The concentrations of organophosphate flame retardants in the environment are increasing due to the growing volume of their production and usage. Trichloropropyl phosphate (TCPP), which is an organophosphorus ester (OPE), can be found in air, water, and soil. A significant amount of OPEs enters water bodies. Aquatic plants have been understudied in terms of their ability to accumulate organic esters. Meanwhile, plants are an important primary link in food chains. They play a significant role in the transformation and migration of organic compounds within ecosystems. The accumulation of TCPP in three species of aquatic plants, Lemna minor L., Ceratophyllum demersum L. and Elodea canadensis Michx, was studied experimentally at initial ether concentrations of 100, 500, and 1000 ng L–1. All plants accumulated TCPP. The maximum accumulation coefficient (BCF) was determined for all studied species at the lowest concentration of TCPP (100 ng L–1). In water with higher concentrations of TCPP, the BCF values decreased. With a tenfold increase in TCPP concentration, the BCF value decreased the least in C. demersum (by 17
Facing unprecedented challenges in biodiversity conservation due to global environmental changes and human activities, traditional survey methods are limited by inefficiency, high costs, and poor detection of rare/cryptic species. Environmental DNA (eDNA) technology, extracting and analyzing genetic material from environmental matrices (water, soil, etc.), has revolutionized monitoring. With non-invasiveness, ultra-high sensitivity and high throughput, it boosts detection of elusive/endangered species and enables large-scale spatiotemporal biodiversity research. Its applications cover three core areas: targeted detection of single species (e.g., endangered/invasive taxa), multi-species community profiling, and population genetic analysis. It also assesses ecosystem health, guides ecological restoration, and warns of invasive species for informed management. However, bottlenecks exist: no standardized protocols across matrices, data interpretation uncertainties (e.g., eDNA concentration vs. species abundance), and incomplete regional reference databases. Future priorities include matrix-specific standardized workflows, integrating mechanistic models to correct artifacts, and curating quality regional databases, to drive its adoption and build intelligent real-time monitoring systems for conservation.
This study systematically identified the key drivers of Myrmeleotettix palpalis habitat distribution using integrated machine learning models and ecological mechanism analysis. Through Pearson correlation matrix-based feature selection and hyperparameter optimization, we retained 15 environmental variables across topographic, climatic, and surface parameter dimensions. Random Forest and MaxEnt models were employed to quantify variable importance and stability, revealing a “tripartite regulatory framework”: (1) Topographic factors (Aspect, DEM) mediate microclimate through solar radiation redistribution; (2) Climatic factors (Bio18: warmest quarter precipitation, Bio4: temperature seasonality) serve as core energy-water suppliers; (3) Surface parameters (soil sand content, land use) constitute the resource foundation. The optimized MaxEnt model exhibited excellent performance (AUC = 0.966), identifying optimal habitats concentrated in the central-eastern Inner Mongolia steppe (3.67 × 105 km2) with a critical precipitation threshold (Bio18 > 320 mm). Our composite feature evaluation framework (importance-weighted 0.6 + stability-weighted 0.4) reliably prioritized ecologically robust drivers (Aspect composite score = 0.94, Bio18 = 0.81). These findings provide scientific targets for precision locust control and ecological intervention in grassland ecosystems.
The goal of the study was to conduct histological and morphometric examination on kidney tissue in small mammals inhabiting the Norilsk-Pyasino ecosystem. Three locations were identified at different distances from the industrial facilities of the Norilsk mining-metallurgic complex (and smelting company). Thirteen mammals were captured from three sites, including 10 males and 3 females. Kidney tissues of wild mouse-like rodents (Myomorpha) were examined by histological and morphometric methods. Hematoxylin-eosin was used for staining the histological sections of the kidneys. The following morphometric parameters were determined in the kidney histological section: (1) percentage of non-sclerotic renal glomeruli (
The dynamics of the abundance and distribution patterns of mycelial fungi, yeasts, and bacteria have been studied in the soil of a bilberry–sphagnum birch forest in Yaroslavl oblast, taking into account the biogeochemical background, and the contribution of fungi and bacteria to the net ammonification process is determined using inhibitor analysis. Bacteria are predominant in the birch forest soil (43.5–98.7 NH_4^ + , between the C/N ratio and CO2–C emission, and between yeast and soil moisture. The dynamics of the numbers of fungi, yeasts, and bacteria in the upper soil horizon are close and negatively correlated with temporary changes in ammonification (r = –0.86…–0.97). In the AT1 horizon, the contribution of fungi to ammonification prevails over bacteria, 208 ± 5 and 121 ± 3 mg N/100 g. In the peaty layer (AT2 horizon), a slight predominance of fungal activity over bacteria is noted: 98 ± 4 and 72 ± 4 mg N/100 g. In the eluvial part of the profile (the A2 horizon), a similar contribution of these groups is obtained, amounting to 8.7 ± 0.4 and 9.7 ± 0.5 mg N/100 g.
