigate the MAUP in LST and its influencing factors. The analysis covered 87 cities across seven climate zones in China, examining MAUP in 12 spatial scales to discern the scale and zoning effects on LST and its influencing factors. The research findings were as follows: (1) The sensitivity of LST influencing factors to spatial scales exhibited both spatial and temporal heterogeneity. Significant differences in the q-values of LST influencing factors were observed across various climate zones and periods (daytime and nighttime), with human factors, particularly those related to residents' work, buildings, life, and rest, showing higher spatial scale dependency than natural factors. (2) Zoning effects significantly impacted the q-values of LST influencing factors and were closely linked to the discretization methods and quantities used, which could alter the trends of these q-values. (3) Across the 12 spatial scales, more than 67.34 % of LST influencing factor interaction types were classified as bi-variable enhancement types. The q-values for LST influencing factor interactions were higher and more stable than those of single factors. LST influencing factor interactions in transitional climate zones exhibited high sensitivity to spatial scales. This research enhances our understanding of LST variations, providing valuable insights for urban climate adaptability planning and the development of climate-resilient cities.

Primary return air or all fresh air? A novel method for air source designing of heat pump desiccant wheel systems

Hybrid desiccant wheel systems are widely adopted for low humidity control in industrial field. The clarification of process and regeneration air management is required to achieve energy saving. The all-fresh air dehumidification and primary return air dehumidification are compared for a high-polymer desiccant wheel and heat pump system. The system simulation model was established and validated by field test results of a low humidity industrial workshop. Firstly, the fresh air flowrate and air stream pattern are analyzed and optimized, for achieving low annual energy consumption. Secondly, the system power of the optimized fresh air mode and primary return air mode were compared for different outdoor air temperature, outdoor air humidity and indoor humidity requirement. At last, energy saving rate of all fresh air dehumidification mode was analyzed for five typical climate zones in China. It was found that the optimized fresh air flowrate numerically equals to the summation of regeneration air flowrate and the positive pressure required air flowrate. With the optimized fresh air flowrate, 20.4% of the annual energy can be saved compared with primary return air system. Outdoor air conditions were divided into three zones on psychrometric chart, and the boundaries are related to indoor temperature and humidity ratio. Fresh air is energy efficient for high temperature high humidity and low temperature low humidity conditions. By using fresh air dehumidification mode, the energy saving rate can reach 69.6% for severe cold region. Primary return air dehumidification mode is suitable for HSCW and HSWW region for indoor relative humidity of 40%, and 41.8% of the energy can be saved.

Multi-objective optimization of daylighting performance and energy consumption of educational buildings in different climatic zones of China

With the implementation of China's “Healthy Building” and “Dual Carbon” strategies, daylight health and energy-saving carbon reduction in buildings have become key research areas. In educational buildings, early design decisions significantly impact students' eye health and energy consumption reduction, making it crucial to balance these concerns. Studies indicate that sufficient and continuous daylight can significantly improve students' eye health, mood and sleep. To maximize the UDI level at the eye level (seated) and minimize EUI and DGP, this study used the multi-objective optimization tool Wallacei based on NSGA-II (Non-dominated Sorting Genetic Algorithm II) for genetic optimization. This study uses the Shiji Building of Central South University in Changsha, Hunan, as a reference model to provide optimal classroom designs for China's five major thermal design zones: severe cold, cold, hot summer and warm winter, hot summer and cold winter, and mild. The results indicate that optimizing the classroom's deflection angle, length, width, height, and WWR significantly improves energy efficiency and daylighting performance. Specific data shows that an orientation 5° east or 5° west of south helps balance energy consumption and daylighting performance in both large and small classrooms. The length and width of the classrooms vary greatly, but the height generally converges to 3.2 m. Increasing the WWR to 0.5–0.7 demonstrates good energy efficiency and daylighting performance in both large and small classrooms in hot climate zones. In all climate zones, compared to the initial scheme, the Knee solutions reduced the EUI of both types of classrooms by up to 19.0 %, reduced DGP by up to 56.4 %, and increased UDI by up to 19.0 %.

