Supplementary Material

Is it possible to make rubber extraction ecologically and economically viable in the Amazon? The Southern Acre and Chico Mendes Reserve case study.

Jaramillo C., Soares-Filho B., Carvalho-Ribeiro S., Gonçalves, R.

Index of TablesTable S1. Data sources.....................................................................................................2

Table S2. Fixed and variable costs (US$/kg).....................................................................4

Table S3. Transport costs in US$/kg/km by mode of transport.......................................5

Table S4. Production costs (US$/ha)................................................................................5

Table S5. Costs of Production and formation (rubber plantations)................................6

Table S6. Summary of sensitivity analysis........................................................................6

Index of Figures

Figure S1. Production trend in the nine Production Units of Amoprex during harvest months of 2009................................................................................................................7

Figure S2. Sampling areas in Southern Acre....................................................................7

Figure S3. Spatial point patterns of Hevea spp................................................................9

Figure S4. Selected biophysical variables and their weights of evidence for modeling tree density....................................................................................................................11

Figure S5. Observed density of rubber trees (trees/ha) and simulated Probability Density Function (PDF)..................................................................................................12

Figure S6. Spatial point patterns of productivity classes................................................14

Figure S7. Selected biophysical variables and their weights of evidence for modeling tree productivity............................................................................................................16

Figure S8. Observed productivity of rubber trees (liters/trees) and simulated Probability Density Function (PDF)................................................................................17

Figure S9. Sensitivity analysis of rents...........................................................................18

Figure S10. Rubber production (tons) from different sources.......................................19

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Tables

Table S1. Data sources.Variable Source

1.1. BiophysicalVegetation classes Acre ecological-economic zoning phase II.

Acre Government. Programa Estadual de Zoneamento Ecológico-Econômico do Estado do Acre. Zoneamento ecológico-econômico do Acre fase II: documento Síntese – Escala 1:250.000. Rio Branco: SEMA. 2006a.

Soil classesLand suitability

Geomorphology

Hydrography National Water Agency (ANA). National Information System on Water Resources. Scale 1:250.000. Date 2010; Available at http://hidroweb.ana.gov.br

Municipalities Brazilian Institute of Geography and Statistics Date: 2006. Available at: Instituto Brasileiro de Geografia e Estatística (IBGE) http://www.ibge.gov.br

Land cover

National Institute for Space Research– Monitoring Tropical Forest form Space: the PRODES digital project. Resolution: 60 m Date 2010. Available at: Instituto Nacional de Pesquisas Espaciais (INPE). Projeto PRODES - Sistema de monitoramento da Amazônia por imagem de satélite. http://www.obt.inpe.br/prodes/index.php

Slope and elevationNasa - Shuttle Radar Topography Mission. Resolution: 90 m. Date 2000; Available at: http://www-radar.jpl.nasa.gov/srtm

1.2 BioclimaticAnnual Mean Temperature

Worldclim. Resolution 30 arc-second (~1 Km2). Mean values for the period 1950-2000; http://www.worldclim.org

Mean Diurnal Range Isothermality Temperature Seasonality Max Temperature of Warmest MonthMin Temperature of Coldest MonthTemperature Annual Range Mean Temperature of Wettest QuarterMean Temperature of Driest QuarterMean Temperature of Warmest QuarterMean Temperature of Coldest QuarterAnnual PrecipitationPrecipitation of Wettest MonthPrecipitation of Driest MonthPrecipitation Seasonality (Coefficient of Variation)Precipitation of Wettest QuarterPrecipitation of Driest QuarterPrecipitation of Warmest QuarterPrecipitation of Coldest Quarter1.3 Ecological Occurrence and ecology of Hevea spp Association of Residents of Xapurí (AMOPREX)

9 Productive units “estradas de seringueira” were ecologicaly assessed by Associação de Moradores de Xapuri (AMOPREX) in 2009. This data allowed at establishing morphologic differences amongst Hevea spp, (Real, Vermelha e Branca). For each one of these the production on liters by tree per week for a total period of 6 months as

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well as its geographic location were used in the analysis of productivity

Occurrences and ecology of Hevea spp

Forest Management Plans by TECMAN Technology and Forest Management. Date of data collection 2009-2012, Available at: http://www.tecman.eng.br152 Annual plans (2009 to 2012). From these 329 Annual Working Units were selected totaling of 4,148 ha (Figure 2). Geographic coordinates of each tree as well as the DBH were used for estimating tree density and tree productivity.

