Marine protected areas have been established as essential components for managing and protecting coral reefs to mitigate natural and anthropogenic stressors. One noteworthy example within the Mexican Caribbean is the Arrecife de Puerto Morelos National Park (APMNP), where several studies on the coral communities have been carried out since 2006. In June 2019, we conducted a study in eight sites of the APMNP applying a coral reef assessment method based on biological indicators of both the benthos and the fish communities. In this paper, we present the quantitative results of our study and provide a qualitative criterion assessing seven condition indexes through a scoring system. We also present a statistical comparison with a previous study carried out in 2016. The general status of coral reefs was classified as regular due to the low values of coral recruitment rate and biomass of key commercial fish species. However, living coral cover average was above 20%, with a slight dominance of framework building coral species and the presence of low values of fleshy algae cover, these being positive indicators. Our study found a higher proportion of reef promoter elements and a lower proportion of detractors, compared to a previous study carried out in 2016.

In the Mexican Caribbean, 15 marine protected areas (MPAs) have been established for managing and protecting marine ecosystems. These MPAs receive high anthropogenic pressure from coastal development, tourism, and fishing, all in synergy with climate change. To contribute to the MPAs’ effectiveness, it is necessary to provide a long-term observation system of the condition of marine ecosystems and species. Our study proposes the establishment of a new marine biodiversity monitoring program (MBMP) focusing on three MPAs of the Mexican Caribbean. Five conservation objects (COs) were defined (coral reefs, seagrass beds, mangroves, marine turtles, and sharks-rays) for their ecological relevance and the pressures they are facing. Coral reef, seagrass and mangroves have multiple biological, biogeochemical and physical interactions. Marine turtles are listed as endangered species, and the status of their populations is unknown in the marine area of the MPAs. Elasmobranchs play a key role as top and medium predators, and their populations have been poorly studied. Indicators were proposed for monitoring each CO. As a technological innovation, all information obtained from the MBMP will be uploaded to the Coastal Marine Information and Analysis System (SIMAR), a public, user-friendly and interactive web platform that allows for automatic data management and processing.

Mexico has committed to protecting 30% of its marine territory by 2030 to comply with Target 3 of the Kunming–Montreal Global Biodiversity Framework, adopted during the 15th Conference of the Parties to the Convention on Biological Diversity. In this paper, we demonstrate the feasibility of meeting this commitment by determining the marine extent of conservation measures based on legally established Marine Protected Areas and areas that meet the criteria to be considered as Other Effective area-based Conservation Measures (OECMs) and determining the marine extent of areas proposed in various conservation planning exercises that can be created as any of the area-based instruments that exist in Mexico. The total coverage of existing and proposed areas was calculated by merging the dataset to remove duplicates and dissolving the boundaries between polygons to determine the total area. Spatial analysis was carried out in ArcGIS using geoprocessing tools. Currently, more than 25% of Mexico’s marine area is legally protected or conserved, with federal marine protected areas covering more than 22% of the Exclusive Economic Zone. The legally established areas that can be considered OECMs cover about 3% of the marine territory. We found that more than 9% of Mexico’s Economic Exclusive Zone contains areas of high conservation importance that are not covered by any area-based instrument. This study shows that Mexico has the potential to protect or conserve 32.8% of its marine territory by 2030.

Earth observation (EO) data play a crucial role in monitoring ecosystems and environmental processes. Time series of satellite data are essential for long-term studies in this context. Working with large volumes of satellite data, however, can still be a challenge, as the computational environment with respect to storage, processing and data handling can be demanding, which sometimes can be perceived as a barrier when using EO data for scientific purposes. In particular, open-source developments which comprise all components of EO data handling and analysis are still scarce. To overcome this difficulty, we present Tools for Analyzing Time Series of Satellite Imagery (TATSSI), an open-source platform written in Python that provides routines for downloading, generating, gap-filling, smoothing, analyzing and exporting EO time series. Since TATSSI integrates quality assessment and quality control flags when generating time series, data quality analysis is the backbone of any analysis made with the platform. We discuss TATSSI’s 3-layered architecture (data handling, engine and three application programming interfaces (API)); by allowing three APIs (a native graphical user interface, some Jupyter Notebooks and the Python command line) this development is exceptionally user-friendly. Furthermore, to demonstrate the application potential of TATSSI, we evaluated MODIS time series data for three case studies (irrigation area changes, evaluation of moisture dynamics in a wetland ecosystem and vegetation monitoring in a burned area) in different geographical regions of Mexico. Our analyses were based on methods such as the spatio-temporal distribution of maxima over time, statistical trend analysis and change-point decomposition, all of which were implemented in TATSSI. Our results are consistent with other scientific studies and results in these areas and with related in-situ data.