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CHAPTER TWO
2. Drivers of deforestation
2.1.
The view from the farmer’s field: potential land
values affect deforestation and income
Put yourself in the place of a farmer. You have some forest, or use some nearby forest, or
are thinking about claiming some forest. Should you log it?
If so, should you extract as
much as you can right now, or plan for a sustainable pace of harvesting over the coming
decades? Or should you simply clear-cut the forest, and replace it with crops, pasture, or
tree plantations?
Your choices will be shaped by your own constraints and abilities, by the characteristics of
your forest plot, by your rights over it, and by the wider social, economic, and political
context. And your choices will in turn affect your income and your local environment.
Understanding landholders’ behavior is essential if we want to understand how policies and
context affect deforestation and forest poverty.
Attempts to understand the effect of
sweeping policies, such as structural adjustment, on sweeping outcomes, such as aggregate
forest loss in an entire country, are doomed to inconclusiveness. Policy changes typically
pull many different economic and social levers, changing prices and wages, stimulating one
sector, dampening another. Each lever could have a distinctive impact on deforestation and
forest poverty, and those impacts might systematically differ between regions. Jumbled up
to the national level, these impacts might be difficult to disentangle. So our strategy is to try
to understand how each potential lever works.
This chapter, which draws on Angelsen (2006) is based on a simple but powerful model of
the landholder’s deforestation decision at a particular point in space and time3 (Box 5). After
3
A similar exposition is in Hyde (in prep.)
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summarizing the model’s predictions, the chapter then examines how different factors affect
the landholder’s decision and its outcomes – in theory and in practice. It then uses it to
examine how forest cover and poverty might evolve over time for entire regions.
Box 5 von Thünen (1826) said it all (almost)
The most powerful framework for understanding tropical deforestation is not exactly new; it
was published by Johann von Thünen in 1826! In essence, von Thünen’s The Isolated State is
about how land rent – determined by distance from a center – shapes the land uses.
Consider a simple model where land only has two uses: agriculture and forest, e.g., Angelsen
et al. (2001). Agricultural production per hectare (ha) of the homogenous land is given (y),
and the produce sold in a central market at a given price (p). The labour and capital required
per ha are l and k, with inputs prices w (wage) and q (annual costs of capital). Finally,
transport costs per km are denoted v and the distance from the centre d. This defines the
land rent or profit of agriculture: r = py – wl – qk – vd. The rent declines with distance, and
the agricultural frontier is where agricultural expansion is not profitable anymore, i.e., r = 0.
Thus the frontier is at d = (py – wl – qk)/v.
This simple model yields several critical insights on the immediate causes of deforestation.
Higher output prices (p) and technologies that increase yield (y) or reduce input costs (l, k)
make expansion more attractive. Lower costs of capital (q) in the form of better access to
credit and lower interest rates pull in the same direction. Higher wages (w), reflecting the
costs of hiring labour or the best alternative use of family labour, work in the opposite
direction. Reduced access costs (v) - new or better roads - also provide a great stimulus for
deforestation.
Extensions of this model are possible (see Angelsen 2006). However, the key lesson from
the von Thünen model remains the same: farmers or companies deforest because it is the most
profitable alternative and they have the necessary means to do so.
Text taken from Angelsen (2006) background paper.
The following chapter builds on this model.
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2.1.1. Overview of predictions
Effect on Environment
Effect on Welfare
- indicates deforestation
Credit market access; own
assets
-
+ indicates poverty
alleviation or growth
+
Higher prices for extensive
farm output
-
+
Higher prices for intensive
farm output
+ Where labor markets are
imperfect, this could decrease
deforestation by attracting
labor away from the extensive
product
+
- where capital markets are
imperfect, this could increase
deforestation by funding the
costs of forest conversion
Higher prices for timber
-spurs deforestation of old
growth standing timber;
- increases deforestation in
open access areas
+ encourage sustainable
management of secondary
forests where there is secure
tenure
? effect on local poverty
depends on who extracts the
timber and wider economic
effects. Poverty may increase
if outsiders degrade forests on
which locals depend
+ spurs reforestation in forest
poor areas
Higher off farm wages
+ where labor markets are
imperfect, or in-migration is
limited, draws labor away from
deforestation of marginal
areas
+
- could possibly fund
deforestation
More secure land tenure
+ reduces deforestation as a
means of claiming land
+
+ increases attractiveness of
sustainable management of
forest
- increases attractiveness of
investments in land
improvements including
perennial crops
Good soils, moderate
rainfall
-
+
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Effect on Environment
Effect on Welfare
- indicates deforestation
+ indicates poverty
alleviation or growth
+
Lower interest rates
? possibly – if intensive sector
pulls resources from extensive
Higher yielding agricultural
technologies
- if labor and capital can
migrate to the forest margins
+ (though possibility of
indirect negative effects)
+ if marketwide effects reduce
prices
+ if technologies absorb labor
and in-migration is limited
Road extension or
improvement
- by increasing farmgate price
of outputs, reducing price of
inputs, increasing attractiveness to in-migration
+ (unless outsiders displace
locals)
2.1.2. Richer farmers are better able to finance deforestation costs
A poor household can’t afford to clear very much forest. In Bolivia, for instance, clearance
costs range from $350 to $605 per hectare (Merry et al. 2002). Sometimes these costs can be
partly or fully defrayed by sales of timber; sometimes wealthy interests are willing to finance
clearing by smallholders on their behalf. Where these markets are lacking, successful
deforesters need to be able to mobilize a lot of family labor, or have to be able to pay for
hired labor, chainsaws, and bulldozers. Migrants have to be able to finance their subsistence
while waiting for an initial crop.
2.1.3. Good land is cleared first
Soils, topography, and climate strongly affect land rents. Mendelsohn et al. (2001) for
instance have shown that soils and climate explain most variation in county-level land values
in the US, Brazil and India. Chomitz (2005a) looking at rural property values for Bahia,
Brazil, shows that land prices increase with soil quality but decrease with slope, holding
constant other characteristics such as road access. We would expect deforestation to be
more rapid on land that offers higher rents.
There is strong evidence to support this view. A dramatic example is Sumatra where
deforestation has nearly eliminated lowland forest, leaving forest remnants only on slopes
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and in highlands (Whitten et al. 2000; Stolle et al. 2003; MacKinnon et al. 2003). Studies of
deforestation at the farm or local level universally find that deforestation rates are lower on
hillsides, other things constant. (see Appendix Table 2). These studies also find a strong
correlation between soil quality and deforestation.
