Southwestern Region Research Articles

Applying the driver-pressure-state-impact-response model to ecological restoration: A case study of comprehensive zoning and benefit assessment in Zhejiang Province, China

Ecosystem degradation is a global problem that poses a significant threat to the sustainable development of human societies, particularly in developing countries, such as China. In response, China has implemented a series of ecological restoration (ER) policies over recent years. However, significant regional developmental disparities, pronounced spatial heterogeneity of ecological issues, and substantial historical debt for ER in China present considerable obstacles and financial burdens to the effective implementation of ER strategies. Delineating ER zones and assessing the ER benefits are essential for developing effective ER strategies and implementing ER projects. In this study, we constructed a comprehensive framework for ER utilizing the Driver-Pressure-State-Impact-Response (DPSIR) model, quantified the urbanization levels, ecological state, and restoration costs in Zhejiang Province to delineate ER zones, integrated the patch-generating land use simulation model with the ecosystem service value assessment method to quantify the benefits of ER, and ultimately developed tailored ER strategies. The results showed that: (1) The pattern of urbanization levels was characterized by high levels in the northeast and low levels in the southwest, which constrated with the ecological state. The areas of high restoration costs were located in the northeastern and southeastern regions, and the areas of low restoration costs were situated in the southwestern region. (2) The rate of construction land expansion is significantly curtailed under the ER scenario compared to the natural development scenario in 2035, while forest areas have seen effective protection and an increase from the levels of 2020. (3) The ER policy is projected to generate ecological benefits totaling CNY 8.23 billion by 2035, substantially reducing the rate of ecosystem degradation. (4) Zhejiang Province is divided into five zones at the county scale: ecological autonomous protection zone, ecological core protection zone, ecological priority restoration zone, ecological control zone, and moderate development zone. Strategies have been devised based on the forecasted benefits of ER, offering valuable insights into ecological management. These findings aim to enhance the understanding of ER and support the development and implementation of regional ecological policies.

A Multi-Scale Content-Structure Feature Extraction Network Applied to Gully Extraction

Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion control. Traditional field measurement methods consume a large amount of human resources, so it is of great significance to use artificial intelligence techniques to automatically extract gullies from satellite remote sensing images. This study obtained the gully distribution map of the southwestern region of the Dahe Bay Farm in Inner Mongolia through field investigation and measurement and created a gully remote sensing dataset. We designed a multi-scale content structure feature extraction network to analyze remote sensing images and achieve automatic gully extraction. The multi-layer information obtained through the resnet34 network is input into the multi-scale structure extraction module and the multi-scale content extraction module designed by us, respectively, obtained richer intrinsic information about the image. We designed a structure content fusion network to further fuse structural features and content features and improve the depth of the model’s understanding of the image. Finally, we designed a muti-scale feature fusion module to further fuse low-level and high-level information, enhance the comprehensive understanding of the model, and improve the ability to extract gullies. The experimental results show that the multi-scale content structure feature extraction network can effectively avoid the interference of complex backgrounds in satellite remote sensing images. Compared with the classic semantic segmentation models, DeepLabV3+, PSPNet, and UNet, our model achieved the best results in several evaluation metrics, the F1 score, recall rate, and intersection over union (IoU), with an F1 score of 0.745, a recall of 0.777, and an IoU of 0.586. These results proved that our method is a highly automated and reliable method for extracting gullies from satellite remote sensing images, which simplifies the process of gully extraction and provides us with an accurate guide to locate the location of gullies, analyze the shape of gullies, and then provide accurate guidance for gully management.

Measuring Food Insecurity in Children under 5 Years of Age with Acute Undernutrition in Valle Del Cauca-Colombia.

