Understanding the drivers of deforestation and forest degradation and the agents of such drivers is important for introducing appropriate policy interventions. Here, we identified drivers and agents of drivers through the analysis of local perceptions using questionnaire surveys, focus group discussions, and field observations. The Likert scale technique was employed for designing the questionnaire with scores ranging from 1 (strongly disagree) to 5 (strongly agree). We found nine direct drivers of forest deforestation and forest degradation, namely illegal logging (4.53 ± 0.60, ± is for standard deviation), commercial wood production (4.20 ± 0.71), land clearing for commercial agriculture (4.19 ± 1.15), charcoal production (3.60 ± 1.12), land clearing for subsistence agriculture (3.54 ± 0.75), new settlement and land migration (3.43 ± 0.81), natural disasters (3.31 ± 0.96), human-induced forest fires (3.25 ± 0.96), and fuelwood for domestic consumption (3.21 ± 0.77). We also found four main indirect drivers, namely lack of law enforcement, demand for timber, land tenure right, and population growth. Our analysis indicates that wood furniture makers, medium and large-scale agricultural investors, charcoal makers, land migrants, firewood collectors, and subsistent farmers were the agents of these drivers. Through focus group discussions, 12 activities were agreed upon and could be introduced to reduce these drivers. In addition to enforcing the laws, creating income-generating opportunities for locals along with the provision of environmental education could ensure long-term reduction of these drivers. The REDD+ project could be an option for creating local income opportunities, while reducing deforestation and forest degradation.

This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estimation caused by the use of a specific allometric model were also calculated. Finally, the overall uncertainty of individual tree biomass by combining the two uncertainties was calculated. The allometric model including tree height was 6 % more accurate than that excluding tree height when the uncertainty caused by allometric models became the only consideration. However, in terms of the uncertainty caused by measurement, the allometric model excluding tree height was three times more accurate than allometric model including tree height. As a result, the allometric model excluding tree height was 5 % more accurate than the allometric model including tree height when both causes of uncertainty, the allometric model and measurement errors were considered. In conclusion, errors in tree height measurement have the potential to increase the error of aboveground biomass estimation.

Cambodia covers 181,035 km2 (a little over half size of Vietnam), among them, the forest area is cover about 53 percent, so there are abundant insects diversities. The family Arctiidae so called tiger moths are belonging to superfamily Noctuoidea, with more than 11,155 named species of 750 genera are distributed worldwide (Heppner, 2005). Taxonomic study of the Arctiidae in Cambodia has been done by a few foreign entomologists (). In the present study, we were collected four times from 2009–2010 in three protected forests are Seima, Central Cardamom, and North Cardamom. Each time, we were collected from 3 to 5 sites in each forest by using light trap. As a result of this study, a total of 183 species of 13 families belonging to Lepidoptera. Of which, 70 species of 32 genera of 2 subfamilies (Lithosiinae and Arctiinae) belonging to Arctiidae family were identified from Cambodia.