Article

Land-Use Allocation Protects the Peruvian Amazon

Department of Global Ecology, Carnegie Institution of Washington, Stanford, CA 94305, USA.
Science (Impact Factor: 33.61). 09/2007; 317(5842):1233-6. DOI: 10.1126/science.1146324
Source: PubMed

ABSTRACT

Disturbance and deforestation have profound ecological and socioeconomic effects on tropical forests, but their diffuse patterns
are difficult to detect and quantify at regional scales. We expanded the Carnegie forest damage detection system to show that,
between 1999 and 2005, disturbance and deforestation rates throughout the Peruvian Amazon averaged 632 square kilometers per
year and 645 square kilometers per year, respectively. However, only 1 to 2% occurred within natural protected areas, indigenous
territories contained only 11% of the forest disturbances and 9% of the deforestation, and recent forest concessions effectively
protected against clear-cutting. Although the region shows recent increases in disturbance and deforestation rates and leakage
into forests surrounding concession areas, land-use policy and remoteness are serving to protect the Peruvian Amazon.

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    • "Colombia's annual deforestation rate was 0.62% between 1990 and 2005 (Armenteras, Cabrera, Rodríguez, & Retana, 2013), while Bolivia lost 0.48% of its forests per year between 2001 and 2004 (Killeen et al., 2007)Ichikawa, Ricse, Ugarte, & Kobayashi, 2014) and immigrants from other regions (Goy & Waltner-Toews, 2005). Particularly , migration from the Peruvian Andes is known to be an important cause for population growth and a driver of deforestation in the Ucayali region (Guerra, 2009;Oliveira et al., 2007;Perz, Aramburú, & Bremner, 2005). Settlement policies and development programs in the 1940s used to promote Andean migration to the Amazon region. "
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    ABSTRACT: This study examines the relation between primary forest loss and landscape characteristics in the Ucayali region, Peru. Seven variables (rivers, elevation, annual precipitation, soil suitability for agriculture, population density, paved roads, and unpaved roads), were identified as potential deforestation drivers. The variables were converted into spatially explicit layers of continuous data and divided into a 9 km2 grid. A multiple regression analysis was conducted to determine variable significance. Distance to paved and unpaved roads were strongly associated with deforestation, followed by distance to rivers, annual precipitation and elevation. All significant variables were negatively correlated with deforestation. Variables excluded from the model were population density and soil suitability for agriculture, suggesting that the influence of population density on forest clearing across the study area was not significant, and that deforestation activities were undertaken regardless whether soils are suitable for agriculture or not. Based on the linear regression analysis, the significant variables were selected and added to the Land Change Modeler in order to project primary forest coverage by 2025. The modeling results predict extensive deforestation along the Aguaytia River and at the forest/non-forest interface along the paved highway. The rate of primary forest removal is expected to increase from 4783 ha y−1 (for the 2007–2014 period) to 5086 ha y−1 (for the 2015–2025 period). A preliminary survey questionnaire conducted to explore deforestation intentions by farmers in the region, partly confirmed the overall deforestation trends as projected by the model.
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    • "Edición extraordinaria -53- comunidades científicas de investigaciones de cambios globales han recalcado la necesidad de intensificar el enfoque de estudio hacia la evaluación de la dinámica de cambios (Lambin & Geist, 2006; Turner et al., 2004; Fox et al., 2003; Oliveira et al., 2007). La estimación de áreas deforestadas y los estudios de tasas de deforestación son pasos importantes para cuantificar el valor del bosque y los servicios ecosistémicos de los bosques tropicales. "
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    • "The study region has been connected to Lima and other urban centers in the coast and mountains of Peru by a highway and networks of roads for more than six decades. It has attracted many migrants from elsewhere in Peru in recent years (Uriarte et al., 2012) and has undergone extensive land-use change and deforestation including conversion of forest to oil palm (Gutié rrez-Vé lez and DeFries, 2013; Oliveira et al., 2007). Since the early 1980s, there has been significant rural-to-urban migration, with 75% of the population living in cities as of 2007, up from 56% in 1972 (Instituto, 2009). "
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