Microplastic pollution in marine environments represents a significant ecological threat due to its persistence and harmful effects on biodiversity and human health. In Colombia, coastal ecosystems (particularly in La Guajira) have exhibited increasing microplastic concentrations, but systematic monitoring remains limited. This study explored the application of remote sensing, including multispectral satellite imagery (Sentinel-2) and machine learning algorithms, to detect and monitor microplastics in the coastal zone of Riohacha, La Guajira. To inform the model selection and ensure methodological relevance, a focused systematic literature review was conducted, serving as a foundational step in identifying effective remote sensing strategies and machine learning algorithms previously applied to microplastic detection in aquatic environments. Moreover, microplastic samples were collected from four coastal sites on Riohacha’s coast and analyzed via Fourier transform infrared spectroscopy (FTIR), while environmental parameters were recorded in situ. The remote sensing data were processed and integrated with field observations to train linear regression, random forest, and artificial neural network (ANN) models. The ANN model achieved the highest accuracy (MAE = 0.040; RMSE = 0.071), outperforming the other models in estimating the microplastic concentrations. Based on these results, environmental risk maps were generated, identifying critical zones of pollution. The findings support the integration of remote sensing tools and field data for scalable, cost-efficient microplastic monitoring, offering a methodological framework for marine pollution assessment in Colombia and other developing coastal regions.

Understanding the interactions between vegetation dynamics and surface water availability is essential for assessing the resilience of tropical floodplain ecosystems under increasing hydroclimatic variability. This study analyzes the spatio-temporal dynamics of vegetation cover, surface water, and land use in Zambrano, a floodplain-dominated sector of the lower Magdalena River basin (Colombian Caribbean), over the period 1990–2025. Multi-temporal Landsat imagery was used to derive the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), enabling the evaluation of seasonal and interannual ecohydrological variability under contrasting dry and rainy conditions. In addition, land-use classification was performed using a CORINE Land Cover methodology adapted for Colombia (CLC-C) to characterize the spatial organization of the landscape and its influence on vegetation–water interactions. Results show that vegetation dynamics are strongly controlled by hydroclimatic seasonality. Dense vegetation consistently expands during rainy periods, while dry seasons promote the expansion of open and sparse vegetation, reflecting seasonal vegetation stress rather than long-term degradation. NDWI patterns indicate that surface water and soil moisture are highly seasonal and spatially constrained, with open water largely confined to the Magdalena River channel and localized floodplain depressions. Extreme hydroclimatic events associated with the El Niño–Southern Oscillation (ENSO) produce abrupt but temporary changes in vegetation structure and surface moisture distribution. A strong inverse correlation between NDVI and NDWI reflects the contrasting spectral responses of vegetation and water surfaces resulting from the shared near-infrared (NIR) band in both indices. This spectral relationship is consistent with the observed seasonal variations in vegetation greenness and surface moisture across the floodplain. Land-use analysis reveals the progressive consolidation of the landscape, where the agropastoral matrix expanded from ~18,000 ha in 1990 to over 22,000 ha by 2025, driving a systematic reduction in natural and semi-natural forest structures. Forest conservation areas serve as critical ecological buffers, exhibiting lower seasonal variability in vegetation greenness. Overall, the results indicate that the Zambrano floodplain functions as a structurally stable yet highly responsive ecohydrological system, where vegetation dynamics and surface water availability are predominantly governed by interannual hydroclimatic pulses rather than long-term directional degradation. These findings demonstrate that while the structural matrix of the floodplain exhibits strong baseline resilience, its ecological functioning remains critically coupled with, and vulnerable to, the extreme phase shifts in ENSO cycles.

Strategic wetlands in the Colombian Caribbean underpin local livelihoods through vital ecosystem services, yet they face severe degradation from hydrological alterations, urbanization, and anthropogenic pressures. To address the lack of integrated socioecological evaluations, this study examines community–wetland relationships, ecosystem reliance, environmental perceptions, and governance arrangements. We used a multi-scale approach, combining a regional baseline assessment of 25 strategic wetlands with localized empirical fieldwork across three contrasting study sites: Sinú-Cispatá, Magdalena River estuary, and Tasajera–Ciénaga Grande de Santa Marta. We collected data through 150 structured household surveys, semi-structured interviews, and participatory social cartography. Findings reveal a strong, structural dependence on wetland resources, dominated by artisanal fisheries, navigation, and mangrove-based livelihoods. Communities consistently link ecosystem decline to hydrological disruptions, fisheries collapse, and deteriorating water quality, with marked spatial variations driven by urban–industrial stress in Atlántico versus hydrological fragmentation in Magdalena. Results also highlight significant governance gaps, including institutional distance and multi-agency fragmentation between regional environmental authorities and fisheries bodies. Ultimately, this research underscores the necessity of establishing participatory, territorially grounded governance frameworks that integrate local ecological knowledge, community-based monitoring, and adaptive management to foster long-term socioecological resilience in Caribbean wetlands.

Artisanal fisheries are fundamental to riverine socioecological systems, yet fishing communities remain underrepresented in environmental governance and decision-making. This gap constrains the incorporation of local knowledge into environmental decision-making and may reduce the effectiveness of governance strategies for addressing complex socioecological challenges. This study analyzes the socio-environmental characteristics of artisanal fisheries in the lower Magdalena River estuarine zone (Colombia) and discusses their implications for water governance and monitoring systems. Using a mixed-methods integrative design, we combined a PRISMA-guided literature review with a structured survey of 43 community members in the strategic territory of Bocas de Cenizas–Ciénaga de Mallorquín. The results reveal strong livelihood dependence on aquatic ecosystems, increasing environmental pressures, and limited institutional coordination. Respondents reported clear perceptions of environmental degradation, including declines in fish availability, vegetation cover, and water quality. Crucially, local actors possess detailed experiential knowledge of these transformations and show favorable conditions for participatory engagement. The integrative analysis indicates that artisanal fishers are not merely vulnerable populations, but key environmental observers whose knowledge can enhance adaptive and inclusive water governance. The findings identify a specific monitoring gap in the lower Magdalena estuarine zone: the environmental changes most consistently perceived by local actors—including declining fish availability, deteriorating water conditions, vegetation loss, and shoreline erosion—are directly linked to livelihood dependence but remain weakly connected to formal governance processes. These locally observed variables provide a context-specific basis for developing integrated socioecological and hydroenvironmental monitoring systems that combine conventional scientific indicators with community-based observations, thereby improving the territorial relevance of environmental information for water governance and decision-making.