Climate Change Trends Research Articles

Long-term change in relative humidity across China from 1961-2018

Using observational data of daily relative humidity obtained from 2479 meteorological stations from 1961-2018 and the homogenized monthly data set of national ground meteorological stations, this paper analyzes the climate change characteristics of average relative humidity across China as well as in 9 individual regions. From 1961-2018, the climate change trend in annual average relative humidity across China was negligible, but there were large differences among different regions. Overall, annual relative humidity in the Qinghai-Tibet Plateau and Xinjiang area showed a significant increase, while Northwest China, Northeast China and northern North China showed a significant decrease. Seasonally, average relative humidity in China chiefly decreased in spring, and there was no discernable trend in other seasons. The Qinghai-Tibet Plateau showed a significantly increasing trend in winter, spring and summer, especially in spring; Xinjiang exhibited a significant increasing trend in winter, summer and autumn; Northeast China presented a significantly decreasing trend in winter; Northwest China, North China, Central China and East China witnessed a significantly decreasing trend in spring; and South China and Southwest China showed a slightly decreasing trend across all 4 seasons. Large urban agglomerations exert an influence on relative humidity to some degree, with urban areas experiencing lower relative humidity than rural areas.

Awareness On Recent Trends of Global Climate Change

Awareness On Recent Trends of Global Climate Change

Nutrient optimization for plant growth in Aquaponic irrigation using Machine Learning for small training datasets

With the recent trends in urban agriculture and climate change, there is an emerging need for alternative plant culture techniques where dependence on soil can be eliminated. Hydroponic and aquaponic growth techniques have proven to be viable alternatives, but the lack of efficient and optimal practices for irrigation and nutrient supply limits its applications on a large-scale commercial basis. The main purpose of this research was to develop statistical methods and Machine Learning algorithms to regulate nutrient concentrations in aquaponic irrigation water based on plant needs, for achieving optimal plant growth and promoting broader adoption of aquaponic culture on a commercial scale. One of the key challenges to developing these algorithms is the sparsity of data which requires the use of Bolstered error estimation approaches. In this paper, several linear and non-linear algorithms trained on relatively small datasets using Bolstered error estimation techniques were evaluated, for selecting the best method in making decisions regarding the regulation of nutrients in hydroponic environments. After repeated tests on the dataset, it was decided that Semi-Bolstered Resubstitution Error estimation technique works best in our case using Linear Support Vector Machine as the classifier with the value of penalty parameter set to one. A set of recommended rules have been prescribed as a Decision Support System, using the output of the Machine Learning algorithm, which have been tested against the results of the baseline model. Further, the positive impact of the recommended nutrient concentrationson plant growth in aquaponic environments has been elaborately discussed.

Global Impacts of the COVID-19 Pandemic on the Environment, Economy, Education, Climate Change, Policy and Vaccination Trends

The effects of the coronavirus are obvious in every sectors of life. The COVID-19 pandemic has evidently disturbed global and local economies and the ecosystem. The COVID-19 pandemic has greatly interfered with the biotic and abiotic aspects of the environment. Hence the need for this review. This review article analyzed the effects of the COVID-19 on education, environmental ethics and policy, climate change, the physical environment, consumer behavior, the price and level of production of goods and services, disturbances in local and global economies, social gathering, the society, vaccination trends, and the impacts on man and his future generations. Articles search were conducted using, Web of Science, PubMed, Scopus index journals and Google Scholar databases for research articles, review related to COVID19, environment, national development and vaccine measures adopted globally. Vaccination is taking place all over the world, and this may help to curb the spread of the virus. The reduction in emissions have led to improvements in air quality which may be beneficial to the environment. Meanwhile, significant research is provided for the causes of pollution and the sudden stop in various form of economic activities, especially transportation. The implementation of environmental policy, development of research institute, employment opportunities, discovery of vaccine have improved national development.

Use of Allele-Specific Amplification for Rapid Identification of Aromatic and Non-aromatic Rice Germplasms.

