Search Results (46)

In sub-Saharan Africa, land degradation and climate change continue to undermine agricultural productivity by reducing soil productivity and water availability. This review identifies soil and water conservation technologies successfully applied in climatically analogous regions of sub-Saharan Africa with the aim of informing effective technology transfer to Senegal, particularly Sédhiou and Tambacounda. Using K-means clustering on WorldClim bioclimatic variables, 35 comparable countries were identified, of which 17 met inclusion criteria based on data availability and ≥60% climatic similarity. Eighty-five technologies were documented and assessed for their compatibility across rainfall patterns, land gradients, and uses, with 12 emerging as consistently effective. Quantitative evidence shows that zai/tassa pits, stone bunds, and half-moons increase crop yields by 50–200%, while stone bunds and mulching reduce runoff by up to 80% and improve soil moisture retention. Terracing and tied-ridging were also linked to higher water-use efficiency, with tied-ridging increasing soil moisture by 13%. Burkina Faso, Kenya, and Malawi lead in adoption and diversity, whereas Senegal lags due to institutional gaps, limited funding, and weak extension systems. These technologies offer a readily available, evidence-based toolkit for building agricultural resilience in Senegal. However, their successful adoption requires stronger policy integration, stakeholder empowerment, cross-border learning, and private-sector engagement. Full article

Understanding the factors that structure freshwater invertebrate assemblages is essential for predicting biodiversity patterns across heterogeneous landscapes. Here, we provide the first comprehensive assessment of ostracod diversity across multiple freshwater ecoregions of Botswana, a semi-arid country encompassing a wide range of hydrological and climatic conditions. We analyzed ostracod assemblages from 19 sites, integrating spatial, regional, and local environmental variables with biotic predictors derived from macro-, meio-, and microinvertebrate communities. Multivariate analyses revealed that spatial variables, strongly correlated with bioclimatic gradients, were the dominant predictors of ostracod assemblage composition. These gradients reflected broad-scale climatic differences among ecoregions and explained substantially more variation than local physical and chemical water properties. Biotic interactions, represented by taxonomic and functional composition of associated invertebrates and vegetation type, also significantly contributed to model performance, highlighting their previously underappreciated role in shaping ostracod assemblages. Local abiotic environmental factors had comparatively weak explanatory power. Our findings demonstrate that ostracod diversity in Botswana is primarily structured by large-scale spatial–bioclimatic patterns, with additional influence from biotic interactions. This study provides new insights into the ecological drivers of freshwater microcrustaceans in semi-arid regions and establishes a baseline for future biodiversity assessments in southern Africa. Full article

The teaching of the phytosociological method comprises several stages and aligns closely with the research-oriented teaching–learning process promoted by active methodologies. In both cases, preliminary inquiry is essential to review existing knowledge on vegetation in all its dimensions: bioclimatic, biogeographical, ecological, floristic composition, distribution, and conservation status. The main objective is to connect active teaching methodologies with phytosociological research. To this end, the natural environment is used to bring students into direct contact with plant communities, and the phytosociological research method is applied, through which students learn sampling techniques. This approach provides a rapid and effective assessment of habitat conservation status (EU Habitats Directive 92/43/EEC, European Council, 21 May 1992). As notable results, we highlight the poor conservation status of the three communities described, which is evident from the decline in characteristic association species. The present study focuses on the wetlands of the Costa Tropical, where communities of Juncus acutus, Typha dominguensis, Phragmites australis, and Arundo donax predominate. In this case, these communities act as open-air laboratories for teaching the phytosociological method. The Juncus acutus communities differ from those of Scirpus holoschoenus and other Juncus acutus stands by the presence of the endemic Linum maritimum. Meanwhile, the reedbeds differ from Thypho-Phragmitetum australis through the presence of Halimione portulacoides. In both cases, the influence of sea spray conditions the presence of subhalophilous species such as Juncus acutus, Linum maritimum, and Halimione portulacoides. This has enabled us to establish two new plant associations: LmJa = Lino maritimi–Juncetum acuti (rush stands) and Hp–Phra = Halimione portulacoidis–Phragmitetum australis (reedbeds). Ecological gradients also make it possible to separate Typha communities belonging to the Ca–Td = Cynancho acuti–Typhetum dominguensis association, and Phragmites into two distinct associations. This distinction arises because Typha communities require soil water during the summer period, whereas in Phragmites stands the upper soil horizon dries out. Full article

