Average Precipitation Research Articles

Coupling Coordination of Multi-Dimensional Urbanization and Ecological Security in Karst Landscapes: A Case Study of the Yunnan–Guizhou Region, China

Globally, karst regions face the dual challenges of urbanization and ecological protection, with the coupling coordination of multi-dimensional urbanization (MDU) and ecological security (ECS) being a necessary condition for achieving sustainable development. This study, based on statistical data on MDU and ECS in the Yunnan–Guizhou Region (the YGR) in China, employs the entropy weight TOPSIS model, degree of coupling coordination (CCD) model, and panel Tobit regression model to explore the coupling relationship between MDU and ECS. The main conclusions are as follows. (1) MDU in the YGR increased from 0.299 to 0.305, indicating low-level and sluggish development. Spatially, it is characterized by a “dual-core” structure centered on Kunming and Guiyang. (2) ECS decreased from 0.456 to 0.423, with a spatial pattern of “high in the east, low in the west”. The impact of human activities on ECS increased from 0.579 to 0.631 due to the increase in social and economic activities. (3) CCD increased to 0.579, achieving moderate coordination. The spatial feature evolved into a tri-cluster pattern of “high–low–high” across the “eastern–central–northwestern” regions. (4) Regression results indicate that annual average precipitation has a “both promoting and limiting” dual effect on CCD. The coefficient for the proportion of afforested land area is 0.205, with a significance level of 5%, suggesting that increasing forest cover is a key measure for improving CCD. The study reveals the factors influencing the evolution of MDU and ECS from a negative to a positive correlation, providing a basis for decisions related to sustainable development for urban and ecological management in karst landscapes globally.

Climate Change, Biased Technological Advances and Agricultural TFP: Empirical Evidence from China

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies.

Changes in precipitation phases based on the multi-discrimination method in the Tibetan Plateau

Global warming is rapidly changing the precipitation structure, and the shift in precipitation phases is even more pronounced in the Tibetan Plateau (TP), a region sensitive to global climate change. The accuracy of precipitation phase discrimination is essential for studying precipitation variability. Based on the observed data from 112 meteorological stations in the study area obtained from the China Meteorological Administration (CMA) and the National Climatic Data Center (NCDC) before 1980, we compared and assessed six methods for distinguishing precipitation phases and the optimal method was determined to complete the precipitation phase data after 1980 in the study area. Subsequently, the changes in precipitation amount, intensity, and frequency were analyzed by classifying them into light, moderate, heavy, and extreme precipitation using the percentile threshold discrimination method. It found that the dynamic threshold temperature method (presented by Ding et al., 2014) was the most effective to distinguish precipitation phases in the TP, and its performance was further improved from 80.9% to 86.1% after using frequency intersection and probability guarantee methods. Precipitation was mainly concentrated in July. Meanwhile, the proportion of snowfall to total precipitation (S/P) was approximately 9%. From 1961 to 2020, the amount of total precipitation, rainfall and snowfall in the TP exhibited increasing trends, while the sleet demonstrated a persistent decline. Spatial and temporal heterogeneity existed in the changes of precipitation of different phases. The average single precipitation amount increased. Moreover, the changes in the amount and frequency of extreme precipitation were more pronounced. Increased frequency and amount of both rainfall and snowfall were distributed in the central and eastern parts of the study area with a more significant proportion. In contrast, the peripheral areas witnessed a decrease. The spatial distribution of frequency and amount of different precipitation intensities was comparable to that of the total precipitation. This study offers novel procedure into changes of precipitation phases at high altitudes, which will inform future research on climate change and water resource management.

Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China

Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, 93.08%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93.08\\%$$\\end{document} of the land in the research region exhibited a declining LDI trend, 3.95%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3.95\\%$$\\end{document} showed no change, and only 2.96%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.96\\%$$\\end{document} showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.

