Main Climatic Factors Research Articles

Experimental Studies of the Effect of Schisandrachinensis Extract on the State of Adaptive Capabilities of Rats under Chronic and General Exposure to Cold.

Currently, there is an objective need to create fortified food products that allow not only to provide the body with energy, but also to replenish the deficiency of essential nutrients. A generalization of the information published by Rospotrebnadzor and the Institute of Nutrition of the Russian Academy of Medical Sciences indicates a deficiency in the diet of Russians of vitamins C, group B and β-carotene and minerals, including calcium and iron, regardless of the season of the year. The identified deviations lead to a violation of the immune status, a decrease in the body’s resistance to infections, and other unfavorable environmental factors, leading to an increase in the level of morbidity and a decrease in working capacity. The main unfavorable climatic factor that the population of the Far Eastern region has to face is low freezing temperatures. Adaptation to cold exposure is a complex process that requires a long period and may be accompanied by functional disorders and morphological changes in body tissues. In connection with the above, the problem of increasing the adaptive capabilities of a person to unfavorable environmental factors by means of correcting daily nutrition, providing the body with essential macro- and micronutrients, which is important in the prevention of possible diseases, is of particular importance. This study is aimed at assessing the effect of Schisandrachinensis extract on the adaptive capacity of rats in conditions of chronic and general cold. It was found that the extracts obtained from the fruits of Schisandra chinensis are characterized by a high content of biologically active substances. In experiments with determining the duration of running on the treadmill, a distinct act-protective effect was observed with the introduction of Schisandra chinensis extracts at a dose of 150 mg/day, against the background of reduced resistance to physical activity due to cold exposure. It was found that exposure to cold significantly reduced the swimming resistance of rats on all days of the study. The introduction of Schisandra chinensis extract into the diet led to an increase in resistance to fatigue and an increase in the duration of swimming on all days of the experiment. Conclusions: in this experimental model, a gradually increasing effect of increasing the physical performance of rats was demonstrated with prolonged (28 days) intake of the developed drinks, which coincides with the literature data on a number of other adaptogens and indicates the presence of cumulative properties of biologically active substances of Schisandra extract.

Maize grain yield and water use efficiency in relation to climatic factors and plant population in northern China

Water scarcity has become a limiting factor for increasing crop production. Finding ways to improve water use efficiency (WUE) has become an urgent task for Chinese agriculture. To understand the response of different maize populations to changes in precipitation and the effects of changes in maize populations on WUE, this study conducted maize population experiments using maize hybrids with different plant types (compact and semi compact) and different planting densities at 25 locations across China. It was found that, as precipitation increased across different locations, maize grain yield first increased and then decreased, while WUE decreased significantly. Analyzing the relationship between WUE and the main climatic factors, this study found that WUE was significantly and negatively correlated with precipitation ($$ (daily mean precipitation) and R (accumulated precipitation)) and was positively correlated with temperature (TM (daily mean maximum temperature), TM–m (Tm, daily mean minimum temperature) and GDD (growing degree days)) and solar radiation ($$ (daily mean solar radiation) and Ra (accumulated solar radiation)) over different growth periods. Significant differences in maize grain yield, WUE and precipitation were found at different planting densities. The population densities were ranked as follows according to maize grain yield and WUE based on the multi-site experiment data: 60 000 plants ha–1 (P2)>90 000 plants ha–1 (P3)>30 000 plants ha–1 (P1). Further analysis showed that, as maize population increased, water consumption increased significantly while soil evaporation decreased significantly. Significant differences were found between the WUE of ZD958 (compact type) and that of LD981 (semi-compact type), as well as among the WUE values at different planting densities. In addition, choosing the optimum hybrid and planting density increased WUE by 21.70 and 14.92%, respectively, which showed that the hybrid played a more significant role than the planting density in improving WUE. Therefore, choosing drought-resistant hybrids could be more effective than increasing the planting density to increase maize grain yield and WUE in northern China. Comprehensive consideration of climatic impacts, drought-resistant hybrids (e.g., ZD958) and planting density (e.g., 60 000 plants ha–1) is an effective way to increase maize grain yield and WUE across different regions of China.

