Climate change and recurrent extreme climatic events have intensified the vulnerability of water-stressed regions like Tunisia to droughts, severely impact agriculture, the economy, and society. This study analyzes hydrometeorological drought patterns using the Gravity Recovery and Climate Experiment (GRACE) satellitederived Groundwater Drought Index (GGDI), alongside traditional indices, including Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), and Standardized Runoff Index (SRI). A stochastic analysis of monthly SPEI-GGDI values was conducted using a first-order Markov chain model, to investigate regional drought hazards formation, persistence, and evolution. Pearson's correlation coefficient and wavelet coherence were applied to evaluate interactions among indices and their teleconnections with largescale climate patterns. Results reveal persistent droughts, with extreme events exhibiting high stability and low recovery probabilities. The most severe groundwater drought occurred in 2014-2015, averaging a GGDI value of -1.36, while 2002-2003 was the driest based on SPEI, SPI, and SRI, averaging -1.9. Correlation analysis highlights complex interactions between meteorological and hydrological droughts, with GDDI-identified droughts exhibit greater severity in frequency, intensity, and duration, indicating significant anthropogenic influence. El Nino-Southern Oscillation (ENSO) significantly influenced drought evolution, with intense negative phases exacerbating severity. This study highlights the potential of GRACE satellite data for integrated drought monitoring and provides novel insights for developing sustainable drought management strategies in Tunisia.
Biogenic Volatile Organic Compounds (BVOCs) play crucial roles in terrestrial environments, acting as defense compounds against environmental stresses and as chemical cues in species interactions. These roles were mainly highlighted on terrestrial plants whereas marine BVOCs are still understudied except dimethyl sufide (DMS) or isoprene. However, recent research highlights that marine organisms, particularly phytoplankton, and to a lesser extent benthic organisms such as macroalgae, seagrasses, and corals, also produce and emit a larger panel of BVOCs. In this review, we compiled and analyzed articles focusing on BVOCs production and emission by benthic photosynthetic organisms. Our review synthesizes current knowledge on the BVOCs produced or emitted by these species, categorized by compounds classes, geographic location and sampling methods. This synthesis provides a preliminary overview of the chemical diversity among benthic organisms, indicating rich and varied BVOCs profiles that warrants further investigation. Furthermore, we explore the potential physiological and ecological roles of BVOCs in benthic ecosystems, discussing their implications for environmental stress responses and interspecies communication. This review underscores the need for more comprehensive studies to fully understand the ecological significance and chemical complexity of BVOCs in benthic environments.
Internet of Things (IoT) based precision irrigation system has proven to be promising tool for optimizing water use and crop production. In this study, two irrigation water-saving techniques, double-line drip irrigation (DI) and partial-root zone drying (PRD) were assessed on 27-year-old Washington Naval orange trees. Four strategies of irrigation based on crop water requirements (100, 75, 50, and 25% of ETc) were applied in the maturity stage of growth development (phase III). Soil water contents were monitored in real-time using 10HS sensors and the Zentra cloud IoT system. Results showed that the water availability in the soil approaches the TAW threshold for DI-50%, DI-25%, PRD-50%, and PRD-25% treatments, while it remains relatively higher than RAW for the other treatments. Deficit irrigation regimes did not significantly affect the final tree yield and the irrigation water productivity (WPirrig). Nevertheless, PRD mean values were slightly higher than those under DI treatments. Regarding fruit quality parameters, results revealed that the treatments PRD-75%, PRD-50% and PRD-25% yielded significantly higher fruit flesh firmness compared to fully irrigated and DI treatments. Despite the clear decline in titratable acid (TA) trait with increasing stress level, no significant difference among treatments was registered for maturity index (MI). Our results mirror a better adaptation of orange trees to water-saving irrigation under PRD than DI. However, further and deeper research in this direction is required for more efficient irrigation water use, enhancing citrus yield and organoleptic properties.
Litter size records from two lines of Tunisian Barbarine sheep were analysed across parities using an RRM. A total of 2751 and 2562 litter records from the first to the sixth parity from the prolific and the conventional lines, respectively, were included in the analysis. The total number of animals in the pedigree was 1277 for the prolific line and 1102 for the conventional line. The estimation of genetic parameters was based on Bayesian inference under categorical distribution. Fixed effects included the year and month of lambing and a fixed quadratic regression coefficient for the lambing number with Legendre polynomials. The random additive and permanent environmental effects were modelled by second-order Legendre polynomials. Heritability ranged from 0.04 to 0.18 for the prolific line and from 0.17 to 0.39 for the conventional line. Genetic correlations within trait through parities showed a wide range of values, from 0.25 to 0.96 for the prolific line and from zero to 0.93 for the conventional line. Due to the changes in the variances and the genetic correlations different from unity across parities, the use of an RRM is recommended to analyse litter size in the Barbarine sheep.
