Climatic Conditions Research Articles

Modeling of the modern climatic range of <i>Cydalima perspectalis</i> (Lepidoptera, Crambidae) in Eurasia

Modeling of the modern climatic range of a dangerous plant pest of the genus Buxus L. box tree moth Cydalima perspectalis (Walker, 1859) is carried out in order to determine possible territories of its further expansion in Eurasia. Information on the loci of actual C. perspectalis detection both in native (East and South Asia) and invasive (Europe and West Asia) parts of the range was collected from various sources (species distribution databases and publications). Six bioclimatic (three temperature and three humidity) parameters are used as distribution predictors. Original methods for determining the number of pseudo-absence points and their selective generation are developed and applied. The final classification and partitioning of the space of bioclimatic factors is carried out using gradient boosting. The modern Eurasian climatic range of the box tree moth is calculated and mapped. It is shown that the invasion has not yet reached its limits and there are a number of territories in Eurasia where climatic conditions are favorable for the emergence of C. perspectalis populations both in the native part of the range (certain southern and eastern regions of China, the DPRK, the southern foothills of the Himalayas) and in its invasive part (Northern and Eastern Europe, Caucasus, and Turkey). A comparative assessment of the importance of different climatic factors in determining the box tree moth distribution area is given. It has been found out that the sum of the driest month precipitation is of greatest importance for constructing a model of the C. perspectalis climatic range (47.6%). A significant difference in climatic conditions between the native and invasive parts of the range is revealed and assumptions about the possible causes of its occurrence are made.

Impact of climate changes on agroresources of Ukrainian Polissia based on geospatial data

Aim. To determine the patterns of the climate change impact on the transformation of agricultural production and the ecosystem of Ukrainian Polissia in terms of time and space. Methods. Satellite and statistical data for the last 40 years (1982–2022) were used. The mean temperature for the vegetation period was defined by the sum of radiation temperatures of the terrestrial surface, calculated using the data of the infrared range (10.3–11.3; 11.4–12.4 μm) of the high-precision AVHRR radiometer of artificial meteorological Earth's satellites, NOAA, and the precipitation dynamics – using the data of ERA5 ECMWF/Copernicus Climate Change Service. The impact of climate change on the vegetation state and phenological parameters, including the beginning, end, and duration of the vegetation season, was determined by the normalized difference vegetation index (NDVI), obtained using the data of the infrared (0.72–1.1 μm) and red (0.58–0.68 μm) ranges of the AVHRR radiometer on the website of STAR NESDIS NOAA. Crop yields and the dynamics of sown areas were determined by the data from the State Statistics Service of Ukraine. The information about the dynamics of the forest cover was obtained using the Global Forest Watch satellite data. To evaluate the impact of climate change on Ukraine's forests, the investigation was conducted on burnt forest areas, using the MCD64A1 6.1 index, developed on the basis of the MODIS satellite data. Results. According to the satellite data, the radiation temperature of the terrestrial surface during the growing period increased by 2.2 ºС on average in the territory of Ukrainian Polissia over the last 40 years. There is a regional difference in the temperature regime observed in the direction from west to east. In the territory of western Polissia, the increase in the temperature of the terrestrial surface in recent decades was within the range of 1.2–1.6, and in the central and eastern parts – within 2.3–2.9 ºС. Due to the warming, the duration of the growing period was extended by 21–35 days, mostly because of earlier spring onset. There is a descending trend in the average annual precipitation amount down to 20–30 mm, which is especially notable for central and eastern Polissia. The warming was the reason for the introduction of the crops, new for this region, into the structure of sown areas, especially corn and sunflower, which had a generally positive effect on the vegetation state by the NDVI index, which increased from 0.30 in 1982–1992 to 0.36 in 2012–2022 on average. The crop yield increased accordingly, and according to the statistical data for the recent years, amounted to: corn – 7.0–9.5 t/ha, winter wheat – 4.5–5.0, and sunflower – 1.5–2.0 t/ha, which is close to the level of their yield on chornozem. At the same time, due to climate change and the transformation of agricultural activity, there has been a higher risk of deterioration in the ecological state of typical Polissia landscapes, droughts, and soil degradation. According to the results of the analysis of twenty-two years of the dynamics in forest fires, the largest areas of burnt forests were registered in 2012 (694.30 sq.km), 2015 (1,078.81 sq.km), and 2020 (776.27 sq.km), which demonstrated the increase in fires during the recent decade along with the tendency towards longer fire hazard period. Conclusions. The increase in the temperature of the terrestrial surface of the Ukrainian Polissia during the growing period and the lengthening of the growing period created the conditions for corn and sunflower to be introduced into the arable areas, which had a positive impact on the vegetation state index, NDVI. As a result of these transformations both in the sown area of these crops and their yield, Polissia is becoming a new grain-oil belt of Ukraine. Concurrently, there are higher risks associated with maintaining high performance of agroecosystems and the increase in the risks for soil degradation processes, the deterioration of the ecological state of wetlands and forests, as well as drying-out of small rivers and lakes. Balancing the high yield of modern agroecosystems and safe nature management requires systemic measures in adapting the agricultural activity and nature management to new climatic conditions, which requires implementing the management of soil, water, and bio-resources, achieving optimal parameters of fertility for mineral and peaty-swampy soils. Reconstructing current land reclamation systems to optimize water regimes for the agricultural lands and protect typical Polissia ecosystem is needed.

