Academic literature on the topic 'Mangrove forests – Cuba'

Hidrozoos de aguas poco profundas fueron recolectados en 17 estaciones, en julio del 2004. Las estaciones se localizaron en manglares, pastos marinos y arrecifes coralinos. Se encontraron hidrozoos de dos subclases (Anthoathecata y Leptothecata), 11 familias, 27 géneros y 34 especies. Se indican la localidad de recolecta, la profundidad, el tipo de sustrato, la descripción y las figuras de 15 especies de hidrozoos tecados. Se confirma la presencia de Hebellopsis communis Calder, 1991a y Antennella siliquosa (Hincks, 1877) para el Mar Caribe. Se expresa la abundancia relativa en tres categorías: abundante, común y rara. Las especies más abundantes fueron Dynamena crisioides Lamouroux, 1824 en el hábitat de manglar, Cnydoscyphus marginatus (Allman, 1877) y Sertularella diaphana (Allman, 1885) en los arrecifes. Monostaechas quadridens (McCrady, 1859) y Diphasia tropica Nutting, 1904 fueron de baja representación en las muestras. Los sustratos más colonizados fueron la raíz sumergida de mangle rojo y las esponjas en arrecife. El hidrozoo más colonizado fue C. marginatus. El material fue depositado en la colección de invertebrados marinos del Acuario Nacional de Cuba.ABSTRACT Hydrozoans from shallow waters were collected at 17 stations in July 2004. Stations were located in mangrove forests, seagrass meadows and coral reefs. Two subclases (Anthoathecata and Leptothecata) of hydrozoans were found, including 11 families, 27 genera and 34 species. The collection site, depth, type of substrate, description and pictures are recorded for the fifteenth thecate hydrozoan species. The presence of Hebellopsis communis Calder, 1991a and Antennella siliquos (Hincks, 1877) is confirmed for the Caribbean Sea. The relative abundance is expressed in three categories: abundant, common and rare. Most abundant species were Dynamena crisioides Lamouroux, 1824 in mangrove habitat, Cnydoscyphus marginatus (Allman, 1877) and Sertularella diaphana (Allman, 1885) in coral reefs. Monostaechas quadridens (McCrady, 1859) and Diphasia tropica Nutting, 1904 were rare in general. The most colonized substrates were the submerged red mangrove roots and sponges in the reef. The most colonized hydrozoan was C. marginatus. Specimens were deposited in the collection of marine invertebrates at the National Aquarium of Cuba.

This study establishes the use of the Earth Observation Data for Ecosystem Monitoring (EODESM) to generate land cover and change classifications based on the United Nations Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) and environmental variables (EVs) available within, or accessible from, Geoscience Australia’s (GA) Digital Earth Australia (DEA). Classifications representing the LCCS Level 3 taxonomy (8 categories representing semi-(natural) and/or cultivated/managed vegetation or natural or artificial bare or water bodies) were generated for two time periods and across four test sites located in the Australian states of Queensland and New South Wales. This was achieved by progressively and hierarchically combining existing time-static layers relating to (a) the extent of artificial surfaces (urban, water) and agriculture and (b) annual summaries of EVs relating to the extent of vegetation (fractional cover) and water (hydroperiod, intertidal area, mangroves) generated through DEA. More detailed classifications that integrated information on, for example, forest structure (based on vegetation cover (%) and height (m); time-static for 2009) and hydroperiod (months), were subsequently produced for each time-step. The overall accuracies of the land cover classifications were dependent upon those reported for the individual input layers, with these ranging from 80% (for cultivated, urban and artificial water) to over 95% (for hydroperiod and fractional cover). The changes identified include mangrove dieback in the southeastern Gulf of Carpentaria and reduced dam water levels and an associated expansion of vegetation in Lake Ross, Burdekin. The extent of detected changes corresponded with those observed using time-series of RapidEye data (2014 to 2016; for the Gulf of Carpentaria) and Google Earth imagery (2009–2016 for Lake Ross). This use case demonstrates the capacity and a conceptual framework to implement EODESM within DEA and provides countries using the Open Data Cube (ODC) environment with the opportunity to routinely generate land cover maps from Landsat or Sentinel-1/2 data, at least annually, using a consistent and internationally recognised taxonomy.

