Estimating the Spatial Amplification of Damage Caused by Degradation in the Amazon

Working Paper: NBER ID: w31550

Authors: Rafael Araujo; Juliano Assuno; Marina Hirota; José A. Scheinkman

Abstract: The Amazon rainforests have been undergoing unprecedented levels of human-induced disturbances. In addition to local impacts, such changes are likely to cascade following the eastern-western atmospheric flow generated by trade winds. We propose a model of spatial and temporal interactions created by this flow to estimate the spread of local disturbances to downwind locations along atmospheric trajectories. The spatial component captures cascading effects propagated by neighboring regions while the temporal component captures persistence. All these network effects can be described by a single matrix, acting as a spatial multiplier that amplifies local disturbances. This matrix can be used to easily map where the damage of an initial forest disturbance is amplified and propagated to. We identify regions that are likely to cause the largest impact throughout the basin, and those that are the most vulnerable to shocks caused by remote deforestation. On average, the presence of cascading effects mediated by winds doubles the impact of an initial damage. However, there is heterogeneity in this impact. While damage in some regions does not propagate, in others amplification may reach 250%.

Keywords: Amazon rainforest; forest degradation; spatial amplification; climate change; causal modeling

JEL Codes: C23; Q54; Q57


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Local disturbances (D59)Leaf Area Index (LAI) (Q24)
Atmospheric pathways (Q59)Amplification of disturbances (E32)
Local disturbances (D59)Spatial propagation of disturbances (C69)
Leaf Area Index (LAI) at a location (Q24)Leaf Area Index (LAI) of upwind locations (R14)
Cascading effects mediated by winds (Q54)Understanding dynamics (C69)

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