Over the last three decades, the first continuous road has been paved to connect northern South America’s Atlantic and Pacific coasts. The final sections of this Inter-Oceanic Highway are now being completed through the western Amazon Basin, a global biodiversity hotspot, at the triple-border of Brazil, Bolivia and Peru. Satellite images from 1989, 2000, and 2007 reveal accelerating clearing across the region, but the countries’ prior infrastructures governed their individual responses to the road. Brazilian deforestation slowed as the frontier expanded away from the highway with a network of capillary roads, but Bolivian clearing accelerated as its urban centers sprawled toward the road. Peru’s forests remain relatively intact, but similar trends isolated from Brazil suggest imminent acceleration as Peruvian infrastructural capacity increases.
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The Selva Maya is an important tropical forest, the second biggest in the Americas after the Amazon and the largest continuous forest patch of the ‘Mesoamerican hotspot’ which contains around 7% of the world species . Located across Mexico, Belize and Guatemala, Selva Maya is subject to different policy, cultural and historical influences and to a grand road expansion program that will intersect its core . Given its biological importance and the environmental services it provides at a local and global scale, this region is a good case to consider road impacts. We focus on four questions: 1) what are the short and medium term effects of paved and unpaved roads investments on deforestation?; 2) do these impacts differ when roads are placed in areas with existing pressure vs. in less developed locations?; 3) do the effect of non-road drivers also vary with development contexts? We might expect that roads in previously pristine areas a new road will be the dominant predictor; and 4) using a different measure of context, do road impacts vary across the countries?
Entry Points for Considering Ecosystem Services within Infrastructure Planning: how to integrate conservation with development in order to aid them both
New infrastructure is needed globally to support economic development and improve human well-being. Investments that do not consider ecosystem services (ES) can eliminate these important societal benefits from nature, undermining the development benefits infrastructure is intended to provide. Such tradeoffs are acknowledged conceptually but in practice have rarely been considered in infrastructure planning. Taking road investments as one important case, here we examine where and what forms of ES information have the potential to meaningfully influence decisions by multilateral development banks (MDBs). Across the stages of a typical road development process, we identify where and how ES information could be integrated, likely barriers to the use of available ES information, and key opportunities to shift incentives and thereby practice. We believe inclusion of ES information is likely to provide the greatest development benefit in early stages of infrastructure decisions. Those strategic planning stages are typically guided by in-country processes, with MDBs playing a supporting role, making it critical to express the ES consequences of infrastructure development using metrics relevant to government decision makers. This approach requires additional evidence of the in-country benefits of cross-sector strategic planning and more tools to lower barriers to quantifying these benefits and facilitating ES inclusion.
We examine the evidence on Amazonian road impacts with a strong emphasis on context. Impacts of a new road, on either deforestation or socioeconomic outcomes, depend upon the conditions into which roads are placed. Conditions that matter include the biophysical setting, such as slope, rainfall, and soil quality, plus externally determined socioeconomic factors like national policies, exchange rates, and the global prices of beef and soybeans. Influential conditions also include all prior infrastructural investments and clearing rates. Where development has already arrived, with significant economic activity and clearing, roads may decrease forest less and raise output more than where development is arriving, while in pristine areas, short-run clearing may be lower than immense long-run impacts. Such differences suggest careful consideration of where to invest further in transport.
Understanding the impact of road investments on deforestation is part of a complete evaluation of the expansion of infrastructure for development.We find evidence of spatial spillovers from roads in the Brazilian Amazon: deforestation rises in the census tracts that lack roads but are in the same county as and within 100 km of a tract with a new paved or unpaved road. At greater distances from the new roads the evidence is mixed, including negative coefficients of inconsistent significance between 100 and 300 km, and if anything, higher neighbor deforestation at distances over 300 km.
While previous empirical analysis of deforestation focused on population, this paper builds from a model of land use which suggests many determinants of deforestation in the Brazilian Amazon. I derive a deforestation equation from this model and test a number of those factors using county-level data for the period 1978-1988. The data include a satellite deforestation measure which allows improved within-country analysis. The major empirical finding is the significance of both land characteristics (such as soil quality and vegetation density) and factors affecting transport costs (such as distance to major markets and both own- and neighboring-county roads). Government development projects also appear to affect clearing, although credit infrastructure does not. However, as such policies themselves may be functions of other factors, estimated effects of policies must be interpreted with some caution. Finally, the population density does not have a significant effect on deforestation when many potential determinants are included. However, a quadratic specification reveals a more robust result: the first migrants to a county have greater impact than later immigrants. This implies that the distribution of population affects its impact.