Evaluation of Foxtail Millet Varieties for Thermotolerance at Seedling Stage using Temperature Induction Response Technique (TIR)

In the present scenario of climate change, Foxtail millet is the best crop of choice and an indispensable component of dryland farming due to its C4 plant type and tolerance against the abiotic stresses. However, all the foxtail millet varieties may not sustain under severe temperature stress particularly at germination and seedling growth stages. Therefore, screening of varieties is required to identify the stress tolerant varieties in foxtail millet which can combat temperature stress at seed germination and early seedling growth stages which is the need of the hour under ever changing climatic conditions. Hence, A lab experiment was conducted to standardize the temperature induction response (TIR) protocol for foxtail millet seedlings using WGC-450 programmable plant growth chamber. Temperatures were standardized as sub lethal i.e. challenging temperatures as 38°C – 54°C for 5 hours and lethal temperatures as 56°C for 3 hours. Seven foxtail millet varieties (Suryanandi, SiA 3156, Srilakshmi, SiA 3085, Narasimharaya, Krishnadevaraya and Prasad) were screened for intrinsic tolerance using the standardized Thermo Induced Response (TIR) protocol. Out of the seven varieties evaluated, SiA 3085, Prasad, Suryanandi, Srilakshmi were identified to possess high level of thermo tolerance in terms of higher seedling survival with less reduction in root and shoot growth. The varieties with intrinsic heat tolerance can be explored for the development of heat stress tolerant varieties.

Assessment of Packaging Materials for Bulk Packaging of Mustard

A study was conducted to develop effective bulk packaging solutions for mustard, focusing on testing various packaging materials with liners and analysing shelf life for export purposes. To maintain the quality of spices, it is crucial to have oxygen and gas barrier properties to preserve aroma. To address this, a novel liner combination has been introduced to evaluate its effectiveness in extending the shelf life of mustard. Mustard was packed in nine types of packaging materials selected based on sustainability aspects and subjected to accelerated climatic conditions (38±1°C and 90±2% RH) for six months. Physico-chemical parameters were measured in triplicate. Throughout the exposure period, moisture content and water activity in the mustard increased exponentially. Significant changes in colour, aroma, and microbial growth were observed in samples packaged in PP woven bags without liners and multiwall paper bags. However, no damage to the packaging materials was noted during transport testing. The maximum shelf life was recorded for mustard packed in PP woven bags with liners and multiwall paper bags with aluminium foil. Hence, the results indicated that exploring advanced liner combinations can significantly enhance the shelf life and maintain the quality of mustard.