In the current context of global climate change trends, threat to food and nutrition security, collection, conservation and management, and characterization and evaluation of crop germplasms especially traditional landraces are gaining momentum more than ever before. Aromatic rice is an elite category of cultivated rice having huge sociocultural heritage value, fetching premium prices globally. Hence, its identification, in situ conservation, and appropriate characterization are likely to augment reliability of this distinctive category of rice, and rice commodity chain actors. badh2.1 is recognised as the major allele responsible for rice 2-acetyl-1-pyrroline aroma production in a vast number of aromatic rice globally. However, most of the previous works on the genetics and biochemical pathways of aroma expression in rice have encompassed mainly Basmati, Sadri, Della, Jasmine, and a few modern hybrids. But apart from these spotlighted varieties, a myriad of indigenous, aromatic rice germplasms exists. Allele-specific amplification, a low-cost, accurate method invented by Bradbury et al. 2005, can be utilized successfully for discriminating the rarely explored aromatic and nonaromatic rice as described.

Vulnerability of forest ecosystems under the impact of climate change (case study Southeast Republic of Moldova

The forest ecosystems in the South-Eastern part of the country are distinguished by rich biological diversity, with rare species, located at the limit of their natural distribution area, induced by the presence of the territory at the contact of several biogeographical regions. Under the impact of current environmental changes, the sensitivity of forest ecosystems to climate change directly related to their ability to respond / adapt to these changes. The concomitant use of the eco-climatic indices De Martonne Aridity Index (IM) and the Ellenberg Coefficient (EQ) give the estimation of the exposure of tree mesophilic species to the aridization of the regional climate. It established that the forest ecosystems in the region have a high level of vulnerability to climate aridity, with tendencies towards a very high level of vulnerability - conditions that induce a lasting deficit in humidity and, respectively, forest degradation. Accelerated climate change trends will modify the sensitivity of forest species to water scarcity (increased risk), changes in the compositional structure of those ecosystems and chorological movements of species (from mesophilous deciduous forests in the temperate zone will move to climatic conditions specific to the growth and development of arid oak forests, with thermophilic species). We consider that the results are of practical interest in the sustainable management of the forestry sector.

English

Hydropower is cost effective environment friendly and worldwide proven sustainable energy source. Driven by streamflow stream flows, it is vulnerable to climate change and land use change. The hydropower production from the two-existing run-of-river hydropower projects on the Sondu Miriu River are vulnerable to rainfall variability and requires proper understanding of the climate change trends and policies to support sustainable hydropower development and put in place strategies for building resilience for the local communities. The objective of this paper is to examine climate change trends and their impacts on hydropower in the Sondu Miriu River basin. The methodology involved analysis of downscaled climate data from CORDEX for the period from 1950 to 2100, gridded data from Kenya Meteorological department for a period of 2007 to 2018, river flows data from Water Resources Authority for a period of 2007 to 2018 and hydropower output data from KenGen for a period of 2007 to 2018 to examine the climate change trends within the Sondu Miriu River basin and impacts on hydrology and hydropower. The results indicate that maximum and minimum annual temperature increased by 0.7 and 0.9°C, respectively between 1950 and 2005. Both the maximum and minimum annual temperatures are projected to increase by 1.9°C based on the RCP4.5 and RCP8.5 scenarios between 2006 and 2100 within the Sondu Miriu basin. Annual rainfall increased by 74.8 mm between 1950 and 2005. This is projected to increase by 24.7 and 117.8 mm based on RCP4.5 and RCP8.5 scenarios, respectively. For the period between 2007 and 2018, the observed maximum increased by 5°C while the minimum temperatures decreased by 1°C. The rainfall decreased by 193.14 mm while the mean daily river flows decreased by 0.3 m3/s annually during the same period. This resulted in the decrease of hydropower production by 8.3 GWh in Sondu Miriu HPP between 2007 and 2018 while the production reduced by 14.18 GWh for Sang’oro HPP between 2012 and 2018. Understanding climate change trends within Sondu Miriu River basin should guide the planning for hydropower development projects.   Key words: Climate change, hydropower, Sondu Miriu River basin, downscaling, impacts.

