An integrated pan-tropical biomass map using multiple reference datasets.

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

BACKGROUND: Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. RESULTS: Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. CONCLUSIONS: Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

Ecological strategies of woolly monkeys (Lagothrix lagotricha) at Tinigua National Park, Colombia.

Information on the use of space, activity patterns, diet, and social interactions were recorded for a group of woolly monkeys (Lagothrix lagotricha) during 13 months at Tinigua National Park, Macarena, Colombia. In this region, fruit abundance changes throughout the year with a peak during March-April (beginning of the rainy season) and less fruit during September-November (end of rainy season). Woolly monkeys spent most of their time in mature forest where fruit abundance is higher than in opendegraded or flooded forests. Changes in habitat used by monkeys were coupled with changes in fruit supply across vegetation types. On an annual basis, woolly monkeys spent 24% of point samples locomoting, 36% resting, 36% feeding, and 4% on other activities. However, these proportions varied across the year depending on fruit availability. Based on instantaneous samples, the diet consisted mostly of fruits (60%), arthropods (23%), vegetative parts and flowers (17%), and other items (1%). Non-lactating females and juveniles spent more time eating insects than adult males and lactating females; however, significant differences between classes were detected only during the period of fruit scarcity. These differences are probably due to the high extent to which non-lactating females and juveniles were excluded from fruiting trees by males. The high proportion of arthropods in their diet is unusual for primates with large body size and is a possible factor influencing group cohesiveness in woolly monkeys. © 1994 Wiley-Liss, Inc.