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Published on February 5, 2014

Author: GWDGroup

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Independent assessment for GW Group Eucalyptus plantation Growth projection Version 4 - May 24, 2010

Table of Contents Rationale, pg. 3 Site conditions, pg.4 Soils, pg. 4 Agro-ecological Zoning, pg. 4 Trees per Hectare, pg. 6 Climatic data, pg.6 Growth projection notes - Conclusions, pg. 9 Conversion Factor - Wood volume to charcoal MDC, pg. 13 Growth projections based on Barreiras Meteo Station data, pg.12 References - Resources, pg.19 Software resources, pg. 20 Acknowledgments, pg. 20

Rationale This document is an independent assessment developed for GW Group, describing the results of a software growth model for the production of Eucalyptus wood volume and charcoal for the plantation sites located in the Municipalities of Baianopolis, Cristopolis and Catolandia, Bahia, Brazil. Specific data for the sites was provided by GW Group and also collected from international and national data sources as described in this document and in the References. Results are given based on data provided by GW Group, assumptions and conditions as mentioned in this document. Scenarios 1 and 2 describe 2 hypothetical model projections per hectare of Eucalyptus plantations, based on resource availability and management practices. Please note that this document describes customized modeled results which, depending also on model parametrization, can under or overestimate the actual site conditions and future plantation productivity. This is a theoretical assessment of Eucalyptus growth, based on scientific methodology and data available, and can present variations of the actual future Eucalyptus plantation growth . While the utmost care has been taken to ensure the validity of the results, the author can not be held responsible for variations between the current projections and actual future Eucalyptus plantation growth, due to managerial, anthropogenic, or other reasons. 3

Site conditions Soils According to the soil maps reviewed (Ref: Embrapa Solos & IBGE), the soils at the areas of north Baianopolis Municipality, south west Cristopolis Municipality and west Catolandia Municipality - were the sites are located - have medium/prominent clay texture and belong at the class of “LVd4: Latosolo Vermelho Amarelo Distrofico”. Soil fertility in literature (ZANE) as also presented on relevant maps is considered low, but suitable for agroforestry use. The sites soil fertility for the projection modelling is classified as in similar Eucalypt plantantion sites in Minas Gerais with the same soil class (Latosolo Vermelho Amarelo Distrofico) [Filho et al. 2006; Couto et al. 2004]. The 1:100.000 soil maps of IBGE (See References) were the highest resolution source of information, and thus these were used for the site projections. Agro-ecological Zoning The Zoneamento Agroecologico de Nordestre (ZANE), reports that the Municipalities of interest are classified as “Chapadas Altas” suitable also for agroforestry land use (agroflorestas). Chapadas altas are reported having an alitutde of more than 800 m above sea level, while from local analysis the areas are at somewhat lower location, 750 meters approximately. The sites have a dry period during which a precipitation deficit occurs. The climate is considered semi-humid with a dry period from April to October. The Growing Season Length for the area of Barreiras is approximately 200 days, starting on the beginings of October and ending at the first days of May. Precipitation deficit during the dry period is the limiting factor for plant growth based on the Miami Model Climatic Net Primary Productivity [Lieth, 1972] simulated for these sites. This is something already taken into management consideration, since, as mentioned before (Data Provided by GW Group) the plantantion sites are irrigated. 4

Trees per Hectare Their number is defined as in data provided by GW Group, 1333 per hectare. Climatic data The mean monthly data used for the area as input to projections is provided as temeperature/rainfall graphs in this report. Several climatic data sources were reviewed and examined, either from Brazil (CPTEC/INPE, SUDENE, INMET), international (FAOCLIM,GHCN), and several web weather forecast resources (Ref. ClimateCharts). Mean monthly data (temperature and precipitation) and literature data (radiation and evapotranspiration) for the City of Barreiras, BA (12.09, -45.00) were used for the growth projections, and also interpolated mean climatic data for points close to the plantation site locations. From literature sources, such as the Zoneamento Agroecologico de Nordestre (ZANE) , the Cristopolis area receives a mean precipitation of 1067 mm. The closest meteorological station (~20km) to Cristopolis and Baianopolis, Mariquita, receives a mean annual precipitation sum of 970 mm approximately. Again in comparison with literature sources, the meteorological station of Barreiras, although in larger kilometric distance (~45km) and lower altitude than the two sites (450m above sea level, in comparison to approximate of 750m for the site locations) presents more precipitation annual amount similarity with Cristopolis as found on literature (ZANE) – than the closer in distance Mariquita meteo station. Recorded (measured) data from meteorological stations is usually preferred in scientific assessments over estimated/modeled data. For the development of this document, both recorded and estimated data was used, as an input to the growth model. - The (measured) recorded meteorological data of Barreiras city was used in separate calculations, applying again the same growth-management scenarios. - Since measured meteorological station data for the specific areas of plantations were not available according to the review made for this assessment, several meteorological data 6

