The use of native plants in urban green spaces is an optimal strategy for mitigating pest and disease outbreaks, preserving the genetic resources of associated flora and fauna, and conserving water. To evaluate the effects of drought stress on the ornamental plant Heteropappus altaicus, a two-year experiment (2021–2022) was conducted using a randomized complete block design with three replications. The treatments included three irrigation regimes: a control (no stress), moderate stress (60 mm cumulative evaporation from a Class A pan), and severe stress (90 mm cumulative evaporation). Morphological and physiological parameters were assessed. The results showed significant differences (P ≤ 0.05) among treatments in branch number, leaf count, fresh weight, and plant height. A significant reduction in dry (22.5
Wiltshire's white, Leucoma wiltshirei Collenette, 1938 (Lepidoptera: Erebidae) is a major defoliator of oak forests in Iran, particularly in Fars Province. This study evaluated the efficacy of three native entomopathogenic nematodes (EPNs) Heterorhabditis bacteriophora Poinar, 1976 (Nematoda: Heterorhabditidae), Steinernema borjomiense Gorgadze et al. 2018 (Rhabditida: Steinernematidae), and Oscheius onirici (Torrini et al., 2015) (Rhabditida: Rhabditidae) for the biological control of L. wiltshirei larvae under laboratory and field conditions. Laboratory assays assessed nematode survival and infectivity in water and water-olive oil mixtures at 14 degrees C and 24 degrees C over different post-treatment intervals. The highest infective juvenile (IJ) survival (94.33%) was observed at 14 degrees C on day 1 in the water-based mixture with S. borjomiense, which also maintained 8.33% viability at 24 degrees C after 14 days. Infectivity tests demonstrated significant larval mortality, with H. bacteriophora causing 95% mortality at 14 degrees C on day 7 in the water-olive oil mixture. Mortality was 84% and 45% for S. borjomiense and O. onirici, respectively, under the same conditions. In field trials conducted in 2023 and 2024, nematode suspensions were applied to oak tree trunks to target overwintering larvae. Heterorhabditis bacteriophora produced the highest mortality (51.91% in 2023 and 57.15% in 2024), followed by S. borjomiense (40.21-43.12%) and O. onirici (37.05-38.85%) after 14 days. These results highlight the potential of native EPNs, particularly H. bacteriophora, as effective and environmentally sustainable agents for managing L. wiltshirei in Iranian oak forests.
Understanding the joint influence of geoenvironmental and anthropogenic variables on wildfire occurrence is crucial for developing predictive models that balance accuracy and explainability. Here, we introduce a wildfire susceptibility assessment framework that integrates fuzzy logic with multi-objective evolutionary algorithms (NSGA-II and ENORA) to derive interpretable rules describing how environmental variables are associated with wildfire events. Cohen's d effect-size analysis was used to identify key discriminative variables, while Monte Carlo-based sensitivity analysis (+/- 10% perturbation, 95% confidence) assessed model responsiveness and rule uncertainty. Applied to a fire-prone region in southern Iran, the framework produced fuzzy rules linking wildfire likelihood to specific geoenvironmental and anthropogenic conditions. Effect-size analysis identified rainfall (d = 3.83), topographic wetness index (d = 2.86), slope (d =-2.18), distance to roads (d = 2.11), drought magnitude (d =-2.07), land use/cover (d =-1.79), soil type (d =-1.74), NDVI (d = 1.32), and distance to rivers (d =-1.03) as the most discriminative predictors, whereas curvature, valley depth, aspect, and distance to settlements showed limited influence. The Monte Carlo sensitivity analysis indicated that temperature (0.168), distance to settlements (0.136), drought magnitude (0.116), soil type (0.104), and distance to roads (0.102) were the most dynamically sensitive variables, suggesting that small perturbations in these parameters may substantially influence predicted fire susceptibility. Collectively, the results indicated that wildfire occurrence arose from nonlinear interactions among climatic, hydrologic, and anthropogenic drivers. While the proposed framework is fully reproducible and transferable in methodology, the derived fuzzy rules and calibrated parameters are context-dependent and needed to be recalibrated when applied to other regions or ecosystems.
High-performance transparent polymers are of great interest in the automotive and electronics industries, but conventional plastics lack mechanical strength, while high-performance systems are generally opaque. In this study, polyvinyl alcohol (PVA)-based transparent wood composites were fabricated from beech, maple, and poplar via delignification and vacuum-assisted infiltration. The resulting composites exhibited light transmittance values of 83.5% (beech-PVA), 20.5% (poplar-PVA), and 5.4% (maple-PVA), with corresponding haze values of 95.9%, 95.9%, and 82.9%, respectively. Linear regression models established strong correlations between optical properties and Hunter color parameters: haze versus lightness (R 2 = 0.82) and haze versus yellowness (R 2 = 0.80), enabling targeted optical design. PVA infiltration achieved the lowest yellowness (b = +11 to +13) reported for additive-free transparent wood composites, producing a near-neutral, glass-like appearance. Electron microscopy confirmed complete pore filling and nanoscale PVA penetration into the cell walls, forming a dense hydrogen-bonded network. This interaction produced exceptional viscoelastic behavior: beech-PVA achieved a glass transition temperature of 169.2°C, while maple-PVA exhibited the broadest damping among transparent wood composites (tan δ > 0.27 from 20°C to 95°C). These thermomechanical characteristics, combined with tunable haze through color control, make this material ideal for hot climates requiring heat management and visual comfort. PVA-based transparent wood functions as a natural “smart surface,” paving the way for sustainable, shock-resistant construction materials derived entirely from biological sources.
Subsurface data from Well no. 954, Tabas, east-central Iran, constitute the foundation for an integrated palynological, paleoenvironmental, and paleobiogeographical analysis of the Upper Triassic (Rhaetian) Qadir Member of the Nayband Formation. The assemblage consists of diverse, moderately preserved spores and pollen. Of the latter, such taxa as Falcisporites nuthallensis, Lunatisporites rhaeticus, Ovalipollis ovalis, Ricciisporites tuberculatus, and Araucariacites australis dominate the assemblages. Representatives of such trilete spores as Dictyophyllidites mortonii, Gleicheiniidites senonicus Kyrtomisporis laevigatus, Limbosporites spp., and Lophotriletes bauhiniae, are essentially abundant in the palynofloras examined. Vertical distribution of miospores allows recognition of Dictyophyllidites-Striatella seebergensis-Ricciisporites tuberculatus assemblage zone (Rhaetian). The inferred natural relationships of the sporae dispersae indicate a parental flora derived from, in descending order: Pterophyta, Cycadophyta, Pteridospermophyta, Coniferophyta, Lycopodophyta, Ginkgophyta, and Bryophyta. Fern abundance suggests a moist, warm climate. Sporomorph EcoGroup (SEG) analysis shows dominant lowland/plain communities over upland and coastal/tidal ones, indicating deposition during relatively low sea level in shallow marine conditions. Palynological analysis identifies three palynofacies following Tyson's methodology. Palynofacies I represents very proximal, shallow shelf environments during sea-level fall and regression. Palynofacies II suggests dysoxic to anoxic, restricted shallow-water settings. Palynofacies VI indicates conditions from low-oxygen coastal to anoxic shelf environments. Key proxies—the transparent/opaque AOM ratio, equidimensional/blade-shaped opaque phytoclasts (P1/P2) ratio, and terrestrial/marine (T/M) ratio—support this interpretation. The palynofloras show strong biogeographic affinities with both northern Gondwana and southern Laurasia, highlighting Iran's position as a biogeographic crossroads on the southern margin of Eurasia during the Late Triassic.
