Abstract: In this paper, we emphasize the importance of understanding the nesting ecology and nesting behaviour of green marine turtles (Chelonia mydas). Data were collected from 2007 until 2012 from nesting beaches at Setiu Terengganu, Malaysia. We focused on one of the beaches, Telaga Papan, based on data collected in 2012. We recorded the distribution of nesting areas, the emergence hour and the correlation between successful nesting attempts and false crawls. Telaga Papan had a significantly higher distribution of green marine turtle nesting compared with the other five beaches (ANOVA, F5,42 = 8.874, P < 0.01, mean = 36.750 ± 3.727). The highest number of successful nesting attempts was recorded in 2012 (mean = 28.714). A majority of the species landed between 22:00 and 23:59 h (25%). There was a strong correlation between successful nesting attempts and false crawls (rs = 0.883, P = 0.02). Based on these findings on the nesting ecology and nesting behaviour of green marine turtles, we suggest that scientific research, strict monitoring, awareness programs and policy implementation should be carried out proactively. Such activities are necessary to reduce the anthropogenic pressures at the nesting beaches as well as to ensure more successful nesting attempts of green marine turtles in Setiu.

Abstract: The growing availability of free or inexpensive satellite imagery has inspired many researchers to investigate the use of earth observation data for monitoring economic activity around the world. One of the most popular earth observation data sets is the so-called nighttime lights from the Defense Meteorological Satellite Program. Researchers have found positive correlations between nighttime lights and several economic variables. These correlations are based on data measured in levels, with a cross-section of observations within a single time period across countries or other geographic units. The findings suggest that nighttime lights could be used as a proxy for some economic variables, especially in areas or times where data are weak or unavailable. Yet, logic suggests that nighttime lights cannot serve as a good proxy for monitoring the within-in country growth rates all of these variables. Examples examined this paper include constant price gross domestic product, nonagricultural gross domestic product, manufacturing value
added, and capital stocks, as well as electricity consumption, total population, and urban population. The study finds that the Defense Meteorological Satellite Program data are quite noisy and therefore the resulting growth elasticities of Defense Meteorological Satellite Program nighttime lights with respect to most of these socioeconomic variables are low, unstable over time, and generate little explanatory power. The one exception for which Defense Meteorological Satellite Program nighttime lights could serve as a proxy is electricity consumption, measured in 10-year intervals. It is hoped that improved data from the recently launched Suomi National Polar-Orbiting Partnership satellite will help expand or improve these outcomes. Testing this should be an important next step.