The data obtained from field-based forest inventories, mainly basal area and stem density, are relevant for the analysis of aboveground biomass and forest fragmentation. Due to its persistently flooded ground, fieldwork in mangrove forests is time-consuming and complicated. Since mangroves are sensitive to the effects of climate change, selecting a reliable field method is of utmost importance. To this end, we analyzed 4 mangrove classes: Rhizophora mangle (RM), Laguncularia racemosa (LR), Avicennia germinans (AG), and AG shrub. We georeferenced and counted all mangrove stems within four 0.04 ha (20 × 20 m square). We analyzed data from 3 circular area plots and the plotless point-centered quarter method (PCQM) based on the original square plots. Depending on the mangrove class, PCQM overestimated basal area by up to 34% and stem density by 21%. The 3 circular plot surveys underestimated basal area from –1% to –29% and stem density from –3 to –25%. Based on the results, we suggest using a circular plot of 0.04 ha (r = 11.28 m) in less dense forests (RM and AG) and a circular plot of 0.015 ha (r = 6.9 m) with forest densities greater than 3,500 stems/ha (LR and AG shrub). The advantages of using the circular plot approach over PCQM are that mangrove inventories can be quantified quickly and do not require a minimum number of sampling points.

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.