1.4 Economic River and roads Instituto Brasileiro de Geografia e Estatística

Collection Points Male condom company NATEX and Central Cooperative of Extractivism of Acre (COOPERACRE)

Costs and Revenues State Department of Agroforestry Extension and Family Production (SEAPROF).2012 data from Inform Economics (2013) and Gonçalves et al., 2013)

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Table S2. Fixed and variable costs (US$/kg) as of 2012 for Pressed Virgin Rubber (PVR), Liquid Latex (LL), Liquid Smoked Sheet (LSS) products under the full cycle (FC) and the partial cycle (PC) scenarios. Extraction from native rubber trees in the presence (PS) and absence (AS) of subsidies.

Activity

Production scenarios

PVR LL LSS

FC PC FC PC FC PC

PS AS PS AS PS AS PS AS PS AS PS AS

Fixed Costs

Cleaning of productive unit and opening panels

0.00 0.05 0.00 0.06 0.00 0.05 0.00 0.06 0.00 0.05 0.00 0.06

Cutting out panels, collecting latex and internal transport

0.00 0.19 0.00 0.26 0.00 0.19 0.00 0.26 0.00 0.19 0.00 0.26

Post-harvest treatment of latex

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.71 0.00 0.82

Storage and sale of product

0.00 0.00 0.00 0.00 0.00 0.48 0.00 0.64 0.00 1.02 0.00 1.36

Variable Costs

Cleaning of productive unit and opening panels

0.21 0.21 0.29 0.29 0.21 0.21 0.29 0.29 0.21 0.21 0.29 0.29

Cutting out panels, collecting latex and internal transport

2.37 2.37 1.38 1.38 2.37 2.37 1.38 1.38 2.37 2.37 1.38 1.38

Post-harvest treatment of latex

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.60 0.60 0.30 0.30

Storage and sale of product

0.00 0.00 0.00 0.00 0.50 0.50 0.31 0.31 0.17 0.17 0.31 0.31

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Table S3. Transport costs in US$/kg/km by mode of transport

Transport mode motorcycle mule boat truckProduct

PVR and LSS 0.016 0.002 0.005 0.011

LL

0.017 0.003 0.005 0.011

Table S4. Production costs (US$/ha) as of 2012 for extracting Pressed Virgin Rubber (PVR) from rubber plantations in southern Acre according to FNP (2013) and Gonçalves (2005).

Year

Subtotals of production cost

Mechanized operation

Manual operation Agricultural Inputs Administration

1 672.11 927.80 2101.85 0.00

2 237.30 281.25 404.40 0.00

3 227.60 202.50 311.90 0.00

4 243.54 213.75 283.90 0.00

5 222.21 172.50 295.90 0.00

6 222.21 172.50 295.90 0.00

7 107.50 855.00 654.85 0.00

8 92.36 960.00 122.35 0.00

9 92.36 960.00 122.35 0.00

10 92.36 960.00 122.35 0.00

11 80.97 1312.50 370.10 0.00

12 55.91 1249.50 126.05 0.00

13 55.91 1249.50 89.80 0.00

14 55.91 1249.50 89.80 0.00

15 55.91 1249.50 89.80 0.00

Year 16 to 30

55.91 1264.50 89.80 0.00

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Table S5. Costs of formation (Cform) and expected yields (Qt) of rubber plantations on deforested land and cost of production of Pressed Virgin Rubber (PVR) Liquid Latex (LL) and Liquid Smoked Sheet (LSS) from plantations (FNP, 2013, Gonçalves et al., 2013).

