Search Results (136)

Soil salinization, particularly under irrigation in the arid regions of North Africa, represents a major constraint to sustainable agricultural development. This study investigates the Chott El Hodna region in Algeria, a Ramsar-classified wetland severely affected by salinization. Two representative soil profiles (P1 and P2) were initially characterized, revealing chemical properties dominated by calcium-chloride and calcium-sulfate types. Based on these findings, 26 additional profiles with moderate levels of gypsum, limestone, and soluble salts were analyzed. The limited number of profiles reflects the environmental homogeneity of the area, allowing the study site to be considered a pilot zone. Fuzzy logic was employed to classify soils, identify intergrade soils, and determine their degree of membership to Solonchaks within the Calcisol class, addressing the lack of precision in conventional classifications. Results indicate that 50% of soils are Solonchaks, 46.15% are Calcisols, and 3.85% are intergrades. Principal Component Analysis (PCA) revealed that soil solution chemistry is mainly governed by the dissolution of evaporite minerals (gypsum, halite, anhydrite) and the precipitation of carbonate phases (calcite, aragonite, dolomite). Statistical analyses using Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) demonstrated that ANN achieved superior predictive performance for the Solonchak index (Is), with R² = 0.70 and RMSE = 0.17, compared with R² = 0.41 for MLR. This study proposes a robust framework combining fuzzy logic and ANN to improve the classification of saline wetland soils, particularly by identifying intergrade soils, thus providing a more precise numerical classification than conventional approaches. Full article

This study aimed to evaluate the effects of phytase enzyme supplementation on the thermoregulatory responses of Japanese quails (Coturnix japonica) exposed to different thermal environments. A total of 720 one-day-old laying quails were assigned to a completely randomized design with five dietary treatments (0, 500, 1000, 1500, and 3000 FTU of phytase) and three thermal conditions: thermal comfort (24 °C) and heat stress environments (30 °C and 36 °C). Each treatment had six replicates with eight quails per experimental unit. Data were collected during the early laying phase, peak egg production, and the final laying phase. Measurements included rectal and surface temperatures (assessed via thermographic imaging), allowing the calculation of core-to-surface and surface-to-environment thermal gradients. Quails exposed to severe heat stress (36 °C) showed increased heat dissipation via convection (p = 0.001) and radiation (p = 0.029) when supplemented with phytase doses above 1500 FTU/kg. Additionally, high-dose phytase supplementation reduced the cloacal temperature and optimized thermal gradients, indicating a potential protective effect of exogenous phytase in alleviating heat stress. Overall, these findings highlight phytase supplementation as a promising nutritional strategy to enhance heat tolerance, mitigate thermal stress, and improve the welfare and physiological resilience of quails throughout the production cycle. Full article

This data descriptor presents δ-MedBioclim, a newly developed dataset for the Euro-Mediterranean region. This dataset applies the delta-change method by comparing the values of 25 General Circulation Models (GCMs) for the reference period (1981–2010) with their projections for future periods (2026–2050, 2051–2075, and 2076–2100) under the SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios. These anomalies are added to two pre-existing datasets, ERA5-Land and CHELSA, yielding resolutions of 0.1° and 0.01°, respectively. Additionally, this manuscript provides a ranking of GCMs for each major river basin within the study area to guide model selection. δ-MedBioclim includes, for all the aforementioned scenarios, monthly mean temperature, total monthly precipitation, and 23 bioclimatic variables, including 9 (biorm1 to biorm9) from the Worldwide Bioclimatic Classification System (WBCS) that are not available in other databases. It also provides two bioclimatic classifications: Köppen–Geiger and WBCS. This dataset is expected to be a valuable resource for modeling the distribution of Mediterranean species and habitats, which are highly affected by climate change. Full article

Digital repeat photography is currently applied mainly in geophysical studies of ecosystems. However, its role as a tool that can be utilized in conventional phenology, tracking a plant’s seasonal developmental cycle, is growing. This study’s main goal was to develop an easy-to-reproduce, single-camera-based novel approach to determine the flowering phases of 12 woody plants of various deciduous species. Field observations served as binary class calibration datasets (flowering and non-flowering stages). All the image RGB parameters, designated for each plant separately, were used as plant features for the models’ parametrization. The training data were subjected to various transformations to achieve the best classifications using the weighted k-nearest neighbors algorithm. The developed models enabled the flowering classifications at the 0, 1, 2, 3, and 5 onset day shift (absolute values) for 2, 3, 3, 2, and 2 plants, respectively. For 9 plants, the presented method enabled the flowering duration estimation, which is a valuable yet rarely used parameter in conventional phenological studies. We found the presented method suitable for various plants, despite their petal color and flower size, until there is a considerable change in the crown color during the flowering stage. Full article