Horodynamic Mapping of Open Sands in the East of the Stavropol Region

The desertification processes that are dynamically occurring in the north-east of the Stavropol Territory are closely interrelated with climatic conditions, which necessitates the rapid mapping of qualitative changes in the state of open sands in accordance with various scenarios. The mapping was carried out on the basis of the technique of chorodynamic (diachronic) mapping for two periods (July-August 2022 and June-July 2023), data on the monthly dynamics of open sand areas, precipitation and dust storms were used to select time slices. The mapping was carried out visually on the basis of multispectral satellite images of Landsat for each month. In 2022, 14 dust storms were registered, in 2023 none were registered, and days with critical wind speeds were accompanied by heavy precipitation, in connection with which a significant decrease in the visible areas of open sands was revealed as a result of overgrowth. Based on the available data, using overlay operations, schemes of qualitative transitions in the test area (part of the Levokumsky district) corresponding to qualitative transitions in the “dry” and “wet” scenarios were compiled. Despite the progressive overgrowth of the sands, stimulated by the absence of dust storms and abundant precipitation in 2023, starting from areas with the lowest sediment capacity, the restoration of the original plant communities without carrying out phytomeliorative measures is extremely unlikely due to high anthropogenic load and seed desertification, as a result of which low-value annual crops grow on open sands (weed solyanka, kumarchik, nightshade horned, etc.).

Morphological variability and vitality of Rindera tetraspis (Boraginaceae) in the South Urals and Western Kazakhstan

Population studies of Rindera tetraspis Pall., a rare endemic species of the steppe zone of the European part of Russia and Kazakhstan, were carried out. The study of the habitats of 11 populations in the Orenburg Region and the Republic of Kazakhstan has shown that the species is confined to various variants of calciphyte steppes on chalk substrates or sandstones. In terms of most morphometric indicators, the northern coenopopulation “Rodnichny” is the leader; the minimum values are noted in the coenopopulation “Verkhnechebendinskie Chalk Mountains, northern extremity”. The discriminant analysis has revealed morphostructural differences between individuals from the majority of coenopopulations. In terms of vitality, four coenopopulations are prosperous, seven ones are depressed. The optimal conditions for the species growth are in the northern part of its range, in more favorable climatic conditions in terms of temperature and humidity, mainly on soils of sand origin. When moving southward, a decrease in size parameters of individuals is observed, associated with insufficient moisture, while their morphological diversity increases. The state of R. tetraspis coenopopulations is stable, but the species is not provided with proper protection measures, so further monitoring of its habitats and improvement of conservation measures are necessary.

Adaptive Agronomic Strategies for Enhancing Cereal Yield Resilience Under Changing Climate in Poland

Climate-driven changes have raised concerns about their long-term impacts on the yield resilience of cereal crops. This issue is critical in Poland as it affects major cereal crops like winter triticale, spring wheat, winter wheat, spring barley, and winter barley. This study investigates how soil nutrient profiles, fertilization practices, and crop management conditions influence the yield resilience of key cereal crops over a thirteen-year period (2009–2022) in the context of changing climate expressed as varying Climatic Water Balance. Data from 47 locations provided by the Research Centre for Cultivar Testing were analyzed to assess the combined effects of agronomic practices and climate-related water availability on crop performance. Yield outcomes under moderate and enhanced management practices were contrasted using Classification and Regression Trees to evaluate the relationships between yield variations and agronomic factors, including soil pH, nitrogen, phosphorus, potassium fertilization, and levels of phosphorus, potassium, and magnesium in the soil. The study found a downward trend in Climatic Water Balance, highlighting the increasing influence of climate change on regional water resources. Crop yields responded positively to increased agricultural inputs, especially nitrogen. Optimal soil pH and medium phosphorus levels were identified as crucial for maximizing yield. The findings underscore the importance of tailored nutrient management and adaptive strategies to mitigate the adverse effects of climate variability on cereal production. The results provide insights for field crop research and practical approaches to sustain cereal production in changing climatic conditions.

Climate change mitigation and adaptation for rice-based farming systems in the Red River Delta, Vietnam

