Reproductive aspects of the snapping shrimp Alpheus packardii (Decapoda, Alpheidae) in Mahahual reef lagoon, southern coast of Quintana Roo, Mexican Caribbean

2021 ◽  
pp. 1-9
Author(s):  
Mario Martínez-Mayén
Keyword(s):  
Quintana Roo ◽  
Southern Coast ◽  
Snapping Shrimp ◽  
Reef Lagoon ◽  
Mexican Caribbean

scholarly journals Suelos Y Karst, Origen De Inundaciones Y Hundimientos En Chetumal, Quintana Roo, México

2018 ◽  
Vol 14 (14) ◽  
pp. 33 ◽  
Author(s):  
Patricia Fragoso-Servón ◽  
Alberto Pereira-Corona
Keyword(s):  
Land Use ◽  
Growth Rate ◽  
Population Growth Rate ◽  
Land Use Changes ◽  
Development Program ◽  
Quintana Roo ◽  
Development Programs ◽  
Mexican Caribbean ◽  
The City ◽  
Over Time

The Mexican Caribbean and its main cities have the highest population growth rate in Mexico. This work goal was to analyze the growth of the city of Chetumal and the geopedological characteristics in which it has been developed, to identify potential hazards and thereby improve development programs. The methodology consisted in the study of geopedological characteristics and the analysis of land use changes in the city over time. The main problems of Chetumal are floods and subsidence. Floods are more common in areas where Gleysols soils are found in low-lying areas. The subsidence is associated to Leptosols with a phreatic mantle at a shallow depth where the precipitations favors dissolution of rock. The extrapolation of the relationships between geopedological conditions and the area occupied by the city, allows us to suppose that areas which the current Urban Development Program proposes for future city expansion will develop the same problems of subsidence and flooding as the areas already built in sites with similar conditions.

scholarly journals ERISNet: Deep learning network for Sargassum detection along the coastline of the Mexican Caribbean

2018 ◽  
Author(s):  
Javier Arellano-Verdejo ◽  
Hugo-Enrique Lazcano-Hernandez ◽  
Nancy Cabanillas-Terán
Keyword(s):  
Deep Learning ◽  
Recurrent Neural Networks ◽  
Algal Blooms ◽  
Quintana Roo ◽  
Negative Consequences ◽  
Learning Network ◽  
Learning Techniques ◽  
Mexican Caribbean ◽  
Modis Imagery ◽  
Deep Learning Network

Recently, Caribbean coasts have experienced atypical massive arrivals of pelagic Sargassum with negative consequences both ecologically and economically. Based on deep learning techniques, this study proposes a novel algorithm for floating and accumulated pelagic Sargassum detection along the coastline of Quintana Roo, Mexico. Using convolutional and recurrent neural networks architectures, a deep learning network (named ERISNet) was designed specifically to detect this macroalgae along the coastline through remote sensing support. A new dataset which includes pixels values with and without Sargassum was built to training and testing ERISNet. Aqua-MODIS imagery was used to build the dataset. After the learning process, the designed algorithm achieves a 90 % of probability in its classification skills. ERISNet provides a baseline for automated systems to accurately and efficiently monitor algal blooms arrivals.

scholarly journals ERISNet: deep neural network for Sargassum detection along the coastline of the Mexican Caribbean

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6842 ◽  
Author(s):  
Javier Arellano-Verdejo ◽  
Hugo E. Lazcano-Hernandez ◽  
Nancy Cabanillas-Terán
Keyword(s):  
Neural Network ◽  
Recurrent Neural Networks ◽  
Algal Blooms ◽  
Deep Neural Network ◽  
Quintana Roo ◽  
Negative Consequences ◽  
Learning Techniques ◽  
Mexican Caribbean ◽  
Modis Imagery ◽  
Novel Algorithm

Recently, Caribbean coasts have experienced atypical massive arrivals of pelagic Sargassum with negative consequences both ecologically and economically. Based on deep learning techniques, this study proposes a novel algorithm for floating and accumulated pelagic Sargassum detection along the coastline of Quintana Roo, Mexico. Using convolutional and recurrent neural networks architectures, a deep neural network (named ERISNet) was designed specifically to detect these macroalgae along the coastline through remote sensing support. A new dataset which includes pixel values with and without Sargassum was built to train and test ERISNet. Aqua-MODIS imagery was used to build the dataset. After the learning process, the designed algorithm achieves a 90% of probability in its classification skills. ERISNet provides a novel insight to detect accurately algal blooms arrivals.

scholarly journals ERISNet: Deep learning network for Sargassum detection along the coastline of the Mexican Caribbean

2018 ◽  
Author(s):  
Javier Arellano-Verdejo ◽  
Hugo-Enrique Lazcano-Hernandez ◽  
Nancy Cabanillas-Terán
Keyword(s):  
Deep Learning ◽  
Recurrent Neural Networks ◽  
Algal Blooms ◽  
Quintana Roo ◽  
Negative Consequences ◽  
Learning Network ◽  
Learning Techniques ◽  
Mexican Caribbean ◽  
Modis Imagery ◽  
Deep Learning Network

