Search Results (167)

The Caucasus region, characterized by its complex topography and diverse climatic regimes, exhibits pronounced spatial variability in temperature and precipitation patterns. This study investigates the seasonal behavior of air temperature, precipitation, vertical temperature gradients, and inversion phenomena across distinct landscape types using observational data from 63 meteorological stations for 1950–2022. Temperature trends were analyzed using linear regression, while vertical lapse rates and inversion layers were assessed based on seasonal temperature–elevation relationships. Precipitation regimes were evaluated through Mann-Kendall trend tests and Sen’s slope estimators. Results reveal that temperature regimes are strongly modulated by landscape type and elevation, with higher thermal variability in montane and subalpine zones. Seasonal temperature inversions are most frequent in spring and winter, especially in western lowlands and enclosed valleys. Precipitation patterns vary markedly across landscapes: humid lowlands show autumn–winter maxima, while arid and semi-arid zones peak in spring or late autumn. Some landscapes exhibit secondary maxima and minima, influenced by Mediterranean cyclones and regional atmospheric stability. Statistically significant trends include increasing cool-season precipitation in humid regions and decreasing spring rainfall in arid areas. These findings highlight the critical role of topography and landscape structure in shaping regional climate patterns and provide a foundation for improved climate modeling, ecological planning, and adaptation strategies in the Caucasus. Full article

In water-scarce regions, natural ecosystems and agriculture increasingly compete for limited water resources, intensifying stress during periods of drought. To assess these competing demands, we applied a modified PT-JPL model that incorporates the thermal inertial approach as a substitute for relative humidity (RH) in estimating soil evaporation—a method that significantly outperforms the original PT-JPL formulation in Mediterranean semi-arid irrigated areas. This remote sensing framework enabled us to quantify spatial and temporal variations in water use across both natural and agricultural systems within the UNESCO World Heritage site of Doñana. Our analysis revealed an increasing evapotranspiration (ET) trend in intensified agricultural areas and rice fields surrounding the National Park (R = 0.3), contrasted by a strong negative ET trend in wetlands (R < −0.5). These opposing patterns suggest a growing diversion of water toward irrigation at the expense of natural ecosystems. The impact was especially marked during droughts, such as the 2011–2016 period, when precipitation declined by 16%. In wetlands, ET was significantly correlated with precipitation (R > 0.4), highlighting their vulnerability to reduced water inputs. These findings offer crucial insights to support sustainable water management strategies that balance agricultural productivity with the preservation of ecologically valuable systems under mounting climatic and anthropogenic pressures typical of semi-arid Mediterranean environments. Full article

Wildfires, whether natural or human-caused, significantly alter soil properties and increase soil erosion susceptibility, particularly through changes in rill detachment capacity (Dc). This study aimed to evaluate the influence of fire intensity on key soil properties and to recognize their relationships with Dc under controlled laboratory conditions. The research was conducted in the Darestan Forest, Guilan Province, northern Iran, a region characterized by a Mediterranean semi-arid climate. Soil samples were collected from three fire-affected conditions: unburned (NF), low-intensity fire (LF), and high-intensity fire (HF) zones. A total of 225 soil samples were analyzed using flume experiments at five slope gradients and five flow discharges, simulating rill erosion. Soil physical and chemical characteristics were measured, including hydraulic conductivity, organic carbon, sodium content, bulk density, and water repellency. The results showed that HF soils significantly exhibited higher rill detachment capacity (1.43 and 2.26 times the values compared to the LF and NF soils, respectively) and sodium content and lower organic carbon, hydraulic conductivity, and aggregate stability (p < 0.01). Strong correlations were found between Dc and various soil properties, particularly a negative relationship with organic carbon. The multiple linear equation had good accuracy (R² > 0.78) in predicting rill detachment capacity. The findings of the current study show the significant impact of fire on soil degradation and rill erosion potential. The study advocates an urgent need for effective post-fire land management, erosion control, and the development of sustainable soil restoration strategies. Full article

