We analyzed diatoms, lithology, and stable isotopes in a sediment core from the Ciénaga Grande de Santa Marta lagoon to reveal the history of late Holocene relative sea level rise and the ontogeny of the lagoon on the Caribbean coast of Colombia. At ~5300 cal. yr BP, the area was characterized by shallow, freshwater ponds that were prone to seasonal flooding. From ~4250 to ~2060 cal. yr BP, these ponds became brackish as relative sea level began to rise, and since ~2060 cal. yr BP, marine conditions have prevailed. In addition to tracking relative sea level rise, we also investigated periods of greater and lesser precipitation during times of brackish and marine conditions, respectively, as indicated by diatom-inferred changes in water salinity and shifts in the source of sediment organic matter. Comparisons with other regional paleoenvironmental records suggest that humid climate conditions prevailed in the Caribbean until about 4000 cal. yr BP. After that time, climate became more variable, with drier conditions registered from ~ 4000 to 2000 cal. yr BP. Wetter conditions returned after ~2000 cal. yr BP.

Plastic pollution (PP) is an ongoing, pervasive global problem that represents a risk to the Galápagos archipelago, despite it being one of the world's most pristine and well-protected regions. By working closely with citizen scientists, we aimed to quantify and map the magnitude and biological effects of PP. With macroplastic abundance ranging from 0.003 to 2.87 items/m2, our research indicates that all five sampled Galápagos bioregions are contaminated with PP along their coastlines. The distribution of this debris is not uniform, with macroplastics significantly higher on the windward shores. Based on the identification information found on the examined items, Polyethylene terephthalate (PET) was the most predominant type of plastic originating from both consumer and fisheries-based products deriving primarily from Perú, China, and Ecuador. The top three manufacturers were AjeCroup, Coca-Cola, and Tingy Holding Corporation. Through citizen science, we documented PP exposure in 52 species (20 endemic) in Galápagos terrestrial and marine environments, with exposure occurring in two ways: entanglement and ingestion. These included reptiles (8 species), birds (13 species), mammals (4 species), cartilaginous fish (7 species), bony fish (14 species), and invertebrates (6 species). The top five species with the greatest risk of serious harm due to entanglement (in decreasing order) were identified as green sea turtles, marine iguanas, whale sharks, spine-tail mobulas, and medium-ground finches. In contrast, Santa Cruz tortoises, green sea turtles, marine iguanas, black-striped salemas, and Galápagos sea lions were at the highest risk of harm due to the ingestion of plastics. Our research indicates that PP is a growing problem in the Galápagos archipelago and that additional work is necessary to mitigate its impact now and in the future.

In the management of ecosystem services, it is signi cant to relate land use with the physical characteristics of the terrain, which allows establishing the conditioning factors of human activities and planning their distribution. These analyzes are based on thematic cartography, usually generated with visual classi cations of satellite images. Traditional mapping techniques involve limiting the timely availability of information by taking extended periods for interpretation and integration of multiple data sets. This article presents a methodology to overcome these di culties, implements big data, machine learning, and cloud computing to generate timely thematic cartography and spatial analysis to support land use planning. The study area was delimited according to altitudinal levels that de ne braided and anastomosed river systems. Acquisition, processing, and classi cation of input data for modeling were performed on the Google Earth Engine platform. The spatial correlation between hemeroby and geomorphology was calculated with the odds ratio and its respective con dence interval. Maps of 27 geomorphological units, 11 types of land use, and six hemeroby levels are presented at a scale of 1: 50,000. Confusion matrices of implemented classi cation models were also reported, allowed evaluating global, user's, and producer's accuracy. Correlations between relict of natural areas with the structural environment and urban infrastructure with alluvial fans stand out. The information generated by these procedures is essential for planning land use and prioritizing the maintenance of ecosystem services.

No abstract

In the management of ecosystem services, it is significant to relate land use with the physical characteristics of the terrain, which allows establishing the conditioning factors of human activities and planning their distribution. These analyzes are based on thematic cartography, usually generated with visual classifications of satellite images. Traditional mapping techniques involve limiting the timely availability of information by taking extended periods for interpretation and integration of multiple data sets. This article presents a methodology to overcome these difficulties, implements big data, machine learning, and cloud computing to generate timely thematic cartography and spatial analysis to support land use planning. The study area was delimited according to altitudinal levels that define braided and anastomosed river systems. Acquisition, processing, and classification of input data for modeling were performed on the Google Earth Engine platform. The spatial correlation between hemeroby and geomorphology was calculated with the odds ratio and its respective confidence interval. Maps of 27 geomorphological units, 11 types of land use, and six hemeroby levels are presented at a scale of 1: 50,000. Confusion matrices of implemented classification models were also reported, allowed evaluating global, user's, and producer's accuracy. Correlations between relict of natural areas with the structural environment and urban infrastructure with alluvial fans stand out. The information generated by these procedures is essential for planning land use and prioritizing the maintenance of ecosystem services.