The pantropical data discussed in
Chapter 1 shows that, in peri-urban areas of Latin America and Asia, tree cover is about
twice as high on the poorest soils, compared to the best soils for rainfed agriculture.
Deforestation also skirts areas with high rainfall. Very high rainfall is inimical to cultivation
of annual crops, and discourages cattle raising, especially when there is no dry spell. A
detailed study of the Brazilian Amazon by Chomitz and Thomas (2003) showed that,
controlling for road access, higher rainfall is associated with lower deforestation, more land
abandonment, and lower grazing densities (see also Figure 8).
High densities of saleable trees can also promote deforestation. Roads built by loggers and
revenue from timber sales can help to finance agricultural clearing. And, if the density is
sufficiently high, extraction can lead to deforestation even in the absence of agriculture. This
is thought to be characteristic of Southeast Asia, where lowland forests have high densities
of valuable dipterocarp trees. For instance, logging is blamed for deforestation in sparsely
populated protected areas of Kalimantan (Curran et al. 2004).
2.1.4. High farmgate prices of crops and beef induce forest conversion and
benefit farmers
Our model views a forest plot through the eyes of a profit-minded developer.
Through
these eyes, some plots appear to be more profitable to deforest. These are plots which – due
to location or prevailing policies – would enjoy high farmgate prices for their produce and
low prices for fertilizer and other inputs. Our simple model predicts that, other things equal,
more favorable prices will spur more rapid deforestation. This is an important prediction,
because many policies can affect farmgate prices: tariffs, taxes, exchange rate policies,
subsidies, road improvements.
To test the prediction, we can look for variation in prices across the landscape within a
country, between countries, or over time, and try to correlate prices with deforestation rates.
This is difficult to do. Within a country, at a single point in time, there may not be much
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price variation. Comparisons between countries, or over time, are problematic because there
are many other confounding influences vary, and because measurements of deforestation
may be inconsistent. So there are only a modest number of relevant studies.
Figure 8 Deforestation in Brazilian Amazonia is strongly shaped by rainfall and
farmgate price of beef
Source : Wertz-Kanounnikoff and Chomitz, in prep
The verdict: most studies strongly support a link between higher agricultural prices and more
rapid or extensive deforestation. The degree of price-sensitivity varies, but tends to increase
with more precisely localized measurements. For instance, Wertz-Kanounnikoff and
Chomitz (in prep.) used remote sensing data to show that deforestation rates in the Brazilian
Amazon were strongly related to the farm gate price of beef after controlling for other
important factors.
They found that there is negligible deforestation in protected and
indigenous areas, and where rainfall is more than 2500 mm/year, and that deforestation is
closely related to road access and to farmgate price. Figure 8 focuses on non-protected
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lands, excluding land reform settlements, and exhibits the strong effect of rainfall and
farmgate price on deforestation rate. Holding constant road accessibility, the deforestation
rate is closely related to farmgate price. For instance, in moderate rainfall areas (2000-2500
mm) near roads, the three year deforestation rate was 8.2% where the beef prices was above
R$600/ton, 4.5% where beef prices are between R$400 and R$800, and 0.9% where beef
prices were below R$400.
In a study of Mexico, Deininger and Minten (1999) looked at the relationship between
deforestation and proximity to depots that purchase maize, the main forest-competing crop,
at a government-set fixed price. Given the bulkiness of maize, greater proximity translates
into lower transport costs and a higher farmgate price. They found that an increase of one
standard deviation in depot density corresponded to a 40% increase in the rate of
deforestation.
Barbier and Cox (2004) examined mangrove deforestation (for shrimp
farming) across Thai provinces and found that higher shrimp prices modestly promote
deforestation (with an elasticity of .16) while higher prices for ammonium phosphate (an
input) more strongly deter it (with an elasticity of -.45). But not all studies find strong
effects; Gbetnkom (2005), for instance, finds negligible effects of price changes in coffee,
cocoa, and food on forest clearance in Cameroon.
When two land uses compete with the forest, the impact of price changes becomes more
complicated. Suppose one use is extensive: long-fallow cultivation of some staple food.
Suppose that the other is much more intensive: it uses much more labor per hectare. Think
of cacao or irrigated rice or coca, versus shifting cultivation of maize or rice or plantains.
Suppose also that labor supply is limited: outsiders can’t easily move in to take advantage of
new opportunities. Then, theory says, an increase in the price of the intensive land use could
absorb labor from the extensive one, at least in the short to medium run.
There is some evidence that this happens. Coxhead and Demeke (2004), in a study of
upland farmers in the Philippines, find strong cross-effects between vegetable and maize
production. An increase in the price of vegetables, the more intensive crop, is predicted to
slightly reduce the total area under cultivation.
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Higher prices for farm products benefit land owners, and lead to increased employment of
labor. So in general, higher prices for outputs and lower prices for inputs will reduce rural
poverty.
There are two important cases where this might not be so. First, some farmers
with tiny plots might be net buyers of food; food price increases will hurt them. Second,
substitution between crops could indirectly hurt the poor. For instance, increases in the
price of beef or soy – which use relatively little labor – could divert land away from more
intensive cultivation.
2.1.5. High timber prices induce people to cut the old growth, tend the new
Do high timber values promote conservation or deforestation? The answer depends on the
state of the forest (von Amsberg 1998). New roads, or new markets, can confer great value
on standing old-growth forests. Individual trees can be worth thousands of dollars. But
mature trees grow slowly, if at all, so they make poor investments.
(The problem is
compounded if forest tenure is insecure, so that a tree left unlogged today may be cut
tomorrow by an interloper.) Studies show that when prices rise or areas open up, loggers
sweep through, extracting the saleable trees (Stone 1998).
And, as we have seen, the
revenues from logging can help to finance forest conversion. So higher timber prices
provoke ‘mining’ of old-growth forests.
After the most valuable stems have been removed, land managers face a choice: continue to
tend the forest, nurturing a slow growing but potentially high-value ‘crop’ of timber? Or,
convert the forest, in part or whole, to something with a more rapid return, including tree
crops or faster-growing exotic tree species? The choice is not a simple dichotomy; many
agroforestry systems retain (or regenerate) some forest trees in combination with planted
trees and crops. But the decision on how much to modify will be driven by a comparison of
the revenue stream from native timber versus that from perennials, annuals, and exotic
timber. In general, the silvicultural treatments necessary for long-term sustained native
timber yield may not be financially attractive when discount rates are high and payoffs are
decades in the future.