Monitoring climate change, drought conditions and wheat production in Eurasia: the case study of Kazakhstan

Wheat is an important global food security commodity. Kazakhstan is currently a producer and exporter of high-quality wheat to global markets. The most important wheat-growing regions, which lie in the northern part of Kazakhstan, are based on spring-sown rain-fed cultivation and are susceptible to climate change and drought. Using the monthly surface air temperature and precipitation data from 1950 to 2020 from 110 meteorological stations over Kazakhstan and in addition wheat cultivation data, the research aims to analyze climate change, drought occurrence, and wheat cultivation trends in Kazakhstan in recent 70 years and investigate relationships between wheat productivity and drought. The linear method and two drought indices (Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index) and in addition, Pearson's correlation coefficient have been used to characterise the climate change trends and vulnerability of agriculture in Kazakhstan to drought. The geographic information system (GIS) was applied to display climate change, drought, and wheat referenced information. The research has shown that the 70-year (1950–2020) linear rates of annual mean surface temperature in Kazakhstan have significantly increased (on average 0.31 °C per decade) with the precipitation trends are not obvious and fluctuated trends of drought. The wheat yield demonstrates strong internal variability and wheat yields were significantly correlated with 3-month June and July drought indices over the period of 1950–2020. The results underline the potential susceptibility of wheat yields in Kazakhstan to any future reductions in precipitation and increase in drought occurrence and intensity.

An Economic Analysis of Climate Change Trend and Its Impact in Sivagangai District of Tamil Nadu, India

The present study was taken up in Sivagangai district to examine the issues of trend in climate change, association between climate change and area, production and productivity of crops and impact of climate change on production of crops. The climate trend in Sivagangai district was studied using the descriptive statistics of skewness, kurtosis, coefficient of variation and compound growth rate of climatic variables of maximum temperature, minimum temperature and rainfall over the past 50 years from 1971 to 2020. Pearson correlation technique was used to analyze the degree of association between climatic variables and area, production and productivity of principal crops namely paddy, black gram and groundnut. Cobb-Douglas production function model was fitted to study the quantitative relationship between the average production of principal crops grown in the district and the climatic variables of temperature and rainfall and cropped area. Maximum temperature and minimum temperature were negatively skewed and rainfall was positively skewed. Kurtosis for maximum temperature was platykurtic and for the minimum temperature and rainfall of Sivagangai district, the kurtosis was Leptokurtic. The maximum temperature and minimum temperature were less variable and rainfall was highly variable. Pearson correlation coefficient revealed that maximum temperature, minimum temperature and rainfall had significant association with area, production and productivity of crops in Sivagangai district of Tamil Nadu. Cobb- Douglas production function analysis revealed that annual rainfall had a positive relationship with production of paddy. On the other hand, climatic variables of temperature and rainfall were not influencing the groundnut and black gram production.

Comparative Analysis and Statistical Optimization of Fuel Economy for Sustainable Vehicle Routings

In this 21st century, there has been an increase in the usage of renewable products for the economic drifting of vehicle transportations systems. Furthermore, due to recent trends in climate change, researchers have started focusing on statistical optimization techniques for sustainable vehicle routings. However, until now, a major gap has been noticed in the multidomain statistical analysis for optimizing the parametric levels of the vehicle fuel economy. Therefore, in this research work, two widely utilized cars (Toyota and GMC Yukon) are considered on a particular route of Jeddah for the collection of the fuel economy data under the realistic conditions of air conditioner temperature, traffic patterns, and tire pressure. The outcomes of the factorial design of the experiment highlight that the fuel economy is optimal under the low air conditioner temperature, light traffic patterns, and 34 PSI tire pressure. Three replications of the fuel economy have been considered, and the statistical significance of the correlated variables has been justified by implementing the analysis of variance (ANOVA) approach on the various levels of fuel economy. During the analysis, the statistical hypothesis for random exogenous factors has been developed by incorporating a multivariate regression model. The outcomes highlight that both air conditioner temperature and traffic patterns in Jeddah have a significant negative effect on fuel economy. Results also depict that the effect of air conditioner temperature, traffic patterns, and tire pressure is substantially higher for heavy-engine automobiles such as the GMC Yukon compared to light-engine cars (Toyota Corolla). Furthermore, a normality test has also been considered to validate the outcomes of the proposed model. Therefore, it is highly recommended to utilize the proposed methodology in optimizing the trends of fuel economy for sustainable vehicle routings. Based on the findings of multidomain statistical analysis, it is also highly recommended the utilization of the Toyota Corolla car model for investigating the correlation of external undeniable factors (braking frequency, metrological conditions, etc.) with the trends of vehicle fuel economy.