Optimal HVAC setpoints for energy efficiency and thermal comfort in Chinese residential buildings

The easiest way to improve energy efficiency and thermal comfort in existing buildings is to adjust setpoints. However, although Chinese standards regulated the heating and cooling setpoints for different climate zones in China, they lacked consideration for occupants’ thermal comfort and ignored the ventilation setpoints. Therefore, this study aimed to identify optimal heating, cooling, and ventilation setpoints at the design stage to enhance building energy performance and indoor thermal comfort in Chinese residential buildings. This study used DesignBuilder to simulate the energy usage and thermal comfort with different setpoints and judged which combination was the best. To conduct this study across the whole of China, the typical cities in different climate zones were selected by using machine learning. Results indicated that adjusting setpoints in Harbin, Beijing, and Shanghai could increase comfortable days by 43.95 %, 54.23 %, and 23.36 % respectively, with minimal impact on energy usage. In Guangzhou, energy usage could be reduced by 7.56 % with a 5.91 % decrease in comfortable days, while Kunming could see an 11.11 % increase in comfortable days with a 5.92 % rise in energy consumption. Additionally, sensitivity analysis revealed that activity template variation was most critical for energy usage in Harbin, Beijing and equipment power density variation was most important for thermal comfort in Shanghai, Guangzhou, and Kunming. Furthermore, proposed setpoint combinations demonstrated resilience to future weather conditions in most typical cities, except for Guangzhou. These findings provide valuable insights for designers and researchers aiming to retrofit residential buildings, emphasizing the importance of considering both energy efficiency and occupant comfort. This study introduces innovative approaches like comprehensive setpoint optimization and machine learning for typical city selection, providing practical solutions to improve energy efficiency and thermal comfort in residential buildings.

Impact of urban form on building energy consumption in different climate zones of China

Despite numerous studies on the relationship between urban form and building energy demand, understanding the impact mechanisms of urban form is still insufficient. Here, we identified the direct and indirect influences of urban form on building energy demand. The direct influence includes the blocking of solar radiation. The indirect influence is exerted through the urban heat island (UHI) effect as different urban forms produce different UHI intensities. The UHI effect was calculated using the urban weather generator (UWG) tool. Then, the analysis of the direct and indirect influences on the building energy demand was carried out using building energy modeling (BEM) based on the output of UWG. Five cities in different building climate zones in China were investigated, and the corresponding direct and indirect influences were quantified based on the proposed UWG + BEM framework. Results show that warmer temperatures lead to an average increase in space cooling of 16 %–46 % while reduced space heating of 8 %–17 %. The shading of surrounding buildings allows an increase of 7 %–36 % in space heating and a decrease of 14 %–48 % in space cooling compared to that of an isolated building. In addition, direct influence due to shading is prominent in Shuangyashan, Xuzhou, and Fuzhou, accounting for 50 %, 80 %, and 57 % of variations in building energy consumption.

Numerical study of the impact of make-up air in a residential kitchen on the heating and cooling demands of ULEBs

Ventilation significantly impacts energy consumption in ultra-low-energy buildings (ULEBs). However, in Chinese residential kitchens, the influence of mechanical ventilation formed by range hoods and make-up air systems on energy consumption has received limited attention. This study assesses the heating and cooling demands in ULEBs resulting from kitchen make-up air across different climate zones in China. The results reveal that in natural make-up air mode, there is a substantial rise in annual heating demand in cold and severe cold zones and a notable increase in annual cooling demand in hot summer and warm winter as well as hot summer and cold winter zones. Additionally, the natural make-up air mode often poses challenges in maintaining a satisfactory thermal environment in kitchens during both heating and cooling seasons. Conversely, the mechanical make-up air mode, especially with pretreatment of outdoor air to ensure thermal comfort in kitchens, significantly elevates both annual heating and cooling demands, making it hard for the building to meet the ULEB specifications, particularly in cold and severe cold zones. Furthermore, despite a generally small increase in annual cooling demand, the percentage rise in heating demand often exceeds the ULEB limits, ranging from 12.0% to 36.0%, depending on the climate zone.

Field measurement study of indoor thermal environment of badminton halls in a hot summer and cold winter region in different seasons in China

The indoor thermal environment has a direct impact on human thermal comfort and health. In order to assess the status of the indoor thermal environment of typical sports buildings in hot summer and cold winter climate zones in China, 14 badminton halls in 10 cities in Hubei Province (including 5 venues in Wuhan) in this climate zone are chosen as research objects for field testing of indoor thermal environment parameters in 4 seasons. All the tested stadiums are naturally ventilated in non-event conditions. The results reveal that the average indoor temperature of badminton halls in summer is excessively high (i.e., 31.89 °C), which is higher than the regulation specified in JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in summer, (i.e., (26–28 °C) or (22–28 °C), respectively). The average indoor temperature of badminton halls in winter is too low (i.e., 12.95 °C), and it is lower than the recommendations of JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in winter (i.e., (16–18 °C) or (16–24 °C), respectively), relative humidity and air velocity are in the thermal comfort interval for all seasons, and the indoor thermal environment factors of badminton courts in spring and autumn meet the comfort requirements. The indoor and outdoor temperatures and the relative humidity of badminton courts are highly correlated. The indoor temperature and relative humidity vary according to changes in those factors outdoors, whereas the air velocity is not affected by outdoor changes. In the hot summer and cold winter climate zones, some discrepancies in the indoor temperature variation patterns of badminton halls at various altitudes are detectable. The results of this study aim to provide a solid basis for the development of indoor thermal-comfort standards for sports stadiums in China.