Understanding global patterns of tree canopy height and density is essential for effective forest management and conservation planning. This study examines how these attributes vary along latitudinal gradients and identifies key climatic drivers influencing them. We utilized high-resolution remote sensing datasets, including a 10 m resolution canopy height dataset aggregated to 1 km for computational efficiency, and a 1 km resolution tree density dataset derived from ground-based measurements. To quantify the relationships between forest structure and environmental factors, we applied nonlinear regression models and climate dependency analyses, incorporating bioclimatic variables from the WorldClim dataset. Our key finding is that latitude exerts a dominant but asymmetric control on tree height and density, with tropical regions exhibiting the strongest correlations. Tree height follows a quadratic latitudinal pattern, explaining 29.3% of global variation, but this relationship is most pronounced in the tropics (−10° to 10° latitude, R² = 91.3%), where warm and humid conditions promote taller forests. Importantly, this effect differs by hemisphere, with the Southern Hemisphere (R² = 67.1%) showing stronger latitudinal dependence than the Northern Hemisphere (R² = 35.3%), indicating climatic asymmetry in forest growth dynamics. Tree density exhibits a similar quadratic trend but with weaker global predictive power (R² = 7%); however, within the tropics, latitude explains 90.6% of tree density variation, underscoring strong environmental constraints in biodiverse ecosystems. Among climatic factors, isothermality (Bio 3) is identified as the strongest determinant of tree height (R² = 50.8%), suggesting that regions with stable temperature fluctuations foster taller forests. Tree density is most strongly influenced by the mean diurnal temperature range (Bio 2, R² = 36.3%), emphasizing the role of daily thermal variability in tree distribution. Precipitation-related factors (Bio 14 and Bio 19) moderately explain tree height (~33%) and tree density (~25%), reinforcing the role of moisture availability in structuring forests. This study advances forest ecology research by integrating high-resolution canopy structure data with robust climate-driven modeling, revealing previously undocumented hemispheric asymmetries and biome-specific climate dependencies. These findings improve global forest predictive models and offer new insights for conservation strategies, particularly in tropical regions vulnerable to climate change. Full article

Gross primary productivity (GPP), the primary driver of carbon accumulation, governs the sequestration of atmospheric CO₂ into biomass. However, GPP cannot be measured directly, as photosynthesis and respiration are simultaneous. At canopy level in plot-scale studies, GPP can be estimated through the closed chamber-based measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco). This technique is cost-effective and widely used in small-scale studies with short vegetation, but measurements are periodic-based and require temporal interpolations. The rectangular hyperbolic model (RH) was the basis of this study, developing two temperature-dependent factors following a linear and exponential shift in GPP when the temperature oscillates from the optimum for vegetation performance. Additionally, a water table depth (WTD)-dependent model and an exponential model were tested. In the peak season, modified RH models showed the best performance, while for the rest of the year, the best model varied for each subplot. The statistical results demonstrate the limitations of assuming the light-use efficiency as a fixed shape mechanism (using only one model). Therefore, a multi-model approach with the best performance model selected for each period is proposed to improve GPP estimations for peatlands. Full article

Vegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used instead of traditional plant phenology based on plant organ emergence and development observations. Despite the estimated timing of the LSP parameters being dependent on the vegetation index (VI) used, inadequate attention was paid to the evaluation of the commonly used VIs for LSP of different vegetation covers. We used two years of data from the experimental site in central European peatland, where plots of two peatland vegetation communities are under a climate manipulation experiment. We assessed the accuracy of LSP retrieval by simple remote sensing metrics against LSP derived from gross primary production and canopy chlorophyll content time series. The product of Near-Infrared Reflectance of Vegetation and Photosynthetically Active Radiation (NIRvP) and Green Chromatic Coordinates (GCC) was identified as the best-performing remote sensing metrics for peatland physiological and structural phenology, respectively. Our results suggest that the changes in the physiological phenology due to increased temperature are more prominent than the changes in the structural phenology. This may mean that despite a rather accurate assessment of the structural LSP of peatland by remote sensing, the changes in the functioning of the ecosystem can be underestimated by simple VIs. This ground-based phenological study on peatlands provides the base for more accurate monitoring of interannual variation of carbon sink strength through remote sensing. Full article

