This collective article presents new information about 18 species occurring in 12 Mediterranean countries from the Alboran Sea to the Levantine Sea. Five lessepsian species namely Erugosquilla massavensis, Syrnola fasciata, Plocamopherus ocellatus, Maritigrella fuscopunctata and Siganus javus have spread within 2025 to neighbouring MSFD areas. Another five are here reported as first country records [Polyandrocarpa zorritensis (Malta), Gonioinfradens giardi (Italy), Istiblennius meleagris (Egypt), Epinephelus fasciatus (Israel), Lophocladia trichoclados (Montenegro)]. Cladophora patentiramea has spread from the Levantine to the Aegean Sea, while Pinctada radiata has reached Granada, and C & aacute;diz. The Atlantic fish Enchelycore anatina and Synodus synodus have expanded their distribution to Montenegro and Syria respectively. Three rare native species are reported for first time at country level, while a fourth (Mobula birostris) has made an appearance more than a century after its first Mediterranean record.
Water erosion processes primarily cause soil degradation and environmental issues in Morocco. The Middle Atlas Mountains have faced significant problems related to soil erosion. In addition to the actual increase of this phenomenon, this study aims to (i) evaluate soil erosion dynamics using the Intensity of Erosion and Outflow (IntErO) model, (ii) identify the main environmental factors controlling sediment generation within the Mkhdach Mediterranean headwater catchment, and (iii) validate the model outputs through field monitoring of representative gullies between January 2021 and December 2023. Some representative gullies were monitored to estimate the rate of soil loss in this headwater. To achieve this goal, the study applied the Intensity of Erosion and Outflow (IntErO) method in conjunction with the Geographic Information System (GIS) to assess the soil erosion dynamic in the study area. Field observations were used to analyze the interaction between soil properties and precipitation related to rainfall erosivity. Representative gullies were monitored between January 2021 and December 2023 to assess soil erosion dynamics under varying rainfall conditions. The studied catchment covers an area of approximately 2,537 hectares (> 25 km²) and is characterized by geological formations dominated by marls, red clay, limestone, and shale, which influence soil erodibility and sediment generation within the basin. Consequently, the obtained results indicate that rainfall is characterized by a significant variability at annual and seasonal scales. This variability is in line with the Mediterranean climate’s tendency for irregular rainfall distribution. The modeling results revealed a substantial intensity of soil erosion, with a total estimated sediment production of approximately 417,484.70 m³ yr⁻¹. Considering the catchment’s deposit retention coefficient (Ru = 0.34), only a portion of this material is expected to remain within the basin, while the remainder is effectively exported as sediment yield. Accordingly, the net or “actual” soil loss reaching the outlet was estimated at 143,368.44 m³ yr⁻¹, corresponding to approximately 51.2 Mg ha⁻¹ yr⁻¹ when normalized by basin area. A Pearson correlation matrix of key IntErO parameters revealed strong interdependencies between erosion variables and highlighted the central role of precipitation in soil erosion and sediment generation. Nevertheless, it should be noted that the IntErO model assumes simplified relationships between variables and may have several limitations that can underestimate or generalize complex erosion processes. These findings indicate a high risk of excessive soil erosion compared with other small Mediterranean mountain catchments, mainly due to the basin’s erodible lithology and limited vegetation cover, which together amplify runoff and sediment yield intensity. Gully erosion is a complex process in the studied area, indicating the high intensity of soil loss. This study offers a valuable and unique contribution by combining field data on gully erosion with the IntErO model and GIS techniques to evaluate soil erosion in a Mediterranean mountain area that hasn’t been well researched. Consequently, this study’s results offer substantial understanding of the geographical patterns and factors that influence soil erosion in Mediterranean mountain ecosystems. They will aid decision-makers to mitigate erosion risks through climate-resilient land management policies specifically designed for vulnerable headwater catchments.
Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multi-level governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.
BACKGROUND:Real-time continuous glucose monitoring (RT-CGM) is widely used in patients with type 1 diabetes (T1D) to improve glycemic control by reducing postprandial glucose peaks and hypoglycemic episodes. In addition, traditional biomarkers such as glycated hemoglobin (HbA1c), glycated albumin, and fructosamine provide retrospective estimates of glucose regulation over varying timeframes. This study aimed to evaluate the correlation between these biomarkers and glycemic metrics obtained from two types of RT-CGM systems: an implantable sensor (Eversense E3) and subcutaneously inserted sensors (Dexcom G6 and Guardian 4). METHODS:We analyzed data from 35 patients with T1D: 13 used the Eversense E3 system, and 22 used Dexcom G6 or Guardian 4. Mean blood glucose (MBG) and time in range (TIR) were assessed at multiple time points and correlated with HbA1c, glycated albumin, and fructosamine levels. RESULTS:In the Eversense group, no significant correlation was observed between CGM-derived metrics and any of the biomarkers. Conversely, in the Dexcom/Guardian group, MBG and TIR demonstrated significant correlations with all biomarkers, showing large effect sizes for HbA1c and fructosamine, and medium for glycated albumin. CONCLUSIONS:These findings suggest that the Dexcom G6 and Guardian 4 systems more reliably reflect established biochemical markers of mid- to long-term glucose control, while Eversense may be less consistent in this regard. This highlights the importance of sensor selection when interpreting CGM data for clinical or research applications in diabetes management.
The aim of this study was to characterize multidimensional external-load profiles obtained from sensor-based tracking data over a four-month competitive period in an elite men's handball team and to investigate their associations with the session type, the playing position, and weekly workload fluctuations, as measured by the acute:chronic workload ratio (ACWR). Data were collected from 23 elite players using an ultra-wideband tracking system. Six variables, i.e., total distance, maximum speed, accumulated acceleration load (AAL), the number of exertions, maximum jump height, and the number of jumps ≥0.30 m, were standardized and clustered using k-means (k = 4). The cluster with the highest composite z-score was defined as a high load. The association between weekly density of high-load sessions and the likelihood of an ACWR spike (≥1.30) was tested using logistic regression. Results showed that match sessions were 1.8 times more likely than training sessions to fall into the high-load cluster. Wings and center-backs were significantly more represented in high-load clusters than goalkeepers and pivots. Additionally, when 15% or more of the previous week's sessions were classified as of the high load, the odds of an ACWR spike in the following week increased by 10.7 times. These findings suggest that data-driven (unsupervised) clustering of external-load variables supports early identification of high-risk workload patterns. Monitoring the weekly distribution of high-load sessions may help mitigate fatigue-related maladaptation by enabling proactive, position-specific load management in elite handball.