Abstract Background Rice is a major contributor to anthropogenic greenhouse gas (GHG) emissions, primarily methane, and at the same time will be negatively impacted by regional climate changes. Identifying rice management interventions to reduce methane emissions while improving productivity is, therefore, critical for climate change mitigation, adaptation, and food security. However, it can be challenging to conduct multivariate assessments of rice interventions in the field owing to the intensiveness of data collection and/or the challenges in testing long-term changes in meteorological and climate conditions. Process-based modeling, evaluated against site-based data, provides an entry point for evaluating the impacts of climate change on rice systems and assessing the impacts, co-benefits, and trade-offs of interventions under historical and future climate conditions. Methods We leverage existing site-based management data to model combined rice yields, methane emissions, and water productivity using a suite of process-based coupled crop-soil model experiments for 83 growing sites across the Red River Delta, Vietnam. We test three rice management interventions with our coupled crop-soil model, characterized by Alternate Wetting and Drying (AWD) water management and other principles representing the System of Rice Intensification (SRI). Our simulations are forced with historical as well as future climate conditions, represented by five Earth System Models for a high-emission climate scenario centered on the year 2050. We evaluate the efficacy of these interventions for combined climate change mitigation and adaptation under historical and future climate change. Results Two SRI interventions significantly increased yields (one by over 50%) under historical climate conditions while also reducing (or not increasing) methane emissions. These interventions also increase yields under future climate conditions relative to baseline management practices, although climate change decreases absolute yields across all management practices. Generally, where yield improved, so did crop water-use efficiency. However, impacts on methane emissions were mixed across the sites under future climate conditions. Two of the interventions resulted in increased methane emissions, depending on the baseline management point of comparison. Nevertheless, one intervention reduced (or did not significantly increase) methane under both historical and future climate conditions and relative to all baseline management systems, although there was considerable variation across five selected climate models. Conclusions SRI management principles combined with high-yielding varieties, implemented for site-specific conditions, can serve climate change adaptation and mitigation goals, although the magnitude of future climate changes, particularly warming, may reduce the efficacy of these interventions with respect to methane reductions. Future work should better bracket important sensitivities of coupled crop-soil models and disentangle which management and climate factors drive the responses shown. Furthermore, future analyses that integrate these findings into socio-economic assessment can better inform if and how SRI/AWD can potentially benefit farmer livelihoods now and in the future, which will be critical to the adoption and scaling of these management principles.

Enhancing water security through advanced modeling: integrating deep learning and a novel metaheuristic optimization algorithm for accurate pan evaporation prediction

ABSTRACT This study evaluates and enhances machine learning models for predicting pan evaporation under diverse climatic conditions. Five fundamental machine learning models were employed and tested across four different stations. Subsequent comparisons were made with advanced techniques, including long short-term memory (LSTM) networks. An innovative approach was introduced, combining LSTM with Binary Al-Biruni Earth Radius (BER–LSTM). This hybrid method was benchmarked against other optimization techniques. The BER–LSTM model consistently outperformed other models across all stations and time scales, achieving up to a 97.54% improvement in root mean square error (RMSE) compared to standard LSTM on daily time scales. Compared to simpler models like Multilayer Perceptron and Support Vector Regressor, BER–LSTM showed even more substantial improvements, with up to a 99.03% reduction in RMSE. The BER–LSTM model demonstrates superior predictive capabilities for pan evaporation across varied climatic conditions, offering significant improvements over both traditional and advanced machine learning techniques. This approach shows promise for enhancing evaporation forecasting in diverse environmental contexts.

Carcinogenic and non-carcinogenic health risk assessment of river Ganges in different climatic conditions and regions of Uttarakhand, India

Carcinogenic and non-carcinogenic health risk assessment of river Ganges in different climatic conditions and regions of Uttarakhand, India

Cooling peak load reduction potential of ventilated slabs: a numerical study

Thermally activated building systems provide an effective method to combine thermal inertia and HVAC systems, and can be used to promote comfortable indoor conditions in summer. Ventilated slabs (VS) use supply air flow directly for heating or cooling, without the need for separate auxiliary systems. This paper proposes a detailed model of an office building equipped with VS under three different climatic conditions during one month in the summer. A Model Predictive Controller and a Genetic Algorithm, developed in MATLAB, are subsequently implemented to reduce energy consumption of the system while maintaining the room temperature set point. The outcomes of both short and extended sequences are presented after conducting modelling considerations. The dynamic behaviour of the room is highlighted, while the cooling demand is further evaluated using statistical indexes. The reduction in peak cooling load was noted in all instances, including during outdoor conditions that are unfavourable to free cooling strategies.