Our objective was to assess food insecurity among children under 5 years old with moderate, and severe malnutrition from Valle del Cauca, a state located in the southwestern region of Colombia. A descriptive observational study was conducted, including children whose weight-for-height (W/H) indicator was below 2 SD, as recorded on the World Health Organization (WHO) growth charts, or who exhibited severe malnutrition phenotypes such as marasmus or Kwashiorkor. Family and child food security were evaluated using the Latin American and Caribbean Food Security Scale (ELCSA). 58.6% of households with acutely malnourished children experienced food insecurity. A statistically significant relationship was found between food insecurity and children of Afro-Colombian and Indigenous descent. According to caregivers' perceptions, 30.2% of child malnutrition cases were related to poor feeding and caregiving practices. Not all children with acute malnutrition suffer from food insecurity. Therefore, the findings of this research suggest that governmental efforts should focus not only on ensuring food availability, but also on educating caregivers about the importance of a balanced and nutritious diet tailored to the specific characteristics of each region and promoting appropriate caregiving practices.

Nitrate sources and transformation in surface water and groundwater in Huazhou District, Shaanxi, China: Integrated research using hydrochemistry, isotopes and MixSIAR model

Global water resources affected by excessive nitrate (NO3−) have caused a series of human health and ecological problems. Therefore, identification of NO3− sources and transformations is of pivotal significance in the strategic governance of widespread NO3− contaminant. In this investigation, a combination of statistical analysis, chemical indicators, isotopes, and MixSIAR model approaches was adopted to reveal the hydrochemical factors affecting NO3− concentrations and quantify the contribution of each source to NO3− concentrations in surface water and groundwater. The findings revealed that high groundwater NO3− concentration is concentrated in the southwestern region, peaking at 271 mg/L. NO3− concentration in the Wei River and Yuxian River exhibited an increase from upstream to downstream, but in the Shidi River and Luowen River, its concentration was highest in the upstream. Groundwater NO3− has noticeable correlation with Na+, Ca2+, Mg2+, Cl−, HCO3−, TDS, EC, and ORP. In surface water, NO3− level is significantly correlated with NH4+ and ORP. Major sources of NO3− in surface and groundwater comprise manure & sewage and soil nitrogen. Source contribution for surface water was calculated by MixSIAR model to obtain soil nitrogen (57.7%), manure & sewage (23.8%), chemical fertilizer (12%), and atmospheric deposition (6.4%). In groundwater, soil nitrogen and manure & sewage accounted for 19% and 63.8% of nitrate sources, respectively. Both surface water and groundwater exhibited strong oxidation, with nitrification the primary process. It is expected that this study will provide insights into the dynamics of NO3− and contribute to the development of effective strategies for mitigating NO3− contaminant, leading to sustainable management of water resources.

Public perceptions of counterfeit drugs in Nigeria and the European Union

Purpose The purpose of this paper is to examine the perception and experience of counter pharmaceuticals in Nigeria compared to the European Union. Design/methodology/approach The findings from this paper are based upon a survey of 362 Nigerians sourced in public places with the data and then compared results from a survey by the European Union. Findings The key findings from this research showed some areas of similarity between Nigerians and Europeans on their views on the acceptability of purchasing counterfeits. However, Nigerians were more open to purchasing counterfeits despite the risks. There was also more anxiety over the risk of purchasing counterfeit medicines compared to the European Union. Research limitations/implications Due to security issues, survey data could only be sourced from Abuja, Lagos and the relatively peaceful southwestern region of Nigeria. The data is, therefore, not representative of Nigeria. Practical implications The purchasing experience of counterfeit medicines by Nigerians along with their anxieties highlights the need for more enforcement action to tackle this problem and reassure the public. Social implications The paper highlights the challenges of securing genuine pharmaceutical products in the Global South and the need for more greater cross-border action to tackle the problem. Originality/value To the best of the authors’ knowledge, this is the first survey of Nigerian citizens on this issue.