Anatomical tree-ring chronologies and seasonal patterns of cambial dynamics are valuable indicators of tree performance of two oak species at the Atlantic-Mediterranean boundary

Northwestern Iberia is characterized for being an Atlantic/Mediterranean transitional area, where the most natural forests contain certain species, typical from either biogeographic region, growing under limiting conditions due to their marginal location. In order to identify the main climatic factors controlling growth, and thus better understand how they impact wood formation processes of the key tree species in these ecosystems, we analyzed tree rings of two somehow contrasting oaks (Quercus robur, Atlantic; and Q. pyrenaica, sub-Mediterranean) at their distribution boundary towards the Mediterranean region. For this, two nearby sites with slightly different regime of water availability were selected for each species. We developed chronologies of radial increment (expressed as latewood width) and functional anatomical traits (size and number of earlywood vessels) for the last decades, and also monitored wood formation along two growing seasons. Our results suggest that the combination of anatomical traits and radial growth constitute a useful tool to understand the behavior of these species in boundary distribution areas. We found some differences between sites, especially for Q. pyrenaica, but the main factors controlling growth were clearly identified at all sites. Earlywood characteristics were mainly related to temperature, whereas latewood width responded to precipitation, regardless of the species. However, vessels of low-elevation Q. robur seemed to be controlled by factors affecting carbohydrate balance, while those of high-elevation Q. pyrenaica were associated to spring conditions for growth resumption. Summer water availability was linked to a wider latewood for both species. In addition, the analysis of xylogenesis carried out at all sites was essential to interpret climate responses by providing evidences for the existence of a cause-effect relationship.

Vegetation dynamics and responses to climate change and anthropogenic activities in the Three-River Headwaters Region, China

The Three-River Headwaters Region (TRHR) is an area of crucial significance for the ecological security of China. Owing to dramatic climate change and human activities driven by a series of ecological restoration projects, the ecological environment and vegetation have changed drastically in recent years. However, our knowledge of the current state and driving force of the change in the entire region is limited. This study mapped the spatiotemporal changes in vegetation coverage and quantitatively identified the contributions of climate change and anthropogenic factors to such variations from 2000 to 2018 using 133 MODIS NDVI images at 250 m resolution. The results show that over the past 19 years, the average NDVI demonstrated a fluctuating but upward trend, with a rate of increase of 0.0013 yr−1. Areas with increased vegetation coverage accounted for 54.93% of the entire area, and among them, 18.52% showed a significant greening trend. Based on the Hurst exponent, areas with sustained increasing trends were primarily concentrated in the northeastern, western, and southwestern parts of the Yellow River region, and the western Yangtze River region. The average contributions of the precipitation, temperature, and sunshine duration to NDVI were 0.069, 0.098, and 0.059%·yr−1, respectively. Sunshine duration had the greatest influence on the inter-annual change of NDVI during the entire study period, while the temperature was the main climatic factor from 2000 to 2010. The average contributions of climate change and anthropogenic factors to inter-annual variations of NDVI were 0.226 and –0.096%·yr−1, respectively. The general climate conditions are beneficial to the vegetation recovery, whereas human activities negatively impact the vegetation growth. However, the ecological afforestation projects positively influenced the east Yellow River, Lancang River, and west Yangtze River regions.

Spatio-Temporal Changes of Land Surface Temperature and the Influencing Factors in the Tarim Basin, Northwest China

Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001–2019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 °C) and the lowest was in January (−9.5 °C). On a seasonal scale, LST decreased in the order: summer > spring > autumn > winter. Annual LST showed an increasing trend of 0.2 °C/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February–December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations.