Bidens pilosa L. is a cosmopolitan and invasive weed that strongly impacts agricultural systems in tropical regions. In Veracruz, Mexico, its presence extends mainly across mid-elevation zones where coffee, maize, and sugarcane are cultivated. This study characterized the bioclimatic and edaphic determinants of B. pilosa distribution using 581 georeferenced occurrences combined with 19 bioclimatic variables, elevation, and soil data. A Maxent model revealed the highest habitat suitability (0.65–1.0) in the central mountainous region between 800 and 1500 m.a.s.l., particularly under temperate–humid climates (Cfa, Cfb) and Acrisol–Leptosol soils. Principal component and redundancy analyses showed that annual precipitation (BIO12), precipitation of the driest month (BIO14), and temperature seasonality (BIO4) explained 74.7% of the total environmental variance. Cluster analysis identified four distinct ecological groups, confirming broad ecological plasticity. These findings indicate that B. pilosa is not randomly distributed but structured along climatic and soil gradients, with precipitation and elevation as major determinants of its ecological niche. Understanding these relationships provides a quantitative framework for predicting its expansion under future climate scenarios and for designing targeted management strategies in tropical agroecosystems. Full article

Insect herbivory exerts strong selective pressure on plants, yet no study has documented its effects on the halophytic Apiaceae Crithmum maritimum L. (sea fennel). Here, we present the first evidence of natural insect attack on this species, based on five Tunisian coastal populations distributed along a transparent bioclimatic gradient—from sub-humid to semi-arid—and exposed to different levels of herbivory. We implemented an integrative, multi-trait analytical design encompassing morphological, biochemical, mineral, and lipophilic datasets. Each dataset was explored through a suite of complementary multivariate analyses, including ANOVA coupled with Tukey’s HSD, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) with variable-importance-in-projection (VIP) scores, correlation matrices, hierarchical clustering, and distance-based redundancy analysis (dbRDA). This integrative strategy provided a robust framework for disentangling the complex trait associations underlying two distinct defense syndromes. Populations from low-herbivory, sub-humid sites (Tabarka, Bizerte, Tunisia) showed higher levels of phenolics, tannins, antioxidants, sterols, PUFA, and structural robustness, indicating a tolerance strategy. Conversely, high-herbivory, semi-arid sites (Haouaria, Monastir, Tunisia) were marked by elevated apiol and terpene levels, sodium and phosphorus accumulation, and reproductive adjustments, reflecting a resistance strategy. The site Cap Negro exhibited a transitional expression, revealing intermediate phenotypic plasticity. These findings show that herbivory intensity and bioclimatic conditions jointly influence the defense syndromes of C. maritimum, emphasizing its remarkable phenotypic plasticity and providing the first ecological evidence of insect herbivory in sea fennel. Full article

Urbanization imposes complex environmental gradients that threaten plant diversity and urban ecosystem integrity. Understanding the multifactorial drivers that govern species distribution in urban contexts is essential for biodiversity conservation and sustainable landscape planning. This study addresses this challenge by examining the environmental determinants of urban flora in a rapidly developing city. We integrated data from 397 floristic sampling sites and 13 environmental monitoring locations across Düzce, Türkiye. A multidimensional suite of environmental predictors—including microclimatic variables (soil temperature, moisture, light), edaphic properties (pH, EC (Electrical Conductivity), texture, carbonate content), precipitation chemistry (pH and major ions), macroclimatic parameters (CHELSA bioclimatic variables), and spatial metrics (elevation, proximity to urban and natural features)—was analyzed using nonlinear regression models and machine learning algorithms (RF (Random Forest), XGBoost, and SVR (Support Vector Regression)). Shannon diversity exhibited strong variation across land cover types, with the highest values in broad-leaved forests and pastures (>3.0) and lowest in construction and mining zones (<2.3). Species richness and evenness followed similar spatial trends. Evenness peaked in semi-natural habitats such as agricultural and riparian areas (~0.85). Random Forest outperformed other models in predictive accuracy. Elevation was the most influential predictor of Shannon diversity, while proximity to riparian zones best explained richness and evenness. Chloride concentrations in rainfall were also linked to species composition. When the models were recalibrated using only native species, they exhibited consistent patterns and maintained high predictive performance (Shannon R² ≈ 0.937474; Richness R² ≈ 0.855305; Evenness R² ≈ 0.631796). Full article

