A study was conducted to assess the diversity of biological communities at Mt. Banahaw de Dolores in Sitio Kinabuhayan, Sta Lucia, Dolores, Quezon; the area was characterized by identifying the forest trees present, species richness and diversity, and dominance. This was after a 5 year moratorium visitation in the national park. The forest inventory used the quadrat sampling method. Wildlife
Ecologically Valuable Areas play an important role in providing ecosystem services, however, human activities such as land conversion and urban sprawl pose pressures and threats to these areas. The study assessed the land use/land cover and urban sprawl in the Mount Makiling Forest Reserve (MMFR) Watersheds and Buffer Zone from 1992 to 2015 using remote sensing and Geographic Information System (GIS). Results showed that the land use/cover within the MMFR buffer zone has changed from 1992 to 2015 with built-up areas increasing by 117% despite Proclamation 1257, s. 1998 which regulates human activities in the zone. Based on the Shannon entropy analysis the land development in the MMFR buffer zone tends to be dispersed and sprawling. However, when the magnitude of change of urban sprawl in the buffer zone from 2002 to 2015 was calculated, a decrease in the entropy value was observed which implies a compacting pattern as the human settlement in the buffer zone increases over time. Proclamation 1257, s. 1998 needs to be strengthened to protect MMFR and its buffer zone from further encroachment and pressure. Moreover, remote sensing and GIS proved to be useful tools for assessing urban sprawl in ecologically valuable areas such as MMFR.
Native bees are pollinators and bioindicators of ecosystem health but only little is known about its abundance, species distribution, and habitat range, especially in the Philippines. This study assessed the diversity and spatial distribution of native bees in Mt. Banahaw de Lucban (MBDL). Belt transect coupled with opportunistic sampling were used in the inventory of bees and their nests. Nests occurrence and 7 environmental predictor variables including; 1) annual mean temperature; 2) precipitation of warmest quarter; 3) elevation; 4) slope; 5) Normalized Difference Vegetation Index (NDVI); 6) distance to agricultural areas (m); and 7) distance to forested areas (m) were used for modeling species distribution by MaxEnt. A total of 16 species of native bees including representatives from genus Apis, Tetragonula, Lasioglossum, Halictus, Hylaeus and Megachile were identified. A total of 96 bee nests from 5 species were also recorded yielding a nests density of 234 nests per km2. Results showed medium diversity of solitary native bees with H’ of 2.488. Most bee nests were found in lower elevations while the distance from agricultural areas and the distance from forest areas had the highest contributions to the nesting of Apis breviligula, A. cerana, and Tetragonula biroi. The mean distance from forest areas of all bee nests was 649.930 m and the mean extent of suitable area for these species was 5.340 km2. Hence, a landscape approach may be more appropriate to conserve native bees and sustain the ecosystem services they provide in MBDL.
Na cidade de São Luís do Maranhão houve um crescimento populacional de 17% durante os anos de 2000 à 2010. O crescimento urbano decorrente de aumento populacional afeta a cobertura vegetal, em algumas áreas essa alteração pode ser positiva devido ao aumento da vegetação ou negativa devido a perda de vegetação. Uma vez que a expansão urbana afeta diretamente as áreas vegetadas faz-se interessante a realização de mapeamentos constantes da cobertura vegetal. Diante disso, o sensoriamento remoto e o geoprocessamento aliados a um Sistema de Informações Geográficas (SIG) podem ser alternativas viáveis para o estudo sobre o vigor vegetativo de determinadas regiões por meio do Índice por Diferença Normalizada (NDVI), como forma de estimar a alteração na vegetação decorrente da expansão urbana entre os anos de 2000 e 2010, na capital maranhense. Neste estudo, identificou-se os quinze bairros da cidade que obtiveram maior crescimento populacional, além disso os bairros foram classificados de acordo com os padrões de ocupações. A partir das imagens de satélites provenientes do sensoriamento remoto, aliadas com as técnicas de geoprocessamento foi possível estimar as áreas vegetadas e não vegetadas dos bairros de maior crescimento da cidade de São Luís-MA, nos anos de 2000 e 2010. Sete bairros apresentaram perdas de vegetação ao longo do período, outros sete apresentaram um aumento das áreas de vegetação e um bairro não apresentou variação.
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