Response of Hydrothermal Conditions to the Saturation Values of Forest Aboveground Biomass Estimation by Remote Sensing in Yunnan Province, China

Identifying the key climate variables affecting optical saturation values (OSVs) in forest aboveground biomass (AGB) estimation using optical remote sensing is crucial for analyzing OSV changes. This can improve AGB estimation accuracy by addressing the uncertainties associated with optical saturation. In this study, Pinus yunnanensis forests and Landsat 8 OLI imagery from Yunnan were used as case studies to explain this issue. The spherical model was applied to determine the OSVs using specific spectral bands (Blue, Green, Red, Near-Infrared (NIR), and Short-Wave Infrared Band 2 (SWIR2)) derived from Landsat 8 OLI imagery. Canonical correlation analysis (CCA) uncovered the intricate relationships between climatic variables and OSV variations. The results reveal the following: (1) All Landsat 8 OLI spectral bands showed a negative correlation with the Pinus yunnanensis forest AGB, with OSVs ranging from 104.42 t/ha to 209.11 t/ha, peaking in the southwestern region and declining to the lowest levels in the southeastern region. (2) CCA effectively explained 93.2% of the OSV variations, identifying annual mean temperature (AMT) as the most influential climatic factor. Additionally, the mean temperature of the wettest quarter (MTQ) and annual precipitation (ANP) were significant secondary determinants, with higher OSV values observed in warmer, more humid areas. These findings offer important insights into climate-driven OSV variations, reducing uncertainty in forest AGB estimation and enhancing the precision of AGB estimations in future research.

A Probabilistic Statistical Risk Assessment Method for Soil Erosion Using Remote Sensing Data: A Case Study of the Dali River Basin

Soil erosion risk assessment enables the identification of areas requiring priority treatment and avoids wasting human and material resources. The factor scoring method used in existing studies has high subjectivity, and the method of expressing erosion risk according to the soil erosion intensity ignores the random nature of the occurrence of erosion; therefore, neither method accurately reflects the risk of soil erosion. In order to address this issue, this study proposes a soil erosion risk assessment method that integrates the outcome and the probability of occurrence of soil erosion by means of a probabilistic statistical model. Subsequently, experimental research is conducted in the Dali River Basin. On the basis of long time-series data, using mathematical statistics as a tool and drawing on the empirical frequency formula, the probabilistic statistical risk assessment model is combined with the Modified Universal Soil Loss Equation (RUSLE) model to account for the probability of regional soil erosion at different intensity levels in the long time-series, which is combined with the intensity of erosion to carry out soil erosion risk assessment. The results of our study show the following: (1) The central and southwestern regions of the Dali River Basin (DRB) present medium and high levels of soil erosion risk, with the proportion of low-risk areas increasing annually, accounting for 78.97% of the DRB in 2020, while extremely high-risk areas account for only 0.40% of the DRB. (2) The major components impacting soil erosion risk in the DRB, as revealed by the geodetector, are the normalized difference vegetation index (NDVI) and slope, where the interaction between the two dominated the spatial variation in soil erosion risk. (3) Comparing the soil erosion risk and its status in the coming years, the proposed assessment method based on the occurrence probability can reveal the future soil erosion risk better than the traditional assessment method.

Pollution source characterization and evaluation of groundwater quality utilizing an integrated approach of Water Quality Index, GIS and multivariate statistical analysis

ABSTRACT The Mid-Gangetic Plain, a vital farmland in India, faces increasing groundwater quality deterioration due to anthropogenic activities. This study aimed to assess groundwater quality and contamination sources in the region utilizing statistical methods. A total of 78 groundwater samples were collected and analyzed using standard methods. The hydrochemistry analysis of samples revealed that several parameters such as Ca2+, Mg2+, HCO3−, NO3−, F− and PO43− surpassed the limits prescribed by the Bureau of Indian Standards (BIS). The principal component analysis yielded three significant factors, explaining 68.96% variation, highlighting geogenic and anthropogenic influences on groundwater chemistry. Hierarchical cluster analysis categorized groundwater into three clusters based on the parameters with similar trends of variation. Furthermore, Discriminant analysis identified four significant variables (Mg2+, F−, Cl− and NO3−) responsible for creating the distinction among the identified clusters. Hydrogeochemical categorization and multivariate statistical analyses indicated that rock–water interaction, weathering, leaching and anthropogenic activities collectively influenced groundwater quality throughout the studied region. The Water Quality Index reveals that 59% of samples have good water quality, while 41% exhibit poor quality predominantly concentrated in the south-western, south-eastern and central regions. This study demonstrates the efficacy of statistical techniques to interpret complex datasets and grasp water quality dynamics, enhancing groundwater management.