Spatial patterns and species coexistence in mixed Abies marocana-Cedrus atlantica forest in Talassemtane National Park

Understanding spatially-explicit interactions between co-existing tree species provides valuable information about the trade-offs between facilitation and competition driving species coexistence and forest dynamics. Here, we analyzed the fine scale spatial pattern of Moroccan fir (Abies marocana) and Cedrus atlantica (Cedrus atlantica) in a mixed forest (Talassemtane National Park, northern Morocco) and discuss its consequences on intra- and inter-specific interactions and stand dynamics. All trees were mapped and measured in ten plots to investigate uni- and bivariate spatial point patterns using pair-correlation and mark correlation functions. Tree ring data was also investigated from increment cores to assess the growth and age patterns of both species. Fir and cedar trees showed similar basal area and mean diameter distributions, while A. marocana presented a higher density and regeneration. There was an overall aggregation of conspecific and heterospecific individuals at small distances up to 2 m. Univariate analysis of tree size classes supports that juveniles of both species, as well as A. marocana adult trees, show an aggregated pattern at fine scales up to 2 m, while C. atlantica adults exhibit a random pattern. Observed spatial patterns are consistent with the hypothesis of attraction mechanisms between fir and adult trees of C. atlantica. Abies marocana recruitment mainly occurred inside the canopy of dominant trees (at distances varying from c.a 1 m under cedar adults to 3 m under adult conspecifics), while C. atlantica was the dominant regeneration in small gaps. The studied A. marocana-C. atlantica mixed forests showed a transition from an initiation phase led by C. atlantica to a subsequent stem exclusion phase, where dominant trees shade out less-competitive trees and mainly fir trees can establish in the forest understory. According to the observed spatial patterns and growth rates, enhancing C. atlantica establishment in degraded areas may be a suitable proactive and adaptive management to promote long-term conservation of endemic Abies marocana under current climate change trends.

Trend analysis in rainfall time series in some Brazilian semiarid cities

Nowadays, climate changes are a frequent issue of the scientific community, and although it occurs on a global scale, its impacts often vary from region to region. The objective of this research was to identify the climatic change trends from rainfall in some Brazilian semiarid cities of the Pernambuco state. The Mann-Kendall and Sen-slope trend tests were applied to detect possible trends in the rainfall time series. In addition, the Pettitt test was also applied to identify abrupt changes in precipitation records represented by breakpoints in the time series. The results showed trends of climatic changes in rainfall in fifteen cities, being observed in some localities the decrease of the tendencies in the rainy season, representing a serious problem that compromises the water supply, suppresses agricultural activities, thus making life difficult for the population, because it's in this short rainy season that the water reservoirs of the region are replenished.

Recent Climate Change in the Lake Kyoga Basin, Uganda: An Analysis Using Short-Term and Long-Term Data with Standardized Precipitation and Anomaly Indexes

