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Coastal wetlands can have exceptionally large carbon (C) stocks and their protection and restoration would constitute an effective mitigation strategy to climate change. Inclusion of coastal ecosystems in mitigation strategies requires quantification of carbon stocks in order to calculate emissions or sequestration through time. In this study, we quantified the ecosystem C stocks of coastal wetlands of the Sian Ka'an Biosphere Reserve (SKBR) in the Yucatan Peninsula, Mexico. We stratified the SKBR into different vegetation types (tall, medium and dwarf mangroves, and marshes), and examined relationships of environmental variables with C stocks. At nine sites within SKBR, we quantified ecosystem C stocks through measurement of above and belowground biomass, downed wood, and soil C. Additionally, we measured nitrogen (N) and phosphorus (P) from the soil and interstitial salinity. Tall mangroves had the highest C stocks (987±338 Mg ha(-1)) followed by medium mangroves (623±41 Mg ha(-1)), dwarf mangroves (381±52 Mg ha(-1)) and marshes (177±73 Mg ha(-1)). At all sites, soil C comprised the majority of the ecosystem C stocks (78-99%). Highest C stocks were measured in soils that were relatively low in salinity, high in P and low in N∶P, suggesting that P limits C sequestration and accumulation potential. In this karstic area, coastal wetlands, especially mangroves, are important C stocks. At the landscape scale, the coastal wetlands of Sian Ka'an covering ≈172,176 ha may store 43.2 to 58.0 million Mg of C.

Mangrove deforestation threatens to release large stores of carbon from soils that are vulnerable to oxidation. Carbon stored in deep soils is not measured in national carbon inventories. Thus, policies on emission reductions have likely underestimated the contribution of mangrove deforestation to national emissions. Here, we estimate that emissions from deforestation and degradation of mangroves in Mexico are 31 times greater than the values used to determine national emission reduction targets for the Paris Agreement. Thus, Mexico has vastly undervaluated the potential of mangrove protection to reduce its emissions. Accounting for carbon emissions from mangrove soils should greatly increase the priority of mangrove forests to receive funding for protection under carbon trading programs.

Research into renewable energy is an active field of research, with photovoltaic and wind being the most representative technologies. A promising renewable energy source is Ocean Thermal Energy Conversion (OTEC), based on the temperature gradient of seawater. This technology has two contradictory features, as its efficiency is relatively low while, on the other hand, its energy source is almost unlimited. OTEC research has focused on optimizing energy extraction, with different techniques having been used for this purpose. This article presents a review of the advances and applications of OTEC technology around the world. Throughout the document, the different uses of deep seawater are analyzed; further, the current systems which generate energy through the marine temperature gradient are reviewed, and the main advantages and disadvantages of each method are highlighted. The technical operations, construction variations, and the projects that have been developed around the world and those which are in the planning phase are also detailed. The two main conclusions are that this technology is still under development, but it is quite promising, especially for regions with little access to drinking water. Second, given the high implementation costs and low conversion efficiency, the development of this technology must be sponsored by governments.

ObjectiveTo assess the true efficacy of direct acting antiviral (DAA) therapy in real-world clinical practice, taking into account those patients that do not complete therapy or the necessary follow-up to establish sustained viral response (SVR).MethodsRetrospective data collection of 261 genotype 1 HCV-infected patients, treatment naïve or treatment experienced, treated with ledipasvir/sofosbuvir combination therapy at an academic medical center. All patients received individualized teaching and counseling prior to starting therapy stressing importance of compliance with laboratory monitoring and treatment completion. Intention to treat SVR rates (ITT-SVR) and per-protocol SVR rates (PP-SVR) were calculated. Chi-squared test was used to compare the number of subjects lost to follow-up in the treatment-naïve vs. treatment-experienced groups. Characteristics of noncompliant patients were compared to compliant patients.ResultsITT-SVR rates for the entire cohort were 74%, significantly lower than the 95% PP-SVR rate for the compliant patients (p < 0.001). ITT-SVR was lower in treatment-naïve patients compared to treatment-experienced patients (68% vs. 86%). Among the entire cohort, 22% of patients either discontinued therapy prematurely (7%) or did not return for SVR assessment (15%). Failure to complete therapy or return for SVR assessment was statistically more common among treatment-naïve patients compared to treatment-experienced patients (28% vs. 11%, p = 0.0016).ConclusionsThere is a significant rate of noncompliance among patients treated with DAA in real-world clinical practice despite pre-treatment education efforts. The ITT-SVR rates observed in clinical practice were significantly lower than those reported by clinical trials, and this difference was most pronounced among treatment-naïve patients.