Trend analysis of precipitation and drought characteristics over Churu district of northeast Rajasthan, India

ABSTRACT Drought is one of the most destructive natural disasters, becoming more extreme and less predictable due to climate change. Drought directly affects a region's water resources, leading to inadequate water availability and harming crops, animals, and humans. The objective of the present study is to assess the long-term trends of precipitation and drought characteristics for the Churu district of northeast Rajasthan, India. For this purpose, mean monthly precipitation data are collected through the India-WRIS from 1901 to 2022. The trend analysis uses statistical methods (M-K test & amp; SS estimator), and the results are compared with a graphical method (innovative trend analysis). Drought events are found using precipitation-based drought indices, i.e., standardized precipitation index, Z-score index, and percentage of normal precipitation index. Interestingly, the results of the statistical method are well matched with the results of the graphical method. The study concludes that during the annual precipitation a rising trend is observed, which can help to mitigate the severity of drought. Also, it is found that moderately dry droughts occur most frequently compared with other drought events. This study will help policy-makers and local administrators to take necessary action to mitigate the severity of drought.

Projecting Climate Change Impact on Precipitation Patterns during Different Growth Stages of Rainfed Wheat Crop in the Pothwar Plateau, Pakistan

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation.

Impacts of future climate change on rice yield based on crop model simulation—A meta-analysis

Rice is one of the world's major food crops. Changes in major climatic factors such as temperature, rainfall, solar radiation and carbon dioxide (CO2) concentration have an important impact on rice growth and yield. However, many of the current studies that predict the impact of future climate change on rice yield are affected by uncertainties such as climate models, climate scenarios, model parameters and structure, and showing great differences. This study was based on the assessment results of the impact of climate change on rice in the future of 111 published literature, and comprehensively analyzed the impact and uncertainty of climate change on rice yield. This study utilized local polynomial (Loess) regression analysis to investigate the impact of changes in mean temperature, minimum temperature, maximum temperature, solar radiation, and precipitation on relative rice yield variations within a complete dataset. A linear mixed-effects model was used to quantitatively analyze the relationships between the restricted datasets. The qualitative analysis based on the entire dataset revealed that rice yields decreased with increasing average temperature. The precipitation changed between 0 and 25 %, it was conducive to the stable production of rice, and when the precipitation changed >25 %, it would cause rice yield reduction. The change of solar radiation was less than −1.15 %, the rice yield increases with the increase of solar radiation, and when the change of solar radiation exceeds −1.15 %, the rice yield decreases. Elevated CO2 concentrations and management practices could mitigate the negative effects of climate change. The results of a quantitative analysis utilizing the mixed effects model revealed that average temperature, precipitation, CO2 concentration, and adaptation methods all had a substantial impact on rice production, and elevated CO2 concentrations and management practices could exert positive influences on rice production. For every 1 °C and 1 % increase in average temperature and precipitation, rice yield decreased by 3.85 % and 0.56 %, respectively. For every 100 ppm increase in CO2 concentration, rice yield increased by 7.1 %. The variation of rice yield under different climate models, study sites and climate scenarios had significant variability. Elevated CO2 concentrations and management practices could compensate for the negative effects of climate change, benefiting rice production. This study comprehensively collected and analyzed a wide range of literature and research, which provides an in-depth understanding of the impacts of climate change on rice production and informs future research and policy development.

Vertebrate taxonomic and functional hotspots in the Brazilian Atlantic Forest

AbstractAimWe aim to find the main drivers of the taxonomic and functional richness and functional dispersion of vertebrates (amphibians, birds, primates, marsupials, rodents, bats and medium‐ and large‐sized mammals) across the Brazilian Atlantic Forest. We also aim to identify hotspots of vertebrate diversity and quantify the extent to which they are legally protected.LocationBrazilian Atlantic Forest.MethodsWe gathered data on the occurrence of vertebrates based on the most recent published databases for Atlantic Forest vertebrates and measured taxonomic richness, functional richness and functional dispersion. We then related variation in diversity, within each group and overall, to environmental and landscape variables. Also, we modelled the diversity of each group for the entire extent of the Atlantic Forest, superimposing the diversity maps to delimit the vertebrate biodiversity hotspots and verified how much of these hotspots are covered by protected areas.ResultsTaxonomic/functional diversity were driven by environmental (e.g., average annual precipitation and precipitation of the driest quarter) and landscape variables (e.g., amount of forest and agricultural areas) for most taxonomic groups. The main hotspots of taxonomic richness are located in the central region of the Atlantic Forest, whereas those for functional diversity occur in the southern region of the biome. Only a little over 10% of the Atlantic Forest is covered by protected areas, and, as such, the vast majority of the medium and high diversity areas fall outside of protected areas, being therefore not legally protected.Main ConclusionsWe found evidence for previously described patterns, including the predicted positive effects of the amount of forest in the landscape and precipitation and the negative effects of agricultural areas on vertebrate diversity. Finally, our results show that most diversity hotspots are outside of legally protected areas, indicating that more conservation efforts should be made towards safeguarding these important areas.