Hydrological Similarity-Based Parameter Regionalization under Different Climate and Underlying Surfaces in Ungauged Basins

Hydrological similarity-based parameter regionalization is the dominant method used for runoff prediction in ungauged basin. However, the application of this approach depends on assessing hydrological similarity between basins. This study used data for runoff, climate, and the underlying surface of the Hulan River Basin and Poyang Lake Basin to construct a novel physical hydrological similarity index (HSI). The index was used to compare the efficiency of transfer of the parameters of commonly used regionalization methods and to finally apply parameters to ungauged basins. The results showed that: (1) Precipitation is the main climatic factor regulating magnitude of runoff in the Poyang Lake Basin. Spring runoff in Hulan River Basin was regulated by precipitation and temperature. (2) The GR4J and CemaNeigeGR4J models achieved reasonable simulations of runoff of Poyang Lake Basin and Hulan River Basin. Although CemaNeigeGR4J considers snowmelt, the model simulations of spring runoff in the Hulan River Basin were not accurate. (3) There was a significant correlation between climate, the underlying surface, and hydrological model parameters. There were fewer significant correlations between environmental factors and between environmental factors and hydrological model parameters in the Hulan River Basin compared to those in the Poyang Lake Basin, possibly due to less sub-basins in the Hulan River Basin. (4) The HSI based on a combination of principal component analysis and the entropy method efficiently identified the most similar gauged basin for an ungauged basin. A significant positive correlation existed between the HSI and parameter transfer efficiency. The relationship between the HSI and transfer efficiency could be represented by logistic regression and linear regression in the Poyang Lake Basin and Hulan River Basin, respectively. The HSI was better able to quantify the hydrological similarity between basins in terms of climate and underlying surface and can provide a scientific reference for the transfer of hydrological model parameters in an ungauged basin.

Distribution characteristics of climate potential productivity of soybean in frigid region and its response to climate change.

The scope of this study is to analyze the climatic potential productivity of soybean [Glycine max (L.) Merr.] and explore the impact of climate change on soybean in the frigid region in China by using daily climatic variables from 144 meteorological stations for the period 1971‒2019. The gradually descending model is used to estimate photosynthesis, light-temperature, and climatic potential productivity of soybean. The results show thatclimate potential productivity of soybean in the frigid region ranges from large to small: Liaoning > Jilin > Heilongjiang > East Four Leagues (four cities in eastern Inner Mongolia), with Heilongjiang and East Four Leagues showing a significant upward trend. Spatially, the climate potential productivity is larger on plains than that on mountains. The Northeast Plain and Sanjiang Plain are areas with high climate potential productivity. Changes in climatic factors have different impacts on the climate potential productivity of soybean. The influence of temperature changes on the climate potential productivity shows a positive effect, and climate warming compensates for the lack of heat in the frigid region. Furthermore, radiation and precipitation are the main climatic factors leading to spatial differences in the climate potential productivity of soybean in the frigid region. Radiation changes have a positive effect on soybean climate potential productivity in plain areas and a negative effect on the mountains. However, precipitation reduction negatively affects most of the frigid region, while it has a positive effect on the two plains of Heilongjiang. Precipitation responses the needs of soybean growth. Our findings recommend that a transition of soybean planting from the mountainous region to plain, that is, from low potential productivity areas to high potential productivity areas, could be an effective strategy for regional optimization for planting structure and rational utilization of irrigation technology.

Spatio-Temporal Analysis of Drought Variability in Myanmar Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Its Impact on Crop Production

Drought research is an important aspect of drought disaster mitigation and adaptation. For this purpose, we used the Standardized Precipitation Evapotranspiration Index (SPEI) to investigate the spatial-temporal pattern of drought and its impact on crop production. Using monthly precipitation (Precip) and temperature (Temp) data from 1986–2015 for 39 weather stations, the drought index was obtained for the time scale of 3, 6, and 12 months. The Mann–Kendall test was used to determine trends and rates of change. Precip and Temp anomalies were investigated using the regression analysis and compared with the drought index. The link between drought with large-scale atmospheric circulation anomalies using the Pearson correlation coefficient (R) was explored. Results showed a non-uniform spatial pattern of dryness and wetness which varied across Myanmar agro-ecological zones and under different time scales. Generally, results showed an increasing trend for the SPEI in the three-time scales, signifying a high tendency of decreased drought from 1986–2015. The fluctuations in dryness/wetness might linked to reduction crop production between 1986–1999 and 2005, 2008, 2010, 2013 cropping years. Results show relationship between main crops production and climate (teleconnection) factors. However, the low correlation values (i.e., <0.49) indicate the extent of the relationship within the natural variability. However, readers are urged to interpret this result cautiously as reductions in crop production may also be affected by other factors. We have demonstrated droughts evolution and trends using weather stations, thus providing useful information to aid policymakers in developing spatially relevant climate change adaptation and mitigation management plans for Myanmar.

