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1 THE ECOLOGICAL AND ECONOMIC VIABILITY OF SMALLHOLDER TIMBER MANAGEMENT IN THE AMAZON ESTUARY By LUCAS BERIO FORTINI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010
2 2010 Lucas Berio Fortini
3 Escapamos a fome da ona, fugimos dos bufalos selvagens, sobrevivemos a picada da cobra, o corte da serra afiada, aguentamos a fome em lugares distantes, muito carapan, agua e lama, e sofremos com a distancia dos que amamos. To my Guanabana, Dona Rosaria, Dona Raimunda, my parent s, and the Mazago River
4 ACKNOWLEDGMENTS First and foremost, I would like to thank my wife for her encouragement, support and in general making life during dissertation writing as pleasant as could be. Thanks to all people of the Mazago River who received me with open arms and taught me so much beyond their wisdom of the forest Itamar, Geroncio, Nonato, Tom and family, Dona Zuleide, Seu Martel, Rubilota, Seu Amilton, Jurac and many, many others. Um agradecimento especial para Dona Rosaria, Dona Raimunda e sua familia, o meu lar e familia na Amaznia hoje e sempre. Thanks to the time and valuable feedback of all my committee members, especially to my advisor Daniel Zarin. Thanks to all my Gainesville friends, many of whom have come and gone, that made my time in Florida a truly wonderful and memorable part of my lifenaming names would unfortunately risk me exceeding dissertation size limitations, but you know who you are. Lastly, thanks to Monkey for her trusty company during most of my writing. This research would not have been possible without the generous support from a Tropical Conservation and Development (TCD) fellowship and research grant, a NSF IGERT Working Forest in the Tropics fellowship and research grant, a NSF doctoral dissertation research improvement grant, a NSF South East Alliance for Graduate Education and the Professoriate (IGERT) fellowship and an EPA Science to Achieve Results (STAR) fellowship. Thank you for believing my research was possible and that I was not entirely crazy.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 9 LIST OF FIGURES ........................................................................................................ 10 ABSTRACT ................................................................................................................... 12 CHAPTER 1 INTRODUCTION .................................................................................................... 14 The Potential Role of STM in SFM ......................................................................... 15 Timber, Smallholders and the Amazon Estuary ...................................................... 16 Scope of Dissertation .............................................................................................. 17 Component 1: From Regional to Watershed .................................................... 18 Component 2: Timber Species Ecology, Population Dynamics, and LongTerm Timber Use in an Amazon Tidal Floodplain Watershed. ...................... 19 Component 3: Timber Resource Use and Economics in an Amazon Tidal Floodplain Watershed. .................................................................................. 20 Component 4: Integrating Ecological, Management and Economic Models at the Watershed Scale to Explore the Prospects of Management and LongTerm Forest Use. ................................................................................. 21 2 MIXED POTENTIAL FOR SUSTAINABLE FOREST USE IN THE TIDAL FLOODPLAIN OF THE AMAZON RIVER ............................................................... 23 Background ............................................................................................................. 23 Study Area .............................................................................................................. 24 Methods .................................................................................................................. 25 Results .................................................................................................................... 28 Discussion .............................................................................................................. 32 Mixed Potential for Contrasting Forest Uses .................................................... 32 Palm Dominance and Alternative Forest Uses ................................................. 33 Concluding remarks on Amazon Estuary composition variability ..................... 35 3 POPULATION DYNAMICS AND MANAGEMENT OF AMAZON TIDAL FLOODPLAIN FORESTS: LINKS TO THE PAST, PRESENT AND FUTURE ........ 47 Background ............................................................................................................. 47 Methods .................................................................................................................. 48 Study Region .................................................................................................... 48 Species Selection ............................................................................................. 49
6 Permanent Inventory Plots ............................................................................... 50 Evaluation of Timber Use History ..................................................................... 51 Analysis ............................................................................................................ 51 DBH estimates ........................................................................................... 52 Estimating commercial volumes ................................................................. 52 Create population models for species or species groups ........................... 53 Modeling diameter increments and matrix transition probabilities .............. 53 Modeling survival ....................................................................................... 54 Estimating recruitment and modeling fertility .............................................. 54 Exploring tree population demography with matrix models ........................ 56 Results .................................................................................................................... 57 Diameter Distributions ...................................................................................... 57 Diameter Increment Analysis ............................................................................ 58 Tree Growth Determinants ............................................................................... 59 Survival and Recruitment Estimates ................................................................. 59 Evaluation of Timber Use History ..................................................................... 60 Matrix Model Outputs ....................................................................................... 61 Population growth estimates ...................................................................... 61 ............................................................................ 62 Stable stage distributions and r eproductive values .................................... 62 Population growth sensitivities and elasticities ........................................... 63 Population growth sensitivity to harvested individuals and volume ............ 63 Stable age distributions .............................................................................. 64 Discussi on .............................................................................................................. 64 Species Distribution and Densities ................................................................... 64 Tidal Floodplain Tree Demography and Dynamics ........................................... 65 Population Ecology and the Past and Future of Forest Use and Management ................................................................................................. 67 Concluding remarks on Amazon Estuary tree population ecology ................... 68 4 PROSPECTS FOR CONTINUED TI MBER PRODUCTION IN AMAZONIAN TIDAL FLOODPLAIN FORESTS ............................................................................ 81 Background ............................................................................................................. 81 Methods .................................................................................................................. 83 Study Region .................................................................................................... 83 Species Selection ............................................................................................. 84 Permanent Inventory Plots ............................................................................... 84 Estimating Population Commercial Proportion ................................................. 85 Monitoring of Harvesting Activities ................................................................... 86 Harvest Model .................................................................................................. 86 Results .................................................................................................................... 91 Post Harvest Demographic Effects .................................................................. 91 Harvest Damage and Mortality ......................................................................... 93 Management Simulation Outputs ..................................................................... 93 STM Sensitivity to Management Criteria .......................................................... 96 Discussion .............................................................................................................. 97
7 Demography Differences Between Recently Logged and Recently Undisturbed Estuarine Forests ...................................................................... 97 Harvest Damage from Nonmechanized Small scale Logging ......................... 99 Prospects for Sustainable Timber Yield ......................................................... 100 Determining Best Management Regimes for Sustainable Timber Management ............................................................................................... 102 5 TIMBER MICRO FIRMS OF THE AMAZON ESTUARY: A VIABLE ECONOMIC MODEL FOR DEVELOPMENT? .......................................................................... 117 Introduction ........................................................................................................... 117 Methods ................................................................................................................ 119 Study Region .................................................................................................. 119 The Vrzea Smallho lder Timber Production System ...................................... 119 Monitoring of Extraction and Sawmill Activities .............................................. 120 Financial Returns Model ................................................................................. 121 Model Perturbation and Sensitivity Analyses .................................................. 122 Evaluating Aa Costs and Revenues ............................................................ 123 Results .................................................................................................................. 124 Extraction Practices ........................................................................................ 124 Sawmill Practices ........................................................................................... 124 Cost and Revenues of Micro Timber Firms .................................................... 125 Aa Fruit Production Costs and Revenues .................................................... 126 Timber and Aa Comparison ......................................................................... 126 Discussion ............................................................................................................ 127 The Smallholder Timb er Micro Firm ............................................................... 127 Micro Firm Profitability .................................................................................... 129 Timber vs Aa Production in the Amazon Estuary ........................................ 130 Micro Scale Timber Production: A Poverty Driven System? ........................... 132 6 SYNTHESIS: DETERMINING THE ECOLOGICAL AND ECONOMIC VIABILITY OF TIMBER MANAGEMENT IN THE AMAZON: A WATERSHED SIMULATION APPROACH .......................................................................................................... 143 I ntroduction ........................................................................................................... 143 M ethods ................................................................................................................ 144 The Vrzea Smallholder Timber Production System ...................................... 144 Mazago Watershed Simulation Model .......................................................... 145 Scaling and Integrating Precursor Models to Watershed/ Industry Scale ....... 146 Model Optimization and Stochasticity ............................................................. 148 Watershed Scenarios ..................................................................................... 150 Model Outputs ................................................................................................ 151 R esults .................................................................................................................. 152 Scenario Outcomes ........................................................................................ 152 What are the prospects for the Mazago timber industry operating informally under current levels of timber demand? (Scenarios 1, 3, 7) 152
8 What are the prospects for industry operating informally seeking financial returns similar to Aa fruit production? (Scenarios 2, 5, and 9) .......................................................................................................... 153 What is effect of legality on the viability of timber production by Mazago smallholders? (Scenarios 4, 6, 8,10) ..................................... 154 Consequences of Changing Factors of Production ........................................ 155 D iscussion ............................................................................................................ 158 The Benefits of Forest Management .............................................................. 158 Importance of Model Parameters ................................................................... 158 Industry Economic Viability ............................................................................. 159 Industry Ecological Viability ............................................................................ 160 The Consequences of Legalization ................................................................ 160 Prospects for Management ............................................................................ 162 APPENDIX: SPECIES LIST AND ABUNDANCE FOR MAZAGO AND IPIXUNA SAMPLE PLOTS .................................................................................................. 172 LITERATURE CITED .................................................................................................. 177 BIOGRAPHICAL SKETCH .......................................................................................... 195
9 LIST OF TABLES Table page 2 1 Summary of structural differences between Mazago and Ipixuna .................... 36 2 2 Summary of compositional differences between Mazago and Ipixuna ............. 37 2 4 Potential of alternate forest uses between Mazago and Ipixuna, Amap, Brazil .................................................................................................................. 39 3 1 Study species. .................................................................................................... 70 3 2 Auxiliary information collected for inventory trees. .............................................. 71 3 3 Categories of measurement quality for model data use ..................................... 72 3 4 Matrix projection model based on underlying vital rates. .................................... 72 3 5 Actual vs stable population yearly recruitment rates ........................................... 73 4 1 Study species ................................................................................................... 106 4 2 Transition matrix model used for management simulations .............................. 106 4 3 Values for management criteria used in management simulations ................... 107 4 4 R esidual stand damage from monitored timber extraction ............................... 108 4 5 Optimal management regim es defined by alternative sustained timber yield indicators .......................................................................................................... 109 4 6 Comparison of species specific optimal management regimes according to four STM indicators .......................................................................................... 110 4 7 Differences in performance between species specific and general optimal management regimes ....................................................................................... 111 5 1 Economic indicators of timber and aa management ...................................... 135 5 2 Model parameters and their elasticities ............................................................ 136 6 1 Watershed management scenarios .................................................................. 164 6 2 Parameters and values used in model sensitivity analyses .............................. 165 6 3 Watershed management scenario outcomes ................................................... 166
10 LIST OF FIGURES Figure page 1 1 Map of Amazon Estuary with location of areas contemplated in the dissertation.. ....................................................................................................... 22 2 1 Map of Amazon Estuary with location of forest inventory plots. .......................... 40 2 2 DBH distribution for harvestable species in Mazago and Ipixuna. .................... 4 1 2 3 Species accumulation curves for overstory and understory of Mazago and Ipixuna sites. ....................................................................................................... 42 2 4 DCA results for (a) overstory and (b) understory for Mazago and Ipixuna. ....... 43 2 5 Individual species in DCA ordination space with respect to species characteristics. .................................................................................................... 44 2 6 Negative relationships between palm and nonpalm dominance ........................ 45 2 7 Two dimensional DCA solution for overstory data (DBH > 10 cm) from Mazago, Ipixuna and Guam at the genus level. .............................................. 46 3 1 Study region ....................................................................................................... 74 3 2 Diameter distribution for studied species. Vertical dashed line indicates legal harvest size ........................................................................................................ 75 3 3 Median and maximum diameter increments. Vertical dashed line indicates legal harvest size ................................................................................................ 76 3 4 Proportion of trees under full light ....................................................................... 77 3 5 Proportion of reproductive trees ......................................................................... 77 3 6 Population growth estimates for studied species by year with 95% confidence intervals .............................................................................................................. 78 3 7 Observed vs stable state diameter distributions ................................................. 79 3 8 Median age at stable state distribution ............................................................... 80 4 1 Map of study area ............................................................................................. 112 4 2 Life table response experiment for M. paraensis demonstrating demographic differences between logged and recently undisturbed plots and their contributions to population growth .................................................................... 113
11 4 3 Management simulation projections illustrating differences between species and grouped density depende nt models .......................................................... 114 4 4 Shifts in commercial proportion under the Brazilian legal scenario with 30 yr cutting cycle but without volumebased harvest limits ...................................... 115 4 5 Simulation H in response to varying management criteria. ........................................................................................ 116 5 1 Map of study site. ............................................................................................. 138 5 2 Average costs per extraction activity standardized by timber volume delivered to sawmill. ......................................................................................... 139 5 3 Average extraction costs per m3 of timber delivered to sawmill by category .... 140 5 4 Sawmill volume processed daily by person hours of work ................................ 141 5 5 Average firm's yearly costs and revenues (processing, forest) ......................... 142 6 1 Map of Mazago watershed landcover ............................................................. 167 6 2 Graphical representation of simulated yearly harvests on watershed forests ... 167 6 3 The consequence of local industry size to watershed scenarios with business as usual (BAU) informal production. .................................................. 168 6 4 Decrease in the probability of industry persis tence with increasing watershed areas unavailable for management under alternate profit optimizing forest management scenarios. ................................................................................... 169 6 5 Consequence of adopting legalization for watershed scenarios with firms seeking aa profit equivalence while adopting federal management guidelines (FDM) and regionally derived sustainable timber management guidelines (STM). ............................................................................................. 170 6 6 Decrease in the probability of industry persistence with increasing watershed areas unavailable for management under business as usual (BAU) informal production. ........................................................................................................ 171
12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE ECOLOGICAL AND ECONOMIC VIABILITY OF SMALLHOLDER TIMBER MANAGEMENT IN THE AMAZON ESTUARY By Lucas Berio Fortini December 2010 Chair: Daniel J. Zarin Major: Forest Resources and Conservation Amazonian tidal floodplain forests were among the first to be exploited by Europeans and represent the oldest commercial logging frontier in the region. Today, thousands of families rely on timber from the tidal floodplain forests as a source of income. They harvest timber manually, without legal sanction, and process it locally at any of the hundreds of smallholder owned micro sawmills in the area. Some previous researchers suggest that smallholders are producing timber sustainably in the region, while others have argued that timber resources are being depleted. However, past assessments lack the quantitative analyses needed to evaluate these claims critically. This dissertation tackles the issue of the sustainability of smallholder timber use from multiple perspect ives and scales. In the Mazago watershed of the Amazon Estuary, I analyzed and modeled patterns of tree community composition and timber species population dynamics (Chapters 2 and 3); used simulation modeling to define sustainable timber management (STM) regimes for local stands (Chapter 4); and used financial return models to explore the economic viability of micro firms (Chapter 5).
13 Lastly, I integrated previous ecological, management, and economic models (Chapters 3, 4, and 5) to create an interdiscipl inary watershed model (Chapter 6) to evaluate the future of local forests and the local timber industry under alternate scenarios of management, legality, and production levels. While the majority of STM related research in the Amazon has revealed discour aging prospects for both sustainable forest management and STM, results from this research show that, with changes in management and adequate institutional support, a sustainable model for smallholder timber use in the estuary is possible. Unfortunately, over centuries of mismanagement, the long history of timber extraction in the Amazon Estuary hides a gradual process of resource depletion as preferred species are sequentially exhausted. If such practices do not unchanged, the prospects for longterm management will decrease as the densities of preferred highvalue species (e.g., Carapa guianensis Virola surinamensis ) fall to critically low levels that make management economically unattractive at smallholder scales. This research demonstrates that conceptually simple models can help reveal management options and explore their projected consequences at watershed and landscape scales. Such models can lead to management that yields better ecological and economic outcomes that consider regional specific tree community composition and ecology.
14 CHAPTER 1 INTRODUCTION Despite decades at the center of global environmental concerns, the crisis of tropical forest loss endures (Hansen et al. 2010) The net effect has been massive biodiversity loss, dubious gains in local welfare and development, and massive carbon emissio ns that equal that of the entire global transportation sector (IPCC 2007, Hubbell et al. 2008, Rodrigues et al. 2009) Years of divisive debates regarding the appropriate strategy to stem the ongoing crisis have focused on false choices between preservation and conservation. On one sid e, some argue strict preservation would leave large forest areas at risk of conversion and ignore the needs of forest inhabitants (Schwartzman et al 2000) On the other, researchers have expressed doubt about productionbased forest conservation strategies (Homma 1992, Redford and Sanderson 2000, Rice et al. 2001) However, it is increasingly clear that the ecological and social complexity and variability of tropical forests re quire a flexible approach where preservation and conservation are coupled with a more comprehensive valuation of forest goods and services. Studies of forest succession, along with evidence of preColombian largescale forest conversion in seemingly intact forests indicate that tropical forests are more ecologically resilient than generally acknowledged (Uhl et al. 1988, Willis et al. 2004, Heckenberger et al. 2007) F orests seem able to recover structurally and compositionally (in terms of richness) within years to decades from small scale human disturbances such as logging gaps and small agricultural plots To acknowledge the long history of human disturbance and powerful regenerative ability of tropical forests does not mean humans should exploit forests without concern. On the contrary, it
15 shows we cannot take a snapshot of a forest that holds no physical sign of human interference today and hold it as the single measuring stick It is to recognize tropical rain forests as dynamic entities and people as shapers of past and present environmental change. From a conservation perspective, sustainable forest management (SFM) at its core attempts to curb deforestation by making lowimpact forest based activities competitive over other destructive land uses. However, SFM has been an illus ive goal as its competitiveness depends on a set of ecological, economic, and social conditions that must be maintained indefinitely to ensure forest persistence (ITTO 2005, UNFF 2009) The Potential R ole of STM in SFM According to the ITTO (2006) only 7% of areas under timber use are managed sustainably. Yet, across most tropical forests, the viability of longterm timber management is still unexplored. For remote tropical areas where timber is a main product, this means sustainable timber management (STM) that ensures yields harvest after harvest should be an important component of SFM ( Seydack 1995; Zarin et al. 2007 but see Luckert and Williamson 2005 ). With 25% of worlds poor being forest dependent and an estimated 0.51 billion smallholders managing trees and remnant forests, the need for SFM and STM at community and smallholder scales is clear (Scherr et al. 2004) Unfortunately most forest legislation focuses on administrative requirements, fees, taxes and property rights that pos e challenges to small holders and are not directly related to SFM (Kaimowitz 2003) and most tropical forest management research has focused on l argescale industrial operations.
16 In the Amazon Estuary smallholders have developed a microscale vertically integrated system of timber production (Pinedo Vasquez et al. 2001, Sears et al. 2007a) Contrary to community led efforts elsewhere, these informal micro firms are owned individually and commonly integrate timber extraction and processing in local circular sawmills. For decades, hundreds of these micro firms have produced sawn lumber sold primarily at local and regional markets (Barros and Uhl 1995) As an example of a small scale localized timber production system, the Amazon Estuary is ideal for exploring issues of smal lholder vertically integrated timber use. Timber Smallholders and the Amazon Estuary Floodplain forests cover 25,000 km2 of the Amazon estuary (Lima, 1956) Compared to the terra firme forests, floodplain forests have a lower diversity of tree species and a high abundance of economically valuable species (Lopez & Kursar, 2003; Martin et al. 1992; Parolin et al. 2004; Terborgh & Andresen, 1998) Low floodplain forests may experience tidal flooding from fresh water back up twice a day, while higher areas may ex perience flooding only in the wettest months between January through May. After centuries of disturbance, the persistence of Amazon tidal floodplain forests indicates a potential for sustainable timber management (Raffles, 1997) This potential is further bolstered by an abundance of timber, relatively fertile soil, and low cost/ low damage of water transport (Anderson 1990, Zarin et al. 1998) In relatio n to timber harvesting in Amazonian upland forests, floodplain forest operations have lower negative environmental impacts due to the lack of heavy machinery use and the reliance on river transportation that precludes road construction and eventual defores tation (Kaimowitz and Angelsen 1998, Laurance 2001) Additionally, the dangerous firefe edback mechanisms that often hinder the recovery of upland forests
17 following logging are absent in floodplain forests (Nepstad et al. 1999, Gerwing 2002, Cochrane and Laurance 2002) C aboclos are the traditional inhabitants with mixed indigenous, European and African descent and show a detailed knowledge of their environment. Caboclos have developed ecologically integrated livelihood strategies through centuries of coexistence with the Amazonian floodplains (Hiraoka, 1992) Much of the Amazon tidal floodplain has been hi storically inhabited by communities of caboclo smallholders. At present, timber remains an important resource for subsistence and an important source of income for many caboclo families. Hundreds of small scale, family run timber operations supplied by many more thousands of smallholders with forest resources rely on timber as a source of income (Barros & Uhl, 1995; 2005) Past research on caboclo smallscale timber production has documented cases of apparently sustainable forest use in the region (PinedoVasquez et al. 2001, Sears and Pinedo Vasquez 2004) while others have argued that timber resources are being depleted (Macedo and Anderson 1993, Barros and Uhl 1995) But these assessments lack quantitative analyses needed for accurat e evaluation of impacts of past, present, and future forest use. Scope of D issertation In this dissertation I evaluate the sustainability of timber production in the region based on modeling watershedscale timber resource availability and use. A watershed approach allowed me to incorporate the current extent of forest cover types compatible with timber production within the watershed, the ecology and yield of species utilized, and the economics of timber production. Results are useful for the eval uation of current
18 and future scenarios of timber extraction intensity and methods while providing insights into the main factors limiting sustainable timber use in the Amazon estuary. My research is primarily focused in the Mazago watershed at the Western side of the Amazon estuary ( Figure 1; Chapters 36). This 160 sq km watershed has a long history of timber use and is similar in composition and land use history to several adjacent watersheds. Preliminary surveys in the study area show timber as the base of a complex economy where some households will often extract and process timber in family run sawmills from the land of other households within the watershed. Because of this, the study of timber use and management at stand and property scales is inappropriate since timber related activities commonly happen across property boundaries and over multiple forest stands. A watershed scale approach is also more appropriate because the caboclo community that extracts, processes, and markets timber resources of t he watershed is entirely enclosed within the watershed, facilitating linking ecological and social processes at a compatible scale. Component 1: From Regional to W atershed Most forest use in the Amazon estuary now occurs on plots of < 100 ha (Sears and Pinedo Vasquez 2004) ; regionwide generalizations are not particularly relevant to this scale unless conditions are homogeneous. In Chapter 2, I examine stands selected to represent what is characterized as intact forest by local people, whose primary use of such areas is for hunting and limited harvesting of fruit from unmanaged aa palms. Results illustrate high, estuary w ide variability in forest structure and composition among apparently similar estuarine floodplain forests, and emphasize how local structural and compositional differences
19 result in contrasting potential for sustainable forest management. This chapter serv es as a regional context for the other chapters. Component 2: Timber Species Ecology, Population D ynamics, and LongTerm Timber Use in an Amazon Tidal Floodplain W atershed. The absence of tree demography data has inhibited the formulation and evaluation o f tidal floodplainspecific guidelines for ecologically sound forest management. In Chapter 3 I evaluate species specific abundance, diameter and spatial distributions, and recruitment, growth and mortality rates of timber species in tidal floodplain fores ts. I also employ matrix population models to explore the underlying population dynamics of common tidal floodplain species and explore the link between species population ecology and past, present, and future timber use. In my analysis, I combine conventi onal tree demography methods with data from interviews with tidal floodplain C aboclos regarding land use and ecological knowledge. While a wide choice of models have been applied to address the ecological viability of STM (Vanclay 1995, Kammesheidt et al. 2001, Glauner et al. 2003, Phillips et al. 2004, Gourlet Fleury et al. 2005, Valle et al. 2007) most relevant research has focused on the evaluation of harvest damage, post harvest effects on growth, recruitment and mortality separately (Fredericksen and Mostacedo 2000, Chapman and Chapman 1997, Finegan and Camacho 1999) Without integrating these population demography responses, however, net population effect s of timber harvest and management remain unclear. Furthermore, most related research to date has focused on evaluating current practices instead of searching for alternate sustainable management regimes relevant to forest managers and regulators.