ФАКТОРЫ ОКРУЖАЮЩЕЙ СРЕДЫ И ЗАРАЖЕННОСТЬ ЛОШАДЕЙ ЖЕЛУДОЧНО-КИШЕЧНЫМИ ГЕЛЬМИНТАМИ В ГОРНОМ АЛТАЕ

The aim of the study is to conduct a comparative assessment of the infestation of horses with intestinal helminths in various administrative districts and to characterize the patterns of the relationship between abiotic and anthropogenic environmental factors and the rates of infestation of horses with intestinal helminths in the Gorny Altai. Based on long-term (2019–2023) ovoscopic examinations of 1.2 thousand horses from 10 districts of the region, the infestation of animals with helminths of the gastrointestinal tract was characterized. Correlation analysis was used to characterize the relationship between the level of infestation of animals with helminths, the number of parasites with abiotic and anthropogenic environmental factors in the context of farms and districts of the Gorny Altai. Horses are mostly infected with helminths in the Chemalsky District, where the prevalence of infestation is 95.8 %, and the infection intensity is 458.3 eggs per gram of feces. The lowest prevalence of helminths in animals was recorded in the Ust-Kansky District – EI 56.3 %, with IIs – 186.7 specimens. g/f. The prevalence of infestation in animals is significantly lower in areas characterized by low temperatures and precipitation, and significantly higher in warmer and more humid areas of the region. The prevalence of infestation in horses is 84.6 %, with IIs – 337.5 specimens. g/f. The most significant factors influencing the infection of animals with intestinal helminths (EI, % and IIs) in farms are the long-term average annual precipitation (r = 0.42 and 0.52) and the degree of anthropogenic pressure (r = –0.55 and –0.63), in the context of regions, long-term average annual temperatures (r = 0.55 and 0.65) and long-term average precipitation (r = 0.69 and 0.65).

Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices

Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.

Has IMERG_V07 Improved the Precision of Precipitation Retrieval in Mainland China Compared to IMERG_V06?

Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) is the primary high spatiotemporal resolution precipitation product of the GPM era. To assess the applicability of the latest released IMERG_V07 in mainland China, this study systematically evaluates the error characteristics of IMERG_V07 from the perspective of different seasons, precipitation intensity, topography, and climate regions on an hourly scale. Ground-based meteorological observations are used as the reference, and the performance improvement of IMERG_V07 relative to IMERG_V06 is verified. Error evaluation is conducted in terms of precipitation amount and precipitation frequency, and an improved error component procedure is utilized to trace the error sources. The results indicate that IMERG_V07 exhibits a smaller RMSE in mainland China, especially with significant improvements in the southeastern region. IMERG_V07 shows better consistency with ground station data. IMERG_V07 shows an overall improvement of approximately 4% in capturing regional average precipitation events compared to IMERG_V06, with the northwest region showing particularly notable enhancement. The error components of IMERG_V06 and IMERG_V07 exhibit similar spatial distributions. IMERG_V07 outperforms V06 in terms of lower Missed bias but slightly underperforms in Hit bias and False bias compared to IMERG_V06. IMERG_V07 shows improved ability in capturing precipitation frequency for different intensities, but challenges remain in capturing heavy precipitation events, missing light precipitation, and winter precipitation events. Both IMERG_V06 and IMERG_V07 exhibit notable topography dependency in terms of Total bias and error components. False bias is the primary error source for both versions, except in winter, where high-altitude regions (DEM > 1200 m) primarily contribute to Missed bias. IMERG_V07 has enhanced the accuracy of precipitation retrieval in high-altitude areas, but there are still limitations in capturing precipitation events. Compared to IMERG_V06, IMERG_V07 demonstrates more concentrated error component values in the four climatic regions, with reduced data dispersion and significant improvement in Missed bias. The algorithm improvements in IMERG_V07 have the most significant impact in arid regions. False bias serves as the primary error source for both satellite-based precipitation estimations in the four climatic regions, with a secondary contribution from Hit bias. The evaluation results of this study offer scientific references for enhancing the algorithm of IMERG products and enhancing users’ understanding of error characteristics and sources in IMERG.