The Atlas cedar Cedrus atlantica is a relict and endemic conifer from Morocco and Algeria, although plantations may be found in several locations aside from its natural range. Recurrent droughts have been widely related to Atlas cedar dieback, growth decline, and mortality, but the genetic basis of potential adaptive capacity is unknown. We used the double digest restriction-site associated DNA sequencing technique (ddRAD-seq) to describe the genetic structure and variability of Atlas cedar along an aridity gradient in Morocco. Furthermore, we investigated the potential genetic origin of three Spanish plantations, also along an aridity gradient. The obtained single nucleotide polymorphisms (SNPs) were used to perform genotype–environment associations (GEAs) to define SNPs related to bioclimatic variables of temperature and precipitation. The vulnerability of this species to environmental variations was also estimated by its risk of non-adaptedness (RONA). Population structure showed a divergence between the Moroccan natural stands and some of the Spanish plantations, with each Moroccan nucleus being genetically distinct. The genetic variability was significantly lower in plantations than in natural populations. The drier Spanish plantations (easternmost) were genetically very similar to the driest Moroccan population (southernmost), suggesting that as its origin. A total of 41 loci under selection were obtained with the Moroccan dataset. In relation to temperature and precipitation variables, isothermality showed the highest number of associated loci (10) in GEA studies, and genotype–phenotype associations (GPAs) showed one locus associated with the Specific Leaf Area. RONA value was higher in the southernmost High Atlas population, where rising temperature was the main driver of expected genetic offset by allele frequency changes under the worst emissions scenario. In contrast, Spanish plantations would need smaller genetic changes to cope with the expected climate change. Likely gene flow from southern to northern areas suggests a latitudinal heading, where Spanish plantations might operate as an assisted migration. Moreover, one locus showed a northern/southern pattern in saplings but not in adults, suggesting a potential latitudinal pattern of selection. Our results are discussed on the basis of their management and conservation. Full article

To build climate-resilient livestock systems, public policies must be informed by bioclimatic zoning, enabling region-specific interventions and more efficient resource allocation. This study aimed to conduct bioclimatic zoning for dairy cattle farming in the state of Maranhão, Brazil. Big data analysis techniques and predictive geostatistical modeling were applied to historical (2012–2023) and future climate scenarios under intermediate (RCP4.5) and high-intensity (RCP8.5) greenhouse gas emissions. Kriging maps of THI revealed a decreasing north–south thermal gradient, with values exceeding 80 during critical years. Milk yield losses were more pronounced in high-producing cows, reaching up to 5 kg/cow/day under extreme heat. Areas identified as drought-prone exhibited spatial patterns consistent with THI distributions. The projections indicate that, under the RCP 4.5 scenario, over 60% of Maranhão will exhibit average THI values between 78 and 81 by the end of the century. Under the RCP 8.5 scenario, large areas of the state are expected to reach THI values above 86. Under these conditions, estimated milk production losses may exceed 4 kg/cow/day for moderate-yielding animals and 9 kg/cow/day for high-yielding ones, respectively. The results reinforce the importance of bioclimatic zoning to support informed policymaking in the context of climate change. Full article

