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We examined a new method to detect the biodiversity hotspots in terms of complex patch mosaics at a regional scale in East Java, Indonesia, in order to develop the safeguard against further expansion of monocultures by REDD+. A land-cover map consisting of five major landcover types (forest, agricultural land, bare land, water, and residential) was generated with a 30 m x 30 m resolution by the unsupervised classification of a Landsat8-OLI image. Shannon's diversity index (H') was calculated for each of 10.98 ha (11 x 11 pixels) landscape throughout the study area based on the dominance of the land-cover types by five calculation methods with different combinations of landcover types. Then, the landscapes of upper 5% in H' was selected as the potential hotspots in terms of highly complex patch mosaics. Among the five potential hotspots, the calculation of H' with four landcover types (forest, agriculture, water and bare land) was thought to be most suitable to set conservation targets at a regional scale, because the potential hotspots by this method showed aggregated distribution patterns, and was less sensitive to the small residential patches. While, no clear distribution trend was observed along the environmental gradients stage. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]