modeling deforestation risks for the maya biosphere reserve, guatemala wolfgang grunberg school of...

Modeling Deforestation Risks for Modeling Deforestation Risks for

the Maya Biosphere Reserve, the Maya Biosphere Reserve,

GuatemalaGuatemala

Modeling Deforestation Risks for Modeling Deforestation Risks for

the Maya Biosphere Reserve, the Maya Biosphere Reserve,

GuatemalaGuatemalaWolfgang Grunberg

School of Renewable Natural Resource SciencesThe University of Arizona

Tucson, Arizona, 85721, USA

July 14, 2000

AcknowledgementAcknowledgementAcknowledgementAcknowledgementThe author would like to thank the following organizations and

individuals for their indispensable help: ART Group - The University of Arizona CARE Guatemala CONAP - CEMEC CI - ProPeten WCS - Gainesville Perfecto Carillo, Teresita Chinchilla, Gary

Christopherson, Reno Fiedler, Georg Grünberg, D. Phillip Guertin, Vinicio Montero, Howard R. Gimblett, Gustavo Rodriguez Ortiz, Marco Antonio Palacios, Victor Hugo Ramos, Steven Sader, Claudio Saito, Norman Schwartz, William W. Shaw, Carlos Soza, Laura Stewart, and Craig Wissler

OverviewOverviewOverviewOverview The Maya Biosphere Reserve (MBR)

– Landscape, People, & Deforestation Methods & Results

– Data - Types, Sources, and Accuracy– Spatial Analysis

Roads, Settlements, & Soil Results– Deforestation Probability Surface

1986-99 Deforestation Probability Results

– Forecasting Deforestation 1999 Deforestation Forecast Results 2001 Deforestation Scenario Results

Discussion– Deforestation Model– Future Improvements– Conclusions

Guatemala*, Central AmericaGuatemala*, Central AmericaGuatemala*, Central AmericaGuatemala*, Central America

Area: 108,890 km2 Climate:Tropical; hot, humid in lowlands; cooler in highlands Terrain: Mostly mountains with narrow coastal plains and

rolling limestone plateau (Peten) Population: 12,300,000 (2.68 % growth rate) Ethnic Groups:

– 56 % Ladino (Mestizo)– 44 % Mayas and other

indigenous Peoples Literacy: 55.6 % Labor Force:

– Agriculture 58 %– Services 14 %– Manufacturing 14 %– Commerce 7 %– Construction 4 %– Other 3 %

* According to the CIA World Factbook 1999

The MBR and its Buffer Zones (ZAM and ZUM)The MBR and its Buffer Zones (ZAM and ZUM)The MBR and its Buffer Zones (ZAM and ZUM)The MBR and its Buffer Zones (ZAM and ZUM)

Founded 1990 21,130 km2 Reserve and Buffer Zone Hilly Limestone Carst Landscape 100-300 m Elevation 25° C Mean Annual Temperature 1600 mm Yearly Precipitation Average Predominantly Tropical Lowland Forest

The Agricultural FrontierThe Agricultural FrontierThe Agricultural FrontierThe Agricultural Frontier

Slash and BurnSlash and BurnSlash and BurnSlash and Burn

Road ConstructionRoad ConstructionRoad ConstructionRoad Construction

Oil Pipeline and RanchingOil Pipeline and RanchingOil Pipeline and RanchingOil Pipeline and Ranching

The Peoples and their Primary OccupationThe Peoples and their Primary OccupationThe Peoples and their Primary OccupationThe Peoples and their Primary Occupation

Itza Maya - Majority in 1 Settlement– Native Mayan population– Swidden Agriculture (Corn), Agroforestry, Forest Products

Ladino Petenero - Majority in 6 Settlements– Non-Immigrant Population of Hispanic Descent– Wage Labor, Swidden Agriculture, Agroforestry