The increasing global demand for resilient, sustainable agricultural systems has intensified the need for advanced monitoring strategies, particularly for climate-adaptive crops such as Moringa oleifera Lam. This study presents an integrated approach using Unmanned Aerial Vehicles (UAVs) equipped with multispectral and thermal cameras to monitor the vegetative performance and determine the optimal harvest period of four M. oleifera genotypes in a Mediterranean environment. High-resolution data were collected and processed to generate the NDVI, canopy temperature, and height maps, enabling the assessment of plant vigor, stress conditions, and spatial canopy structure. NDVI analysis revealed robust vegetative growth (0.7–0.9), with optimal harvest timing identified on 30 October 2024, when the mean NDVI exceeded 0.85. Thermal imaging effectively discriminated plant crowns from surrounding weeds by capturing cooler canopy zones due to active transpiration. A clear inverse correlation between NDVI and Land Surface Temperature (LST) was observed, reinforcing its relevance for stress diagnostics and environmental monitoring. The results underscore the value of UAV-based multi-sensor systems for precision agriculture, offering scalable tools for phenotyping, harvest optimization, and sustainable management of medicinal and aromatic crops in semiarid regions. Moreover, in this study, to produce M. oleifera leaf powder intended for use as a food ingredient, the leaves of four M. oleifera genotypes were dried, milled, and evaluated for their hygiene and safety characteristics. Plate count analyses confirmed the absence of pathogenic bacterial colonies in the M. oleifera leaf powders, highlighting their potential application as natural and functional additives in food production. Full article

In this study, we selected a series of pothole wetlands to investigate their nucleation, evolution, and recent anthropogenic degradation in the Alcores Depression (AD), southern Iberian Peninsula, where over 100 closed watersheds containing shallow, ephemeral water bodies up to 2 hm² have been identified. We surveyed the regional geological framework, utilized digital elevation models (DEMs), orthophotos, and aerial images since 1956. Moreover, we analyzed precipitation and temperature data in Seville from 1900 to 2024, collected hydrometeorological data since 1990 and modelled the water level evolution from 2002 to 2025 in a representative pothole in the area. Our observations indicate a flooded surface reduction by more than 90% from the 1950s to 2025. Climatic data reveal an increase in annual mean temperatures since 1960 and a sharp decline in annual precipitation since 2000. The AD’s inception due to tectonic isolation during the Quaternary favoured the formation of pothole wetlands in the floodplain. The reduction in the hydroperiod and wetland degradation was primarily due to agricultural expansion since 1950, which followed an increase in groundwater extraction and altered the original topography. Recently, decreased precipitation has exponentially accelerated the degradation and even the complete disappearance of many potholes. This study underscores the fragility of small wetlands in the Mediterranean basin and the critical role of human management in their preservation. Restoring these ecosystems could be a highly effective nature-based solution, especially in semi-arid climates like southern Spain. These prairie potholes are crucial for enhancing groundwater recharge, which is vital for maintaining water availability in regions with limited precipitation. By facilitating rainwater infiltration into the aquifer, recharge potholes increase groundwater levels. Additionally, they capture and store run-off during heavy rainfall, reducing the risk of flooding and soil erosion. Beyond their hydrological functions, these wetlands provide habitats that support biodiversity and promote ecological resilience, reinforcing the need for their protection and recovery. Full article

Semi-Mediterranean (SM) and semi-arid (SA) regions, exemplified by the Kurdo-Zagrosian forests in western Iran and northern Iraq, have experienced frequent wildfires in recent years. This study proposes a modified Non-Negative Matrix Factorization (NMF) method for detecting fire-prone areas using satellite-derived data in SM and SA forests. The performance of the proposed method was then compared with three other already proposed NMF methods: principal component analysis (PCA), K-means, and IsoData. NMF is a factorization method renowned for performing dimensionality reduction and feature extraction. It imposes non-negativity constraints on factor matrices, enhancing interpretability and suitability for analyzing real-world datasets. Sentinel-2 imagery, the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and the Zagros Grass Index (ZGI) from 2020 were employed as inputs and validated against a post-2020 burned area derived from the Normalized Burned Ratio (NBR) index. The results demonstrate NMF’s effectiveness in identifying fire-prone areas across large geographic extents typical of SM and SA regions. The results also revealed that when the elevation was included, NMF_L1/2-Sparsity offered the best outcome among the used NMF methods. In contrast, the proposed NMF method provided the best results when only Sentinel-2 bands and ZGI were used. Full article