20 In Chapter 4 I used a matrix based harvest simulation model to evaluate the prospects for sustained timber production in the Amazon estuary. Based on a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), I projected the population and yield outcomes of hundreds of longterm timber management regimes. These results were then compared using simple quantitative indicators of STM to find optimal standlevel and species specific sustainable timber management regimes relev ant to similar forests in the Amazon Estuary. Component 3: Timber Resource Use a nd Economics i n a n Amazon Tidal Floodplain Watershed. In order to understand the potential for timber management, we must not only consider the ecological limitations to management but also the economic viability of timber harvesting (Boot, 1997; Buongiorno et al. 1995; Lu & Buongiorno, 1993) Smallholder timber operations may vary substantially from industrial operations in techniques, technology, capital availability, market reach and ecological impacts (chapter 4, Salafsky et al. 1998, Rockwell et al. 2007a, Keefe 2008) Previous research has estimated that there are nearly 800 family run sawmills in the Amazon Estuary that function under a different set of costs and limitations than the larger operations commonly found in other areas in the Amazon (Barros & Uhl, 1995; 2005; 2003) In the Mazago watershed, 12 timber micro firms were responsible for processing the harvested wood from the watershed. Surprisingly, relatively little attention has been paid to the potentials and limitations of timber management at smallholder scales, with the most relevant research focusing on community forestry efforts (d'Oliveira 2000, Rockwell et al. 2007b) Without the proper knowledge and consideration of the
21 potentials and limitations of smallholder timber management, most regulation o f timber use in the tropics has focused on the industrial scale, leading to unrealistic expectations for smallholders and communities (d'Oliveira 2000, Rockwell et al. 2007a, Zarin et al. 2007) In Chapter 5 I use data from multiple sources including landowner and firm surveys, participatory monitoring of firms, and detailed forest and sawmill operation monitoring to devise a financial returns model of smallholder timber micro firms and a simpler model for smallholder aa fruit production. I then explore the economics of timber micro firms to address th e following questions: (1) What are the financial costs and revenues of timber micro firms? (2) What micro economic factors most influence longterm economic viability of timber production by micro firms? (3) How does timber micro firm profitability comp are to regional economic alternatives? How can this be used to advance tropical conservation and development? Component 4: Integrating Ecological, Management a nd Economic Models a t t he Watershed Scale t o Explore t he P rospects of Management and LongTerm Forest Use. With a few exceptions, the ecologic and economic viability of production in tropical forestshas been evaluated at single fir m/ single stand scales However, to effectively balance conservation and economic viability necessary for sustainable tr opical forest use, ecological and economic limitations must be considered simultaneously (B oot and Gullison 1995, Merry et al. 2009) In Chapter 6, following the previous chapters exploring community composition (Chapter 2), timber s pecies population ecol ogy (Chapter 3), sustainable timber management (STM) regimes for local stands (Chapter 4) and the economic viability of
22 micro firms (Chapter 5), I create an interdisciplinary model to evaluate watershed timber resource availability and use under alternat iv e scenarios of management, legality, and production levels. We employed multiple forest use scenarios to address questions of sustainability at the scale of a whole watershed (and its related local timber industry) to explore the link between ecological, economic and legal constraints to forest use and proposed management. Figure 11. Map of Amazon Estuary with location of areas contemplated in the dissertation. The regions of Ipixuna, Guam, Barca rena, Cajuuna, Chaves and Xing are considered only in Chapter 2. All other chapters focus on Mazago watershed as a comprehensive microcosm study.
23 CHAPTER 2 MIXED POTENTIAL FOR SUSTAINABLE FOREST USE IN THE TIDAL FLOODPLAIN OF THE AMAZON RIVER Background The tidal floodplain forests of the Amazon estuary have supported timber harvesting since at least as ear ly as the 17th century, but in a much more selective form (in size and species) than modern extraction. Beginning in the late 1950s, large saw and plywood mills were established in the region during a period of intense exploitation that lasted until the 1980s. During this period Cedrela odorata, Virola surinamensis Carapa guianenesis Hura crepitans and Maquira coriaceae were the most sought after species (Raffles 1999) Since then, small scale logging and milling operations have replaced the larger sawmills (Barros and Uhl 1995, PinedoVasquez et al. 2001) The persistent of logging activity in the region suggests an underlying potential for sustainable management of timber production, potential that is bolstered by a high number of timber species, the relativ ely low impact of extraction due to water transport, relatively fertile soils, and well developed local ecological knowledge (Anderson 1990, Hiraoka 1992, Zarin et al. 1998, Laurance 2001) While some researchers suggest that smallholders are managing timber production sustainably in the region (Pinedo Vasquez et al. 2001, Sears and PinedoVasquez 2004) others have argued that sustainable management is largely unrealized and that timber resources are being depleted (Macedo and Anderson 1993) Additionally, non timber forest products, especially the aa palm ( Euterpe oleracea), have become increasingly important in the subsistenc e and market economies of floodplain inhabitants ( e.g., Brondizio 2004). It is
24 unclear whether nontimber forest produc ts are complementary or incompatible with timber production and forest conservation (Alavalapati and Zarin 2004) Most forest management in the Amazon estuary now occurs on plots of < 100 ha (Sears and PinedoVasquez 2004) ; regionwide generalizations are not particularly rel evant to this scale unless conditions are homogeneous. Within the Amazon estuary, there are few cross site comparisons (de Almeida et al. 2004) Previous regional analyses of vegetation cover in the estuary were unable to detect subtle compositional differences with remote sensing (Zarin et al. 2001, Pereira et al. 2002) or lack consideration of natural variability of forest composition at the local property or community scale relevant to riverine forest management (Brondizio et al. 1994) Most previous research on tidal floodplain forest has focused on the description and viability of currently managed forests (Anderson 1986, 1991, Anderson et al. 1995, Munizmiret et al. 1996, Brondizio and Siqueira 1997, Sears and PinedoVasquez 2004) In this study, we examine stands selected to represent what is characterized as intact forest by local people, whose primary use of such areas is for hunting and limited harvesting of fruit from unmanaged aa palms. We illustrate the degree of heterogeneity among apparently similar estuarine floodplain forests, and emphasize how local structural and compositional differences result in contrasting potential for sustainable forest management. Study A rea We conducted our research at two tidal floodplain forest sites in the Amazon Estuary near Macap, the state capital of Amap. Mean annual temperature is 27C and average daily temperature varies by less than 3C from month to month in the region. Mean annual precipitation is 2550 mm and occurs mostl y in the wet season months of
25 January May. This part of the Amazon estuary is characterized by freshwater tidal fluctuations of 23 m. The two sites, Mazago (00 03 N and 50 37W) and Ipixuna (00 30 S and 51 13W), are southwest and northeast from Macap, respectively; both sites are on tributaries near the main stem of the Am azon Rivers north channel (Figure 2 1). Because of the elevated river level in the wet season, both sites are flooded twice daily during high tide. We also used published data from two other studies to compare our results within the larger context of intact Amazon estuarine forests. Data from an early 3.8 ha inventory of a tidal floodplain forest by the Guam River (Pires and Koury 1959) was included to compare the composition of Mazago and Ipixuna plots with that of an old growth forest site. Although Pires and Koury did not include formal collection of land use history fo r their inventory area, they characterize the stand as primary forest. In addition, we included four 1ha estuary forest plots from Almeida et al. (2004) to expand our geographical extent of compositional comparisons. These plots were located across the Amazon Estuary in the municipalities of Barcarena, Afu (Cajuuna Island), Chaves, and at the lower Xing River. Methods At each research site, five 1 ha plots were located within a 75 ha area in Ipixuna and 90 ha area in Mazago. Plots were not located randomly at each site due to limited available areas for permanent plot establishment. Instead, plots were selected to represent intact forest. Diamete r measurements and species identifications were made for all stems > 5 cm DBH within each plot (hereafter overstory). Stems > 10 cm height and < 5 cm DBH were identified and counted within 5 X 5 m subplots (n = 16 per plot, hereafter understory). The G uam inventory included all trees with DBH > 10 cm in a
26 380 x 100 m strip (Pires and Koury 1959) For the purposes of comparing Guam composition with that of Ipixuna and Mazago on an equal area basis, we divided the Guam data into three 1 ha separated by 40 m buffers. The four 1 ha plots sampled by Almedia et al. (2004) also included only trees with DBH > 10 cm. Interviews with landowners, loggers, and sawmill operators were carried out from May to August, 2004 in Mazago and Ipixuna. Questions regarding the historical use of local forests and the distribution of commercial species were asked to evaluate land use history and local perception of patterns of forest composition within and between Mazago and Ipixuna. To compare forest management potential between areas, we separated inventoried species into palm and nonpalm (eudicots) categories and separated timber species as a separat e subcategory within the nonpalm group. Density, frequency, dominance, species richness, Sorensen distance, Simpson, Shanon and evenness indices and measures were calculated using standard methods and formulas (Nebel et al. 2001, McCune and Grace 2002) Species accumulation curves, ordinations, indicator species analysis, multi response permutation procedure (MRPP), Simpson diversity and evenness and Sor ensen distance were calculated using PC ord software (version 4, SAS institute inc.) following procedures suggested by McCune and Grace (2002). Species accumulation curves were created for each region by classifying individuals measured as unique data entr ies and then calculating average richness for all subsamples from n=1 until n=N, with 500 randomly picked replicates for each sample size. We used detrended correspondence analysis (DCA) of the log transformed abundance data [ log (x + 1) ] for ordination p urposes because it produced the most
27 stable and clearly interpretable results. The use of DCA in our ordination analyses allowed us to look at how species are positioned within ordination space. We hypothesized that, if forest composition were influenced by differences in land use history, species ordination along the main axis that separated plots from the two areas would follow a gradient of successional status. We used the same technique to test if other life traits, such as light and soil moisture requi rements influenced the position of species along axes of our DCA solution. We acquired life trait information from field observations, interviews with local forest users about species distributions, and from the available literature about the species (Vera et al. 1999, Webb 1999, Lopez and Kursar 1999, Adler and Kielpinski 2000, Lorenzi 2000, Sears 2003) We also inspected the clustering of species in ordination space and performed cluster analysis to identify possible species associations and related life history trait similarities. No species or plots were picked out by multivariate outlier analyses (Pc ord version 4, SAS institute inc.) and hence all data were included in the analysis. All comparisons between Mazago and Ipixuna were done at the species level. Biomass was calculated for all 1 ha plots in Mazago and Ipixuna using DBH whole tree biomass regression equations from Johnson (1999) to all overstory stems. These equations were derived from a tidal floodplain forest site at Mazago. Palm biomass = 0.0052 DBH 3.74 (R = 0.993, n = 6) Virola biomass = 0.0481 DBH 2.55 (R = 0.985, n = 5) Dicot (no Virola) biomass = 0.1155 DBH 2.501 (R = 0.985, n = 18)
28 Given the very high relative frequency of palms in all Mazago and Ipixuna plots (accounting for 47 and 72% of individuals >5cm DBH, respectively), and their commercial importance, we looked at the possible relations between palm abundance and overall forest structure and composition. We looked specifically at the relationship between the two most abundant palms in the study, A. murumuru and E. oleracea, and forest structure and composition since they accounted for almost all palm individuals measured in the study. We performed all comparisons between Mazago, Ipixuna, Guam and the Almeida et al. plots at the genus level which makes compositional similarities between sites more apparent (Terborgh and Andresen 1998) Genus level comparisons were used because of the difficulty in tracking changes in names for the species present in the Guam inventory and because of the geographic distance between the areas. A dditionally, only individuals with DBH > 10 cm were used in this analysis because of the differences in minimum DBH between our methods and those of the other two studies. Results Total stem density > 5 cm dbh was 15% lower for Mazago than for Ipixuna, but 35% higher for Mazago for nonpalm species. A similar pattern is evident in the understory data20% lower total stem density for Mazago, but 50% higher for Mazago when palm species were excluded (Table 2 1). These differences result from larger populations of A. murumuru and aa palms at Ipixuna than at Mazago (Appendix). Stem density of commercial timber species was more than twice as high at Mazago than at Ipixuna, both for all stems > 5 cm dbh and for large timber individuals (> 30 cm dbh); density of commercial timber species < 5 cm was three times greater at
29 Mazago. Mean basal area and biomass values were higher in Mazago, but only the basal area differences were statistically significant. A few timber species showed clear differences in their size class distribution between plots from Mazago and Ipixuna (Figure 2 2). For instance, while C. spruceanum size distribution showed an inverseJ shape in Ipixuna, the distribution of the same species in Mazago was characterized by much fewer indiv iduals in the smaller size classes but many more individuals in the larger size classes. On the other hand, this pattern was inverted for Licania heteromorpha, a species currently not utilized in the either site. Additionally, Carapa guianensis Mora paraensis Pentaclethra macroloba and Quararibea guianensis were practically absent from all Ipixuna plots but present in all Mazago plots with individuals as large as 60cm DBH. Mazago plots had a combined total of 88 overstory species, with a mean of 51 ha1, while Ipixuna plots contained fewer species, having a combined total of 67 overstory species, and a mean of 36 ha1. For understory individuals Mazago had a cumulative species richness of 68 and Ipixuna had 42. Simpsons diversity and evenness values w ere higher in Mazagao for both strata, but only the overstory differences were statistically significant (Table 2 2). Species accumulation curves also reflect a higher diversity of Mazago plots (Figure 2 3). The percentage of tree species represented by only one individual in each area was similar between Mazago and Ipixuna (23% v 24%, respectively). 31% of trees species in Mazago were represented by only 12 individuals, compared to 40% of Ipixuna species. 41% of understory species in Mazago were repre sented only by 12
30 individuals while only 26% of species in Ipixunas understory were represented only by 1 2 individuals. The two areas shared 5 of the 10 most abundant tree species ( E. oleraceae, A. murumuru, C. spruceanum L. heteromorpha, and T. surinamensis ), with E. oleracea and A. murumuru being the first and second most abundant species in both areas. Four of Mazagos 10 most abundant species were commercial timber species ( C. spruceanum L. heteromorpha, P. macroloba and G. augusta), whereas the 10 most abundant species from Ipixuna included only two commercially harvestable species ( C. spruceanum and L. heteromorpha). Species list and abundance for Mazago and Ipixuna sample plots are provided in appendix A. Indicator species analysis yielded 21 tree species that are significantly associated to Mazago and 9 species that were associated to Ipixuna (Table 2 3). Nine of Mazagos indicator species were of commercial logging value while none of Ipixunas indicator species were harvestable. Separati on between Mazago and Ipixuna plots in our DCA results occurs along in the primary axis representing the strongest gradient in the data set. This separation was clearer when ordinating tree and understory layers in separate analyses (Figure 2 4). The posi tioning of early to mid succesional species along the primary axes of the DCA ordination of tree data reveal no successional gradients between Mazago to Ipixuna sites. DCA results also show there is no clear gradient in species soil moisture or light requirements along the ordination axes (Fig ure 2 5). The ordination of species data also revealed no isolated clusters of species in ordination space, signaling no clear species grouping besides the vertical clustering that happened on either extreme of the primary
31 axis which represent species that happened exclusively in either of the two areas; also, the additional cluster analysis did not reveal any clear groups of common life history traits. Timber basal area was significantly correlated with palm basal ar ea at the plot level ( r = 0.66, p < 0.05; Figure 2 6). Nonpalm basal area was strongly correlated to A. Murumuru basal area ( r = 0.89, p < 0.001; Figure 2 6). E. oleracea abundance had no clear relation to forest structure and composition. The Pearson product moment correlation between plot level nonpalm total abundance and A. murumuru abundance yielded a significant negative relationship ( r = 0.8625, p < 0.01). Plot level richness and diversity were also negatively related to A. murumuru abundance. For tree data, the abundance of A. murumuru was negatively related to richness ( r = 0.8414, p < 0.01) and Simpson diversity ( r = 0.7240, p < 0.05) at the plot level. For this correlation analysis, we excluded E. oleracea and A. murumuru data from the Simpson calculation to avoid the strong impact of palms in the results and the autocorrelation of the Simpson index to A. murumuru abundance. A weaker relation between palm abundance and species composition of the understory was also observed where results res emble patterns of palm impact on overstory composition. A. murumuru abundance had a negative correlation to understory richness ( r = 0.6260, p < 0.05). The twodimensional DCA solution with Mazago, Ipixuna, Guam and the Almeida et al. data show a clear compositional separation of plots by region. These differences reflect the geographical distribution of the sampled regions (Figure 2 1 and Fig ure 2 7). Only five genera were present in all of the seven regions including Virola
32 (Myristicaceae), Inga (Mimosaceae) and Ficus (Moraceae). Neither the Euterpe or Astrocaryum genera, arguably the most abundant genera across the estuary, were present in all of the seven regions. When compared to Mazago and Ipixuna plots, the composition of the unlogged Guam plots were more similar to the composition of Mazago plots as shown by the two dimensional DCA solution (Figure 2 7). The first axis of the solution clearly divides each of the three areas while the second axis explains primarily compositional variation in Guam plots. The results from the DCA analysis were supported by the multi response permutation procedure (MRPP) that shows a clear significant compositional separation between the 3 sites ( p < 0.00001) and the smaller average Sorensen distance between Mazago and Guam plots compared to Ipixuna and Guam plots and Mazago and Ipixuna plots. Discussion Mixed Potential for Contrasting Forest Uses Although tidal floodplain forests have been commonly perceived as a homogenous forest type (Hiraoka 1992) these forests vary greatly in forest composition and structure between individual stands and subregions (Martin et al. 1992, Anderson et al. 1995) For the typical estuarine smallholder or riverine communit y, this local variability of forest composition results in widely differing potential for forest management (Table 2 4). The majority of the most important saw timber species used today ( Carapa guianensis Callycophyllum spruceanum, Mora paraensis and Pen taclethra macroloba) had noticeably higher abundances in Mazago compared to Ipixuna. Most of the other saw timber species had similarly low abundances for both regions. In terms of plywood production, neither site has good potential for plywood management given the low
33 abundance of plywood species ( e.g., Ceiba pentandra, Olmedia caloneura, Virola surinamensis Calophyllum brasiliense, Hura crepitans ), especially in the larger size classes. However, Mazago has a noticeably higher potential for management for seed oil production given its high abundances of Carapa guianensis and Pentaclethra macroloba, both important oil producing species that were practically absent from Ipixuna. All of the potential for management for seed oil in Ipixuna is related to a high density of A. murumuru palms, but although extraction of A. murumuru fruits was an important activity from the earlier part of the 20th century to the 1970s, it is currently not used due to lack of outside demand. Ipixuna only has a slightly higher management potential for fruit production having a greater abundance of Euterpe oleracea, Spondias mombin and Theobroma cacao. Smallholder s are well aware of local differences in forest composition and value land holdings according to local forest composition. Palm Dominance and Alternative Forest Uses One important variable in tidal floodplain forest composition is the degree of dominance of palm species. The dominance of palms in tidal floodplain varies from the monospecific palm stands to diverse forests w ith understory palms (Zarin et al. 2001) Our results show that sites with low palm abundance are more suitable for timber management. However, aa palm distribution is not related to observed variation in forest composition and structure, suggesting that tidal floodplain forests may be sustainably managed for both timber and aa production. This results is of special importance given that timber and aa are the two most important forest products for smallholders in the estuary, and is consistent with reports of extant sustainable dual production systems described by PinedoVasquez et al. (2001)
34 There is concern that the high price of aa palm fruit will gradually transform the tidal floodplain forests into aa dominated palm forests due to the preferential management of aa over other floodplain species (Brondizio et al. 1994, Brondizio and Siqueira 1997) Several studies show how the management for aa fruit production greatly increases the dominance of the palm often at the detriment to other species including timber (Anderson 1986, 1990, Brondizio 2004) In sites li ke Ipixuna where there are few other attractive forest based land uses, land holders are increasingly managing forests for aa production. In fact, land cover change analysis show an increase in palm forest area in Ipixuna between 1970s to 1990s (Zarin et al. 2001) Although palm forest areas have expanded in and around Mazago during the same period, today the diversity of livelihood strategies in Mazago reflect the potential for multiple forest uses including many family run sawmills. The relatively high potential for timber management in Mazago also is reflected in recent descriptions of sustainable management of tidal floodplain forests of Mazago, despite the past intensive logging boom that strongly impacted local forests from 19501980s (Pinedo Vasquez et al. 2001, PinedoVasquez and Rabelo 2002, Sears and PinedoVasquez 2004) Mazago has a recent logging history that dates back to the beginning of the 19th century when steam ships would purchase high valued species for export, through the logging boom of the 19501990s, through the current thriving smallholder dominated industry in Mazago. Ipixuna on the other hand had its modern period of timber extraction lasting from the opening of a small sized sawmill in the region in the 1950s until its closing in the 1980s and since then has increasingly focused on aa production.
35 Concluding remarks on Amazon Estuary composition variability Our results indicate that contrasting views of the management potential of Amazonian tidal floodplain forests may reflect not only heterogeneity of forest use by riverine peoples, but also the heterogeneity of the forests them selves. Indeed, the notion of a homogeneous tidal floodplain forest type is incompatible with the diversity of estuarine livelihood systems. The forest composition of sites similar to Mazago facilitates sustainable management for timber and other forest uses, whereas the current management potential for timber of areas similar to Ipixuna is low. Poor understanding of potential growth and yield of tidal floodplain species prevents us from understanding the current constraints of forest management and limits our ability to devise viable guidelines and policy interventions (Sears and Pinedo Vasquez 2004)
36 Table 21. Summary of structura l differences between Mazago and Ipixuna (Means per ha and SE) All trees Non palm species Timber species Large timber individuals a Overstory Density (ind/ ha) Mazago 1033 (94) 544 (35)* 285 (17)*** 104 (8)*** Ipixuna 1177 (206) 329 (69)* 116 (26)*** 51 (2)*** Basal area (m 2 /ha) Mazago 38.3 (1.3)* 33.7 (1.4)** 24.1 (1.6)** 20.4 (1.4)* Ipixuna 33.9 (1.5)* 25.8 (1.4)** 17.6 (1.1)** 16.2 (1.1)* Biomass (Mg/ha) Mazago 386 (12.9) 348 (16.7) 254 (17.6) 230 (16.4) Ipixuna 352 (13.7) 303 (16.3) 214 (17.3) 206 (18.1) Understory Density (1000 ind/ ha) Mazago 24.8 (6.2) 17.5 (4.0) 7.4 (1.2)** Ipixuna 29.3 (4.0) 11.9 (3.0) 2.4 (0.3)** a All commercial trees >30cm DBH. p < 0.05, ** p < 0.01, *** p < 0.001
37 Table 22. Summary of compositional differences between Mazago and Ipixuna (Means per ha and SE) Overstory Understory a Richness Mazago 51.4 (2.1)** 30.8 (3.1)* Ipixuna 36.4 (3)** 21 (1.8)* Simpson Mazago 2.59 (0.12)*** 2.31 (0.25) Ipixuna 1.77 (0.05)*** 1.76 (0.16) Evenness Mazago 0.66 (0.03)** 0.67 (0.06) Ipixuna 0.50 (0.01)** 0.58 (0.06) a Based on a 0.04 ha sampled area for each hectare plot. p < 0.05, ** p < 0.01, *** p < 0.001
38 Table 23. Indicator species analysis for Mazago and Ipixuna overstory data Mazago Ipixuna Species Indicator value P Species Indicator value p Combretum cacoucia 100 0.004 Chrysophyllum argenteum 100 0.004 Hevea brasiliensis 100 0.004 Chrysophyllum excelsum 100 0.004 Metrodorea flavida 100 0.004 Parinari excelsa 100 0.004 Mora paraensis 100 0.004 Calyptranthes speciosa 95.4 0.01 Pentaclethra macroloba 100 0.004 Spondias mombin 94.4 0.014 Pouteria sagotiana 100 0.004 Theobroma cacao 92.6 0.004 Pterocarpus amazonicus 100 0.004 Herrania mariae 85 0.019 Pterocarpus officinalis 100 0.004 Inga lentiscifolia 80 0.049 Quararibea guianensis 100 0.004 Astrocaryum murumuru 78.2 0.004 Sarcaulus brasiliensis 100 0.004 Swartzia cardiosperma 99.3 0.004 Carapa guianensis 99.1 0.004 Pachira aquatica 94.4 0.015 Tachigali paniculata 93.3 0.02 Alibertia sp. 80 0.049 Attalea phalerata 80 0.041 Dendrobangia boliviana 80 0.049 Matisia paraensis 80 0.041 Pouteria bilocularis 80 0.041 Zygia juruana 80 0.049
39 Table 24. Potential of alternate forest uses between Mazago and Ipixuna, Amap, Brazil Mazago Ipixuna Timber Sawnwood High Low Plywood Low Low Non timber Latex Medium Low Seed oils High High a Palms and other fruits High High a based on the high abundance of A. murumuru palm which is currently not utilized for oil production
40 Figure 21. Map of Amazon Estuary with location of forest inventory plots from current study (Mazago and Ipixuna), Pires and Koury (1959; Guam), and Almeida et al. (2004; Barcarena, Cajuuna, Chaves and Xing).
41 Figure 22. DBH distribution for harvestable species in Mazago and Ipixuna.
42 Figure 23. Species accumulation curves for overstory and understory of Mazago and Ipixuna sites.
43 Figure 24. DCA results for (a) overstory and (b) understory for Mazago and Ipixuna.
44 Figure 25. Individual species in DCA ordination space with respect to species characteristics.
45 Figure 26. Negative relationships between palm and nonpalm dominance T imber basal area versus palm basal area (A) and nonpalm basal area versus A. murumuru basal area (B).
46 Figure 27. Twodimensional DCA solution for overstory data (DBH > 10 cm) from Mazago, Ipixuna and Guam at the genus level.