interpolations methods were tested, and the Thin Plate Spline interpolation method was selected for providing the best predictions of the literature (ex. ZANE) precipitation data. Assessment results vary depending on the climatic data used in the simulations, but since the climatic data variation is low between the stations (Barreiras) and the interpolated points the MAI results are very slightly influenced (See Growth Projections Chapter). That said, the projection tables and graphs developed based on Barreiras climatic data can be considered representative of all others. Growth projection notes - Conclusions The objective of this assessment was to customize theoretical projections as much as possible to local conditions. The results rely also on data, parameters and methodological growth projections from the neighboring region of Minas Gerais (methods which are also widely applied and to other regions of Brazil) for several the Eucalyptus species such as E. camaldulensis x E. urophylla (which is the clonal variety of interest to GW Group ), E. urophylla and others. The widely applied 3-PG Model software [Landsberg et al, 1997], as also specifically referenced in the References and Acknowledgments Chapters, was used for the growth projection analysis, since it is deployed in numerous scientific and commercial projects for Eucalyptus plantations in Brazil, and globally for other species and biomes. The local parametrization of the modelfor the climate and soil variables used are outlined below and in the other relevant chapters of this report. Since, as reported by GW Group, detailed local data on plantation growth is not always available for Bahia for the specific Eucalyptus species, the projections were locally adjusted based also on parameters of sites in Minas Gerais with similar climatic, soil and clonal Eucalyptus plantation characteristics [Embrapa Solos, 1973; IBGE; Filho et al. 2006; Couto et al. 2004]. The soil at these sites is also a Latosolo Vermelho Amarelo Distrofico [Filho et al. 2006; Couto et al. 2004] and with mean min/max temperature of 17 to 29 Degrees Celsius, but with higher precipitation annual sum. These growth projections were customized for the plantation sites in Bahia using local and interpolated climatic data. Soil fertility and available soil water were also adjusted according to the site and soil characteristics, based on literature parametrization for the similar ecological conditions reported above. After adapting parameters, several simulations were run with the 3-PG model, and 2 representative scenarios are described and tabulated results are provided: - The first scenario (Scenario No1) assumes site treatments to bring soil fertility to the medium level (0.5) which is gradually decreasing after the third year (0.4), reaching a lower level (0.3) at year 5 and afterwards, to simulate nutrient loss. Available soil water -calibrated as in literature for similar soil types in the area- is assumed to be at its highest level at the time of planting. - The second scenario (Scenario No 2) represents a different management regime and soil fertility class, assuming that additional actions are taken to further increase site characteristics and available water to plants. Irrigation is assumed to be 8ml/Ha/year for the first 6 years. Site fertility rating for the 3-PG model is assumed to be at a higher level (0.8) for the first 5 years, slightly reducing to a lower level (0.7) for the next 2 years, and gradually reducing (0.3) after year 7. This is a rather optimal theoretical growth scenario. The rotation used in many commercial plantations and experiments in Brazil is between year 6 and 9 for biomass production in agroforestry systems, and also in scientific reports for plantations for energy biomass production the 7nth year is the recommended one for harvest in certain cases. Model simulations present similar results such as the graph intersection of Mean Annual Increment (MAI) and Periodic Annual Increment (PAI). Mean and Periodic Annual Increment (MAI and PAI) in this case are, the mean annual volume growth per stand hectare, and the periodic (annual) change on volume per plantation hectare, respectively. As mentioned before, assuming a certain site quality scenario, but substituting the Barreiras meteo data with the point interpolated climatic one, has no significant difference to growth projections. However, this simulation was made to further customize the projections and examine any hypothetical variability of such influence. 9

The tabulated results, using the Barreiras meteorological mean monthly data, for each of the two scenarios, no1 & no2. However, significant differences are obtained when simulating different site fertility and management scenarios (Scenario no1 or no2). The first scenario, is based on assumptions discussed above and its results are similar with studies made for neighboring regions in Brazil [Filho et al. 2006; Couto et al. 2004], where fertilization and nitrogen fixing crops are part of the agroforestry system management practices. Significant variation is observed between the response of the growth projections to the 2nd management scenario discussed, with simulated growth to increase substantially given that field conditions and applications (ex. nitrogen fixing plants, fertilization, irrigation, clonal species characteristics, silviculture) can decrease significantly growth limitations to plantation trees. Local management practices and site conditions, such as increased irrigation, mixed cultivation of 10