Spatio-Temporal Differentiation of Non-Grain Production of Cropland and Its Influencing Factors: Evidence from the Yangtze River Economic Belt, China

Food security is important to guarantee national security and people’s livelihoods, but the increasingly serious problem of non-grain production (NGP) on croplands has exacerbated the risk of food security and directly affected the sustainable development of the national economy and society. This study adopted 130 cities (states) in the Yangtze River Economic Belt as the research units and used ArcGIS10.8, GeoDA1.22, and Origin2022 software and spatial autocorrelation, standard deviational ellipse, and GeoDetector methods to conduct analyses. This study explored the spatial evolution patterns and factors influencing cropland NGP in the Yangtze River Economic Belt. The results show, firstly, that the NGP rate of cropland in the Yangtze River Economic Belt increased from 35.85% in 2006 to 38.62% in 2022. The number of cities (states) with mild and moderate NGP decreased, while the number of cities (states) with severe NGP increased significantly. Secondly, the spatial distribution of the rate of cropland NGP in the Yangtze River Economic Belt had a strong positive correlation, with “high–high agglomeration” tending to be dispersed, “low–low agglomeration” tending to be concentrated, and the overall trajectory of the center of gravity migrating from the northeast to the southwest. Thirdly, the single-factor detection found that the per capita food possession, slope, elevation, and average annual precipitation had strong explanatory power regarding the spatial difference in cropland NGP in the Yangtze River Economic Belt, and the interaction of any two influencing factors showed nonlinear enhancement. The results of this study can help to precisely identify the spatial and temporal evolution characteristics of cropland NGP in the Yangtze River Economic Belt, which is of great significance for supporting the country in controlling the risk of NGP cultivation, promoting the sustainable development of the Yangtze River Economic Belt, and guaranteeing food security.

Podnebne projekcije temperature zraka in padavin za porečja Ledave, Pesnice in Vipave do konca 21. stoletja

As part of the project ‚CeVoTak‘, Integrated Management of Small Water Retention and Soil Erosion Prevention Measures in Agricultural Catchments, we studied changing temperature and precipitation conditions up to the year 2100. The study was conducted on agricultural lands in the catchments of the Ledava and Pesnica rivers in the sub-Pannonian region and the Vipava river in the sub-Mediterranean region. A common climate database was used to create the climate projections - RCM (Regional Climate Model) simulations from the project EURO-CORDEX and scenarios RCP (Representative Concentration Pathway), RCP2.6, 4.5 and 8.5. The projections were prepared for three time periods 2011-2040; 2041-2070 and 2071-2100 for 6 different regional climate models for average, minimum and maximum air temperatures and precipitation. Analysis of the ensemble of model simulations for all scenarios shows similar results for the basin of all rivers, an increase in temperature (maximum in winter, minimum in spring), with high confidence for all scenarios and periods. Projections of precipitation are less reliable, but show an increase in annual precipitation due to the winter increase. The use of climate change projections with expert interpretation is essential for determining the vulnerability of individual areas and building resilience through the implementation of climate change adaptation.