Viticulture contributes significantly to Chile’s exports and GDP. However, the development and productivity of grapevines is threatened by climate change. Grapevines are grown in diverse regions; thus, adaptable tools for evaluating climate risk at the local level are required. In this study, a local climate risk index (LCRI) was developed to assess the vulnerability of Chilean viticulture (wine, table, and pisco grapes) in the current (2017–2024) and future (2046–2065) periods. Various components, including exposure, sensitivity, and adaptive and response capacities, were analyzed using different indicators based on municipal-level information. The results for the current period indicated that most municipalities were at medium risk, whereas future projections showed a marked increase in climate risk, principally due to changes in climate suitability. In the current period, the highest LCRI values were observed in semi-arid and mediterranean zones, particularly in the northern regions of Atacama and Coquimbo; in the future period, this situation intensified. In contrast, the lowest values in the current period occurred in the Maule region and further south, where the climate transitions from mediterranean to temperate conditions, and in the future period, valley and mountainous areas presented improvements in the index. Some municipalities showed improvement or stability with local adaptation efforts. The results highlight the urgent need for region-specific adaptation policies that prioritize water management, infrastructure, and increased capacities. Full article

The fig (Ficus carica L.) is one of the oldest fruit crops cultivated in arid and semi-arid regions, valued for both its nutritional and economic importance; thus, ensuring sustainable fig production under climate change conditions is very important, as water scarcity increasingly affects fruit quality and production. Selecting and preserving resilient varieties among traditional varieties, representing centuries of local adaptation, is a vital strategy for addressing the challenges driven by climate change. In this context, this study assessed the physiological and biochemical parameters of the leaves of four fig landrace varieties (Fassi, Ghouddane, Nabout, and Ounq Hmam) grown in three different Mediterranean transitional zones of northern Morocco (Chefchaouen, Taounate, and Taza), during a single timepoint assessment conducted in late August 2023. The combined effects of location, variety, and their interactions on chlorophyll fluorescence (F_v/F_m), Soil Plant Analysis Development (SPAD) index, total chlorophyll content (ChlT), canopy temperature depression (CTD), proline content, protein content, total soluble sugar (TSS), hydrogen peroxide (H₂O₂), and malondialdehyde (MDA) were determined. Significant variation was observed among varieties and locations, with the location effect being observed for proline content, protein content, TSS, CTD, and ChlT, while variety had a stronger influence on SPAD, F_v/F_m, H₂O₂, and MDA. The results showed that Nabout and Ounq Hmam varieties had the greatest photosynthetic efficiency, as indicated by their elevated SPAD index, ChlT, and F_v/F_m values, and showed lower sensitivity to oxidative stress (low proline content, H₂O₂, and MDA levels). In contrast, Ghouddane and Fassi displayed better stress tolerance, presenting higher levels of oxidative stress markers. Among locations, Chefchaouen showed the highest protein, TSS, H₂O₂, and MDA levels, reflecting active stress tolerance mechanisms. These variations were confirmed by principal component analysis, which revealed a clear separation between photosynthetically efficient varieties (Nabout and Ounq Hmam) and stress-tolerant varieties (Ghouddane and Fassi). More than a conventional crop physiology study, this work highlights the adaptive strategies in traditional Mediterranean fig germplasm that could be crucial for climate change adaptation. While our findings are limited to a single season, they offer valuable, practical insights that can inform grower decision-making in the near term, especially when considered alongside local knowledge and additional research. Full article