The graphs based on the tabulated results or the previous page, using the Barreiras meteorological mean monthly data, for each of the two scenarios, no1 & no2. These results are the representative of the projection runs made for the Eucalyptus plantation sites. 11

nitrogen fixing plants and/or higher levels of fertilizer input and selected clonal Eucalyptus varieties (similar to Scenario No2), up to a level where tree growth limiting factors are significantly reduced, can increase the volume production. Yields higher than 40 cubic meters per ha per year are widely reported in Brazil Eucalyptus plantation literature [BEPP and citations within; Rossi et al, 2003]. On a recent published scientific study in Bahia, Brazil, an Eucalyptus plantation was established on “Typic Hapludox” soils, and treated for increased fertility and irrigated experimental plot reached an MAI of 90 m3/ha/year, “which is one of the highest ever reported on forests”, not just in Eucalyptus plantations [Reference: Stape et al, 2007]. Conversion Factor - Wood volume to charcoal MDC The conversion factor of solid wood volume to charcoal which was used for the projection results is defined by literature of Brazilian eucalyptus forestry, and is provided below: Solid wood cubic meter/MDC of charcoal = 2,2 Please note that this conversion factor applies not to stacked wood volume, but to solid wood volume dry wood- (Stacked wood volume to MDC has a conversion factor of 1,47. This conversion factor (2.2) above is for solid wood volume, and the mean annual increment is used to calculate charcoal MDC). The MDC factors and calculations derived from literature [Álvaro Nogueira de Souza,2007] were developed in Brazil for Eucalyptus species, and in the referenced article the clonal variety in question for this assessment, Eucalyptus urophylla x Eucalyptus camaldulensis is mentioned. In the pages of the “Growth Projection results” paragraph one can observe that the Periodic Annual Increment (solid wood volume) is divided by the MDC factor of 2.2 to calculate Charcoal MDC. The cumulative increment of charcoal MDC provides the amount of charcoal produced until that period, for example “Year 7 of Cumulative Charcoal MDC” provides the amount of charcoal potentially produced until that date. 13

The tabulated results of simulation runs made with interpolated mean climatic data for the three locations in Baianopolis, Cristopolis and Catolandia, for the Scenario 1. These interpollated point mean monthly data has no significant difference with the Barreiras meteorological attributes, so it does not influence projection results significantly. However, there is a significant diffrence between scenarios, as it can be observed in the next page. 14

The tabulated results of simulation runs made with interpolated mean climatic data for the three locations in Baianopolis, Cristopolis and Catolandia, for the Scenario 2. Please note the differences with the Scenario 1 pesented at the previous page. 15

