Search Results (33)

In coastal wetlands, Tamarix chinensis often occurs as patches intermixed with Phragmites australis, Suaeda salsa, and saline–alkaline bare soil. This mixed distribution makes tamarisk prone to omission in medium-resolution remote sensing classification, while the recall of the target species is often masked by a relatively high overall accuracy. In this study, we focused on the Yellow River Delta National Nature Reserve and developed a multi-source feature set using summer 2025 Sentinel-2, Sentinel-1, and UAV/GPS data, comprising spectral, SAR, phenological, and red-edge-oriented features. To enhance the separability between tamarisk and co-occurring herbaceous vegetation, we introduced a red-edge–vegetation-cover coupling feature (RE_cov) based on their contrasting responses in the red-edge region. Within an XGBoost framework, we evaluated the marginal contribution of this feature using feature ablation, replacement, and spatial block cross-validation. The full feature set achieved an AUC of 0.8042, a recall of 0.9340, and an overall accuracy of 0.8194 on an independent test set. Ablation and replacement experiments showed that the red-edge-oriented features contributed to both model separability and tamarisk recall, and this contribution remained evident under spatial block validation. We further converted the pixel-level extraction results into local tamarisk density grades, revealing a pattern of a few clustered cores embedded within a broad low-density background. These results suggest that target-species-oriented red-edge–vegetation-cover coupling features can improve tamarisk recall while maintaining acceptable overall accuracy, providing a spatial product to support zoned patrol and management in protected coastal wetlands. Full article

The genus Myricaria is one of the four genera within the Tamaricaceae family. It comprises 13 species distributed across Eurasia. Phytochemical studies carried out on Myricaria plants revealed the presence of flavonoids (including rare, sulfated derivatives), tannins, phenolic acid derivatives, triterpenoids, steroids, and alkanediols. Studies on the extracts and compounds isolated from the described to date have demonstrated various biological activities, including antioxidant, anti-inflammatory, cytotoxic, antimicrobial, analgesic, antinociceptive, cholinergic, and glucose absorption reducing properties. This work provides a comprehensive overview of the botanical and detailed phytochemical characteristics, ornamental value, pharmacological properties, and traditional uses of the Myricaria genus representatives. The article fills a longstanding gap in the literature as no other integrative description is currently available. Full article

The mealybug Trabutina serpentina has two generations in southeastern Kazakhstan. The second instars of the second generation overwinter. Between 2003 and 2005, for the second time in 50 years, a large reproduction of this pseudococcid was observed in the Ile River valley. The Kazakhstan populations of this species should be removed from the list of potential biocontrol agents for Tamarix ramosissima considered suitable for use in the USA, due to its demonstrated potential to harm American populations of T. aphylla, as shown in our host-specificity tests. Nonetheless, the species could be used for biological control of tamarisk in South Africa, Australia, and other countries, given its narrow host range, which excludes beneficial species in these regions. Full article

The forest soil carbon pool plays a vital role in terrestrial ecosystems, being of great significance for maintaining global balance, regulating the global carbon cycle, and facilitating ecological restoration. Shandong Changyi Marine Ecological Special Protection Area is the only state-level marine special protection area in China with tamarisk as the main object of protection, and it is the largest continuous and the best preserved natural tamarisk forest distribution area on the mainland coast of China. Compared to other forested areas, research on the spatial distribution of SOC at the core area in coastal Tamarix forests’ inland side appears to be relatively scarce. Based on this, this paper takes the core area of the Changyi National Marine Ecological Special Protection Zone, located on the southern coast of Laizhou Bay, as the research subject, based on the potassium dichromate oxidation-external heating, one-way ANOVA, and Bonferroni methods, analyzing the spatial distribution of the SOC content inland of coastal Tamarix forests. The research yielded the following conclusions: (1) The surface layer (0–10 cm) contributes significantly to the total SOC content within a 0–60 cm depth, accounting for at least 31% and shows notable surface accumulation. (2) The combined SOC content in the surface and subsurface layers (10–20 cm) accounts for at least 50% of the total SOC content within a 0–60 cm depth, indicating the dominance of these two soil layers in carbon storage. (3) The SOC content decreases with the soil depth at all six sampling points within the 0–60 cm range, with a marked drop from 0–10 cm to 10–20 cm. (4) One-way ANOVA and multiple comparisons reveal that the soil depth significantly affects the SOC distribution, particularly between the surface and 20–30 cm layers (p < 0.001), indicating high robustness and statistical significance. (5) Horizontally, the total SOC at 0 m is 45% lower than at 2 m in the 0–60 cm layer. The SOC in the 0–20 cm layer fluctuates significantly with distance from the shrub trunk, while the SOC in the 30–60 cm layers is low and stable, with minimal variations with depth. In addition, this study found that the SOC content in the core area of the protected area is lower than that in the common forest ecosystem. In the future, scientific ecological restoration projects and management protection methods should be used to improve soil’s carbon storage and carbon sink capacity. These findings not only validate the patterns of SOC’s spatial distribution in coastal Tamarix forest wetlands but also provide a scientific basis for carbon assessment and the formulation of ecological protection measures in coastal wetlands. Full article