Among the set of phenological traits featuring mangrove ecosystems, litterfall production stands out with marked intra-annual and longer-term variation. Furthermore, mangrove forests resilience is one of the most important ecological attribute, reconciling the juxtaposed terrestrial and marine environment such transitional systems occupy. However, world’s mangroves are nowadays facing recurrent climatic events, reflected in anomalies depicted by major drivers, including temperature and precipitation. This physical-environmental setting may either constrain or favor overall forest productivity. A combination of time series analysis (spectral density and cross-correlation techniques) and statistical model fitting (General additive model) was implemented to explore trends in total litterfall of a well-developed mangrove forest in southeastern Gulf of Mexico (Celestun Lagoon, SE Mexico) and potential association with the varying behavior of temperature (°C) and precipitation (mm month -1 ), highlighting their anomalies. The results are consistent with a synchronous response between litterfall production and climatic variables (mean monthly temperature and total monthly precipitation). Concurrent peak litterfall production in Celestun lagoon with high temperatures and precipitation occurred during June and October, featuring a two-month time lag for the response time. More than half of the litterfall anomalies (53.5%) could be reflecting either multiple sources of climatic anomalies (maximum, minimum, and monthly average temperature and monthly total precipitation) or single point events (cyclone landfall). This relationship dynamics showed an interannual persistence (1999–2010). The structure portrayed by the litterfall time-series was not unequivocally related to climatic anomalies. Arguably, climatic anomalies behave with different intensities and even may exhibit complex interactions among them. The study of anomalies provides a baseline for a better grasp of: i) mangrove anomalies responses and ii) their vulnerability to these extremes.

In this study, we report for the first time an exploration of the physicochemical characteristics and the prokaryotic diversity of three different types of microbial mats from karstic habitats located in Sisal, Progreso and Ría Lagartos, in the Yucatan Peninsula, Mexico. Our results showed that lift-off mats were found in the lower salinity (2.2%) area (Sisal), while flat and pustular mats were detected in hypersaline (6–9%) sites (Progreso and Ría Lagartos). Notably, some of these microbial mat structures were in close proximity to mangrove forest ecosystems with both degraded and restored regimes. XRD analysis revealed different mineral compositions of the mats; however, aragonite, calcite, and halite were commonly found in all samples studied. High-throughput sequencing of the 16S rRNA gene identified differences in microbial communities across the different mat types, and statistical analyses revealed that salinity, redox potential, and temperature were significant factors in explaining the variance of the prokaryotic assemblages. Microbial groups identified in this study include those known to be important in the biogeochemical cycling of key elements, such as carbon, nitrogen, and sulfur. Interestingly, the community composition of flat and pustular mats from Progreso was similar, with Bacteroidia, Anaerolineae, and Phycisphaerae being the most abundant microbial groups in flat mats; and Bacteroidia, Anaerolineae, and Alphaproteobacteria dominating pustular mats. By contrast, flat mats from Ría Lagartos were dominated by Halobacteria, Cyanobacteria and Bacteroidota, while Bacteroidia, Gammaproteobacteria and Cyanobacteria dominated lift-off mats from Sisal. This work contributes to understanding the distribution, physicochemical characteristics and microbial diversity of coastal microbial mats, providing valuable new insights into microbial mats that develop in karstic ecosystems. This information is relevant to ongoing and future efforts to manage and preserve coastal ecosystems in the Yucatan Peninsula.