A Comparative Study of Standard Center Pivot and Growers-Based Modified Center Pivot for Evaluating Uniformity Coefficient and Water Distribution

The center pivot irrigation system is a type of irrigation technology used to apply water effectively and uniformly over a wide variety of areas and topographies. These irrigation systems’ uniformity of water application greatly affects water use, energy consumption, and crop production. Performance tests of the standard lateral galvanized and modified polyethylene plastic pipes in the center pivot irrigation systems were conducted in different regions of Saudi Arabia. Water distribution depths along the laterals, coefficient of uniformity (CU), and distribution uniformity of the low quarter (DU) were determined. The results revealed that profiles of water distribution ranged from 4 to 14 mm for the standard-center pivot irrigation systems, while those for the modified-center pivot irrigation systems ranged from 6.5 to 50 mm. Standard-center pivot irrigation systems’ CU values ranged from 74 to 90%, with an average of 86%. In comparison, the modified-center pivot irrigation systems’ CU values ranged from 62 to 83%, with an average of 78%. The DU values ranged from 60 to 82% for the standard-center pivot irrigation systems, with an overall average of 77%. For the modified-center pivot irrigation systems, the DU values, in contrast, ranged from 31 to 75%, with an average of 65%. Thus, the accuracy and uniformity of the standard-center pivot irrigation systems are superior to those that have been modified. Additionally, a statistical model was developed to investigate the relationship between the water losses and the main climatic factors under field operating conditions. Therefore, the study results are expected to draw attention to standard lateral pipes’ value on the one hand and demonstrate the detrimental consequences of growers’ incorrect practices in pivot irrigation systems, motivating them to take strong action against these activities, on the other hand.

Vegetation Changes in Response to Climatic Factors and Human Activities in Jilin Province, China, 2000–2019

Dynamic change in vegetation is an integral component of terrestrial ecosystems, which has become a significant research area in the current context of global climate warming. Jilin Province in northeast China is an ecologically fragile area, and there is an urgent need to understand its vegetation changes and responses to both climatic factors and human activities. The normalized difference vegetation index (NDVI) was used to analyze trends in vegetation growth, and indicated significant growth overall. The NDVI of different vegetation cover types is increasing, indicating that the vegetation is continuously greening, and in descending order, the growth trends were grassland (0.0035/year) > permanent wetland (0.0028/year) > cropland (0.0027/year) > forest land (0.0022/year) > barren land (−0.0001/year). Grassland and cropland vegetation types included the most severely degraded areas, with fluctuating NDVI values. Precipitation was the main positive controlling climatic factor of NDVI in the western regions of the study area, while average temperature was the main factor in the eastern regions. Precipitation was the main climatic control factor for grassland and cropland, while forest land was limited by precipitation and average temperature. Barren land and permanent wetland were slightly negatively correlated with precipitation. From 2000 to 2019, the residual values for NDVI increased from −0.0121 to 0.0116, and the impact of human activities on vegetation changed from negative to positive. By 2019, the proportion of positively affected zones was as high as 94.01%, and the negatively affected zones were mainly distributed across transitional areas of cropland and grassland, and urban and built-up land and forest land.

Comparison of the Radial Growth Response of Picea crassifolia to Climate Change in Different Regions of the Central and Eastern Qilian Mountains

It is important to explore the responses of radial tree growth in different regions to understand growth patterns and to enhance forest management and protection with climate change. We constructed tree ring width chronologies of Picea crassifolia from different regions of the Qilian Mountains of northwest China. We used Pearson correlation and moving correlation to analyze the main climate factors limiting radial growth of trees and the temporal stability of the growth–climate relationship, while spatial correlation is the result of further testing the first two terms in space. The conclusions were as follows: (1) Radial growth had different trends, showing an increasing followed by a decreasing trend in the central region, a continuously increasing trend in the eastern region, and a gradually decreasing trend in the isolated mountain. (2) Radial tree growth in the central region and isolated mountains was constrained by drought stress, and tree growth in the central region was significantly negatively correlated with growing season temperature. Isolated mountains showed a significant negative correlation with mean minimum of growing season and a significant positive correlation with total precipitation. (3) Temporal dynamic responses of radial growth in the central region to the temperatures and SPEI (the standardized precipitation evapotranspiration index) in the growing season were unstable, the isolated mountains to total precipitation was unstable, and that to SPEI was stable. The results of this study suggest that scientific management and maintenance plans of the forest ecosystem should be developed according to the response and growth patterns of the Qinghai spruce to climate change in different regions of the Qilian Mountains.

