Stopping Deforestation: What Works and What Doesn't

CGD Climate and Forest Paper Series #3

The Many Benefits of Forests

Forests provide a wealth of public and private goods and services, including carbon storage, biodiversity, water filtration, storm mitigation, timber and nontimber products, wild foods and medicines, and tourism. Yet despite its inherent value, forested land is being cleared for other uses such farming, pasturing, mining, and urban development. Every year claims a net forest loss of 125,000 square kilometers—an area the size of Greece or Mississippi—and that rate is increasing by 2,000 square kilometers per year.^[1] Of the current net forest loss, 58 percent is in the tropics, where forests are being converted to cropland and pasture for the production of soy, beef, palm oil, and timber.

A variety of deliberate policies have been devised to slow the rate of deforestation. Forested countries have designated protected areas, increased law enforcement, and set up programs to pay for ecosystem services; consumer countries have placed import restrictions on illegal tropical timber; and private supply-chain actors have introduced eco-labeling, certification, and sustainable sourcing measures. As international concern about climate change has grown, attention has intensified on reducing the 10–15 percent of global greenhouse gas emissions resulting from deforestation and forest degradation (REDD+).

Investigating Drivers of Deforestation

All efforts to safeguard forests benefit from research on the factors that drive deforestation and the policies that can stop it. Dozens of individual spatially explicit econometric studies of deforestation have investigated drivers of deforestation in particular places at particular times. Several previous articles have reviewed this literature (see further reading), but until now, no systematic and comprehensive review of these studies has been produced. By examining all such studies collectively, we are able to quantify and compare the relative influence on deforestation of dozens of commonly studied factors.

We compiled a comprehensive database of all spatially explicit econometric studies of deforestation that met five prespecified criteria. ^[2] This resulted in a database of 117 studies published in peer-reviewed academic journals from 1996 to 2013, spanning 36 countries, and covering two-thirds of all tropical forests. These studies collectively contained 1,159 uniquely named explanatory variables, which we grouped into 40 categories. We counted the number of times that variables in each category were shown to be positively associated with deforestation, negatively associated, or neither (see figure 1). Understanding which factors are consistently associated with higher or lower rates of deforestation can assist public agencies seeking to conserve forests for their many public and private values (see box 1 for a summary of the most promising approaches).

Figure 1: What Drives Deforestation and What Stops It? A Meta-Analysis

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Ratio of regression coefficients showing significant negative association with deforestation to regression coefficients showing significant positive association with deforestation, based on 5,605 regression coefficients in 117 spatially explicit econometric studies. “Not significant” denotes not statistically significantly different from 1:1 in a two-tailed t-test at the 95 percent confidence level. Results displayed for the 20 most commonly included meta-variables only; meta-variables with fewer than 55 coefficients are not displayed.

What Drives Deforestation, and What Stops It?

Agricultural variables are consistently associated with higher deforestation. This is not surprising since most forestland is cleared for agriculture and pasture. However, agricultural effects vary across mechanized agriculture, small-scale agriculture, and cattle ranching. (Evidence base: 17 countries on 5 continents)

Biophysical variables (physical characteristics of the land and forest) have a clear impact on deforestation by affecting accessibility, clearing costs, and agricultural productivity. Deforestation is consistently lower at higher elevations, on steeper slopes, and in wetter areas, whereas it is consistently higher on soil that was more suitable for agriculture. Proximity to water is not significantly associated with higher or lower deforestation. (Evidence base: 34 countries on 5 continents)

Built infrastructure is consistently associated with higher deforestation. Proximity to roads and urban areas increases deforestation by lowering transportation costs to markets, by making frontier land more accessible to new migrants, and by enabling remote economies to transform from local subsistence agriculture to market-oriented farming systems. (Evidence base: 33 countries on 5 continents)

Community forest management is not consistently associated with either higher or lower deforestation. (Evidence base: El Salvador, Ethiopia, Guatemala, Mexico)

Demographic variables, such as age, education, gender, or property size, have no consistent association with either higher or lower deforestation. (Evidence base: 17 countries on 4 continents)

Indigenous peoples are consistently associated with low deforestation in areas with both low and high levels of baseline threat. (Evidence base: Bolivia, Brazil, Mexico)

Land-tenure security shows no consistent association with either higher or lower deforestation. While more secure property rights for indigenous peoples is sometimes associated with lower deforestation, more secure land tenure can also increase investment, leading to greater deforestation. The converse is sometimes true: insecure property rights can reduce the present value of standing forests and encourage owners to convert the land to benefit from more productive uses and to reduce the risk of expropriation. (Evidence base: 9 countries on 3 continents)

Law enforcement outside of protected areas is consistently associated with lower deforestation. (Evidence base: Brazil, Indonesia)

Payments for ecosystem services are consistently associated with lower rates of deforestation. While early research found little effect of PES on deforestation rates in Costa Rica, subsequent studies found PES in Costa Rica to have had a positive effect on total forest cover, which includes forest regrowth in addition to deforestation. (Evidence base: Costa Rica, Mexico)

Population shows a strong association with greater deforestation, though endogeneity makes a causal link difficult to infer. Population can increase deforestation by increasing the supply of labor and the local demand for agricultural products, but population growth occurs simultaneously with other rural economic expansion that increases deforestation pressure, and an increase in cleared land can support a greater population. (Evidence base: 26 countries on 5 continents)

Poverty is consistently associated with lower rates of deforestation, but no consistent evidence shows that higher income is sufficient on its own to slow and reverse deforestation without additional deliberate policy interventions. In the absence of careful study design, the changes in deforestation that can be directly attributed to poverty or to changes in income or wealth are difficult to separate from concurrent geographical or temporal trends that also affect deforestation. Increased income from rural support programs is consistently associated with increased rates of deforestation. (Evidence base: 17 countries on 5 continents)

Protected areas is the variable most consistently associated with lower deforestation. Lower deforestation in protected areas is often due to the geographical remoteness of those areas, in addition to their legal status. (Evidence base: 19 countries on 4 continents)

Proximity to cleared land is consistently associated with greater deforestation. This may be a consequence of either increased access and reduced clearing costs or omitted variables that are correlated with a greater likelihood of deforestation. (Evidence base: 19 countries on 5 continents)

Timber variables (timber activity and timber price) are not consistently associated with either higher or lower deforestation. The mixed relationship between timber variables and deforestation suggests that the economic returns that forests provide through timber harvest may be forestalling more rapid conversion of these forests to agriculture, even while logging activity can degrade forests and increase access into remote areas, which can lead to later deforestation. (Evidence base: Bolivia, Brazil, Indonesia, Mexico, Myanmar, Panama, Thailand)

Further Reading