However, higher prices for native timber, poor conditions for
cropping, and scarce labor will tend to favor native forest management
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Once all nearby forests have been logged over, timber may begin to get scarce. As timber
prices continue to rise, it becomes attractive to manage secondary forests, or plant new ones.
Younger trees may grow in value faster than the rate of interest: a good investment. If
timber prices are high enough, or if the land is not suitable for other kinds of crops, forest
management can be more attractive than forest conversion.
2.1.6. Roads: the path to rural development and to forest clearance
Provision of road access is, on theoretical and empirical grounds, the single most effective
determinant of deforestation that is under policy control. The theoretical argument is
strong.
It says that road provision increases farmgate prices for outputs and decreases
farmgate prices for inputs, with all the effects we have just reviewed. Property-level studies
of land value for Nepal (Jacoby 2000) and for the Atlantic Forest area of Brazil (Chomitz et
al. 2005a) support this linkage. This means that, in general, improved accessibility to a forest
plot would be expected strongly to increase the pressures to deforest it. The theory does
allow for exceptions. In rural areas where tenure is strong, and immigration is limited, better
road access might attract people to towns, or shift them from extensive production of
subsistence crops, to more intensive production of commercial crops. Deforestation might
then decrease as long as residents were able and willing to exclude in-migrants. It is possible
that road links to nearby towns might boost local wages more than farmgate prices,
attracting farmers away from marginal lands. And, where forests are already exhausted,
better road access could trigger tree planting for poles, firewood, and timber.
However an extensive empirical literature strongly supports the proposition that roads tend
to promote, rather than retard, deforestation.
A great challenge for this literature is
disentangling the ‘chicken and egg’ problem of causality when we see roads and
deforestation occurring together. Did the roads facilitate deforestation, or were the roads
built in response to settlement which would have occurred in the absence of roads? One
approach to resolving this question is through detailed case studies of deforestation. Geist
and Lambin’s metareview of 152 case studies finds that road access was a driver of
deforestation in 93 of these cases (Geist and Lambin 2001); Angelsen and Kaimowitz’s
metareview concurs on the importance of road access (Kaimowitz and Angelsen 1998). The
case studies describe how major new highways opened access to forested areas where
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logging roads facilitated forest conversion by follow-on settlers or where colonists built their
own roads in order to make settlement economically viable (Arima et al. 2005). Another
approach uses spatial econometric analysis to relate the incidence of deforestation to road
proximity. Here the investigator considers each point on the landscape to be under different
pressures for deforestation, depending on road proximity, the suitability of the soil for
cultivation, prevailing land tenure conditions, and so on. These influences are very difficult
to disentangle when data are aggregated to the national or even district level, but show a
great deal of variation as attention zooms in to particular points. Thus, these analyses are
able to control for confounding factors (such as fertile, flat soils) that simultaneously affect
road placement and deforestation. We reviewed 26 such studies. Of these, 23 found a
positive relationship between road proximity or density and deforestation. (See Appendix
Table 2). However, the magnitude of the measured impact varied greatly.
Rural roads are generally thought to improve rural incomes and alleviate poverty, for the
same reasons that our model suggests they promote deforestation: by increasing farmgate
prices, reducing prices paid for urban manufactures, and promoting more intensive demand
for labor.
In addition, rural roads would be expected to facilitate access to nonfarm
employment in towns; many studies find that nonfarm employment is crucial to poverty
alleviation in rural areas. For these reasons, rural road provision is considered to be a
mainstay of rural development strategy.
Considering the importance of rural roads to development strategy, the literature on their
impact is thin. We reviewed 26 studies and two metastudies covering 56 others. They were
virtually unanimous in finding positive impacts, though the magnitude of the impacts varies
greatly. Very few employed rigorous, quasi-experimental evaluations of how roads affect
income and welfare. One of the most rigorous evaluations of rural road impacts compared
Peruvian villages receiving rehabilitated road links with similar ‘control’ villages (Instituto
Cuanto 2005). After five years, male wages (but not female wages) experienced a 20%
relative rise in the road villages.
Poverty dropped about 4% in the villages receiving
motorized roads, and 6.7% in those with non-motorized roads. Two recent studies are of
particular interest because they look at countries with high forest cover. In Papua New
Guinea, a simulation study (Gibson and Rozelle 2003) assessed the impact of reducing to
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three hours the access time of all households who currently require more time to reach a
road. This potentially expensive undertaking would reduce the number of people below the
poverty line by 12%. A simulation by Warr (2005) found that provision of all-season roads
to the 50% of Laotians now lacking them would release about 5% of Laotians from poverty.
Most other studies involve econometric analysis of district or provincial level data,
attempting to control for other potentially confounding factors. Fan and Chan-Kang (2004)
summarize a number of such studies, reporting astounding rates of return of 339%-834% in
China, similar returns in Uganda, and over 10000% in rainfed regions of India. Other
reported returns are much more modest, but still positive (see Appendix Table 1).
The inconsistency of the relationship between rural roads and poverty alleviation may
reflect a variety of factors. First, it may be modulated by other policies and conditions, such
as inequality of land ownership. Second, when immigration is possible, road impacts may
manifest as an increase in workforce rather than an increase in wages (Chomitz et al. 2005b).
Where immigration is not possible, roads may result in significant reductions in the poverty
rate in remote areas – but have little effect on the number of poor, a paradox to which we
will return.
2.1.7. Higher off-farm wages discourage deforestation in marginal areas
Many, though not all, forest dwellers have some opportunity to earn wages.
The
opportunity may be in a neighboring farm or plantation, a nearby market town, or a distant
metropolis. The model tells us that as these opportunities become more lucrative, there is a
lower incentive to use forestlands for subsistence or low-value crops. A 1998 review by
Kaimowitz and Angelsen (1998) found broad support for this proposition.
A dramatic long-run example of this is the abandonment of the hillsides of Puerto Rico. By
1950, almost all of the island’s hillside forests had been converted to coffee plantations or
other agriculture, leaving only 9% of the island under forest. Subsequently, there was
massive outmigration from the hillsides, as people sought better-paying employment in San
Juan and in the US. The result was regeneration of the deforested area: in 1990 the 37% of
the island was again under forest (Rudel et al. 2000; Lamb et al. 2005b).