Phosphorus (P) is a crucial limiting nutrient in soil ecosystems, significantly influencing soil fertility and plant productivity. Soil microorganisms adapt to phosphorus deficiency and enhance soil phosphorus effectiveness through various mechanisms, which are notably influenced by land use practices. This study examined the impact of different land use types (long-term continuous maize farmland, abandoned evolving grassland, artificial tamarisk forests, artificial ash forests, and wetlands) on soil phosphorus-cycling functional genes within the Tanyang Forest Farm in a typical region of the Yellow River alluvial plain using macro genome sequencing technology. The gene cluster related to inorganic phosphorus solubilization and organic phosphorus mineralization exhibited the highest relative abundance across different land use types (2.24 × 10⁻³), followed by the gene cluster associated with phosphorus transport and uptake (1.42 × 10⁻³), with the lowest relative abundance observed for the P-starvation response regulation gene cluster (5.52 × 10⁻⁴). Significant differences were found in the physical and chemical properties of the soils and the relative abundance of phosphorus-cycling functional genes among various land use types. The lowest relative abundance of soil phosphorus-cycling functional genes was observed in forestland, with both forestland types showing significantly lower gene abundance compared to wetland, farmland, and grassland. Correlation analysis and redundancy analysis (RDA) revealed a significant relationship between soil physicochemical properties and soil phosphorus-cycling functional genes, with ammonium nitrogen, organic carbon, total nitrogen, and pH being the main environmental factors influencing the abundance of these genes, explaining 70% of the variation in their relative abundance. Our study reveals land use’s impact on soil phosphorus-cycling genes, offering genetic insights into microbial responses to land use changes. Full article

The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic vegetation under the influence of climate change and human activities, and exploring their potential distribution areas, is crucial for maintaining ecological security in saline regions. This study focuses on Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya, integrating geographic information systems, remote sensing, species distribution models, and landscape ecological risk (LER) theories and technologies. An optimized MaxEnt model was established using the ENMeval package, incorporating 143, 173, and 213 distribution records and 13 selected environmental variables to simulate the potential suitable habitats of these three Tamarix species. A quantitative assessment of the spatial characteristics and the area of their potential geographical distribution was conducted. Additionally, a landscape ecological risk assessment (LERA) of the highly suitable habitats of these three Tamarix species was performed using land use data from 1980 to 2020, and the results of the LERA were quantified using the Landscape Risk Index (LERI). The results showed that the suitable areas of Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya were 9.09 × 10⁵ km², 6.03 × 10⁵ km², and 5.20 × 10⁵ km², respectively, and that the highly suitable habitats for the three species were concentrated in flat areas such as plains and basins. Tamarix austromongolica faced increasing ecological risk in 27.22% of its highly suitable habitat, concentrated in the northern region, followed by Tamarix chinensis in 16.70% of its area with increasing ecological risk, concentrated in the western and northern highly suitable habitats; Tamarix chinensis was the least affected, with an increase in ecological risk in only 1.38% of its area. This study provides valuable insights for the protection of halophytic vegetation, represented by Tamarix, in the context of China’s national land development. Full article