Highland Mayas - Majority in 25 Settlements– Recent Immigrants from Guatemala’s Central Highlands– Swidden Agriculture

Ladino Sureño - Majority in 134 Settlements– Recent Immigrants of Hispanic and Mayan Descent– Swidden Agriculture and Ranching

Maya House with Corn Maya House with Corn FieldFieldMaya House with Corn Maya House with Corn FieldField

Ladino House along a Ladino House along a RoadRoadLadino House along a Ladino House along a RoadRoad

Methods - Methods - Data Used and Their SourcesData Used and Their SourcesMethods - Methods - Data Used and Their SourcesData Used and Their Sources

1986, 90, 93, 95, 97, and 99 Forest Change Detection Images based on NDVI analysis of 30 m resolution TM Landsat Images:

– Maine Image Analysis Laboratory, University of Maine 1:200,000 Soil Map, reclassified for agricultural suitability:

– CONAP and FAO 194 Settlement locations and associated socio-economic data from

1820 to 1999:

– CARE Guatemala and CEMEC-CONAP Roads and associated attributes:

– CEMEC-CONAP, WCS-Gainesville, and SEGEPLAN Administrative boundaries:

– CEMEC-CONAP and WCS-Gainesville

The Vector and Raster Themes have a Root Mean Square Error of 400 Meter to Each Other

Methods - Methods - Spatial AnalysisSpatial AnalysisMethods - Methods - Spatial AnalysisSpatial Analysis

Settlement Points Analysis:

– 20 concentric 1 km buffers per settlement and analysis year

– Averaged deforestation distance decay curves according to socio-economic categories

Soil Polygons Analysis:

– Reclassification according to agricultural suitability

– % deforestation per soil category and analysis year Road Lines Analysis:

– Only perennial roads were included in the models

– The entire area is assumed to be easily penetrated on foot, with mules, or with 4-wheel-drive vehicles

– Perennial roads, however, are significant for market access and public transportation

Buffering the El Naranjo SettlementBuffering the El Naranjo SettlementBuffering the El Naranjo SettlementBuffering the El Naranjo SettlementFounded 1981; Ladino Sureño Majority; in Transition from Agriculture to Ranching; 3500 Inhabitants in 1996

Perennial RoadPerennial RoadPerennial RoadPerennial Road

Results - Results - Deforestation Distance Decay Deforestation Distance Decay CurvesCurves

According to the Settlements’ Primary According to the Settlements’ Primary Occupation Occupation

Results - Results - Deforestation Distance Decay Deforestation Distance Decay CurvesCurves

According to the Settlements’ Primary According to the Settlements’ Primary Occupation Occupation

Exclusion of Wage Labor Settlements from the Model due to Minimal Deforestation Impact

Average Deforestation of Settlements in 1997 - Primary Occupation

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Distance to Settlement (km)

% A

vera

ge D

efor

esta

tion

Agriculture (85 Samples)Transition from Agriculture to Ranching (52 Samples)Ranching (16 Samples)Forestry etc. (13 Samples)Wage Labor (9 Samples)

Average Deforestation of Settlements in 1997 - Primary Occupation

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Distance to Settlement (km)

% A

vera

ge D

efor

esta

tion

Agriculture (85 Samples)Transition from Agriculture to Ranching (52 Samples)Ranching (16 Samples)Forestry etc. (13 Samples)Wage Labor (9 Samples)

Results - Results - Deforestation and Agricultural Deforestation and Agricultural SoilSoil

SuitabilitySuitability

Results - Results - Deforestation and Agricultural Deforestation and Agricultural SoilSoil