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Coxhead and Demeke (2004) observed a wage rise of about 50% over a decade for hillside
farmers in the Philippines, as transport and communication improved. According to their
analysis, this increase would by itself reduce land cultivation by about 20%.
However, wage increases may affect deforestation through a number of channels. Barbier
and Cox found that higher wages were associated with higher clearance of mangroves for
shrimp farming. They suggest that this is because shrimp growers, faced with higher wages,
had ways of substituting land for labor (Barbier and Cox 2004). Additionally, wage increases
can lead to increased demand for fuelwood or food, and thus spur additional local
deforestation.
Whatever the effect on deforestation, increases in off-farm wages are unambiguously
important for poverty alleviation. A growing literature documents the potential role of off
farm employment in alleviating rural poverty (Reardon et al. 2001).
2.1.8. Agricultural
technologies:
growth-promoting
with
ambiguous
implications for deforestation
Technological improvements in agriculture are an important avenue for increasing rural
welfare (through increased farm incomes) or consumer welfare (through reduced food
prices). However, the gains from these improvements may be unequally shared. And
depending on whether the technology benefits more or less intensive production, pressures
on the forest can increase or decrease. And depending on the nature of labor and food
markets, pressures can decrease for the long term, or only for the short to medium term.
The basic consideration is this4. To be adopted, a technical innovation generally has to save
a farmer’s time, or increase farm output. But any innovation that increases the profitability
of farming is likely to prompt the expansion of existing farms into forests or attract new
farmers to the forest frontier. And anything that reduces labor requirements could make
forest conversion more attractive by increasing the supply of labor.
4
This discussion draws heavily on Angelsen 2006.
So, in order to
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simultaneously increase farmer welfare and reduce forest pressure, a technological
innovation has to meet one of the following conditions:
o The “Borlaug hypothesis” model (Angelsen 2006) – intensification of food
production outside the forest. This is most easily explained by example. Suppose
that rice can be produced in an upland system that encroaches on forest, or a
lowland irrigated system that doesn’t. Suppose that the demand for rice is inelastic
(easily saturated). Then widespread application of green revolution technologies
boosts supply from irrigated rice fields, drives down the price of rice, and increase
the demand for labor. Decreased rice prices and increased wages reduce pressure on
the forest.
Note that this requires that the productivity boost is sufficiently
widespread - nationally or even globally - to markedly reduce the price of rice.
o Labor supply is limited, either because the new technology is introduced in a remote
area where labor is scarce, or because local residents have secure tenure over large
amounts of land and prefer not to rent or sell to newcomers. In these conditions –
more characteristic of frontier areas than mosaiclands – some kinds of intensive
farming systems could absorb labor away from extensive, more forest-damaging
ones.
o Subsistence farmers are not closely tied into food markets, so that an increase in land
productivity or sustainability translates directly into reduced need for clearing.
Again, this scenario is less likely in the mosaiclands, which tend to be closer to major
markets.
A dramatic example of technological change on an extensive crop is the impact of improved
soybean varieties in Brazil's cerrado (savanna) region. EMBRAPA, the Brazilian agricultural
research agency, bred varieties adapted to the region's soils and short days (it is closer to the
equator than traditional soybean zones) (Warnken 1999). The result was an explosion in the
area cultivated -- at the expense of pasture, savanna, and, more recently, moist forest. Area
cultivated increased from virtually zero in 1970 (Warnken 1999) to 117,000 sq. km. in 2004
(IBGE 2006). Soybean and soy product exports were US$9.8 billion in 2004 (Economist
Intelligence Unit 2005). While soybean cultivation is highly mechanized, requiring few
workers, it may have a significant indirect impact on job generation. In southern Brazil, the
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introduction of soy had earlier displaced existing small farmers, some of whom migrated to
the forest frontier. But in the savanna zone of Brazil and in Bolivia, new soybean varieties
expanded into relatively unpopulated woodlands and forests (Kaimowitz and Smith 2001).
The direct beneficiaries of this growth were the soybean farmers, including large scale and
industrial growers.
Induced growth in services, transport, and processing may have
contributed to the rapid growth of urban centers in the soybelt. These cities accounted for
much of Brazil's net employment growth over 1990-2000. However, this economically
favorable expansion came at the expense of the cerrado, which contains globally significant
biodiversity.
Technological change in intensive crops has ambiguous impacts on deforestation.
It
depends on whether the improved crop absorbs labor from the extensive system, or whether
it frees labor and provides start-up funds for new crops. Ruf (2001) claims that, in Sulawesi,
the introduction of mechanized cultivators and herbicides in lowland rice production
liberated labor for upland deforestation. On the other hand, Holden (2001) found that
expansion of intensive maize cultivation in Zambia reduced expansion of a shifting
cultivation system for maize. And Shively and Pagiola (2004), Shively and Martinez (2001)
and Coxhead and Demeke (2004) describe how expansion of intensified land use systems
can draw labor away from extensive, deforesting land uses.
The key consideration in these technological impacts of intensification is whether farmers
are closely tied in to labor and food markets. If labor supply is limited – for instance, if local
people have secure tenure and are not interested in selling or renting land to immigrants –
then a shift to labor-absorbing, land-intensive, productive land uses could reduce pressure
on the forest.
2.1.9. Tenure: good for the landholder, ambiguous implications for
deforestation
Landholders with more secure tenure are more apt to make physical improvements to the
land, to invest in perennial crops, to plant and maintain forests. They worry less about
defending their property or lives from thieves. They are better able to tap credit markets.
And large landholders with secure tenure feel freer to rent out land to tenants or
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sharecroppers, rather than keeping it idle or under pasture. For all these reasons, tenure
security boosts incomes of rural landowners and workers (Deininger 2003).
Poorly defined tenure is generally bad for people, and bad for the forest. There are many
areas of the world where governments have nominal control of forests, but are too weak, in
practice, to regulate their use. This can lead to a ‘tragedy of the commons’ where forest
resources are degraded.
The relationship between secure tenure and deforestation is more ambiguous. In frontier
areas, deforestation is a common means of establishing a claim to land and securing tenure,
both in practice and in law. This encourages a destructive ‘race for property rights at the
frontier’ (Schneider 1995), where land is prematurely deforested – that is, deforested before
it has any economic rent – in speculation that roads or government will eventually confer
value on it. And in countries with pressure for land reform, largeholders will feel pressured
to deforest in order to demonstrate ‘productive use’ of the land and thereby avoid invasion
or expropriation. This has especially been the case in Brazil. There, uncertainty over land
rights has led to violent fights over forested properties.