Study on the Effect of Liquefiable Overburden Foundations of Rockfill Dams Based on a Pore Pressure Model

China’s southwestern region boasts abundant hydropower resources. However, the area is prone to frequent strong earthquakes. The areas surrounding dam sites typically have deep overburden, and the liquefaction of saturated sand foundations by earthquakes poses significant safety risks to the construction of high dams in the southwest. The effects of liquefaction and reinforcing measures on the foundations of rockfill dams on liquefiable overburden under seismic action are currently the subject of somewhat unsystematic investigations. The paper utilizes the total stress and effective stress methods, based on the equivalent linear model, to perform numerical simulations on the overburden foundations of rockfill dams. The study explores how factors such as dam height, overburden thickness, liquefiable layer depth, liquefiable layer thickness, ground motion intensity, and seismic wave characteristics affect the liquefaction of the overburden foundations. Additionally, it examines how rockfill dams impact the dynamic response, considering the liquefaction effects in the overburden. The results show that although the total stress method, which ignores the cumulative evolution of pore pressure during liquefaction, can reveal the basic response trend of the dam, its results in predicting the acceleration response are significantly biased compared to those of the effective stress method, which comprehensively considers the cumulative changes in liquefaction pore pressure. Specifically, when the effect of soil liquefaction is considered, the predicted acceleration response is reduced compared to that when liquefaction is not considered, with the reduction ranging from 4% to 30%; with increases in the thickness and burial depth of the liquefiable layer, the effective stress method considering liquefaction significantly reduces the predicted peak acceleration; the effect of liquefiable soil on the attenuation of the speed response is more sensitive to the low-frequency portion of the seismic wave. The study’s findings are a significant source of reference for the planning and building of rockfill dams on liquefiable overburden.

Incorporating Ecosystem Service Trade-Offs and Synergies with Ecological Sensitivity to Delineate Ecological Functional Zones: A Case Study in the Sichuan-Yunnan Ecological Buffer Area, China

Enhancing regional ecosystem stability and managing land resources effectively requires identifying ecological function zones and understanding the factors that influence them. However, most current studies have primarily focused on ecosystem service bundles, paying less attention to the trade-offs, synergies, and ecological sensitivity, leading to a more uniform approach to functional zoning. This study aimed to analyze and describe the spatial and temporal patterns of four essential ecosystem services, including water yield (WY), net primary productivity (NPP), soil conservation (SC), and habitat quality (HQ), in the Sichuan-Yunnan ecological buffer area over the period from 2005 to 2019. Spatial overlay analysis was used to assess ecological sensitivity, trade-offs, synergies, and ecosystem service bundles to define ecological functional zones. Geographic detectors were then applied to identify the primary drivers of spatial variation in these zones. The findings showed a progressive improvement in ecosystem service functions within the Sichuan-Yunnan ecological buffer zone. Between 2005 and 2019, NPP, soil conservation, and water yield all demonstrated positive trends, while HQ displayed a declining trend. There was significant spatial heterogeneity and distinct regional patterns in ecosystem service functions, with a general decrease from southwest to northeast, particularly in NPP and HQ. Trade-offs were evident in most ecosystem services, with the most significant between WY and HQ and most in the northeast and east regions. Ecological sensitivity decreased from southwest to northeast. Regions with a higher ecological sensitivity were primarily situated in the southwestern region, and their spatial distribution pattern was comparable to that of high habitat quality. The spatial overlay analysis categorized areas into various types, including human production and settlement zones, ecologically vulnerable zones, ecological transition zones, and ecological conservation zones, accounting for 17.28%, 22.30%, 7.41%, and 53.01% of the total area, respectively. The primary environmental factor affecting ecological function zoning was identified as precipitation, while the main social variables were human activity and population density. This study enhances the understanding of ecological functions and supports sustainable development in the Sichuan-Yunnan ecological buffer area, offering important guidance for ecological zoning.