A preliminary integrated analysis of regional paleoclimate variations in China over the past ∼ 21 ka

In this study, we employ biological, geochemical and mineral, and physical proxies to quantitatively and semi-quantitatively reconstruct regional paleoclimate variations in China over the past ∼21 thousand years (ka). We have constructed state-of-the-art transfer functions between proxies and climatic variables in East Asia, revealing substantial paleoclimate variability, and demonstrate significant diversity of paleoclimate variations in regions of China over the past ∼21 ka. Compared with observational data between 1961 and 1990, averaged mean annual temperature (MAT) was ∼5 °C (3–8 °C) lower during the Last Glacial Maximum (LGM, ∼21 ± 3 ka), and ∼ 2 °C (1–3 °C) higher during Holocene Optimum (HO, ±9 ka) in China; while averaged mean annual precipitation (MAP) and averaged summer precipitation varied between 30 and 150%, with enhanced seasonality during the warmer Holocene (8–5 ka). Our quantitative and semi-quantitative paleoclimate reconstructions reveal both similarities and contrasts with previous studies of regional temperature and precipitation variability. The most remarkable paleoclimate variability is recorded in the transitional zone between the humid monsoon and arid desert regions of central and northern China. We conducted a dynamic downscaling paleoclimate simulation with a regional climate model (RegCM4), using the output from the fully-forced transient simulation of the global climate (TraCE-21 K) as the prescribed boundary conditions, to simulate regional climate changes at high spatial resolution in China over the past ∼21 ka. The results improve paleoclimate simulations at regional scales, but reveal differences in comparison with TraCE-21 K, thereby highlighting uncertainties in the simulation modeling. Moreover, we compare proxy-based paleoclimate reconstructions and the output of TraCE-21 K to identify inconsistencies in relation to regional paleoclimate variations, and confirm a generally consistent warming trend in MAT from the LGM to the HO followed by a cooling trend during the late Holocene. An overall increase in both annual and summer precipitation is observed from LGM to Holocene. This general paleoclimate pattern is likely to have been driven by northern hemisphere ice volume and atmospheric greenhouse gas concentrations (GHGs) during the last deglaciation, and boreal summer insolation during the Holocene. This study represents the first attempt to use multi sources and large datasets of proxy reconstructions and numerical simulations to evaluate regional paleoclimate variability in China since the LGM. Our research provides a comprehensive overview of climate change over the past 21 ka and underscores the critical importance of conducting high-resolution simulations and quantitative paleoclimate studies. This approach is essential for deciphering patterns of paleoclimate change that are currently poorly defined.

Research on the spatiotemporal distribution and factors influencing intangible cultural heritage in Fujian Province from a multiscale perspective

The spatiotemporal distribution of intangible cultural heritage in Fujian Province, China, and the factors that influence it were explored using multiple spatial scales. The samples include five batches of Chinese national-level and six batches of Chinese provincial-level intangible cultural heritage items, totaling 554. The samples involve city-scale, county-scale, and traditional dwellings, and the analysis uses various methods, such as gravity migration theory and the GeoDetector model. The results show that, in terms of historical timescales, the moving trajectory of the center of gravity of the intangible cultural heritage distribution in Fujian Province involves reciprocation from north to south, and the center moves south in time from the pre-Qin period to the modern period. Spatially, intangible cultural heritage in Fujian Province forms an overall aggregate pattern, among which traditional skills fall into an aggregate pattern; five categories, including traditional drama, fall into an aggregate-random pattern; and four categories, including traditional medicine, fall into a random pattern. The traditional art category and other intensive distribution areas are located in coastal areas, and the traditional dance category is scattered in northwestern Fujian Province. Experiments on the factors influencing intangible cultural heritage distribution were conducted at the city and county levels. At the city level, human geography factors, such as the resident population, urbanization rate, and gross domestic product, have a greater influence on distribution. At the county level, the influence of physical geographical factors clearly increases. The dominant factors for coastal cities are the normalized difference vegetation index (NDVI), average precipitation, and coastline, and that for inland cities is elevation. From the perspective of categories, the dominant factors of traditional music and Quyi are human geography factors, and those of other types of intangible cultural heritage are the synergistic effects of physical geography and human geography. The conclusions of this study are helpful for systematically protecting and developing the intangible cultural heritage industry and improving research theories and methodological systems of the spatiotemporal distribution and mechanism influencing intangible cultural heritage.