Secure tenure, however, doesn’t guarantee that landowners will spare the forest. As we’ve
seen, a landowner is likely first of all to extract and sell large, mature, slow-growing trees.
That done, the landowner will weigh the relative advantages of forest maintenance versus
cropping. With secure tenure, investments in perennial crops such as oil palm may look
more attractive.
2.2.
Private gains from deforestation: sometimes
miniscule, sometimes huge
How big are the private gains to deforestation? Gauging this magnitude is essential if we are
to confront the economic and political costs of encouraging more sustainable management
of forests.
The answer – not surprisingly, but importantly – is that these gains vary
tremendously between places and between technologies, or land use systems. Per hectare
profits from deforestation vary from near zero to thousands of dollars per hectare.
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Two aspects of gains are worth measuring. Profits are the benefit to the landholder, from
sale of timber and agricultural products, after costs of conversion and production, including
labor. For a smallholder dependent on unpaid family labor, this concept of profits can be
interpreted as income above what family members could earn elsewhere. In other words, a
strict measure of profit deducts the opportunity cost of family labor. The resulting measure
of net profits per hectare is a convenient measure of the economic pressure for conversion,
or of the opportunity cost of forest conservation.
But where labor markets are imperfect, workers and policymakers may count labor
absorption to be a benefit. So employment per hectare is another way of assessing the gains
from forest conversion.
It is challenging to document the value of land at the forest margin in the world’s tropics.
There are a few places, mostly in Latin America, where markets give us a direct reading on
the profitability of land at the forest margin. In theory, prices for pasture or prepared fields
should reflect the net present value of future revenue from farming, including expected gains
from future road construction and improvements in tenure security. Elsewhere in the
developing world, where land, labor, and product markets are thin, we have to rely on
estimates of profitability based on farm studies. To compute the profitability of converting
logged-over forest to pasture, however, we would have to deduct from the land price the net
cost of clear-cutting after timber sales, and of planting the pasture; in Bolivia this cost was
estimated at a mean of $267 (Merry et al. 2002). The Alternatives to Slash and Burn (ASB)
Program has undertaken especially rigorous measurements of economic benefits and
environmental impacts of forest conversion in Brazil, Cameroon, and Indonesia. Some of
their results are shown in Table 8.
Table 5 shows a compilation of measures taken from
the literature.
Table 5 Land values in forested areas
STUDY
Kazianga and
Masters (2005)
COUNTRY
Cameroon
DATE
2001
ACTIVITY
Average land cost at
the frontier
VALUE US$/ha
86
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STUDY
Merry et
al.(2002)
COUNTRY
Bolivia
DATE
n.a.
ACTIVITY
Pasture land
Ravindranath
and
Somashekhar
(1995)
Zelek and
Shively (2003)
India
1994
Land rent
Philippines
1994-1996
Net returns /yr:
• Low-input corn
farm
• High-input
vegetable farm
Tomich et al.
(2002)
Sumatra
(Indonesia)
1997
Fearnside
(1995)
Para (Brazil)
1994
Kihiyo (1996)
Norton-Griffiths
and Southey
(1995)
Tanzania
Kenya
1992
n.a.
1989-1993
Ninan and
Sathyapalan
(2005)
Ghats, India
1999-2000
VALUE US$/ha
24-500 depending
on accessibility.
Limited access is
commonly valued
100-300.
16 /yr
• Commercial
logging
• Rubber
agroforestry
• Rubber agrof.
with clonal
planting
• Oil palm
• Upland rice
• cassava
• Extensive
ranching
• Land value
• 260
• 2225
• 13-875
• 30
• 97-1510
•
•
•
•
617
75
131
31 /yr (gross
return)
• 150
Maize farming
Farming in:
1171 (~NPV)
Net returns/yr:
• High potential
zone
• Medium potential
• Per humid
• arable
• 150.7
Ranching in
semiarid zone
Pasture in arid zone
Coffee in farm:
•
•
•
•
<2.5 acres
2.5-5
5-10
>10 acres
• 90.7
• 38.3
• 54.2
5.3
0.6
Net returns:
•
•
•
•
2580
2837
7111
11833
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STUDY
Olschewski and
Benitez (2005)
COUNTRY
Ecuador
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DATE
2001
page 53
ACTIVITY
Cattle ranching:
• North
• Coastal strip
• Closest to Quito
Price for grazing
land:
• North
• Coastal strip
• Closest to Quito
Shone and
Caviglia-Harris
(2005)
Rondonia,
Brazil
PinedoVasquez et
al.(1992)
Amazon, Peru
2001
1988-1989
Chomitz et
al.(2005a)
Ricketts et
al.(2004)
Bahia, Brazil
2000
Costa Rica
1999
Naidoo and
Adamowicz
(2005)
Angelsen
(1995)
Uganda
1993-2001
Sumatra,
Indonesia
1991-1992
Ninan and
Sathyapalan
(2005)
Ghats, India
1999-2000
VALUE US$/ha
Returns net of costs
(except labor):
• 25 /yr
• 42 /yr
• 110 /yr
• 150-500
• 400-1000
• 800-2000
Gross return /yr:
• Annual crops and
coffee
• Cattle and milk
Forest
clearing
(timber selling)
One rotation in
swidden agriculture:
rice, cassava,
plantain, fallow (~7
yr)
Median land value
• Pasture for beef
cattle
• Sugar cane
Farming
• 359.5
• 327
Net revenues:
480
958
400
• 151 /yr (not
specified if net or
gross)
• 825 /yr
Net return /yr:
114
Gross returns /yr:
• Annual crops
(rice, maize,
cassava)
• Rubber
Coffee in farm:
•
•
•
•
<2.5 acres
2.5-5
5-10
>10 acres
• 125
• 170
Net returns:
•
•
•
•
2580
2837
7111
11833
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STUDY
Glomsrod et
al.(1998)
Davies and
Abelson (1996)
Fundacão
Getulio Vargas
COUNTRY
Nicaragua
PRR v2.07.doc
DATE
1992
Bolivia
n.a.
Brazil
n.a.
ACTIVITY
Total income
generated by
farming (Maize,
Beans, Rice)
Mechanized
soybean/maize
Mean prices of
pasture by state,
Dec. 2004
page 54
VALUE US$/ha
Gross return /yr:
150
1500 (NPV)
200 (Pará)
318 (Rondônia)
Notes: n.a. (not available)
Some clear lessons emerge:
•
In some places, there are huge incentives to degrade or convert forest. In Sumatra
or Cameroon, logging followed by conversion to oil palm would yield profits of over
$1200/ha. In Brazil’s cerrado (savanna) region, conversion of native woodlands to
soy yields properties worth over $3000/ha.