Assessing terrestrial water storage dynamics and multiple factors driving forces in China from 2005 to 2020

In the context of global warming, comprehending the dynamics of terrestrial water storage (TWS) and its responses to natural and anthropogenic factors is paramount for hydrological research and the management of water resources in China. This study utilized GRACE (Gravity Recovery and Climate Experiment)/GRACE-Follow On (GRACE-FO) satellite data to analyze terrestrial water storage across nine basins in China from 2005 to 2020 at multiple temporal and spatial scales. Subsequently, employing a Geographic detector model, potential influencing factors were identified, and an enhanced Geographically Weighted Regression (GWR) method was proposed for attributing changes in TWS in China. The findings reveal a consistent declining trend in TWS based on GRACE/GRACE-FO data across different temporal scales, with the most pronounced decreases observed in August and September. Geographic Detector analysis unveils significant interactions among various environmental factors, with climate variables playing a pivotal role in modulating hydrological characteristics of major river basins, where rising temperatures can exacerbate the severity of precipitation events, thus increasing the risk of floods and droughts. Moreover, analysis of the primary influencing factors indicates significant impacts of population density and topography on water resources in the southeastern and southwestern regions, particularly amidst increasing human activities and urbanization expansion. The results of this study are crucial for comprehending the dynamic changes and mechanisms of TWS in China, as well as for formulating water resource management strategies.

The environmental capacity of rare heavy metal calculation in the Qinghai‒Tibet Plateau region via multifractal analysis.

Accurate assessments of the soil environmental capacity are important for evaluating heavy metal pollution levels, facilitating effective prevention and control measures against such pollution. However, due to the lack of risk screening values for certain key elements, such as Rb, Sn, and Th, the assessment of the soil environmental capacity is not comprehensive. Therefore, in this study, the Menyuan-Huangzhong area of Qinghai Province was selected as the research area, and local background and risk values were established via multifractal analysis, thereby systematically examining the environmental capacity. The findings indicated that within the study area, the static environmental capacity values of 15 elements could be ranked as follows: Ba, Cu, Zn, Cr, Rb, Ni, La, Pb, Th, As, U, Sn, Tl, Cd, and Hg. In general, the residual capacity distribution of the various elements varied across the study area, with lower values primarily found in the northern and central regions and higher values obtained in the northwestern and southwestern regions. Between 2018 and 2068, there was a notable and rapid decline in the dynamic environmental capacity of Hg, Cu, and Cd in the study area. In the Menyuan-Huangzhong area of Qinghai, the average comprehensive soil environmental capacity index reached 0.91, indicating a moderate environmental capacity and slight associated health risks. The findings of this study could serve as a valuable reference for soil heavy metal pollution assessment, early warning, and management in this area; enhance the study of soil environmental capacity methods; and provide a theoretical foundation for subsequent research.