47 CHAPTER 3 POPULATION DYNAMICS AND MANAGEMENT OF AM AZON TIDAL FLOODPLAI N FORESTS: LINKS TO THE PAST, PRESENT AND FUTURE Background Amazon tidal floodplain forests were among the first of the Amazon's resources to be exploited by Europeans and represent the oldest commercial logging frontier in the Amazon (Barros and Uhl 1995, Raffles 1999) Floodplain forests that today are classified as intact often hide a past of crop and cattle production and a long history of timber extraction (Hiraoka 1992, Denevan 1996, Raffles 1999, Roosevelt 1999) Until the mid 20th century, the post contact use of tidal forests for timber was a highly selective high grading of a handful of species for log exports (PinedoVasquez et al. 2001) Tidal forest timber harvests dramatically accelerated in pace and intensity from the 1950s until the 1990s when industrial scale plywood and sawmills consumed a large volume of tidal forest wood from a wilder selection of species (Palmer 1977, Browder 1989) As the supply of large highvalued trees decreased, these large estuarine mills were gradually replaced by small scale family run mills (Pinedo Vasquez et al. 2001) Today, thousands of families supplying hundreds of small scale timber operations rely on timber as a source of income (Lentini et al. 2005) by harvesting tidal floodplain manually, selectively, and without any fixed cutting cycle. Past research on estuarine timbe r production has documented cases of apparently sustainable forest use in the region (PinedoVasquez et al. 2001, Sears and Pinedo Vasquez 2004) while others have argued that timber resources are being depleted (Macedo and Anderson 1993, Barros and Uhl 1995) Given the long history of timber use in the Amazon Estuary, such retrospective analyses are necessary to better underst and the prospects of forest management. However, past assessments lack the
48 quantitative analyses of species ecology and demography that are crucial to accurately evaluate claims of ecological sustainability or resource depletion. Furthermore, the absence of tree demography data still prevents a shift towards ecologically based management after 300 years of unregulated timber extraction. In this study we evaluate whether the demography of tropical tidal floodplain trees is compatible with long term sustain able timber management, while considering the importance of past timber use in defining future prospects of forest management. We characterize species specific abundance, size class frequency distributions, spatial distributions, and recruitment, growth and mortality rates of timber species in tidal floodplain forests. We also employ matrix population models to explore the underlying population dynamics of common tidal floodplain species and explore the link between species population ecology and past, pres ent, and future timber use and availability In our analysis, we combine conventional tree demography methods with data from interviews with tidal floodplain C aboclos regarding land use and ecological knowledge. Methods Study Region We conducted our rese arch in the 160 sq km Mazago watershed at the western side of the Amazon estuary (Figure 3 1). The Mazago watershed has a long history of timber use (PinedoVasquez et al. 2001) with current small scale timber extraction as part of diverse livelihood strategies that often include palm fruit and timber harvesting, fishing, and cropping. Mazago is similar in composition and land use history to several adjacent watersheds, as confirmed by region wide inventories and surveys conducted in 2005 (Fortini et al. 2006) Mean annual temperature i s 27C and average daily temperature varies by less than 3C from month to month. Mean annual precipitation is
49 2550 mm and occurs mostly in the wet season months of January May. This part of the Amazon estuary is characterized by freshwater tidal fluctuati ons of 23 m. Tidal variations including daily, bimonthly, and equinoctial fluctuations, coupled with seasonal river level variations due to precipitation, result in a localized gradient of flooding that includes microsites flooded 12 times a year, 12 ti mes a day, or even constantly during the wet season. These high frequency flooding regimes shape community composition of these forests (Cattanio et al. 2002) and produce a dynamic forest landscape from rapid erosion and deposition ( Allison et al. 1995, Wittmann et al. 2004) Species Selection Based on interviews we conducted with owners of the estuarys family run logging operations and smallholders in 2003 2005, we chose 9 timber species that account for the majority of commercial volume extracted in the region in the past and present or that are expected to have timber value in the future (Table 3 1). Initially Olmedia calouneura, Symphonia globulifera, Cedrela odorata and Aspidosperma desmanthum were also selected but were later excluded due to small sample sizes. Based on five 1 ha plots, monitored species represent 47% of stand basal area and 53% of eudicot basal area. Cedrela odorata, Platymiscium filipes Car apa guianensis Olmedia caloneura and Virola surinamensis were extracted during the industrial scale logging boom that lasted from the 1950s until the 1990s (Pinedo Vasquez et al. 2001) Since then, Callycophyllum spruceanum, Carapa guianensis, Virola surinamensis, and Licaria mahuba have been the primary species utilized by smallholder saw mills spread across the region. Mora paraensis a species with highdensity wood, has only been harvested
50 at commercial levels by caboclo smallholders in the last decade because its heavy weight and low buoyancy make ground and water transport difficult. Permanent Inventory Plots Species demography in recently undisturbed forest was estimated from 3 largescale 360 x 360 m plots (13 ha per plot, 39 ha total; unharvested plots hereafter ) established and monitored yearly from 2005 to 2008. We measured all tree s 5 cm DBH in the 200 x 200 m core area of each large plot. Only tree s 30 cm DBH were measured in the remaining area. Additionally, we measured all tree s 5 cm DBH in five 1ha plots first measured in 1997 yearly from 2004 to 2007. We selected areas indicat ed by land use history surveys to have had no or very low intensity extraction in the recent 20year past. To be broadly representative of forest stands elsewhere in the Amazon Estuary, our intent was to find stands that have a continual history of timber use but would likely not be under recent post harvest effects (Silva et al. 1995, Boot and Gullison 1995, Finegan and Camacho 1999) For all measured trees in our unharvested plots we collected information on individual and environmental factors that could influence demography including flooding and light regime (Table 3 2). Commercial height ( i.e., height of crown base) was estimated using a vertical hypsometer and ocular estimates frequently calibrated by hypsometer measurements. Study trees were tagged at 1.2m height or 50 cm above buttressing and stem defects, with tag height recorded. Annual tree measurements consisted of 2 diameter measurements 10 cm above and below tag height. The short distance between measurements allowed for measurement comparisons that improved data quality. Tree diameter increments were calculated using the average increment at both measurement heights. Additionally, in 2007 a random subset (approx. 5%) of all
51 trees was re measured to evaluate measurement error, yielding a typical 01 mm error e stimate that rarely exceeded 2 mm. A 5 m collapsible aluminum ladder was used for all inventories due to the high level of buttressing of many floodplain trees (Parolin et al. 2004) All tree s with buttresses or defects extending above 6 m had diameter at breast heights (1.3 m; hereafter DBH) estimated. These estimates were not used for diameter increment calculations, but were still useful for diameter distribution and survival estimates. Field tests showed diameter estimates consistently within 5 cm from actual size due to the field crew's familiarity with size estimation used for selling and purchasing of logs. Evaluation of Timber Use History W e used a combination of unstructured interviews along with structured surveys with sorting and participatory mapping exercises to evaluate the extent and intensity of past timber extraction in the watershed, changes in forest structure and composition due to past extraction, and the extent of local knowledge of timber species ecology and distribution. Approximately 30 participants were included in these activities; all were longtime residents that witnessed and directly participated in the extraction of ti mber resources since the 1970s. We used a snowball sampling approach for participant selection. Analysis All inventory data were stored in a single database where for each tree, annual measurements were preceded by columns specifying measurement quality ( Table 3 3). This eased processing large amounts of individual tree data for multiple analytical purposes. The developed matrix model creation and analysis routines can be applied to similar datasets and are available by the author upon request.
52 DBH estimat es One known consequence of flooding is the high incidence of buttress formation in trees (Parolin 2002) This results in the absence of direct DBH measurements for a large portion of tree s > 30 cm DBH. To obtain a DBH estimate for these tree s, we extrapolated taper derived from all pairs of diameter measurements spaced 20 cm apart. To avoid using individual taper which varied from tree to tree (and was sometimes negative for the measured stem section), we employed a multiple linear regression appr oach to model taper as a function of tree diameter and height of measurement by species. If the model used for a given species resulted in poor fit, we used generic coefficients from all species combined. We then used this species specific taper mode to ex trapolate diameter from measured height to breast height (1.3 m). Although this method ignores the Neiloid shape of lower stem sections (Husch et al. 1972) extrapolated distances were mostly less than 1 m. After generating DBH estimates for all tree s, we used field data to model species specific commercial height / DBH relationship using a power function (Eq. 31). Height b DBHa 3 1 F or species with height models not statistically significant a general model using all species was used. Significant parameter estimates varied widely among species (mean a = 0.43 sd = 0.31; mean b = 4.62 sd = 3.78). Estimating commercial volumes Since t here were no species specific bole volume equations for all our study species, we used a commercial stem volume equation derived in Mazago for C. spruceanum to all of our study species (Eq. 32; Applegate et al. 2000).
53 Commercial stem volume 1.93 10 4 DBH1.665 Height0.973 3 2 Using a limited field derived diameter and stem volume data set (Johnson 1999) we compared the quality of the fit of the above equation to other generic Amazon derived bole volume equations (Brazil 1978, Ribeiro 1996) Given the similarity in form of floodplain trees, the C. spruceanu m equation showed a better fit to the field data. Create population models for species or species groups To evaluate the population dynamics of the study species, we created matrix models based on lower level vital rates (Table 3 4, Morris and Doak, 2002). All species specific matrix models are based on modeled tree growth, survival, and recruitment as described below. For maximum analytical flexibility, matrix model creation, subsequent projection, and analysis routines were all directly linked to the inventory database. This approach allowed for flexible outputs based on user specified DBH size classes, plot selec tion, species subselection or grouping, and multi year and cross year averaging and bootstrapping. Modeling diameter increments and matrix transition probabilities To determine the probability of up growth from one size class to another we first used an increment estimator approach based on the mean increment distance from the upper size class boundary, appropriate for small sample sizes (Picard et al. 2007) However, to avoid over parsing the data into a limited number of size classes, we opted for modeling diameter increment ( DBH) by tree size (DBH) using the Hossfeld IV equation (Eq. 3 3; Zeide 1993, Zuidema and Boot 2002) Comparison of same sized matrices derived from parsing tree dat a into individual size classes and our equation based methods yielded nearly identical results.
54 DBH b c DBHc 1 b DBHc/ a 2 3 3 Beside using increment data for matrix model parameterization, we used this information along with auxiliary data collected for each tree including estimated flooding regime, vine loading, and light regimes in ANOVA and standard least square models to evaluate the influence of these factors on diameter increments. Flooding effects were not evaluated for C. spruceanum and P. filipes because they had few tree s in the 0.05. Marginal significance was defined as 0.10 Modeling survival For all species and years of interest, we estimated size class survival using a binomial logistic fit (Morris and Doak 2002) The derived mortality function was then evaluated at the median observed size for each size class for each species/ year combination. If the logistical fit was not statistically significant, the matrix creation routine uses standard mortality rates calculated across all individuals (i.e., proportion of tree s surviving a given time interval). In few species/ yr combinations, low mortality rates and numbers of trees resulted in the survival of all individuals. In these cases, the matrix creation routine used generic mortality rates curves derived from grouping all species combined for the same time period. Lastly, if calculating survival rates for intervals > 1 year, the matrix creation routine discounted rates to a yearly rate using a simple rate discounting function. Estimating recruitment and modeling fertility Fertility estimates were based on observed recruitment to the smallest size class (5 cm DBH) observed yearly at permanent inventory plots Fertility was distributed
55 among size classes using Caswells (2001) approach to calculate anonymous fertility rates. Fertility was distributed among size classes using the r eproductive weight of individuals per size class calculated as relative individual reproductive output times proportion of reproductive individuals in each size class. While size is likely to influence reproductive output, the relationship is likely not linear due to increased respiratory costs with increasing tree sizes (Mencuccini et al. 2005) On the other hand, light limitation is likely an important threshold to reproductive output (Svenning 2002) To calculate relative reproductive output we devised a combined approach where the si ze class of full reproductive output is assumed to be reached when most tree s reach full crown illumination (based on data gathered for each tree). Trees in this or larger size classes have full reproductive weight, whereas smaller size classes have relati ve reproductive output based on relative size compared to the size of the first full reproducing size class. To estimate the proportion of reproductive individuals for any given size class, in 2007 we employed a local expert to evaluate each tree growing in PIP plots for their potential to flower and reproduce. The matrix creation routine uses this data in a logistic regression by chosen species or species group to estimate the proportion of reproducing individuals by size class. Using this modified anonymous fertility approach, size at first reproduction was > 20 cm for all species. To avoid problems associated with reducible matrices (Caswell 2001) in the instances we did not observe recruitment for a species group and time interval, we used recruitment values observed between 1997 and 2005 at the five 1 ha plots, discounted for annual mortality rates. Preliminary comparisons showed that while this adhoc
56 reducibility fixed avoided erroneous right and left eigenvectors, it had only minor effects on estimates of population vital rates and population growth. Exploring tree populat ion demography with matrix models (Cochran and Ellner 1992, Caswell 2001) to explore the demography of tidal floodplain timber species To avoid inflationary effects from small matrices (Zuidema et al. 2010) most size classes were set 2 cm wide. This value was the minimum width above maximum yearly individual growth during the entire study period. Model results were consolidated into larger size classes to aid in interpretation. We excluded temporal growth autocorrelation from our models after preliminary model projections deemed its effect negligible (Brienen et al. 2006) A dditionally, we calculated population growth sensitivity to logged individuals and logged volume by expanding on the formula for sensitivity of population growth rates to si ze class survival rates (Eq. 3 4 ; Morris and Doak 2002). sj aij j 1 saijsj i 1 s 3 4 Sensitivity of to volume of individuals harvested from a given sizeclass can be estimated based on a simple expansi on using the chain rule (Eq. 3 5 ). mj 3 aij j 1 saijsj sjIj Ijmj 3 i 1 s 3 5 size class to the additional death (e.g., harvest) of an individual of the same size class; and 3 represents the ratio of individuals by cubic meter of wood. This approach can help find harvest strategies that
57 avoid depleting all large trees that typi cally have large contributions to population growth but relatively low densities (Zuidema and Zagt 2000) Results Diameter Distributions Mora paraensis L. heteromorpha, and P. sagotiana have clear inverseJ diameter distributions that seem to reflect their shade tolerant recruitment (Figure 3 2). These same species, along with C. spruceanum were represented by larger trees than the remaining species. Carapa guianensis V. surinamensis L. mahuba had more even diameter distributions, while P. filipes and C. spruceanum had unimodal size distributions with peaks around 3545 cm DBH. Only M. paraensis and C. spruceanum had densities of harvestable t rees > 1 tree/ha (15.7 and 1.5, respectively). Mora paraensis was more than twice as abundant as all other harvestable study species combined. DBH height model results yielded good results for most study species. Resulting fits were used to improve the est imates of tree commercial volume. Harvestable volume for all trees > 50 cm DBH was 64.6 m3 ha1, 51 m3 ha1 of which was from M. paraensis Because monitored tree s were growing in relatively undisturbed stands, we examined diameter distributions for indications of shade tolerance species groups (Hartshorn 1980, Swaine and Whitmore 1988) While the resulting groups were compatible with traditional ecological data collected in assessment of local ecological data, we opted not to group species while modeling (Grubb 1977) because species in each shade tolerance group differed in sizeclass specific growth and survival patterns (Grubb 1977)
58 Diameter Increment Analysis Mean and median diameter tree growth for all species across the 3 measurement intervals was 0.32 and 0.25 cm/yr respectively Except for 60 74.9 cm V. surinamensis mean diameter tree growth for all species across all size classes was < 1 cm/yr (Figure 3 3). Tree growth was most often < 5 mm/yr for most tree s measured. Mora paraensis C. spruceanum, and L. mahuba had the lowest mean diameter tree growth. Licani a heteromorpha, C. guianensis P. sagotiana, P. filipes showed intermediate rates. Virola surinamensis had clearly higher tree growth rates than all other study species. Mora paraensis L. mahuba, and C. spruceanum showed slow tree growth throughout thei r size ranges, with small differences between maximum and mean tree growth. All other species showed varied tree growth patterns across size classes with maximum increment generally following the same patterns as mean tree growth, except when small sample sizes clearly influenced outcomes (typically the largest size classes with few measured tree s). While some species exhibited decreasing diameter increments within the largest size classes, this did not lead to zero or negative tree growth for any of the species. In contrast, C. guianensis and V. surinamensis showed increasing mean tree growth as tree s reached maximum sizes. These increment patterns could be indicative that larger observed tree s of these species do not represent the largest possible sizes due perhaps to past episodes of selective logging. Callycophyllum spruceanum shows near zero tree growth in the smallest size class, possibly reflecting its limited success under a shaded canopy. Licania heteromorpha and P. sagotiana showed optimum tree growth in middle size classes with growth rates declining in smaller and larger trees. Species of similar shade tolerance, as estimated
59 by size class frequency distributions, did not show similar diameter increment patterns across size classes. Tree Growth Determinants Neither forest type nor vine load affected growth rates, but trees suffering high vine loads or growing in gaps were uncommon. Additionally, plot effects modeled as random effects were not significant for any species, meaning that tree growth variation observed is not explained by plot locations. In contrast, both flooding and light clearly affected tree growth rates. Tree growth for all species except L. mahuba increased at least m arginal ly with increased crown exposure. Flooding had at least a marginally significant negative effect on growth for M. paraensis L. heretomorpha, C. guianensis and V. surinamensis Although these results show the link between tree growth, and crown expo sure and flooding regimes, these two factors combined explained only about 7 to 25 % of the variation within study species. Survival and Recruitment Estimates Survival rates across all size classes varied little for all species during the study period, w ith values between 0.980 and 0.993, and 0.988 when averaged across all species and years No clear pattern of decreasing mortality with size class was observed for any species or species groups. Given the small range of survival rates and the apparently st ochastic nature of mortality events, small differences among species are not easily interpretable. There was an average of 0.006 new recruits per standing tree per year into the 5 cm diameter size class during the study period. Recruitment per area of M. paraensis was higher than all other study species combined (Table 3 5). Callycophyllum spruceanum L. mahuba and P. sagotiana showed average recruitment rates < 3 tree s
60 per 100 ha per yr for the entire measurement period. Considering recruitment relative to population size, recruitment rates for most species was between 0.52% per year. Although P. filipes had a markedly higher recruitment rate (6%), this only translates to approximately 13 tree s recruited per 100 ha per year given low population densities We evaluated the sensitivity of matrix models to the choice of fertility calculation method (conventional fertility spread evenly across size classes and our modified method) and llumination proportion and reproductive proportion, both used to scale fertility across size classes and calculated from local ecological knowledge, show ed clear size related logistical patterns (Fig ures 3 4 and 3 5). Evaluation of Timber Use History Participatory mapping and surveys reveal that no forests in the Mazago watershed (and surrounding regions) have escaped logging over the past 6 0 years. Similar to other Amazon tributaries, the mouth of the Mazago river is where past landowners enforced t rade of products from upstream residents for outside goods at the barraco (trading post; Raffles 1997) Besides agric ultural products, rubber and other nontimber forest products, highvalue logs from species such as C. odorata always figured prominently in the list of local products traded. Starting approximately in the 195060s, the volume of timber extraction increased as large ships bound to farther markets docked at the Mazago trade post and purchased large volumes of highquality P. filipes and C. guianensis logs. Allegedly to make use of lower grade logs, a medium sized band sawmill was installed at the location, all the while large rafts of C. guianensis and V. surinamensis logs floated downstream during high tides to the large but short lived sawand plywood mills near the state capital. After their demise due to lack of
61 continuous timber supply for their high c apacity operations, along with the failure of the Mazago sawmill, several small scale circular sawmills began to dot the estuary (Barros and Uhl 1995, PinedoVasquez et al. 2001) with the number of such mills in the Mazago watershed varying from 612 at any given time since then. Nearly all longterm residents were involved in this history of timber use and recall the extraction of markedly larger logs than maximum tree sizes observed today for several species with long timber use history including C. guianensis V. surinamensis P. filipes, and C. odorata. Independent ranking exercises show that these were the species with most volume harvested in the region excluding C. odorata, which was ranked as one of the least abundant species approximately 40 years ago. Contrary to results from long used species, maximum recalled harvested log sizes for M. paraensis and C. spruceanum were within the range of maximum tree sizes observed within and outside inventory plots. As partial cross validation of results, the ranks of study species by recruitment rates offered by local participants differed little from plotderived results. Locals also correctly ranked V. surinamensis as the fastest growing species, but were not as accurate in ranking tree growth rates of most other species. Matrix Model Outputs Population growth estimates Most species displayed bias corrected bootstrapped confidence intervals including 1 across the 4year measurement period, indicating the possibility that these populations are stable over longer time intervals (Fig ure 3 6). Only the fast growing V. surinamensis and C. guianensis for 20072008, while both L. mahuba and C. spruceanum significantly below 1, indicating potential
62 population declines Population growth rates seemed to increase during the last measurement interval of 20072008. Given the likely stochasticity of recruitment events and their potential consequences to modeled population dynamics, we devised a simulatedannealinglike search algorithm to find the recruitment r each iteration, the search window narrowed until the calculated was within 109 of 1. Although the absolute differences between observed and stable population recruitment rates were small for all species, proportionally these differences were very large for L. heteromorpha, C. spruceanum and L. mahuba (Table 3 5). For these populations, poisson distribution tests show that measured recruitment rates are unlikely statistically different from stable population r ecruitment rates. Stable stage distributions and r eproductive values The observed diameter distributions of species least harvested in the past follow those derived from stable stage distributions ( M. paraensis L. heteromorpha, and P. sagotiana; Fig ure 3 7). All other species show some form of deviation between actual and stable state distributions. For several species, this discrepancy was largest for the larger sized classes. Callycophyllum spruceanum and L. mahuba showed strongly bimodal stable stage distributions that were likely a result of nearly no observed recruitment and resulting population decline. Platymiscium filipes also showed large discrepancies between actual and stable state distributions, but it is not clear why. For all species but M. paraensis maximum reproductive values are reached between 34 and 44 cm DBH and remain high until maximum size. Mora paraensis shows the same
63 pattern of increasing reproductive value with size, but only reaching a peak at the 54 cm DBH. Population growth sensitivities and elasticities Computed elasticity matrices show the typical pattern of longlived, slowgrowing species where is most se nsitive to stasis probabilities; However, most species show gradual ly decreasing sensitivity to stasis probabilities w ith increasing size, excluding the stasis probabilities of the largest size classes that were clearly important for most study species. The analysis of population growth sensitivity to underlying vital rates showed this pattern was due to the overwhelming influence of survival to population growth, which followed a similar size related pattern as described above. Survival of large tree s was a strong determinant of C. spruceanum and L. mahuba recruitment, the rate of population decline of these two species is strongly dependent on the persistence of large tree s. In contrast, M. paraensis L. heteromorpha and P. filipes survival of the smallest size classes T ree diameter contribution of Population growth sensitivity to harvested individuals and volume For all species except P. filipes harvest of larger individuals is expected to cause the largest drop s in s. Depending on the underlying vital rates and observed diameter distributions, these adult harvest effects substantially influence s for M. paraensis C. spruceanum and C. guianensis For other species such as L. heteromorpha, P. sagotiana, and P. filipes the greatest potential harvest effects were observed for multiple large size classes. The sensitivity of population growth to volume extrac ted by size class yielded similar results; However, these results are only valid for the current diameter
64 distribution because they are based on the contribution of an individual relative to the total number of individuals in a given size class. Stable age distributions Stable age distributions indicative of tree age at each sizeclass, varied widely among species ( Figure 3 8 ). The median time needed to reach the stable age of individuals in the first harvestable class was as low as 67 years for V. surinamensis and as high as 190 years for C. spruceanum Mora paraensis displayed a relatively high value of 143 years. Median stable age of largest observed size class varied even more, with low values for V. surinamensis ( 95 years) and C. spruceanum w ith median stable age at full maturity of 480 years. However, these values are not easily comparable because species had differing maximum sizes. Discussion Species Distribution and Densities Although varzea low species richness has been commonly associ ated with more abundant species (Wittmann et al. 2006) most study species showed low abundances similar to those of upland species (Pitman et al. 2001, Schulze et al. 2008) Commercial timber volume of the forests inventoried was al so similar to those from upland tropical forest sites (Verissimo et al. 1992, Barreto et al. 1998, Sist et al. 1998) Most of this volume was attributed to M. paraensis and does not account for stem defects and volume wasted in harvests (Valle et al. 2007) T he extent to which current population distributions have been influenced by prior harvests cannot be precisely determined, but timber use surveys and calculat ed stable stage distributions together yield some clues about the past. Comparisons between stable stage distributions and measured proportional size distributions suggest a larger
65 number of harvest sized tree s for most species would be present under unlog ged conditions (e.g., C. guianensis V. surinamensis ). Moreover, local surveys indicate that the maximum log size of longused timber species has decreased over the past decades. Because models cannot project or estimate the size distribution beyond currently observed sizes, stable stage distributions may underestimate actual shifts in population structure. Except for M. paraensis the current size distributions and population densities of all Mazago timber species constrain the management potential of small landholdings by limiting per area yields and requiring time for recovery that often cannot be afforded by resident smallholders (Pinedo Vasquez et al. 2001) Tidal Floodplain Tree Demography and Dynamics It has been hypothesized that high soil fertility of floodplains could lead to more rapid tree growth rates than in upland forests (Kvist and Nebel 2001) In fact, averaging across all species and sizes, the 0.32 cm/yr diameter tree growth is over 50% higher than the Amazonwide upland forest conservative estimate of 0. 140.2 cm/yr by Da Silva et al. (2002) but is still below rates from plantation and actively managed stands I n seasonal floodplain forests strong tree growth periodicity leads to cambium dormancy (Schongart et al. 2002) but although we did not measure withinyear tree growth variability, the lack of deciduousness and no clear growth ring formation on nearly all species suggest most tidal floodplain trees have year round tree growth (Brienen and Zuidema 2005) Nonetheless, most study species presented a negative growth response to flooding, reinforc ing the idea of tolerance, and not specialization strategies, to flooding stress (Kozlowski 1984) While these results show flooding affects tree growth, these effects are hard to incorporate into management because they are not easily altered and are related to
66 topographical variation occurring at microsite scales due to the numerous and far reaching natural drainage canals present in tidal stands. However light availability showed a stronger and more consistent effect across study species, and is a stand quality that can be managed through thinning (Guariguata 1999, Dolanc et al. 2003) low sensitivity to tree growth and high sensitivity to survival indicate attempts to increase tree growth (such as improving light regime though thinning) may increase yield but will offer limited improvements to sustainability of harvesting regimes compared to management prescriptions that reduce mortality (e.g., reduction of residual stand damage). Nevertheless the fact that the importance of tree growth to population s was highly concentrated in the smaller size classes of all studied spec ies make it a potential target for management intervention. Given observed diameter tree growth, tree age estimates were within the published longevity estimates of 500 years or less with the light wood species V. surinamensis showing considerably shorter longevit y (Worbes et al. 1992, Br ienen and Zuidema 2006, Schongart 2008) Species variability in median age of the first harvestable size class (50 cm) illustrates the challenge to the current use of single harvest rotation cycles in tropical forest management (Schongart 2008) The unexpectedly high stable age estimate for C. spruceanum is likely due to its lowest diameter growth among all study species a surprising result for a pioneer species that suggests its limited success in closedcanopy mature forests with small gaps While the m easured tree survival rates are on the intermediate range of published values for other Amazonian sites (Lieberman and Lieberman 1987, Schulze and Zweede 2006, Sist and Ferreira 2007, Swaine et al. 1987) the high sensitivity of
67 to survival bodes well for tidal floodplain timber harvests given low residual stand damage ( Chapter 4). Unfortunately, because the relative importance of adult and are unlikely to be effective across species. Recruitment rates into the 5 cm diameter class were also low for most species (Condit et al. 1999) and for all species combined represented only 74% of mortality over the 3year study period. Similarly low recruitment rates from o lder (albeit smaller) plots and local survey ranking results indicate these low recruitment rates are not the result of temporal/stochastic variability. Relatively high M. paraensis recruitment is likely enhanced by the abundant advance regeneration stock commonly present in these forests (Rabelo 1999) The proportion of tree s likely to reproduce by size class calculated from local ecological knowl edge assessments showed a clear sizerelated logistical pattern that seems to reflect underlying reproductive biology (Read et al. 2006, Naito et al. 2008) These results suggest this approach may also be a good alternative to weighing anonymous tree fertility data when no other reproductive data are available. Population Ecology and the Past and Future of Forest Use and Management Considering the population ecology of the study species collected from inventory and survey assessments, the long legacy of forest use in the tidal floodplain forests clearly will influence the future of forest use and management. According to social surveys, M. paraensis was already the dominant species prior to most timber extraction in the region. Due to difficulties in transport, M. paraensis was historically harvested at only low levels and for that has lik ely benefited from past timber use by reduced canopy competition and enhanced recruitment ( Chapter 4) The fact that most other species showed markedly lower recruitment rates and that M. paraensis
68 commonly dominates the forest understory with advance regeneration also suggest that this species was better positioned to make use of small logging gaps (Rabelo 1999) Today, compared to most other timber species studied, the abundance and inverseJ population distribution of M. paraensis makes it a species potentially fit for management (Schulze et al. 2005, 2008) In comparison, for species like C. spruceanum and C. odorata, which inventory and survey data indicate as light demanding pioneer species, recruitment limitation is likely not overcome by small selective harvest gaps (Chapter 4) The fact that C. spruceanum trees are usually found in size cohorts lend support to this idea and suggest that large disturbances such as c hanging geomorphology, large blowdowns and ironically, ancient clearings and intense timber harvests likely contributed to the species success (Nelson et al. 1994, Condit et al. 1998) Cedrela odorata has the unfortunate distinction of having very low natural densities, resulting in a combination of traits that led to its near population collapse in the studied watershed. Concluding remarks on Amazon Estuary tree population ecology At first glance, tidal floodplain forests offer challenges to management similar to those seen in tropical forests elsewhere: low recruitment tree growth rates that are often species specific (Dauber et al. 2005, Rondon et al. 2009) combined with variable population densities and size distributions (Schongart 2008, Schulze et al. 2008) The long historical timber use in the region also limits the opportunity for small scale management of several species that have declined in abundance over decades of low intensity extraction. Management of these and other species that occur at low densi ties will likely require efforts that cross smallholder property boundaries a prospect that likely entails its own set of challenges different from largescale timber management operations or management of community owned land. Like most other tropical forest
69 studies evaluating the ecological constraints on forest use and management (Dauber et al. 2005, Gourlet Fleury et al. 2005, Brienen and Zuidema 2007, Valle et al. 2007, Grogan et al. 2008, Rondon et al. 2009) these results are not encouraging. Nevertheless a full ecological evaluation should consider the potentially large effects of selective harvests and silvicultural treatments on tree growth and recruitment (Silva et al. 1995) While timb er extraction in the estuary has endured centuries, our results suggest longterm timber use does not necessarily entail sustainability. For the Mazago watershed, its long timber use history has meant a gradual process of resource depletion due to the sequential removal of preferable timber species over time. If current practices are left unchanged, the prospects for longterm management are likely to decrease further as the densities of trees fall to levels that make management economically unattractive at smallholder scales. Fortunately, in Mazago's case, the abundant presence of Mora paraensis may still provide the opportunity for sustained timber management while historically depleted species with strong recovery potential (e.g. Virola surinamensis Ca rapa guianensis ) can regenerate. These results contrast with recent optimistic studies that emphasize the potential of agroforestry projects in the estuary (Sears and PinedoVasquez 2004, Sears et al. 2007b) While such agroforestry projects are not a substantial component of the current estuarine timber economy, they should be c onsidered as potential ingredients for a strategy to ensure recovery of historically degraded forests.