Climate change (CC) is now a global challenge due to uncertainties on the drivers and the multifaceted nature of its impacts. It impacts many sectors such as agriculture, water supply, and global economies through temperature and precipitation, affecting many livelihoods. Although there are global, regional, and national studies on CC, their application to determine local CC occurence mitigation and adaptation measures is not ideal. Therefore, this study aimed to determine climate change trends in Lake Kyoga Basin using standardized precipitation and anomaly indexes. Short-term (39 years, 1981–2020) and long-term (59 years, 1961–2020) monthly data from eight strategic meteorological stations were acquired from the Uganda National Meteorological Authority and supplemented with satellite and model reanalysis climate datasets. Change in precipitation was determined by SPI-6, while SAI determined change in temperature. The Mann–Kendall test was used to determine the trend significance. Whereas two (Serere and Lira) long-term data stations showed significant changes in precipitation, all the short-term data stations showed a significant increasing trend. Decadal relative rainfall anomaly increased from 85.6–105 in 1981–1990 to 92.0–120.9 in 2011–2020, while mean temperature anomaly increased from 0.2–0.6 °C to 1.0–1.6 °C in the same period. The frequency of severe wet weather events was more than for dry weather events in many stations, indicating an increase in precipitation. Maximum, mean, and minimum temperatures increased, with resultant warmer nights. The findings showed that the Lake Kyoga basin is experiencing climate change, with both temperature and rainfall increasing spatially and temporarily. Climate change affects agriculture, which is the main economic activity, and causes the destruction of infrastructure from floods, landslides, and mudslides. The results of this study are helpful in pointing out climate change-affected areas, and hence for designing mitigation and adaption strategies for local communities by policy and decision-makers from relevant stakeholders.

Trends of climate change at the mid-low Nazas-Aguanaval inland basin based on a geographical approach

An integrative geographical climatology is presented to objectively identify regional patterns of climate variability within the mid-low Nazas-Aguanaval basin within the States of Durango and Coahuila in Central Northern Mexico, using decadal mean values for maximum and minimum temperature, as well as monthly precipitation during the seven periods from 1951-2020. The historical data was acquired from 26 field meteorological stations and 44 grid points from the SWAT model. Furthermore, the data was categorized by means of geographical features of altitude, longitude and latitude in three groups each. A combination of meteorological vulnerability from all the categories for each sampling point was then estimated for each locality. From the overall analysis, western sites resulted as the most vulnerable to climatic changes, while eastern and central (latitude) displayed the lowest variability occurrence. By means of downscaling the meteorological variation, it is possible to improve the understanding of mechanisms relying on regional climate variability and climate change. This evaluation can be further incorporated to management strategies for different stakeholders in arid and semi-arid lands, particularly within the Chihuahuan Desert.

Temporal analysis of rainfall and drought characteristics over Jalore District of S-W Rajasthan

Abstract Drought forecasting is being considered an important tool to help understand the rainfall pattern and climate change trend. Drought is a prolonged period of months or years in which an area, whether surface water or groundwater, becomes insufficient in its water supplies. Drought is considered as the most difficult but least known environmental phenomenon, impacting more persons than any other. There are several indices used to classify droughts. For this study, precipitation-based drought indices are considered (i.e., SPI, RAI and Percentage Departure of Rainfall). The objective of the research is to examine and determine the possible rainfall trends over the Jalore district of South-West Rajasthan in Luni river basin. In this research, trend analysis using the rainfall data from the years 1901 to 2021 was carried out on a monthly, seasonal and annual basis. To define the current trend path, the Mann-Kendall test and Sen's slope estimator test were used. In order to detect the trend and its change in magnitude over a particular period of time, Sen's slope estimator was used. During the southwest monsoon, declining rainfall leads to short-term meteorological droughts, which have severe effect on the agriculture sector and Jalore district's water supplies, while rising rainfall during other seasons tends to mitigate the severity of drought. The result of research reveals that there is rise of pre-monsoon and post-monsoon rainfall, but it also depicts a fall in the annual rainfall which reflects in reduced Winter and S-W monsoon rainfall.

