Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.11.10.687714

Seagrass Extent Expansion in the Gulf of Mexico and Northwestern Caribbean (1987-2021)

Abstract

Historically, the areal extent of seagrass beds in the Gulf of Mexico, Florida peninsula, and Northwestern Caribbean (Mexico and Cuba) have been estimated to cover approximately 35,510 km2. However, the absence of regular monitoring limits our ability to detect interannual variability and up-to-date health conditions, and to respond to stressors, such as degraded water quality. Seagrass areal extent is one of the core Essential Ocean variables (EOV) of the Global Ocean Observing System (GOOS). Resource managers and researchers are interested in how this seagrass extent and the distribution of this habitat changes over time to focus possible action to mitigate impacts of various stressors, such as degraded water quality. In this study, we mapped 19,405 km2 of seagrasses for the region for the period 2019-2021, using satellite imagery from Landsat 5, Landsat 7, Landsat 8, and Sentinel-2. Interannual changes in seagrass areal extent at 17 representative sites indicated that seagrass habitats increased by 12.3% between 1987 and 2021. Sites off the West Florida coast showed the highest increasing rates in seagrass extent (up to 3.1% yr-1) and lowest rate (-0.43% yr-1) was observed in Biscayne Bay, South Florida. Seagrasses in the Mexican Caribbean showed positive extent expansion rates (1.3-1.8% yr-1), while in Texas were stable over the period of study. Continuous observations of seagrasses like these help managers to understand spatial and temporal patterns of change and encourage further studies on seagrass ecology and carbon stocks.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lizcano-Sandoval, L., Bell, S., Cerdeira-Estrada, S., Martinez-Daranas, B., Montes, E., van Tussenbroek, B., Muller-Karger, F.. 2025-11-12. Seagrass Extent Expansion in the Gulf of Mexico and Northwestern Caribbean (1987-2021). https://doi.org/10.1101/2025.11.10.687714

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Rapid estimation of insect biodiversity using AI assisted image analysis:a cost-effective tool for monitoring and ecological assessmen

Protection of natural areas and environmentally friendly management of anthropogenic landscapes require reliable tools for monitoring and comparing biodiversity. Bioindicator-based approaches can support large-scale ecological assessment, but insect monitoring remains constrained by the taxonomic expertise required for species identification. Here, we propose an AI-supported index for estimating the biodiversity of flying insects, based on the diversity of visual features of insect bodies. Flying insects were captured using yellow sticky traps across agricultural and natural habitats, seasons, crops, and sites in Israel's Mediterranean region. Traps were scanned at high resolution and uploaded to a dedicated image database. A machine learning model was used to detect and delineate insects, after which engineered visual features representing body size, color, and shape were extracted. Biodiversity was estimated from distances among feature vectors and compared with taxonomic diversity derived from expert identification of a representative validation set. The AI-derived diversity index correlated strongly with expert-based taxonomic diversity, supporting the hypothesis that morphological variation in insect images can provide a proxy for taxonomic diversity. Applying the index to the full dataset revealed a negative relationship between insect abundance and diversity, while diversity also varied across habitats and sampling seasons. Our results demonstrate the potential of AI-based image analysis to provide rapid and cost-effective assessments of insect biodiversity without requiring complete taxonomic identification. This approach may facilitate biodiversity monitoring and support timely ecological assessment and decision-making in sustainable agricultural and landscape management.

ecology↗

Pervasive ethanol in the fruits and floral nectars consumed by tropical frugivores

Dietary ethanol has long been proposed as a selective force shaping the diets and physiology of tropical frugivores and nectarivores, yet this idea has rested on measurements from only a few species and sites. Here, we present the first global survey of ethanol in wild fruits and flowers (591 and 37 species, respectively, across 18 countries) and test ecological and phylogenetic predictors of its variation. We detected ethanol in the ripened fruits of 72% of angiosperm species (211 species, N [≥] 3 per species; 0.021% - 3.9% alcohol by volume (ABV)). Ethanol was also detected in the flowers of 12 species (0.037% - 0.73% ABV). Maximum fruit ethanol varied with temperature, humidity, and phylogenetic relatedness, and it was higher in ripe fruits collected from the forest floor relative to their canopy counterparts. We then extrapolated potential daily ethanol consumption for 10 primate species. Estimated maximum daily ethanol ingestion for primates ranged from negligible to 0.72 g/kg/day on average (equivalent to 5.1 international standard drinks, 10 g ethanol each, for a 70 kg human). Our findings show that ethanol is widespread in plant reproductive tissues and shaped by both phylogeny and environment, supporting the hypothesis that dietary ethanol has been a pervasive selective pressure on fruit- and nectar-feeding animals.

ecology↗

Thermal Similarity Attenuates the Strength of Bergmanns Rule in Birds

Geographic body size variation, classically framed as Bergmann's rule, is a fundamental indicator of temperature-mediated morphological adaptation. However, empirical support for Bergmann's rule in birds remains highly unpredictable across lineages. We hypothesized that this variation is caused by differences in thermal similarity among species within the same genus, which may limit temperature driven changes in body size and be influenced by ecological factors. Using a global dataset comprising 5,715 bird species across 513 genera, we observed that thermal similarity was the strongest predictor of variation in the strength of Bergmann's rule among competing hypotheses. Among genera exhibiting significantly negative body mass temperature relationships, higher thermal similarity was consistently associated with less negative slopes, indicating weaker Bergmannian clines. Subgroup analyses indicated that the positive thermal similarity slope association was supported in dense and semi open habitats and among nonmigratory birds, but was not clearly supported in open habitats or among migratory birds. Our findings provide a novel explanation for variation in the strength of Bergmannian clines among avian lineages, showing that stronger morphological differentiation along thermal gradients is associated with greater thermal contrast. Consequently, our findings provide a basis for testing whether incorporating thermal similarity and ecological context can improve forecasts of avian morphological responses to ongoing climate change.

ecology↗