70 Table 31. Study species. Family Species Local name Fabaceae Mora paraensis Pracuba Chrysobalanaceae Licania heteromorpha Macucu Rubiaceae Callycophyllum spruceanum Pau mulato Meliaceae Carapa guianensis Aubl. Andiroba Myristicaceae Virola surinamensis Virola Lauraceae Licaria mahuba Maba Sapotaceae Pouteria sagotiana Maaranduba Fabaceae Platymiscium filipes Macacaba
71 Table 32. Auxiliary information collected for inventory trees. Forest type Tree stature Crown Damage Stem damage Crown illumination Vineload Flooding regime (using local typology) At least one main branch broken but canopy > 50% intact High: visibly affecting individual performance High lateral light but overhead shade; partial overhead light; partial overhead and substantial lateral light Substantial vineload but canopy not significantly shaded by vine canopy Full overhead light; full overhead and lateral light Canopy heavily infested by vines and substantial shading occuring
72 Table 33. Categories of measurement quality for model data use Tree data used for Year tree status Diameter measured x x Diameter estimated x Circumference at BH estimated x Not 'born' yet Dead x Errordiscard high measurement x x diameter distribution and survival diameter increment Table 34. Matrix projection model based on underlying vital rates. Szcl 1 t+1 Szcl 2 t+1 Szcl 3 t+1 Szcl 4 t+1 Szcl 5 t+1 Szcl 6 t+1 Szcl 7 t+1 Szcl 1 t s 1 *(1-g 1 ) + F 1 F 2 F 3 F 4 F 5 F 6 F 7 Szcl 2 t s 1 *g 1 s 2 *(1-g 2 ) Szcl 3 t s 2 *g 2 s 3 *(1-g 3 ) Szcl 4 t s 3 *g 3 s 4 *(1-g 4 ) Szcl 5 t s 4 *g 4 s 5 *(1-g 5 ) Szcl 6 t s 5 *g 5 s 6 *(1-g 6 ) Szcl 7 t s 6 *g 6 s 7 s 1 survival for size class 1; g 1 transition probability of size class 1; F 1 fertility rate for size class 1
73 Table 35. Actual vs stable population yearly recruitment rates
74 Figure 31. Study region
75 Figure 32. Diameter distribution for studied species. Vertical dashed line indicates legal harvest size 20 40 60 2 4 6 8 1 2 3 4 5 10 15 Individuals per ha 2 4 6 8 1 2 3 4 1 2 3 4 5-19.9 20-34.9 35-49.9 50-64.9 65-79.9 80-94.9 >=95 0 1 2 DBH Mora paraensis Licania heteromorpha Pouteria sagotiana Carapa guianensis Virola surinamensis Licaria mahuba Callycophyllum spruceanum Platymiscium filipes
76 Figure 33. Median and maximum diameter increments. Vertical dashed line indicates legal harvest size 0.5 1 1.5 2 0.5 1 1.5 2 0.5 1 1.5 2 0.5 1 1.5 2 Increment (cm/yr) 0.5 1 1.5 2 0.5 1 1.5 2 0.5 1 1.5 2 5-19.9 20-34.9 35-49.9 50-64.9 65-79.9 80-94.9 >=95 0 1 2 DBH Median increment Max increment Mora paraensis Licania heteromorpha Pouteria sagotiana Carapa guianensis Virola surinamensis Licaria mahuba Callycophyllum spruceanum Platymiscium filipes
77 Figure 34. Proportion of trees under full light Figure 35. Proportion of reproductive tree s 0 0.2 0.4 0.6 0.8 1 5-19.9 20-34.9 35-49.9 50-64.9 65-79.9 80-94.9 >=95 DBH Prop. of indiv. under full light 0 0.2 0.4 0.6 0.8 1 5-19.9 20-34.9 35-49.9 50-64.9 65-79.9 80-94.9 >=95 DBH Prop. of reproductive indiv.
78 Figure 36. Population growth estimates for studied species by year with 95% confidence intervals
79 Figure 37. Observed vs stable state diameter distributions Vertical dashed line indicates legal harvest size
80 Figure 38. Median age at stable state distribution
81 CHAPTER 4 PROSPECTS FOR CONTINUED TIMBER PRO DUCTION IN AMAZONIAN TIDAL FLOODPLAIN FORESTS Background One underlying tenet of sustainable forest management (SFM) is that forests should provide for multiple needs continuously into the future (Wang 2004) For remote tropical areas where timber is a main product, sustainable timber management (STM) to ensure yields harvest after harvest should be an important component of SF M ( Seydack 1995; Zari n et al. 2007 but see Luckert and Williamson 2005). While models have been applied to addr ess the ecological viability of STM (Vanc lay 1995, Kammesheidt et al. 2001, Glauner et al. 2003, Phillips et al. 2004, Gourlet Fleury et al. 2005, Valle et al. 2007) most research has instead focused on the evaluation of harvest damage, post harvest effects on growth, recruitment and mortalit y alone (Fredericksen and Mostacedo 2000, Chapman and Chapman 1997, Finegan and Camacho 1999) W ithout integrating these population demography responses, however, net population effects of timber harvest and management remain unclear. Exceptions aside (Huth et al. 2005) the majority of research to date has focused on evaluating current practices instead of searching for alternate sustainable management regimes relevant to concerned forest managers and legislators In the Amazon, the majority of STM related research has resulted in discouraging prospects for both SFM and STM (Dauber et al. 2005, Gourlet Fleury et al 2005, Brienen and Zuidema 2007, Valle et al. 2007, Grogan et al. 2008, Rondon et al. 2009) but see Phillips et al. 2004) Nevertheless for the Amazon estuary, the oldest logging frontier in the region, lack of relevant research is a glaring omission. After centuries of disturbance, the resilience of these forests indicates a potential for sustainable timber
82 management (Raffles 1997) This potential is further bolstered by a n abundance of timber relatively fertile soil, and lo w cost/ low damage of water transport (Anderson 1990, Zarin et al. 1998) In relation to timber harvesting in Amazonian upland forests, floodplain forest operations have lower negative environmental impacts due to the lack of heavy machinery use and the reliance on river transportation that precludes road construction and eventual deforestation (Kaimowitz and Angelsen 1998, Laurance 2001) Additionally, the dangerous firefeedback mechanisms that often hinder the recovery of upland forests following logging are absent in floodplain forests (Nepstad et al. 1999, Gerwing 2002, Cochrane and Laurance 2002) While recent research explores the population ecology of timber species and its link to centuries of selective logging in the region (Chapter 2 and 3) it remains unclear to what extent tidal floodplain tree demography and past use affect the prospects for STM and SFM A t present, timber remains an important resource for subsistence and income generation for many smallholder caboclo families in the Amazon Estuary. Hundreds of small scale, family run timber operations supplied by many more thousands of smallholders rely on timber as a source of income (Barros and Uhl 1995, Lentini et al. 2005) While past research into these small scale production systems have characterized caboclo timber use as either sustainable (PinedoVasquez et al. 2001, Sears and PinedoVasquez 2004) or unsustainable (Macedo and Anderson 1993) Attention to how demography dictates the possibility of recovery after management interventions has been lacking. In this study we used a matrix based harvest simulation model to evaluate the prospects for sustained timber production in the Amaz on estuary Based on a wide
83 range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the population and yield outcomes of hundreds of longterm timber management scenarios. These results were then compared using simple quantitative indicators of STM to find optimal standlevel and species specific sustainable timber management regimes relevant to similar forests in the Amazon Estuary. Methods Study Region We conducted our research in the 160 km2 Mazago watershed at the Western side of the Amazon estuary (Figure 4 1). This area has a long history of timber use (PinedoVasquez et al. 2001) with current small scale timber extraction as part of diverse livelihood strategies that often also include palm fruit harvesting, fishing, and smallscale agriculture. Despite great compositional and structural variability across Amazon tidal floodplain forests, Mazago is similar in composition and land use history to several adjacent wat ersheds, as confirmed by regionwide inventories and surveys conducted in 2005 (chapter 3, Fortini et al. 2006) Mean annual temperature is 27C and average daily temperature varies monthly by < 3 C. Mean annual precipitation is 2550 mm and fa lls mostly in January May. This part of the Amazon estuary is characterized by freshwater tidal fluctuations of 23 m. Field data were collected primarily from recently undisturbed forests (forests with little or no sign of recent timber harvests but with a long history of multiple use including harvests) and recently logged forests.
84 Species Selection We chose 9 timber species that account for the majority of commercial volume extracted in the region over the past century as well as species that are likely to have timber value in the future (Table 4 1). Olmedia calouneura, Symphonia globulifera, Cedrela odorata, and Aspidosperma desmanthum were initially selected but were later excluded because there were < 50 tree s inventoried per species. Cedrela odorat a Platymiscium filipes Carapa guianensis Olmedia caloneura and Virola surinamensis were extracted during the industrial scale logging boom that lasted from the 1950s until the 1990s (Pinedo Vasquez et al. 2001) Since then, Callycophyllum spruceanum, C guianensis, V surinamensis, and Licaria mahuba have been the primary species utilized by smallscale saw mills in the region. Mora paraensis a species with high density wood, has only been harvested at commercial levels by caboclo smallholders over the last decade because its weight and low buoyancy make ground and water transport difficult. Permanent Inventory Plots Species demography in recently undisturbed forest was estimated from 3 largescale 360 x 360 m plots ( 13 ha per plot, 39 ha total; unharvested plots hereafter ) established and monitored yearly from 2005 to 2008 and five 1ha plots first measured in 1997 and then yearly from 2004 to 2007. To evaluate demographic responses to logging, in 2007 we established 14 small permanent inventory plots ( totaling 6.2 ha; harvested plots hereafter ) in areas logged in 20012006. Due to the small scale of logging operations, harvested plots were either 60 x 60 m or 80 x 80 m to avoid surrounding unharvested areas. Using the same methodology for recently undisturbed
85 forest plots (Chapter 3) we measured all H plot tree s in 2007 and 2008. A total of 5800 trees were monitored for this study. In addition to the collection of demographic data from permanent inventory plots, for all measured tree s, we collected information on individual/ environmental factors that could influence demogr aphy including flooding and light regimes (Chapter 3) Commercial height (i.e. height of crown base) was also estimated for all trees from our unharvested plots using vertical hypsometers to improve tree volume estimates. Estimating Population Commercial Proportion To avoid the unrealistic yieldinflating assumption that all harvest sized trees are commercial (Valle et al. 2006) all inventory trees were classified into commercial/ defective grade by a local field crew with expertise in tidal floodplain logging practices. We defined defective tree s as those with defects severe enough that they would not be felled. Since past harvests altered the proportion of commercial tree s in surviving populations only data from seldom harvested M. paraensis w ere used to calculate commercial proportion for all species. While species characteristics ( e.g., physiognomy wood density) likely influence the merchantable proportion of tree s in undisturbed populations, the use of M. paraensis alone was preferred to avoid likely larger biases resulting from the inclusion of populations that have had their commercial proportion altered by past harvests. While this appr oach may lead to optimistic first harvests for species more heavily used in the past, it yields a clear er pattern of increased incidence of defects with size which is more important to projected longterm population dynamics. Furthermore, preliminary model results showed that species with long use histories contribute substantially less to first harvest yields than M. paraensis making the size of the inherent bias in our approach likely small.
86 Monitoring of Harvesting Activities In July August 2008 we m onitored the harvesting activities of 3 local logging crews to evaluate residual stand damage and related logging practices. A total of 413 manhours were monitored in which the extraction of 40 standing trees was closely followed from forest to sawmill. W e identified and measured the DBH of all trees harvested, damaged or killed during logging. By monitoring harvest effects during logging it was easier to detect damage and determine if it was caused by operations. Because damaged trees may not die immediately following harvests, trees with extreme harvest damage where assumed dead. Harvest Model To simulate the impact of differing harvest regimes on timber tree populations, we devised a matrix harvest model using methods described in Fortini (Chapter 3) The harvest model is an areabased, nonspatial model that allows for the specification of management criteria including harvest rotation length, multiple target species, minimum cut diameter ( MCD), harvest intensi ty (1 seedtree retention proportion of trees with DBH ), minimum commercial density (MD ) and limits of harvest volume per ha. Model mechanics are described in detail below. Modeling defective stems. We used a multi site approach to model sizedependent shifts in com mercial/ defective population ratios (Morris and Doak 2002) Commercial and defective portions of each species population whe re modeled separately (Table 4 2). Defective tree s are still projected each year, may contribute to new regeneration, and may also suffer residual stand damage ( see below ). Based on the field data, the model assumes that for largesized tree s, a defective status is irreversible and that with increasing size, more commercial tree s develop defects and
87 become unmerchantable. Harvests select only commercial tree s (but also result in indiscriminant residual stand mortality) and thus result in a shift in the com m ercial/ defective population ratios. Because the role of population genetic s to the development of stem defects is unclear projected shifts in the contribution of defective adult trees to population recruitment do not influence the probability of defects occurring in juvenile classes. Seed trees selection can include the preferential selection of defective tree s (low seedtree quality, assuming short term profit maximization behavior by harvester) or may include only the commercial proportion of the population (high seedtree quality). Modeling density dependence. We included density dependent recruitment regulation (Condit et al. 1994, Blundell and Peart 2004) using a c omplemented Weibull function (Haefner 1996) to avoid unrealisti c model outcomes due to the intrinsic exponential nature of matrix projections (Bierzychudek 1999) Re cruitmentNa a exp Na b 6 4 1 Where a and b are parameters related to recruitment rates at average plot density (Np) and at carrying capacity (K) and Na is current stand density per ha. The complemented Weibull function was chosen because it regulates recruitment rates only when densities approach K, as opposed to other commonly used models (Cropper and Loudermilk 2006) This density dependent approach avoids overestimates of populati on growth by not increasing recruitment rates when Na falls below Np. This was done by subtracting Np from K during parameter estimation and calculating Na by subtracting Np from yearly population density estimates (but not allowing negative values). This normalization was used because all underlying demography ( i.e., recruitment, growth,
88 and mortality) was by definition evaluated at Np, with no auxiliary information to determine demography at lower population densities. K was calculated as the maximum subplot population density observed in all data from our unharvested plot data using all tree sizes. This calculation was done through an embedded moving window algorithm with a 100 x 100 m window size. The hasized window not only was compatible with the model's per ha outputs but also was the smallest window size that avoided effects from small scale variability in the distribution of trees K and Na in the model can be specified for individual species, user defined density dependence groups, or all species combined. Since it is highly unlikely that the observed highest densities for all species would be observed in a same subplot due to limits on overall stand density, species specific Ks were scaled proportionally to the maximum density observed for all species combined. Species grouped K and Na model parameterizations allowed for the competitive replacement of species being harvested or dying naturally by individual of species with ample recruitment, allowing for a simple mechanism for species composition shift after logging. Harvest damage modeling. Based on harvest monitoring field data, we calculated a residual stand mortality ratio. After each simulated harvest, we applied the ratio to all populations based on the number of tree s harvested. Because there were no clear size related patterns in residual stand mortality, t he residual stand mortality ratio used in the model is indiscriminate of commercial and defective tree s and size class. Post harvest demographic effects assessment and modeling. All tree s surviving a harvest are modeled using a post harvest matrix that includes post harvest demographic effects. First we attempted to define the length of post harvest effects on
89 growth and mortality u sing standard least square regression of post harves t diameter increments against years since logging. Unharvested plots were grouped for subsequent analyses since no effect of time since last harvest was found in the data. Post harvest demographic effects were determined by the comparison of diameter growt h, recruitment, and mortality rates between unharvested and harvested plots for the 20072008 measurement interval. These effects were included in projection matrices by considering the change in vital rates between the two treatments. To explain treatment differences in growth, we calculated the proportion of tree s per species and size class under varying growth conditions (e.g., light, and stem and crown damage differences). Management simulation model outputs. Every management simulation included a projection period of at least 120 years under simulated harvest regimes were calculated empirically from model projections (Eq. 42). H Nyr 120Nyr 0 1 / 120 4 2 Based on H, for each harvest regime simulation, the model also calculates the necessary compensatory recruitment needed to stabilize population size at preharvest levels Simulation of m ultiple management regimes. We applied the management simulation model over a range of possible management criteria: cutting cycles of 1 0 40 years ; MCD s of 30 7 0 cm DBH; harvest intensity of 0.50.9 of stand volume; minimum species density (MD) of 0.03 and 1 trees/ha per harvest species; high and low seedtree quality ( i.e., exclusion or inclusion of defective tree s in the calculation of harvest
90 intensity) ; and simulations with or without a harvest volume limit of a 1 m3 ha1 yr1 (Table 43). A total of 1440 management regimes resulted from all possible management criteria combinations. The harvest model applied each management regime to all study species combined until the end of the 120 yr projection period. Model outcomes where also analyzed separately for each species to explore species specific outcomes of common management criteria. The range of management regimes simulated also included the federal management guidelines as required by Brazilian law ( i.e., 10 or 30 yr cutting cycle maximum 90% harvest intensity, 50 cm MCD, MD of 0.03 trees/ha and a 1 m3 ha1 yr1 harvest volume limit; Table 43; http://ibama2.ibama.gov.br ). To evaluate which management regimes yielded the best longterm yield and population stability, all management regime simulation outcomes were rated according to 4 different STM indicators: annualized yield of fifth harvest (H5 AY) annualized yield of third harvest (H3 AY) mean annualized yield (mean AY) during the 120 years excluding the f irst harvest and the combined rank sum of mean AY H (mean AY H). The H5 AY indicator was considered indicative of STM since management regimes were applied by the model consistently across each harvest. This temporal consistency kept the model from 'cheating' by selecting low harvest intensities in initial harvests and higher intensities in later harvests. In contrast, a management regime chosen to improve future stocks that is excessively conservative will also restrict the volum e of future harvests. The H3 AY indicator was included to determine whether projection length influences analysis results. The mean AY H indicator was calculated simply as
91 the summation of the ranked mean annualized yield H. First harves ts were excluded from mean AY because annualized yields are not computable. To evaluate inter specific differences in optimum management regimes, for each of the 4 indicators used, all optimal species specific management regimes were compared. This comparison allowed the evaluation of how optimum management regimes for any given indicator varied among species. To determine whether differences in species specific optimum management regimes led to suboptimal management at the stand level we compared group and species specific optimum management regime outputs. Lastly, we used correlation analyses to evaluate the influence of management criteria on simulation outcome indicators by harvest species combined and individually. Results Post H arvest Demographic Ef fects Based on comparisons between recently logged and unlogged plots, n early all species showed a positive growth response after logging. Surprisingly, C. spruceanum, the most shade intolerant species in the study was the only one that showed a small growth reduction in response to logging. Most species showed a proportional increase in growth rates of trees in the juvenile size class (520 DBH) and no consistent treatment response for the adult size classes (> 20 DBH) F or the purposes of including pos t harvest diameter growth effects in management simulations, we maintained species response differences while summarizing post harvest growth effects as juvenile and adult effects. Additionally post harvest diameter growth was not clearly related to maxim um unlogged forest growth, precluding the use of maximum growth as post harvest growth (Rondon et al. 2009)
92 While there were no l arge recruitment boosts into the 5 cm DBH class after logging for any focal species other than Mora paraensis, low recruitment and population densities precluded the possibility of observing small recruitment effects for the remaining species (i.e., demog raphic stochasticity is larger than expected range of recruitment increases) Given these results, we chose to model post harvest recruitment increases only for M. paraensis Post harvest increases in mortality were not apparent for any focal species and w ere hence not included in the simulation model. Overall, the comparison of population projection matrices using only 20072008 data for either unlogged or recently logged plots for M. paraensis and C. spruceanum (species with data sufficient to independe ntly parameterize matrices for both treatments) showed that post harvest increases ar e large for M. paraensis (1.0272 vs 1.0032; logged vs unlogged, respectively) but not for C. spruceanum (0.9944 vs 0.9946; logged vs unlogged, respectively). A life table response experiment decomposition of post harvest effects by underlying vital rates (Caswell 2001, Morris and Doak 2002) shows that the increases in M. paraensis is mostly due to increases in growth of the smaller size classes and increases in fertility by the middle size classes, despite larger responses observed in the larger size classes (Figure 4 2). There were no differences between unharvested and harvested plots in the proportion of tree s suffering from stem and crown damage, or for vine loading, likely a consequence of generally low residual harvest damage. A la rger proportion of 520 cm DBH trees were observed under high light conditions in harvested plots compared to unharvested plots (25% vs 7%, respectively). Using only data from harvested plots, an a nalysis of growth increment by time since logging revealed no clear temporal trend.