Features of the dynamics of heat waves in selected cities of Ukraine

Formulation of the problem. One of the main manifestations of regional climate changes in Ukraine on the background of global warming is substantial rise of air temperature and increasing of extreme weather conditions. Therefore heat waves became a concern. Detection of heat waves and their physical and statistical characteristics on the territory of Ukraine was done by many researchers only during warm period of the year and on the basis of fact data. But it's interesting to find out what happens in this context during cold period as well because heat waves affect not only human health but also agriculture, transportation etc throughout the year. Besides in order to overcome negative consequences and for adaptation of people for climate changes prognostic values of meteorological indices, in particular air temperature according to modern climate change scenarios. Review of previous publications. Consequences of thermal waves impact on population health is being studied in different countries of the world and in the main medical data base PubMed there are more than 1000 publications in this branch of research. But still there is no universal definition of heat waves which could be used as criteria for detecting this anomaly in all the researches. This can be explained that depending on challenges of scientific research or practical service of household activity waves of certain intensity or duration can be the most interesting. Purpose. The aim of this work is detection of heat waves on the basis of actual and scenario data and analysis of their physical and statistical characteristics and dynamics until 2050. Methods. Heat waves were detected on the base of actual data and model ranges by low (RCP 2.6), medium (RCP 4.5), high (RCP 8.5) levels of greenhouse gases emissions and also there were analyzed their physical and statistical characteristics and dynamics until 2050 in different regions of Ukraine. Results. The smallest annual number of heat waves is recorded in the south of Ukraine and the maximum heat wave duration is approximately the same at all the research stations (Uzhgorod, Kharkiv, Odessa). According to all climate change trends that were used, the greatest number of heat waves in the next thirty years is expected in the south of Ukraine, with a maximum in the cold season (October-April). The intensity of heat waves, expressed by the cumulative temperature, during the cold period slightly exceeds this index during the warm period in the west and north-east and substantially exceeds it in the south, and heat waves of the same duration can have quite different intensities. Conclusions. In the west of Ukraine, there is a trend of increasing the number of heat waves and their duration over the studied period by decades, in the northeast and south - these indicators have fluctuated. It was discovered that in all regions, according to actual data, heat waves of 6-9 days have the highest recurrence (82% of total amount of heat waves per year); according to the RCP2.6 scenario, their recurrence will be minimized (up to 52%) in the south of the country. According to all used climate change trends by 2050, the highest number of heat waves is expected in southern Ukraine, with a maximum during the cold season (October-April). The intensity of heat waves of the cold period is higher than during the warm period in all regions of Ukraine, especially the south.

Правовой режим технологий и продукции, полученной с использованием ГМО: дискуссионные вопросы

Introduction: the paper examines the problems associated with the definition of the legal regime of the technologies and products obtained using GMOs. The experts in the field of genetics have not yet come to an unambiguous conclusion about the degree of harm or benefit of products obtained using genetic modifications. Russia has strict restrictive measures for the production of genetically modified products. Consequently, there is virtually no market for genetically modified seeds produced in Russia. Nevertheless, the world is actively developing industries for the production of genetically modified agricultural products, and the market for the production of seeds is “captured” by a small number of foreign companies. On the other hand, climate change dictates the inevitability of using genetically modified products, the need to accelerate genetic research, and the production of GMO seeds and food. In this context, the authors set a goal to find a compromise (balanced) legal regulation of the legal regime of the technologies and products obtained using GMOs. Methods: the methodological framework for the research is a set of methods of scientific cognition, among which the formal-legal method and the method of comparative legal analysis are the leading positions. Results: the authors propose to consider the bans or support for GMO products in the context of trends in global climate change and ensuring food security. The authors have made a comparative analysis of the provisions of the international norms and the Russian legislation on the research and application of GMO technologies and products, which helped to identify an unbalanced legal regulation of the use of the GMO technologies in Russia, which reduces its competitiveness in this area on the world market. Conclusions: the Russian legislation needs to minimize this legal imbalance, which puts researchers in the field of plant genetics and producers of GMO seeds and food in unequal (worse) conditions. The legal regulation should ensure the coexistence of organic (environmentally friendly) agriculture, traditional agriculture, and the use of the GMO technologies; the introduction of special labeling of GMO products; the broadening of the powers of regional authorities in the use of GMO technologies; as well as the application of the principle of “traceability” to GMO products.