1CTpdr are calculated for PVR and extrapolated to LL and LSS using the respective ratios of costs of these products from native rubber trees, i.e. 1.35 and 1.40.

Table S6. Summary of sensitivity analysis for rents from Pressed Virgin Rubber (PVR), Liquid Latex (LL), Liquid Smoked Sheet (LSS) under PC and PS scenarios. Parameters evaluated were annual yields (Qxy), selling price (Pn), total production costs (CTprdn), and transportation costs (Ctr).

Level of influence Parameters PVR LL LSS

1 Pn2.95 6.55 5.67

2 CTprdn-2.79 -3.32 -3.43

3 Qxy0.14 3.05 2.12

4 Ctr -0.13 -0.17 -0.11

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Phase Expected yields (kg/ha) Years Cform

(US$/ha) CTprd1 (US$/kg)

PVR LL LSS

Formation 0

1 37022 9233 7424 7415 6916 691

Growth

450 7 3.59 4.85 5.03650 8 1.81 2.44 2.53900 9 1.31 1.76 1.83

1200 10 0.98 1.32 1.371400 11 1.26 1.70 1.76

Stable 1500

12 0.95 1.29 1.3313 0.93 1.25 1.3014 0.93 1.25 1.3015 0.93 1.25 1.30

16-30 0.94 1.27 1.31

Figures

May June July August September October

Figure S1. Production trend in the nine Production Units of Amoprex during harvest months of 2009.

Figure S2. Sampling areas in Southern Acre.

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Figure S3. Spatial point patterns of Hevea spp. K Ripley's function measured in different ranges of distance (in meters) was used to assess randomness of trees. Upper and lower limits (dashed lines) of the envelope of the theoretical function of randomness and the estimated distribution (solid line).

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Figure S4. Selected biophysical variables and their weights of evidence for modeling tree density.

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Figure S5. Observed density of rubber trees (trees/ha) and simulated Probability Density Function (PDF). A) and B) observed PDFs. Simulated PDFs were divided into two groups: Probability ≤ 0.8 was adjusted using a Weibull function (C and D). Probability > 0.8 was adjusted using a Lognormal function (E and F).

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Figure S6. Spatial point patterns of productivity classes of Hevea spp trees in two Production Units from nine PU used for calculating the spatial distribution of tree productivity. Productivity classes from top to bottom in liters/year: Class A, 0 to 1; Class B, 1.1 to 2.6; Class C ≥ 2.6. K Ripley's function measured in different ranges of distance (in meters) was used to assess randomness of tree productivity. Upper and lower limits (dashed lines) of the envelope of the theoretical function of randomness and the estimated distribution (solid line).

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Figure S7. Selected biophysical variables and their weights of evidence for modeling tree productivity.

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Figure S8. Observed productivity of rubber trees (liters/trees) and simulated Probability Density Function (PDF). A) and B) observed PDFs. Simulated PDFs were divided into two groups: Probability ≤ 0.6 was adjusted using a Lognormal function (C and D). Probability > 0.6 was adjusted using a Weibull function (E and F).

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A)

-75% -50% -25% 0% 25% 50% 75%

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Figure S9. Sensitivity analysis of rents from A) Pressed Virgin Rubber (PVR), B) Liquid Latex (LL), and C) Liquid Smoked Sheet (LSS) under PC and PS scenarios. Parameters evaluated were annual yields (Qxy), selling price (Pn), total production costs (CTprdn), and transportation costs (Ctr).

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A)

B)

Figure S10. Rubber production (tons) from different sources: A) Secretary of the State Government of Acre (Seplan), Brazilian Institute of Geography and Statistics (IBGE), Yearbook of Brazilian Agriculture, Agrianual (FNP, 2013). B) Rubber production (tons) for the southeast of Acre according to Seplan.

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