93 Based on these results and limited literature indicating that post harvest effects on growth generally do not last longer than 10 years (Silva et al. 1995, Asner et al. 2004) we chose to use a post harvest effect duration of 10 years The difference in yield between using a 5 or 10 yr post harvest effect scenarios was approximately 2 m3 ha1 harvest1, which does not drastically alter model projections and related conclusions. Harvest Damage and Mortality O bserved residual stand damage was small and mostly affected palm s and nontimber spec ies (Table 44 ). Observ ed harvest induced damage and mortality was minimal for trees >35 cm DBH For each m2 of basal area harvested, an additional 0.11 m2 of basal area from timber trees >35 cm DBH was removed due to damage and mortality from felling Mo st notably, there was no observed damage or mortality of tree s DBH >35 cm due to transport related activities. Management Simulation Outputs The model based on groupedK density dependence yielded simulation outputs in which the speed of shifts in species relative abundance seemed related to species s and intensity of management regimes (Figure 4 3). W hile using a group K allowed for the shift in species composition that is well documented in logging operations elsewhere (Dickinson et al. 2000, Fredericksen and Mostacedo 2000, Dekker and de Graaf 2003) this approach essentially yields a nonvalidated competition model. While such a minimalist model for stand dynamics merits future research, results presented herein utilize species specific Ks. Despite the long history of timber use in the region, model outputs show that under the management requirements of Brazilian law, on average 50. 9 m3 of commercially harvestable timber is available per ha in the recently undisturbed forests
94 we sampled. Of this volume, 30 m3 would be avail able for harvest under a 30 yr cutting cycle and 10 m3 under a 10 yr cycle according to Brazilian law. Model projections indicate fast stock recovery allows continued extraction of maximum allowed volume in subsequent harvests However, the harvest yields per species change considerably across harvests. Using the 30 year Brazilian legal scenario, Mora paraensis which accounts for 87% of the first harvest, yields approximately 50% of the volume (15 m3) for subsequent harvests. Similarly, Callycophyllum spruceanum yields 9% of the first harvest volume but by the fifth harvest yields 4% of total harvest volume. On the other hand, yields of historically harvested C. guianensis and V. surinamensis increase from 2% (0.5 m3) during the first harvest to 23% (7 m3) during the fifth harvest for the two species combined. Commercial proportion decreased for all harvested species due to harvesting in Brazilian 30 yr cutting cycle legal management regime without volumebased harvest limits (Fig ure 4 4). Nevertheless the rapid population turnover of species with high s results in the stabilization of commercial proportion at high levels before each simulated harvest (e.g., V. surinamensis and P. filipes ). In contrast, species with low s have a low ability to recover between harvests and therefore have commercial proportions that drop after each harvest (e.g., C. spruceanum and L. mahuba ). The remaining species with s slightly above 1 stabilized at preharvest commercial proportions of approximately 0.60.7. Under the same scenario, second harvest volume falls to 39 m3 (a 75% stock recovery rate). The inclusion of volumebased harvest limits generally decreased the rate of decline of commercial proportion in modeled projections.
95 The most intensive management regimes resulted in the largest first harvests (87 m3 with a MCD of 30 cm DBH, 0.9 harvest intensity, and no harvest volume restrictions) but also resulted in very low future harvest volumes (6.2 m3 per ha at fifth harvest under a 30yr cutting cycle ). The optimal management regimes for the four STM indicators varied in terms of most management criteria except for the common prescription of short 10year cutting cycles and no volume limits per harvests (Table 4 5 ). The management regime with highest H3 AY resulted in slightly more aggressive harvests by specifying a MCD of 40 cm DBH. Optimal management regimes for all STM indicators but highest H3 AY (the most short sighted STM indicator) included MCDs of 50 cm DBH or greater. Most of the top mean AY H management regimes required a MCD of 60 cm DBH and volume harvest limits. These STM regimes showed little indication of yield decreases over time and required little additional recruitment to compensate for population growth decreases. All optimal management regimes for the other three STM indicators showed signs of declining yields and higher compensatory recruitment needs. However, of the three, the management regime with highest mean AY also required the least number of compensatory recruitment. The Brazilian legal scenarios resulted in lower mean AY than any of the optimal STM regimes while still requiring similar numbers of compensatory recruitment, indicating potential resource under utilization. For each STM indicator we evaluated the differenc es in optimum management criteria among species. Given the inter specific demographic differences, there was nearly no overlap among the three best species specific management regimes according to the four STM indicators (Table 4 6 ). The inclusion of speci es specific
96 regimes led to better results compared to general optimal management regimes (Table 4 7 ). The best species specific management regimes for highest H5 AY resulted in a 0.34 m3/yr annualized yield gain. The best species specific management regimes for highest mean AY resulted in a 0.12 m3/yr annualized yield gain. STM Sensitivity to Management Criteria Stand mean AY decreases with longer cutting cycles and the inclusion of harv est volume limits, but peaks at a MCD of 50 cm (Figure 4 5). While other management criteria were not significantly correlated to stand mean AY (harvest intensity, minimum commercial density, and seedtree quality), species specific analyses yielded more nuanced results. Longer cutting cycles lead to large mean AY reductions in M. paraensis but also to small increases to V. surinamensis Harvest intensity had a small negative impact on mean AY for slow growing species ( M. p araensis C. spruceanum and L. ma huba) Higher MCD has a small positive effect on mean AY of M. paraensis but strong effects on all other species. However, this relationship was curvilinear with mean AY peaking around a MCD of 5060 for most species. High MD decreases the mean AY of the least common species ( C. spruceanum L. mahuba, and P. filipes ), with its negative effects increasing with species scarcity. Harvest volume limitations reduce mean AY of the fast growing species ( C. guianensis V. surinamensis and P. filipes ), but cause t he opposite effect in C. spruceanum H increases with higher MCD and the inclusion of harvest volume limits but also suffers mild decreases with increasing harvest intensity. Species H results H results above wi th few exceptions. MD has a positive H for the three least common species, indicating a trade off for these species
97 considering the opposite effect of MD on mean AY of the same species. Increasing cutting cycles also has a mild positive effect on all species but M. paraensis Discussion Demography Differences Between Recently Logged and Recently Undisturbed Estuarine Forests Results from monitoring of harvesting operations show that demographic effects of selective harvesting were small and li kely a result of small damage from nonmechanized operations in relatively vinefree forests The observed weak harvest effects are in agreement with upland forest studies that show tree fall gaps have small and short lived demographic effects (Finegan and Camacho 1999, Fredericksen and Mostacedo 2000, Sist and NguyenThe 2002, Smith and Nichols 2005) Crown illumination evaluations and field observations suggest canopy gaps close quickly after logging in the study area, which agrees with assessments of felling damage in upland forest (Asner et al. 2004, Broadbent et al. 2006) Although stem diameter growth was the demographic rate most affected by selective logging, and that light availability controls diameter growth in undisturbed stands (Chapter 3) the fact that post harvest growth effects were not driven by changes in light availability is surprising (Chazdon et al. 1996) Given the small size of logging gaps, full canopy closure could occur long before stand density has recovered, resulting in continued underground competition (Kammesheidt et al. 2001) The unexpected lack of growth response by C. spruceanum (a light demanding species) may be due to relatively small canopy openings that benefited its shade tol erant competitors (PeaClaros et al. 2008) Logging damage seems an unlikely reason the lack of growth response in C. spruceanum because damage assessment in logged plots and recently
98 logged areas showed minimal damage that affects species indiscriminately, hence any damage effect should have affected other species as well. While other studies have found increased post harvest mortality persisting years after initial harvests ( Schulze and Zweede 2006; Figueira et al. 2008; but see Silva et al. 1995), morta lity rates in logged plots did not differ from those observed in recently unlogged plots in this study. The lack of mortality effect could be partially explained by the observed low residual stand damage, and relatively small gaps that close quickly. Another possibility may be that, unlike unlogged mature stands elsewhere that may contain many structurally weak tree s sheltered by a closed canopy (Gardiner et al. 1997) the long history of logging may have already culled large structurally compromised tree s in previous harvests. Widespread advanced regeneration of Mora paraensis produced a strong increase in recruitment into the smallest measured s ize class (>5 cm DBH) after logging for that species alone. Because logged plots varied from 1 to 6 years since last extraction, it is possible that the post harvest recruits of other species had not yet reached measurement size. Nevertheless field observations also show there were nearly no C. spruceanum saplings present in logged and natural gaps, indicating the common extent of logging disturbance is likely insufficient for the recr uitment of this and other light demanding species. Low intensity harvests have been found elsewhere to be insufficient to boost regeneration of light demanding species (Wittmann and Junk 2003) These results indicate t hat the challenge to promote regeneration of light demanding species and to simultaneously reduce logging damage extends to the Amazonian
99 floodplain (Fredericksen and Mostacedo 2000, Fredericksen and Putz 2003, Zarin et al. 2007) Using M. paraensis (the most abundant species) as an example, the integration of demographic effects of logging using life table response experiments (LTRE) shows that demographic rates most affected by logging may not be the most important for determining post harvest tree populatio n dynamics. These conclusions are important because harvest evaluations commonly consider growth, survival, and recruitment effects separately, and may misrepresent changes in population dynamics resulting from observed demographic effects (Fortini et al. 2010) W ithout the use of an integrated population approach, however, it would not be possible to detect the larger contribution that smaller juv enile growth increases offer to the persistence of the species in the stand. Harvest Damage from Nonmechanized Small scale Logging R esidual stand damage was relatively low compared to other s tudies (Johns et al. 1996, Pinard and Putz 1996, Jackson et al. 2002, Rockwell et al. 2007b) with no observed damage to large trees during yarding operations These results bode well for future harvest s as these larger tree s will likely constitute the second harvest cohorts. This low residual stand damage is likely a consequence of several favorable factors including the low abundance of vines and lianas that hinder directional felling and cause multiple tree falls, the large abundance of palms which may provide safe felling z ones (Chapter 2), the lack of heavy machinery use, and the absence of road construction. A proportion of residual stand mortality resulted from the need for t ransport rails and float wood used in the manual transport of timber from the forest causes of harvest mortality
100 not observed in upland logging operations. These practices avoid use of timber species and instead use species of little to no economic value (e.g., Inga spp and palms). Prospects for Sustainable Timber Yield Most evaluations of stock rec overy rates in tropical forest s are below 50% over government specified cutting cycles casting doubt over the feasibility of longterm STM (Dauber et al. 2005, Brienen and Zuidema 2007, Sist and Ferreira 2007, Schulze et al. 2008, Rondon et al. 2009) In contrast while the potential for SFM in Amazonian estuarine floodplains has long been recognized, it has been little explored (Barros and Uhl 1995, PinedoVasquez et al. 2001) The fact that timber is still extracted today after hundreds of years of low intensity logging in the estuary supports results from this study t hat suggest sustaining future harvests is possible. In this study, recovery rate s are high for most simulated management regimes due to the comparatively high projected mean AYs (Van Gardingen et al. 2006) that are close to the maximum estimated tropical forest productivity limits (Rice et al. 2001) T hese large mean AYs are primarily due to projected increases in yields from the two fast growing species V. surinamensis and C. guianensis that effectively counterbalance the projected yield declines from other species. Given the historically high volumes of C. guianensis and V. surinamensis extracted in the past, the drastic projected recovery of these two species may be explained by the stark differences between common extractive practices and simulated forested management. As described elsewhere, smallholders often practice reentry logging where tree populations are harvest ed down to small tree diameters (Barros and Uhl 1995, Lima et al. 2006) In fact, model projections show that the harvesting of all commercial individuals down to small
101 diameters will lead to rapid population and yield decline s for both C. guianensis and V. surinamensis While our results point to increases in the proportion of noncommercial trees due to consecutive harvest s, model results suggest that fast population grow th and related fast diameter growth preclude the possibility of forests of unmerchantable trees. Nevertheless slowgrowing populations exhibit slow recovery in tree densities and volumes afte r logging and face continuously decreasing proportion of commercial tree s while under a timber harvest regime. For instance, while most study species under simulated management reached a new lower proportion of commercial tree s under intensive harvests th e two species that showed signs of population decline, C. spruceanum and L. mahuba, not only exhibited limitations in population recovery but had continuously declining proportions of commercial trees after each harvest cycle (Chapter 3) Fortunately, the number of recruits needed to maintain population stability was low. This need for additional recruits is particularly relevant to the Amazon estuary because, at the smallholder scale of management, additional costs related to managing timber species regeneration are low due to low opportunity costs (Keefe 2008) Local initiatives to improve seedling supply are underway, but a better understanding of enrichment planning may be needed to ensure success (Schulze 2008, Keefe et al. 2009) Preliminary model results based on applying density dependence using stand level carrying capacity show that forest composition can change considerably over the co urse of multiple harvest rotations. While few studies explore the consequences of logging on tropical forest composition, those that address it generally conclude these
102 changes can affect longterm ecological and economic viability of yields (Alder and Silva 2000, Phillips et al. 2004) Nonetheless, prospects for STM are better i n the studied stands than for many other areas evaluated elsewhere in the Amazon (Dauber et al. 2005, Rondon et al. 2009) Lastly, Callycophyllum spruceanum's lack of post harvest recruitment, despite its ample regeneration in large forest clearings and secondary forests (De Jong 2001, Sears 2003) and commonly observed cohort like size distributions (Chapter 3) indicates this species is a longlived canopy pioneer species heavily dependent on large scale disturbances (Condit et al. 1998) The prospects for STM of this species would likely be best evaluated by considering how population dynamics of the species interacts with landscape dynamics of the region. This landscape analysis could be done by integrating a landscape model than considers the probability of disturbances large enough for pioneer recruitment along with appropriate demographic modeling of resulting cohorts. Determining Best Management Regimes for Sustainable Timber Management The variability and complexity of population responses to logging observed h ere and elsewhere suggest limited prospects for simple and effective onesize fits all management prescriptions (Dauber et al. 2005, Sebbenn et al. 2008, Schongart 2008) Due to contrasting species demography, the importance of management criteria on yield and population growth varied widely among species. In some cases even universally important management criteria had contrasting effects across species (e.g., harvest volume limits). This complexity of species specific responses tended to be averaged out in standlevel analyses. For instance, analysis with all species combined showed minimum density limits barely affected yield and population growth, as noted elsewhere (Schulze et al. 2008) ; However, t he same analysis at a species level show
103 this variable is important in terms of yield and population growth for the few rare species included in the analysis. S urpri singly, the comparison of species specific vs. general (but study specific) optimal management regimes did not show substantial differences in yield s or population growth under simulated longterm forest management. However it is likely these results are highly dependent on the range of demographic variability included and the set of species studied. Applying a similar analytical approach to a larger set of species could reveal patterns in optimal management criteria related to commonalities in species demography, thus resulting in demography specific management guidelines. Aside from the general and species specific management guidelines devised in this study, this research shows how population modeling tools can help inform decisions about harvest regulations Population dynamic sbased outputs such as compensatory recruitment, and population growth rates under logging are valuable tools for deciding which management regimes are most appropriate for a given region and species/ functional group. Nevertheless, this study shows how optimal STM regimes depend on how STM is quantified. STM indicators with potentially short management horizons, such as the H3 and H5 AY indicators, led to aggressive optimal management regimes that still resulted in large drops in harvest volume between fi rst and later harvests. The other STM indicators, mean AY and mean AY H, were calculated over a fixed 120 yr management horizon and seem to lead to better STM regimes by providing high AYs while requiring lower numbers of compensatory recruits per harvest. Overall, mean AY H seems to be the best performing STM indicator as it prevents decreases in harvest volumes, guarantees high mean AY while requiring the least number of compensatory
104 recruits per harvest of the four indicators used. However, it gives arbitrary equal weight to yield and population growth and yields results not comparable to other studies since it is a sum of ranks. While we cannot easily implement different harvest intervals for individual species or species groups due to logistic and economic constraints, we can more readily alter species specific harvest intensity and MCDs. The importance of MCDs to most species future yield and population growth, and the ease of implementing species specific MCDs suggest that biologically meaningful and species (or functional group) specific management criteria may provide a feasible combined STM and SFM oriented strategy (Sc hulze et al. 2008) A post hoc analysis for optimal species specific management regimes under the mean AY H indicator using the optimal cutting cycle length and harvest volume limits indicated by the stand analysis result s in easily implementable speciesspecific management regimes (Table 4 5 ). Almost all optimal STM regimes exclude the possibility of MCD lower than 50 cm DBH, which bodes well for current Brazilian legislation with similar requirements. A central factor in determining yields of the Braz ilian legal management regimes is the inclusion of harvest volume limits. This study shows that such an overarching rule may in some cases lead to resource underutilization. In fact, the mean AY H optimal management regimes produc es a much higher mean A Y with nearly no need for extra compensatory recruitment. While this study focused on rotationbased management as required by Brazilian law, most smallholders in the Estuary practice reentry logging that vary from low to very high intensity (Macedo and Anderson 1993, Barros and Uhl 1995) On one hand,
105 common highintensity and frequent re entry harvests have large influences on population persistence as evidenced by the historical decline of populations of C. guianensis and V. surinamensis (Chapter 3). On the other hand, as evidenced in few smallholder properties in Mazago, at low harvest intensities it is not clear reentry logging is more damaging per volume extracted given the generally low harvest damage. On the contrary, field observations and local knowledge suggest that fewer intense harvests may release the undesirable Astrocaryum palm in the understory leading to decreased regeneration of woody species. While rotation and areabased management is the current paradigm of tropical forest management, it may drive smallholder s in the estuary into illegality partly due to management plans that require long time intervals with no revenue and complex requirements that require costly technical assistance (Hirakuri 2003) Although current Brazilian law specifies simpler timber licensing procedures for smaller properties, future research should explore potential management requirements that are more compatible with small scale low intensity forest management operations (Hirakuri 2003, Zarin et al. 2007)
106 Table 41. Study species Family Species Local name Characteristics Caesalpiniaceae Mora paraensis Pracuba Recently harvested, shade tolerant, high density Chrysobalanaceae Licania heteromorpha Macucu Not yet harvested, shade tolerant Rubiaceae Callycophyllum spruceanum Pau mulato Harvested since 1990s, shade intolerant, pioneer Meliaceae Carapa guianensis Andiroba Long used, shade tolerant Myristicaceae Virola surinamensis Virola Long used, low wood density, shade tolerant Lauraceae Licaria mahuba Maba Long used, shade tolerant Sapotaceae Pouteria sagotiana Maaranduba Low local use, shade tolerant, high wood dens ity Fabaceae Platymiscium filipes Macacaba Long used, shade intolerant, high wood dens ity Table 42. Transition matrix model used for management simulations xProbability that commercial (C) tree s growing to next size class will become noncommercial (NC) because of defects. S= survival probability, G= siz e class upgrowth probability, F= Fertility rate per capita; Numerical subscripts denote 15 cm wide size classes from 5 cm DBH to maximum observed size
107 Table 43. Values for management criteria used in m anagement simulations Cutting cycle Harvest intensity MDC Min. com. density Seed tree quality Max volume per harvest (m 3 yr 1 ha 1 ) 10* 0.5 30 0 High 20 0.6 40 0.03* Low* 1* 30* 0.7 50* 1 40 0.8 60 0.9* 70 denote criteria specified by Brazilian federal management guidelines
108 Table 44 R esidual stand damage from monitored timber extraction BA (m 2 ) of trees > 5 cm DBH killed* by BA (m 2 ) of timber extracted Tree fall Transport Total Palm 0.17 0.03 0.2 Timber 0.13 0 0.13 Other woody spp. 0.28 0 0.28 Total 0.58 0.04 0.62 BA (m2) of trees > 35 cm DBH killed* by BA (m2) of timber extracted Tree fall Transport Total Palm 0 0 0 Timber 0.11 0 0.11 Other woody spp. 0.17 0 0.17 Total 0.28 0 0.28 *estimate of mortality also includes tree s clearly damaged beyond potential recovery.
109 Table 45 Optimal management regimes defined by alternative sustained timber yield indicators Optimal criteria Management outcomes Management optimized for Considering Cutting cycle Harvest intensity MCD Min. com. density Seed tree quality Max volume per harvest Volume of first harvest Volume of fifth harvest Compensatory recruitment Mean AY Largest mean AY All species 10 0.5 50 0.03 Low 300 28.94 19.34 10 1.8 Largest H 5 AY All species 10 0.9 50 1 Low 300 49.91 21.23 12 1.55 Largest H 3 AY All species 10 0.5 40 0.03 Low 300 40.35 16.16 20 1.47 High mean AY H All species 10 0.5 60 1 High 300 15.77 15.02 4 1.44 Brazilian legal scenario All species 30 0.9 50 0.03 Low 30 30 30 22 1 Brazilian legal scenario All species 10 0.9 50 0.03 Low 10 10 10 3 1 High mean AY H M. paraensis 10* 0.5 60 1 Low 300* 18.02 15.91 5 1.52 High mean AY H C. spruceanum 10* 0.6 60 1 High 300* 18.92 15.66 5 1.48 High mean AY H C. guianensis 10* 0.8 60 1 Low 300* 28.84 14.50 5 1.48 High mean AY H V. surinamensis 10* 0.6 50 1 Low 300* 33.27 17.50 10 1.71 High mean AY H L. mahuba 10* 0.5 50 0.03 Low 300* 28.94 19.34 10 1.8 High mean AY H P. filipes 10* 0.9 50 1 Low 300* 49.91 21.23 12 1.55 management criteria fixed based on optimal value from analysis of all species combined
110 Table 46 Comparison of species specific optimal management regimes according to four STM indicators M. paraensis C. spruceanum C. guianensis V. surinamensis L. mahuba P. filipes Largest mean AY M. paraensis 1 C. spruceanum 0 1 C. guianensis 0 0 1 V. surinamensis 0 0 1 1 L. mahuba 0 0 0 0 1 P. filipes 0 0 0 0 1 1 Largest H 5 AY M. paraensis 1 C. spruceanum 1 1 C. guianensis 1 1 1 V. surinamensis 1 1 1 1 L. mahuba 0 0 0 0 1 P. filipes 0 0 0 0 0 1 Largest H 3 AY M. paraensis 1 C. spruceanum 0 1 C. guianensis 0 1 1 V. surinamensis 0 1 1 1 L. mahuba 0 0 0 0 1 P. filipes 0 0 0 0 0 1 Hi gh mean AY M. paraensis 1 C. spruceanum 0 1 C. guianensis 1 1 1 V. surinamensis 0 0 0 1 L. mahuba 0 0 0 0 1 P. filipes 0 0 0 1 0 1 Ones denote a match in optimal management prescriptions between species, zeros a mismatch
111 Table 47 Differences in performance between species specific and general optimal management regimes Mean AY (m 3 yr 1 ha 1 ) H 5 AY (m 3 yr 1 ha 1 ) M. paraensis 0.03 0.11 C. spruceanum 0.02 0.04 C. guianensis 0.05 0.03 V. surinamensis 0.01 0.01 L. mahuba 0 0.14 P. filipes 0 0 Total 0.12 0.34
112 Figure 41. Map of study area
113 Figure 42. Life table response experiment for M. paraensis demonstrating demographic differences between logged and recently undisturbed plots and their contributions to population growth
114 Figure 43. Management simulation projections illustrating differences betw een species and grouped density dependent models
115 Figure 44. Shifts in commercial proportion under the Brazilian legal scenario with 30 yr cutting cycle but without volumebased harvest limits Licania heteromorpha and P. sa gotiana were not harvested during simulations. Licaria mahuba was harvested until year 180, after which densities were too low for continued harvests.