References - Resources Several literature, web and other resources were reviewed for this assessment, which are mentioned in detail below: - Avery, T.E., B.E. Harold, 2002. Forest Measurements, fifth edition, New York; McGrow-Hill 426 p. - J.J. Landsberg, R.H. Waring, A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning, Forest Ecology and Management, Volume 95, Issue 3, 1 August 1997, Pages 209-228, ISSN 0378-1127 - R.H. Waring, N.C. Coops, J.J. Landsberg, Improving predictions of forest growth using the 3-PGS model with observations made by remote sensing, Forest Ecology and Management, Volume 259, Issue 9, Productivity in Tropical Plantations, 15 April 2010, Pages 1722-1729, ISSN 0378-1127 - J. J. Landsberg, R. H. Waring, N. C. Coops, Performance of the forest productivity model 3PG applied to a wide range of forest types, Forest Ecology and Management, Volume 172, Issues 2-3, 20 January 2003, Pages 199-214, ISSN 0378-1127 - N. C. Coops, R. H. Waring, J. J. Landsberg, Assessing forest productivity in Australia and New Zealand using a physiologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity, Forest Ecology and Management, Volume 104, Issues 1-3, 12 May 1998, Pages 113-127, ISSN 0378-1127 - P. J. Sands, J. J. Landsberg, Parameterisation of 3-PG for plantation grown Eucalyptus globulus, Forest Ecology and Management, Volume 163, Issues 1-3, 28 June 2002, Pages 273-292, ISSN 0378-1127 - ALMEIDA, A.C.; LANDSBERG, J.J.; SANDS, P.J. Parameterisation of 3-PG model for fastgrowing Eucalyptus grandis plantations. Forest Ecology and Management, v.193, p.179-195. 2004. - SILVA, G.G.C. Nutrição, crescimento e sua modelagem em povoamentos de eucalipto em resposta à disponibilidade de água e nutrientes. Viçosa, MG: UFV, 2006. 102f. Tese (Doutorado em Solos e Nutrição de Plantas) – Universidade Federal de Viçosa, Viçosa. - SANDS, P.J. 3PGpjs - A User – Friendly interface to 3-PG, the landsberg and waring model of forest productivity. Cooperative research centre for sustainable production forestry and CSIRO forestry and forestry products. Technical Report n. 29, Edition 2.3, february, 2003. - Silva, Welliam Chaves Monteiro da, 1973- Modelagem dos balanços de radiação e de água e simulação do crescimento do eucalipto na Bacia do Rio Doce-MG / Welliam Chaves Monteiro da Silva. – Viçosa, MG , 2007. Tese (doutorado) - Universidade Federal de Viçosa - BEPP Brazilian Eucalyptus Productivity Model online resources at http://lamar.colostate.edu/~mryan/Research/BEPP.htm, and also http://lamar.colostate.edu/~binkley/Brazileucalyptus.htm and http://www.ipef.br/bepp/. Websites and citations within. - FAOCLIM 2: World-wide Agroclimatic Database, Version 2.01. January 2001. Environment and Natural Resources Working Paper Number 5. Available on CD-ROM from the Agrometeorology Group, Environment and Natural Resources Service (SDRN), Sustainable Development Department (SD), Food and Agriculture Organization of the United Nations (FAO), Rome, Italy. FAOCLIM 2 CD-ROM is described at [http://www.fao.org/sd/2001/EN1102_en.htm]. - CLIMPAG: Climate Impact on Agriculture, Environment, CLimate Chaneg and Bioenergy Divistion 18

(NRC), Food and Agriculture Organization of the United Nations http://www.fao.org/nr/climpag/ - Lieth, H., 1972. "Modelling the primary productivity of the earth. Nature and resources", UNESCO, VIII, 2:5-10. - "POTENTIAL FOREST SPECIES FOR PLANTATIONS IN BRAZILIAN AMAZONIA" Luiz Marcelo Brum Rossi , Celso Paulo de Azevedo, Cintia Rodrigues de Souza and Roberval M. B. de Lima. FAO. Publication year:2003 Issue number: 0537-B1 - Renabio - Rede Nacional de Biomassa para Energia, Rua Professor Alberto Pacheco, 125 – sala 506 – Bairro de Ramos – 36570-000 Viçosa – MG http://www.renabio.org.br/index.php - "AVALIAÇÃO DE DENSIDADES DE PLANTIO E ROTAÇÃO DE PLANTAÇÕES DE RÁPIDO CRESCIMENTO PARA PRODUÇÃO DE BIOMASSA" Documento Técnico RENABIO, n. 2, 2006 Autores: Marcelo Dias Müller e Laércio Couto - "FIXAÇÃO DE CARBONO E PRODUÇÃO DE BIOMASSA EM UM SISTEMA AGROFLORESTAL COM EUCALIPTO NA REGIÃO DO CERRADO DE MINAS GERAIS" Documento Técnico RENABIO, n. 1, 2006. Autores: Antonio de Arruda Tsukamoto Filho*, Laércio Couto, Júlio César Lima Neves, Carlos Alberto Moraes Passos, Carlos Antonio Álvares Soares Ribeiro, Márcio Lopes da Silva e Marcelo Dias Müller ISSN: 1809-7561; available online (* Trabalho de Tese apresentado à Universidade Federal de Viçosa, como parte das exigências do Programa de Pós-Graduação em Ciência Florestal, para obtenção do título de Doctor Scientiae) - Stape, Jose Luiz; Ryan, Michael G.; Binkley, Dan "Testing the utility of the 3-PG model for growth of Eucalyptus grandis x urophylla with natural and manipulated supplies of water and nutrients" 2004, Forest Ecology and Management. 193: 219 - Stape, Jose Luiz; Binkley, Dan; Ryan, Michael G. "Eucalyptus production and the supply, use and efficiency of use of water, light and nitrogen across a geographic gradient in Brazil" 2004, Forest ecology and management. Vol. 193, no. 1/2 (May 2004): p. 17-31. - Stape et al, 2007. “Production and carbon allocation in a clonal Eucalyptus plantation with water and nutrient manipulations” Forest Ecology and Management 255 (2008) 920-930 - Auro C. Almeida, Anders Siggins, Thiago R. Batista, Chris Beadle, Sebastiao Fonseca, Rodolfo Loos, Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG, a process-based growth model, Forest Ecology and Management, Volume 259, Issue 9, Productivity in Tropical Plantations, 15 April 2010, Pages 1730-1740, ISSN 0378-1127 - Laércio Couto, Antonio de Arruda Tsukamoto Filho, Júlio César Lima Neves, Carlos Alberto Moraes Passos, Carlos Antonio Álvares Soares Ribeiro e Michelle Margarido Fonseca Couto Araujo "PRODUÇÃO E ALOCAÇÃO DE BIOMASSA EM UM SISTEMA AGRISSILVIPASTORIL COM EUCALIPTO NA REGIÃO DO CERRADO DE MINAS GERAIS" Renabio - Biomassa & Energia, v. 1, n. 4, p. 321-334, 2004 - Daniel Pereira Guimarães, Gualter Guenther Costa Silva, Luiz Marcelo Aguiar Sans, Fernando Palha Leite "Uso do modelo de crescimento 3-PG para o zoneamento do potencial produtivo do eucalipto no estado de Minas Gerais". NOTA TÉCNICA. Revista Brasileira de Agrometeorologia, Piracicaba, v.15, n.2, p.192-197 Recebido para publicação em 07/11/06. Aprovado em 06/08/07. ISSN 0104-1347 - IBGE: Instituto Brasileiro de Geografia e Estatística http://www.ibge.gov.br/home/ - Mapa Exploratorio-Reconhecimiento de solos de municipio de Cristopolis, BA. Fonte: Leventamento Exploratorio-Reconhecimiento de Solos de Estado de Bahia (Embrapa/SUDENE 1973) DIREITOS RESERVADOS: EMBRAPA SOLOS, UEP Recife - Mapa Exploratorio-Reconhecimiento de solos de municipio de Baianopolis, BA. Fonte: 19