SuitabilitySuitability More Deforestation on Well Draining Soils than on Poorly

Draining Soils

Accumulated Deforestation vs. Soil Quality

0

5

10

15

20

25

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

% D

efor

esta

tion

Well Draining Deep Soils Poorly Draining Deep Soils

Well Draining Shallow Soils Poorly Draining Shallow Soils

Accumulated Deforestation vs. Soil Quality

0

5

10

15

20

25

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

% D

efor

esta

tion

Well Draining Deep Soils Poorly Draining Deep Soils

Well Draining Shallow Soils Poorly Draining Shallow Soils

Methods - Methods - Deforestation Probability Deforestation Probability SurfaceSurfaceMethods - Methods - Deforestation Probability Deforestation Probability SurfaceSurface

Cell by Cell Logistic Regression for Each Analysis Year (1986 to 1999) using 5 % Stratified Random Samples (> 1,100,000 cells):– Dependent Variable: Deforested (1) / Forested (0)– Independent Variables: LN distance to Roads, LN

Distance to Settlements, Well (1) / Poorly (0) Draining Soils

Soil drainswell/poorly

LN roaddistance 1997

LN sitedistance 1997

Deforestation1997

Variables:

-> 10.006 ->

x -1.087 =

x -0.430 =

x 0.955 =

Logisticregression

coefficients:

Independent

Dependent

Weighted Grids:

Deforestationprobability

surface 1997

Corrected y-intercept

logisticallytransformed

Sum ofweighted

grids

Soil drainswell/poorly

LN roaddistance 1997

LN sitedistance 1997

Deforestation1997

Variables:

-> 10.006 ->

x -1.087 =

x -0.430 =

x 0.955 =

Logisticregression

coefficients:

Independent

Dependent

Weighted Grids:

Deforestationprobability

surface 1997

Corrected y-intercept

logisticallytransformed

Sum ofweighted

grids

1986 - 1986 - Deforestation Deforestation

Probability Probability SurfaceSurface



Observed Observed DeforestationDeforestationObserved Observed DeforestationDeforestation

Results Results 19861986





Observed Observed Deforestation &Deforestation &Man Caused Man Caused Wild Fires Wild Fires (Summer 1998)(Summer 1998)

Observed Observed Deforestation &Deforestation &Man Caused Man Caused Wild Fires Wild Fires (Summer 1998)(Summer 1998)


Methods - Methods - Forecasting DeforestationForecasting DeforestationMethods - Methods - Forecasting DeforestationForecasting Deforestation

Forecasting Deforestation for 1999:– Forecasted Deforestation Probability Surface based on:

1997’s probability surface regression coefficients Roads and settlements observed in 1999

– Deforestation Forecast based on: Percent deforestation in 1997’s deforestation probability

zones– Comparing 1999 Observed and Forecasted Deforestation

The 2001 Deforestation Scenario:– Forecasted Deforestation Probability Surface based on:

1999’s probability surface regression coefficients 2001 roads scenario

– Deforestation Forecast based on: Percent deforestation in 1999’s deforestation probability

zones

Results - Results - The Forecasted 1999 The Forecasted 1999 DeforestationDeforestation

Probability SurfaceProbability Surface

Results - Results - The Forecasted 1999 The Forecasted 1999 DeforestationDeforestation

Probability SurfaceProbability Surface The 1999 Forecast is based on the 1997 Regression

Coefficients and in 1999 Observed Roads and Settlements

Results - Results - Forecasting Percent Area Forecasting Percent Area Deforested Deforested Results - Results - Forecasting Percent Area Forecasting Percent Area Deforested Deforested

0

10

20

30

40

50

60

70

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1

Deforestation Probability Zone

% o

f Pro

ba

bili

ty Z

on

e D

efo

rest

ed

1986

1990

1993

1995

1997

1999

0

10

20

30

40

50

60

70

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1


% o

f Pro

ba

bili

ty Z

on

e D

efo

rest

ed

1986

1990

1993

1995

1997

1999

The 1997 and 1999 Observed Probability Zone Deforestation Percentages were used respectively for the 1999 Deforestation Projection and 2001 Scenario

Results - Results - 1999 Deforestation Forecast1999 Deforestation ForecastResults - Results - 1999 Deforestation Forecast1999 Deforestation Forecast

