Population, Land Use and Deforestation in the Pan Amazon Basin: a Comparison of Brazil, Bolivia, Colombia, Ecuador, Perú and Venezuela

This paper discusses the linkages between population change, land use, and deforestation in the Amazon regions of Brazil, Bolivia, Colombia, Ecuador, Perú, and Venezuela. We begin with a brief discussion of theories of population–environment linkages, and then focus on the case of deforestation in the PanAmazon. The core of the paper reviews available data on deforestation, population growth, migration and land use in order to see how well land cover change reflects demographic and agricultural change. The data indicate that population dynamics and net migration exhibit to deforestation in some states of the basin but not others. We then discuss other explanatory factors for deforestation, and find a close correspondence between land use and deforestation, which suggests that land use is loosely tied to demographic dynamics and mediates the influence of population on deforestation. We also consider national political economic contexts of Amazon change in the six countries, and find contrasting contexts, which also helps to explain the limited demographic-deforestation correspondence. The paper closes by noting general conclusions based on the data, topics in need of further research and recent policy proposals.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42720/1/10668_2003_Article_6977.pd

Symbolic Decision Procedures for QBF

Much recent work has gone into adapting techniques that were originally developed for SAT solving to QBF solving. In particular, QBF solvers are often based on SAT solvers. Most competitive QBF solvers are search-based. In this work we explore an alternative approach to QBF solving, based on symbolic quantifier elimination. We extend some recent symbolic approaches for SAT solving to symbolic QBF solving, using various decision-diagram formalisms such as OBDDs and ZDDs. In both approaches, QBF formulas are solved by eliminating all their quantifiers. Our first solver, QMRES, maintains a set of clauses represented by a ZDD and eliminates quantifiers via multi-resolution. Our second solver, QBDD, maintains a set of OBDDs, and eliminate quantifier by applying them to the underlying OBDDs. We compare our symbolic solvers to several competitive search-based solvers. We show that QBDD is not competitive, but QMRES compares favorably with search-based solvers on various benchmarks consisting of non-random formulas