•
At the Latin American frontier, forest is being converted to very low-value uses that
generate little employment. Conversion of forest to traditionally-managed pasture
in Amazonia yields pasture worth only a few hundred dollars a hectare. In Table 8,
we see that ASB (Tomich et al. 2005) reckons that a hectare returns profits of only
$2, and provides just 11 days of employment. Table 5 reports that pasture at the
Ecuadorian frontier is worth $150-$500; at the Bolivian frontier, $24-$500.
However, substantially higher values are reported near cities and on well managed
farms using improved production systems.
•
Chomitz et al.(2005a) analyze in detail land values in the Atlantic Forest of Bahia,
considered one of the most important places for biodiversity conservation in the
world. This is a long-settled region; active deforestation over the last few decades
have left only small fragments of remaining forest. The study finds a median land
value of $400; this can be taken as the opportunity cost of devoting existing pasture
to regeneration of forest. The study finds further that remaining forested land sells
at a steep discount to other land of similar characteristics. This may reflect the effect
of laws, even though imperfectly enforced, against deforestation. It may also reflect
relegation of the poorest quality land to forest; after decades of occupation, most
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agriculturally suitable land has already been cleared. Both effects may be present in
other biodiversity hotspots where forests have been heavily fragmented.
•
In Table 5, we see that Naidoo and Adamowicz (2005) calculate mean profits of
$114/ha/year in forest regions of Uganda.
Translating a figure like this into
deforestation incentives requires some knowledge of discount rates and clearing
costs. In a different study, Naidoo and Adamowicz (2006) present evidence
supporting a discount rate of 15% - 25% for Paraguay and argue that discount rates
of this magnitude may be typical of the developing world. As noted earlier, Merry et
al. estimate forest clearing costs at $300-$600/ha. These rough figures suggest that
net revenues of $150/ha/yr correspond to a deforestation incentive of between $0
and $700.
•
Sustainable management of logged-over forest for timber can provide lower returns
and employment than commercial agriculture.
In Sumatra, for instance, Table 8
shows that community forest management employees 0.3 persons per hectare per
year and returns just $5, while oil palm cultivation employs 108 persons/ha/year and
returns $114.
In summary, there is great variation across the pantropical forest margins in strength of
incentives for deforestation. Where conditions are amenable to crops such as soybeans, oil
palm, or cacao, and where old-growth timber is still standing, the deforester is rewarded with
thousands of dollars a hectare. On marginal lands, lands far from markets, or where
agricultural technologies are unavailable, there may be little incentive besides the ability to
eke out a living at the going wage.
2.3.
Forest trajectories: roads, markets, and rights
shape regional outcomes for environment and
income
2.3.1. From urban center to the forest frontier: a stylized view of the
landscape
Astronomers teach us that the further out in space we peer, the further back in time we see.
So too, when we stand at an urban center and look towards the remote forest frontier, we
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see not only a changing spatial pattern of forests on today’s landscape, but also a kind of
history of how that landscape has evolved. Seen from the other direction, conditions near
contemporary towns, or old frontiers, give us some hints about the future prospects of
today’s frontier regions. In this chapter, we build on our understanding of landholders’
behavior, expanding our vision from a single plot to an entire landscape, and from a
snapshot to an evolving pattern.
Let’s first take a stylized journey from the urban center out towards the forest frontier, at a
moment in time. Our guide is von Thünen (see Box 5). Von Thünen’s enduring insight was
that farms or forests closer to town were more valuable, other things (such as soils and
topography) equal. The reason is simple: if the price of rice or wood is determined in the
town’s market, then close-in farmers bear lower costs in getting their products to market.
They make higher profits, so their land is worth more – its rent for agriculture is higher, to
use a standard but confusing term in economics. Rent falls with distance to town – rapidly
for bulky or perishable commodities (vegetables and milk), more slowly for valuable ones
(beef, coffee, hardwood timber). As land values decrease, land uses become more and more
extensive, with pasture displacing crops, and rotating fallows replacing permanent fields. At
some distance, farmers can no longer profitably supply crops to market, and the land has no
agricultural rent. This is the agricultural frontier; beyond, only subsistence farmers and
standing forest will be found. So this highly stylized model predicts concentric rings of
different land uses centered on urban areas. And there is ample evidence that this model,
inspired by German landscapes of the early 19th century, describes landscapes across the
developing world (Chomitz and Thomas 2003; Barnes et al. 2005). How does forestry fit
into this picture? There’s an important distinction between one-time extraction of oldgrowth trees and sustainable management of planted or natural forests. Big valuable, old
trees will tend to get extracted as soon as they are accessible. Smaller, less valuable trees will
often be sold as a byproduct of clearing for agriculture in the inner von Thünen rings. This
is especially true where the central town has an appetite for fuelwood or charcoal. Only
when natural forests are depleted does it become attractive to manage them, or plant new
forests, for sustained harvest over time. When this happens, a von Thünen forest ring can
emerge at the edge of the agricultural ring.
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Of course, real landscapes don’t look like archery targets. Two important elaborations are
necessary to make the model more realistic. First, the effects of distance are strongly
modulated by soil, climate, and topography, as we have seen. Forests may remain on steep
slopes close to cities. Remote areas with excellent soils may attract early colonization. And,
different combinations of accessibility, soil characteristics, and topography may appeal to
different kinds of land uses and users. Chomitz and Gray (1996), for instance, use extremely
detailed land cover, topography, and soils data for Belize to elucidate the determinants of
land use. They find that semi-subsistence shifting cultivators -- who can’t afford fertilizers
and don’t sell much in the market --favor hilly areas with nitrogen-rich soil, and are only
moderately sensitive to distance from town. In contrast, commercial cultivators –who can
afford fertilizers but rely on tractors -- favor flat lands, regardless of soil fertility, and tend to
be closer to markets.
Second, and crucially, security of land tenure is a crucial part of the picture. While the
determinants of land tenure are complex and rooted in history and institutions, they follow
an important geographical pattern. Typically, the more remote a plot of forest from settled
areas, the more difficult it is to establish and defend property rights. This has been especially
true in forest areas. So, elaborating von Thünen’s model, we can imagine that the cost of
defending property rises with distance from the town. This means that if we account for
these costs, net land rent (theoretical profitability less the cost of defending property rights)
falls more rapidly with distance from town: the curve is steeper. At some point, the cost of
defending property rights exceeds the profitability of land.