The impacts of global warming on climate zones over China based on CMIP6 models

AbstractClimate zones are expected to shift in response to climate change, which significantly influences vegetation distribution and provides essential guidance for human activities including production, lifestyle and economic development. Quantifying the shifts in climate zones due to global warming is therefore crucial. The primary metric for categorizing climate zones is the number of days with a daily mean temperature above 10°C (DT10). Utilizing DT10 and the ERA5 reanalysis data, it is observed that climate zones in China have gradually shifted northward over the past 65 years. Notably, the interdecadal changes in the climate zones differ between the eastern and western regions divided by the 110°E longitude. The western regions show minimal shifts, whereas the eastern regions, particularly the central and southern parts of Northeast China, exhibit obvious northward shifts. Consequently, the simulation capabilities of 41 CMIP6 models for Chinese climate zones were assessed, and it was found that 11 models demonstrated robust performance. These models were further used to analyse interdecadal variations and project future shifts in climate zones in China. The results show that the spatial pattern of climate zones in China can be well captured by the CMIP6 models, except for ACCESS‐CM2, FGOALS‐g3 and GFDL‐CM4. Each CMIP6 model seems to be more suitable for specific climatic zones concerning trends and decadal variations in China. By 2100, a northward shift is projected for all climate zones in the east of 110°E under SSP2‐4.5 and SSP5‐8.5 emission scenarios, particularly in northern China. It should be noted that the potential disappearance of the northern subtropical belt, likely to be replaced by the middle subtropical belt in the future.

Population genetic structure of Culex tritaeniorhynchus in different types of climatic zones in China

BackgroundCulex tritaeniorhynchus is widely distributed in China, from Hainan Island in the south to Heilongjiang in the north, covering tropical, subtropical, and temperate climate zones. Culex tritaeniorhynchus carries 19 types of arboviruses. It is the main vector of the Japanese encephalitis virus (JEV), posing a serious threat to human health. Understanding the effects of environmental factors on Culex tritaeniorhynchus can provide important insights into its population structure or isolation patterns, which is currently unclear.ResultsIn total, 138 COI haplotypes were detected in the 552 amplified sequences, and the haplotype diversity (Hd) value increased from temperate (0.534) to tropical (0.979) regions. The haplotype phylogeny analysis revealed that the haplotypes were divided into two high-support evolutionary branches. Temperate populations were predominantly distributed in evolutionary branch II, showing some genetic isolation from tropical/subtropical populations and less gene flow between groups. The neutral test results of HNQH (Qionghai) and HNHK(Haikou) populations were negative (P < 0.05), indicating many low-frequency mutations in the populations and that the populations might be in the process of expansion. Moreover, Wolbachia infection was detected only in SDJN (Jining) (2.24%), and all Wolbachia genotypes belonged to supergroup B. To understand the influence of environmental factors on mosquito-borne viruses, we examined the prevalence of Culex tritaeniorhynchus infection in three ecological environments in Shandong Province. We discovered that the incidence of JEV infection was notably greater in Culex tritaeniorhynchus from lotus ponds compared to those from irrigation canal regions. In this study, the overall JEV infection rate was 15.27 per 1000, suggesting the current risk of Japanese encephalitis outbreaks in Shandong Province.ConclusionsTropical and subtropical populations of Culex tritaeniorhynchus showed higher genetic diversity and those climatic conditions provide great advantages for the establishment and expansion of Culex tritaeniorhynchus. There are differences in JEV infection rates in wild populations of Culex tritaeniorhynchus under different ecological conditions. Our results suggest a complex interplay of genetic differentiation, population structure, and environmental factors in shaping the dynamics of Culex tritaeniorhynchus. The low prevalence of Wolbachia in wild populations may reflect the recent presence of Wolbachia invasion in Culex tritaeniorhynchus.