Wetlands, such as those in Laguna Bacalar, Mexico, are highly productive and biodiverse ecosystems that provide a wide range of invaluable ecosystem services (ES). Despite their importance, these ecosystems are under significant threat from disturbances such as land-use changes, making them among the most endangered ecosystems worldwide. This study aimed to (1) assess the spatio-temporal variation of ecosystem services in Laguna Bacalar, Mexico, between 1999 and 2021 using medium-resolution satellite imagery from the Landsat sensor; and (2) estimate the monetary value of ES losses attributable to land-use changes by applying a unit value transfer method with global value coefficients based on data from Brander et al. (2024). Twenty-two key ESs were identified and associated with mangroves, inland wetlands, and the hydrological system. A total of 277 hectares of natural ecosystems were lost, leading to a reduction in the total value flow of ecosystem services (ES), which was estimated at 10,411,098 Int$/year over the study period. The loss of inland wetlands is particularly alarming due to their critical role in filtering agrochemicals and organic matter from the watershed. Increasing pressures from human activities, including urbanization and tourism, significantly contribute to the degradation of these ecosystems. This highlights the urgent need for responsible environmental management and the implementation of conservation strategies to protect their functionality and the invaluable ecosystem services they provide to local communities.

The Lie group method is a powerful technique for obtaining analytical solutions for various nonlinear differential equations. This study aimed to explore the behavior of nonlinear elastic wave equations and their underlying physical properties using Lie group invariants. We derived eight-dimensional symmetry algebra for the (3+1)-dimensional nonlinear elastic wave equation, which was used to obtain the optimal system. Group-invariant solutions were obtained using this optimal system. The same analysis was conducted for the damped version of this equation. For the conservation laws, we applied Noether’s theorem to the nonlinear elastic wave equations owing to the availability of a classical Lagrangian. However, for the damped version, we cannot obtain a classical Lagrangian, which makes Noether’s theorem inapplicable. Instead, we used an extended approach based on the concept of a partial Lagrangian to uncover conservation laws. Both techniques account for the conservation laws of linear momentum and energy within the model. These novel approaches add an application of variational calculus to the existing literature. This offers valuable insights and potential avenues for further exploration of the elastic wave equations.

Background/Objectives: We identified the factors related to post-intensive care syndrome in a sample of patients from northern Colombia. Methods: This study employed a quantitative, observational, descriptive, and correlational approach. A sample of 277 adults was obtained through non-probabilistic convenience sampling, and a characterization form comprising sociodemographic and clinical variables was applied. The Healthy Aging Brain Care Monitor (HABC-M) instrument was also used, which is a clinical tool with a high capacity to detect post-intensive care syndrome (PICS) in surviving intensive care unit (ICU) patients. Results: The final sample consisted of 277 adults, 67.5% male, with university degrees, cohabiting in a marital union, working, from urban areas, and of the Catholic religion. Seventy percent of the sample presented both cardiovascular and neurological alterations and was admitted to the ICU, and 66% had a personal history of arterial hypertension (AHT) and type 2 diabetes mellitus (DM2). Patients had a mean ICU stay of 10.7 days, with a standard deviation of 4 days, and displayed a moderate risk of morbidity and mortality according to Acute Physiology and Chronic Health Evaluation II (APACHE II). A total of 38.6% of the sample received mechanical ventilation, with a mean duration of 8.3 days, and 7.5% underwent tracheostomy. As for sedation, 38.6% were administered fentanyl. In total, 83.4% of the sample presented the syndromes under study, with a predominance of the severe category. The global score of the scale was taken as the dependent variable, and statistical significance (p < 0.05) was found with sociodemographic variables, including origin and religion, and with clinical variables such as receiving pharmacological treatment. Conclusions: The sample presented PICS globally and showed how it affects the different dimensions, showing associations with the sociodemographic and clinical variables of interest.