116 Figure 45. SimulationH in response to varying management criteria.
117 CHAPTER 5 TIMBER MICRO FIRMS O F THE AMAZON ESTUARY: A VIABLE ECONOMIC MODEL FOR DEVELOPMENT? Introduction While the majority of timber management literature from the Amazon has focused on industrial operations, it is estimated that 95% of rural properties in the Amazon are less than 500 ha ( IBGE, 1996), providing as much as 28% of regional timber output (Lentini et al. 2005) Government settlements in the Amazon alone account for approximately 500,000 small holder families that commonly sell timber (Lima et al. 2006) Surprisingly, relatively little attention has been paid to the potentials and limitation s of timber management in small holder scales, with the most relevant research focusing on community forestry efforts (d'Oliveira 2000, Rockwell et al. 2007b) Smallholder timber operations may vary substantially from industrial operations in techniques, technology, capital availability, market reach and ecological impacts (chapter 4, Salafsky et al. 1998, Rockwell et al. 2007a, Keefe 2008) Without the proper knowledge and consideration of the potentials and limitations of smallholder timbe r management, most legislation on timber use in the tropics has focused on the industrial scale, leading to unrealistic expectations to smallholder s and communities (d'Oliveira 2000, Rockwell et al. 2007a, Zarin et al. 2007) In the mouth of the A mazon River, smallholder s have developed a microscale vertically integrated system of timber production (Pinedo Vasquez et al. 2001, Sears et al. 2007a) Contrary to community led efforts elsewhere, these informal micro firms are owned individually and commonly integrate timber extraction and processing in local cir cular sawmills. For decades, hundreds of these micro firms have produced sawn lumber sold primarily at local and regional markets (B arros and Uhl 1995) As past
118 research in Amazon tidal forests have documented the potential for small scale sustainable timber management, these micro firms bear special relevance to the potential role of smallholder s in sustainable timber management (chapter 4, Barros and Uhl 1995, PinedoVasquez et al. 2001) Surprisingly, one of the largest threats to micro firm timber production in the estuary appears to be the aa palm ( Euterpe oleracea) fruit. Characterized as a nontimber forest products by some or as a pressure for forest conversion by others, it is nevertheless an increasingly popular alternative to timber production in the Amazon Estuary (Brondizio 2004, Weinstein and Moegenburg 2005) Intensified aa production often results in monospecific stands where most competitors species (including timber) are eliminated while the abundance of aa is increased from natural regeneration and additional plantings. As one of few examples of small scale localized timber production systems, the Amazon Estuary is ideal for exploring issues of smallholder vertically integrated timber use. In this study we use data from multiple sources including landowner and firm surveys, participatory monitoring of firms, and detailed forest and sawmill operation monitoring to devise a financial returns model of smallholder timber micro firms and a simpler model for smal lholder aa production. We then explore the economics of timber micro firms to address the following questions: (1) What are the financial costs and revenues of timber micro firms? (2) What micro economic factors most influence longterm economic viabili ty of timber production by micro firms? (3) How does timber micro fi rm profitability compare to regional economic alternatives? How can this be used to advance tropical conservation and development?
119 Methods Study Region We conducted our research in the 160 sq km Mazago watershed at the Western side of the Amazon estuary (Figure 5 1). The Mazago watershed has a long history of timber use (PinedoVasquez et al. 2001) with current micro scale timber extraction as part of diverse livelihood strategies that often also include palm fruit, fishing, and cropping. Mazago is similar in composition and land use history to several adjacent wat ersheds, as confirmed by region wide inventories and surveys conducted in 2005 (Fortini, unpublished data) Mean annual temperature is 27C and average daily temperature varies by less than 3C from month to month. Mean annual precipitation is 2550mm and occ urs mostly in the wet season months of January May. This part of the Amazon estuary is characterized by freshwater tidal fluctuations of 23m. Because of the elevated river level in the wet season, local forests may flood twice daily during high tides. The Vrzea Smallholder Timber Production System The micro scale timber producing firms are centered around the small sawmills that process locally harvested timber to be sold regionally. Although past research suggests sawmills worked independently from those who extracted timber and sold as logs (Barros and Uhl 1995) forest extraction is increasingly performed by the same 4 5 person crew responsible for sawmill operations (Lentini et al. 2005) While up to 1020 years ago felling by axe was common in the region, now chainsaws are prevalent (Barros and Uhl 1995, Lima et al. 2006) One of the characteristics of these firms is the high dependence in nonmechanized labor. Once trees are felled, tracks are manually cleared where bucked logs are pushed over small rails made from small non-
120 commercial stems to river edge. Logs are then manually floated with the aid of tides to the mill using float wood or larger rafts (Barros and Uhl 1995) As of 2008, 12 micro firms where installed in the 160 sq km Mazago watershed. Monitoring of Extraction and Sawmill Activities We monitored extraction activities between June and August 2008 to quantify all costs and production of related activities. Because crews alternate time spent in the forest and sawmill, we monitored the activities of two crews. We devised a monitoring methodology to log time spent by each crew in each of five activities : felling and bucking; clearing path and laying tracks, pushing logs, floating logs, and transportation to and from forest sites. All trees and tracks between felled trees and river edge were mapped and georeferenced. Using a tree, log and trail numbering system, the production for any particular activity (e.g., volume felled, m trail created) was related to time spent on each category. To calculate harvest efficiency, we measured total stem volume (i.e., from base to crown base) and harvested volume for each felled tree by measuring diameter along the stem. We conducted a similarly detailed monitoring of two sawmills between May and October of 2007. We recorded the processing time, volume and yield of each log processed and all related labor, fuel and food expenses. Additional cost and production data was obtained through the participatory monitoring of three firms from 2006 to 2008. Using simple accounting books, firm owners registered all log and tree purchases by species, listing the place of origin, species, volume or number of logs, and related sawmill processing costs. To check a nd complement daily cost and revenue estimates with estimates of capital investment, equipment durability and maintenance costs, we also conducted detailed surveys with all firm owners present in the Mazago watershed
121 in July August 2008. Because this study follows 4 years of local rapport building during other related research, we expected our close monitoring to accurately reflect timber activity in the region. Financial Returns Model The field data collected was used to construct a singlefirm financial return model that assumes firms operate under short run conditions, no market power and no economies of scale for a period of 30 years. The 30year time horizon was selected to include the lifespan of a sawmill and at least one full typical harvest rotation (10 to 30 years according to Brazilian forestry legislation). To reflect the way timber is usually produced in the watershed, the model includes three modes of production: firms using timber from own property, firms purchasing standing trees, and firms purchasing felled logs. We used depreciation as a means to annualize periodical replacement costs of capital assets (i.e., an annual contribution necessary to ensure future replacement costs) to avoid peaks in year to year costs based on estimates of equipment durability. We calculated straight line depreciation based on use or time depending on whether the durability of asset was dependent on usage (e.g., mill engine, chainsaws) or tim e (e.g., mill housing, wood boats). Operational costs were modeled for all stages of production from felling to milling. Since chainsaws are used for extraction and for longitudinally splitting large logs in the sawmill, we divided chainsaw depreciation and maintenance costs according to their proportional use in extraction and milling. Similarly, we excluded a portion of boat and boat engine depreciation and maintenance costs proportional to the estimated boat use unrelated to timber production. The final model also included changes in extraction practices during the flood season (i.e., shorter pushing distances)
122 and incorporates temporal trends in parameter values. Annual firm revenue was calculated as firm output (based on forest, transportation and sawmi ll efficiency), allocated among the four predominant product types and their respective prices Revenue from the sale of solid wood residues to charcoal producers was also included in the model. The model outputs cost and revenues by year and by m3 and cal culates NPV of the firm by discounting all costs and revenues over the 30year projection period. Due to the limited economic opportunities in the region, an interest rate of 6 79 % was used for discounting based on the average rate on savings from 2006 to 2008. Model Perturbation and Sensitivity Analyses Following model creation and parameterization, we performed perturbation analysis to evaluate parameter importance to overall model output using multiple model runs with parameters varying randomly withi n their observed ranges (Boltz et al. 2001) Since results of the perturbation analysis are based on the observed variability of e ach model param eter we consequently relied instead on a simpler elasticity analyses that considered the effect of a 1% reduction in mean parameter value on model output NPV. We used a simple formula to evaluate the elasticity of model output to changes in individual par ameters (Eq. 41). Ela NPVparameter i NPV NPV 0.01 5 1 This elasticity formula allowed me to evaluate the direction and percent change in model NPV given a percent change in a particular parameter value.
123 Evaluating Aa Costs and Revenues To compare the attr activeness of timber production to pervasive aa fruit production, we used previously published data along with interviews with aa producers in the watershed to quantify startup costs (e.g., clearing and planting), yearly management and harvesting costs (Hiraoka 1992, Munizmiret et al. 1996) Average per ha production estimates for the region were calculated by estimating average aa stand density from 25 aa stand inventories and using a sec ond degree nointercept polynomial function relating per hectare production and aa density calculated from previously published data (Brondiz io and Siqueira 1997) Pr oduction baskets 3.56 10 4 aa clumps2 0.243 aa clumps 5 2 Since production is highly seasonal and largely synchronous across households, we used production and price data collected from a single household between 20052008 to calculate weighted average revenue per 18 kg basket of aa for the region (Munizmiret et al. 1996) Startup costs, annual revenues and management costs were used to calculate the NPV of establishing a 1 ha stand of aa from recently undisturbed forest and managing it for 30 years. Unlike economic analyses performed elsewhere (Munizmiret et al. 1996) aa stand NPV was calculated as a finite payment series discounted from year of first harvest minus initial startup costs (Klemperer 1996) NPV p 1 1 r 26r 1 r 3 C0 5 3 Where p is annual net revenue of producing years, r is discount rate, and C0 is startup costs. The first half of the equation gives the discounted value at year 3 of p from years 4 30 (i.e., 26 harvest years). The resulting product is then discounted from third year dollar values to the present. This approach was preferred because local aa
124 management includes the continuous thinning of older less productive stems that allows for continuous production without the need for the clearance and replanting of the entire stand every 1520 years. Results Extraction Practices The annual costs of extracting 750 m3 of standing volume to sawmill harbor (the average per firm in the watershed) was $4457. This value excludes stumpage costs and results in 532 m3 of timber reaching the sawmill based on a 71% timber extraction efficiency. Costs per extraction activity standardized by volume output show floating costs to transport timber from forest river edge to sawmill is larger than all other activities including felling and bucking (Figure 5 2). As expected due t o the low level of mechanization, labor related expenses (6.62 $/m3) entirely overshadow fuel and equipment costs (0.49 $/m3and 1.27 $/m3, respectively; Figure 5 3 ). Forest monitoring also revealed that o n average 15% of labor time is spent in travelling t o and from the forest. Sawmill Practices Based on detailed sawmill monitoring data, firms produce on average 195 m3 of sawn wood per year with a mean sawmill processing efficiency from round wood to sawtimber of 37%. A two way anova also revealed differences in milling efficiency between sawmills and among species sawn (Species df = 4, F = 3.36, p < 0.01; Mills df = 1, F = 12.83, p < 0.0004; Species*Mills df = 3, F = 4.84, p< 0.002). While mean processing efficiency between sawmills varied little (0.41 vs 0.36), processing efficiency varied widely among species, with M. paraensis and P. filipes having mean values around 0.3 and C. spruceanum C. guanensis and L. mahuba having mean values
1 25 around 0.4. Surprisingly, while volume input and output per log were strongly related ( r = 0.82, p < 0.0001), log use efficiency was not correlated with log diameter. This is likely a result from an increased proportion of irregularities and defects with age and due to the use of chainsaws to split large logs that sawmill s aws could not process. Perhaps due to these patterns, while it clearly took longer time to process larger logs ( r = 0.61, p < 0.0001), volume output per hr was not related to log size. Lastly, a link between volume processed daily and person hours of effor t was apparent (Figure 5 4 ; r = 0.75, p < 0.0001). Cost and Revenues of Micro Timber Firms Firms need approximately $7451 to cover startup costs (e.g., sawmill machinery and housing, chainsaws, assorted equipment) and spend considerably more on milling th an in forest operations (47.35 vs 8.38 $/m3 output, respectively). Only when purchasing extracted timber as logs does the cost of raw materials approach yearly processing costs ($6892 vs $9246, respectively; Figure 5 5 ). On the other hand, average yearly depreciation and maintenance costs (619 and 968 $/yr, respectively) are relatively low due to the highly labor dependent system of production. Gross revenue per m3 of sawn lumber produced was $95.75. In comparison, average cost per m3 produced for firms us ing their own timber and purchasing standing timber were $70.19 and $77.68, respectively. For firms purchasing logs, average cost per m3 produced was slightly below gross revenue per m3, $89.83. According to model simulations, all modes of firm production were very profitable (Table 5 1); However, differences in profitability among the three modes of firm production were large and resulted in differences in the time required to recoup initial startup costs and internal rates of return ( IRR; Table 5 1).
126 Model elasticity analyses revealed labor related parameters such as daily wages and work hours per day exert important influence over the NPV of a micro timber producing firm (Table 5 2). Discount rate also has a very large influence over a firm's NPV, especially because it may vary largely above the range of values used in calculating elasticity. Given the high costs of processing, several sawmill production parameters had a large influence over NPV as well (e.g., mill processing efficiency, processing capaci ty and days of operation). Asset related values had minimal impacts on the profitability of a firm, whether in terms of initial price, durability, salvage value or maintenance. Surprisingly, output of extraction activities had a generally small impact on N PV, with only output for floating logs having a moderate effect over NPV. Aa Fruit Production Costs and Revenues Average startup costs for clearing and planting 1 ha of aa was $948. Yearly revenue based on the seasonality of production and average a a stand density in the region is $1040. Yearly management and harvesting costs are approximately $518. Nearly all costs associated with aa fruit production were labor related since no special equipment is needed for the activity (except for a $41 yearly expense in harvest baskets). NPV for the establishment of 1 ha of aa was $4222. Timber and Aa Comparison NPV over initial investments show timber production yields a better return per dollar invested than aa fruit production only when firms mill t heir own timber or timber purchased standing (Table 5 1). Payback periods to recoup timber production startup costs varied greatly depending on the source of raw material (29 years; Table 5 1). aa payback period was also long at 8 years, due to the init ial 4 year wait between planting and full production. Based on average timber stocking of regional forests
127 ( Chapter 4), to recoup startup costs micro firms would have to harvest at least 22 ha of their own forests or process as much as 95 ha of timber as purchased logs (excluding harvest schedule discounting; Table 5 1). On the other hand, aa producers can offset the initial startup costs of stand establishment by selling 9 ha worth of standing timber per ha of aa stand planted. Discussion The Smallhol der Timber Micro Firm The total cost of timber extraction and transport of $11.12 per m3 of this study is among the lowest values reported for tropical forests for either conventional and reduced impact logging (Verissimo et al. 1992, Barreto et al. 1998, Holmes et al. 2002, Pokorny and Steinbrenner 2005) This particularly low cost is due to a combination of logging costs slightly below other studies and transportation costs within the lowest reported elsewhere ($7.37 and $3.75 per m3, respectively). Estimated stumpage costs per m3 are also within the lowest bound of reported values ($2.75/m3) being only larger than those reported by small scale conventional logging operations (Verissimo et al. 1992, Stone 1998) While there are generally few economic studies of timber use in the Amazonian f loodplains (Barros and Uhl 1995, Lentini et al. 2005) this study supports the notion that varzea extraction can be substantially cheaper than upland timber extraction (Barros and Uhl 1995) Despite the high incidence of buttressing of floodplain trees (Parolin et al. 2004) timber use efficiency of monitored forest operations was high. This result could be partially explained by the small scale of extraction which led to no observed lost logs or felled trees and the utilization of logs as small as 20 cm in diameter, resulting in little stem volume unutilized below the crown. Additionally, the apparent selectiveness of the
128 sawyer (who commonly is also the firm owner who pays landowners per tree harvested) means partially defective trees were avoided. Vertical integration of production means micro firms buying or harvesting their own standing trees can select trees that give better return with no incentive to intensify harvests per area. On the other hand, since some firms pay per trees extracted, trees that fall accidentally during harvests and that otherwise would be partially utilized may be left in the forest if it is deemed not worth the tree based stumpage price. The estimate of proce ssing costs per m3 is in par with average Amazonwide estimates, when corrected for recent exchange rate fluctuations ($47 vs. $51 per m3, respectively; Lentini et al. 2005) However, this studys processing cost estimate is notably higher than previous survey based exchangerate corrected values for similar circular sawmills ($47 vs. $26 per m3, respect ively; Lentini 2005). The Estimate of sawmill processing efficiency obtained from detailed per log monitoring (0.37) is higher than those published for similar micro sawmills elsewhere (0.28 and 0.35; Barros and Uhl 1995, Lentini et al. 2005a, respectively) but within range of Amazonianwide industry estimates (Lentini et al. 2005) On the other hand, the present estimates of yearly processing volume per firm are markedly lower than previous survey based studies. Based on measured average sawmill dai ly processing capacity and mean number of days of mill operation per month, the 532 m3 of timber processed annually by sawmills in this study is only a third of values published in previous studies (Barros and Uhl 1995, Lentini et al. 2005) This difference is likely partially explained by the fact that nearly all ti mber in the present study was purchased standing (and not as logs, thus requiring all firms labor split between forest and mill operations) and smaller average
129 sawmill crew size. Nevertheless it is unclear how methodological differences may have also shape d these differences, as this study relied on longterm rapport with fewer firms and detailed quantitative monitoring while previous studies utilized survey methods of a much larger number of firms (Barros and Uhl 1995, Lentini et al. 2005) The micro firms dependence on manual labor instead of oil subsidized mechanized work means costs of pushing and floating logs are relatively high compared to other harvesting costs and explains why low density (i.e., lighter, more buoyant) timbers have been traditionally preferred. Although the current analysis is based on the processing of a mix of timber species with varying wood density, the observed differences in handling and processing difficulty between high and low density species suggest that a shi ft in harvests towards either end of the spectrum would likely impact production costs. This link between wood density and labor costs is particularly relevant in the Mazago watershed where previous research has shown that current intensive reentry logging practices may be suppressing longterm yields of low wood density, highvalue species ( Virola surinamensis and Carapa guianensis ; Chapter 4). Micro Firm Profitability In general, timber production by estuarine micro firms is extremely profitable. This extremely high profitability is likely a consequence of multiple favorable factors. Besides the low stumpage, extraction, transportation and milling costs and no legal costs, as vertically integrated operations micro firms profit from both extraction and processing. Although IRRs are rarely reported elsewhere, high profitability may be common in the Amazon timber industry, with legal RIL timber extraction yielding an IRR of 35% (Bacha and Rodriguez 2007) Lastly, as Mazago smallholders have an average property size of 27 ha (Pin edoVasquez et al. 2001) most firms likely rely heavily on
130 timber purchased from other properties in the watershed, thus making the prospects of longterm high profits from harvesting own forests unlikely. Economic model elasticity analysis yielded an unprecedented look at the relative importance of production factors to firm profitability. As a labor dependent production system, labor related factors were very important but an area where little could be done to improve profitability (e.g., the current daily wage rate is already low and work days are long). Due to the contribution of processing costs to total firm costs, low quality of mill output and the importance of product price to total revenue, improvements in sawmill processing are likely to have a longterm impact on the economic viability of these micro firms. Yet, it is still remarkable that overall costs per unit volume are so low and the activity remains profitable given the low level of technology employed in this production system. Timber vs Aa Production in the Amazon Estuary The choice between investing in timber or aa for a smallholder in the Amazon Estuary is complex and yields drastically different outcomes. While timber is largely more profitable to micro firm owners than aa net yearly revenue per firm is small with a system of production that is not easily scalable. A firm's typical small size is likely what has allowed the industry to operate largely in the informal sector. Micro firms also require much larger initial investment s than aa production. Initial aa investment can be much smaller and is easily scalable by the size of area to be planted. However aa has a delay between planting and production commonly between 35 years (Hiraoka 1995) While cropping (e.g., manioc, bananas) in the Amazon estuary ensured a continuous revenue stream during this waiting period (Hiraoka 1995) cropping in the region has nearly vanished due to competition from cheaper imports (Almeida 1996)
131 While the two activities provide employment opportunities due to high labor use and low dependence on outside inputs, aa production startup and maintenance costs are almost entirely based on household labor and not capital, resulting in minimum cash outlays (Anderson and Jardim 1989) However aa product ion is highly seasonal (Munizmiret et al. 1996) making the full reliance on the activity challenging if household finances are not carefully managed. In contrast, a t imber firm s year round operations commonly require at least 45 workers and thus often require paid wages. One major disincentive for smallholders to produce timber is the challenge to operate legal l y. Current harvesti ng licensing procedures seem incompatible with small scale timber production (Hirakuri 2003, Scherr et al. 2004) While recent laws attempt to address this issue by simplifying small scale forestry licensing procedures, licensing is still very costly, requiring technical assistance that results in the dependency on outside institutional support (Hirakuri 2003). Consequently, while aa fruit harvesting is highly physically demanding and dangerous due to tree climbing, unregulated timber production involves the performance of even more dangerous tasks under an absolute lack of safety procedures and equipment. Environmentally, while aa at the intensity of planting observed in the region can be classified as forest conversion (Weinstein and Moegenburg 2005) it is not necessarily the worse alternative to timber extraction since it is an intense land use and a conversion to a forest type that still provide s some valuable environmental services (Brockerhoff et al. 2008, Paquette and Messier 2010) For an average firm extracting 532 m3 of timber yearly, operating under the legal extraction limits of 10 m3 every 10 years or 30 m3 every 30 years per ha requires a minimum management area of 532 ha.
132 On the other hand, only 12.5 to 18.6 ha of permanent aa cultivation is needed to provide the same NPV as a timber firm processing purchased trees or their own trees, respectively. This simple calculations show how the 'aaization' of the estuary (Hiraoka 1995) has the potential of changing the dynamics of human disturbance in the Amazon estuarine forests from widespread nearly ubiquitous logging disturbance ( Chapter 3 and 4) into highly intensified, albeit still forested aa production areas. Within diversified livelihood systems common in the Amazon Estuary (Anderson and Ioris 1992) it is not surprising to find timber and aa are to some degree complementary and integrated. Firstly, aa and timber are not temporally exclusive activities because aa harvests peak in the dry season when low water levels makes access to distant timber harvest areas difficult. Har vest monitoring also revealed some level of integration between the two activities. Chainsaw operators showed concern for unnecessary damage to wild aa stock and directionally felled trees away from aa clumps. Logging crews commonly felled old less productive wild aa stems to use as rails for pushing logs from forest to stream. Loggers were aware this practice was beneficial to the wild aa stock as thinning of old stems is a common practice to ensure continuous aa production (Anderson and Jardim 1989) While the $124 timber subsidy per hectare of forest converted to aa is far from sufficient to cover initial planting costs ( based on an average of 16 harvestable trees per hectare, sold standing at $7.77), many locals showed some degree of preference in converting recently logged areas into aa stands. Micro Scale Timber Production: A Poverty Driven System? The price of mic ro firm timber is limited by its low quality and quantity of production that restricts sales mostly to regional markets and principally for low income
133 housing (PinedoVasquez et al. 2001) This low price has left local firms in a challenging situation as, with the spread of aa fewer landowners are interested in selling timber given the currently low stumpage prices. A secondary effect of the spread of aa management is the increase of local wages alleged by local firm owners. With aa producers during the harvest season easily earning 23 times the daily wage rate by harvesting aa firm owners now have less bargaining power in ne gotiating wages with potential employees. While an improvement for the local workforce, wage rate increases have a large influence on the economic viability of timber micro firm operations. In the preceding analyses, all daily wage costs were calculated using the standard regional rate whether the wage was supplied by the entrepreneur's household or not. To a timber or aa entrepreneur, however, labor provided by household members often does not require cash payments and is likely valued much lower than daily wage rates as limited investment alternatives and few employment options lower the opportunity cost of household labor Feldman and Edward Taylor 2009) By alternatively computing NPV of cashflows to and from entrepreneur's household (i.e., setting household labor rate as zero and assuming two household workers available based on local observations), the relative financial attractiveness of the two activities (in terms of NPV per initial investment) changes significantly (Table 5 3). While these values show that at the household level aa management becomes much more worthwhile, these values are only valid within a limited size of aa management area that can be managed by household members. These results may partially explain why aa management is being increasingly adopted in the Amazon estuary generally at
134 scales smaller than 10 ha per household while the number of micro firms in t he region have been on a long decline (Barros and Uhl 1995, Hiraoka 1995, Lentini et al. 2005) While this research explores the economic rationale and consequences of Amazon Estuary smallholder timber and aa management, questions regarding whi ch of these two activities are more compatible with conservation goals are left unanswered. As both activities currently provide positive returns to smallholder investment, their comparative effects on landscapelevel carbon balance, erosion, plant, fish and faunal populations should be explored. If aa is deemed a better choice in balancing conservation and development goals, a program targeted at those currently pursuing timber related activities could provide loans for aa planting to help overcome startup and management costs in preproduction years. If timber is deemed the better alternative, research leading to improvements in sawmill processing technology could have large impacts in the profitability of the activity by cutting costs and improving pr oduct quality along with help in reaching farther markets Additionally, as most micro firms operate informally, assistance in legalization of the sector would likely have large impacts on timber production in the region.