The endmember spectrum method can improve image classification quality based on the spectral features of pure pixels in remote sensing images. The CART (Classification and Regression Tree) is a powerful machine learning algorithm that can also be used for remote sensing image classification. In this study, the Tamarix chinensis forest in the Changyi National Marine Ecological Special Reserve in Shandong Province was taken as the research object, and the endmember spectrum method and the CART decision tree method were used to compare and analyze the results of land-use/cover-type classification extraction. In the extraction process, the land use/cover types of the Tamarix forest in the study area were first divided into forested land types such as high-density forest land, medium-density forest land, and low-density forest land, as well as non-forested land types such as water bodies, roads, dams, buildings, and bare soil. Through analysis, the following conclusions could be drawn: while the overall forest cover of the Tamarix forest is high, there is still some room for further afforestation and ecological restoration in the protection area; from the results of land-use/cover extraction results based on the endmember spectrum method in the study area, it can be seen that this method has better results when extracting well-grown forested land, such as high-density Tamarix chinensis forests and medium-density Tamarix chinensis forests, and poorer results when extracting non-forested land, such as low-density tamarisk forests, roads, buildings, dams, and water bodies; from the results of land use/cover extraction based on a CART decision tree in the study area, it can be seen that this method is more effective when extracting non-forested land, such as roads, buildings, dams, and water bodies, but less effective when extracting forested land, such as high-density Tamarix chinensis forests, medium-density Tamarix chinensis forests, and low-density Tamarix chinensis forests. The relevant research results and conclusions of this study can provide some reference for the classification and extraction of large-scale shrub forest cover types based on remote sensing images. Full article

Tamarisk witches’ broom, yellowing, and little leaf symptoms were observed during 2018–2023 surveys of rural deserts in central regions of Iran with the highest disease incidence up to 72% in Chah Afzal (Yazd province). A verification of the presence and identity of phytoplasmas associated with these symptoms was then performed. Tamarisk tree branch cuttings obtained from symptomatic plants sprouted up to 90.3% but with 15–25 days’ delay compared to the asymptomatic ones and showed internode shortening and witches’ broom, while the branch cuttings from asymptomatic plants had normal growth and sprouted up to 97.8%. Phytoplasma transmission by dodder bridges to periwinkle did not succeed, while nested polymerase chain reaction on the phytoplasma ribosomal gene followed by RFLP and phylogenetic analyses revealed the presence of ‘Candidatus Phytoplasma asteris’, ‘Ca. P. australasiae=australasiaticum’, and ‘Ca. P. trifolii’ (ribosomal subgroups 16SrI-B, 16SrII-D, and 16SrVI-A, respectively) in the samples from symptomatic plants only. Further amplifications were performed on selected phytoplasma-positive samples on tuf and secA genes, and the produced sequences indicated the presence of mixed phytoplasma infection in some of the samples. In particular, in the tuf gene, a mixed infection of ‘Ca. P. australasiae=australasiaticum’ and ‘Ca. P. trifolii’ was detected, while in the secA gene, the presence of ‘Ca. P. asteris’ or ‘Ca. P. tritici’ strains was identified. The first-time detection of diverse phytoplasma strains in symptomatic T. aphylla suggests that this species represent a relevant source of infection for the agricultural crops and for landscape plants especially when temperature allows insect vector transmission, and therefore, it represents a risk in every environment especially in the frame of climatic changes. Full article

Tamarisk is an invasive evergreen shrub native to arid regions of Africa and Eurasia and is considered a weed in some countries with dry climates. The complex of gall mites from tamarisks includes fourteen species from four genera of the family Eriophyidae. We reinvestigated the type species of the genus Dicruvasates, D. tamaricis from Egypt, described D. ngubani n. sp. from Tamarix usneoides from South Africa, and revised the generic concept of Dicruvasates. This genus possesses cuticular plates marking longitudinal opisthosomal ridges typical of various phyllocoptine genera, e.g., Echinacrus. We sequenced three genes of Dicruvasates and Phyllocoptes mites from Tamarix and Echinacrus from Frangula, combined our sequences with the data from GenBank, and performed single-gene phylogenetic analyses. All analyses inferred the following: (1) a transcontinental clade Tam comprising Dicruvasates + Aceria + Phyllocoptes from Tamarix; (2) Echinacrus distantly related to Dicruvasates, suggesting the homoplastic nature of the cuticular plates on the opisthosomal ridges, and (3) polyphyly of the genera Aceria and Phyllocoptes. We also investigated partially cleared specimens of Dicruvasates under CLSM and, for the first time, visualized a well-developed anal secretory apparatus (ASA) in the immatures of gall mites, which was previously shown to be a specialized system evolved in Eriophyoidea for silk production. We hypothesize that the ASA contributes to finding nymphs by conspecific males and advocate for the importance of the future molecular biology studies of gall mite silk for developing new methods for controlling mites based on the knowledge of their ecology, behavior, and silk gene genetics. Full article