The Origin and Geography of Brown Forest Soils

Brown soils, Brown forest soils, Burozems or Cambisols have been studied for more than 100 years, and to this day, their nature, origin and process organization remain controversial. In addition, issues of their geography are quite controversial, especially in such a large country as Russia. A brief review of the literature on the morphological diversity features of the genesis and origin of brown soils in the various geographical locations of Eurasia is given. It was shown that the genesis of brown soils is not as closely related to the type of forest vegetation as previously thought, although, at the same time, the vast majority of brown soils are forest soils. Depending on the geographic situation and local climatic and geogenic conditions, Brown forest soils have related subtypes among adjacent soil types in different natural zones. Thus, in the polar zone, they are close to Entic Podzols, in the subtropics to Cinamonic soil, and in the forest-steppe, they replace zonal Retisols in positions with a relatively less contrasting and even climate. Being to a certain extent intrazonal soils, brown soils are combined with other more intrazonal soils—Rendzinas—and form the so-called Burozem-Rendzinas on uplands, composed of carbonate rocks in various natural zones. The article is illustrated with original photographs of Brown forest soils from various natural zones, taken by the author during numerous expeditions. It has been established that Burozems combine the characteristics of intrazonal soil, which is inherent in all natural zones, and have elements of zonal soils, as well as adjacent intrazonal soils in invariant combinations of soil-forming factors. From this, two conclusions can follow about their further classification fate: a more thorough justification for an independent soil type or a classification of structural metamorphism and in situ transformation of minerals among various existing zonal soil types.

Seasonal and annual trends in reference evapotranspiration and prediction using machine learning models across seven climatic zones of Bangladesh

ABSTRACT The primary aim of this investigation is to examine the historical (1989–2020) and future trends and magnitude of Reference Evapotranspiration (ET0) in terms of spatiotemporal measures, considering its significance as a hydro-meteorological parameter influenced by changing climate. The FAO-56 Penman-Monteith method is employed to analyze ET0, while the Modified Mann Kendall test is utilized to assess trends and Sen’s Slope Estimator is used for magnitude analysis. The future prediction is conducted using Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest (RF) models. Results show an increasing ET0 trend annually in the southeastern and northeastern zones, while decreased values are observed in other regions, particularly in the northwest (0.83 mm). Sen’s slope estimator reveals distinct fluctuations in ET0, with notable disparities in the Southeastern, Northeastern, Southwestern, and South-Central zones. Notably, Chattogram and Sitakunda experience an ET0 magnitude of 0.02 mm/Year, while other zones show a magnitude of 0.01 mm/Year. SVM outperformed other models, predicting rising ET0 in various seasons. These findings offer insights for optimizing irrigation systems and sustainable water management under changing climatic conditions.

Distinct impacts of the El Niño–Southern Oscillation and Indian Ocean Dipole on China's gross primary production

Abstract. Gross primary production (GPP), a crucial component in the terrestrial carbon cycle, is strongly influenced by large-scale circulation patterns. This study explores the influence of the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on China's GPP, utilizing long-term GPP data generated by the Boreal Ecosystem Productivity Simulator (BEPS). Partial correlation coefficients between GPP and ENSO reveal substantial negative associations in most parts of western and northern China during the September–October–November (SON) period of ENSO development. These correlations shift to strongly positive over southern China in December–January–February (DJF) and then weaken in March–April–May (MAM) in the following year, eventually turning generally negative over southwestern and northeastern China in June–July–August (JJA). In contrast, the relationship between GPP and IOD basically exhibits opposite seasonal patterns. Composite analysis further confirms these seasonal GPP anomalous patterns. Mechanistically, these variations are predominantly controlled by soil moisture during ENSO events (except MAM) and by temperature during IOD events (except SON). Quantitatively, China's annual GPP demonstrates modest positive anomalies in La Niña and negative IOD years, in contrast to minor negative anomalies in El Niño and positive IOD years. This outcome is due to counterbalancing effects, with significantly larger GPP anomalies occurring in DJF and JJA. Additionally, the relative changes in total GPP anomalies at the provincial scale display an east–west pattern in annual variation, while the influence of IOD events on GPP presents an opposing north–south pattern. We believe that this study can significantly enhance our understanding of specific processes by which large-scale circulation influences climate conditions and, in turn, affects China's GPP.