Probability assessment of slope instability in seasonally cold regions under climate change

To semi-quantitatively assess the effects of climate change on the slope failures, this paper proposes an effective approach for evaluating the influences of climate change on slope stability in seasonally cold regions. To discuss climate change, this study firstly analyzes the trend of the two main climate factors (precipitation and air temperature) based on the regression analysis results of the meteorological monitoring data during the past 120 years in different scales (e.g., world, country (Japan), and city (Sapporo)), and the downscaled outputs of three different regional atmospheric models (RAMs) with lateral boundary conditions from three different general circulation models (GCMs). Next, to discuss the effects of different climate factors (air temperature, precipitation, etc.) and to determine the key climate factors on the slope instability, a slope stability assessment approach for evaluating the effects of climate changes on slope instability is proposed through the water content simulation and slope stability analysis with considering freeze-thaw action. Finally, to check the effectiveness of the above assessment approach, assessment of instability of an actual highway embankment slope with the local layer geometry is done by applying the past and predicted future climate data. The results indicate that affected by global warming, the air temperature rise in some cold cities is more serious. The climate changes (especially the increase in precipitation) in the future will increase the infiltration during the Spring season. It will lengthen the time that the highway slope is in an unstable state due to high volumetric water content, causing the occurrence of slope failures will be more concentrated in April. While during the Ssummer-Autumn period, the time domain of its occurrence will become wider.

A generalized machine learning approach for dissolved oxygen estimation at multiple spatiotemporal scales using remote sensing

Dissolved oxygen (DO) is an effective indicator for water pollution. However, since DO is a non-optically active parameter and has little impact on the spectrum captured by satellite sensors, research on estimating DO by remote sensing at multiple spatiotemporal scales is limited. In this study, the support vector regression (SVR) models were developed and validated using the remote sensing reflectance derived from both Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data and synchronous DO measurements (N = 188) and water temperature of Lake Huron and three other inland waterbodies (N = 282) covering latitude between 22–45 °N. Using the developed models, spatial distributions of the annual and monthly DO variability since 1984 and the annual monthly DO variability since 2000 in Lake Huron were reconstructed for the first time. The impacts of five climate factors on long-term DO trends were analyzed. Results showed that the developed SVR-based models had good robustness and generalization (average R2 = 0.91, root mean square percentage error = 2.65%, mean absolute percentage error = 4.21%), and performed better than random forest and multiple linear regression. The monthly DO estimates by Landsat and MODIS data were highly consistent (average R2 = 0.88). From 1984 to 2019, the oxygen loss in Lake Huron was 6.56%. Air temperature, incident shortwave radiation flux density, and precipitation were the main climate factors affecting annual DO of Lake Huron. This study demonstrated that using SVR-based models, Landsat and MODIS data could be used for long-term DO retrieval at multiple spatial and temporal scales. As data-driven models, combining spectrum and water temperature as well as extending the training set to cover more DO conditions could effectively improve model robustness and generalization.

Effects of climate changes on the distribution of Rhipicephalus microplus in China