135 Table 51. Economic indicators of timber and aa management Activity Production mode NPV Initial investment IRR NPV/ Investment ratio Payback period Ha of logged forest to recoup startup costs Equivalent annual annuity Timber Purchased trees $40,296 $7,451 84.00% 5.41 3 31.2 $3,179.11 Timber Own timber $60,105 $7,451 202.00% 8.07 2 22.1 $4,741.87 Timber Purchased logs $8,206 $7,451 52.00% 1.10 9 95.4 $647.39 Aca $3,230 $1,114 22.00% 2.90 8 9.0 $254.82
136 Table 52. Model parameters and their elasticities
137 Table 53. NPV of household cashflows for timber and aa management Activity Production mode NPV Initial investment NPV/ Investment ratio Timber Purchased trees $96,290 $7,451 12.92 Timber Own timber $116,099 $7,451 15.58 Timber Purchased logs $49,807 $7,451 6.68 Aca $8,898 $166 53.60
138 Figure 51. Map of study site.
139 Figure 52. Average c osts per extraction activity standardized by timber volume delivered to sawmill
140 Figure 53 Average e xtraction costs per m3 of timber delivered to sawmill by category
141 Figure 54 Sawmill volume processed daily by person hours of work
142 Figure 55 Average f irm's yearly costs and revenues (processing, forest)
143 CHAPTER 6 SYNTHESIS: DETERMINI NG THE ECOLOGICAL AND ECONOMIC VIABILI TY OF TIMBER MANAGEMENT IN THE AMAZON: A WATERSHED SIMULATION APPROACH I ntroduction I ntegrated ecological and socioeconomic watershed models have been employed to address a variety of complex land use and conservation issues (Beaulieu et al. 1998, Okumu et al. 1999, Gassman et al. 2002, Costanza et al. 2002, Sankhayan et al. 2003, Lant et al. 2005) These models permit analy sis of management alternatives and allow for the simulation of complex scenarios that help unravel underlying dynamics, interactions and limitations of study systems (Wear et al. 1996, Weinberg et al. 2002, Costanza et al. 2002, He 2003, Sankhayan et al. 2003, Machado et al. 2003) A watershed modeling approach is par ticularly wellsuited to contribute to the examination of the sustainability of tropical forest use (Rice et al. 1997, Putz et al. 2000, Richards 2000, Pearce et al. 2003) because the models provide explicit focus at spatial scales where the principal ecological and socioeconomic factors that constrain sustainability are effectively linked. In the Amazon Estuary, hundreds of family run vertically integrated micro firms harvest, transport and process timber informally to be sold at local and regional markets (Barros and Uhl 1995, Lentini et al. 2005) Consequently timber remains an important source of income for many smallholder families. At the Mazago watershed in the Amazon Estuary, f ollowing studies of community composition and timber species population ecol ogy (Chapters 2 and 3), sustainable timber management (STM) regimes for local stands have been found (Chapter 4) and the economic viability of micro firms has been explored (Chapter 5). In this chapter we integrate previous ecological,
144 management and economic models (Chapter s 3, 4, and 5) to evaluate watershed timber resource availability and use under alternate scenarios of management, legality, and production levels (Shao et al., 2005). We employed multiple forest use scenarios to address questions of sus tainability at the scale of a whole watershed (and its related local timber industry) to explore the link between ecological, economic and legal constraints to forest use and proposed management: What is likely to happen to the Mazago watershed if the local industry fails to adopt forest management guidelines ? Do federal management guidelines (FDM) included in Brazilian l aw improve longterm viability of local industry? How does a regionally derived optimal S T M management regime perform in terms of ecological and economic viability compared to federal management guidelines or extraction without management ? What are the ecological and economic consequences of legalizing the local industry? Can micro firms operate to achieve the same return on inv estments as alternate land uses in the region? M ethods The Vrzea Smallholder Timber Production System The 160 km2 Mazago watershed has a long history of timber use (PinedoVasquez et al. 2001) with current small scale timber extraction. Mazago is similar in composition and land use history to sev eral adjacent watersheds, as confirmed by regionwide inventories and surveys conducted in 2005 (Chapter 3, Fortini et al. 2006). The micro scale timber producing firms are centered around small sawmills that process timber harvested in the floodplains o f the watershed to be sold regionally (Chapter s 4 and 5). Once trees are felled, tracks are manually cleared where bucked logs are pushed over small rails made from small noncommercial stems to river edge.
145 Logs are then manually floated with the aid of ti des to the mill using float wood or larger rafts (Barros and Uhl 1995) As of 2008, 12 micro timber producing firms where installed in the Mazago watershed. Mazago Watershed Simulation M odel The watershed model is based on the integration and scaling up of a demographic population model, a stand management simulation model and a singlefirm financial returns model (C hapter s 3, 4, and 5). The underlying demographic model is based on a multi species equationbased matrix model created for 9 timber species that account for the majority of commercial volume extracted in the region over the past century as well as species that are likely t o have timber value in the future ( Chapter 3). Based on the demographic model, the stand management model uses a multi site approach to model sizedependent shifts in commercial and defective portions of each species population (Morris and Doak 2002) and incorporates the effects of density dependence, harvest damage and post harvest demographic effects in its simulation. The stand management simulation model allows for the specification of several management criteria including harvest rotation length, minimum cut diameter (MCD), intensity (1 proportion of trees > MCD left as seed trees), seedtree quality (whether or not to include def ective trees in seedtree proportion), and minimum commercial density per ha (MD; Chapter 4). The firm based financial returns model is a mechanistic model based on the detailed monitoring of extraction and milling activities, participatory monitoring of t hree firms and detailed surveys with a majority of Mazago firm owners ( Chapter 5).
146 Scaling and Integrating Precursor Models to Watershed/ I ndust ry S cale Determining mature forest extent To scale the stand management model to the Mazago watershed scale, we used an estimate of available forest area based on the classification of watershed landcover (Figure 61) Given the small size of individual palm stands, clearings and secondary forests, we used a combination of high spectral resolution Landsat TM imag ery and high spatial resolution Quickbird imagery for the classification. After attempts to classify landcover usi ng multiple statistical patternrecognition methods (e.g., pixel based classification algorithms and indices, segmentation, object based class ification methods, and crown recognition approaches) we resorted to heads up digitizing given the small size of the watershed. Initial data layers used in the digitization included Landsat TM tassel edcap wetness index (Crist and Cicone 1984) useful for upland/ floodplain forest differentiation, and a water cover map created by a custom Matlab segmentation routine applied to Quickbird imagery. Clearings, shrubdominated areas mature, secondary and palm forests were further differentiated using a Gransmidt pansharpened Quickbird image (0.6 m spatial resolution), a principal component analysis image output of Q uic kbird bands (useful for palm forest differentiation). We also used 338 ground control points collected randomly across the watershed, including nearly two hundred 40 m diameter circular plots to aid the classification. The base Quickbird image was georefer enced with a root mean squared error of 1.2 m, meaning GCPs were likely correctly located on the map. Model u pdate and i ntegrationWe scaled the single stand management model (Chapter 4) by allowing it to simulate the effects of management over the estimated mature forest area available in the watershed. At each year of the simulation, based on the management regime specified, the model calculates how much forest is needed to
147 supply the timber industry demand. While the model is not spatially explicit, it efficiently simulates the process of large contiguous forests subdivided into stands with diverse patterns of use (Figure 62) Consequently, the watershed model does not consider distancebased costs. However, marginal river transportation costs are low and are not a major c ost factor in firm operation (Chapter 5). The firm economic model was simply scaled by multiplying singlefirm inputs and outputs by the number of firms present in the watershed. The starting condition of each simulation is a large forest area of structure and composition reflecting the ~40 ha of permanent inventory plots spread in recently undisturbed areas across the watershed ( i.e., in areas with no sign of logging in the last 20 years). This is likely an optimist assumption as timber has been continuously harvested in the watershed. To partially counter this bias, from the original mature forest area we subtracted a degradation proportion equivalent to assuming all mature within 100 meters of mapped rivers and streams are not manageable (14% of watershed) following the field observation that most forests along rivers commonly have few timber trees of commercial value (e.g., older timber poor secondary forests heavily logged forests ). The importance of this degradation parameter was later assessed in our model sensitivity analyses. Once the total available management area was determined, this area was divided into two hypothetical stands, one owned by firm owners calculated as the number of firms times average property size derived from PinedoVasquez et al. (2001), and stands owned by the other approximately 100 smallholde r families residing in the watershed. At each yearly time step, previously harvested stands old enough for more
148 harvests (determined by the management cutting cycle), can have their area entirely or partially harvested again if necessary. To reflect local behavior, firms will preferentially harvest firm owned stands to avoid stumpage costs. At each level of production, the model calculates the mean volume per tree harvested based on total volume and number of individuals harvested in all harvested areas. M ean volume per tree influences extraction costs and stumpage costs as firms purchase standing timber per tree. Lastly, stumpage costs are calculated using mean volume per tree values only for the proportion of trees harvested outside of firm owned areas. A ll resulting watershed simulations used a 50year time horizon to balance between short run economic assumptions and longterm ecological consequences of management. Model O ptimization and S tochasticity Given aa fruit production is a common alternative to timber production in the Amazon Estuary (Anderson 1986, Munizmiret et al. 1996) we created a simulated annealing optimization that finds the optimal yearly timber harvests for firms in the industry to maintain a comparative worthwhile investment. At the start of each simulation the model calculates the NPV/start up costs ratio of aa fruit production in the watershed for a 50year period ( Chapter 5). This ratio is then used to estimate the necessary NPV equivalent for timber production based on average firm startup costs. To ensure NPV of timber firms equal the a a equivalent at the end of the simulation, the model optimizes industry production each year such that Re venue Costs Annualized startup cos ts Annualized Aa NPV equivalent 6 1
149 The aa NPV equivalent and startup costs were annualized using an equivalent future annual payment formula further discounted for 1 year for present value (Klemperer 1996; equation 62) where V0 is present value, r is discount rate, and n the number of payment years. These annualized values were necessary to find the industry yearly production that yielded the desired NPV at the end of the 50year simulation. p r [ V 0 ( 1 r )] [ 1 ( 1 r ) n ] 6 2 The yearly optimization considers industry production volume between 0 and maximum potential production based on saw mill processing capacity but is also bounded by watershed available timber. The model selects the industry production level that will most closely satisfy the above objective function, including no production when marginal costs are greater than marginal revenue. While we do not assume real smallholder firms perform a similarly complex calculation, this optimization is useful to evaluate whether timber production is a competitive land use option for the Mazago watershed. Once the base industry simulation model was completed, we incorporated uncertainty of underlying costs, revenues and production parameters to perform a viability analysis of the entire industry over the projected simulation period. Random values for propor tion variables (e.g., sawmill efficiency ) were modeled using the beta distribution. All other nonzero parameters had random values drawn from a normal distribution truncated at zero (e.g., mean days of sawmill operation per month). At the beginning of eac h stochastic run, the model draws values for each economi c parameter based on their mean values and standard errors. For any given watershed management scenario ( described below ), industry viability was calculated as the proportion of its
150 10,000 stochastic runs that had average firm NPV above the aa NPV equivalent for optimization scenarios or zero for business as usual scenarios. Wat ershed S cenarios A total of 10 watershed scenarios considered variation in management regimes, local industry timber consumption and informal and legalized modes of production (Table 6 1). Forest management regimes included extraction with no management, federal management as required by Brazilian law (FDM), and the optimal sustained timber management regime (STM) based on longterm projections of population growth and timber yield for the region (Table 6 1; Chapter 4). The nomanagement scenario was used to simulate current common practices in the watershed and is based on extensive fi eld monitoring and interviews (Chapter 4 and 5). It assumes small minimum harvest size, no commercially viable seed trees (i.e., 100% harvest intensity), and a very short harvest cycle that approximates continuous re entry logging. While not all watershed inhabitants, especially some longterm re sidents, allow such levels of intense harvests in their private plots, most inhabitants harvest or sell standing timber without concern for tree size, species used or remaining stock. Our federal management scenarios may lead to conservative harvests since the Brazilian Federal Law includes a special clause that allows harvests of 3 trees per ha in floodplain forest areas (instead of the standard 10 m3 per ha limit). However, we did not consider this special clause in our model since its approval is done in a caseby case basis, and depends on volumetric studies conducted by the agency enforcing the law. Furthermore, w e were interested in the effectiveness of the federal law that applies to more than 95% of timber harvests in the Amazon (Lentini et al. 2005) Watershed scenarios varied in yearly timber industry consumption by either including constant business as usual (BAU)
151 timber consumption rates derived from local firm monitoring or dynamic consumption rates based on our NPV optimizing routine. Since estuarine smallholder firms operate informally without regards to Brazilian environmental, labor and fiscal laws ( Chapter 5, Barros and Uhl 1995), we created watershed scenarios that included the additional costs of legalization of timber production. These costs include inventory costs for each years harvest area, costs of management plan elaboration, wage legal burden (payroll taxes and related legal obligations), costs of mandated safety equipment, training costs and state sales tax. The wage legal burden, inventory, safety and training costs were based on inflationdiscounted values from Holmes et al (2002) Management plan elaboration costs were based on consultations with the Brazilian Forest Service and companies that provide the service to small and community sized operations ($16.84/ha or $31.09/ha if including inventorying). Lastly, since smallholders operating under informa lity generally sell tim ber at low prices (Chapter 5, Scherr et al. 2004) we included a timber sale price adjustment for all scenarios pondering legalization of timber production. This legal timber price was estimated from the sale value of floodplain forest timber by a communi ty forestry project in Amazonas (Humphries 2010) The influence of legal timber price on industry viability was explored in subsequent sensitivit y analyses. Model O utputs For each watershed scenario the model created multiple outputs including species size distributions for each resulting stand, detailed per year costs and revenues. To quantify and contrast the ecological consequences of the local timber industry on watersheds forests, for each simulation the model calculated population growth rates for species (lambdas, ), the proportion of available forest area harvested, total volume
152 harvested, the average number of harvests per ha of available forest area and total harvested area. To differentiate changes in forest structure due to contrasting management, the model also calculated the proportion of initial available area experiencing a 50% decline in stand structure parameters including total number of individuals, harvest species volume, number of large trees, number of large commercial grade trees. Besides simple elasticity and correlation analyses between model parameter and model outcome to evaluate model performance, we chose a select number of variables of interest for a detailed sensitivity analysis : interest rate; species used; area owned by firms; number of firms in watershed; proportion of area degraded; sawmill efficiency ; and timber price. The importance of these variables was explor ed by changing them to a set of values representing a their likely range and including values of particular interest (Table 62). R esults Scenario Outcomes What are the prospects for the Mazago timber industry operating informally under current levels of timber demand? ( S cenarios 1, 3, 7) Model simulations show that NPV is high for the industry when operating informally under current levels of timber demand, whether without management, FDM or STM ( S 1, S3 S7 ; Table 63 ). Average firm NPV was highest for STM ($47,555) and FDM ($36,669) compared to no m anagement ($23,966). Due to per area harvest volume limits, the FDM scenario leads to the entire available area in the watershed being harvest ed every cutting cycle of 10 years (i.e., 5 harvests per ha of manageable forest in 50 years). The STM scenario also leads to the entire watershed being
153 harvested, albeit under a less frequent regime (3.5 harvests per ha). In contrast, under no management only 47% of the available watershed forest is harvested. However, these intense harvests lead to worse ecological consequences in terms of reduced average population growth rates and all areas harvested showing substantially altered population structure at the end of the 50year projection period. While both STM and FDM showed stable or increasing population growth and no area being significantly structurally altered, the STM scenario outperformed the legal scenario in terms of profitability and greater protection to populations with few individuals. Consequently, stochas tic simulations show that the probability of longterm industry viability is largest for STM (99 % ) but closely followed by FDM (95% ). The lack of management drops the probability of industry persistence to 0.77% What are the prospects for industry operating informally seeking financial returns similar to Aa fruit production? (S cenarios 2, 5, and 9) Given average firm start up costs, firms would need a NPV of $26 300 to have a similar profitability to aa fruit production. Model results show this is only possible if the industry uses FDM or STM guidelines. Without management, when the industry seeks higher yearly profits it runs out of unharvested areas within 15 years and must reharvest areas not yet recovered from recent intense harvests. Under no management, harvesting trees down to small sizes also lead to more costly future harvests as stumpage paid per tree yields less volume to be processed and sold. The final result is that without management the industry crashes yielding a low average NPV of $4, 402, with several years of no production due to high marginal costs and the entire management area being significantly affected structurally (Table 63) In contrast, by
154 using either FDM or STM guidelines, timber production remains profitable compared to e xtraction with no management during the 50year projection while keeping watershed forests structurally healthy. However, the STM scenario leads to slightly better results since it requires less total volume (3.1x105 vs 3.5x105, respectively) and reduced n umber of harvests per ha (2.07 vs 4.20, respectively). Consequently, the probability firms in the industry will keep an average NPV equal or higher to $26, 300 is highest under STM (0.86), followed by FDM (0.52), and very low if the industry uses no managem ent (0.05). What is effect of legality on the viability of timber production by Mazago smallholders? ( Scenarios 4, 6, 8,10) All legal scenarios exhibited similar legalization costs. Using the FDM BAU scenario as example, average yearly costs of legalizati on per firm was 11% ($1, 905) of average yearly operational costs. This cost per firm was divided among management plan elaboration ($1, 184.88), inventorying ($296.23), training ($245. 39), block layout ($153.24), and safety ($25.49). Legal costs per ha of h arvests was $27.08 and would be slightly higher for the Mazago industry if it opted to hire consultancy firms that also conduct all necessary fieldwork ($31.45/ha). The added legalization costs changed the profitability of all management scenarios. Under BAU production and FDM, average firm NPV goes from $36, 669 to $2, 429, making timber production an unprofitable investment. STM under BAU also suffers a large decrease in NPV by legalization, but fares better than FDM by still resulting in a positive NPV ( $15, 894). Consequently, if firms continue to produce at similar levels to current volumes, the probability of industry persistence under legality is highest for STM (0.73) than FDM (0.27). When optimizing for aa NPV equivalence
155 under l egalization, FDM only reaches a NPV slightly above 0 falling far short of the necessary $26,300 value and leading to many years without production. Legal STM also fails to reach NPVs equivalent to aa but reaches an NPV much higher than FDM while avoiding years without production ($21,489). Consequences of Changing Factors of P roduction Interest rateAs expected, increasing interests rates from the current 6% to 25% leads to drastic reductions in NPV for all scenarios. Apart from the optimized legal FDM scenario, NPVs o f all scenarios remained positive ev en at the highest interest rate. SpeciesThe exclusion of M. paraensis from harvests is catastrophic for all watershed scenarios. For scenarios with no management, h ad the industry not changed recently to use M. paraensis it would face a bleak future with all available forest s harvested, NPV near zero, and a large number of harvests per ha leading to all watershed forests suffering large structural changes by the end of the simulations. For FDM NPV drops substantially in all cases but only down to negative values when combined with legalization ( S4 and S6 ). Exclusion of M. paraensis from FDM scenarios also leads in most cases to an increase of years without production, but no longterm structural consequences. Due to higher DCM, SFM scenarios are entirely dependent on M. paraensis dominant share of large trees. Without the species, NPV drops from generally high values to below zero with most years without production due to timber shortages. In contrast, the exclusion of the fast growing but currently scarce V. surinamensis has little influence on most scenario outcomes. Area owned by firms In BAU scenarios, increases in firmowned forest area increases average NPV, allowing NPV to be positive for FDM legal BAU scenario (S 4 ) when firm area exceeds twice the current estimate (54 ha). Except for that scenario,
156 firms can operate with a positive NPV even with no firm owned area, suggesting that firms are not entirely dependent on timber from own properties to maintain profitability. In optimization scenarios where firms failed to be as profitable as aa palm fruit production ( S2 S6 S10 ) increasing firmowned forest area to 200 ha (a size larger than all but one property in the watershed) was still not enough to make timber production as profitable as aa fruit production. For optimization scenarios where aa NPV equivalence was reached (S5 and S9) additional firmowned area allowed for reducing total volume harvested and the number of harvests per ha for watershed forests. Number of firms Surprisingly, average NPV remains unchanged with an increased number of firms in the watershed under the informal BAU scenario with no management. However, number of harvests per ha and proportion of area suffer ing large structural changes increase with each additional firm (Figure 6 3). For all other FDM and STM BAU scenarios, NPV falls gradually with an increasing number of firms in the watershed. For scenarios with management, despite the decreases in NPV and increase in number of harvests per ha with an increase in number of firms only a small portion of watershed forests (<10%) suffers major structural changes by the end of simulations. Percent of area degradedFor nearly all BAU scenarios, with increasing degraded forest area not immediately available for management, NPV decreases as the number of years without operation increase due to timber shortages. Only the no management informal scenario has average NPV immune to decreasing forest area available to management ( S 1). However, in this scenario, with increased area degraded
157 remaining areas are more frequently harvested and proportion of watershed suffering large structural changes increase. Similarly to BAU scenarios, under optimizing scenarios NPV decr eases and number of shortage years increases with area degraded but with STM scenarios being less affected than FDM and no management scenarios. As with other variables, forests suffer little to no large structural changes under FDM or STM at all levels o f watershed degradation. Mill efficiency Because mill processing was the large contributor to total operational costs, mill efficiency had one of the largest impacts on scenario viability. For all BAU scenarios, average firm NPV is positive at the high efficiency value representative of average sawmill efficiency in the Amazon (Lentini et al. 2005) including those incorporating leg alization costs. For nearly all optimization scenarios, at the low mill efficiency level representative of average efficiency for all micro firms of the Estuary (Lentini et al. 2005) marginal costs exceed marginal revenues resulting in nearly no harvests for most years. Above the average mill efficiency observed in the watershed, optimization scenarios resulted in fewer years without production and fewer harvests per ha. Timber priceEspecially relevant to the legalization scenarios, timber prices had a large effect on industry profitability. At the high price estimate ($315.34 per m3 of sawn wood) NPVs of all scenarios were multipli ed well above the aa NPV equivalent of $26, 300. T he small difference between current and legal price used ($92.35 vs $ 112.00 per m3 of sawn wood) was enough to make NPV s negative in all legal scenarios ( S4, S6, S8, S10 ). For STM and FDM optimizing scenarios without legalization costs, average NPV remained above the aca NPV equivalent regardless of
158 timber price. For optimization scenarios, with increasing price the necessary number of harvests per ha decreased steeply, changing, for instance, from 5 to <1 between low and high legal price for STM and FDM legal scenarios ($112.00 vs $ 315.34; S6 and S10 ). D iscussion The B e nefits of Forest M anagement Our scenario simulations show that on a watershed/ local industry scale, forest management in general yields better ecological and economic outcomes than extraction with no management. Federal management guidelines provide a clear improvement over no management scenarios, but the STM guidelines designed for the Mazago watershed in previous analyses ( Chapter 5) fares even better. In general, management improves the prospects for longterm profitability, consequently increasing the probability of industry persistence in all cases. Conservation wise, manageme nt results in extensive harvests that allow for faster population recovery while preventing large changes in forest structure. As shown in the no management profit optimizing scenario, a more aggressive profit seeking industry can lead to population crashes. In contrast, STM guidelines can be what makes legalization possible under current levels of production. Importance of Model Parameters Economic factors beyond forest management (e.g., price, sawmill efficiency) were very important in defining industry v iability, bridging the difference in several management scenarios between industry failure and persistence. While these results illustrate the importance of the proper consideration of economic factors in efforts to expand the area under management in tropic forests increased profitability alone is not
159 a recipe for SFM (Rice et al. 2001) Ecological factors (e.g., species used, waters hed degradation proportion) also had a large effect on scenario outcomes. Partially due to the reduced diversity of flooded forests (Ferreira and Stohlgren 1999) the exclusion of the predominant species, M. paraensis from watershed scenarios greatly reduced the probability of industry longterm viability. The importance of M. paraensis to the future prospects of the local industry is also likely tied to the long history of sequential timber species depletion in the region ( Chapter 3). Given the species studied account for 62% of basal area of trees >= 30 cm DBH in Mazago forests and that most other species seem to lack merchantable wood properties ( Fortini, unpublished data), M. paraensis is one of Mazagos last chance to make forest management work. Industry Economic V iability Our study supports past findings showing that great profitability is possible for individual firms operating informally in the watershed ( Chapter 5). However, using a singlefirm economic model detached from estimates of avai l able forest area and species ecology can lead to overestimates of firm profitabil ity and industry viability. In our study we tie economic production to limited timber resources, the forests ability to regenerate, changes in harvests from shifts in species abundan ce and size distributions, and a dynamic estimate of timber produced from firm owned forests. Under these restrictions, most scenarios where the industry attempts to achieve the same profitability as aa fruit production ran into the ecological limits of the watershed, a fact that would otherwise be concealed from a simple economic analysis However, firm profitability aside, the labor dependent nature of timber use by micro firms represent a major source of employment to a local work force that has few other economic opportunities (Chapter 5).