0

50

100

150

200

250

300

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1

Deforestation Probability Zones

De

fore

ste

d A

rea

(km

^2)

1999 PredictedDeforestation

1999 ObservedDeforestation

0

50

100

150

200

250

300

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1

Deforestation Probability Zones

De

fore

ste

d A

rea

(km

^2)

1999 PredictedDeforestation

1999 ObservedDeforestation

1999 Forecasted Deforestation for Each Probability Zone = Area of Forecasted 1999 Deforestation Probability Zone

x % of Zone Deforested in 1997 1999 Observed vs Predicted Deforestation

Results - Results - Testing the 1999 Deforestation Testing the 1999 Deforestation ForecastForecastResults - Results - Testing the 1999 Deforestation Testing the 1999 Deforestation ForecastForecast

Deforestation (km^2)DeforestationProbability

Zone

% deforestedin 1997

Forecasted 1999Probability Surface Area

(km^2)Predicted Observed

Difference(km^2)

%Difference

0 - 0.5 0.39 x 2562.9 = 9.9 7.2 2.7 38.010.05 - 0.1 0.14 x 3463.9 = 4.9 1.7 3.2 186.590.1 - 0.15 0.54 x 1839.8 = 10.0 11.2 -1.2 -10.400.15 - 0.2 1.33 x 1474.7 = 19.7 21.1 -1.4 -6.720.2 - 0.25 2.12 x 1240.7 = 26.3 28.7 -2.3 -8.160.25 - 0.3 2.15 x 1025.7 = 22.1 26.3 -4.2 -16.100.3 - 0.35 2.76 x 882.4 = 24.3 31.9 -7.6 -23.810.35 - 0.4 5.38 x 788.2 = 42.4 45.2 -2.7 -6.030.4 - 0.45 9.05 x 749.8 = 67.8 71.9 -4.1 -5.710.45 - 0.5 11.06 x 693.1 = 76.7 81.6 -4.9 -6.050.5 - 0.55 12.94 x 680.3 = 88.1 96.9 -8.9 -9.160.55 - 0.6 16.01 x 697.7 = 111.7 121.5 -9.8 -8.080.6 - 0.65 18.22 x 698.1 = 127.2 137.8 -10.6 -7.710.65 - 0.7 20.29 x 682.8 = 138.5 146.9 -8.4 -5.710.7 - 0.75 25.40 x 655.6 = 166.5 168.5 -2.0 -1.200.75 - 0.8 30.30 x 620.3 = 187.9 181.1 6.8 3.770.8 - 0.85 35.09 x 596.1 = 209.2 201.0 8.2 4.060.85 - 0.9 40.52 x 559.3 = 226.6 214.3 12.3 5.760.9 - 0.95 50.10 x 497.0 = 249.0 235.2 13.8 5.880.95 - 1 66.37 x 333.6 = 221.4 206.0 15.5 7.51

2030.4 2036.1 9.9 0.49

Deforestation (km^2)DeforestationProbability

Zone

% deforestedin 1997

Forecasted 1999Probability Surface Area

(km^2)Predicted Observed

Difference(km^2)