Green Infrastructure Mapping in Almeria Province (Spain) Using Geographical Information Systems and Multi-Criteria Evaluation

Green infrastructure (GI) is increasingly prioritised in landscape policy and planning due to its potential to benefit ecosystems and enhance wildlife conservation. However, due to the uneven distribution of protected areas (PAs) and the fragmentation of habitats more generally, multi-level policy strategies are needed to create an integrated GI network bridging national, regional and local scales. In the province of Almeria, southeastern Spain, protected areas are mainly threatened by two land use/land cover changes. On the one hand, there is the advance of intensive greenhouse agriculture, which, between 1984 and 2007, increased in surface area by more than 58%. On the other hand, there is the growth of artificial surfaces, including urban areas (+64%), construction sites (+194%) and road infrastructures (+135%). To address this challenge, we present a proposal for green infrastructure deployment in the province of Almeria. We combine Geographic Information Systems (GISs) and multi-criteria evaluation (MCE) techniques to identify and evaluate suitability for key elements to be included in GI in two key ways. First, we identify the most suitable areas to form part of the GI in order to address vulnerability to degradation and fragmentation. Second, we propose 15 ecological corridors connecting the 35 protected areas of the province that act as core areas. The proposed GI network would extend along the western coast of the province and occupy the valleys of the main rivers. The river Almanzora plays a leading role. Due to its remoteness from the coast and its climatic conditions, it has not attracted intensive greenhouse agriculture and urban development, the main drivers of the transformation and fragmentation of traditional land uses. Around 50% of the area occupied by the proposed corridors would be located in places of medium and high suitability for the movement of species between core areas.

Investigating Genetic Diversity and Correlations Between Mineral Concentration and Neurotoxin (β-ODAP) Content in the Lathyrus Genus

Grass pea (Lathyrus sativus L.) is a nutritious legume crop well-adapted to fragile agro-ecosystems that can survive under challenging climatic conditions. The cultivation of grass pea faces stigma primarily due to the presence of β-N-Oxalyl-L-α, β-diaminopropionic acid (β-ODAP), which is associated with a risk of inducing neurolathyrism upon prolonged consumption of its grains as a staple diet. The grass pea improvement program of the International Center for Agricultural Research in the Dry Areas (ICARDA) aims to reduce β-ODAP content to a safe level along with improving yield potential and nutritional quality of grass pea. In this study, 183 germplasm accessions representing 13 different Lathyrus species and 11 L. sativus breeding lines were evaluated for β-ODAP content based on Rao protocol and mineral concentration using ICP-OES. Significant variability was observed among the accessions for the studied traits. The results showed low β-ODAP content and high mineral concentration in 25 accessions of crop wild relatives, which included L. cicera, L. ochrus, and L. cassius, with one accession IG65277 of L. cassius, in addition to two lines, IG117034 and ACC1335, of L. sativus having very low β-ODAP content. Furthermore, some accessions of L. pseudocicera, L. aphaca, L. cicera, L. marmoratus, L. gorgoni, and L. tingitanus also showed low β-ODAP content. The results showed significant positive correlations among different trait combinations, viz., K and P (r = 0.193 ***), K and Fe (r = 0.177 ***), Mn and Fe (r = 0.210 ***), Mn and Se (r = 0.137 ***), β-ODAP and Mg (r = 0.158 **), and β-ODAP and Ca (r = 0.140 **). L. cicera, L. ochrus, and L. cassius were identified as a great source for improving the mineral concentration and reducing β-ODAP content in the cultivated grass pea.

Host influence on life history traits of Ceratitis capitata Wiedemann in an arid region of Argentina.

The fruit fly Ceratitis capitata is a successful generalist due to the trade-off between different variables in its life history traits. The present study aimed to assess some life history traits of C. capitata recovered from peach, plum and fig, three key host species, under the climatic conditions of an irrigation oasis in the arid province of San Juan, Argentina. Pupal abundance, sex ratio and morphometric parameters such as pupal and adult weight, pupal volume, wingspan and head-caudal length were influenced by the host in which the larvae were reared. Sexual maturity, measured as the peak of calling (pheromone emission), was homogeneous on the sixth and seventh days after emergence, but males recovered from fig showed early calling activity on the third day after emergence. The plasticity of C. capitata to adapt its life history traits to specific nutrient variations within the larval environment allows it to colonise and establish populations where key hosts, as those studied here, are available. The knowledge of the interactions between host fruit trees and C. capitata populations provides helpful information for planning the management of local orchards and urban fruit plantations within irrigation oases, taking into consideration the concept of key hosts as peach and fig.