In some estuaries, low inflow and/or isolation from the ocean can result in evapoconcentration and hypersalinity (≥40 ppt). This can create osmoregulatory and energetic challenges for the faunal community, leading to reductions in diversity as more species pass their thresholds. As climate change is increasing the magnitude and duration of hypersaline conditions, we used benthic macroinvertebrate data from 12 estuaries across a Mediterranean climatic region (southwestern Australia) to assess the influence of salinity (0–122 ppt) on the invertebrate fauna. Taxa richness and diversity were highest in salinities between 0 and 39 ppt, peaking at salinities closest to seawater, while total density peaked at 40–49 ppt. Beyond 50 ppt, these measures declined significantly. Community composition changed markedly along the salinity gradient. In lower salinities, communities were diverse, comprising polychaetes, malacostracans, hexapods, ostracods, bivalves, and gastropods. However, in salinities ≥50 ppt, many taxa declined, leading to communities dominated by polychaetes (mainly Capitella spp.) and hexapods (mostly larval chironomids). At 90 ppt, only polychaetes and hexapods remained, and at ≥110 ppt, only the latter taxon persisted. This faunal shift towards insect dominance in hypersaline conditions mirrors observations in other Mediterranean and arid/semi-arid regions, with the resulting communities resembling saline wetlands or salt lakes. This loss of invertebrates can substantially impact ecosystem functioning and trophic pathways, and the findings of this study provide a basis for predicting how these communities will respond to increasing hypersalinity driven by climate change. Full article

The preservation of historic irrigation infrastructure is vital for sustainable water management, especially in regions grappling with rural depopulation, land degradation, and wildfire risk. This study presents a rehabilitation framework for the Acequia del Diablo (Teruel, Spain), a centuries-old gravity-fed canal that supported 60 hectares of agriculture and contributed to ecological connectivity. Its deterioration—following landslides in 1992 and water source loss in 2020—has led to land abandonment, biodiversity decline, and increased wildfire vulnerability. The proposed solution, centered on restoring the original intake at the Azud de Fonseca and stabilizing damaged sections, reestablishes water autonomy and integrates heritage conservation into water governance. A multi-criteria analysis identified this gravity-based alternative as the most technically, economically, and environmentally viable. Drawing from precedents in the literature, the conservation and rehabilitation of historical irrigation systems play a crucial role in sustainable water management in rural areas; this initiative offers a replicable model for other Mediterranean and semi-arid areas. However, challenges include engineering complexity in unstable terrain, administrative delays, and long-term maintenance. Despite these, this intervention enhances rural resilience, wildfire prevention, and biodiversity, while aligning with circular economy principles and European Green Deal objectives. Full article

Protostrongylid nematodes (small lungworms) are very common in Mediterranean sheep and have long been recorded in North Africa. Here, the following four species are found: Muellerius capillaris, Neostrongylus linearis, Cystocaulus ocreatus, and Protostrongylus rufescens. Previous risk factors studies for protostrongylids have been conducted in a single farm and therefore have limitations. Sixty-one meat sheep farms in north-eastern Algeria were surveyed for protostrongylid infection and anthelmintic treatment in late autumn/early winter. The climates of the nine regions ranged from subhumid to arid for humidity and from mild to cool for winter temperature. The highest infection, estimated by the number of larvae per gram of faeces (LPG), was found in subhumid and semi-arid climates. The Rembi breed was more infected than the Ouled Djellal or their crosses. LPG decreased with increasing number of treatments. The latter was also associated with an increased percentage of M. capillaris and a decrease in species diversity. The anthelmintic regimen (ivermectin, levamisole, and albendazole) directly targets gastrointestinal nematodes and indirectly protostrongylids. The use of effective drugs targeting protostrongylids at key moments may provide more effective control. Full article

Young vegetative quinoa (YVQ) has gained attention as a high-protein leafy crop for human consumption with potential for cultivation in Mediterranean and semiarid regions. We investigated the effects of inter-row spacing and genotype on YVQ fresh and dry matter (DM) yield, protein content (PC), and protein yield during summer cultivation in northern Israel in two separate, independent, randomized field experiments over two consecutive years (2020–2021). We hypothesized that row spacing and genotypic differences would significantly impact yield and PC. Inter-row spacing significantly affected plant density, ranging from 55 to 366 plants m⁻². Fresh and DM yields ranged from 4957 to 28,469 kg ha⁻¹ and 661 to 3737 kg DM ha⁻¹, respectively. PC ranged from 20.5 to 26.6% and was not significantly influenced by row spacing. Total protein yield ranged from 147 to 884 kg ha⁻¹. Among the five tested genotypes, no significant differences were observed in fresh (7477–17,776 kg ha⁻¹) or dry (1122–2199 kg DM ha⁻¹) biomass, PC (21.2–26.5%), or protein yield (260–579 kg ha⁻¹), suggesting limited genetic differentiation under the specific environmental and agronomic conditions tested. Amino acid analysis confirmed the presence of all nine essential amino acids, fulfilling over 30% of the recommended daily intake per 100 g DM. These findings highlight YVQ as a promising, sustainable, and protein-rich leafy crop for Mediterranean agriculture. Further research should explore multi-harvest potential, mechanical weeding, and optimized agronomic practices for commercial-scale production. Full article