Systematic Mapping of Climate Change Impacts on Human Security in Bangladesh

There is an increasing consensus that climate change undermines human security by exacerbating existing challenges, acting as a “threat multiplier”. Bangladesh is a climate hot spot due to its geographical location, dense population and vulnerable socio-economic infrastructure. Although there is an increasing number of studies on the impacts of climate change in Bangladesh, aggregated research that combines this evidence and provides a comprehensive overview is lacking. The aim of this research is to thoroughly investigate the characteristics of the academic literature on the complex pathways through which climate variability affects different components of human security in Bangladesh, allowing for determination of the trends and research gaps, as well as whether they lead to conflict or cooperation. We used a systematic mapping methodology to search and screen 1839 publications in Web of Science, including 320 publications for the final synthesis. We found a predominant research focus on rural areas, especially in the southwestern region, with declining crop yield, economic loss, migration, water shortage, food scarcity and health hazards being the highlighted impacts of climate change for Bangladesh. The impacts on food, economic, environmental, health and water security have been well studied, but we found significant research gaps in some human security components, especially energy security. Women and the economically disadvantaged are disproportionately affected, and the causal pathways between conflict or cooperation and the ever-changing climate lack research efforts, implying a dire need to focus on under-researched areas before they become more complex and difficult to address. Policies and interventions should prioritise climate-resilient agricultural practices and infrastructure in high-risk areas, building local capacities and integrating climate risk assessments into urban planning, considering the high influx of environmental migrants. This systematic map provides a foundation for future longitudinal studies, establishes a baseline for this era for future comparisons and serves as a reliable database for relevant stakeholders and policy makers.

The chain mediating role of family health and physical activity in the relationship between life satisfaction and health-promoting lifestyles among young adults in China.

Unhealthy lifestyles during adolescence are significant factors leading to chronic diseases in the future. Enhancing health-promoting lifestyles among young adults in China is crucial for preventing and reducing the risk factors of chronic diseases. This study aims to explore the relationships between life satisfaction, family health, physical activity, and health-promoting lifestyles among young adults in China. It also seeks to confirm the chain mediation role of family health and physical activity in the influence of life satisfaction on health-promoting lifestyles in this population. This study, conducted from August 2023 to November 2023, employed a random sampling method to recruit young adult participants aged 18-40 in the southwestern region of China. Variables were measured using the Satisfaction with Life Scale (SWLS), the Family Health Scale-Short Form (FHS-SF), the Physical Activity Rating Scale-3 (PARS-3), and the Health-Promoting Lifestyle Profile II Revised (HPLP-IIR). Data analysis was performed using SPSS 27.0 and the PROCESS macro version 4.1. The results indicated that life satisfaction was positively correlated with family health (r = 0.225), physical activity (r = 0.245), and health-promoting lifestyles (r = 0.506). Family health was positively correlated with physical activity (r = 0.320) and health-promoting lifestyles (r = 0.312). Physical activity was positively correlated with health-promoting lifestyles (r = 0.429). Additionally, life satisfaction could influence health-promoting lifestyles directly (effect = 0.369) and through three mediation pathways: (a) family health (effect = 0.033); (b) physical activity (effect = 0.050); (c) family health and physical activity (effect = 0.020). This study supports the mediating role of family health and physical activity in the influence of life satisfaction on health behaviors among young adults in China. Therefore, we recommend that future public health initiatives place greater emphasis on family health and create conditions that facilitate physical activity for this group. This could be an important direction for further enhancing health-promoting lifestyles among young adults in China.

Spatio-Temporal Diversification of per Capita Carbon Emissions in China: 2000–2020

Exploring the low-carbon transition in China can offer profound guidance for governments to develop relevant environmental policies and regulations within the context of the 2060 carbon neutrality target. Previous studies have extensively explored the promotion of low-carbon development in China, yet no studies have completely explained the mechanisms of the low-carbon transition in China from the perspective of per capita carbon emissions (PCEs). Based on the statistics and carbon emissions data of 367 prefecture level cities in China from 2000 to 2020, this study employed markov chain, kernel density analysis, hotspots analysis, and spatial regression models to reveal the spatiotemporal distribution patterns, future trends, and driving factors of PCEs in China. The results showed that China’s PCEs in 2000, 2010, and 2020 were 0.72 ton/persons, 1.72 ton/persons, and 1.91 ton/persons, respectively, exhibiting a continuous upward trend, with evident regional heterogeneity. PCEs in northern China and the eastern coastal region were higher than those of southern China and the central and southwestern regions. The PCEs in China showed obvious spatial clustering, with hot spots mainly concentrated in Inner Mongolia and Xinjiang, while cold spots were mainly in some provinces in southern China. The transition of PCEs in China exhibited a strong stability and a ‘club convergence’ phenomenon. A regression analysis revealed that the urbanization level and latitude had negative effects on PCEs, while the regional economic development level, average elevation, average slope, and longitude showed positive effects on PCEs. These findings have important implications for the promotion of the low-carbon transition and the effective achievement of the “dual carbon” goal.