This study examines the spatio-temporal evolution of bioclimatic belts in peninsular Spain and the Balearic Islands from 1953 to 2022 using the World Bioclimatic Classification System and data from 3668 meteorological stations. Findings indicate a shift toward warmer and more arid conditions, with thermotypes showing an increase in mesomediterranean and thermomediterranean types and a decrease in mesotemperate and supratemperate types. Ombrotype analysis revealed a rise in semiarid types and a decline in humid and hyperhumid types. Significant changes occurred in climate transition zones and mountainous regions, where a process of “Mediterraneanisation”—a process characterised by the expansion of warmer and drier conditions typical of Mediterranean climates into previously temperate areas and/or an altitudinal rise in thermotypes—has been observed. The spatial variability of changes in ombrotypes was greater than that in thermotypes, with regions showing opposite trends to the general one. These results highlight the need for adaptive conservation strategies, particularly in mountainous and climate transition areas, where endemic species may face increased vulnerability due to habitat loss and fragmentation. The results of this study provide insight into how climate change is affecting bioclimatological conditions in the Iberian Peninsula and the Balearic Islands. Full article

This study aims to present the benefits of unmanned aircraft systems (UAS) in atmospheric aerosol research, specifically to obtain information on the vertical variability of aerosol single-scattering properties in the lower troposphere. The results discussed in this paper were obtained during the Polish Radar and Lidar Mobile Observation System (POLIMOS) field campaign in 2018 at a wetland and rural site located in the Rzecin (Poland). UAS was equipped with miniaturised devices (low-cost aerosol optical counter, aethalometer AE-51, RS41 radiosonde) to measure aerosol properties (scattering and absorption coefficient) and air thermodynamic parameters. Typical UAS vertical profiles were conducted up to approximately 1000 m agl. During nighttime, UAS measurements show a very shallow inversion surface layer up to about 100–200 m agl, with significant enhancement of aerosol scattering and absorption coefficient. In this case, the Pearson correlation coefficient between aerosol single-scattering properties measured by ground-based equipment and UAS devices significantly decreases with altitude. In such conditions, aerosol properties at 200 m agl are independent of the ground-based observation. On the contrary, the ground observations are better correlated with UAS measurements at higher altitudes during daytime and under well-mixed conditions. During long-range transport of biomass burning from fire in North America, the aerosol absorption coefficient increases with altitude, probably due to entrainment of such particles into the PBL. Full article

The rising global temperature makes understanding the impact of warming on plant physiology in critical ecosystems essential, as changes in plant physiology can either help mitigate or intensify climate change. The northern peatlands belong to the most important parts of the global carbon cycle. Therefore, knowledge of the ongoing and future climate change impacts on peatland vegetation photosynthesis is crucial for further refinement of peatland or global carbon cycle and vegetation models. As peat moss (Sphagnum spp.) and bog cranberry (Vaccinium oxycoccos L.) represent some of the most common plant functional groups of peatland vegetation, we examined the impact of experimental warming on the status of their photosynthetic apparatus during the early vegetation season. We also studied the differences in the winter to early spring transition of peat moss and bog cranberry photosynthetic activity. We have shown that peat moss starts photosynthetic activity earlier because it relies on light-dependent energy dissipation through the winter. However, bog cranberry needs a period of warmer temperature to reach full activity due to the sustained, non-regulated, heat dissipation during winter, as suggested by the doubling of photosystem II efficiency and 36% decrease in sustained heat dissipation between the mid-March and beginning of May. The experimental warming further enhanced the performance of photosystem II, indicated by a significant increase in the photosystem II performance index on an absorption basis due to warming. Therefore, our results suggest that bog cranberry can benefit more from early spring warming, as its activity is sped up more compared to peat moss. This will probably result in faster shrub encroachment of the peatlands in the warmer future. The vegetation and carbon models should take into account the results of this research to predict the peatland functions under changing climate conditions. Full article

Climate change is altering the temperature and precipitation patterns in the Iberian Peninsula and on the Balearic Islands, with potential impacts on the distribution of plant communities. This study analyses the evolution of bioclimatic units in this region during the 1953–2022 period. Data from 3668 weather stations distributed throughout the study area were analysed. Two 35-year periods (1953–1987 and 1988–2022) were compared to assess changes in macrobioclimates and bioclimates. The results showed expansion of the Mediterranean macrobioclimate, whose total area increased by 6.93%, mainly at the expense of the Temperate macrobioclimate. For bioclimates, a trend towards more xeric and continental conditions was observed in the Mediterranean region, while temperate areas moved towards homogenisation of climate conditions. Likewise, two new bioclimates were detected, which indicate the emergence of new climate conditions. These results suggest a reorganisation of bioclimatic conditions, with particular implications for biodiversity in mountainous and transitional areas, where endemic species face higher risks of habitat loss. This study provides useful information for developing targeted conservation strategies, establishing a baseline for monitoring future changes and developing early warning systems for vulnerable ecosystems, thus supporting the design of climate-adapted conservation measures in the region studied. Full article