Micronutrient malnutrition, often caused by the low bioavailability of zinc (Zn) and selenium (Se) in soil, poses serious health risks worldwide. To address these deficiencies, this study evaluated the efficacy of combined Se and Zn fertilization in durum wheat (Triticum durum) through a two-year field experiment conducted under semi-arid Mediterranean conditions. The experimental design was a split-split-plot, considering the growing season (2017/18 and 2018/19) as the main plot, an initial soil application of Zn (50 kg ZnSO₄-7H₂O ha⁻¹ vs. no Zn) as the subplot, and different foliar treatments as the sub-subplot factor: no application (0F), 10 g Se ha⁻¹ (SeF), 8 kg ZnSO₄-7H₂O ha⁻¹ (ZnF), and a combination of ZnF + SeF. While Zn soil application resulted in a 16% increase in both grain and straw yields, the combined Zn and Se foliar application resulted in a significant 15% increase in grain yield, as well as for the highest concentrations of Zn (by 1.44- and 7.38-fold in grain and straw, respectively) and Se (by 3.41- and 4.41-fold in grain and straw, respectively). These results indicate that durum wheat is a promising crop for biofortification initiatives that could contribute to reducing Zn and Se deficiencies in human diets and livestock feed in the Mediterranean region. Full article

Thornthwaite’s water balance approach serves as a fundamental tool for assessing hydrological dynamics, particularly in regions vulnerable to aridity and water stress. This study evaluates the performance of gridded datasets in estimating Thornthwaite’s water balance attributes in Greece, leveraging climatic averages of the period 1960–1997. Ground station data from 91 meteorological sites and gridded data from the Climate Research Unit (CRU) of the University of East Anglia were utilized to assess key water balance components. The results indicate that while gridded datasets offer an alternative for regions with limited ground data, local calibration is required due to notable discrepancies. More specifically, it was found that gridded data tended to underestimate precipitation, with estimates approximately 25% lower compared to ground station data. The potential evapotranspiration (PET) estimates using gridded data were more accurate, with underestimation on the order of 10%. Moreover, the gridded data produced overestimations for all of the water balance key components including soil moisture (St), monthly changes in soil moisture (ΔSt), and actual evapotranspiration (AE) compared to the ground station data. The water surplus (S) estimates showed a significant dispersion of values when using the gridded data, particularly in regions characterized by more arid conditions. In addition, the application of gridded data led to a great increase in the aridity index (AI) values, altering the desertification classification of sites from semi-arid to sub-humid or humid categories. These findings underscore the importance of careful consideration when utilizing gridded datasets for hydrological and bioclimatic assessments, particularly in Mediterranean climate regions characterized by a complex topography and temporal climatic variability. Full article

Regional mapping of Above Ground Biomass Density (AGBD) using Remote Sensing data has shown high accuracy but lacks replicability at a global scale. In contrast, global models capture AGBD variability across biomes but struggle with biome-specific accuracy. To address this gap, we develop and assess the performance of a Deep Learning model for mapping AGBD at 10-m resolution using multi-source satellite data (Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI) across four biomes: Mediterranean, taiga (boreal forests), tropical rainforests, and semi-arid savannas. The model is trained and validated separately for each biome, yielding four regional models with normalized RMSEs of 0.43–0.67 and correlation coefficients (r) of 0.61–0.77 against forest inventories. We compare predictions from these models to a benchmark dataset and to a model trained on all four biomes combined. The regional models consistently outperform both, achieving better metrics than the benchmark. Additionally, an analysis of prediction drivers reveals biome-specific differences, reinforcing the importance of per-biome mapping approaches. This study highlights the advantages and limitations of regional against global modeling, creating the basis for biome-specific, replicable, scalable and multi-temporal AGBD mapping. Full article