Analysis of the epidemiological characteristics and influencing factors of tuberculosis among students in a large province of China, 2008–2018

This study examines tuberculosis (TB) incidence among students in Jilin Province, China, focusing on spatial, temporal, and demographic dynamics in areas of social inequality. Variation in incidence rate of TB was analyzed using the joinpoint regression method. Spatial analyses techniques included the global and local Moran indices and Getis-Ord Gi* analysis. Demographic changes in new cases were analyzed descriptively, and the Geodetector method measured the influence of risk factors on student TB incidence. The analysis revealed a declining trend in TB cases, particularly among male students. TB incidence showed geographical heterogeneity, with lower rates in underdeveloped rural areas compared to urban regions. Significant spatial correlations were observed, with high-high clusters forming in central Jilin Province. Hotspots of student TB transmission were primarily concentrated in the southwestern and central regions from 2008 to 2018. Socio-economic factors exhibited nonlinear enhancement effects on incidence rates, with a dominant bifactor effect. High-risk zones were predominantly located in urban centers, with university and high school students showing higher incidences than other educational stages. The study revealed economic determinants as being especially important in affecting TB incidence among students, with these factors having nonlinear interacting effects on student TB incidence.

Effect of Sowing Date on Some Agronomical Characteristics of Rye Cultivars in Iraq

The introduction of rye cultivation in Iraq necessitates the implementation of agrotechnological experiments. Two-year irrigated field experiments were carried out in Al-Muthanna Governorate (in the southwestern region of Iraq) in 2021/2022 and 2022/2023 to evaluate the performance of three European rye cultivars introduced to Iraq, focusing on the most significant agronomical and morphological characteristics. Three sowing dates (01 November, 15 November and 01 December) were tested in a split plot, randomized complete block design. We observed that both the cultivar and sowing date, but not the crop year, influenced the studied characteristics. In general, the early sowing dates enhanced the growth and development of rye and resulted in a higher yield compared to the later sowing dates. We observed that all evaluated rye cultivars can be grown safely in the agroclimatic and soil characteristics of this region. The grain yield was 3.1, 4.2 and 6.9 t ha−1 on average for all the sowing dates, and the above ground biomass results were 13.6, 12.0 and 22.9 on average for all sowing dates in ‘Krzyca’, ‘Dańkowskie złote’ and ‘Horyzo’, respectively. In addition, the highest grain yield (8.8 t ha−1) was harvested in ‘Horyzo’ when it was sown on 01 November; thus, we recommend choosing ‘Horyzo’ for cultivation in Iraq and sowing it in early November. Although further study is required to improve agro-technology (such as the nutrient supply) by using a larger number of cultivars, we can conclude that rye can be grown safely in Iraq under irrigated conditions.

Western disturbances: Occurrence and impact on wheat productivity in Punjab

Western disturbances (WD) bring moderate to heavy rain in the northern parts of the country as well as heavy snow to the mountain areas of the Indian subcontinent. It is the source of most of the winter and post-monsoon rainfall in northwest India. Spatio-temporal analysis of western disturbances was carried out by using weather data recorded at Ballowal Saunkhri (sub-mountainous region), Ludhiana (central plain region) and Bathinda (south west region). The WD events per month were lowest in November and highest in March month averaged over all the agroclimatic regions. The highest numbers of WD events were found during February month in the Sub-mountainous region and during March in central plain region and south-western region. Winter rainfall quantity and number of rainfall events were higher in the sub-mountainous region followed by the central plain region and lowest in the south-western region. Higher number of WD during wheat growing season along with less and well distributed rainfall resulting in lower maximum temperature conditions were conducive for higher productivity in Punjab. The significantly positive correlation was observed between the number of western disturbances and wheat productivity during April month at central plain region and southwest region, whereas, the seasonal total number of WDs showed significant positive relationship at submontane region and southwest region.