Abstract A description is provided for Arcyria cinerea, one of the most consistently abundant and widespread myxomycete species associated with lianas, aerial woody remnants, leaves and inflorescences in tropical and mangrove forests. Some information on its associated organisms and substrata, interaction and habitats, infraspecific variation, dispersal and transmission, and conservation status is given, along with details of its geographical distribution (AFRICA: Algeria, Angola, Burundi, Cameroon, Democratic Republic of the Congo, Egypt, Equatorial Guinea, Gambia, Kenya, Liberia, Madagascar, Malawi, Mayotte, Morocco, Mozambique, Nigeria, Rwanda, Sierra Leone, Somalia, South Africa, Tanzania, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe; NORTH AMERICA: Canada (Alberta, British Columbia, Manitoba, New Brunswick, Ontario, Quebec, Saskatchewan), Mexico, USA (Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Vermont, Virginia, West Virginia); CENTRAL AMERICA: Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama; SOUTH AMERICA: Argentina, Bolivia, Brazil (Alagoas, Amazonas, Bahia, Ceara, Mato Grosso, Minas Gerais, Paraiba, Parana, Pernambuco, Rio Grande do Norte, Rio Grande do Sul, Rondonia, Roraima, Santa Catarina, Sao Paulo, Sergipe), Chile, Colombia, Ecuador (including Galapagos), French Guiana, Guyana, Paraguay, Peru, Surinam, Venezuela; ANTARCTICA: Antarctica; ASIA: China (Anhui, Guangdong, Guangxi, Heilongjiang, Hong Kong, Jiangsu, Kwangtung, Yunnan), Christmas Island, Georgia, India (Assam, Chandigarh, Himachal Pradesh, Jammu & Kashmir, Karnataka, Madhya Pradesh, Maharashtra, Orissa, Uttarakhand, Uttar Pradesh, West Bengal), Indonesia, Iran, Japan, Kazakhstan (Aktobe, Atyrau, Pavlodar, West Kazakhstan), Laos, Nepal, Papua-New Guinea, Philippines, Russia (Altai Krai, Altai Republic, Chukotka Autonomous Okrug, Irkutsk Oblast, Khabarovsk Krai, Khanty-Mansi Autonomous Okrug, Krasnoyarsk Krai, Magadan Oblast, Primorsky Krai, Republic of Buryatia, Sakhalin Oblast, Tyumen Oblast, Yamalo-Nenets Autonomous Okrug), Singapore, Sri Lanka, Taiwan, Thailand, Turkey, Uzbekistan, Vietnam. Atlantic OCEAN: Ascension Island, Spain (Canary Islands); AUSTRALASIA: Australia (New South Wales, Northern Territory, Queensland, Tasmania, Victoria, Western Australia), New Zealand, Raoul Island; CARIBBEAN: American Virgin Islands, Antigua and Barbuda, Bahamas, Cuba, Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti, Jamaica, Martinique, Puerto Rico, Trinidad & Tobago; EUROPE: Andorra, Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Lithuania, Luxembourg, Moldova, Netherlands, Norway, Poland, Portugal, Romania, Russia (Astrakhan Oblast, Chelyabinsk Oblast, Kalinigrad Oblast, Komi Republic, Krasnodar Krai, Kursk Oblast, Leningrad Oblast, Moscow Oblast, Murmansk Oblast, Orenburg Oblast, Perm Krai, Republic of Bashkortostan, Republic of Karelia, Rostov Oblast, Smolensk Oblast, Tver Oblast, Voronezh Oblast, Volgograd Oblast, Vologda Oblast), Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, UK; Indian OCEAN: Mauritius, Reunion, Seychelles; Pacific OCEAN: French Polynesia, New Caledonia, USA (Hawaii)).

Introduction: Mangroves represent 11 % of the emerged land of Cuba. There is no previous research describing foliar characteristics, but these variables can be used as health indicators in forest ecosystems. Objective: In the current study we describe folial morphometry in four mangroves around Havana city: Bajos de Santa Ana, Cojímar, Rincón de Guanabo and El Cobre – Itabo lagoon. Methods: We collected 1 472 leaves´ samples of Rhizophora mangle, Avicennia germinans and Laguncularia racemosa, between April and July in 2019, to extract eight foliar variables: length, width, area, perimeter, lateral asymmetry, inner angles and shape index. Results: Geographic differences several variables of leaves in R. mangle and A. germinans were detected, but L. racemosa showed high similarity among localities. Differences can be explained by environmental differences in localities. Conclusions: There is a need for more extensive research on these kinds of foliar indicators to support it use in future monitoring or researches, and for that using digital pictures fotografías pose many advantages.

Introduction: Mangroves represent 11 % of the emerged land of Cuba. There is no previous research describing foliar characteristics, but these variables can be used as health indicators in forest ecosystems. Objective: In the current study we describe folial morphometry in four mangroves around Havana city: Bajos de Santa Ana, Cojímar, Rincón de Guanabo and El Cobre – Itabo lagoon. Methods: We collected 1 472 leaves´ samples of Rhizophora mangle, Avicennia germinans and Laguncularia racemosa, between April and July in 2019, to extract eight foliar variables: length, width, area, perimeter, lateral asymmetry, inner angles and shape index. Results: Geographic differences several variables of leaves in R. mangle and A. germinans were detected, but L. racemosa showed high similarity among localities. Differences can be explained by environmental differences in localities. Conclusions: There is a need for more extensive research on these kinds of foliar indicators to support it use in future monitoring or researches, and for that using digital pictures fotografías pose many advantages.

This research analyses the dynamics of coastal resource management in the village of Las Canas, located in the province of Pinar del Rio, Cuba. More specifically, this study examines the environmental practices and discourses of individuals in the community of Las Canas, of researchers involved in a sustainable development project focused on the mangroves in the région, and of state représentatives from the Ministry of Science, Technology and Environment (CITMA), as well as other governmental agencies involved in the area of Las Canas. This research examines how, in a context of transformation characterized by environmental dégradation, deep économie crisis and state decentralization, thèse three catégories of social actors, that is, individuals, researchers, and state représentatives, exploit and protect natural resources and construct socio-environmental relations through linkages among themselves and with the environment.