160 Industry Ecological V iability The majority of past research in tropical forests addresses the issue of sustainability of use and management from a single stand perspective (Osho 1995, Gourlet Fleury et al. 2005, Hao et al. 2005) Our results show that we m ust keep in mind the dif ference be tween stand and watershed/landscape ec ological sustainability. A stand may have the potential to provide sustainable yields, but the watershed/landscape may still not have enough area to make a shift to STM possible. Ecologically despite the sequential depletion of some timber species in the region (Chapter 3), stand conditions and favorable population dynamics still allow for a l evel of sustainable production (Chapter 4). Using our watershedscale approach, with further degradation of waters hed forests the ecological resource base necessary to ensure SFM is threatened (Figure 6 4). In that respect, our results show management is crucial to safe guard against further forest degradation. Finally, due to lack of long term ecological monitoring data and computational limitations, our model only incorporates economic stochasticity, which likely underestimates the importance of underlying species ecology to longterm industry persistence The Consequences of Legalization L egalization cannot be viewed simply as a costly bureaucratic environmental licensing requirement Legalization offers benefits such as increased workforce safety and benefits and is currently tied to management guidelines that were shown to be very effective in improving ecological and economic viability of timber production in the watershed (Chapter 4) Nevertheless, the inadequacy of forest management legislation to smallholder and community enterprises is a longstanding root of informality in the sector (Kaimowitz 2003, Scherr et al. 2004) The additional costs of legalization
161 primarily fro m inventorying and management plan elaboration greatly reduced profitability and consequently lowered industry longterm viability of all scenarios with and without management. As a result, in scenarios were profits were optimized to reach equivalence to a a fruit harvests, forest use intensified greatly to compensate for larger costs (Figure 6 5). As an example, under the STM profit optimizing scenarios harvests have to nearly double to compensate for extra legalization costs, lowering probability of industry persistence from 0.86 to 0.19 while yielding profits below those expected from aa fruit production. The issue of undervalued tropical timber is a known barrier to forest management adoption (Richards 2000) In our study, the viability of all legalization scenarios relied heavily on the legalized local industry having access to better prices than currently low timber prices. Perhaps the largest challenge to legalization of timber use in Mazago and similar watersheds is that, due to lack of viable mechanisms for smallholder legalization (d'Oliveira 2000, Scherr et al. 2004) l egal scenarios assume a cooperative approach in which firms share legalization costs and coordinate their activit ies across multiple smallholder property boundaries. While progress is slowly being made in terms of legal support for community management in tropical forests, with 400,000 smallholders in Amazon forests alone, the lack of viable legal mechanisms for smal lholder timber use is a glaring omission (Nepstad et al. 2009) In the few places where simplified management plans are required, care must be taken not to compromise long term sustainability with potentially over simplified management guidelines devoid of ecological principles (Keller et al. 2007)
162 Prospects for M anagement Whether legalized or not, forest management in Mazago should be of interest to forest users and conservationists alike, a finding that is clearly contrasted with a general lack of management in the region. The low rates of management adoption in tropical forests have mystified forest managers and ecologists (Putz et al. 2000) As our model only contemplates firm activity in the watershed, it does not reflect the pattern of firm mobility documented in upland Amazonian forests (S tone 1998) W ith firm mobility, even micro firms can move from watershed to watershed following a pattern of forest depletion. In fact a few Mazago firm owners have moved to the region in the last 10 years from timber depleted islands down river Unfortunately, as firms continue to operate without restraint, effective management area decreases thus reducing the prospect of future management. Under this self feeding loop, the present industry (extracting timber informality and without management) can avoid the negative consequences of increasi ng forest degradation by harvesting remaining forests more frequently. In contrast, this decrease in effective management area will lead to the reduced probability of industry persistence if the industry tries to adopt management such as the federal management guidelines that require longer harvest cycles and per hectare harvest limits (Fig ure 6 6). Our research demonstrates that conceptually simple interdisciplinary models can help to find management options and explore their projected consequences at a watershed/landscape scale. With better longterm monitoring of forest use and responsive forest managers, similar models could be a key component in adaptive management for SFM in the tropics (McGinley and Finegan 2003) As we show in our results, such models can lead to optimized management regimes that yield better
163 economic and ecological outcomes (Chapter 4) that consider regional specific community composition and ecology (Chapter 2 and 3). Our past research shows that the ecological potential for sustainability was likely present in Mazago from the start (Chapter 2 and 3). H owever, this potential is hidden by a long history of mismanagement (Chapter 3) undervalued timber prices (Chapter 5) and lack of adequate legislation and government support In that respect, the search f or SFM is not simply a search for a hidden technical solution. While the ecologically based management is a critical component of SFM, action must be taken that counters the myriad of factors beyond forest canopies that preclude SFM in the first place. The unfortunate irony is that increasing government efforts to restrict informal timber use in the region suggest timber production will likely be phased out within a few years closing a door to a potentially sustainable model of forest management in the Amazon.
164 Table 61. Watershed management scenarios Scenario Management type Industry output Legal Harvest intensity M in cut diameter ( cm DBH) Min density (n/ha) High quality seed trees Length harvest cycle ( years ) Per ha harvest limit (m 3 /ha) S1 No_mgm Inf BAU None BAU n 1 30 0 n 5 S2 No_mgm Inf Opt None Optimized n 1 30 0 n 5 S3 Fd_mgm Inf BAU Federal BAU n 0.9 50 0.03 n 10 10 S4 Fd_mgm Leg BAU Federal BAU y 0.9 50 0.03 n 10 10 S5 Fd_mgm Inf Opt Federal Optimized n 0.9 50 0.03 n 10 10 S6 Fd_mgm Leg Opt Federal Optimized y 0.9 50 0.03 n 10 10 S7 STM Inf BAU STM BAU n 0.5 60 1 y 10 S8 STM Leg BAU STM BAU y 0.5 60 1 y 10 S9 STM Inf Opt STM Optimized n 0.5 60 1 y 10 S10 STM Leg Opt STM Optimized y 0.5 60 1 y 10
165 Table 62. Parameters and values used in model sensitivity analyses Parameter Values Description Interest rate 0.0679*, 0.1, 0.15, 0.2, 0.25 Species used All*, Mora Virola Excluded either Mora or Virola to assess the importance of the two most important yield species in the watershed Area owned by firms 0, 27*, 54, 100, 200 Number of firms in watershed 6, 9, 12*, 15, 18 Proportion of area degraded 0.14*, 0.2, 0.3, 0.4, 0.5 From current low estimate of degradation to a high degradation estimate Sawmill efficiency 0.28, 0.37*, 0.42 0.28average for Amazonian micro firms; 0.42average for Amazonian mills Timber price (U$/m3) 92.35, 112, 315.34 $92.35 current timber valeu; U$112price floodplain community forest operation sell legal timber; $315.34Brazilian Forest Service price estimate for low grade timber parameter value for deterministic model
166 Table 63. Watershed management scenario outcomes S1 No_mgm Inf BAU S2 No_mgm Inf Opt S3 Fd_mgm Inf BAU S4 Fd_mgm LegBAU S5 Fd_mgm Inf Opt S6 Fd_mgm LegOpt S7 STM Inf BAU S8 STM Leg BAU S9 STM Inf Opt S10 STM Leg Opt 0.993 0.995 1.000 1.000 1.000 1.001 1.000 1.000 0.999 1.000 Prop of available area harvested 0.47 1 1 1 1 1 1 1 1 1 Total volume harvested (M3) 4.5E+5 3.6E+5 4.2E+5 4.2E+5 3.5E+5 4.2E+5 4.5E+5 4.5E+5 3.1E+5 5.6E+5 Average firm NPV (U$) 23966 4402 36669 2429 26306 1378 47555 15894 26306 21489 Years without production 0 18 0 0 0 25 0 0 0 0 Largest interval without production 0 4 0 0 0 5 0 0 0 0 Mean # of harvests per ha of available area 0.81 2.37 5 5 4.2 5 3.51 3.51 2.07 4.83 Mean # of harvests per ha of harvested area 1.74 2.37 5 5 4.2 5 3.51 3.51 2.07 4.83 Prop available area w/ 50% size 0.47 1 0 0 0 0 0 0 0 0 Prop available area w/ 50% 0.47 1 0 0 0 0 0 0 0 0.08 Prop available area w/ 50% 0.47 1 0 0 0 0 0 0 0 0 Prop available area w/ 50% commercial trees 0.47 1 0 0 0 0 0 0 0 0 Probability of longterm industry viability 0.77 0.05 0.95 0.27 0.52 0.01 0.99 0.73 0.86 0.19
167 Figure 61. Map of Mazago watershed landcover Figure 62. Graphical representation of simulated yearly harvests on watershed forests
168 Figure 63. The consequence of local industry size to watershed scenarios with business as usual (BAU) informal production. White no management, grey federal management guidelines (FDM), black regionally derived sustainable tim ber management guidelines (STM).
169 Figure 64. Decrease in the probability of industry persistence with increasing watershed areas unavailable for management under alternate profit optimizing forest management scenarios. Circles FDM, squares STM; Whit e informal production, black legal production.
170 Figure 65. Consequence of adopting legalization for watershed scenarios with firms seeking aa profit equivalence while adopting federal management guidelines (FDM) and regionally derived sustainable timber management guidelines (STM). Note that only under informal production do profits reach the aa equivalent value of U$ 26,302.
171 Figure 66. Decrease in the probability of industry persistence with increasing watershed areas unavailable for management under business as usual (BAU) informal production. White no management, grey federal management guidelines (FDM), black regionally derived sustainable timber management guidelines (STM).
172 APPENDIX SPECIES LIST AND ABU NDANCE FOR MAZAGO AND IPIXUNA SAMPLE PL OTS Abundance values r eported as average number of individuals per hectare and standard errors. Abundance of understory individuals is reported in thousands of individuals per hectare. DBH >= 5 cm DBH >= 30 cm Understory Species Common name Family Mazago Ipixuna Mazago Ipixuna Mazago Ipixuna Spondias mombin L. tapereba Anacardiaceae 2 (1) 14 (4) 1 (0) 8 (2) 7 (0) 13 (1) Tapirira guianensis Aubl. tatapiririca Anacardiaceae 12 (0) Guatteria inundata envireira Annonaceae 1 (0) Guatteria poeppigiana Mart. envira preta Annonaceae 4 (1) 10 (2) 1 (0) 2 (1) 13 (0) Ambelania acida pipeira Apocynaceae 9 (0) Aspidosperma desmanthum Benth.ex.Mull Arg. pau de arara Apocynaceae 2 (1) 2 (1) 1 (0) Malouetia tamaquarina (Aubl.) A.DC. molongo Apocynaceae 1 (0) Dieffenbachia cf. seguine (L.) Schott. aninga para Araceae 13 (3) Philodendron sp taj Araceae 392 (48) 281 (137) Astrocaryum gynacanthum Mart. munbaca Arecaceae 3 (0) Astrocaryum murumuru Mart. murumuru Arecaceae 78 (7) 281 (28) 1 (0) 2968 (144) 9300 (488) Attalea excelsa Mart. urucuri Arecaceae 7 (3) 5 (2) 60 (10) Bactris maraja Mart. maraj Arecaceae 70 (8) 251 (30) Euterpe oleracea Mart. aa Arecaceae 403 (84) 566 (164) 1538 (200) 1970 (100) Geonoma aspidiifolia ubim Arecaceae 151 (15) 84 (0) Manicaria saccifera Gaertn. buu Arecaceae 3 (0) 50 (0) Oenocarpus distichus Mart. bacaba Arecaceae 3 (0) Socratea exorrhiza (Mart.) Wendl. paxiuba Arecaceae 2 (0) 7 (0) 20 (1) 64 (8) Tabebuia sp ceru Bignoniaceae 1 (0) Bombax munguba Mart. et Zucc. munguba Bombacaceae 1 (0) 3 (2) 1 (0) 3 (2) 3 (0) Ceiba pentandra (L.) Gaertn. samauma Bombacaceae 1 (0) 1 (0) Matisia paraensis Huber. cupuaurana Bombacaceae 8 (4) 1 (0) 7 (0) Pachira aquatica Aubl. mamorana Bombacaceae 4 (1) 1 (0) 2 (1) 7 (0) Quararibea guianensis Aubl. inajarana Bombacaceae 14 (5) 27 (3) Protium sp breu Burseracea 3 (0) 382 (76)
173 Protium pubescens Ducke. breu branco Burseraceae 6 (2) 6 (1) 2 (0) 7 (0) 27 (3) Campsiandra laurifolia Benth. acapurana Caesalpiniaceae 8 (3) 1 (0) 2 (1) Crudia oblonga Benth. iperana Caesalpiniaceae 2 (1) 2 (0) Cynometra spruceana Bth. pau ferro Caesalpiniaceae 2 (1) 1 (0) 2 (0) 7 (0) Macrolobium pendulum Willd. Ex. Vog. ingarana Caesalpiniaceae 11 (7) 2 (0) 13 (0) 40 (5) Mora paraensis Ducke. pracuuba Caesalpiniaceae 23 (12) 7 (3) 472 (53) Swartzia longsdorffii Raddi patroneira Caesalpiniaceae 1 (0) Swartzia racemosa pacapea Caesalpiniaceae 28 (6) 1 (0) 5 (2) 479 (24) Cecropia palmata Willd. embauba Cecropiaceae 2 (1) 4 (2) 3 (1) Licania heteromorpha Benth. macucu Chrysobalanaceae 23 (8) 32 (5) 13 (5) 27 (4) 1082 (90) 429 (28) Licania kunthiana H. F. cariperana Chrysobalanaceae 2 (0) Licania macrophylla Benth. anoera Chrysobalanaceae 15 (10) 4 (3) 50 (0) Parinari excelsa S. parinari Chrysobalanaceae 6 (2) 4 (2) 3477 (1050) 328 (157) Calophyllum brasiliense Cambess. jacareuba Clusiaceae 2 (2) 3 (1) 3 (0) 20 (0) Caraipa grandiflora Mart. tamaquare Clusiaceae 2 (1) 1 (0) Clusia grandiflora cebola brava Clusiaceae 7 (3) Licaria mahuba (Kuhlm & A. Samp) Kosterm. anani Clusiaceae 2 (1) 201 (11) 10 (0) Rheedia macrophylla (Mart.) Pl. et Jr. bacuri pari Clusiaceae 1 (0) 40 (3) Buchenavia ochroprumna Eichler tapacu Combretaceae 3 (2) Combretum cacoucia Excell&Sandw ioioca Combretaceae 34 (8) 657 (62) Terminalia dichotoma G. Meyer cuiarana Combretaceae 1 (0) 1 (0) Terminalia guianensis Aubl. cinzeiro Combretaceae 4 (3) 4 (3) Commelina sp maria mole Commelinaceae 844 (31) Tetracera cf. willdenowiana cipo de fogo Dilleniaceae 7 (2) Alchornea glandulosa Poepp. E.Endl. tamanqueira Euphorbiaceae 1 (0) 1 (0) Croton sp pau santo Euphorbiaceae 1 (0) Hevea brasiliensis Mull. Arg. seringueira Euphorbiaceae 5 (1) 3 (1) 114 (6) Hura crepitans L. assacu Euphorbiaceae 4 (0) 2 (0) Mabea pulcherrima Muell. Arg. faveira Euphorbiaceae 2 (1) 2 (1) 7 (0) Manihot subscandens maniva de veado Euphorbiaceae 7 (0) Sapium lanceolatum Hub. curupita Euphorbiaceae 2 (1) 3 (1) Ormosia macrocalyx Ducke tento Fabaceae 1 (0) 3 (2) 1 (0) 1 (0) 20 (3) Ormosia smithii Rudd tento branco Fabaceae 2 (0) Platymiscium filipes Benth. macacauba da vrzea Fabaceae 8 (3) 3 (1) 5 (2) 2 (0) 57 (18) 3 (0)
174 Pterocarpus amazonicus Huber. mututi Fabaceae 11 (3) 2 (1) 1866 (179) Pterocarpus officinalis Jacq. mututirana Fabaceae 3 (1) 3 (1) 7 (0) Ilex sp catingueira Fagaceae 38 (14) 1 (0) Banara guianensis Aubl. andorinha Flacourtiaceae 1 (0) Hernandia guianensis Aubl. ventoza Hernandiaceae 1 (0) Salacia sp1 cipo capa bode Hippocrateaceae 4 (1) Salacia sp2 cipo castanha de v Hippocrateaceae 1 (0) Saccoglotis guianensis Benth. var. guianensis uxirana Humiriaceae 2 (1) 2 (1) 1 (0) 1 (0) Dendrobangia boliviana Rusby caferana Icacinaceae 4 (2) 2 (1) 302 (141) Emmotum fagifolium Desv. ex Hamilt. muiraximb Icacinaceae 1 (0) Poraqueiba sericea Tul. magonalo Icacinaceae 1 (0) 1 (0) Aniba puchuryminor (Mart) Mez. louro amarelo Lauraceae 2 (1) 1 (0) Licaria mahuba (Kuhlm & A. Samp) Kosterm. mauba Lauraceae 5 (2) 4 (1) 2 (1) 3 (1) 107 (11) 101 (21) Ocotea canaliculata (Rich.)Mez. louro pimenta Lauraceae 1 (0) Ocotea sp louro Lauraceae 3 (1) 10 (9) 3 (0) 171 (13) 20 (7) Ocotea sp louro preto Lauraceae 1 (0) 2 (1) 2 (1) Ocotea sp louro branco Lauraceae 2 (2) Eschweilera tenuifolia (Berg.) Miers. matamata Lecythidaceae 1 (0) Gustavia augusta L. jeniparana Lecythidaceae 24 (0) 60 (0) 127 (0) Vyrsonima sp. muruci Malpigiaceae 1 (0) Calathea ornata Group. cauau marantaceae 13 (3) Ischnosiphon leucophaeus (P&E)Koern. guarum canela Marantaceae 1042 (187) Mouriri acutiflora Naud. camutim Melastomataceae 7 (2) 4 (3) 17 (1) 27 (3) Carapa guianensis Aubl. andiroba Meliaceae 22 (5) 1 (0) 11 (3) 181 (8) Carapa sp andiroba jaruba Meliaceae 1 (0) Cedrela odorata L. cedro Meliaceae 1 (0) 1 (0) 3 (0) 10 (0) Guarea sp culho de mucura Meliaceae 2 (0) Trichilia paraensis C.DC. jatauba Meliaceae 3 (1) 1 (0) 1 (0) 1 (0) 10 (0) Trichilia surinamensis (Miq.) C.DC. marajoo Meliaceae 30 (8) 17 (8) 10 (4) 1 (0) 482 (40) 1149 (195) Inga alba (SW) Willd. inga xixica Mimosaceae 1 (0) 6 (4) 3 (0) 452 (0) Inga cayenensis Benth. inga peludo Mimosaceae 3 (0) Inga cinnamomea Spruce ex. Benth. inga branco Mimosaceae 20 (0) 6 (0) 10 (2) Inga edulis Mart. inga cipo Mimosaceae 7 (0) Inga lenticifolia Benth. inga preto Mimosaceae 17 (6) 87 (0)
175 Inga pilosula (L.C.Rich) Macb inga cavalo Mimosaceae 3 (0) Inga sp inga Mimosaceae 3 (1) 7 (4) 2 (0) 50 (7) 499 (35) Pentaclethra macroloba (Willd) O. Kutzen pracaxi Mimosaceae 61 (9) 13 (4) 372 (27) Pithecellobium inaequale (H.B.K.) Benth. jaranduba do mato Mimosaceae 1 (0) 7 (0) Stryphnodendron guianense (Aubl.) Benth. angelim da varzea Mimosaceae 1 (0) 1 (0) 3 (0) Zygia juruana (Harms) L. Rico inga cururu Mimosaceae 29 (6) 60 (6) Siparuna guianensis Aubl. capitiu Monimiaceae 2 (0) Chlorophora tinctoria (L.) Gaud. cutiti Moraceae 2 (1) Ficus anthelminthica quaxinguba Moraceae 2 (0) 3 (1) 1 (0) Ficus pertusa C.F. apui Moraceae 3 (1) 10 (3) 2 (1) 3 (1) Olmedia caloneura Huber. muiratinga Moraceae 2 (1) 3 (1) 1 (0) 3 (1) 13 (0) 291 (62) Sorocea duckei W. Burger camurim Moraceae 2 (1) 1 (0) Virola surinamensis (Rol.) Warb. virola Myristicaceae 7 (2) 10 (5) 2 (1) 3 (1) 268 (26) 201 (24) Uknown sp jeju Myrsinaceae 1 (0) 4 (2) 3 (0) 228 (22) Calyptranthes speciosa Sagot. goiabarana Myrtaceae 7 (6) 53 (19) 1 (0) 1203 (72) Pariana campestris Aubl. taboquinha Poaceae 2502 (294) Triplaris surinamensis taxi Poligonaceae 7 (2) 2 (0) 1 (0) 2 (0) 13 (0) Polybotrya caudata Ktze. samambaia polipodiaceae 258 (27) 3 (0) Alibertia sp ginja Rubiaceae 2 (1) Bothriospora corymbosa (Benth) Hook. pau macaco Rubiaceae 1 (0) Callycophyllum spruceanum Benth. pau mulato Rubiaceae 58 (7) 33 (24) 45 (5) 12 (4) Chimarhis barbata Ducke canela de velho Rubiaceae 312 (0) Genipa americana L. genipapo Rubiaceae 1 (0) 1 (0) Palicourea cf. calophylla DC. caf bravo Rubiaceae 3 (0) Zanthoxylon sp laranjinha Rutaceae 40 (12) 2 (0) 539 (24) Allophylus amazonicus (Martius) Radlkofer olho de tucano Sapindaceae 1 (0) Talisia sp gogo guariba Sapindaceae 1 (0) 3 (0) Crysophyllum argenteum subsp auratum (miq.) Penn. guajara branco Sapotaceae 9 (2) 3 (1) 121 (7) Crysophyllum excelsum Huber. guajara Sapotaceae 24 (14) 2 (0) 1625 (128) Crysophyllum sp1 guajara grande Sapotaceae 2 (1) 2 (1) 47 (0) Crysophyllum sp2 guajara vermelho Sapotaceae 1 (0) 3 (0) Pouteria caimito (prev. laurifolia Mart.) abiu seco Sapotaceae 3 (0) Pouteria sagotiana (Baill) Eyma. maaranduba da vrzea Sapotaceae 7 (1) 2 (1) 27 (10) Pouteria sp abiurana Sapotaceae 5 (3) 4 (3) 208 (37)
176 Sarcaulus brasiliensis (ADC) Gyma jarai Sapotaceae 11 (3) 2 (1) 104 (8) Simaba multiflora caximbeira Simaroubaceae 14 (9) 1 (0) Guazuma ulmifolia Lam. mutamba Sterculiaceae 1 (0) Herrania mariae (Mart.) Dene. cacau jacare Sterculiaceae 2 (1) 3 (1) 17 (5) 74 (2) Sterculia speciosa K.Schum caputeiro Sterculiaceae 2 (1) 4 (2) 1 (0) 1 (0) 3 (0) Theobroma cacao L. cacau Sterculiaceae 3 (1) 28 (10) 10 (0) 34 (2) Apeiba aspera Aubl. pente de macaco Tiliaceae 3 (1) 1 (0) Uknown sp areu areu 6 (2) 1 (0) Uknown sp carip 1 (0) Uknown sp inga amarelinho 1 (0) Uknown sp marup 1 (0) Uknown sp bariri 881 (70) Uknown sp isqueiro 2 (0) 1 (0) Uknown sp 2 (1) 2 (0) 1 (0) 13 (0) Uknown sp 1 (0)
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195 BIOGRAPHICAL SKETCH Lucas Fortini was born in Rio de Janeiro in 1975. In 1993 he moved to California where he eventually got his A.A. degree in environmental studies from Moorpark College and his B.S. degree in natural resource m anagement from UC Berkeley. Following his life long interest in the natural environment, Lucas has been interested in how the response of populations and communities to natural and humanmade disturbance determine ecological resilience and shape opportunities for conservation and management. After graduating in Berkeley, Lucas decided to focus his research in the tropics. Hired as a research scientist by Daniel Zarin at the UF, he spent a few years working on multiple forest ecology and management research projects in the Brazilian Amazon before starting his PhD. After his PhD, Lucas is driven to make crucial tropical forest conservation and management efforts more science based by pursuing analytical and modeling approaches that yield relevant and applied results. A Brazilian, American, and Italian citi zen, he holds his wife, nature and music as his life's passions.