Spillover effect offsets the conservation effort in the Amazon

doi:10.1007/s11442-018-1539-0

Abstract

Abstract:

Diverse conservation efforts have been expanding around the globe, even under the stress of increasing agricultural production. A striking example is the supply-chain agreements put upon the Amazon forest which had reduced deforestation by 80% from the early 2000s (27,772 km²) to 2015 (6207 km²). However, evaluation of these conservation efforts usually focused on the impacts within the Amazon biome only, while the effects that spill over to other areas (e.g., displacement of environmental pressure from one area to another) were rarely considered. Ignoring spillover effects may lead to biased or even wrong conclusions about the effectiveness of these conservation efforts because the hidden cost outside the target area of conservation may offset the achievement within it. It is thus important to assess the spillover effects of these supply-chain agreements. In this study, we used the two supply-chain agreements (i.e., Soy Moratorium and zero-deforestation beef agreement) implemented in the Amazon biome as examples and evaluated their spillover effects to the Cerrado. To achieve a holistic evaluation of the spillover effects, we adopted the telecoupling framework in our analysis. The application of the telecoupling framework includes the interactions between distant systems and extends the analytical boundaries beyond the signatory areas, which fill the gap of previous studies. Our results indicate that the supply-chain agreements have significantly reduced deforestation by half compared to projections within the sending system (i.e., Pará State in the Amazon, which exports soybeans and other agricultural products), but at the cost of increasing deforestation in the spillover system (i.e., a 6.6 time increase in Tocantins State of the Cerrado, where deforestation was affected by interactions between the Amazon and other places). Our study emphasizes that spillover effects should be considered in the evaluation and planning of conservation efforts, for which the telecoupling framework works as a useful tool to do that systematically.

Key words: telecoupling, Amazon, Cerrado, Brazil, soybean trade, spillover, voluntary agreement, deforestation, conservation, development

Yue DOU, Felipe Bicudo da SILVA Ramon, Hongbo YANG, Jianguo LIU. Spillover effect offsets the conservation effort in the Amazon[J].Journal of Geographical Sciences, 2018, 28(11): 1715-1732.

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Reference	Region	Temporal period	Land use and land cover changes	Control variables	Model or method	Analytical framework
Macedo et al., 2012	Mato Grosso	2001-2010	Post-deforestation land use, indirect land use	Market trends Climate variability Yield Cost of production	Correlation	No framework used, identified policies and market trends as external factors to land use changes in MT.
Richards et al., 2014	Amazon	2002-2011	Deforestation, indirect land use	Market trends Local effects Indirect agricultural influence	Spatial regression	No framework used, indirect influence was calculated as weighted distance.
Arima et al., 2011	Legal Amazon	2003-2008	Deforestation, indirect land use	Soybean planted area Cattle herd Precipitation Farm gate price for cattle	Fixed effect spatial regression	No framework used, distance was measured in the regression.
Barona et al., 2010	Legal Amazon	2001-2006	Deforestation, indirect land use	Pasture land change, Cropland change	Linear regression	No framework
Spera et al., 2014	Mato Grosso	2001-2011	Land use transition	Land characters	t-test	No framework

	PA coefficient	P-value	TO coefficient	P-value
(Intercept)	-2.44	***	-0.46
Soybean price lagged	-0.30		0.12
Soybean price current	0.78	*	-3.35	***
Post2006	0.46		-0.70	**
Soybean price lagged: Post2006	0.59		-0.84
Soybean price current: Post2006	-1.74	***	4.05	***
Beef price current	0.06		-0.04
Beef price lagged	-0.10	*	-0.19	**
Post2009	-0.59	*	-0.85	**
Beef price current: Post2009	-0.10		0.01
Beef price lagged: Post2009	0.18	.	0.29	***
Road density	0.61	***	-1.32	*
Distance to closest major ports	0.00	***	0.00
Available area	0.39	***	0.76	***
R-square	0.53		0.34

	Pará		Tocantins
	Correlation	Significance	Correlation	Significance
Deforestation_t			+	***
Deforestation _t_-1
Deforestation _t_-2	+	**
Soybean yield	+	***	+	***
Soybean price _t			+	***
Soybean price_t_-1			+	***

Sending (Pará)	Sample size	Soybean yield impact	R²
Current model	748	Not applicable	0.59
Soybean yield	203	Not significant	0.63
GDP industry _t _& _t_-1	543	Not significant	0.59
Spillover (Tocantins)	Sample size	Soybean yield impact	R²
Current model	1186	Not applicable	0.35
Soybean yield	580	Not significant	0.36
GDP industry _t_&_t_-1	782	Not significant	0.32