Talk at the preparations for the Special Session of the United Nations General Assembly on the World Drug Problem, Vienna, March 2016

1. The nexus between illicit drug
crop cultivation and deforestation
in Latin America and Asia
Liliana M. Dávalos, Stony Brook University
!
Thank you for inviting me and attending this talk. I’ve been investigating the relationship between forest and illicit crops since the 2000s. At the beginning, data were
scarce, however with the release of many remote sensing products for forest cover, it has become easier to evaluate how one affects the other

2. Colombia
Coca found in areas with more forest cover
First, it’s important to note illicit crops—here is coca in Colombia—are not distributed randomly. In the Andean region, coca concentrates in areas with more forest. This is
important to bear in mind when evaluating deforestation, as deforestation requires there be forest to begin with. In the case of Colombia, these areas are a gradient
between densely populated and more developed Andean and Caribbean towns, and what we call the forest frontier, a region in the process of developing widely since
the mid 20th century. In Bolivia and Peru the forest frontier is almost exclusively Amazonian.

3. Peru & Colombia
Direct deforestation from coca is low
When we zoom into these regions at the interface between denser settlement and much less populated forested areas, we find forest loss. But this loss, although it may
be associated with coca is not directly caused by coca. These are data from Peru and Colombia, and in each case the deforestation rate from coca is several or many
times smaller than the deforestation rate from other, legal crops. These has caused many to argue coca is the ultimate cause, as coca may attract colonists who in turn
clear forest to make room for other uses. If this were correct then we should see higher deforestation rates anywhere where there is coca compared with anywhere where
there is not coca.

4. Andean region
Areas with coca have lower deforestation, but not in
Bolivia
But this is true only for Bolivia. In Bolivia, the prediction turns out to be correct: areas with coca have higher deforestation rates than places without coca—although
statistically these cannot be distinguished. For
Colombia and Peru the areas with coca have lower deforestation rates. In any case, these comparisons of forest loss by itself are hard to interpret. For example, places
with coca in Bolivia might also have rivers or new roads allowing more colonists to get to them, explaining the higher deforestation rates. To actually measure the
contribution of coca to these rates, we need to include some of these spatial factors that we already know affect deforestation rates anywhere in the world.

5. Colombia
No relationship between coca cultivation and
deforestation rates
This requires using statistical models, and including several important factors: how much forest there was at the start, roads, and population. We used data for Colombia,
shown here. If we classify each of the >1000 units into having no coca or having some to a lot, we get this bins at the bottom. If coca cultivation related to deforestation
rates, we would see this upward trend, in which units with more coca experienced higher deforestation rates. We do not find that and, in fact, this kind of analysis has
been carried out by three labs independently, before I completed this study. In each case, no relationship was found. We need similar analyses for Bolivia and Peru.

6. Southeast Asia
Risk of poppy does not increase probability of
deforestation
In fact, such analyses are missing for most of the world. As part of the study, my colleague Jon Flanders and I modeled the relationship between the risk of poppy
cultivation and the probability of deforestation in Laos and Myanmar. As before, we included other variables of importance like roads and population density. If the risk of
poppy cultivation increased deforestation, we would see increasing lines in places with risk. But this is not what we found. Instead, in Laos the effect is more or less non
existent. In Myanmar, the effect if the opposite of what we expected: as the risk increases, the probability of deforestation actually declines.

7. Honduras
Trafficking leads to greater deforestation
There is one case in which illegal drugs have a definitive and negative impact on forests: trafficking. Recent studies have shown a tight correlation between trafficking
activities and deforestation in Honduras. But this doesn’t mean all the deforestation is caused by airstrips. This does happen but, in addition, traffickers grab land
displacing campesinos who then clear out more land. The traffickers also clear out more of their land compared to campesinos and put cattle in it because this helps
launder illegal assets. Similar situations have been described for Colombia and Peru.

8. Colombia
Strongest signal from Amazonia: fumigation directly
related to deforestation rate, same in Chocó
Finally, I wanted to examine the effects of counter drug activities. The most easily measured activity is aerial fumigation with herbicide undertaken in Colombia. As with
coca cultivation, it is important to include other important variables such as roads, population, etc. The relationships vary by region as seen here, and are only statistically
clear for two regions: Amazonia and Choco. In both cases, these relationships are positive: the more fumigation those units have received, the higher the deforestation
rate observed. With that, I want to thank you once more. Thanks!

9. 1400
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0.51.01.52.02.5
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Figure 2
BA
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E FD
H I
Coca -> pastures? Dávalos et al. 2014 Biol Cons
Understanding habitat change
These slides are here in case of questions about disconnect between the Meta-Guaviare study and my results

10. Figure 4
BA
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Aerial Fumigation Previous Year
Growthincocacultivation
Surely there are cows in
those pastures
Dávalos et al. 2014 Biol Cons
Understanding habitat change
These slides are here in case of questions about disconnect between the Meta-Guaviare study and my results

11. A
B
C
Figure 4
Calamar
El Retorno
San Jose
30,000
60,000
90,000
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Year
CattlePriceofbeef(pesos/Kg)RanchingGDP(109
pesos)
2000 2002 2004 2006 2008 2010
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1,800
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2,200
There are cows but
no money
• Relationship
cows:pasture yields
~ 1.08 cow/ha
• This is up to 10X
overestimate
• Beef prices have
barely budged
• Ranching revenues
have plummeted
Understanding habitat change
Dávalos et al. 2014 Biol Cons
These slides are here in case of questions about disconnect between the Meta-Guaviare study and my results

12. Municipality
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Calamar
El Retorno
San Jose
Figure 6
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Percentage population urban
Cocacultivation(ha)
Why did coca
decline?
• Each municipality
started out with
different amounts of
coca
• As the municipalities
become more urban,
there is less coca
• At ~50% urban
population there is 0
coca in the smaller
municipalities Dávalos et al. 2014 Biol Cons
Understanding habitat change
These slides are here in case of questions about disconnect between the Meta-Guaviare study and my results

13. A
B
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Figure 5
Calamar
El Retorno
San Jose
2010
0.00
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2000 2002 2004 2006 2008
Year
FinancialGDP
(109
pesos)
ConstructionGDP
(109
pesos)
PropertyTax
(106
pesos/capita)
What urbanization
looks like
• Urban people
paying more taxes
that finance
construction
• Finance becomes
important
• Less dependence
on ranching (and
agriculture)
Dávalos et al. 2014 Biol Cons
Understanding habitat change
These slides are here in case of questions about disconnect between the Meta-Guaviare study and my results