Is small-scale agriculture really the main driver of deforestation in the Peruvian Amazon? Moving beyond the prevailing narrative

A key premise underlying discussion about deforestation in Amazonian Peru is that small-scale or so-called migratory agriculture is the main driver of deforestation. This premise has been expressed in government documents and public outreach events. How the Peruvian government understands drivers of deforestation in the Amazon has profound implications for how it will confront the problem. It is therefore important to critically revisit assumptions under-lying this narrative. We find that the narrative is based on remote sensing of deforestation patch sizes but not on field data, potentially conflating distinct drivers of deforestation under the umbrella of “migratory,” “small-scale,” or “subsistence” agriculture. In fact, small patches of deforested land may indicate any number of processes, including sustainable fallow management and agroforestry. Moreover, the data underlying the narrative tell us little about the actors driving these processes or their motivations. Different pro-cesses have distinct implications for environmental sustainability and require targeted policy responses. We unpack these diverse actors, geographies, and motivations of small-patch deforestation in the Peruvian Amazon and argue that differentiating among these drivers is necessary to develop appropriate policy responses. We call for researchers to revisit assumptions and critically assess the motivations of observed deforestation to appropriately target policy action

The Effect of Trade Openness on Deforestation: Empirical Analysis for 142 Countries

This study explores the effect of trade openness on deforestation. Previous studies do not find a clear effect of trade openness on deforestation. We use updated data on the annual rate of deforestation for 142 countries from 1990 to 2003, treat trade and income as endogenous, and take into consideration an adjustment process by applying a dynamic model. We find that an increase in trade openness increases deforestation for non-OECD countries while slowing down deforestation for OECD countries. There is a possibility that both capital-labor and environmental-regulation effects have a negative impact on deforestation in developing countries, whereas the opposite holds in developed countries.Trade Openness; Environment; Comparative Advantage; Deforestation

Deforestation in the Tropics: Reconciling Disparities in Estimates for India

Here we examine recent disparate estimates of deforestation obtained for India. We discuss the sources of disparity and the implications of inaccurate estimates and suggest ways in which future attempts at estimating deforestation might reconcile the disparity. Despite the importance of deforestation and its consequences, no attempt has been made to reconcile the different estimates obtained for India

Environmental Costs of Government-Sponsored Agrarian Settlements in Brazilian Amazonia

Brazil has presided over the most comprehensive agrarian reform frontier colonization program on Earth, in which ~1.2 million settlers have been translocated by successive governments since the 1970's, mostly into forested hinterlands of Brazilian Amazonia. These settlements encompass 5.3% of this ~5 million km2 region, but have contributed with 13.5% of all land conversion into agropastoral land uses. The Brazilian Federal Agrarian Agency (INCRA) has repeatedly claimed that deforestation in these areas largely predates the sanctioned arrival of new settlers. Here, we quantify rates of natural vegetation conversion across 1911 agrarian settlements allocated to 568 Amazonian counties and compare fire incidence and deforestation rates before and after the official occupation of settlements by migrant farmers. The timing and spatial distribution of deforestation and fires in our analysis provides irrefutable chronological and spatially explicit evidence of agropastoral conversion both inside and immediately outside agrarian settlements over the last decade. Deforestation rates are strongly related to local human population density and road access to regional markets. Agrarian settlements consistently accelerated rates of deforestation and fires, compared to neighboring areas outside settlements, but within the same counties. Relocated smallholders allocated to forest areas undoubtedly operate as pivotal agents of deforestation, and most of the forest clearance occurs in the aftermath of government-induced migration

A Re-examination of Causes of Deforestation and Environmental Kuznets Curve: Evidences from Latin America, Africa and Asia

Previous cross-country regression analyses on the causes of deforestation seem to have misspecified the regression models, in which the causes at different levels are mixed, leading to flawed cause-effect relationship between the rate of deforestation and its explanatory variables. The paper focuses explicitly on underlying/policy-oriented causes of deforestation and then examines their relationship with rate of deforestation across 43 countries of Latin America, Africa and Asia. An environmental Kuznets Curve (EKC) relationship between rate of deforestation and income is also tested. Results across all regions and based on panel data technique show that forest and allied (non-forest) sector policies and population density increase deforestation, while forest products export promotion policies, export prices and technological progress decrease deforestation. The effects of per capita income, economic growth and agricultural production are found to be varying in different region. An inverted U-shaped EKC empirically fits for Latin America and Africa while a U-shaped EKC does the same for Asia.Africa; Asia; environmental Kuznets Curve; cross-country analysis; Latin America; underling/policy-oriented causes of deforestation; deforesta tion

Effectiveness of China's National Forest Protection Program and nature reserves

There is profound interest in knowing the degree to which China's institutions are capable of protecting its natural forests and biodiversity in the face of economic and political change. China's 2 most important forest-protection policies are its National Forest Protection Program (NFPP) and its national-level nature reserves (NNRs). The NFPP was implemented in 2000 in response to deforestation-caused flooding. We undertook the first national, quantitative assessment of the NFPP and NNRs to examine whether the NFPP achieved its deforestation-reduction target and whether the NNRs deter deforestation altogether. We used MODIS data to estimate forest cover and loss across mainland China (2000-2010). We also assembled the first-ever polygon dataset for China's forested NNRs (n = 237, 74,030 km(2) in 2000) and used both conventional and covariate-matching approaches to compare deforestation rates inside and outside NNRs (2000-2010). In 2000, 1.765 million km(2) or 18.7% of mainland China was forested (12.3% with canopy cover of >= 70%)) or woodland (6.4% with canopy cover = 40%). By 2010, 480,203 km(2) of forest and woodland had been lost, an annual deforestation rate of 2.7%. Forest-only loss was 127,473 km(2) (1.05% annually). In the NFPP provinces, the forest-only loss rate was 0.62%, which was 3.3 times lower than in the non-NFPP provinces. Moreover, the Landsat data suggest that these loss rates are overestimates due to large MODIS pixel size. Thus, China appears to have achieved, and even exceeded, its target of reducing deforestation to 1.1% annually in the NFPP provinces. About two-thirds of China's NNRs were effective in protecting forest cover (prevented loss 4073 km(2) unmatched approach; 3148 km(2) matched approach), and within-NNR deforestation rates were higher in provinces with higher overall deforestation. Our results indicate that China's existing institutions can protect domestic forest cover

Type-Inference Based Short Cut Deforestation (nearly) without Inlining

Deforestation optimises a functional program by transforming it into another one that does not create certain intermediate data structures. In [ICFP'99] we presented a type-inference based deforestation algorithm which performs extensive inlining. However, across module boundaries only limited inlining is practically feasible. Furthermore, inlining is a non-trivial transformation which is therefore best implemented as a separate optimisation pass. To perform short cut deforestation (nearly) without inlining, Gill suggested to split definitions into workers and wrappers and inline only the small wrappers, which transfer the information needed for deforestation. We show that Gill's use of a function build limits deforestation and note that his reasons for using build do not apply to our approach. Hence we develop a more general worker/wrapper scheme without build. We give a type-inference based algorithm which splits definitions into workers and wrappers. Finally, we show that we can deforest more expressions with the worker/wrapper scheme than the algorithm with inlining