Beyond, it doesn’t pay to try to
invest in establishing a farm or in actively managing a forest plot. This point, again, is the
frontier. Note, by the way, that the cost of defending a managed forest may typically be
higher than the cost of defending a pasture.
2.3.2. From the forest frontier to urban center: a stylized view of forest
dynamics
Let’s now take a return journey, starting at the frontier. This time, however, we’ll take the
trip in a time machine, looking in a stylized way at the dynamics of change, and the role of
institutions, markets, and geography in shaping the trajectories of poverty, development, and
environment. Some of these trajectories will end up at an urban center; others will not.
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2.3.2.1.Transfrontier forests: abundant land
We begin our journey beyond the agricultural frontier. Contemporary examples include the
great forests of the Western Amazon, the Congo Basin, and New Guinea.
Here, land is
abundant, and property rights are not well defined. Population is very sparse, and the
inhabitants are mostly long-resident indigenous people. They are poor by material standards,
engage in long-fallow shifting cultivation, and cause no net deforestation. Although some of
these forests have been inhabited for millennia, they exhibit very low degrees of
fragmentation and rate high in measures of biodiversity and carbon storage.
Box 6 the Forest Transition
The concept of the forest transition (FT), introduced by Mather (1992) describes a tendency for
forest cover to decrease as colonization, development and population growth proceed, and
then to rebound, a process which has occurred over the past two centuries in Western
Europe, the US and Japan. Rudel et al. (2005) describe two forces behind the turnaround.
The FT can arise because higher wage rates, associated with the opening of more productive
farmlands, induce the abandonment of marginal farmlands to forest regrowth. The second
route is when deforestation makes wood so scarce that it is worth replanting trees. A
number of developing regions appear to be undergoing FT. According to Rudel et al.
(2005), rebounds in forest cover have already been documented in Bangladesh, China, Costa
Rica, Cuba, Dominican Republic, Gambia, Peninsular Malaysia, Morocco, Puerto Rico,
Rwanda, and South Korea. There are indications that India and Vietnam may also be
experiencing FT. Note that it is possible for total forest cover to show a net increase, due to
planting or secondary forest regrowth even while old-growth natural forest is being lost in
another part of the country.
2.3.2.2.Forest frontiers: the race for property rights
Deforestation frontiers face an advancing wave of farmers and loggers – usually from
outside the forested region involved. Currently, frontiers are evident across the tropical
world – around the edges of the Amazon Basin, in the Atlantic forests of Honduras and
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Nicaragua, along the remaining fringes of moist forest in West Africa and Madagascar, in the
Outer Islands of Indonesia. (See Maps 1-5)
Something happens to trigger the arrival of a forest frontier – a change in forest rents.
Gradually, or suddenly, it is worth mining the forest for timber, or worth defending a plot of
land in order to establish a farm or pasture. In terms of the von Thünen diagram, the rent
curves shift upwards or rotate counterclockwise. Areas that had been beyond the frontier
are now under contention. A race for property rights – or a dispute – begins.
There are a number of triggers, some of them linked. Sometimes, as in Madagascar, the
trigger slow is the growth of populations engaged in subsistence-oriented farming. This
results in increased demand for land, and lower effective wages, and can be visualized as a
shift upwards in the rent curve for agriculture.
However, the most important trigger is the construction or substantial improvement of
major roads. These make it possible to exploit previously inaccessible areas for timber and
agricultural products. In the von Thünen diagram, the impact of new roads can be visualized
as a counterclockwise rotation of the rent curves. The cost of transport decreases, and
eventually the reach of property rights is extended, so there is less of a rent penalty
associated with remoteness.
There are several spurs for the construction of major new roads, which may coincide with
other triggers. First, it may be worthwhile to finance roads precisely because they offer
returns in exploitable timber and create land value. Farmers do this on a small scale with
local road construction. Mahogany loggers, seeking lucrative stands of timber, can finance
forest roads hundreds of kilometers long. Miners can open new roads. And state or national
governments may find it worthwhile to open new areas to forest extraction and conversion.
At the national level, purely economic considerations blur with political ones. In Brazil and
Indonesia, road construction in forested areas during the 1960s through 1980s was used as
part of an agenda to promote colonization by landless farmers. Road expansion, though
without organized colonization schemes, was important in the opening of the Peruvian and
Bolivian Amazon during the same period. Forest road construction is sometimes
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geopolitically motivated, aimed at increasing government or military presence in remote and
border areas. Elite interests and corruption also play a role, where the rents created by road
construction are destined for politically well-connected interests Ross (2001).
Finally, technological and market changes can trigger frontier expansion. These changes can
include booming markets for forest competing commodities such as cacao, oil palm, coffee,
and beef. Agronomic technology can also change incentives for deforestation. For instance,
the breeding of soybean varieties adapted to low latitudes facilitated conversion of Brazilian
savanna areas to cultivation.
Figure 9 Different trajectories of deforestation, poverty, and population
Key: poverty-increasing trajectory; poverty-reducing trajectory
2.3.2.3.Trajectories out of the frontier: disappearing or rebounding
forests, immiserization or growth
When the frontier arrives, people begin to jockey for rights to trees and land. Depending on
who obtains possession of those resources, under what circumstances, and how they dispose
of them, different trajectories of forest cover, population, and income are traced out. Figure
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9 shows some stylized trajectories of forest cover, population, and poverty (coded by color)
for a frontier area; they are summarized in the Table 6. We’ll examine them in turn.
Intensification and deforestation
In this trajectory, market or road changes typically lead to increases in the value both of
standing timber and of agricultural land, in an area with favorable soils and climate. There is
a rush to claim timber and property, often leading to conflicts between large and small
actors. Profits from timber sales are used to finance the costs of clear-cutting and
establishing crops.
Agricultural development and timber harvesting may stimulate the
growth of market towns with sawmills, slaughterhouses, and other agriculturally oriented
service and processing businesses. This drives a feedback cycle of growing local population
and demand for land. Land values rise, benefiting landholders; the results may good or bad
for equity depending on whether large or small holders appropriated the land. Labor
demand rises, either on the farm or in processing and servicing centers. This could have
poverty alleviating benefits. Forest cover stabilizes at a low level, with remaining forest
occupying slopes or poor quality land. Agriculturally favorable areas, especially near cities,
would be expected to follow this trajectory. The soybean areas of the Brazilian cerrado
provide an example.
