The identification and monitoring of invasive plant species utilizing spaceborne sensors have posed substantial challenges over the past few decades, mainly due to a scarcity of state-of-the-art sensors, limited digital processing capabilities, and the presence of a phenological spectral feature that is not readily detectable by conventional methods. The invasive plant Cissus verticillata, first detected in 2017, has affected the largest mangrove system on the eastern Pacific coast—Marismas Nacionales—spreading rapidly and aggressively through the mangrove canopy, and causing degradation and even mortality, mainly of Rhizophora mangle, by obstructing the sunlight over the canopy. The purpose of this study was to isolate the multispectral signal from Cissus verticillata by using a cloud computing approach with Google Earth Engine and generate a comprehensive map of the entire mangrove system by means of a novel dense time series of Sentinel-2 data. Results indicate that the optimal period for detecting Cissus verticillata is between October and December. Furthermore, this species is expanding its range along the riverbanks in the central region of Marismas Nacionales, with its coverage increasing from 426.16 ha in 2019 to 838.08 ha in 2021. These areas were verified with a field endeavor and have signified a substantial development, given that the plant had not been previously identified in this region with conventional field methods due to logistical constraints. The findings and approach of this study will contribute to the decision-making required to manage this invasive plant.

Hurricanes are powerful tropical storms that can severely damage mangrove forests through uprooting trees, sediment erosion, and saltwater intrusion, disrupting their critical role in coastal protection and biodiversity. After a hurricane, evaluating mangrove damage helps prioritize rehabilitation efforts, as these ecosystems play a key ecological role in coastal regions. Thus, we analyzed the defoliation of mangrove forest canopies and their early recovery, approximately 2.5 years after the landfall of Category 3 Hurricane Roslyn in October 2002 in Marismas Nacionales, Mexico. The following mangrove traits were analyzed: (1) the yearly time series of the Combined Mangrove Recognition Index (CMRI) standard deviation from 2020 to 2025, (2) the CMRI rate of change (slope) following the hurricane’s impact, and (3) the canopy height model (CHM) before and after the hurricane using satellite and UAV-LiDAR data. Hurricane Roslyn caused a substantial decrease in canopy cover, resulting in a loss of 47,202 ha, which represents 82.8% of the total area of 57,037 ha. The CMRI standard deviation indicated early signs of canopy recovery in one-third of the mangrove-damaged areas 2.5 years post-impact. The CMRI slope indicated that areas near the undammed rivers had a maximum recovery rate of 0.05 CMRI units per month, indicating a predicted canopy recovery of ~2.5 years. However, most mangrove areas exhibited CMRI rates between 0.01 and 0.03 CMRI units per month, anticipating a recovery time between 40 months (approximately 3.4 years) and 122 months (roughly 10 years). Unfortunately, most of the already degraded Laguncularia racemosa forests displayed a negative CMRI slope, suggesting a lack of canopy recovery so far. Additionally, the CHM showed a median significant difference of 3.3 m in the canopy height of fringe-type Rhizophora mangle and Laguncularia racemosa forests after the hurricane’s landfall.

The city of Acapulco was impacted by two near-consecutive hurricanes. On 25 October 2023, Hurricane Otis made landfall, reaching the highest Category 5 storm on the Saffir–Simpson scale, causing extensive coastal destruction due to extreme winds and waves. Nearly one year later (23 September 2024), Hurricane John—a Category 2 storm—caused severe flooding despite its lower intensity, primarily due to its unusual trajectory and prolonged rainfall. Digital shoreline analysis of PlanetScope images (captured one month before and after Hurricane Otis) revealed that the southern coast of Acapulco, specifically Zona Diamante—where the major seafront hotels are located—experienced substantial shoreline erosion (94 ha) and damage. In the northwestern section of the study area, the Coyuca Bar experienced the most dramatic geomorphological change in surface area. This was primarily due to the complete disappearance of the bar on October 26, which resulted in a shoreline retreat of 85 m immediately after the passage of Hurricane Otis. Sentinel-1 Synthetic Aperture Radar (SAR) showed that Hurricane John inundated 2385 ha, four times greater than Hurricane Otis’s flooding (567 ha). The retrofitted QGIS methodology demonstrated high reliability when compared to limited in situ local reports. Given the increased frequency of intense hurricanes, these methods and findings will be relevant in other coastal areas for monitoring and managing local communities affected by severe climate events.

The mangrove ecosystem is recognized as one of the most productive worldwide; in most cases, this productivity has been quantified through the amount of leaf litter produced per unit area and time. However, there is a large variability in the values recorded for each latitudinal interval, which has been attributed to the diversity of local environmental characteristics. Managing leaf litter production data is the first consideration for the technical management of mangrove resources as an ecosystem. The present review (scientific articles, theses, reports, etc.) shows an analysis of the productivity of mangroves in Mexico, with the objective of synthesizing the knowledge of leaf litter production generated by different structural types of forests, described and explained according to environmental conditions. We consulted 68 publications, where the highest value of litterfall contribution (19.30 Mg/ha/year) was recorded in Atasta, Campeche, a semi-humid tropical region, and the lowest (1.75 Mg/ha/year) in Las Guá-simas, Sonora, a semi-arid subtropical region. The causal factors of leaf litter fall correspond mainly to precipitation, salinity, nutrients, structure, and physicochemical parameters of the interstitial water. It is important to increase and unify efforts between governmental agencies and research centers to generate and organize existing data on the mangrove’s primary productivity for a better understanding of the patterns and controls of the productivity and health of these coastal ecosystems.

1. Mangrove forests rank among the most carbon-dense ecosystems of Earth, sequestering atmospheric CO2 at rates that exceed most terrestrial forests (Alongi 2014; Donato et al. 2011). The bulk of t...