Recently, Caribbean coasts have experienced atypical massive arrivals of pelagic Sargassum with negative consequences both ecologically and economically. Based on deep learning techniques, this study proposes a novel algorithm for floating and accumulated pelagic Sargassum detection along the coastline of Quintana Roo, Mexico. Using convolutional and recurrent neural networks architectures, a deep learning network (named ERISNet) was designed specifically to detect this macroalgae along the coastline through remote sensing support. A new dataset which includes pixels values with and without Sargassum was built to training and testing ERISNet. Aqua-MODIS imagery was used to build the dataset. After the learning process, the designed algorithm achieves a 90 % of probability in its classification skills. ERISNet provides a baseline for automated systems to accurately and efficiently monitor algal blooms arrivals.

scholarly journals Dog predation by jaguars in a tourist town on the Mexican Caribbean

2021 ◽  
Vol 16 (4) ◽  
pp. 461-474
Author(s):  
Mónica Carral-García ◽  
Irene Buenrostro ◽  
Holger Weissenberger ◽  
Víctor Rosales ◽  
Jonathan Pérez-Flores
Keyword(s):  
Disease Ecology ◽  
Pathogen Transmission ◽  
Quintana Roo ◽  
The South ◽  
Potential Conflict ◽  
The North ◽  
Tourist Town ◽  
Mexican Caribbean ◽  
Health And Disease ◽  
The Impact

Invasion of humans and dogs into the jaguars’ habitat opens the way for future negative events. Dog predation by jaguars has only been recorded anecdotally, despite the high risk of pathogen transmission and the potential conflict due to pet predation. In this study, we document jaguar attacks on dogs in Mahahual, Quintana Roo, Mexico, a tourist town in the Mexican Caribbean. In addition, we describe an initiative designed to prevent jaguar persecution by constructing night houses for dogs at the most recent attack sites. A total of 20 attacks were recorded in the last nine years, most of them fatal (60%) on medium-sized dogs (70%), at night (95%) and during the dry season (65%). Half of the attacks occurred in the north of Mahahual´s coastline and the other half in the south. Attacks in the south were concentrated between 0 to 10 km away from the village, while in the north they were dispersed over distances between 0 and > 30 km. Thirty-eight night houses were constructed covering almost 45 km of the 135 km of Mahahual’s coastline. Further research is required to understand the importance of dogs in the jaguar diet and the impact of dog predation on the health and disease ecology of jaguar populations.

Benthic-epiphytic dinoflagellates from the northern portion of the Mesoamerican Reef System

2015 ◽  
Vol 58 (2) ◽  
pp. 115-128
Author(s):  
Antonio Almazán-Becerril ◽  
Sergio Escobar-Morales ◽  
Gabriela Rosiles-González ◽  
Francisco Valadez
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
New Records ◽  
Quintana Roo ◽  
Reef System ◽  
Sampling Locations ◽  
Mexican Caribbean ◽  
Northern Portion ◽  
Protected Natural Areas ◽  
Scanning Electron

Abstract In 2010, we surveyed 42 sampling locations at 11 sites along the Mexican part of the Mesoamerican Reef System, including eight protected natural areas of the coastal state of Quintana Roo, to determine the richness of benthic-epiphytic dinoflagellates in the area. At each site, the host macroalgae of the genera Dictyota, Halimeda, Laurencia, Sargassum, and Stypopodium were manually collected. A total of 383 samples were analyzed microscopically using transmitted light, epifluorescence with calcofluor staining, and scanning electron microscopy. A total of 24 dinoflagellate species distributed among the genera Amphidinium, Bysmatrum, Coolia, Gambierdiscus, Ostreopsis, Prorocentrum, Plagiodinium, and Sinophysis were identified. Prorocentrum is the most diverse genus in the benthic-epiphytic environment with 13 species. This work also includes 15 new records of species from the Mexican Caribbean.

scholarly journals New host report for nematodes in a stranded short-snouted spinner dolphin Stenella clymene (Cetacea: Delphinidae) from the Mexican Caribbean coast

2010 ◽  
Vol 47 (2) ◽  
pp. 136-138 ◽  
Author(s):  
R. Aguilar-Aguilar ◽  
A. Delgado-Estrella ◽  
R. Moreno-Navarrete
Keyword(s):  
Atlantic Ocean ◽  
Caribbean Sea ◽  
Nematode Species ◽  
Quintana Roo ◽  
New Host ◽  
Western Atlantic ◽  
Mexican Caribbean ◽  
Spinner Dolphin ◽  
The Caribbean ◽  
First Time

AbstractOne short-snouted spinner dolphin Stenella clymene individual stranded on the coast of Quintana Roo, Mexico, was examined for stomach and lung nematodes. During necropsy, a large number of nematodes of the species Skrjabinalius guevarai were found in the airways. Additionally, some larval Anisakis sp. were found in the stomach. Both nematode species are reported for the first time from this host. The present is the first helminthological study of the short-snouted spinner dolphin in Mexico and adjacent waters of the Caribbean Sea. S. guevarai is reported for the first time from the western Atlantic Ocean.

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