A Study on the Daylighting, Energy Consumption, and Climate Adaptability of Curved Mesh Shading Based on the Parametric Performance Design Method

Building shading forms are becoming increasingly diversified, driven by both building performance requirements and architectural aesthetics. The application of computer technology in shading design and performance evaluation is becoming increasingly popular. This study adopted a parametric performance design method and created a one-click workflow for parametric curved mesh shading design and performance evaluation based on the Grasshopper platform and Ladybugtools. Applying this workflow, this paper takes five typical cities in different climate zones in China as examples to analyze the impact rules of curved mesh shading parameters (blade width, number of horizontal grids, and number of vertical grids) on building daylighting and energy consumption and explore the application potential of curved mesh shading. This study found that curved mesh shading has the best potential to improve daylighting in Harbin and can increase the annual average UDIa (300~3000 lux) by 7.42%. In Guangzhou, curved mesh shading has the highest potential for energy saving, which can reduce annual energy consumption by 14.8%. This study can provide theoretical, methodological, and data support for the optimal design of curved mesh shading.

The Time Lag Effects and Interaction among Climate, Soil Moisture, and Vegetation from In Situ Monitoring Measurements across China

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity.

Contrasting range changes and drivers of four forest foundation species under future climate change in China

Forest foundation species, vital for shaping community structure and dynamics through non-trophic level interactions, are key to forest succession and sustainability. Despite their ecological importance, the habitat ranges of these species in China and their responses to future climate change remain unclear. Our study employed the optimal MaxEnt model to assess the range shifts and their essential drivers of four typical forest foundation species from three climatic zones in China under climate scenarios, including Acer tegmentosum, Acer pseudo-sieboldianum (temperate zone), Quercus glandulifera (subtropical zone), and Ficus hispida (tropical zone). The optimal MaxEnt model exhibited high evaluation indices (AUC values > 0.90) for the four foundation species, indicating excellent predictive performance. Currently, we observed that A. tegmentosum and A. pseudo-sieboldianum are predominantly inhabited temperate forest areas in northeastern China, Q. glandulifera is primarily concentrated in subtropical forests in southeastern China, and F. hispida is mainly distributed across the tropical forests in southern China. Climate factors, particularly temperature, emerged as the primary environmental factors influencing the potential range of forest foundation species. Moreover, precipitation strongly influenced the potential range of A. tegmentosum and A. pseudo-sieboldianum, while elevation exhibited a greater impact on the range of Q. glandulifera and F. hispida. Under future climate scenarios, suitable areas for A. tegmentosum and A. pseudo-sieboldianum tend to expand southward, F. hispida tends to expand northward, while Q. glandulifera exhibited a tendency to contract towards the center. This study advances our understanding of the spatial and temporal dynamics of forest foundation species in China under climate change, providing critical insights for conservation efforts and sustainable forest management practices.

The Relationship between Trait-Based Functional Niche Hypervolume and Community Phylogenetic Structures of Typical Forests across Different Climatic Zones in China

Functional traits are pivotal for understanding the functional niche within plant communities. Yet, the relationship between the functional niches of typical forest plant communities across different climatic zones, as defined by functional traits, and their association with community and phylogenetic structures remains elusive. In this study, we examined 215 woody species, incorporating 11 functional traits spanning leaf economy, mechanical support, and reproductive phenology, gathered from forests in four climatic zones from tropical, subtropical, warm-temperate to cold-temperate zones in China and supplemented by the literature. We quantified the functional niche hypervolume (FNH), reflecting the multidimensional functional niche variability. We then probed into the correlation between the FNH and community and phylogenetic structures of forests. Our findings reveal that species richness significantly influences the geographic variance of functional niche space in forest vegetation across different climatic zones. Specifically, a community’s species richness correlates positively with the functional niche breadth occupied by the community species. The FNH of woody plants across diverse forest types shows significant associations with both the mean phylogenetic distance (MPD) and the mean nearest phylogenetic taxon distance (MNTD) of the communities. There is a progressive increase in tropical rainforest (TF), subtropical evergreen deciduous broad-leaved mixed forest (SF), and warm-temperate coniferous broad-leaved mixed forest (WF), followed by a decline in the cold-temperate coniferous forest (CF). This pattern suggests potential environmental filtering in CF, which may constrain the spatial extent of plant functional niches. Our research underscores the substantial variability in the FNH across China’s typical forest vegetation, highlighting the complex interplay between functional traits, community richness, and phylogenetic distance.