What represents a water source for the ecological restoration of a plant in an arid region is still up to debate. To address this issue, we conducted an in situ experiment in the Ulan Buh Desert of China, to study desert plants absorbing atmospheric water vapor. We selected Tamarisk, a common drought-salt-tolerant species in the desert, for ecological restoration as our research subject, used a newly designed lysimeter to monitor precipitation infiltration, and a sap flow system to track reverse sap flow that occurred in the shoot, branch, and stem during the precipitation event, and observed the precipitation redistribution process of the Tamarisk plot. The results showed that Tamarisk indeed directly absorbs precipitation water: when precipitation occurs, the main stem, lateral branch, and shoot all show the signs of reversed sap flow, and the reversed sap flow accounted for 21.5% of the annual sap flow in the shoot and branch, and 13.6% in the stem. The precipitation event in the desert was dominated by light precipitation events, which accounted for 81% of the annual precipitation events. It was found that light precipitation can be directly absorbed by the Tamarisk leaves, especially during nighttime or cloudy days. Even when the precipitation is absent, it was found that desert plants can still absorb water from the unsaturated atmospheric vapor; even the absorbed atmospheric water vapor was transported from the leaves to the stem, forming a reversed sap flow, as a reversed sap flow was observed when the atmospheric relative humidity reached 75%. This study indicated that the effect of light precipitation on desert plants was significant and should not be overlooked in terms of managing the ecological and hydrological systems in arid regions. Full article

Many management practices have been implemented to control non-native saltcedar (Tamarix spp.) in the Southwestern U.S. riparian areas. These management practices include herbicide application, mechanical and biological control. Despite these methods have had some success, they are not cost-efficient and some cases not easy to apply and can create environmental harm. In this study, we use a different approach where the mowing of saltcedar is timed according to the trend of evapotranspiration (ET) rates. The approach suppresses saltcedar growth, reduces ET loss, allows native vegetation to flourish, and eventually creates a healthy and diverse plant community in riparian areas. In an experimental study from 2010–2013, saltcedar was managed by mowing in a managed riparian area in New Mexico, USA. The timing of mowing was based on the observation of ET rates which were measured using the eddy covariance method. Normalized Difference Vegetation Index (NDVI) was calculated using Landsat imagery to observe any changes in vegetation of saltcedar before and after mowing and its correlation with ET. During the four years of measurement, it was observed that the timing of mowing led to a suppression of saltcedar, allowing the undergrowth of low water-consuming native grasses and other shrubs to thrive. Nonlinear mixed effects models of years of evapotranspiration during the season showed a significant reduction in ET in 2013 compared to the baseline year of 2010 across the growing stages, especially stage 2 (intercept of −2.0871 with p < 0.001). A reduction in ET of 32% from 1209 mm to 818 mm (difference of 391 mm) was observed between 2010 and 2013. This study showed that the best time to suppress saltcedar and allow native plants to reestablish, is to mow it before it breaks dormancy, at the peak and late parts of the growing season. Mowing can be discontinued once the native plants have been established. Full article

The Yellow River Delta wetland boasts a diverse range of vegetation species and harbors an ecosystem that is both sensitive and fragile, so it is of great practical significance to accurately extract the vegetation information and analyze the spatial and temporal changes of this region. Based on the hyperspectral image data of Zhuhai-1, this study selected the characteristic bands through the continuum removal method. It combined these spectral attributes with index-based characteristics, utilizing the random forest algorithm to classify prevalent vegetation types while subjecting the outcomes to thorough analysis. It was shown that (1) when integrating spectral features, red edge indices, water indices, and vegetation indices to classify five distinct vegetation types in the Yellow River Delta during 2020 and 2022, the random forest classification algorithm showed higher classification accuracy, and the study achieved commendable overall classification accuracy rates and Kappa coefficients of 85.92% and 0.84, and 86.25% and 0.84, respectively. (2) In 2020 and 2022, the distribution of vegetation in the Yellow River Delta exhibited the following order: Suaeda glauca > Phragmites > Spartina alterniflora > Tamarisk > Typha orientalis Presl. With the exception of Spartina alterniflora, all categories of vegetation witnessed an increase in their distribution areas. Phragmites experienced the most significant growth, with an area expansion of 9.42%. (3) The ecological restoration and management measures taken in the Yellow River Delta have proven notably effective. The proportion of Spartina alterniflora within the vegetation decreased by 3.45%, the native vegetation showed a resurgence, the distribution pattern of vegetation communities moved toward stability, and the total area of vegetation in the study area exhibited an upward trajectory. Full article