Leventamento Exploratorio-Reconhecimiento de Solos de Estado de Bahia (Embrapa/SUDENE 1973) DIREITOS RESERVADOS: EMBRAPA SOLOS, UEP Recife - Mapa Exploratorio-Reconhecimiento de solos de municipio de Barreiras, BA. Fonte: Leventamento Exploratorio-Reconhecimiento de Solos de Estado de Bahia (Embrapa/SUDENE 1973) DIREITOS RESERVADOS: EMBRAPA SOLOS, UEP Recife - ZANE, ZONEAMENTO AGROECOLÓGICO DO NORDESTE www.uep.cnps.embrapa.br/zane - Álvaro Nogueira de Souza, Antônio Donizette de Oliveira, José Roberto Soares Scolforo, José Luiz Pereira de Rezende, José Marcio de Mello “VIABILIDADE ECONÔMICA DE UM SISTEMA AGROFLORESTAL” Cerne, Lavras, v. 13, n. 1, p. 96-106, jan./mar. 2007 Software resources Several software resources were used for the realization of this assessment: - The 3-PG Model Software. 3-PG is the acronym of the Physilological Principles Predicting Growth, which is a “generalized forest carbon allocation model, published by Landsberg and Waring on 1997. http://www.csiro.au/products/3PGProductivity.html - Microsoft Excel, http://www.microsoft.com - Microsoft Windows XP Professional, http://www.microsoft.com - Openoffice.org 3.2.0, http://www.openoffice.org/ - Debian Gnu/Linux 5.0.4, http://www.debian.org/ - Grass GIS 6.4.0RC6 (2010) http://grass.osgeo.org/ - Quantum GIS (QGIS) version 1.4.0 Enceladus, http://www.qgis.org - Scribus, http://www.scribus.net Acknowledgments The main data sources, crucial for the realization of this assessment, have to be acknowledged: - Landsat ETM 2000 Mosaics, from EarthExplorer, United States Geological Survey, US Department of Interior - IBGE: Instituto Brasileiro de Geografia e Estatística, Brazil Acknowledgments are also owed to the authors/developers of the 3-PG model, Dr. J.J. Landsberg and Dr. R.H. Waring. - J.J. Landsberg, R.H. Waring, A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning, Forest Ecology and Management, Volume 95, Issue 3, 1 August 1997, Pages 209-228, ISSN 0378-1127 Finally, acknowledgments are expressed to the Australian Commonwealth Scientific and Research Organization (CSIRO)/Forestry Management for the distribution and provision of the 3PG model software. 20

Document details: This independent assessment for Eucalyptus growth projections was developed by bio4met <www.bio4met.com> for GW Group. This document is subject to future improvements. 21

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