Interannual fluctuations in precipitation shape the trajectory of ecosystem respiration along a grazing exclusion chronosequence in a typical steppe in Inner Mongolia

Grazing exclusion (GE), as an effective strategy for revitalizing degraded grasslands, possesses the potential to increase ecosystem respiration (Re) and significantly influence the capacity of grassland soils to sequester carbon. However, our current grasp of Re dynamics in response to varying durations of GE, particularly in the context of precipitation fluctuations, remains incomplete. To fill this knowledge gap, we conducted a monitoring of Re over a 40-year GE chronosequence within Inner Mongolia temperate typical steppe across two distinct hydrologically years. Overall, Re exhibited a gradual saturation curve and an increasing trend with the duration of GE in the wet year of 2021 and the normal precipitation year of 2022, respectively. The variance primarily stemmed from relatively higher microbial biomass carbon observed in the short-term GE during 2022 in contrast to 2021. Moreover, the impacts of GE on the sensitivities of Re to moisture and temperature were intricately tied to precipitation patterns. increasing significantly with prolonged GE duration in 2022 but not in 2021. Our study highlights the intricate interplay between GE duration, precipitation variability, and Re dynamics. This deeper understanding enhances our ability to predict and manage carbon cycling within typical steppe in Inner Mongolia, offering invaluable insights for effective restoration strategies and climate change mitigation.

Assessment of climate change on river streamflow under different representative concentration pathways

Climate change and excessive greenhouse gas emissions profoundly impact hydrological cycles, particularly in arid and semi-arid regions, necessitating assessments of their effects on water resource management, agriculture, soil fertility, nutrient transport, hydropower generation, and flood risk. This study investigates climate change repercussions on streamflow in the Zarrineh River Basin, Iran, across three decadal intervals (2020–2029, 2055–2064, and 2090–2099) aiming to develop effective adaptation and mitigation strategies. Four General Circulation Models (GCMs), chosen based on distinct Representative Concentration Pathways (RCPs) determined by the annual mean temperature gradient, are employed. These models generate daily maximum (Tmax) and minimum (Tmin) temperatures along with precipitation data. Subsequently, these variables are integrated into the Soil and Water Assessment Tool (SWAT) model to analyze river flow alterations for each decadal timeframe. Comparison between future projections and observed climate data reveals a gradual decline in precipitation and Tmax, coupled with a substantial increase in Tmin. The average precipitation diminishes from 0.77 mm in the period 1985–1994 to a range of 0.42–0.28 mm in 2090–2099. The simulated flow at the basin outlet highlights that the GCM with the highest annual mean temperature gradient yields the lowest streamflow, while conversely, the model with the lowest gradient generates the highest. Consequently, streamflow experiences a decline from 52 m3/s in 1985–1994 to a range of 41–20 m3/s in 2090–2099.

Different habitats of ferns growing in the Amonkoton stream, Zerafshan Valley, Uzbekistan

Abstract. Muminov D, Khaydarov K, Zhalov K, Hasanov M, Abdumuminova R, Ochilov U. 2024. Different habitats of ferns growing in the Amonkoton Stream (Zerafshan Valley), Uzbekistan. Biodiversitas 25: 2696-2704. The Zerafshan Valley, Uzbekistan, characterized by a warm and arid climate, has declined vegetation and soil quality over recent decades, marking a stark departure from its once lush past. Understanding the nuanced relationship between species and their habitat is imperative to unraveling this ecological transformation. This research delves into ferns, which are highly responsive to environmental factors, seeking to elucidate their circumstances within the changing ecosystem. Through strategically planned intensive transects and plots as proxies for fern growth and habitat analysis, statistical methods like the Shannon-Wiener Index (H) and Bray-Curtis index were deployed. The climate-related information analysis was conducted using the CRU TS 4.07 tool. We made use of average temperatures and precipitation over 120 years. The results of analyses have been acquired from 490 fern individuals belonging to 13 species, 7 genera, and 6 families. There are four species: Equisetum arvense L., Equisetum ramosissimum Desf., Cystopteris fragilis (L.) Bernh. and Adiantum capillus-veneris L. were employed as indicators of habitat. The findings underscore a substantial decline in fern-populated areas, resulting in diminished diversity and abundance and a relatively high rarity level. Furthermore, a latitudinal correlation with ferns along the stream direction is exhibited by four indicator species, offering valuable insights into the intricate dynamics of the Zerafshan Valley's ecosystem.

