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Artemisia sieberi Besser occurs in many parts of the Irano-Turanian floristic region, which is mostly distributed throughout the Iranian plateau, especially in Iran. This study aimed to identify the effect of the soil and topography variables on A. sieberi distribution. We used canopy cover data to fit models using generalized additive models (GAMs). The results showed that the response pattern of A. sieberi along with the gradient of soil clay, soil saturation moisture, soil nitrogen and soil acidity followed the monotonic increase model, and its canopy cover percentage augmented by increasing the values of the factors. Conversely, the A. sieberi canopy cover percentage decreased by increasing the amount of soil sand, bare soil and the geographic aspect. The A. sieberi responses are in contrast to the niche theory. The relationship between the species response pattern and the gradients of soil silt, soil salinity, lime percentage, organic carbon, altitude, land slope, litter, gravel percentage, stone percentage, mean annual precipitation and mean annual temperature followed a unimodal model (consistent with the niche theory). The optimal growth limits for these factors were 32%, 1.75 ds/m, 35%, 1.3%, 2000 m, 43%, 10%, 32%, 250 mm and 15 °C, respectively. Our results highlight that environmental factors, such as soil texture, amount of soil lime, mean annual precipitation, altitude and land slope, had quantifiable effects on the performance of A. sieberi. Our findings could provide useful information for improvement, restoration and conservation programs. However, a further comprehension of the species–environment relationship is needed to predict the effects of climate change on the species habitat. [ABSTRACT FROM AUTHOR]

Knowledge of variations in soil biological and biochemical indicators with grazing and seasonal changes is important for assessing soil quality and required management. Lack of proper management could induce irreversible damage to the soil structure; therefore, a seasonal experiment was carried out in Salook National Park, Iran; arranged in a factorial-based randomized complete block design (RCBD) in all seasons of a year. The study area had three plots including a no-hunting area, national park, and protected area. Our data showed that overgrazing has altered the chemical–physical components of the soil with effects on the soil microbiome. The most affected areas are those subjected to the hunting ban and in the summer season. It could be concluded that low grazing intensity while protecting the soil ecosystem structure would increase the biochemical and biological characteristics of the soil and provide adequate conditions for providing forage to the natural herbivores living in this area. In order to preserve the biological resources of the region, it is strongly recommended that the level of protection be increased, especially in areas where hunting is prohibited. [ABSTRACT FROM AUTHOR]

A species of Orobanche was observed on spiny cocklebur (Xanthium spinosum) for the first time in Iran and tentatively was named IR-Iso.This study was conducted to make a phylogenetic analysis of the Orobanche using 5.8S rRNA region sequences, and also to better understand its sequence pattern. The full-length ITS1-ITS2 region of the new Orobanche isolate was PCR-amplified from the holoparasitic plant parasitizing X. spinosum. Sequences of the amplicons from the isolate were 100% identical but differed by 5.6–6.7% from most homologous GenBank accessions to 37.9% divergence from distant species. The analysis of the molecular variance showed that variation between-population (61.9%, SE = 0.04) was larger than within-population. Neighbor-joining analysis placed the Iranian isolate in the same clade as most of the Orobanche and Phelipanche species. The isolate was more closely related to Orobanche aegyptiaca (from China), and this was confirmed by using a structure analysis. However, complementary analyses showed that the Iranian isolate has a unique nucleotide substitution pattern, and hence it was considered as an ecotype of O. aegyptiaca (ecotype Alborzica). In this paper we report on the association between this new ecotype of Orobanche and X. spinosum. [ABSTRACT FROM AUTHOR]

Echinacea is a perennial plant that is used for its phytotherapeutic potential. Echinacea crops are often affected by invasive weeds. One of the most effective strategies in weed control is the use of chemicals such as herbicides. However, herbicides also affect the physiological and morphological processes of Echinacea. For this reason, the aim of this study was to determine the effects of different dosages (0, 250, 500, 750, 1000, and 1250 g ha−1) of the postemergent herbicide metribuzin on some morphological and physiological characteristics of Echinacea purpurea and Echinacea angustifolia collected from different locations in Iran (E. purpurea from the Shiraz and Isfahan regions and E. angustifolia from the Ardestan and Kazerun regions). Application of metribuzin decreased leaf dry weight for both Echinacea species at high doses (750 and 1250 g ha−1). At high metribuzin dose (1250 g ha−1), E. purpurea Shiraz leaves showed an increase in MDA (malondialdehyde) up to 9.14, while in other species the MDA content was lower. Minimum and maximum fluorescence increased at both the registered dosage (500 g ha−1) and at high doses (750–1250 g ha−1) of metribuzin treatments in both species. The Fv/Fm (maximum quantum yield) value was reduced in herbicide treated species, compared to the control, starting at the 250 g ha−1 dose, and was lowest at 750 g ha−1 dose. The results of this study indicate that metribuzin has adverse effects on the physiology and morphology of Echinacea species at dosages above 500 g ha−1. [ABSTRACT FROM AUTHOR]

The aims of this research are (i) to compare random forest (RF), boosted regression tree (BRT), and multinomial logistic regression (MnLR) models to prepare the prediction maps of soil great group and subgroup levels, (ii) determination of the most important environmental covariates influencing the production of digital soil mapping (DSM) in an arid climate, (iii) to evaluate the efficiency of spectra indices extracted from Sentinel-2A digital images and data capability of ALOS-PALSAR radar data, and (iv) investigating the effect of sub-surface genetic horizons in the modeling of different types of soil map classes distribution. The principal component analysis method was employed to select the best set from the pool of environmental covariates (n = 46) such as geomorphometric parameters (GPs), RS indices, and diagnostic soil properties (DSP). The relative importance results indicate that Gypsic (GYP) subsurface horizon, standardized height (StH), slope length (SL), and normalized different vegetation index (NDVI) had an important role in the prediction of soil classes compared to the other selected covariates. DSM methodology was used in this research by incorporating of RF model and representative soil-forming factors that can be used for preparing the maps of soil classes in low-relief areas with a similar soil-landscape relationship. Totally, in this study places a spotlight on the profound impact of sub-surface genetic horizons, shedding light on their pivotal role in accurately modeling soil class distributions. These findings not only advance our comprehension of soil variability in arid regions but also hold immense implications for the burgeoning field of pedometrics. [ABSTRACT FROM AUTHOR]