To identify the environmental factors affecting the geographical distribution of Rhipicephalus microplus in China, and to examine the impact of climate changes on the distribution of R. microplus in China. The national and international publications pertaining to the geographical distribution of R. microplus in China were retrieved, and the geographical location was extracted. The suitable habitats of R. microplus and the dominant environmental factors affecting the distribution of suitable habitats of R. microplus were predicted in China based on the geographical data and environmental variables using the ArcGIS 10.7 software and the maximum entropy model. Among the main climatic factors affecting the geographical distribution of R. microplus in China, the factors contributing more than 10% to the suitable habitats of R. microplus mainly include the annual mean precipitation (38.2%), the average temperature of the coldest quarter (28.4%) and the precipitation of the driest month (14.2%). The current suitable habitats of R. microplus were mainly found in southern China, and the high-, medium- and low-suitable areas accounted for 8.6%, 13.1% and 10.5% of the total land area of China, respectively. The suitable habitats of R. microplus were predicted to increase by 399 800 km2 in China using the maximum entropy model under the RCP 4.5 emissions scenario in 2070, and the emerging suitable habitats were mainly distributed in Gansu Province, Ningxia Hui Autonomous Region, Qinghai Province, Hebei Province, Shaanxi Province, Liaoning Province, Inner Mongolia Autonomous Region, Shandong Province, Sichuan Province and Tibeten Autonomous Region. In addition, the suitable habitats of R. microplus were predicted to show an overall expansion towards northward from present to 2070. Climate changes affect the distribution of suitable habitats of R. microplus in China, and annual mean precipitation may be a key factor affecting the distribution of suitable habitats of R. microplus.

The Effects of Some Climate Factors upon Frequency Distribution of Local Sandflies Breed in Misan Province, Iraq

The genus Phlebotomus is naturally responsible for the transmission of many protozoal parasites like Leishmania. The study was conducted to determine the effect of some climate factors on sandflies distribution over a year from December 2019 to November 2020. A total of 268 sandflies of both sexes were collected from different areas in Misan province, Iraq. Sandflies were collected using light traps and stick oil paper, then placed in cups or Petri dishes containing sterile normal saline for examination. The current study showed an inverse relationship between the presence and number of sandflies with temperatures. Rainfall had a significant impact on parasite distribution, while wind speed had a potential impact on sandfly activity. The percentage of female sandflies was significantly (P<0.05) higher than that of males (54.85% for females versus 45.15% for males). In conclusion, heavy precipitation is the main climate factor that affects the frequency distribution of local breed sandflies followed by rising temperature degrees that are seen in the summer season. The climate can affect the activity, spreading, and distribution of sandflies with detected one peak of their activity in December.

Spatio-Temporal Evolution and Prediction of Tourism Comprehensive Climate Comfort in Henan Province, China

The tourism comprehensive climate comfort index (TCCI) was used to evaluate the tourism climate comfort in Henan Province in the last 61 years, and its future development trend is predicted. The results showed that the temporal variation of the TCCI had a “double peak” type (monthly variation), and an overall comfort improvement trend (interannual variation). The change of tourism climate comfort days was similar to the change of the index, especially in the months with a low comfort level. In space, the distribution of the TCCI gradually increased from northeast to southwest, and the area with a high comfort level also increased over time. Meanwhile, it also showed the spatial distribution of months with a low comfort level, which provides reliable information for tourists to use when choosing tourist destinations across all periods of the year. The TCCI was classified by hierarchical classification, and principal components were extracted to explore the main climate factors controlling different types of TCCIs and the relationship between them, and large-scale atmospheric–oceanic variability. According to the temporal change trend and correlation, the long-term change trend of tourism climate comfort was predicted, which will provide a scientific basis for tourism planners to choose tourist destinations.

Soil properties and climate affect arbuscular mycorrhizal fungi and soil microbial communities in Mediterranean rainfed cereal cropping systems