This work establishes the relationship between climate, bioclimate, and forest ecosystems and highlights the need to teach these topics in educational institutions. It was found that such knowledge is not currently taught in universities, leading to scarce or non-existent teacher training in these areas. However, the teaching of bioclimatic aspects over a three-year period as a basis for land use planning, has shown highly positive results. The objective is to propose the teaching of bioclimatology to future managers and teachers in order to obtain a balanced environmental development. The analysis of bioclimatic diagrams makes it possible to stipulate the duration of the water reserve in the soil. This is essential for agricultural and forestry management. The edaphic factor and the bioclimatic ombrotclimatic (Io) and thermoclimatic (It/Itc) indexes condition the types of forests and crops that can exist in a territory, with the particularity that the ombrotype is conditioned by the edaphic factor, which allows a decrease in the ombrothermal index, expressed by the ombroedaphoboxerophilic index (Ioex). The humid ombrotypes condition the presence of Abies pinsapo, Quercus pyrenaica, Q. broteroi, and Q. suber, and the dry ones Q. rotundifolia and Olea sylvestris. Full article

Chickpea (Cicer arietinum L.) is one of the most important legumes currently grown. It is an important source of proteins and nutrients, such as calcium, potassium and iron. As a result, precise crop management is necessary for maximizing its production. The presented study deals with the effect of soil heterogeneity caused by variable contents of macro- and micronutrients on the uptake of nutrients by chickpea. The values measured (contents of macro- and micronutrients in plant samples) indicate that soil heterogeneity is an important factor for the contents of nutrients and soil reactions, which strongly affect the growth of chickpea. We investigated the soil heterogeneity in a chickpea field. Two zones (A and B) with different stand development were found in the model plot. Zone A showed a healthy (green) growth, while Zone B exhibited a yellow-coloured growth, indicating deficits in nutrient uptake. The contents of selected nutrients (P, K, Ca, Mg, Fe, Cu, Zn and Mn) in the soil and in the plant biomass (i.e., stems, leaves, pods and seeds) were analyzed. In the zone with the yellow-coloured biomass, the results showed significantly (p < 0.05) reduced contents of N, P, K, Mg, Fe, Mn, Cu and Zn in the leaves; higher values of soil reaction (pH); and higher contents of calcium and calcium carbonate in the soil. The uptake of nutrients by the plants and their translocation were affected by the above-mentioned soil parameters and by their mutual interactions. Therefore, it is possible to state that soil heterogeneity (caused by variable contents of nutrients in soil) should be taken into account in the precise crop management of chickpeas. Full article

Gamma radiation has been suggested to have post-effects on emerging plants when applied to the seeds. In the present study, we aimed to induce alterations in photosynthetic functionality and subsequent modifications in secondary metabolites of summer savory following seed priming with gamma radiation. Savory seeds were treated with 0, 50, 100, 200, and 300 Gy gamma radiation in a completely randomized design with ten replications for morphological and photosynthetic parameters and three for phytochemical assessments. The results showed that gamma radiation on seeds adversely affected photosynthetic performance, especially at the highest doses. It negatively influenced the growth, while increasing the shoot branching, the number of nodes, and the diameter of the stem. Gamma radiation on seeds generally reduced pigmentation in savory leaves, such as chlorophylls, carotenoids, and anthocyanins. However, soluble sugar, starch, total phenolics, and total flavonoid contents were elevated in the leaves of plants that emerged from gamma-primed seeds. Gamma radiation priming reduced essential oil’s percentage and yield. Carvacrol and limonene components of essential oil were diminished, whereas linalool and thymol were increased. In conclusion, due to its inherent stress-inducing effects, and despite some positive effects on phytochemicals, seed priming with gamma radiation adversely influenced growth, photosynthesis, and quantity and quality of savory essential oils. Further research is still needed to target the use of gamma radiations before harvesting the seeds or determine the cytogenetic characteristics of irradiated plants. Full article

This systematic literature review (SLR) provides a comprehensive overview of remote sensing (RS) applications in northern peatlands from 2017 to 2022, utilising various platforms, including in situ, UAV, airborne, and satellite technologies. It addresses the challenges and limitations presented by the sophisticated nature of northern peatland ecosystems. This SLR reveals an in-creased focus on mapping, monitoring, and hydrology but identifies noticeable gaps in peatland degradation research. Despite the benefits of remote sensing, such as extensive spatial coverage and consistent monitoring, challenges persist, including high costs, underexplored areas, and limitations in hyperspectral data application. Fusing remote sensing data with on-site research offers new insights for regional peatland studies. However, challenges arise from issues like the cost of high-resolution data, coverage limitations, and inadequate field validation data in remote areas. This review suggests refining methodologies, validating with high-resolution data, and addressing these limitations for future research. Full article