In hyper-arid regions, soil moisture’s role in ecohydrological processes can differ significantly from that in arid or semi-arid ecosystems. We investigated the spatial–temporal dynamics of soil moisture and its relationship with groundwater depths in a 200 m × 300 m phreatophytic tamarisk stand in the lower basin of the Tarim River, a hyper-arid zone in China. Soil moisture profiles, from the surface to the water table, were derived using drilling and oven-drying techniques. Over a three-year period, the soil moisture at multiple depths was continuously monitored in a specific plot using nine frequency domain reflectometry (FDR) sensors. Our results indicate a correlation between horizontal variations in soil moisture and groundwater depths (GWDs). Nevertheless, anomalies in this correlation were observed. Variations in horizontal soil moisture were strongly influenced by the clay content in the soil, with finer soils retaining more moisture. Despite varying GWDs, soil moisture profiles remained consistent, with no distinct correlation between them. Soil moisture exhibited stability across layers, with noticeable changes only adjacent to the water table. These results imply that in hyper-arid environments, soil texture primarily governs soil moisture distribution. However, the limited spatial and temporal scopes in our dataset, constrained by the region’s inhospitable conditions, necessitate further investigation. Future work should prioritize amalgamating diverse data sources to devise a region-specific soil moisture model for in-depth analysis of hyper-arid regions. Full article

Populus euphratica and Tamarix chinensis hold significant importance in wind prevention, sand fixation, and biodiversity conservation. The precise extraction of these species can offer technical assistance for vegetation studies. This paper focuses on the Populus euphratica and Tamarix chinensis located within Daliyabuyi, utilizing PointCNN as the primary research method. After decorrelating and stretching the images, deep learning techniques were applied, successfully distinguishing between various vegetation types, thereby enhancing the precision of vegetation information extraction. On the validation dataset, the PointCNN model showcased a high degree of accuracy, with the respective regular accuracy rates for Populus euphratica and Tamarix chinensis being 92.106% and 91.936%. In comparison to two-dimensional deep learning models, the classification accuracy of the PointCNN model is superior. Additionally, this study extracted individual tree information for the Populus euphratica, such as tree height, crown width, crown area, and crown volume. A comparative analysis with the validation data attested to the accuracy of the extracted results. Furthermore, this research concluded that the batch size and block size in deep learning model training could influence classification outcomes. In summary, compared to 2D deep learning models, the point cloud deep learning approach of the PointCNN model exhibits higher accuracy and reliability in classifying and extracting information for poplars and tamarisks. These research findings offer valuable references and insights for remote sensing image processing and vegetation study domains. Full article

Tuberculosis (TB) remains the second leading cause of death globally from a single infectious agent, and there is a critical need to develop improved imaging biomarkers and aid rapid assessments of responses to therapy. We aimed to utilize radiomics, a rapidly developing image analysis tool, to develop a scoring system for this purpose. A chest X-ray radiomics score (RadScore) was developed by implementing a unique segmentation method, followed by feature extraction and parameter map construction. Signature parameter maps that showed a high correlation to lung pathology were consolidated into four frequency bins to obtain the RadScore. A clinical score (TBscore) and a radiological score (RLscore) were also developed based on existing scoring algorithms. The correlation between the change in the three scores, calculated from serial X-rays taken while patients received TB therapy, was evaluated using Spearman’s correlation. Poor correlations were observed between the changes in the TBscore and the RLscore (0.09 (p-value = 0.36)) and the TBscore and the RadScore (0.02 (p-value = 0.86)). The changes in the RLscore and the RadScore had a much stronger correlation of 0.22, which is statistically significant (p-value = 0.02). This shows that the developed RadScore has the potential to be a quantitative monitoring tool for responses to therapy. Full article