Intensification and reforestation
The dynamics here are similar to those of the previous trajectory. Here, however, forest
depletion leads to serious wood scarcity, and improved tenure makes it possible for
households or communities to manage forests.
Under some conditions, it becomes
profitable to convert fields or pastures to woodlots, or to tend and manage secondary
forests. The result is a mosaic of croplands and managed forests. Examples include India
(Foster and Rosenweig 2003), Kenya (Tiffen and Mortimore 1994) and Tanzania (Monela et
al. 2004)
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Table 6 Trajectories of forest cover and deforestation
Agricultural
rent curve
Managed forest
rent curve
Forest cover
trend
IntDef
Intensification
+
deforestation
Shifts up due to
increasing urban
or international
demand,
improved
tenure
Is everywhere
dominated by
agricultural rent
Deforestation
continues and
stabilizes at
low forest
cover
IntRef
Intensification
+reforestation
Shifts up due to
increasing urban
demand,
increasing
returns,
improved
tenure
Decreases
then rebounds
AbReg
Abandonment
with regrowth
Shifts up due to
increasing urban
demand, then
down due to
rising wages
AbDeg
Abandonment
and
irreversible
degradation
Shifts up, then
down due to
land
degradation
Shifts up due to
increased
demand,
exhaustion of
mined sources,
demand for
environmental
amenities
Shifts up due to
improved tenure,
increased
demand for
wood and for
environmental
services
Never ‘surfaces’
either because of
high costs of
tenure or
because of
physical
irreversibility of
degradation
ImDef
Immiserizing
deforestation
Shifts up due to
reduced wages
and increased
food demand
Shifts down due
to soil
degradation,
increases
disputes over
forest tenure
Poverty and
population
trend
Landowners
prosper, labor
demand
probably
increases,
wages and/or
labor force
increases;
possibly labor
growth is in
towns
Landowners
prosper, labor
demand
increases,
wages and/or
labor force
increases
Decreases
then rebounds
Poverty
decreases due
to outmigration
Decreases
towards zero
Outmigration
without
poverty
alleviation
Decreases
towards zero
Higher but
poorer
population
Location or
identifying
characteristics
Peri-urban,
good soils,
higher-input
agriculture,
higher
population
density
Peri-urban,
medium to good
soils, medium to
higher input
agriculture,
medium to high
population
density
Likely on
marginal lands:
hillsides and/or
semi-remote;
forested; low
population
density
Marginal lands,
not proximate
to cities;
nutrient-poor
soils, slopes, or
high incidence
of fire;
grasslands in
forest biomes
Probably not
proximate to
cities;
anomalously
high population
density given
remoteness and
agroclimate
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Abandonment and regrowth
Here one possible trigger may have been population expansion onto marginal lands.
Following this trigger, rents are low and barely provide a subsistence livelihood for
landholders. So if development elsewhere in the economy leads to higher wages, local
populations migrate out to better opportunities and these areas are abandoned to natural
forest regeneration. This is the most familiar manifestation of the Forest Transition, and
summarizes in shorthand the forest experience of the US, Western Europe and Japan. In
the US, for instance, Vermont was largely cleared for agriculture at the beginning of the
nineteenth century, despite its unfavorable terrain and climate. Vermont fields were then
abandoned as western frontier expansion and improved transport brought new more
productive farmlands into the market. Among modern lower-income areas, Puerto Rico is a
striking and well-documented example, noted earlier.
Other potential reasons for abandonment include a decline in the size of the youth cohort,
or in the price of agricultural commodities. Costa Rica’s strong forest regrowth during the
1990’s may be an example of the latter, if pastures were abandoned in response to declining
beef markets.
Abandonment and degradation
This trajectory is similar to the previous one. Here, however, the land uses of in-migrants
prove unsustainable. Soil fertility collapses due to nutrient exhaustion, compaction, or
invasion by persistent weeds. The rent curve collapses, but natural regrowth does not occur.
Examples include millions of hectares of imperata grasslands of southeast Asia and the large
areas of apparently abandoned pasture lands near Belem, Brazil.
Deforestation and immiserization
Here the trigger could be population expansion or road extension.
A combination of
stagnant technologies and immobile labor continues to push the rent curve out, but is
combined with declining returns to labor and increased poverty. Poor agronomic conditions
and inappropriate land use may further reduce incomes and increase pressure for ‘nutrient
rushes’ from fresh deforestation.
In environmental terms, the outcome is similar to the
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abandonment/degradation scenario. It differs in having a higher population and higher
poverty rates. The humid forest of Madagascar exemplifies this scenario.
2.4.
Summary
Soils, climate, markets, and governance systematically shape pressures for deforestation
across space and time. Change can be driven slowly, as population and income growth
boost demand for food; or abruptly, when new roads, crop varieties, or markets create
pressure to convert forests. Formerly valueless land now becomes more valuable without
forest cover than with it. The resulting forest rent can be relatively low, just barely more
than zero, or quite large: thousands of dollars per hectare. Landholders – newcomers as well
as long-time residents – react rationally to these incentives, deforesting those lands in order
to capture the rents.
Positive feedbacks kick in: for instance, burgeoning populations
demanding food, fuel, and secure land rights.
So do negative feedbacks, such as
deteriorating soil quality. The balance of these forces determines the regional trajectory of
environment, population and poverty.
Different trajectories are possible, and imply different associations between poverty and
deforestation (Sunderlin et al. 2005). A prominent win-lose trajectory has historically been
associated with much successful rural development: the conversion of forest to intensive
agriculture. Here the forest declines but employment and incomes increase. Sometimes
forest cover will rebound as wood becomes scarce, approximating a win-win outcome, but
the renovated forest may not be equivalent in biodiversity or carbon storage to the preexisting forest. Alternatively, forest conversion can result in stagnant agriculture, providing
subsistence income to a poorly-off population who might be even worse off if denied access
to this land. And in the worst, lose-lose case, forest conversion provides only an ephemeral
income.
Overall, this chapter stresses that policies or conditions that make forest land valuable for
agriculture will result in a negative association between deforestation and poverty. More
valuable land tends to result in more rapid deforestation but also higher incomes. The next
chapter will contrast this poverty-deforestation connection with the poverty-forest connection.
This seems at first a trivial distinction but it is not.