%Difference

0 - 0.5 0.39 x 2562.9 = 9.9 7.2 2.7 38.010.05 - 0.1 0.14 x 3463.9 = 4.9 1.7 3.2 186.590.1 - 0.15 0.54 x 1839.8 = 10.0 11.2 -1.2 -10.400.15 - 0.2 1.33 x 1474.7 = 19.7 21.1 -1.4 -6.720.2 - 0.25 2.12 x 1240.7 = 26.3 28.7 -2.3 -8.160.25 - 0.3 2.15 x 1025.7 = 22.1 26.3 -4.2 -16.100.3 - 0.35 2.76 x 882.4 = 24.3 31.9 -7.6 -23.810.35 - 0.4 5.38 x 788.2 = 42.4 45.2 -2.7 -6.030.4 - 0.45 9.05 x 749.8 = 67.8 71.9 -4.1 -5.710.45 - 0.5 11.06 x 693.1 = 76.7 81.6 -4.9 -6.050.5 - 0.55 12.94 x 680.3 = 88.1 96.9 -8.9 -9.160.55 - 0.6 16.01 x 697.7 = 111.7 121.5 -9.8 -8.080.6 - 0.65 18.22 x 698.1 = 127.2 137.8 -10.6 -7.710.65 - 0.7 20.29 x 682.8 = 138.5 146.9 -8.4 -5.710.7 - 0.75 25.40 x 655.6 = 166.5 168.5 -2.0 -1.200.75 - 0.8 30.30 x 620.3 = 187.9 181.1 6.8 3.770.8 - 0.85 35.09 x 596.1 = 209.2 201.0 8.2 4.060.85 - 0.9 40.52 x 559.3 = 226.6 214.3 12.3 5.760.9 - 0.95 50.10 x 497.0 = 249.0 235.2 13.8 5.880.95 - 1 66.37 x 333.6 = 221.4 206.0 15.5 7.51

2030.4 2036.1 9.9 0.49

Difference between 1999 Predicted and Observed Deforestation

Results - Results - The Forecasted 2001 The Forecasted 2001 Deforestation Deforestation

Probability SurfaceProbability Surface

Results - Results - The Forecasted 2001 The Forecasted 2001 Deforestation Deforestation

Probability SurfaceProbability Surface The 2001 Forecast is based on the 1999 Regression

Coefficients and a 2001 Roads Scenario

Results - Results - The 2001 ScenarioThe 2001 ScenarioResults - Results - The 2001 ScenarioThe 2001 Scenario

0

50

100

150

200

250

300

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1


De

fore

ste

d A

rea

(km

^2)

1986

1990

1993

1995

1997

1999

2001

0

50

100

150

200

250

300

0 -

0.5

0.05

- 0

.1

0.1

- 0.

15

0.15

- 0

.2

0.2

- 0.

25

0.25

- 0

.3

0.3

- 0.

35

0.35

- 0

.4

0.4

- 0.

45

0.45

- 0

.5

0.5

- 0.

55

0.55

- 0

.6

0.6

- 0.

65

0.65

- 0

.7

0.7

- 0.

75

0.75

- 0

.8

0.8

- 0.

85

0.85

- 0

.9

0.9

- 0.

95

0.95

- 1


De

fore

ste

d A

rea

(km

^2)

1986

1990

1993

1995

1997

1999

2001

2001 Predicted Deforestation vs Observed Deforestation

Results - Results - The 2001 Scenario ContinuedThe 2001 Scenario ContinuedResults - Results - The 2001 Scenario ContinuedThe 2001 Scenario Continued

The 2001 Scenario forecasts an increase in deforestation since of 14.5 % (295 km2) since 1999

Deforestation (km^2)DeforestationProbability Zone 1999 2001

Difference(km^2)

% Difference

0 - 0.5 7.2 4.0 -3.2 -44.100.05 - 0.1 1.7 1.8 0.1 3.920.1 - 0.15 11.2 13.2 2.1 18.430.15 - 0.2 21.1 23.4 2.4 11.160.2 - 0.25 28.7 29.9 1.3 4.400.25 - 0.3 26.3 28.3 1.9 7.340.3 - 0.35 31.9 34.8 2.8 8.890.35 - 0.4 45.2 49.5 4.3 9.520.4 - 0.45 71.9 77.3 5.4 7.450.45 - 0.5 81.6 87.1 5.5 6.770.5 - 0.55 96.9 101.3 4.4 4.520.55 - 0.6 121.5 126.1 4.6 3.810.6 - 0.65 137.8 145.4 7.6 5.530.65 - 0.7 146.9 159.8 12.9 8.780.7 - 0.75 168.5 191.1 22.5 13.370.75 - 0.8 181.1 218.9 37.8 20.900.8 - 0.85 201.0 244.0 43.0 21.390.85 - 0.9 214.3 259.0 44.7 20.870.9 - 0.95 235.2 285.1 49.9 21.230.95 - 1 206.0 251.1 45.2 21.93