IMPACT OF CLIMATE CHANGE ON INVESTMENT ATTRACTIVENESS OF AGRICULTURAL SECTOR ENTERPRISES

The article proves that the trend of climate change has a direct impact not only on the economic development of any enterprise, but for the whole country and the world as a whole. The environmental factor is one of the most influential for the agricultural sector. It is established that an important task for the effective adaptation of the agro-industrial enterprise to global climate change is a clear understanding of the consequences, risks and vulnerabilities in the short, medium and long term. This will allow the company's managers to understand the trend of climate change and how to influence the company in the future against the background of these problems. Studies show the negative consequences of climate change and the forms of their manifestation, which threaten the investment attractiveness of the enterprise. The main ones are: instability of temperature indicators in the field of water resources, soil degradation and the spread of diseases and pests of crops. The task of adapting Kernel agroholding to the new conditions of agricultural business taking into account the conditions of climate change is proposed.

Estimating ecological sustainability in the Guangdong-Hong Kong-Macao Greater Bay Area, China: Retrospective analysis and prospective trajectories

In recent decades, rapid urbanization and intensified global climate change have resulted in a significant difference of environment and resources distribution on space, which would cause trouble for accurate assessment of regional ecological sustainable development, especially in the large urban agglomerations. The parameters used in previous assessment methods have normally ignored spatial heterogeneity, leading to deviations in the evaluation accuracies against the context above. By incorporating remote sensing technology, this study proposed an improved emergy ecological footprint (EEF) method and a novel ecological sustainability index to comprehensively analyze the variability of ecological security states (ESS) from 1994 to 2018 in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and to predict its sustainable growth potential based on a combined factorial decomposition and scenario analysis. Results showed that the pixel-based emergy analysis revealed significant heterogeneity over time and space under the impact of climate change and intense land use activities during the study period. The emergy carrying capacity per capita (ecc) and the emergy ecological footprint per capita (eef) also showed a significant difference between the nine cities in the GBA. In addition, the traditional EEF method, which does not consider the spatiotemporal variation, has indeed overestimated the GBA's ecc by 15% compared with our results. The ESS of the GBA gradually worsened from slight insecurity in the 1990s to moderate insecurity in 2018. If the current trends in socio-economic activities and climate change continue according to the RCP8.5 scenario in the IPCC, the ESS of the GBA will reach the extreme insecurity state in 2050. However, our scenarios show that industrial structure adjustment, energy structure optimization, and especially biological resource conservation can reduce the EFI by approximately 6.52%, 23.4%, and 30.6%, respectively. Consequently, effective implementation of the above measures can limit the increase both in emergy ecological deficit and emergy ecological footprint intensity (EFI) and, together, contribute to a higher security status in the GBA in 2050.

Altitudinal trends in climate change result in radial growth variation of Pinus yunnanensis at an arid-hot valley of southwest China

Climate change has already had observable impact on the biophysical environment, and lead to the different sensitivity of vegetation to climate factors on spatio-temporal scale. Therefore, understanding how the radial growth respond to climate at different spatio-temporal scales is crucial to recognize forest growth dynamic and make scientific management decisions under the background of climatic change. In the present study, the tree ring of Pinus yunnanensis at six altitudes gradients between 1300 m and 2500 m from a typical arid-hot valley in Jinsha River, were collected. We analyzed the relationship between radial growth and climate at different altitudes, and the sensitivity of growth to climatic factors over time. The results showed that the mean width of tree rings decreased as the altitude increasing. The relationship between climatic factors and radial growth at low or high altitudes was different with that at mid altitudes. Radial growth was negatively correlated to the temperatures from February to July at both low altitudes (1300–1500 m) and at high altitudes (2200–2500 m), but positively correlated to the temperatures in October of the previous year to April at mid altitudes (1700–1900 m). Precipitation in October of the previous year, May, and June in growing year had a positive effect on radial growth at all altitudes. Temperature and precipitation in the previous year showed a time-lag effect on radial growth. A moving correlation analysis of the tree ring index and climate variables showed that the limiting factors for tree growth at different altitudes varied over time. The influence of drought on the tree growth increased gradually as the climate warming. In future research, evaluating the dynamic relationship between vegetation growth and climate warming at spatio--temporal scale will be particularly important to guide forest management.