A Bayesian Spatial Model Highlights Distinct Dynamics in Deforestation from Coca and Pastures in an Andean Biodiversity Hotspot

Abstract

Abstract:The loss of tropical forests has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. Here, we examine the conversion of forests to pastures and coca crops (illicit activity) on the San Lucas Mountain Range, Colombia for 2002-2007 and 2007-2010. Land use maps and biophysical variables were used as inputs to generate land use and cover change (LUCC) models using the DINAMICA EGO software. These analyses revealed a dramatic acceleration of the pace of deforestation in the region, with rates of conversion from forest to pasture doubling from the first to the second period. Altitude, distance to other crops, and distance to rivers were the primary drivers of deforestation. The influence of these drivers, however, differed markedly depending on whether coca cultivation or pastures replaced forest. Conversion to coca was more probable farther from other crops and from settlements. In contrast, proximity to other crops and to settlements increased conversion to pasture. These relationships highlight the different roles of coca and pastures in forest loss, OPEN ACCESSForests 2015, 6 3829 with coca tending to open up new forest frontiers, and pastures tending to consolidate agricultural expansion and urban influence. Large differences between LUCC processes for each period suggest highly dynamic changes, likely associated with shifting underlying causes of deforestation. These changes may relate to shifts in demand for illicit crops, land, or mining products; however, the data to test these hypotheses are currently lacking. More frequent and detailed monitoring is required to guide actions to decrease the loss of forest in this highly vulnerable biodiversity hotspot in the Northern Andes.

Spatial autocorrelation reduces model precision and predictive power in deforestation analyses

“…Clear‐cutting in the western Caribbean coast is a destructive yet locally constrained phenomenon (Chadid et al. ). The effect of fires is not as strong elsewhere in the country.…”

“…Fires in the western Caribbean region are associated with clear-cutting preceding development of agricultural land, and this association with deforestation is lost for municipalities east of the Magdalena River. Clear-cutting in the western Caribbean coast is a destructive yet locally constrained phenomenon (Chadid et al 2015). The effect of fires is not as strong elsewhere in the country.…”

Drivers of forest cover changes in the Chocó‐Darien Global Ecoregion of South America

“…Traditionally, the effect of direct and indirect drivers on forest transitions is estimated using different types of regressions (linear regression, logistic regression, generalized linear models, random forest regression, etc. ; Roberts et al 2002, Armenteras et al 2006, Flamenco-Sandoval et al 2007, Hosonuma et al 2012, Houghton 2012, Kissinger et al 2012, Mueller et al 2012, Tng et al 2012, Sanchez-Cuervo and Aide 2013, Alejandra Chadid et al 2015, Leblois et al 2017; these statistical tests assume that all direct and indirect drivers as predictors have the same potential direct effect on a forest transition, deforestation, or reforestation. However, the "equality of effect" assumption is not consistent with the analysis of direct and indirect drivers of forest transitions (see Lambin 2001, 2002).…”

“…Causes of forest change can be classified into two types: (1) direct drivers (proximate or direct causes) which are immediate actions that directly result in forest loss or gain; in other words, direct drivers refer to the land cover that replaces forest or converts back to forest; (2) indirect drivers (underling or indirect causes) are interactions of social, economic, political, cultural, or other processes that indirectly affect forest changes Lambin 2001, 2002). The previous statement has been the basis for a wide array of literature focused on studying direct (Roberts et al 2002, Flamenco-Sandoval et al 2007, Houghton 2012, Mueller et al 2012, Tng et al 2012, Alejandra Chadid et al 2015, Armenteras et al 2017 or indirect drivers (Armenteras et al 2006, Hosonuma et al 2012, Kissinger et al 2012, Mueller et al 2013, Leblois et al 2017 to assess forest cover change at different spatial scales throughout the tropical rain forest domain. Studies that include both direct and indirect drivers as well as their interactions have been less prevalent (Davalos et al 2014, Richards 2015.…”

Avaliação da influência da infraestrutura de transporte nas mudanças de uso e cobertura da terra através de modelagem dinâmica espacial.

“…Este modelo tem sido largamente usado para modelar desmatamentos (CHADID et al, 2015;STAN et al, 2015), regenerações florestais (MALEK et al, 2015), alterações no uso do solo urbano (ALMEIDA et al, 2003b;ALMEIDA, 2004;ALMEIDA, et al, 2005;AKIN et al, 2015), dinâmicas da cobertura da terra Atualmente, há na literatura cientifica uma percepção bastante difundida na qual se afirma que os sistemas viários para transporte de pessoas e cargas em conjunto com a cobertura da terra fazem parte de um sistema dinâmico intimamente integrado, cujas interações interferem mutuamente em suas estruturas.…”