The study presents data on the role of lithological factors in the divergence of soil formation in forest–steppe and steppe ecosystems in a region of the East European Plain characterized by extremely contrasting geogenic conditions. Soils from different lithologic–geomorphologic combinations in the Samara region were chosen as the study object. It was shown that, in some cases, bioclimatogenic conditions are less decisive in the formation of the morphological organization and basic chemical parameters of the solum than the lithological characteristics of a particular locality. These lithological factors can transform soil morphology and affect the taxonomic position of soils at the subtype level and below. In landscapes marked by spatial and lithological contrasts at meso- and macro-levels, the use of a bioclimatic classification approach becomes inadequate, because it fails to highlight individual soil features. Thus, the development of lithological taxonomic and diagnostic criteria is necessary for the protection, proper use, and mapping of soils in complex geogenic, particularly lithological, conditions. Within one soil climatic zone, there can exist a large number of lithological soil subtypes, genera, and varieties. In such cases, the lithological framework has a stronger influence on soil spatial distribution than climatic gradients and associated vegetation ecotones. 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

The Balkan Peninsula is considered one of the most important centres of orchid diversity in Europe. However, the patterns of orchid species richness in the Central Balkans have not been sufficiently studied so far. The aim of this study was, therefore, to identify the centres of orchid diversity and the factors that influence the spatial variation in orchid species richness in the Central Balkans. For the analyses, the area of the Central Balkans was divided into 10 × 10 km grid cells. The environmental variables determined for each grid cell and used in the analyses were altitude, bioclimatic variables, geological substrates and habitat types. A random forest (RF) analysis was used to identify the environmental predictors most strongly associated with species richness. In addition to the total number of taxa, orchids with three belowground organ types were analysed separately: (a) rhizomatous orchids, (b) orchids with palmately lobed and fusiform tubers (“palmate tuberous orchids”) and (c) orchids with spherical or ovoid tubers (“ovoid tuberous orchids”). In the Central Balkans, 54 orchid species and subspecies have been recorded, and the most important centres of diversity are the Tara, Zvijezda, Jadovnik and Zlatar Mountains and the Ovčar-Kablar Gorge. In general, two groups of grid cells with the largest number of orchid taxa, i.e., hotspots, stood out: (1) grid cells with a large altitudinal range and (2) grid cells occupied by gorges and ravines. The most important gradients influencing orchid species richness are specific habitat types and altitudinal ranges, while climatic factors and geological substrates are less important. The most important factors affecting the richness of total and rhizomatous orchids are altitudinal range and habitat types (Abieti-Fagenion, Ostryo-Carpinion orientalis and Pinion nigrae forests), highlighting the important role of habitat heterogeneity. The maximum altitude, percentage of Abieti-Fagenion and Vaccinio-Picetea forests and the minimum value of the mean temperature of the driest quarter are the most important factors for determining the richness of palmate tuberous orchids, whereas the percentage of xero-thermophilous habitat types (Ostryo-Carpinion orientalis, Asplenietea trichomanis and Pinion nigrae) has the greatest influence on the richness of ovoid tuberous orchids. These results confirm the hypothesis concerning the origin and development of underground organs in orchids, emphasising that palmate tuberous orchids are best adapted to cold and humid habitat conditions, whereas ovoid tuberous orchids have the ability to grow in habitats with very warm and dry conditions. This study provides a good basis for better orchid conservation planning and underlines the importance of belowground strategies as a feature of orchid life history that should be considered when studying patterns of orchid diversity. Full article

The Andean paramos are unique and biodiverse environments. Located between the upper limit of forest and perpetual snow, they provide ecosystem services, especially freshwater supply; however, anthropogenic activities and climate change have altered their distribution and composition. This paper analyses the influence of altitude and climatic factors on the floristic composition of the páramos. A quasi-experimental study was used in three altitudinal gradients, collecting geolocalised data on species and bioclimatic variables. Principal component analysis, using the HJ-Biplot visualisation technique and k-means clustering algorithms, was applied to explore the relationships between factors. It was determined that the lower zone is nuanced by the presence of Solanaceae, which are important for human food. In the middle zone, there is a high diversity, with the Ericaceae and Caprifoliaceae families standing out, while in the upper zone, the Ericaceae and Gentianaceae families are accentuated. The PCA reveals that strata 2 and 3 share family taxa, while stratum 1 shows differences. Altitude and precipitation directly influence the distribution of species in each stratum; the Asteraceae family is dominant in the canton for its contribution to the principal components. Full article