Astronomical Representations and Shamanism in the Rock Art of the Semi-Arid North of Chile

This paper describes rock art sites in Cerro La Silla and Cerro Pachón, two hills in the semi-arid north of Chile thought to be associated with the El Molle cultural complex of 300 BC–800 AD. The geographic and climatic conditions in this area make it propitious for observing the sky, and the rock art is adjacent to modern observatories. Analysis of the local geography, motifs, themes and orientations of these symbolically charged locations demonstrates links between the sites and cultural expression relating to observation of nature and the sky in the context of a shamanic cult of the mountains.

Development and Evaluation of Machine Learning Models for Air-to-Land Temperature Conversion Using the Newly Established Kunlun Mountain Gradient Observation System

Mountainous land types are characterized by a scarcity of observational data, particularly in remote areas such as the Kunlun Mountains, where conventional Automatic Weather Stations (AWSs) typically do not record land surface temperature (LST) data. This study aims to develop and evaluate models for converting air temperature (TA) to LST using newly established meteorological station data from the Kunlun Mountain Gradient Observation System, thereby providing time-continuous LST data for AWSs. We constructed a conceptual model to explore the relationship between 1.5 m TA and LST and instantiated it using three machine learning algorithms: Support Vector Machine (SVR), Convolutional Neural Network (CNN), and CatBoost. The results demonstrated that the CatBoost algorithm outperformed the others under complex terrain and climatic conditions, achieving a coefficient of determination (R2) of 0.997 and the lowest root mean square error (RMSE) of 0.627 °C, indicating superior robustness and accuracy. Consequently, CatBoost was selected as the optimal model. Additionally, this study analyzed the spatiotemporal distribution characteristics of cloud cover in the Kunlun Mountain region using the MOD11A1 product and assessed the uncertainties introduced by the 8-day average compositing method of the MOD11A2 product. The results revealed significant discrepancies between the monthly average LST derived from polar-orbiting satellites and the hourly composite monthly LST measured on-site or under ideal cloud-free conditions. These differences were particularly pronounced in high-altitude regions (4000 m and above), with the greatest differences occurring in winter, reaching up to 10.2 °C. These findings emphasize the importance of hourly LST calculations based on AWSs for accurately assessing the spatiotemporal characteristics of LST in the Kunlun Mountains, thus providing more precise spatiotemporal support for remote sensing applications in high-altitude regions.

Sustainable Development Strategies and Good Agricultural Practices for Enhancing Agricultural Productivity: Insights and Applicability in Developing Contexts—The Case of Angola

In general, agricultural productivity in Angola is low due to the limited awareness among stakeholders regarding sustainable development strategies (DSs) and good agricultural practices (GAPs) that could be adjusted to local crops, soil types, and climatic conditions. A structured approach was followed to develop a systematic literature review (SLR) that can address this gap by examining how DSs and GAPs may be adapted for Angola’s context to encourage sustainable agricultural development. Key steps included the selection and exclusion of literature from primary scientific databases based on specific screening indicators such as the publication date, language, relevance to DSs and GAPs, and geographic focus on developing or developed nations with comparable agricultural challenges. The initial search resulted in 11,392 articles, of which 4257 met the primary selection criteria. After further screening for relevance and availability, 98 articles were shortlisted, and 15 studies were ultimately included for in-depth analysis. This strict screening process ensured the inclusion of studies most applicable to Angola’s agricultural context. The key research findings indicate that certain DSs and GAPs have high adaptability potential for Angola. The findings emphasise practices such as drip irrigation and inorganic fertilisation, which are widely implemented in both developed and developing countries due to their efficiency in resource-limited environments. Additional strategies, such as water management systems, organic composting, and agroforestry practices, demonstrate significant potential to enhance soil fertility, water efficiency, and crop resilience against climate variability. By identifying these practices and strategies, this study provides a basic framework for policymakers in Angola to develop targeted implementation guidelines, fostering sustainable agricultural growth and resilience in the face of climatic challenges. Thus, this review contributes to the scientific and practical understanding of sustainable agriculture in developing countries, offering critical insights that support Angola’s efforts to achieve greater self-sufficiency and economic stability through sustainable agricultural practices.