The spatio-temporal variations of cultivated land compensation efficiency and its influencing factors in mainland China

Cultivated land, for which compensation is a practical approach to safeguarding, is a strategic and scarce resource. Evaluating the cultivated land compensation efficiency and identifying its influencing factors are of great significance for monitoring the effect of such compensation and improving the associated policy. A new multi-dimensional framework for estimating the cultivated land compensation efficiency was proposed. This framework not only emphasized the externality of cultivated land but also incorporated its ecological value. Cultivated land compensation efficiency in mainland China from 2000 to 2021 was estimated using this framework and the global Super-SBM model. The panel Tobit model was also adopted to analyze the factors influencing cultivated land compensation efficiency. The results show that (1) Over the past 22 years, the cultivated land compensation efficiency in mainland China initially declined but subsequently exhibited an upward trend, maintaining an average value of 0.724. (2) On a spatial scale, the cultivated land compensation efficiency exhibited pronounced regional pattern, with higher levels observed in the northeastern and southwestern regions of mainland China and lower levels in the eastern region. The cultivated land compensation efficiency in different provinces has distinctive patterns as well. Generally, the cultivated land compensation efficiency is relatively stable in most provinces, though few illustrate an uptrend. (3) Both the ratio of the population with tertiary education and above to the total population and the ratio of primary sector production to GDP affect cultivated land compensation efficiency positively, with the former being more significant. Conversely, GDP per capita, agricultural water consumption, the area affected by disasters, and the ratio of local expenditure on science, technology and education to total fiscal expenditure affect cultivated land compensation efficiency negatively. Therefore, a set of recommendations has been put forward, encompassing the optimization of provincial inputs and outputs, the reinforcement of inter-provincial coordination and collaboration, and the expansion of the talent pool of funds.

Landsat-based spatiotemporal estimation of subtropical forest aboveground carbon storage using machine learning algorithms with hyperparameter tuning.

The aboveground carbon storage (AGC) in forests serves as a crucial metric for evaluating both the composition of the forest ecosystem and the quality of the forest. It also plays a significant role in assessing the quality of regional ecosystems. However, current technical limitations introduce a degree of uncertainty in estimating forest AGC at a regional scale. Despite these challenges, remote sensing technology provides an accurate means of monitoring forest AGC. Furthermore, the implementation of machine learning algorithms can enhance the precision of AGC estimates. Lishui City, with its rich forest resources and an approximate forest coverage rate of 80%, serves as a representative example of the typical subtropical forest distribution in Zhejiang Province. Therefore, this study uses Landsat remote sensing images, employing backpropagation neural network (BPNN), random forest (RF), and categorical boosting (CatBoost) to model the forest AGC of Lishui City, selecting the best model to estimate and analyze its forest AGC spatiotemporal dynamics over the past 30 years (1989-2019). The study shows that: (1) The texture information calculated based on 9×9 and 11×11 windows is an important variable in constructing the remote sensing estimation model of the forest AGC in Lishui City; (2) All three machine learning techniques are capable of estimating forest AGC in Lishui City with high precision. Notably, the CatBoost algorithm outperforms the others in terms of accuracy, achieving a model training accuracy and testing accuracy R2 of 0.95 and 0.83, and RMSE of 2.98 Mg C ha-1 and 4.93 Mg C ha-1, respectively. (3) Spatially, the central and southwestern regions of Lishui City exhibit high levels of forest AGC, whereas the eastern and northeastern regions display comparatively lower levels. Over time, there has been a consistent increase in the total forest AGC in Lishui City over the past three decades, escalating from 1.36×107 Mg C in 1989 to 6.16×107 Mg C in 2019. This study provided a set of effective hyperparameters and model of machine learning suitable for subtropical forests and a reference data for improving carbon sequestration capacity of subtropical forests in Lishui City.