The current study aims to analyze the fundamental ecological niches of five páramo species in the high Andean zones of South America. Hereby, the research focuses on the typical flora species of this ecosystem, such as Azorella aretioides, Azorella crenata, Azorella biloba, Azorella corymbosa, and Azorella pedunculata, testing whether their niches are more similar than expected. The study area in the Ecuadorian Andes encompasses altitudinal gradients between 2000 and 5000 m above sea level, where the species were previously registered. For the methodology, we used data from the Global Biodiversity Information Facility (GBIF) and identified the determining bioclimatic variables for the model as Bio1, Bio2, Bio3, Bio4, Bio12, Bio13, Bio14, Bio18, and Bio19. Moreover, we considered two alternative socioeconomic scenarios of climate change (SSP126 and SSP 245) projected for the period 2021–2040. In the same way, ecological niche models were evaluated and applied in order to identify areas of reduction in geographic space and the ecological space of the five species. Subsequently, the analysis revealed significant sensitivity of these high mountain species to variations in temperature and precipitation, with potential risks to associated species and water resources. In conclusion, changes in the fundamental niche were observed, with all species indicating reductions in distribution for 2040. This occurs particularly under the SSP245 scenario and especially in the equatorial zone, which currently exhibits extraordinary richness concerning the Azorella genus. Therefore, the study highlights evidently the vulnerability of páramo species to climate change, emphasizing the need for conservation efforts. Full article

This study provides pioneering research on the vegetation of archaeological areas in Iran to enhance its naturalistic and bioindication values by selecting the Pasargadae World Heritage Site (WHS). Vegetation surveys were carried out in different homogeneous habitats, analyzing the plant communities through statistical elaboration, syntaxonomic role, mapping, and enhancement of plants with conservation interest. In an ecological approach, the study included an analysis of the recent climate changes and human interventions influencing the water resources. Results revealed seven main vegetation types reflecting ecological gradients shaped by environmental, edaphic, and anthropogenic factors. The syntaxonomic analysis showed a primary subdivision in semi-natural grasslands and synanthropic vegetation. Several key species were identified as bioindicators of multiple factors, such as: Launaea acanthodes, Stipa barbata, Alhagi maurorum, Bellevalia saviczii, Glycyrrhiza glabra, Convolvulus arvensis, and Hordeum murinum. The vegetation map showed how the hilly grassland communities hosted the highest number of species with conservation interest and their need to be better protected. Bio-climatic data, such as the construction of dams and the exploitation for irrigation purposes, pointed to the increasing xeric conditions, which make urging conservation efforts for the site’s historical and naturalistic values. The study underscores the importance of preserving places with high plant diversity for effective site management, and enhances the intricate relationship between vegetation and natural features in the occurring environmental changes. Full article

This study employed an ensemble machine learning approach to evaluate the effect of bioclimatic covariates on the prediction accuracy of soil total carbon (TC) in the Pannonian biogeoregion. The analysis involved two main segments: (1) evaluation of base environmental covariates, including surface reflectance, phenology, and derived covariates, compared to the addition of bioclimatic covariates; and (2) assessment of three individual machine learning methods, including random forest (RF), extreme gradient boosting (XGB), and support vector machine (SVM), as well as their ensemble for soil TC prediction. Among the evaluated machine learning methods, the ensemble approach resulted in the highest prediction accuracy overall, outperforming the individual models. The ensemble method with bioclimatic covariates achieved an R² of 0.580 and an RMSE of 10.392, demonstrating its effectiveness in capturing complex relationships among environmental covariates. The results of this study suggest that the ensemble model consistently outperforms individual machine learning methods (RF, XGB, and SVM), and adding bioclimatic covariates improves the predictive performance of all methods. The study highlights the importance of integrating bioclimatic covariates when modeling environmental covariates and demonstrates the benefits of ensemble machine learning for the geospatial prediction of soil TC. Full article