2036.1 2331.4 295.3 14.50

Deforestation (km^2)DeforestationProbability Zone 1999 2001

Difference(km^2)

% Difference

0 - 0.5 7.2 4.0 -3.2 -44.100.05 - 0.1 1.7 1.8 0.1 3.920.1 - 0.15 11.2 13.2 2.1 18.430.15 - 0.2 21.1 23.4 2.4 11.160.2 - 0.25 28.7 29.9 1.3 4.400.25 - 0.3 26.3 28.3 1.9 7.340.3 - 0.35 31.9 34.8 2.8 8.890.35 - 0.4 45.2 49.5 4.3 9.520.4 - 0.45 71.9 77.3 5.4 7.450.45 - 0.5 81.6 87.1 5.5 6.770.5 - 0.55 96.9 101.3 4.4 4.520.55 - 0.6 121.5 126.1 4.6 3.810.6 - 0.65 137.8 145.4 7.6 5.530.65 - 0.7 146.9 159.8 12.9 8.780.7 - 0.75 168.5 191.1 22.5 13.370.75 - 0.8 181.1 218.9 37.8 20.900.8 - 0.85 201.0 244.0 43.0 21.390.85 - 0.9 214.3 259.0 44.7 20.870.9 - 0.95 235.2 285.1 49.9 21.230.95 - 1 206.0 251.1 45.2 21.93

2036.1 2331.4 295.3 14.50

Discussion - Discussion - The ModelsThe ModelsDiscussion - Discussion - The ModelsThe Models

Pros:

– Can be used to estimate impacts of new roads and settlements in scenarios

– Simple model with relatively good results– Uses common spatial features such as roads, settlement

points, and simple soil maps Cons:

– Does not account for spatial and temporal autocorrelation– Does not account for road and settlement age– Does not predict deforestation location– Forecasting beyond 2 years is questionable due to changing

deforestation trends

Discussion - Discussion - Room for ImprovementsRoom for ImprovementsDiscussion - Discussion - Room for ImprovementsRoom for Improvements

Age of Road and Settlement Factor needs to be included

Spatial and temporal autocorrelation need to be addressed Differentiate settlement deforestation impacts according to their

socio-economic qualities River traffic and oil-pipelines need to be considered as access

ways

Water availability for ranching and agriculture could be included Slope and aspect data of adequate resolution in combination

with better soil maps may turn this regional model into a more localized version

Discussion - Discussion - Mostly Obvious Mostly Obvious ConclusionsConclusions

and Suggestionsand Suggestions

Discussion - Discussion - Mostly Obvious Mostly Obvious ConclusionsConclusions

and Suggestionsand Suggestions Clear relationship between the presence of roads and

settlements & deforestation Simplicity of model is advantageous for forecasting

deforestation in agricultural frontiers on a regional scale Suggestions for reducing deforestation risks:

– Control access to roads– Avoid building perennial roads or upgrading existing

intermittent roads to a perennial status– Pipelines and rivers need to be considered as possible

access routes– Avoid any new settlements in low deforestation risk areas– Consider supporting a forestry or wage-labor based

economy– In an agricultural frontier, regional deforestation trends are

not only controlled by access but also by soil quality

Thank You for Thank You for Your ParticipationYour Participation

Contact Information:Wolfgang Grunberg

School of Renewable Natural Resources, The University of Arizona, Tucson, AZ 85721, USA

Phone: 1 (520) 621 3045e-mail: [email protected]

modeling deforestation risks for the maya biosphere reserve, guatemala wolfgang grunberg school of...

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