Soil microorganisms are generally considered sensitive indicators of soil health and fertility. Understanding the role of environmental factors in driving soil microorganisms’ distributions is vital for sustainable crop production, particularly in vulnerable agricultural systems. This study aims to investigate the effect of environmental factors on the variation of soil microbial biomass and arbuscular mycorrhizal (AM) fungi in Mediterranean rainfed cereal systems. To do so, plant roots and soil were sampled from three cereal crops: Avena sativa L., Hordeum vulgare L. and Triticum turgidum L. growing in 24 rainfed sites from three different bioclimatic zones (sub-humid, superior semi-arid and middle semi-arid) in northern Tunisia. Soil microbial phospholipid fatty acids (PLFA) fingerprints, percentage of root length colonized by AM fungi as well as AM fungal spore density were then assessed. The redundancy analysis (RDA) revealed that soil organic matter (SOM), temperature, altitude and soil sand content accounted for 22.7 % of the variation of the microbial PLFA profiles used to estimate both soil microbial biomass and their distribution across different microbial groups. These environmental factors were the most important drivers affecting bacterial PLFAs. However, no significant relationships were observed between fungal PLFAs and environmental factors. Mycorrhizal colonization differed significantly among the different host species and regions. The RDA results indicated that environmental factors, in particular mean annual precipitation (MAP), pH, available phosphorus (P) and carbon/ nitrogen ratio (C/N) explained 44.8 % of AM fungal root colonization and spore number variation. Mycorrhizal colonization was positively correlated with pH but negatively with P, C/N and MAP. Concerning AM fungal spore number, it was positively linked to P and MAP. In contrast, it was inversely related to soil pH. Highlighting the main edaphic and climatic factors disturbing soil microorganisms, especially AM fungi, helps to better understand how environmental change will influence soil microbial communities in Mediterranean rainfed cereal systems.

Ecosystem-Dependent Responses of Vegetation Coverage on the Tibetan Plateau to Climate Factors and Their Lag Periods

The spatiotemporal variation characteristics of the Normalized Difference Vegetation Index (NDVI) and its climate response patterns are of significance in deepening our understanding of regional vegetation and climate change. The response of vegetation to climate factors varies spatially and may have lag periods. In this paper, we studied the spatiotemporal responses of vegetation to climatic factors on an ecosystem-dependent scale using GIMMS NDVI3g data and climatic parameters. Pure pixels with a single vegetation type were firstly extracted to reduce the influence of mixed vegetation types. Then, a lag correlation analysis was used to explore the lag effects of climatic parameters affecting NDVI. Finally, the stepwise regression method was adopted to calculate the regression equation for NDVI and meteorological data with the consideration of effect lag times. The results show that precipitation has significant lag effects on vegetation. Temperature is the main climatic factor that affects most vegetation types at the start of growing season. At the end of growing season, the temperate desert, temperate steppe, and temperate desert steppe are greatly affected by precipitation. Moreover, the alpine steppe, alpine desert, alpine meadow, and alpine sparse vegetation are greatly affected by temperature. The needleleaf forest, subalpine scrub, and broadleaf evergreen forest are sensitive to sunshine percentage during almost the whole growing season. These findings could contribute to a better understanding of the drivers and mechanisms of vegetation degradation on the Tibetan Plateau.

Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.

Analysis of the Response of Long-Term Vegetation Dynamics to Climate Variability Using the Pruned Exact Linear Time (PELT) Method and Disturbance Lag Model (DLM) Based on Remote Sensing Data: A Case Study in Guangdong Province (China)

The dynamic change and spatial–temporal distribution of vegetation coverage are of great significance for regional ecological evolution, especially in the subtropics and tropics. Identifying the heterogeneity in vegetation activities and its response to climate factors is crucial for projecting ecosystem dynamics. We used long-term (2001–2018) satellite-derived enhanced vegetation index (EVI) datasets and climatic factors to analyze the spatiotemporal patterns of vegetation activities in an experimental area in Guangdong Province (China), as well as their links to changes in temperature (TEM), relative humidity (HUM), precipitation (PRE), sunshine duration (SUN), and surface runoff. The pruned exact linear time change point detection method (PELT) and the disturbance lag model (DLM) were used to understand the detailed ecological coverage status and time lag relationships between the EVI and climatic factors. The results indicate the following. (1) At the whole regional scale, a significant overall upward trend in the EVI variation was observed in 2001–2018. More specifically, there were two distinct periods with different trends, which were split by a turning point in 2005. PRE was the main climate-related driver of the rising EVI pre-2005, and the increase in TEM was the main climate factor influencing the forest EVI variation post-2006. (2) A three-month time lag effect was observed in the EVI response to relative humidity. The same phenomenon was found in the sunshine duration factor. (3) The EVI of farmlands (one type of land use) exhibited the largest lags between relative humidity and the sunshine duration factor, followed by grasslands and forests. (4) The comprehensive index of surface runoff could explain the time lags of vegetation activities, and the surface runoff value showed an apparently negative relationship with the vegetation coverage change.