Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (<1 m) resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities.

Mapping tropical dry forest habitats integrating Landsat NDVI, Ikonos imagery, and topographic information in the Caribbean Island of Mona

Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference vegetation Index (NDvI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDvI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5 500 ha area, with a kappa coefficient of accuracy equal to 79 %. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island. Rev. Biol. Trop. 56 (2): 625-639. Epub 2008 June 30.

El estudio y evaluación de los bosques tropicales secos mediante herramientas de teledetección es una de las prioridades de investigación en los ambientes neotropicales. Desarrollamos una metodología simple para mapear la vegetación de la isla de Mona, Puerto Rico, mediante el uso del índice de vegetación normalizado (NDVI por sus siglas en inglés) de Landsat, información topográfica, e imágenes auxiliares de alta resolución Ikonos. La metodología fue útil para identificar las clases de vegetación en un área de gran variedad de comunidades vegetales y relieve complejo, y puede ser adaptada a otras regiones de bosque seco de las islas del Caribe. El NDVI permitió identificar la distribución de los bosques cerrados, abiertos, y arbustos, proveyendo una representación natural de los patrones de vegetación en la isla. Las imágenes de Ikonos permitieron incrementar el número de clases detectadas. Como resultado, mapeamos 16 clases de cobertura del terreno en las 5 500 hectáreas de la isla de Mona, con un coeficiente de concordancia kappa de un 79%. La información obtenida en este estudio será utilizada para modelar la distribución de los vertebrados terrestres y patrones de biodiversidad en la isla, como parte del proyecto Gap Análisis de Puerto Rico, y es de gran valor para asistir en las actividades de investigación y manejo en la isla.

Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

Inhibin a increases apoptosis in early ovarian antral follicles of diethylstilbestrol-treated rats.

The purpose of this study was to evaluate the role of inhibin A in follicular development and apoptosis-related mechanisms in preantral and early antral follicles from prepubertal diethylstilbestrol (DES)-treated rats. Granulosa cells isolated from the ovaries of 23- to 25-day-old rats were cultured in serum-free medium containing FSH (20 ng/ml), transforming growth factor beta (5 ng/ml), and estradiol (50 ng/ml) in the presence or absence of different concentrations of recombinant human inhibin A. (3)H-Thymidine incorporation was decreased in the presence of Inh, but no significant changes were observed in progesterone and estradiol levels in culture medium. An increase in low molecular weight DNA fragmentation indicative of apoptosis and an increase in the levels of Bax protein with no changes in Bcl-2 protein levels were evident in early antral follicles incubated for 24 h with Inh. For each animal, Inh (0.5 micro g/ovary) was injected intrabursally in one ovary, and the contralateral ovary served as a control. Ovarian histology revealed an inhibitory effect of Inh treatment on the follicular development induced by DES. At 24 h after Inh injection, the number of preantral follicles was increased compared with controls, whereas the number of early antral follicles was decreased. In addition, in vivo Inh treatment caused an increase in the percentage of apoptotic cells in preantral and early antral follicles. These results suggest that inhibin produced by the dominant follicle may act as a paracrine factor inhibiting the growth of neighboring follicles, thus participating in the mechanism of follicular selection.