Effects of forest age and season on soil microbial communities in Chinese fir plantations.

Understanding changes in the distribution patterns and diversity of soil microbial communities from the perspectives of age-related changes, seasonal variations, and the interaction between the two factors can facilitate the management of plantations. In Chinese fir plantations, we collected soils from different depths in over-mature forests, mature forests, near-mature forests, middle-aged forests, and young forests in summer, autumn, and winter in China's subtropical regions. As the forests developed, bacterial and fungal communities' diversity changed, reached a minimum value at near-mature forests, and then increased in mature forests or over-mature forests. Near-mature forests had the lowest topological properties. The Shannon index of microbial communities varied with seasonal changes (P < 0.05). Bacterial and fungal community composition at genus level was more closely related to temperature indicators (including daily average temperature, daily maximum temperature, and daily minimum temperature) (P < 0.01, 0.5554 < R2 <0.8185) than daily average precipitation (P > 0.05, 0.0321 < R2 <0.6773). Bacteria were clustered by season and fungi were clustered by forest age. We suggested that extending the tree cultivation time of plantations could promote microbial community recovery. In addition, we found some species worthy of attention, including Bacteroidetes in autumn in over-mature forests, and Firmicutes in summer in young forests.IMPORTANCEChinese fir [Cunninghamia lanceolata (Lamb.) Hook] is an important fast-growing species with the largest artificial forest area in China, with the outstanding problems of low quality in soil. Soil microorganisms play a crucial role in soil fertility by decomposing organic matter, optimizing soil structure, and releasing essential nutrients for plant growth. In order to maintain healthy soil quality and prevent nutrient depletion and land degradation, it is crucial to understand the changes of soil microbial composition and diversity. Our study determined to reveal the change of soil microbial community from stand age, season, and the interaction between the two aspects, which is helpful to understand how interannual changes in different years and seasonal changes in one year affect soil fertility restoration and sustainable forest plantation management. It is a meaningful exploration of soil microbial communities and provides new information for further research.

FEATURES OF FORMING WATER AVAILABILITY FOR WINTER WHEAT IN THE SOUTH OF UKRAINE

The article examines the importance of considering several factors affecting the soil water regime in the context of developing models for forecasting productive soil moisture reserves. It was established that the main factors, such as the type of soil, its density, and mechanical composition, remain constant in different soil and climatic regions of Ukraine. The second group of factors, such as air temperature, precipitation, and soil moisture, are subject to changes throughout the growing season and even over short periods. Therefore, the dynamics of soil moisture as a function of the main variables, such as average air temperature and precipitation, was considered using calculations. Initial moisture reserves are used in the calculations for more accurate forecasting of moisture reserves at the end of a specified period. Hydrothermal conditions considered as predictors in the regression equation are also used. The reliability of the conducted research is confirmed by the analysis of independent input and output information from the Kherson weather station in the period from 2018 to 2021 regarding the actual reserves of productive moisture in the soil at a depth of 0 - 20,0 - 50 and 0 - 100 cm. The average error between actual and calculated data did not exceed +13,5%. It confirms the reliability and precision of the conducted research making it the basis for further analyses and conclusions. The conclusions noted the need for accurately determining soil moisture to effectively manage agrometeorological conditions and optimize crop yield. The authors believe that the research work presented in this article can significantly contribute to developing modern approaches to water availability in agriculture and agrometeorology. That will contribute to the gradual and improved development of soil moisture forecasting methodology, which is key to ensuring sustainable and productive development in agriculture.