University of Los Andes

About: University of Los Andes is a education organization based out in Bogotá, Colombia. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 17616 authors who have published 25555 publications receiving 413463 citations.

The regional variation of aboveground live biomass in old‐growth Amazonian forests

Abstract: The biomass of tropical forests plays an important role in the global carbon cycle, both as a dynamic reservoir of carbon, and as a source of carbon dioxide to the atmosphere in areas undergoing deforestation. However, the absolute magnitude and environmental determinants of tropical forest biomass are still poorly understood. Here, we present a new synthesis and interpolation of the basal area and aboveground live biomass of old-growth lowland tropical forests across South America, based on data from 227 forest plots, many previously unpublished. Forest biomass was analyzed in terms of two uncorrelated factors: basal area and mean wood density. Basal area is strongly affected by local landscape factors, but is relatively invariant at regional scale in moist tropical forests, and declines significantly at the dry periphery of the forest zone. Mean wood density is inversely correlated with forest dynamics, being lower in the dynamic forests of western Amazonia and high in the slow-growing forests of eastern Amazonia. The combination of these two factors results in biomass being highest in the moderately seasonal, slow growing forests of central Amazonia and the Guyanas (up to 350?Mg?dry weight?ha?1) and declining to 200-250?Mg?dry weight?ha?1 at the western, southern and eastern margins. Overall, we estimate the total aboveground live biomass of intact Amazonian rainforests (area 5.76 × 106?km2 in 2000) to be 93±23?Pg?C, taking into account lianas and small trees. Including dead biomass and belowground biomass would increase this value by approximately 10% and 21%, respectively, but the spatial variation of these additional terms still needs to be quantified

Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation

Abstract: We propose a unified approach for bottom-up hierarchical image segmentation and object proposal generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective use of multiscale information. Finally, we propose a grouping strategy that combines our multiscale regions into highly-accurate object proposals by exploring efficiently their combinatorial space. We also present Single-scale Combinatorial Grouping (SCG), a faster version of MCG that produces competitive proposals in under five seconds per image. We conduct an extensive and comprehensive empirical validation on the BSDS500, SegVOC12, SBD, and COCO datasets, showing that MCG produces state-of-the-art contours, hierarchical regions, and object proposals.

Behavioural Development Economics: Lessons from Field Labs in the Developing World

Abstract: Explanations of poverty, growth and development depend on the assumptions made about individual preferences and the willingness to engage in strategic behaviour. Economic experiments, especially those conducted in the field, have begun to paint a picture of economic agents in developing communities that is at variance with the traditional portrait. We review this growing literature with an eye towards preference-related experiments conducted in the field. We also offer lessons on what development economists might learn from experiments. We conclude by sharing our thoughts on how to conduct experiments in the field and then offer a few ideas for future research.