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We studied the autumn food habits of the Asiatic black bear (Ursus thibetanus) from 1993 to 1997, based on 202 fecal samples in the Chichibu Mountains, central Japan. Nuts occupied the highest proportions of autumn foods (59.9–85.8% important values). Although the proportion of nuts of Quercus crispula, Fagus crenata and Fagus japonica varied greatly between the years, acorns of Q. crispula were most prevalent in four of the five years. We also determined the relative nut production of these three species by counting the number of nuts or cupules on the ground. Black bears consumed the nuts according to their relative availabilities. Nuts of Q. crispula appeared to be the most important food because: (i) these nuts were eaten in the highest proportion in four of the five study years; and (ii) even in poor years the bears consumed acorns of Q. crispula, whereas nuts of Fagus spp. were not consumed. We discuss the significance of alternative foods for black bears in relation to food tree diversity in the forest and the necessity for long‐term studies examining the food habits of Asiatic black bears.

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal.

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